Exploring Personal Saving Orientation’s Influence On Investment Decision-Making

Exploring Personal Saving Orientation’s Influence On Investment Decision-Making | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exploring Personal Saving Orientation’s Influence On Investment Decision-Making Ihsan Ali, Ting Liu, Abdulrahman Alomair, Mohammed Alomair This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8782383/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Individuals’ economic conditions are always under the influence of psychological factors that are more prominent in unpredictable economic conditions, yet the impact of several key elements remains underexplored. Keeping in view the importance of psychological factors, our study examined the mediating role of Personal Saving Orientation (PSO) between psychological factors—desire for learning, flow experience, and social support, and investment decisions. This study analyzed the roles of flow experience, social support, and desire for learning in shaping investment decisions in the context of the collectivist culture of Pakistan. Our study is grounded in the Theory of Planned Behavior (TPB) and collected data from 516 investors. Our analysis using the PLS-SEM technique shows that the Knowledge-seeking behavior and social support play a significant role in shaping investment decisions. However, flow experience did not have a significant effect. Moreover, the personal saving orientation acts as an intermediary variable that strongly influences the relationships of experience and support on investment decisions, except for knowledge-seeking behavior. These results enable investors to understand the influence of social behavior and psychological elements on investing choices and provide a mechanistic description of the mediating impact of personal saving orientation on this outcome. Further implications for practice are discussed. Personal saving orientation learning attitude social support flow experience investment decisions Figures Figure 1 Figure 2 1. Introduction Financial decision-making emerges as a major determining element in personal financial success (Sachdeva et al., 2023). Previous studies have addressed classical finance and the Theory of Planned Behaviors (TPB) in the context of investment decisions. According to utility-maximization-based financial theories, effective market conditions are expected to be associated with rational investor behaviors. In such efficient marketplaces, all market participants receive immediate standardized market information through a uniform distribution mechanism (Parra-Domínguez et al., 2023). While assessing available opportunities, real investors emphasize on accurate information and their risk assessment (Lathief et al., 2024). However, conventional finance lacks consensus regrading operational efficiency of market and investor’s involvement in financial markets (S. Kumar et al., 2022; Schoenmaker & Schramade, 2019; Yang & Zhou, 2025). Behavioral finance introduces an alternative perspective by challenging the core assumptions of investor’s rationality and market efficiency. The theoretical concept of “economic man” was revisited by (Giarlotta & Petralia, 2024; Vira, 2024), who by applying psychological theories demonstrated that humans’ emotions and cognitive limitations in most of the cases distort their rational decision making. Several studies, in this regard, have examined and identified numerous cognitive biases and behavior lapses that directly or indirectly influence their investment choices (Che Hassan et al., 2023; S. Z. A. Shah et al., 2018), leading to undesirable investment outcomes and suboptimal portfolio performance (Ahmad et al., 2024; Kahneman & Tversky, 1979; I. Khan et al., 2021). Plethora of research have identified several demographical, emotional, and psychological elements that individually or collectively affect investment decisions (Baker et al., 2025; Crivelli et al., 2024; Luo et al., 2024), suggesting that the individual’s decisions are not entirely rational. Despite these insights, literature still fails to consider the impact of key psychological and social factors, including, learning motivation, flow experience, and social support, on individuals’ saving and investment behavior. Understanding such relationships is pivotal, especially in emerging markets like of Pakistan, where individuals’ behaviors are motivated from collectivist cultural norms, family influence, and societal expectations, factors that differ from individualistic traits (Andre et al., 2019; “The Influence of Social and Personal Factors in Individual Investment Decision Making,” 2022). By examining these social and psychological factors in such setting, this study extends behavioral finance theory to emerging markets, with aim to explain the process through which investment behaviors are shaped. Henceforth, these insights form the basis of TPB, which explains how individuals’ beliefs, social norms, and perceived behavioral control affect their decision making process (Aren & Hamamci, 2020). Majority of research, in this context, have emphasized demographic attributes (P. Kumar et al., 2023; Priem et al., 1999), while some have investigated the psychological factors such as personality traits (Andreoli & ten Rouwelaar, 2024; Luo et al., 2024; Rajasekar et al., 2023), yet individual’s desire for knowledge, flow experience, social support and their influence on saving behavior is insufficiently addressed. Current study aims to address this gap by answering following Questions: Does social support, flow experience, and desire for learning impact investment decisions? Does personal saving orientation mediate the relationship between desire for learning, social support, and flow experience, and investment decisions? The significance of the present study lies in situating personal saving orientation (PSO) within the financial realities of collectivist societies such as Pakistan. Previously several studies have analyzed the mediation through psychological constructs in literature, however, focusing how PSO, deeply rooted in communal and familial influence, mediates the relationship between psychological factors and investment decisions distinguishes our study. Moreover, to our knowledge, flow experience is not being investigated in the context of investment decisions. Furthermore, our study, through cultural lens, enlightens existing behavioral finance models through embedding constructs such as saving orientation within social and cultural contexts. Doing so provides a more holist review of individuals’ decision making process under the influence of social and psychological factors. Additionally, this study significantly contributes to academia by extending the applicability of TPB applicability to cultural oriented saving behavior, which is currently underrepresented. Lastly, this study contributes to the contextualized behavioral models that encompass realities of emerging economies rather than the assumptions of classical finance. 2. Theoretical Background and Hypotheses Development 2.1. Theoretical Background and Operationalization of Variables. The Theory of Planned Behavior (TPB) is critical framework of (Ajzen, 1991) that provides insight into how individual’s intentions are translated into behavior. According to this framework, individuals’ behavioral intentions are shaped from three primary elements i.e., subjective norms, attitudes, and perceived behavioral control. These elements collectively determine individuals’ behavioral intentions, which further shapes into actual behavior. While attitudes reflect individual’s assessment of engagement in a specific action, subjective norms refer to the perceived social pressure and expectations, whereas perceived control behavior in this model represents the perception of their ability to perform the behavior. Earlier studies have extended the TPB to examine financial choices and behaviors (Raut, 2020; Raut et al., 2018). For example (Abid & Jie, 2023; Liu et al., 2020), used the TPB to investigate financial decision-making process and found subjective norms and perceived behavioral control (PBC) as critical influencers of individuals' investment choices. Similarly, the findings (Che Hassan et al., 2023; Raut & Kumar, 2024) emphasized the importance of social and psychological factors determining financial behavior. In this study, TPB has context-sensitive explanatory power to clarify how financial behaviors are shaped in collectivist societies such as of Pakistan, where behaviors are not shaped by sole personal attitudes, but also by community norms, family expectations and broader social values (Omer et al., 2021; Sarwar et al., 2021). Subjective norms, in collective societies carry more weight than individualist cultures. Whereas psychological elements comprising emotional engagement, motivation and cognitive focus, further influence how individuals might process the available information and evaluate options (Shih et al., 2022). Social interactions in such situations have higher tendency to influence both perceived capability and normative expectations (Bavik et al., 2020; Goyal & Kumar, 2021; Thoits, 1995). Therefore, this study draws on TPB perspective to explain how cultural and psychological factors shape the formation of investment intentions and actual behaviors, emphasizing the interplay of social influence, emotions, and cognitions rather than purely rational decision-making. Principally, learning motivation mirrors the individual’s intrinsic desire to attain valuable knowledge, particularly financial knowledge in the context of our study (Bashir et al., 2024). From the perspective of TPB, learning motivation can be seen as an element that shapes individuals’ attitudes towards gaining knowledge in order to make informed financial decisions. In many cases, learning motivation reflects individuals’ personal drive to understand financial matters deeply. Therefore, individuals with higher intellectual curiosity exhibit favorable attitudes towards financial markets and investment opportunities, improving perceived behavioral control (Bashir et al., 2024). This motivation equips individuals with the knowledge necessary for appropriate decisions, increasing their confidence and improving investment outcomes (Chen et al., 2024). Such motivations are probably higher in collectivist cultures, where financial literacy is viewed as a collective responsibility (De Beckker et al., 2020). Therefore, motivation of learning extends beyond a general curiosity for knowledge, in fact it shows individuals capability to utilize financial literacy in real world. So, we emphasize learning motivation from both cognitive and applied aspects of learning, linking knowledge gathering and its practical use to culturally embedded financial investment decisions. While learning desire reflects the attitude of an individual, social support defines the support from family, friends and mentors in form of instrumental assistance, informational and emotional guidance (Bavik et al., 2020; Thoits, 1995). Within TPB perspective, social support can be explained as a key determinant of subjective norms, highlighting the behaviors that are socially endorsed and expected. Such behaviors are of key significance in collectivist societies, often dictating acceptable saving and investment behaviors, aligning individuals’ behavior with communal expectations. Moreover, it enables individuals to feel more secure and supported, leading to sound decisions in uncertain conditions. Such emotional support is highly relevant in markets like of Pakistan, which has a strong collectivist society (K. B. Khan et al., 2024). Within the framework of TPB, individual’s flow experience can be conceptualized as both a cognitive and affective enhancer which primarily links perceived behavioral control and attitudes of individual (Soren & Chakraborty, 2024). Flow in literature is conceptualized as a multidimensional construct that encompass hedonic and cognitive dimensions (Landhäußer & Keller, 2012; Ozkara et al., 2017). While hedonic flow relates to emotional enjoyment and pleasure, the cognitive flow emphasizes concentration, balance and absorption. Current study analyzes the cognitive flow as a perceived behavioral control. Conceptually, (Csikszentmihalyi & Csikzentmihaly, 1990) defined flow as a state of intrinsic motivation, deep absorption, and focused engagement that significantly improves individual’s task performance. From financial decision-making context, flow can enhance individual’s strength of perceived confidence, focus, and competence in managing complex or uncertain investment situations (Fong et al., 2015). Simultaneously, flow might foster favorable attitudes by means of making financial engagement intrinsically satisfying and emotionally rewarding. Thus, this dual influence reflects bridging capability of flow between cognitive control and affective evaluation processes that are central to TPB. Current study emphasizes the mediating role of Personal saving behavior utilizing TPB to elucidate its impact over financial decision making. Personal Saving Behavior is conceptualized as an individual’s consistent inclination towards savings, emphasizing intentional and habitual behaviors that foster secure financial well-being (Adewoyin et al., 2024). TPB in this context describes PSO as an influencer of attitudes by means of positive evaluations of saving behaviors, that in turn improves perceived behavioral control. Therefore, PSO from financial behavioral context, can be viewed as an attitude-related construct, that reflects individual’s enduring predisposition towards financial security. Personal saving behaviors in number of studies is being linked with cultural contexts, therefore, it is highly relevant in a collectivist society such as of Pakistan where behaviors are being influenced by community (Alwedyan, 2024; Cruz et al., 2025). In summary, our study while extending TPB integrates psychological and cultural determinants into financial decision-making process. While learning motivation and cultural determinants strengthen individual’s attitudes and perceived behavioral control, flow enhances cognitive engagement and confidence in managing financial uncertainty. Collectively, psychological and cultural elements influence PSO, which further translates these affective and cognitive inputs into saving tendencies, shaping individuals’ investment intentions and behaviors. Positioning PSO as culturally grounded mediation within TPB, our study aims to capture the psychological mechanisms, social norms, and their joint impact over individuals’ financial decision making in context of Pakistan. 2.2. Hypotheses Development 2.2.1. Desire for Learning and Investment Decision Desire of learning is defined as a motivation of an individual to acquire knowledge. This motivation is often linked with curiosity which represents one’s intrinsic psychological factor (Loewenstein, 1994). Number of studies have examined curiosity in the context of financial decision making (Shukla et al., 2022; Skinner et al., 2022). Curiosity motivates individual to acquire information and knowledge that is crucial for enlightening their psychological development which navigates them in changing their financial behavior. It emulates the individuals’ attitudes towards learning that is essential for assessing degree of perceive risk (Wagstaff et al., 2021). This learning orientation can be viewed as positive attitude towards information gathering and knowledge seeking, which aligns with the attitudinal dimension of TPB. Therefore, it is rational to argue that individuals with greater desire for learning are more prone towards financial literacy (Pahlevan Sharif & Naghavi, 2020). Several studies have linked curiosity with investment decisions by utilizing different behavioral models. For instance, (Fishbach & Woolley, 2022) argued that individuals’ curiosity leads to development of essential cognitive abilities that supports sound investment decisions through innovation and strategic thinking (Hagtvedt et al., 2019). In the literature of mindfulness, studies have found that knowledge driven culture in societies and organizations improve critical analysis which in turn improves decision making (Kashdan et al., 2020; Polman et al., 2022). (Sourirajan & Perumandla, 2022) in relation to our study, described desires as key influencers of individuals’ investment intentions. Drawing upon these studies, and TPB, it can be inferred that the individuals desire of learning is associated with positive attitudes towards pursuing key information. This suggests that learning is a positive attitude that is pivotal for individual’s perceived capability, openness, and confidence. Individuals who have higher desire of learning are more likely to outperform those who have weak desire in terms of performance. Moreover, such desire of learning will significantly contribute to investment intentions and behaviors. Thus, we hypothesize that: H1: Investors with higher desire of learning prefer investment in stock markets. 2.2.2. Social Support and Investment Decision Social support, in a collective society, plays an important role in shaping individuals’ behavior. Social support is viewed as a guidance, emotional assistance, and help received by individuals from social network (Casillas et al., 2019), including family, friends, and communities. Literature indicates that the nexus of social support and financial decisions is complex mechanism, particularly in highly socio-cultural societies. Number of studies have found social influence a key element of individuals (Rehman et al., 2024; Sachdeva & Lehal, 2024). (Bernstein et al., 2017) While investigating family owned enterprises revealed that family support plays a pivotal role in the governance and organization performance. They further stated that family involvement in times of risk plays a crucial role in mitigation. Through TPB, social influences are viewed as subjective norms (Ajzen, 1991), that play a crucial role in shaping individuals’ behavioral intentions by perceived approval or disapproval. In the context of investment decisions, perceived social support is linked to psychological assurance that significantly improves perceived behavioral control which leads to socially approved behavior. This is substantiated by the study of (White et al., 2009) who revealed that injunctive and descriptive norms strongly predict behavioral intentions. In classical literature, (East, 1993) finds similar impact, suggesting that normative beliefs are directly related to investment intentions through theory TPB mechanisms. From modern literature, study of (Agnew & Sotardi, 2025) investigating family financial socialization concluded that family support improves confidence and enhances financial behavioral decisions. Notably, in the literature of collectivism culture, this relationship is even stronger because in collectivist societies, family expectations and social support are central (Lumpkin et al., 2008). Henceforth, based on this enriched theoretical and empirical evidence, we argue that: H2: Investors who get high social support are more likely to invest in stock markets. 2.2.3. Flow Experience and Investment Decisions Flow experience is viewed as a multi-dimensional construct that includes cognitive and motivational factors. These dimensions are not always constant, i.e., can be altered by malleable characteristics that include both individuals’ traits and social interactions (Davis & Csikszentmihalyi, 1977). For instance, (Newton et al., 2020), proposed that individual’s social interaction affects individuals’ flow experience through social learning. However, current study emphasizes that the flow experience is influenced more by psychological elements than from social interactions. Therefore, in this study, flow experience refers to a psychological state in which individual is fully absorbed in an activity, aiming optimal performance through concentration and sense of accomplishment (Mattke et al., 2021). In essence, cognitive flow experience occur when an individual’s level skill is aligned with the challenges of a task, which in long run results in engaging and rewarding experience (Newton et al., 2020). Despite scarce literature of flow (cognitive flow) in the framework of financial decision making, literature from other relevant fields provides a foundational support for relationship between flow experience and investment decision. Generally, literature highlights that deep task involvement (a key aspect of cognitive flow) positively influences perceived competence and instrumental beliefs about that task. For instance, (Sliwka et al., 2024) revealed that the individuals placed in a stimulating environment are more likely to experience cognitive flow, which results in improved performance and innovative outcomes. In a technology setting, (El Abed & Castro-Lopez, 2024) demonstrated that individuals exposed to immersive technological experiences had positive intentions towards purchasing. Similarly, (Ariely, 2000) found that information flow experience directly impacts consumers’ purchasing intentions. Together, all these studies suggest that flow in financial investment models can enhance investors' perceived behavioral control and spur positive attitudes, which, according to TPB, strengthen investment intentions that convert into actual behavior. This is substantiated by the recent study of (Goswami et al., 2025), who found cognitive absorption as a key influencer of investors’ intention to adopt robot advisors’ technology. Therefore, from the TPB perspective and existing evidence, we propose that experience flow, through absorption, deep learning, and concentration, augments individuals' perceived behavioral control which generates positive attitudes leading to stronger investment intentions. Based on these theoretical and empirical insights, we hypothesize that: H3: Investors with experience in flow are more likely to invest in stock markets. 2.2.4. Mediating Role of Personal Saving Orientation Personal saving orientation refers to an individual's tendency to prioritize saving and financial planning, reflecting their attitude towards and habits related to saving (Sekścińska & Markiewicz, 2020). The desire to learn is a key psychological characteristic of curiosity, and an individual’s tendency to save can play a mediating role between it and investment decisions (Kaur et al., 2020). The desire to learn itself can help investors establish a good savings and knowledge base for new investments. On the other hand, it can also prompt investors to decide whether to try new investments or settle for the status quo (savings) (Furnham & Cheng, 2019; Ghaffar et al., 2024). Research supports this idea, indicating a positive correlation between increased demand for knowledge and disciplined savings habits, leading to sound investment plans. Specifically, individuals who proactively pursue financial knowledge tend to grasp the importance of saving better, which subsequently influences their investment decisions (Sekścińska & Markiewicz, 2020). However, in collectivist societies such as Pakistan, this relationship may be moderated or constrained by family expectations, social norms, and cultural values, which often influence or override individual motivations related to curiosity and learning (Yaqoob et al., 2023). Such cultural contingencies play a significant role in shaping whether and how the desire for learning influences saving orientation and investment decision (Shantha, 2019). In collectivist societies like Pakistan, however, the role of learning motivation and saving behavior is often influenced by family and community values. Social norms, religious beliefs, and cultural practices tend to shape financial behavior, and these factors may influence how personal saving orientation mediates the relationship between social support, investment guidance, and personal savings. As proposed by (Gomes et al., 2021), households with strong social networks have a high desire for savings, which in turn influences investment decisions. (Baker et al., 2021) Further emphasized this point by studying how savings behavior is passed down from generation to generation in households. They showed that the family environment that fosters a savings culture from an early age influences the next generation, thereby influencing investment behavior. Research highlights that financial socializing significantly influences children's financial literacy and saving habits, which affect their investment decisions (LeBaron & Kelley, 2021). Additionally, a study examining the cultural origins of investment behavior found that families with a substantial savings culture tend to pass down financial behaviors to their children. Thereby affecting their investment decisions (Magrelli et al., 2022). In the Pakistani context, this process is further influenced by the family-oriented nature of society, where the decisions of family elders often shape the financial behaviors of younger generations. The role of family and community support in guiding financial behavior is a significant factor in how investment decisions are made (Sajjad et al., 2025). The concept of the flow experience, especially in specific cultural contexts, provides unique insights into the relationship between participation in activities and investment decisions (Dwivedi et al., 2022). An immersive state is a state of high engagement and enjoyment. In specific cultural contexts, achieving an Immersive state may be more meaningful. When investments align with personal values and cultural beliefs, there may be greater satisfaction as these investments resonate more deeply with the investor’s code of conduct (Al-Afeef et al., 2024; Jan & Shafiq, 2021). They found that when people’s behavior aligns with their values and worldview, they are happier investors. Research indicates that individuals who experience are more likely to develop regular saving habits as they understand the role of saving in achieving their goals (Te Brömmelstroet et al., 2022). It is also noted that those who achieve engagement tend to make better financial decisions due to increased focus and engagement (Csikszentmihalyi & Csikzentmihaly, 1990). Additionally, the Study found that individuals with autotelic personalities who often exhibit a State of involvement exhibit higher levels of conscientiousness, which positively influences their saving and investment behaviors (Te Brömmelstroet et al., 2022). This suggests that when people are intrinsically motivated and enjoy the process of financial planning, they are more likely to save consistently and make informed investment choices. Further, it is important to note that in a collectivist society like Pakistan, achieving an optimal experience in investment activities is often influenced by cultural alignment. Investments that resonate with the individual's community or family values tend to yield greater satisfaction and engagement. In collectivist societies, saving and investment behaviors are strongly influenced by family values and community expectations. The importance of saving as a collective activity is reinforced through social support systems, with individuals often relying on family networks for financial guidance. These cultural elements make personal values between saving and investment closely aligned and communal norms (Polman et al., 2022). To summarize, the mediating role of personal savings orientation between learning desire, Social assistance, Immersive state, and investment decision making is evident. Moreover, this relationship may be moderated by socio-cultural factors prevalent in collectivist societies like Pakistan, where family expectations and social norms often influence individual financial behaviors. It has not been studied particularly in socio-cultural contexts similar to those of Pakistan. Although the causal relationship is complex, empirical evidence emphasizes the importance of savings orientations as a key factor in adjusting various antecedents that affect investment decisions. Based on the above discussion, we proposed the following hypothesis: H4: Personal saving orientation mediates the relationship between the desire for learning and investment decisions. H5: Personal saving orientation mediates the relationship between social support and investment decisions. H6: Personal saving orientation mediates the relationship between flow experience and investment decisions. 3. Methodology 3.1. Data and Sample In this study, we used empirical data to examine the investment behaviors of investors in Pakistan by employing a quantitative research approach. Our focus was on investors who engaged in both short-term and long-term stock market investments. The Pakistan Stock Exchange (PSE) and the State Bank of Pakistan (SBP) assisted us in identifying suitable participants for the study. To gather data, we initially developed a questionnaire in English. The questionnaire was divided into two sections. The first section collected demographic information, including gender, age, employment status, income, education level, years of investment experience, and type of investment. The second section included questions on the desire for learning, flow experience, social support, personal savings orientation, and investment decisions. A cover letter was included on the first page of the survey to clarify that the collected data would be used solely for research purposes and that participants' personal information would not be disclosed to the public. Since we collected data from individual investors, before data collection, participants were informed, and verbal consent was obtained for completing the questionnaire. They were also informed that their participation was voluntary. Data were collected using the questionnaire from July 2024 to October 2024. We reached out to 750 investors using a combination of email, phone calls, and face-to-face interactions, with assistance from employees of the Pakistan Stock Exchange (PSE) and the State Bank of Pakistan (SBP). We used convenience sampling, a non-probability sampling method, to collect the data. Although convenience sampling allowed us to gather data quickly and efficiently, it is important to note that this method may limit the representativeness of our sample. As participants were selected based on their availability, we may have missed certain segments of the investor population, leading to a sample that may not fully reflect the diversity of investor groups in Pakistan. Despite achieving a 69% response rate and retaining 516 usable responses, non-response bias remains a concern. As participation was voluntary, investors with lower financial literacy or less experience may have been less likely to respond. This may distort the findings and limit the generalizability of the results. In Pakistan, about 220,000 retail investors are involved in the PSX, while 883 domestic and 1,886 foreign institutional investors are involved. Participation is low in the stock market, as only 0.22% of the population invests (Pakistan Stock Exchange, 2024). Moreover, the financial literacy rate is only 26%, as per the Standard & Poor's Global Financial Literacy Survey. These facts prove the importance of addressing financial literacy gaps and increasing market participation (S. S. Shah et al., 2024). 3.2. Questionnaire Development We utilized validated measures that had already been tested on various Asian markets. The primary method used in this research was a cross-sectional survey. All variables were measured using a five-point Likert scale, ranging from “strongly disagree” = (1) to “strongly agree” = (5). The first draft of the questionnaire was created based on findings from existing literature. Since English is widely used in Pakistan’s financial sector (including the stock market and banking), our target respondents, investors active in the PSE, were expected to be proficient in English. The questionnaire language was simplified to ensure clarity. The desire for learning was measured using 10 scale items adapted from (Shantha, 2019), which was validated in a Sri Lankan investor context of behavioral bias prevention. We adapted the items to fit our research context. The scale had high reliability in our sample α = 0.750. A sample item is "I am interested in discovering new investment opportunities". For flow experience, we used 3 items from (Tuncer, 2021), which were originally developed in a Turkish social commerce context where flow measured immersive engagement with social media (e.g., Instagram) for online shopping. Since the original research focused on online buying behaviors, we adapted these items to assess flow experience in relation to investment activities, for example, the original item “While browsing the goods on Instagram, I generally feel that time is passing quickly” was revised to our sample item “While browsing investment opportunities on social media, I generally feel that time is passing quickly”. The reliability value in our sample is α = 0.820. The 4-item Social support scale was adopted from (Wedgeworth et al., 2017), a measure originally validated in the U.S rural elderly care context, where it focused on satisfaction with support to predict rural elderly adults' quality of life. The scale was later tested in Asian markets by previous studies such as (Dissanayake et al., 2023; Koydemir et al., 2013). To fit our investment behavior context, we revised the original items to focus on the general task “Overall, how satisfied have you been in the last month with the help you have received with transportation, household and yard work, and shopping?” became our adapted version “Overall, how satisfied have you been in the last month with the help you have received with transportation, household chores, and shopping for investment opportunities?". The adapted scale shows good reliability in our sample, α = 0.857. Furthermore, personal saving orientation (PSO) was assessed with 5 items from (Ponchio et al., 2019), a Brazilian consumer finance study where PSO was used to predict the financial security dimension of consumer perceived financial well-being. These items have also been tested in India and Pakistan (Alam & Siddiqui, 2021; Gupta & Mukherjee, 2024). The adapted scale showed high reliability (α = 0.919). a sample item is “I keep a careful watch over my spending daily”. Finally, 5 investment decision-making items were modified from (Ullah et al., 2024), a set of behavioral finance studies applied to emerging markets. The scale showed high reliability for the Pakistan Stock Exchange (PSE) context (α = 0.785). A Sample item is “I like to buy stocks that have recently outperformed the market”. 4. Data Analysis and Results Table 1 presents all the respondents, including their year of investment, type of investment, income, and gender. Males comprise 84% of the respondents, while females’ ratio is 16%. This gender distribution aligns with broader societal and economic norms in Pakistan, where women tend to rely on male family members for financial choices due to long-term patterns of economic dependence. Thus, men typically act as the only decision-makers for household finance and are overrepresented in institutional investment activities, such as participation in the Pakistan Stock Exchange (PSE). This is also due to lower female participation in the workforce and limited independence with finance resources among women in the country. The age of the respondents ranges between 25 and 55 years. The education level of respondents is mainly high school or equivalent, which is about 27%. Most of the respondents, 52%, are self-employed and highly experienced, particularly in various types of stock market investments. Table 1 Demographic Characteristics of the Participants Particular Frequency Percentage % Gender 1. Male 435 84.30 2.Female 81 15.69 Age 1. 18–25 years 30 5.81 2. 26–35 46 8.91 3.36-45 234 45.34 4.46-55 169 32.75 5.56-65 28 5.42 6.66 and above 9 1.74 Employment Structure 1.Full time salaried 58 11.24 2.Par time salaried 55 10.65 3.Self-employed 267 51.74 4.Unemployed 50 9.68 5.Retired 28 5.42 6.Housewife 6 1.16 7.Student 42 8.13 Income (PKR) 1.50,000 or less 116 22.48 2.51000-100000 85 16.47 3.101000–150000 38 7.36 4.151000–200000 30 5.81 5.201000–250000 142 27.51 6.Above 250000 105 20.34 Education 1.Primary school 66 12.79 2.High school 144 27.90 3.Diploma 88 17.05 4.Bachelor 98 18.99 5.Master's degree 108 20.93 6.Ph.D. degree 12 2.32 Year of Investment 1. Under five years 52 10.07 2. 5–10 years 142 27.51 3. 10–15 years 214 41.47 4. Over 15 years 108 20.93 Type of Investment 5. Short term 219 42.44 6. Long term 181 35.07 7. Both short and long term 116 22.48 Total 516 100 4.1. Descriptive Statistics Table 2 depicts the descriptive statistics and multi-collinearity issues. The results indicate that the flow experience has the highest average score of 3.608, while the investment decision has the lowest average score of 3.45. Desire for Learning has the highest standard deviation of 0.709, while flow experience has the lowest standard deviation of 0.625. The VIF (variance inflation factor) is used to analyze multicollinearity (Shahzad et al., 2021). In a research study, a researcher (Sarstedt et al., 2023) concluded that multi-collinearity occurs only when the values of VIF exceed 5, showing a significant level of collinearity. On the other hand, the findings of the current research study show the significant value of VIF, as shown in Table 2 , where it is less than 5, and show that there is no multi-collinearity. In addition, skewness and kurtosis analyses were conducted to check the normality of the data. The skewness and kurtosis values are in a suggested range of +/- 2, as given by (Aslam, 2021). Table 2 Descriptive Statistics Variables Mean Std. Dev Skewness Kurtosis VIF Desire For Learning 3.574 0.709 -0.455 -0.033 2.169 Flow Experience 3.608 0.625 -0.300 -0.016 1.401 Social Support 3.598 0.648 -0.628 0.154 2.812 Personal Saving Orientation 3.605 0.657 -0.719 0.244 4.457 Investment decision 3.435 0.670 -0.679 -0.457 --- 4.2. Common Method Bias Cross-sectional data have a big limitation of common method bias that influences their results. We checked if there is any problem of common method bias in our sample data; the data was obtained from a single source, and it is cross-sectional, due to which the issue of “common method bias or common method variance (CMV)” may arise (Jordan & Troth, 2020). According to (Kock et al., 2021), Common method bias issues can be detected by executing “Harman's Single Factor Test." To follow the (Kock et al., 2021) method, we employed Harman’s single-factor test in SPSS. The test results indicate the absence of a common method bias issue because the percentage variance is lower than the cutoff point (i.e., below 50%). It means that there is no problem of common method bias in our sample data. 4.3. Confirmatory Factor Analysis (CFA) We assessed the measurement model with Smart PLS 4 to cross-validate the theoretical model. First, we conducted Exploratory Factor Analysis (EFA) to confirm adapted items from different domains. All the items retained had EFA factor loadings of between 0.670 to 0.938 (see Table 3 ) well above the 0.5 threshold (Gebremedhin et al., 2022), confirming no items were misaligned with their parent constructs. Next, we looked at Confirmatory Factor Analysis (CFA) item loadings for each factor were found to be above the threshold of 0.5; however, we removed some items from the scale because their values were not satisfactory (below 0.5). The remaining items had outer loadings ranging from 0.664 to 0.914, which were considered sufficient to include every item in the model. Researchers (Asghar et al., 2021) suggest that a Cronbach's alpha and composite reliability (CR) greater than 0.7 indicate a sufficient level of reliability for the constructs. The Cronbach's alpha and CR values were above 0.7, demonstrating the high reliability of the constructs. The range of these values was from 0.750 to 0.924, as shown in Table 3 and Fig. 2 . Additionally, the average variance extracted (AVE) and the square root of the average variance extracted were used to measure the convergent and discriminant validity of all the constructs. The AVE scores and the square root of AVE (see Table 3 ) for all constructs exceeded the recommended thresholds of AVE > 0.50 and the square root of AVE > 0.70, as specified by reference (Hair et al., 2019). Table 3 Factor Loading, Validity, and Reliability Variables and items EFA Factor Loading CFA Factor Loading Cronbach's alpha C.R AVE DV √ AVE Desire For Learning 0.750 0.840 0.798 0.497 dl1 0.853 0.679 dl2 0.765 0.664 dl3 0.845 0.703 dl4 0.670 0.770 Flow Experience 0.800 0.810 0.882 0.714 fe1 0.882 0.852 fe2 0.761 0.797 fe3 0.888 0.884 Social Support 0.857 0.857 0.914 0.779 ss1 0.938 0.921 ss2 0.908 0.893 ss3 0.786 0.832 Personal Saving Orientation 0.919 0.924 0.943 0.805 pso1 0.879 0.866 pso2 0.895 0.903 pso3 0.914 0.914 pso4 0.897 0.905 Investment Decision 0.785 0.789 0.875 0.699 id1 0.868 0.865 id2 0.859 0.835 id3 0.766 0.808 Note: DL: Desire for Learning, FE: Flow experience, SS: Social Support, PSO: Personal Saving orientation, ID: Investment decision. Edu: Education, M. status: Material Status 4.4. Correlations Table 4 provides the correlation coefficient between the constructs. The coefficient values demonstrate a substantial positive relationship between desire for learning (r = 0.125), flow experience (0.074), and social support (r = 0.317) with investment decisions. Similarly, there is a substantial positive association between desire for learning (r = 0.166), experience (r = 0.191), social support (r = 0.216), and personal saving orientation. In addition, there is a substantial relationship between personal saving orientation (r = 0.184) and investment decisions. Table 4 Discriminant validity through HTMT Construct 1 2 3 4 5 1. DL — 2. FE 0.154 — 3. SS 0.216 0.062 — 4. PSO 0.166 0.191 0.216 — 5. ID 0.125 0.074 0.317 0.184 — Note: DL: Desire for Learning, FE: Flow experience, SS: Social Support, PSO: Personal Saving orientation, ID: Investment decision. 4.5. Structural model The study sought to examine how personal saving orientation mediates the relationship between the desire for learning, social support, flow experience, and investment decision-making. Table 5 Hypotheses Paths β-values Mean STDEV t-values p-values Decision Direct Effect s DL -> ID 0.204 0.204 0.049 4.197 0.000 Significant DL -> PSO 0.118 0.131 0.045 2.624 0.010 Significant FE -> ID -0.015 -0.010 0.048 0.302 0.763 Insignificant FE -> PSO 0.144 0.152 0.048 2.982 0.004 Significant PSO -> ID 0.121 0.111 0.47 2.585 0.011 Significant SS -> ID 0.216 0.222 0.044 4.942 0.000 Significant SS -> PSO 0.144 0.143 0.034 4.162 0.000 Significant Mediating Effects DL -> PSO -> ID 0.014 0.015 0.009 1.594 0.114 Insignificant FE -> PSO -> ID 0.017 0.016 0.008 2.050 0.043 Significant SS -> PSO -> ID 0.017 0.016 0.007 2.317 0.023 Significant Note: DL: Desire for Learning, FE: Flow experience, SS: Social Support, PSO: Personal Saving orientation, ID: Investment decision. We used structural equation modeling (SEM) analysis with the PLS bootstrapping approach to examine our study hypotheses. We measured the results using t-statistics, standardized path (Beta coefficient) values, and p-statistics. The results, presented in Table 5 , indicated that there were significant relationships between the variables Desire for Learning with values (β = 0.204, p < .05) and social Support with values (β = 0.216, p .05) did not have a significant impact on investment decisions. We accepted hypotheses H1 and H2 but rejected H3. Furthermore, Learning motivation with values (β = 0.118, p < .05), social support with values (β = 0.144, p < .05), and experience with values (β = 0.144, p < .05) showed significant positive effects on personal saving orientation. Additionally, the Personal Savings Orientation (β = 0.121, p < .05) had a positive impact on investing decisions. To assess the robustness of these core findings and rule out the influence of confounding factors, we conducted a series of tests in Smart PLS-4, following the methodology outlined by Baron and Kenny (Baron & Kenny, 1986). We expanded the model to include control variables employment status (emps), material status (m. status), education (Edu), gender, income, Year of investment, type of investment, and re-examined the key relationship with investment decisions (id) (see Table 06 ). These checks confirmed the stability of our main results: core variable effects persisted, with Desire for learning (dl) remaining a significant positive predictor of id (β = 0.167, p = 0.001) and social support (ss) maintaining a significant positive impact (β = 0.162, p = 0.000), consistent with our initial findings. Flow experience (fe) still showed no statistically significant effect on id (coefficient = -0.035, p = 0.416), further validating our decision to reject H3. Control variables’ influence included employment status (emps), having a significant negative effect on id (β = -0.0164, p = 0.005), and material status (m. status), exerting a significant positive effect (coefficient = 0.468, p = 0.017), additional insights that do not alter our core conclusions. All other controls (age: p = 0.602; education: p = 0.805; gender: p = 0.659; income: p = 0.458; type of investment: p = 0.312; year of investment: p = 0.431) had no significant impact on id, confirming our main results are not driven by these factors. The relationship between PSO and id was marginally significant (p = 0.063) in robustness checks, aligning with its significant positive effect in our main analysis (β = 0.121, p < .05) and suggesting a consistent directional trend. In terms of mediation analysis, the relationship between the knowledge-seeking behavior and investment decisions was found to have an insignificant mediation effect due to personal saving orientation (β = 0.014, p > .05). However, personal saving orientation positively mediated the relationships between social support (β = 0.017, p<.05). and flow (β = 0.017, p < .05) with investment decisions. In conclusion, we accepted hypotheses H5 and H6, rejecting H4. The results highlight the significance of personal saving orientation as a mediator in comprehending the impact of socio-psychological factors on investment decision-making. Table 6 Regression Analysis Model β-values Mean STDEV t-values p-values Age -> Id 0.040 0.041 0.077 0.521 0.602 Dl -> Id 0.167 0.173 0.052 3.211 0.001 Dl -> Pso 0.118 0.121 0.048 2.445 0.015 Edu-> Id 0.010 0.011 0.043 0.247 0.805 Emp -> Id -0.164 -0.162 0.058 2.835 0.005 Fe-> Id -0.035 -0.033 0.043 0.813 0.416 Fe -> Pso 0.144 0.149 0.045 3.218 0.001 Gender -> Id -0.056 -0.051 0.126 0.441 0.659 Income -> Id 0.037 0.039 0.050 0.743 0.458 M.status -> Id 0.468 0.470 0.196 2.383 0.017 Pso -> Id 0.085 0.084 0.045 1.861 0.063 Ss -> Id 0.162 0.163 0.042 3.830 0.000 Ss -> Pso 0.144 0.145 0.038 3.801 0.000 Type of Invetment -> Id -0.046 -0.045 0.046 1.012 0.312 Year of Invetment -> Id 0.054 0.053 0.069 0.788 0.431 Note: DL: Desire for Learning, FE: Flow experience, SS: Social Support, PSO: Personal Saving orientation, ID: Investment decision. Edu: Education, M. status: Material Status 4.6. Subgroup Analysis Subgroup analyses of participants stratified by gender (male vs female) and educational level (bachelor’s degree, diploma, high school, primary school, master's degree) reveal distinct patterns in the interactions between desire for learning, social support, flow experience, personal saving orientation, and investment decisions, with notable variations in statistical significance and effect magnitude. Among the educational subgroups, PhD-level participants were excluded due to a small size (n = 12), which falls below the minimum threshold (n ≥ 30) for reliable subgroup testing in SmartPLS-4. Detailed gender-specific results are presented in Table 7 ; for educational-specific results, see Table 8 . For the desire for learning and investment decisions, the relationship shows a significant positive association in males (β = 0.166, p = 0.002) but is non-significant for females, where the desire for learning does not reliably predict investment decisions. For the desire for learning and personal saving orientation, neither gender exhibits significance (females: p = 0.651; males: p = 0.074), confirming that desire for learning does not drive personal saving orientation across genders. The flow experience and investment decisions relationship is non-significant for both genders, meaning flow experience does not correlate with investment decisions. In the flow experience and PSO relationship, males exhibit a significant positive association (β = 0.161, p = 0.001), while the relationship is non-significant for females. The PSO and investment decisions relationship is non-significant for females but shows a significant positive association in males (β = 0.181, p = 0.001), indicating PSO does not predict investment decisions for females. The Social support and investment decisions relationship yields significant positive associations in both genders (females: β = 0.201, p = 0.031; males: β = 0.211, p = 0.000). Finally, the social support and PSO relationship is significant only in males (β = 0.151, p = 0.000) and non-significant for females. By education, the desire for learning and investment decisions shows significant positive associations in diploma (β = 0.285, p = 0.012) and primary school (β = 0.484, p = 0.044), while the relationship lacks significance for bachelor, high school, and master’s degree participants, where desire for learning does not reliably predict investment decisions. When examining the desire for learning and PSO relationship, significance is limited to high school (β = 0.255, p = 0.002) and primary school (β = 0.266, p = 0.033) subgroups, with modest positive effects observed, and non-significant results for bachelor's, diploma, and master’s degree participants. Regarding the flow experience and investment decisions relationship, no subgroup exhibits significance, indicating flow experience does not correlate with investment decisions. Within the flow experience and PSO relationship, significant positive associations are evident in bachelor's (β = 0.258, p = 0.003), diploma (β = 0.285, p = 0.02), and primary school (β = 0.218, p = 0.018) participants, while the relationship is non-significant for high school and Master's degree participants. The PSO and investment decisions relationship is non-significant across all education levels, meaning PSO does not predict investment decisions. For the social support and investment decisions relationship, significant positive associations are identified in diploma (β = 0.228, p = 0.015), high school (β = 0.306, p = 0.000), and Master's degree (β = 0.222, p = 0.011) participants, with non-significant results for bachelor's and primary school participants. Finally, the social support and PSO relationship is significant only in the high school subgroup (β = 0.173, p = 0.004) and not statistically reliable for all other subgroups. Table 7 Gender Subgroup Analysis Original (female) Original (male) p value (female) p-value (male) dl -> id 0.443 0.166 0.145 0.002 dl -> pso 0.079 0.096 0.653 0.074 fe -> id 0.178 -0.015 0.212 0.771 fe -> pso 0.158 0.165 0.365 0.001 pso -> id -0.060 0.180 0.544 0.001 ss -> id 0.205 0.212 0.039 0.000 ss -> pso -0.059 0.159 0.656 0.000 Table 8 Educational Level Subgroup Analysis Original Bachelor Original Diploma Original High school Original primary school Original Master's degree p-value Bachelor p-value Diploma p-value High school p-value primary school p-value Master's degree dl -> id 0.204 0.285 0.111 0.484 0.242 0.151 0.012 0.095 0.044 0.124 dl -> pso 0.063 0.074 0.255 0.266 0.14 0.337 0.332 0.002 0.033 0.24 fe -> id 0.087 -0.039 -0.034 0.16 0.069 0.236 0.391 0.38 0.069 0.307 fe -> pso 0.258 0.285 0.041 0.218 0.15 0.003 0.02 0.36 0.018 0.245 pso -> id 0.103 0.047 0.158 0.139 0.171 0.17 0.33 0.055 0.18 0.074 Ss -> id 0.115 0.228 0.306 0.073 0.222 0.197 0.015 0 0.277 0.011 Ss -> pso 0.091 0.034 0.173 0.15 0.158 0.323 0.376 0.004 0.162 0.103 5. Discussion and Implications 5.1. Discussion The Current study has thoroughly examined the relationship of psychological, social, and cultural factors in the context of investment behavior. Drawing on the Theory of Planned Behavior, (TPB) we have examined individuals’ investment behavior in the context of Pakistan. Particularly, the current study emphasized how the desire for learning, flow experience, and social support effects the investment intentions. By embedding psychological constructs with social and cultural dimensions, this study further enlightens existing literature with a more comprehensive approach. Investigating such factors, in market of Pakistan, which has collectivist norms and family influences, provides better understanding of individuals’ behavior. Such approach contributes to academia because the majority of existing studies are West context oriented, which often emphasize the individualistic investment decisions. Testing such psychological and social constructs in markets like Pakistan captures the realities of investors’ cognitive behavior. The key significance of this study lies in extending TPB by incorporating motivational and cultural factors, in that way providing deep insights that are essential for policy makers, educators, and fintech firms that are interested in financial engagement in a culturally embedded society. Building on TPB, our study reveals that the individuals’ psychological and social dimensions are significantly related to their investment intentions. It suggests that the cognitive and social forces directly shape investors’ financial choices in emerging markets. Moreover, it contributes to the behavioral finance literature by providing empirical evidence of the impact of psychological factors on the decision-making process. Our study shows that individuals' decisions are strongly influenced by their cognitive abilities and social and family support. Such effects are already reported in the literature (Chauhan et al., 2024; Ghouse et al., 2024; Ho et al., 2025; Mishra & Singh, 2024). Thus, our findings suggest that individuals with strong cultural support are emotionally strong through their social connectedness and familial trust, which in turn boost investment confidence and improve risk perception. In the context of Pakistan, it has a collectivist culture; therefore, individuals’ decisions more often are driven from social validation. Thus, this reaffirms that investors’ decisions are driven from social assurance. Our study proposed that individuals’ flow experience positively affects their investment decisions. However, results indicate that this relationship is insignificant. Number of previous studies have reported flow as a significant influencer of individuals’ decisions (Aubé et al., 2014; Feng et al., 2024; S. J. Shi et al., 2024), but our results show that these engagements do not necessarily convert into actual behavior. There are several possible reasons for this inconsistency. Firstly, literature has indicated the dual nature of flow, i.e. hedonic flow and cognitive flow. While hedonic flow depicts emotional enjoyment, the cognitive flow mirrors the focus and perceived control (Landhäußer & Keller, 2012; Ozkara et al., 2017). It is arguable that the hedonic element, particularly in uncertain financial markets may dilute behavioral transformations. This in turn can affect individuals’ cognitive flow because of excessive risk and uncertainty. Moreover, another explanation for this anomaly could be that the psychological mechanisms such as financial trauma and decision discontinuity after losses from markets due volatility can suppress individuals’ momentum of flow (Adil et al., 2023; Hoffmann et al., 2013). Based on this, it is arguable that market instability might be the reason for insignificance, rather than engagement itself. Similarly, results indicated an insignificant mediating role of personal saving behavior for leaning motivation and investment decision, thus rejecting H4. Conceptually, we expected that the desire for learning would foster financial knowledge acquisition which further could translate into improved personal saving behavior and subsequently investment decisions (CHOI et al., 2009). However, our results suggest that in culture embedded societies, the individuals’ motivations can be overridden by strong social factors (Leigh, 1983). Several studies previously have shown that the behavior of an individual is driven from societal factors like peer influence, societal factors, and social expectations. For instance, (Lössbroek & Van Tubergen, 2024) revealed that family expectations significantly affect individuals saving behavior. Similarly, (Putri & Chandra Wijaya, n.d.) found that individual’s financial behavior is more peer influenced rather than from individual’s cognitions in collectivist societies. Notably, the current study utilized a measurement of desire that captured a general motivational tendency, instead of active financial literacy, that emphasize practical application of financial knowledge. The TPB perspective in this regard suggests that intentions arise from attitudes towards behavior, normative influences, and perceived behavioral control. Thus, learning motivation might enhance saving behavior but due to lack of its alignment with normative and social pressure, they might not translate into actual investment behaviors. Further operationalization of learning motivation that encapsulates the practical attitudes rather than mere desire might result in significance. Our study also predicted the mediating role of PSO between social support and investment decisions. Our results show that the presence of a strong social environment positively contributes to individuals' saving behavior. This corroborates the study of (Sachdeva & Lehal, 2024), who found that contextual factors influence individuals’ investment decisions. In particular, our study is in line with the study of (“The Influence of Social and Personal Factors in Individual Investment Decision Making,” 2022), who found investment decisions and social elements inter-connected in mutual markets. Our findings also correlate with the TPB. For instance, in theory, social support is viewed as a subjective norm which is supposed to spur positive financial behavior that is also consistent to society’s expectations. Therefore, when the individuals perceive strong encouragement and support from community members, they prefer to adopt such behaviors that are in accordance with societal values. Whereas number of studies have found culture, particularly in collectivist societies, a pivotal element that encourage saving behavior (Alshebami & Al Marri, 2022; Costa-Font et al., 2018). This saving behavior further motivates individual to invest in available opportunities. The supported mediation of PSO between social support and investment decisions reinforces the role of collective influence in shaping financial behaviors. Within the TPB, social support represents subjective norms, which motivate individuals to adopt positive financial orientations consistent with community expectations. When individuals perceive strong encouragement from family, peers, or social networks, they develop disciplined saving habits, which subsequently increase their willingness and ability to invest. Empirical evidence supports this mechanism (Lapner et al., 2023) found that social connectedness and family communication foster saving consistency, while (Pak et al., 2024) showed that social encouragement enhances long-term financial planning through improved saving behavior. Similarly, (K. B. Khan et al., 2024) reported that in collectivist societies, perceived social approval reinforces both financial self-regulation and investment commitment. Accordingly, the present findings indicate that in socially interdependent contexts like Pakistan, social norms enhance investment intentions indirectly by cultivating a strong saving orientation, the behavioral channel through which social support translates into concrete financial action (Ali et al., 2022). Although, the direct relationship between flow and investment intentions was found insignificant; interesting, the relationship was found significant through Personal Saving Behavior. This suggests that the flow alone is not strong enough to transform into investment intentions. The indirect impact of flow through saving behavior suggests that individual’s focused cognitive engagement improves their self-discipline and future orientation, which in turn positively affects their investment behavior. This is confirmed by study of (Y. Shi & Qu, 2022) who found that the relationship between students’ cognitive abilities and academic performance is mediated by self-discipline. Similarly, our findings are in line with the study of (Alshebami & Al Marri, 2022) who found saving behavior as bridge between financial literacy and entrepreneurial intentions. TPB also advocates that individual’s attitudinal readiness and behavioral control translate into intentions and behaviors. Collectively, our findings provide a strong foundation to support the integration of motivational and cultural elements into the TPB. These results highlight the critical role of PSO that bridges the relationship between attitudes, motivations and culture. Further, our study demonstrates that in collectivist culture, saving behavior is valued as a virtue because of moral and social reasons which ultimately shapes the actual financial behavior. In collectivist societies like Pakistan, where saving is a socially valued virtue, this mediation pathway becomes even more prominent. Cultural norms emphasizing prudence, family stability, and financial responsibility reinforce saving as a moral and social behavior that precedes investment. Consistent with (Lusardi & Mitchell, 2023), cultures that prioritize saving cultivate long-term planning and investment readiness. Therefore, cognitive flow may enhance psychological control and confidence, but it is through personal saving orientation, shaped by cultural expectations and self-discipline, that these cognitive motivations are ultimately transformed into investment intentions. This reinforces TPB’s proposition that perceived behavioral control operates through behavioral regulators like saving, which concretize cognitive motivation into deliberate financial action. 5.2. Theoretical Implications This study contributes significantly to the literature on investment decisions in several ways. Firstly, we use empirical methods to conduct an in-depth analysis of psychological and social factors, such as how the desire for learning and social support affects investment decisions. Previous studies have extensively researched behavioral, environmental, and demographic factors (Hossain et al., 2024; Liang et al., 2021), there remains a significant gap in addressing the investment process in developing countries. Based on TPB, introducing a psychological understanding of personal saving orientation, we offer a model to explain how a desire for learning and social sport can result in investment behaviors. These factors shape the curiosity of investors, known as the desire for learning, which enhances the professionalism of their investment behavior. An investment strategy supported by strong social networks can improve investors’ decision-making, providing a more grounded and informed approach. This research provides empirical support for understanding investment behavior within the context of behavioral finance (Research & 2014, n.d.; Rice, 1999). To the best of our knowledge, this study is among the few that examine the mediating role of personal saving orientation in the context of investment decision-making in a developing country. We expand the current understanding of the mechanisms through which psychological factors, such as intrinsic motivations, such as the desire for learning and community assistance, affect saving and investment behaviors. Specifically, we examine how personal saving orientation mediates the relationship between psychological factors and investment decisions. In the (TPB) framework, studies have tended to examine the direct influence of variables like attitudes, subjective norms, and perceived behavioral control on behaviors, with less focus on mediation effects. Some studies (Ajzen, 1991) confirm these factors strongly predict intentions and behaviors, but did not examine mediators like saving orientation. Others have proposed a mediation effect, but focused on attitudes and intentions as mediators (Hasan & Rahman, 2023). However, few studies have explored how psychological motivations, such as the desire for learning and social backing, may mediate investment behaviors through a variable like personal saving orientation. In contrast to these studies, our research highlights a mediating role of saving orientation. We argue that inherent psychological motivators, such as the desire for learning and networks, influence investment behaviors indirectly through personal saving orientation, thus extending the TPB framework by incorporating a deeper psychological dimension to investment decision making. Our findings contribute to theory by showing that psychological factors shape investment choices via saving orientation in the context of developing countries where social and cultural factors may have a strong impact on behavior. This research contributes to the academic literature by filling gaps in the current understanding and providing practical insights for financial practitioners and policy makers in culturally diverse societies. 5.3. Practicing Implications This study has important policy implications for policymakers and regulators of the stock market, as well as pragmatic recommendations to educators and fintech firms, based on all its empirical findings about the relationships between desire for learning, flow experience, social support, Personal Saving Orientation (PSO), and investment decisions among Pakistan Stock Exchange (PSE) investors. For policymakers, the results confirm that PSO mediates the positive association between social support and investment decisions, while Pakistan’s low financial literacy rate (26%, Standard & Poor’s Global) limits investors’ capacity to leverage these factors (S. S. Shah et al., 2024). To address this gap, policymakers should prioritize community-based financial literacy programs that train local Inventors to facilitate peer discussions on saving goals. This recommendation directly builds on the finding that social support strengthens PSO, as such programs could help investors translate social guidance into the saving habits that underpin informed investment choices. Additionally, policymakers should implement regulatory nudges in the form of default saving schemes, for instance, automatic enrollment in low-risk PSE-linked savings accounts with opt-out options as per the published consultation rule book under the Security Act 2015 and Future Market Act 2016. The analysis demonstrates that PSO is a critical driver of investment decisions, reducing friction in saving processes, thus removing barriers to translating PSO into actionable investment behavior, particularly for new investors. policymakers could expand incentive programs for long-term savers. This aligns with the result that PSO exerts its strongest influence on sustained investment behavior, as rewards likely reinforce the consistent saving required for long-term investment success. For educators, the findings reveal that the desire for learning directly predicts investment decisions, unlike flow experience, which requires PSO as a mediator, and that hands-on engagement enhances PSO adoption. Educators, therefore, should redesign financial literacy curricula to explicitly link PSO to long-term investment literacy. For example, modules could integrate real PSE historical data to illustrate how monthly savings compound into stock market returns over 5–10 years. This addresses the key result that PSO acts as a bridge between psychological factors and investment choices; without explicitly teaching this connection, learners may struggle to apply theoretical knowledge to real-world investment scenarios. Educators should also integrate interactive tools (e.g., PomPak games-initiated by SBP) into workshops to build flow experience alongside PSO. The data shows that flow enhances investment consistency when paired with PSO, and simulators create low-risk environments where learners can practice aligning their saving goals (grounded in PSO) with concrete investment decisions. For fintech firms, the results demonstrate that social support and PSO together can improve investment confidence. Fintech firms should incorporate auto-enrollment features into savings-investment tools, for instance, apps like Naypay and Easy paisa could automatically allocate a portion of users’ income to PSE funds that align with their stated saving goals. This leverages the finding that reduced friction in saving processes strengthens the PSO investment link, as auto-enrollment eliminates barriers associated with manual action. Firms may also add peer-sharing forums within their platforms (e.g., in-app communities for exchanging saving strategies, PSE insights, and goal-tracking updates). The analysis shows that social support directly boosts PSO, so these forums will enable users to learn from peers and maintain consistent saving habits. Finally, firms should develop culturally tailored saving features. This aligns with the study’s contextual focus and the result that PSO is more impactful when tied to personal values, which will drive higher feature adoption and sustained user engagement. 6. Conclusion, Limitations, and Future Research 6.1. Conclusion This study, grounded in the theory of planned behavior, examines the interaction between the desire for learning, flow experience, social support, and personal saving orientation, influencing investment decisions. Using sample data collected from 516 stakeholders, the findings reveal that learning motivation and social networks significantly influence and strongly impact investment decisions. while flow has no direct effect on investment decisions. Furthermore, the findings indicate that personal saving orientation plays a significant mediating role in the nexus between experience and investment decisions, as well as social support and investment decisions. Interestingly, personal saving orientation plays an insignificant mediating role between the learning motivation and investment. However, the crucial mediating role of personal saving orientation emphasizes its role in linking the learning intention, focused attention, social encouragement, and investment decisions. This research contributes both practically and theoretically to our understanding of effectiveness in the modern digital economy. By examining the roles of learning motivation, complete absorption, and social support, we can inform policy and practice to promote ethical investment behaviors. Educational programs and policy frameworks can help integrate these factors into investment decisions. This study strengthens the TPB by incorporating psychological influences, offering valuable insights for behavioral finance and guidance policies that encourage ethical investment behaviors across cultures. This research adds to the TBP literature by emphasizing the importance of optimal performance state, learning motivation, and social networks in personal saving and investment. These findings highlight how investors' experience, desire, and support from their social networks enable them to save for future investment. While the research is limited to Pakistan’s stock market, future studies should replicate these findings in different countries and cross-cultural settings to better understand how psychological and social factors influence investment decisions. Comparative studies could further explore the role of subjective norms, PBC, and social engagement in shaping investment behavior, thereby contributing to cross-cultural research on TBP. Future researchers could also investigate key determinants of social support, flow experience, and learning intention in cultures, such as those in Europe, where individuals may play a different role in how investors approach saving and investing. 6.2. Limitations and Future Research This research has its limitations that can be addressed through future research. Firstly, the data were gathered from investors trading on the Pakistan Stock Market. To assist in revealing the findings in other countries, future research can consider carrying out similar research in other countries. A comparative study will give a better assessment of the models in other countries. Second, we utilized primary data, and in the future, studies can incorporate secondary trading data to obtain more accurate results. The use of secondary data would reduce social desirability bias and produce more powerful policy implications for stock markets. Third, we analyzed personal saving orientation alone as an intermediary variable in investment decisions. In the future, studies should also explore other variables, such as the influence of social media, risk tolerance, and financial situations. These results would help policymakers to understand investor behavioral patterns to guide the creation of policies and programs that are consistent with cultural heritage and encourage economic growth. Another limitation of this study is the use of convenience sampling, which can limit the applicability of the results. While convenience sampling is an effective approach, it lacks guarantees of a representative sample of the broader population of investors as a whole. For example, it could lead researchers to study easy-to-access subjects rather than a more representative sample. An interesting related limitation is the gender imbalance in our sample (84% male, 16% female). This skew limits external validity in that conclusions about relationships between our key variables (flow experience, social support, personal saving orientation, desire to learn) could overrepresent male perspectives, even with our subgroup analyses. Future studies may use a more representative gender distribution (i.e., 50% male, 50% female or 60% male, 40% female) to detect subtle gender-specific patterns in these variables and increase generalizability to the broader population of Pakistani investors. Future research would be well advised to employ random sampling or other more representative forms of sampling to further enhance the external validity of the research. Future studies might also be improved by more precisely measuring financial literacy to detect active engagement in learning and applying financial knowledge, rather than assessing a general intent to learn. This modification may better clarify the relationship between motivation to learn, saving orientation, and investment decisions. Finally, by exploring more profound psychological or social factors and employing newer methods such as machine learning, future studies would better understand the variables influencing investment decisions. It will make long-term measures to shape sensible investors in developing countries more effective and enhance market efficiency. Declarations Funding Funding and Acknowledgements This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia Ethical approval This study was approved by the Ethics Committee of Beijing University of Technology. All procedures were performed in accordance with the ethical standards of this committee and with the 1964 Helsinki Declaration. Written informed consent was obtained from all participants. Informed Consent: Informed consent was obtained from all participants involved in the study. In line with national regulations and institutional guidelines, written informed consent was not required for this research. Instead, participants completed an online informed consent process. During this process, participants were informed about two key aspects: (i) confidentiality, ensuring that any personal information shared by participants would be kept confidential and not disclosed or published, and (ii) use of data, where it was emphasized that the data collected would only be used for academic research purposes and not for commercial purposes. To proceed with participation, participants had to explicitly acknowledge their understanding and agreement by clicking the “agree and continue” button, which served as their consent to participate and allowed them to access and complete the questionnaires. Author Contribution IA: Writing the original draft, formal analysis, validation, writing review, editing, and methodology. TL: Conceptualization, critical insights. IA,TL, AA & MA: Formal analysis, validation, writing review. IA: Editing, project administration. 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Educational Psychology Review , 34 (4), 2129–2165. https://doi.org/10.1007/s10648-022-09714-0 Sliwka, A., Klopsch, B., Beigel, J., & Tung, L. (2024). Transformational leadership for deeper learning: shaping innovative school practices for enhanced learning. Journal of Educational Administration , 62 (1), 103–121. https://doi.org/10.1108/JEA-03-2023-0049 Soren, A. A., & Chakraborty, S. (2024). Beliefs, flow and habit in continuance of over-the-top (OTT) platforms. International Journal of Retail & Distribution Management , 52 (2), 183–200. https://doi.org/10.1108/IJRDM-06-2023-0379 Sourirajan, S., & Perumandla, S. (2022). Do emotions, desires and habits influence mutual fund investing? A study using the model of goal-directed behavior. International Journal of Bank Marketing , 40 (7), 1452–1476. https://doi.org/10.1108/IJBM-12-2021-0540 Te Brömmelstroet, M., Nikolaeva, A., Mladenović, M., Milakis, D., Ferreira, A., Verlinghieri, E., Cadima, C., de Abreu e Silva, J., & Papa, E. (2022). Have a good trip! expanding our concepts of the quality of everyday travelling with flow theory. Applied Mobilities , 7 (4), 352–373. https://doi.org/10.1080/23800127.2021.1912947 The Influence of Social and Personal Factors in Individual Investment Decision Making. (2022). Quality - Access to Success , 23 (191). https://doi.org/10.47750/QAS/23.191.10 Thoits, P. A. (1995). Stress, Coping, and Social Support Processes: Where Are We? What Next? Journal of Health and Social Behavior , 35 , 53. https://doi.org/10.2307/2626957 Tuncer, I. (2021). The relationship between IT affordance, flow experience, trust, and social commerce intention: An exploration using the S-O-R paradigm. Technology in Society , 65 , 101567. https://doi.org/10.1016/j.techsoc.2021.101567 Ullah, R., Ismail, H. Bin, Islam Khan, M. T., & Zeb, A. (2024). Nexus between Chat GPT usage dimensions and investment decisions making in Pakistan: Moderating role of financial literacy. Technology in Society , 76 , 102454. https://doi.org/10.1016/j.techsoc.2024.102454 Vira, D. K. (2024). Behavioural Finance . Academic Guru Publishing House, 2024. https://books.google.com.sg/books?id=I5YNEQAAQBAJ&dq=Behavioral+finance+poses+an+additional+obstacle+ to+validating+the+efficacy+of+financial+markets+and+the+rationality+of+investor+actions.+The +theoretical+concept+of+%22economic+man%22+was+addressed+by+Si Wagstaff, M. F., Flores, G. L., Ahmed, R., & Villanueva, S. (2021). Measures of curiosity: A literature review. Human Resource Development Quarterly , 32 (3), 363–389. https://doi.org/10.1002/hrdq.21417 Wedgeworth, M., LaRocca, M. A., Chaplin, W. F., & Scogin, F. (2017). The role of interpersonal sensitivity, social support, and quality of life in rural older adults. Geriatric Nursing , 38 (1), 22–26. https://doi.org/10.1016/j.gerinurse.2016.07.001 White, K. M., Smith, J. R., Terry, D. J., Greenslade, J. H., & McKimmie, B. M. (2009). Social influence in the theory of planned behaviour: The role of descriptive, injunctive, and in‐group norms. British Journal of Social Psychology , 48 (1), 135–158. https://doi.org/10.1348/014466608X295207 Yang, T., & Zhou, B. (2025). Does transition finance policies persistently fuel green innovation in brown firms? Investigating the roles of ESG rating and bank connection. Pacific-Basin Finance Journal , 90 , 102674. https://doi.org/10.1016/j.pacfin.2025.102674 Yaqoob, S., Ishaq, M. I., Mushtaq, M., & Raza, A. (2023). Family or otherwise: Exploring the impact of family motivation on job outcomes in collectivistic society. Frontiers in Psychology , 14 . https://doi.org/10.3389/fpsyg.2023.889913 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8782383","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":598589597,"identity":"680d23a0-7bce-4990-b8d3-7648c6313837","order_by":0,"name":"Ihsan Ali","email":"","orcid":"","institution":"Beijing University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Ihsan","middleName":"","lastName":"Ali","suffix":""},{"id":598589598,"identity":"e1bda8a9-15b7-4d57-b394-423cffe51cd6","order_by":1,"name":"Ting Liu","email":"","orcid":"","institution":"Beijing University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Liu","suffix":""},{"id":598589599,"identity":"0802f639-7df4-448f-9541-08dcf76066d6","order_by":2,"name":"Abdulrahman Alomair","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIie3PMYvCMBTA8SeBTrm6RnrYr9DSxcHDr5LSOevR7W6Ki1/Aya8gBDpHOtxgONdAlxNXhZZbHG64V0eRoJtD/vCGDD9eHoDP96z94ARAaij7l76H8AsJCjAPEQCa3UeG823e8rKKw8j8JhsJ49By0p4dhBmhGDdNKkOhOJJsZHkwWrjWaLFmuWwGkr6oupOQr5EAdYh4d1JnJDNJ6UHjlg8kpPtzkMSKqt+SIyH9x3hiOUSuLak9VRO8pZA0yBL9zdKl2cvo1UHGO6FsWzZvqwU5MP0+jcOvou6OrvOvYjiDzweAz+fz+W71Dz4cVKueLPb0AAAAAElFTkSuQmCC","orcid":"","institution":"King Faisal University","correspondingAuthor":true,"prefix":"","firstName":"Abdulrahman","middleName":"","lastName":"Alomair","suffix":""},{"id":598589600,"identity":"02615711-3836-4302-bfe4-1d82d49f893b","order_by":3,"name":"Mohammed Alomair","email":"","orcid":"","institution":"King Faisal University","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"","lastName":"Alomair","suffix":""}],"badges":[],"createdAt":"2026-02-04 06:09:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8782383/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8782383/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103769489,"identity":"21d9d0a1-8de8-477d-8ff9-9a8217ad3460","added_by":"auto","created_at":"2026-03-02 16:46:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":28612,"visible":true,"origin":"","legend":"\u003cp\u003eTheoretical Framework\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8782383/v1/97ade2206cbbc26f8d0a86eb.png"},{"id":104779182,"identity":"557ab444-bff6-467c-9c86-22997aebeea8","added_by":"auto","created_at":"2026-03-17 07:36:10","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":165029,"visible":true,"origin":"","legend":"\u003cp\u003ePath coefficient Through PLS bootstrapping\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8782383/v1/e3a23a1ad50890992818af7f.jpeg"},{"id":106401417,"identity":"2469c2e9-77dd-42f1-80c6-9556f4ad0479","added_by":"auto","created_at":"2026-04-08 08:49:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1837347,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8782383/v1/678cb0f2-13fd-4cf7-a6de-268550963c32.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring Personal Saving Orientation’s Influence On Investment Decision-Making","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eFinancial decision-making emerges as a major determining element in personal financial success (Sachdeva et al., 2023). Previous studies have addressed classical finance and the Theory of Planned Behaviors (TPB) in the context of investment decisions. According to utility-maximization-based financial theories, effective market conditions are expected to be associated with rational investor behaviors. In such efficient marketplaces, all market participants receive immediate standardized market information through a uniform distribution mechanism (Parra-Dom\u0026iacute;nguez et al., 2023). While assessing available opportunities, real investors emphasize on accurate information and their risk assessment (Lathief et al., 2024). However, conventional finance lacks consensus regrading operational efficiency of market and investor\u0026rsquo;s involvement in financial markets (S. Kumar et al., 2022; Schoenmaker \u0026amp; Schramade, 2019; Yang \u0026amp; Zhou, 2025).\u003c/p\u003e \u003cp\u003eBehavioral finance introduces an alternative perspective by challenging the core assumptions of investor\u0026rsquo;s rationality and market efficiency. The theoretical concept of \u0026ldquo;economic man\u0026rdquo; was revisited by (Giarlotta \u0026amp; Petralia, 2024; Vira, 2024), who by applying psychological theories demonstrated that humans\u0026rsquo; emotions and cognitive limitations in most of the cases distort their rational decision making. Several studies, in this regard, have examined and identified numerous cognitive biases and behavior lapses that directly or indirectly influence their investment choices (Che Hassan et al., 2023; S. Z. A. Shah et al., 2018), leading to undesirable investment outcomes and suboptimal portfolio performance (Ahmad et al., 2024; Kahneman \u0026amp; Tversky, 1979; I. Khan et al., 2021). Plethora of research have identified several demographical, emotional, and psychological elements that individually or collectively affect investment decisions (Baker et al., 2025; Crivelli et al., 2024; Luo et al., 2024), suggesting that the individual\u0026rsquo;s decisions are not entirely rational.\u003c/p\u003e \u003cp\u003eDespite these insights, literature still fails to consider the impact of key psychological and social factors, including, learning motivation, flow experience, and social support, on individuals\u0026rsquo; saving and investment behavior. Understanding such relationships is pivotal, especially in emerging markets like of Pakistan, where individuals\u0026rsquo; behaviors are motivated from collectivist cultural norms, family influence, and societal expectations, factors that differ from individualistic traits (Andre et al., 2019; \u0026ldquo;The Influence of Social and Personal Factors in Individual Investment Decision Making,\u0026rdquo; 2022). By examining these social and psychological factors in such setting, this study extends behavioral finance theory to emerging markets, with aim to explain the process through which investment behaviors are shaped. Henceforth, these insights form the basis of TPB, which explains how individuals\u0026rsquo; beliefs, social norms, and perceived behavioral control affect their decision making process (Aren \u0026amp; Hamamci, 2020).\u003c/p\u003e \u003cp\u003eMajority of research, in this context, have emphasized demographic attributes (P. Kumar et al., 2023; Priem et al., 1999), while some have investigated the psychological factors such as personality traits (Andreoli \u0026amp; ten Rouwelaar, 2024; Luo et al., 2024; Rajasekar et al., 2023), yet individual\u0026rsquo;s desire for knowledge, flow experience, social support and their influence on saving behavior is insufficiently addressed. Current study aims to address this gap by answering following Questions:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eDoes social support, flow experience, and desire for learning impact investment decisions?\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDoes personal saving orientation mediate the relationship between desire for learning, social support, and flow experience, and investment decisions?\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe significance of the present study lies in situating personal saving orientation (PSO) within the financial realities of collectivist societies such as Pakistan. Previously several studies have analyzed the mediation through psychological constructs in literature, however, focusing how PSO, deeply rooted in communal and familial influence, mediates the relationship between psychological factors and investment decisions distinguishes our study. Moreover, to our knowledge, flow experience is not being investigated in the context of investment decisions. Furthermore, our study, through cultural lens, enlightens existing behavioral finance models through embedding constructs such as saving orientation within social and cultural contexts. Doing so provides a more holist review of individuals\u0026rsquo; decision making process under the influence of social and psychological factors. Additionally, this study significantly contributes to academia by extending the applicability of TPB applicability to cultural oriented saving behavior, which is currently underrepresented. Lastly, this study contributes to the contextualized behavioral models that encompass realities of emerging economies rather than the assumptions of classical finance.\u003c/p\u003e"},{"header":"2. Theoretical Background and Hypotheses Development","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Theoretical Background and Operationalization of Variables.\u003c/h2\u003e \u003cp\u003eThe Theory of Planned Behavior (TPB) is critical framework of (Ajzen, 1991) that provides insight into how individual\u0026rsquo;s intentions are translated into behavior. According to this framework, individuals\u0026rsquo; behavioral intentions are shaped from three primary elements i.e., subjective norms, attitudes, and perceived behavioral control. These elements collectively determine individuals\u0026rsquo; behavioral intentions, which further shapes into actual behavior. While attitudes reflect individual\u0026rsquo;s assessment of engagement in a specific action, subjective norms refer to the perceived social pressure and expectations, whereas perceived control behavior in this model represents the perception of their ability to perform the behavior. Earlier studies have extended the TPB to examine financial choices and behaviors (Raut, 2020; Raut et al., 2018). For example (Abid \u0026amp; Jie, 2023; Liu et al., 2020), used the TPB to investigate financial decision-making process and found subjective norms and perceived behavioral control (PBC) as critical influencers of individuals' investment choices. Similarly, the findings (Che Hassan et al., 2023; Raut \u0026amp; Kumar, 2024) emphasized the importance of social and psychological factors determining financial behavior.\u003c/p\u003e \u003cp\u003eIn this study, TPB has context-sensitive explanatory power to clarify how financial behaviors are shaped in collectivist societies such as of Pakistan, where behaviors are not shaped by sole personal attitudes, but also by community norms, family expectations and broader social values (Omer et al., 2021; Sarwar et al., 2021). Subjective norms, in collective societies carry more weight than individualist cultures. Whereas psychological elements comprising emotional engagement, motivation and cognitive focus, further influence how individuals might process the available information and evaluate options (Shih et al., 2022). Social interactions in such situations have higher tendency to influence both perceived capability and normative expectations (Bavik et al., 2020; Goyal \u0026amp; Kumar, 2021; Thoits, 1995). Therefore, this study draws on TPB perspective to explain how cultural and psychological factors shape the formation of investment intentions and actual behaviors, emphasizing the interplay of social influence, emotions, and cognitions rather than purely rational decision-making.\u003c/p\u003e \u003cp\u003ePrincipally, learning motivation mirrors the individual\u0026rsquo;s intrinsic desire to attain valuable knowledge, particularly financial knowledge in the context of our study (Bashir et al., 2024). From the perspective of TPB, learning motivation can be seen as an element that shapes individuals\u0026rsquo; attitudes towards gaining knowledge in order to make informed financial decisions. In many cases, learning motivation reflects individuals\u0026rsquo; personal drive to understand financial matters deeply. Therefore, individuals with higher intellectual curiosity exhibit favorable attitudes towards financial markets and investment opportunities, improving perceived behavioral control (Bashir et al., 2024). This motivation equips individuals with the knowledge necessary for appropriate decisions, increasing their confidence and improving investment outcomes (Chen et al., 2024). Such motivations are probably higher in collectivist cultures, where financial literacy is viewed as a collective responsibility (De Beckker et al., 2020). Therefore, motivation of learning extends beyond a general curiosity for knowledge, in fact it shows individuals capability to utilize financial literacy in real world. So, we emphasize learning motivation from both cognitive and applied aspects of learning, linking knowledge gathering and its practical use to culturally embedded financial investment decisions.\u003c/p\u003e \u003cp\u003eWhile learning desire reflects the attitude of an individual, social support defines the support from family, friends and mentors in form of instrumental assistance, informational and emotional guidance (Bavik et al., 2020; Thoits, 1995). Within TPB perspective, social support can be explained as a key determinant of subjective norms, highlighting the behaviors that are socially endorsed and expected. Such behaviors are of key significance in collectivist societies, often dictating acceptable saving and investment behaviors, aligning individuals\u0026rsquo; behavior with communal expectations. Moreover, it enables individuals to feel more secure and supported, leading to sound decisions in uncertain conditions. Such emotional support is highly relevant in markets like of Pakistan, which has a strong collectivist society (K. B. Khan et al., 2024).\u003c/p\u003e \u003cp\u003eWithin the framework of TPB, individual\u0026rsquo;s flow experience can be conceptualized as both a cognitive and affective enhancer which primarily links perceived behavioral control and attitudes of individual (Soren \u0026amp; Chakraborty, 2024). Flow in literature is conceptualized as a multidimensional construct that encompass hedonic and cognitive dimensions (Landh\u0026auml;u\u0026szlig;er \u0026amp; Keller, 2012; Ozkara et al., 2017). While hedonic flow relates to emotional enjoyment and pleasure, the cognitive flow emphasizes concentration, balance and absorption. Current study analyzes the cognitive flow as a perceived behavioral control. Conceptually, (Csikszentmihalyi \u0026amp; Csikzentmihaly, 1990) defined flow as a state of intrinsic motivation, deep absorption, and focused engagement that significantly improves individual\u0026rsquo;s task performance. From financial decision-making context, flow can enhance individual\u0026rsquo;s strength of perceived confidence, focus, and competence in managing complex or uncertain investment situations (Fong et al., 2015). Simultaneously, flow might foster favorable attitudes by means of making financial engagement intrinsically satisfying and emotionally rewarding. Thus, this dual influence reflects bridging capability of flow between cognitive control and affective evaluation processes that are central to TPB.\u003c/p\u003e \u003cp\u003eCurrent study emphasizes the mediating role of Personal saving behavior utilizing TPB to elucidate its impact over financial decision making. Personal Saving Behavior is conceptualized as an individual\u0026rsquo;s consistent inclination towards savings, emphasizing intentional and habitual behaviors that foster secure financial well-being (Adewoyin et al., 2024). TPB in this context describes PSO as an influencer of attitudes by means of positive evaluations of saving behaviors, that in turn improves perceived behavioral control. Therefore, PSO from financial behavioral context, can be viewed as an attitude-related construct, that reflects individual\u0026rsquo;s enduring predisposition towards financial security. Personal saving behaviors in number of studies is being linked with cultural contexts, therefore, it is highly relevant in a collectivist society such as of Pakistan where behaviors are being influenced by community (Alwedyan, 2024; Cruz et al., 2025).\u003c/p\u003e \u003cp\u003eIn summary, our study while extending TPB integrates psychological and cultural determinants into financial decision-making process. While learning motivation and cultural determinants strengthen individual\u0026rsquo;s attitudes and perceived behavioral control, flow enhances cognitive engagement and confidence in managing financial uncertainty. Collectively, psychological and cultural elements influence PSO, which further translates these affective and cognitive inputs into saving tendencies, shaping individuals\u0026rsquo; investment intentions and behaviors. Positioning PSO as culturally grounded mediation within TPB, our study aims to capture the psychological mechanisms, social norms, and their joint impact over individuals\u0026rsquo; financial decision making in context of Pakistan.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Hypotheses Development\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Desire for Learning and Investment Decision\u003c/h2\u003e \u003cp\u003eDesire of learning is defined as a motivation of an individual to acquire knowledge. This motivation is often linked with curiosity which represents one\u0026rsquo;s intrinsic psychological factor (Loewenstein, 1994). Number of studies have examined curiosity in the context of financial decision making (Shukla et al., 2022; Skinner et al., 2022). Curiosity motivates individual to acquire information and knowledge that is crucial for enlightening their psychological development which navigates them in changing their financial behavior. It emulates the individuals\u0026rsquo; attitudes towards learning that is essential for assessing degree of perceive risk (Wagstaff et al., 2021). This learning orientation can be viewed as positive attitude towards information gathering and knowledge seeking, which aligns with the attitudinal dimension of TPB. Therefore, it is rational to argue that individuals with greater desire for learning are more prone towards financial literacy (Pahlevan Sharif \u0026amp; Naghavi, 2020).\u003c/p\u003e \u003cp\u003eSeveral studies have linked curiosity with investment decisions by utilizing different behavioral models. For instance, (Fishbach \u0026amp; Woolley, 2022) argued that individuals\u0026rsquo; curiosity leads to development of essential cognitive abilities that supports sound investment decisions through innovation and strategic thinking (Hagtvedt et al., 2019). In the literature of mindfulness, studies have found that knowledge driven culture in societies and organizations improve critical analysis which in turn improves decision making (Kashdan et al., 2020; Polman et al., 2022). (Sourirajan \u0026amp; Perumandla, 2022) in relation to our study, described desires as key influencers of individuals\u0026rsquo; investment intentions.\u003c/p\u003e \u003cp\u003eDrawing upon these studies, and TPB, it can be inferred that the individuals desire of learning is associated with positive attitudes towards pursuing key information. This suggests that learning is a positive attitude that is pivotal for individual\u0026rsquo;s perceived capability, openness, and confidence. Individuals who have higher desire of learning are more likely to outperform those who have weak desire in terms of performance. Moreover, such desire of learning will significantly contribute to investment intentions and behaviors. Thus, we hypothesize that:\u003c/p\u003e \u003cp\u003e \u003cem\u003eH1: Investors with higher desire of learning prefer investment in stock markets.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Social Support and Investment Decision\u003c/h2\u003e \u003cp\u003eSocial support, in a collective society, plays an important role in shaping individuals\u0026rsquo; behavior. Social support is viewed as a guidance, emotional assistance, and help received by individuals from social network (Casillas et al., 2019), including family, friends, and communities. Literature indicates that the nexus of social support and financial decisions is complex mechanism, particularly in highly socio-cultural societies. Number of studies have found social influence a key element of individuals (Rehman et al., 2024; Sachdeva \u0026amp; Lehal, 2024). (Bernstein et al., 2017) While investigating family owned enterprises revealed that family support plays a pivotal role in the governance and organization performance. They further stated that family involvement in times of risk plays a crucial role in mitigation.\u003c/p\u003e \u003cp\u003eThrough TPB, social influences are viewed as subjective norms (Ajzen, 1991), that play a crucial role in shaping individuals\u0026rsquo; behavioral intentions by perceived approval or disapproval. In the context of investment decisions, perceived social support is linked to psychological assurance that significantly improves perceived behavioral control which leads to socially approved behavior. This is substantiated by the study of (White et al., 2009) who revealed that injunctive and descriptive norms strongly predict behavioral intentions. In classical literature, (East, 1993) finds similar impact, suggesting that normative beliefs are directly related to investment intentions through theory TPB mechanisms. From modern literature, study of (Agnew \u0026amp; Sotardi, 2025) investigating family financial socialization concluded that family support improves confidence and enhances financial behavioral decisions. Notably, in the literature of collectivism culture, this relationship is even stronger because in collectivist societies, family expectations and social support are central (Lumpkin et al., 2008). Henceforth, based on this enriched theoretical and empirical evidence, we argue that:\u003c/p\u003e \u003cp\u003e \u003cem\u003eH2: Investors who get high social support are more likely to invest in stock markets.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Flow Experience and Investment Decisions\u003c/h2\u003e \u003cp\u003eFlow experience is viewed as a multi-dimensional construct that includes cognitive and motivational factors. These dimensions are not always constant, i.e., can be altered by malleable characteristics that include both individuals\u0026rsquo; traits and social interactions (Davis \u0026amp; Csikszentmihalyi, 1977). For instance, (Newton et al., 2020), proposed that individual\u0026rsquo;s social interaction affects individuals\u0026rsquo; flow experience through social learning. However, current study emphasizes that the flow experience is influenced more by psychological elements than from social interactions. Therefore, in this study, flow experience refers to a psychological state in which individual is fully absorbed in an activity, aiming optimal performance through concentration and sense of accomplishment (Mattke et al., 2021). In essence, cognitive flow experience occur when an individual\u0026rsquo;s level skill is aligned with the challenges of a task, which in long run results in engaging and rewarding experience (Newton et al., 2020). Despite scarce literature of flow (cognitive flow) in the framework of financial decision making, literature from other relevant fields provides a foundational support for relationship between flow experience and investment decision.\u003c/p\u003e \u003cp\u003eGenerally, literature highlights that deep task involvement (a key aspect of cognitive flow) positively influences perceived competence and instrumental beliefs about that task. For instance, (Sliwka et al., 2024) revealed that the individuals placed in a stimulating environment are more likely to experience cognitive flow, which results in improved performance and innovative outcomes. In a technology setting, (El Abed \u0026amp; Castro-Lopez, 2024) demonstrated that individuals exposed to immersive technological experiences had positive intentions towards purchasing. Similarly, (Ariely, 2000) found that information flow experience directly impacts consumers\u0026rsquo; purchasing intentions. Together, all these studies suggest that flow in financial investment models can enhance investors' perceived behavioral control and spur positive attitudes, which, according to TPB, strengthen investment intentions that convert into actual behavior. This is substantiated by the recent study of (Goswami et al., 2025), who found cognitive absorption as a key influencer of investors\u0026rsquo; intention to adopt robot advisors\u0026rsquo; technology. Therefore, from the TPB perspective and existing evidence, we propose that experience flow, through absorption, deep learning, and concentration, augments individuals' perceived behavioral control which generates positive attitudes leading to stronger investment intentions. Based on these theoretical and empirical insights, we hypothesize that:\u003c/p\u003e \u003cp\u003e \u003cem\u003eH3: Investors with experience in flow are more likely to invest in stock markets.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4. Mediating Role of Personal Saving Orientation\u003c/h2\u003e \u003cp\u003ePersonal saving orientation refers to an individual's tendency to prioritize saving and financial planning, reflecting their attitude towards and habits related to saving (Sekścińska \u0026amp; Markiewicz, 2020). The desire to learn is a key psychological characteristic of curiosity, and an individual\u0026rsquo;s tendency to save can play a mediating role between it and investment decisions (Kaur et al., 2020). The desire to learn itself can help investors establish a good savings and knowledge base for new investments. On the other hand, it can also prompt investors to decide whether to try new investments or settle for the status quo (savings) (Furnham \u0026amp; Cheng, 2019; Ghaffar et al., 2024). Research supports this idea, indicating a positive correlation between increased demand for knowledge and disciplined savings habits, leading to sound investment plans. Specifically, individuals who proactively pursue financial knowledge tend to grasp the importance of saving better, which subsequently influences their investment decisions (Sekścińska \u0026amp; Markiewicz, 2020). However, in collectivist societies such as Pakistan, this relationship may be moderated or constrained by family expectations, social norms, and cultural values, which often influence or override individual motivations related to curiosity and learning (Yaqoob et al., 2023). Such cultural contingencies play a significant role in shaping whether and how the desire for learning influences saving orientation and investment decision (Shantha, 2019).\u003c/p\u003e \u003cp\u003eIn collectivist societies like Pakistan, however, the role of learning motivation and saving behavior is often influenced by family and community values. Social norms, religious beliefs, and cultural practices tend to shape financial behavior, and these factors may influence how personal saving orientation mediates the relationship between social support, investment guidance, and personal savings. As proposed by (Gomes et al., 2021), households with strong social networks have a high desire for savings, which in turn influences investment decisions. (Baker et al., 2021) Further emphasized this point by studying how savings behavior is passed down from generation to generation in households. They showed that the family environment that fosters a savings culture from an early age influences the next generation, thereby influencing investment behavior. Research highlights that financial socializing significantly influences children's financial literacy and saving habits, which affect their investment decisions (LeBaron \u0026amp; Kelley, 2021). Additionally, a study examining the cultural origins of investment behavior found that families with a substantial savings culture tend to pass down financial behaviors to their children. Thereby affecting their investment decisions (Magrelli et al., 2022). In the Pakistani context, this process is further influenced by the family-oriented nature of society, where the decisions of family elders often shape the financial behaviors of younger generations. The role of family and community support in guiding financial behavior is a significant factor in how investment decisions are made (Sajjad et al., 2025). The concept of the flow experience, especially in specific cultural contexts, provides unique insights into the relationship between participation in activities and investment decisions (Dwivedi et al., 2022). An immersive state is a state of high engagement and enjoyment. In specific cultural contexts, achieving an Immersive state may be more meaningful. When investments align with personal values and cultural beliefs, there may be greater satisfaction as these investments resonate more deeply with the investor\u0026rsquo;s code of conduct (Al-Afeef et al., 2024; Jan \u0026amp; Shafiq, 2021). They found that when people\u0026rsquo;s behavior aligns with their values and worldview, they are happier investors. Research indicates that individuals who experience are more likely to develop regular saving habits as they understand the role of saving in achieving their goals (Te Br\u0026ouml;mmelstroet et al., 2022). It is also noted that those who achieve engagement tend to make better financial decisions due to increased focus and engagement (Csikszentmihalyi \u0026amp; Csikzentmihaly, 1990). Additionally, the Study found that individuals with autotelic personalities who often exhibit a State of involvement exhibit higher levels of conscientiousness, which positively influences their saving and investment behaviors (Te Br\u0026ouml;mmelstroet et al., 2022). This suggests that when people are intrinsically motivated and enjoy the process of financial planning, they are more likely to save consistently and make informed investment choices. Further, it is important to note that in a collectivist society like Pakistan, achieving an optimal experience in investment activities is often influenced by cultural alignment. Investments that resonate with the individual's community or family values tend to yield greater satisfaction and engagement.\u003c/p\u003e \u003cp\u003eIn collectivist societies, saving and investment behaviors are strongly influenced by family values and community expectations. The importance of saving as a collective activity is reinforced through social support systems, with individuals often relying on family networks for financial guidance. These cultural elements make personal values between saving and investment closely aligned and communal norms (Polman et al., 2022). To summarize, the mediating role of personal savings orientation between learning desire, Social assistance, Immersive state, and investment decision making is evident. Moreover, this relationship may be moderated by socio-cultural factors prevalent in collectivist societies like Pakistan, where family expectations and social norms often influence individual financial behaviors. It has not been studied particularly in socio-cultural contexts similar to those of Pakistan. Although the causal relationship is complex, empirical evidence emphasizes the importance of savings orientations as a key factor in adjusting various antecedents that affect investment decisions. Based on the above discussion, we proposed the following hypothesis:\u003c/p\u003e \u003cp\u003e \u003cem\u003eH4: Personal saving orientation mediates the relationship between the desire for learning and investment decisions.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eH5: Personal saving orientation mediates the relationship between social support and investment decisions.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eH6: Personal saving orientation mediates the relationship between flow experience and investment decisions.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Methodology","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Data and Sample\u003c/h2\u003e \u003cp\u003eIn this study, we used empirical data to examine the investment behaviors of investors in Pakistan by employing a quantitative research approach. Our focus was on investors who engaged in both short-term and long-term stock market investments. The Pakistan Stock Exchange (PSE) and the State Bank of Pakistan (SBP) assisted us in identifying suitable participants for the study. To gather data, we initially developed a questionnaire in English. The questionnaire was divided into two sections. The first section collected demographic information, including gender, age, employment status, income, education level, years of investment experience, and type of investment. The second section included questions on the desire for learning, flow experience, social support, personal savings orientation, and investment decisions. A cover letter was included on the first page of the survey to clarify that the collected data would be used solely for research purposes and that participants' personal information would not be disclosed to the public. Since we collected data from individual investors, before data collection, participants were informed, and verbal consent was obtained for completing the questionnaire. They were also informed that their participation was voluntary. Data were collected using the questionnaire from July 2024 to October 2024. We reached out to 750 investors using a combination of email, phone calls, and face-to-face interactions, with assistance from employees of the Pakistan Stock Exchange (PSE) and the State Bank of Pakistan (SBP). We used convenience sampling, a non-probability sampling method, to collect the data. Although convenience sampling allowed us to gather data quickly and efficiently, it is important to note that this method may limit the representativeness of our sample. As participants were selected based on their availability, we may have missed certain segments of the investor population, leading to a sample that may not fully reflect the diversity of investor groups in Pakistan. Despite achieving a 69% response rate and retaining 516 usable responses, non-response bias remains a concern. As participation was voluntary, investors with lower financial literacy or less experience may have been less likely to respond. This may distort the findings and limit the generalizability of the results.\u003c/p\u003e \u003cp\u003eIn Pakistan, about 220,000 retail investors are involved in the PSX, while 883 domestic and 1,886 foreign institutional investors are involved. Participation is low in the stock market, as only 0.22% of the population invests (Pakistan Stock Exchange, 2024). Moreover, the financial literacy rate is only 26%, as per the Standard \u0026amp; Poor's Global Financial Literacy Survey. These facts prove the importance of addressing financial literacy gaps and increasing market participation (S. S. Shah et al., 2024).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Questionnaire Development\u003c/h2\u003e \u003cp\u003eWe utilized validated measures that had already been tested on various Asian markets. The primary method used in this research was a cross-sectional survey. All variables were measured using a five-point Likert scale, ranging from \u0026ldquo;strongly disagree\u0026rdquo; = (1) to \u0026ldquo;strongly agree\u0026rdquo; = (5). The first draft of the questionnaire was created based on findings from existing literature. Since English is widely used in Pakistan\u0026rsquo;s financial sector (including the stock market and banking), our target respondents, investors active in the PSE, were expected to be proficient in English. The questionnaire language was simplified to ensure clarity. The desire for learning was measured using 10 scale items adapted from (Shantha, 2019), which was validated in a Sri Lankan investor context of behavioral bias prevention. We adapted the items to fit our research context. The scale had high reliability in our sample α\u0026thinsp;=\u0026thinsp;0.750. A sample item is \"I am interested in discovering new investment opportunities\". For flow experience, we used 3 items from (Tuncer, 2021), which were originally developed in a Turkish social commerce context where flow measured immersive engagement with social media (e.g., Instagram) for online shopping. Since the original research focused on online buying behaviors, we adapted these items to assess flow experience in relation to investment activities, for example, the original item \u0026ldquo;While browsing the goods on Instagram, I generally feel that time is passing quickly\u0026rdquo; was revised to our sample item \u0026ldquo;While browsing investment opportunities on social media, I generally feel that time is passing quickly\u0026rdquo;. The reliability value in our sample is α\u0026thinsp;=\u0026thinsp;0.820. The 4-item Social support scale was adopted from (Wedgeworth et al., 2017), a measure originally validated in the U.S rural elderly care context, where it focused on satisfaction with support to predict rural elderly adults' quality of life. The scale was later tested in Asian markets by previous studies such as (Dissanayake et al., 2023; Koydemir et al., 2013). To fit our investment behavior context, we revised the original items to focus on the general task \u0026ldquo;Overall, how satisfied have you been in the last month with the help you have received with transportation, household and yard work, and shopping?\u0026rdquo; became our adapted version \u0026ldquo;Overall, how satisfied have you been in the last month with the help you have received with transportation, household chores, and shopping for investment opportunities?\". The adapted scale shows good reliability in our sample, α\u0026thinsp;=\u0026thinsp;0.857. Furthermore, personal saving orientation (PSO) was assessed with 5 items from (Ponchio et al., 2019), a Brazilian consumer finance study where PSO was used to predict the financial security dimension of consumer perceived financial well-being. These items have also been tested in India and Pakistan (Alam \u0026amp; Siddiqui, 2021; Gupta \u0026amp; Mukherjee, 2024). The adapted scale showed high reliability (α\u0026thinsp;=\u0026thinsp;0.919). a sample item is \u0026ldquo;I keep a careful watch over my spending daily\u0026rdquo;. Finally, 5 investment decision-making items were modified from (Ullah et al., 2024), a set of behavioral finance studies applied to emerging markets. The scale showed high reliability for the Pakistan Stock Exchange (PSE) context (α\u0026thinsp;=\u0026thinsp;0.785). A Sample item is \u0026ldquo;I like to buy stocks that have recently outperformed the market\u0026rdquo;.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Data Analysis and Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents all the respondents, including their year of investment, type of investment, income, and gender. Males comprise 84% of the respondents, while females\u0026rsquo; ratio is 16%. This gender distribution aligns with broader societal and economic norms in Pakistan, where women tend to rely on male family members for financial choices due to long-term patterns of economic dependence. Thus, men typically act as the only decision-makers for household finance and are overrepresented in institutional investment activities, such as participation in the Pakistan Stock Exchange (PSE). This is also due to lower female participation in the workforce and limited independence with finance resources among women in the country. The age of the respondents ranges between 25 and 55 years. The education level of respondents is mainly high school or equivalent, which is about 27%. Most of the respondents, 52%, are self-employed and highly experienced, particularly in various types of stock market investments.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Characteristics of the Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticular\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. 18\u0026ndash;25 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. 26\u0026ndash;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.36-45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.46-55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.56-65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.66 and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment Structure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.Full time salaried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.Par time salaried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.Self-employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.Unemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.Retired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.Housewife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.Student\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIncome (PKR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.50,000 or less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.51000-100000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.101000\u0026ndash;150000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.151000\u0026ndash;200000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.201000\u0026ndash;250000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.Above 250000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.Primary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.Diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.Bachelor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.Master's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.Ph.D. degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYear of Investment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Under five years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. 5\u0026ndash;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. 10\u0026ndash;15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Over 15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of Investment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. Short term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6. Long term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7. Both short and long term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Descriptive Statistics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e depicts the descriptive statistics and multi-collinearity issues. The results indicate that the flow experience has the highest average score of 3.608, while the investment decision has the lowest average score of 3.45. Desire for Learning has the highest standard deviation of 0.709, while flow experience has the lowest standard deviation of 0.625. The VIF (variance inflation factor) is used to analyze multicollinearity (Shahzad et al., 2021). In a research study, a researcher (Sarstedt et al., 2023) concluded that multi-collinearity occurs only when the values of VIF exceed 5, showing a significant level of collinearity. On the other hand, the findings of the current research study show the significant value of VIF, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, where it is less than 5, and show that there is no multi-collinearity. In addition, skewness and kurtosis analyses were conducted to check the normality of the data. The skewness and kurtosis values are in a suggested range of +/- 2, as given by (Aslam, 2021).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd. Dev\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSkewness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKurtosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDesire For Learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.169\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlow Experience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.401\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.812\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersonal Saving Orientation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.457\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInvestment decision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Common Method Bias\u003c/h2\u003e \u003cp\u003eCross-sectional data have a big limitation of common method bias that influences their results. We checked if there is any problem of common method bias in our sample data; the data was obtained from a single source, and it is cross-sectional, due to which the issue of \u0026ldquo;common method bias or common method variance (CMV)\u0026rdquo; may arise (Jordan \u0026amp; Troth, 2020). According to (Kock et al., 2021), Common method bias issues can be detected by executing \u0026ldquo;Harman's Single Factor Test.\" To follow the (Kock et al., 2021) method, we employed Harman\u0026rsquo;s single-factor test in SPSS. The test results indicate the absence of a common method bias issue because the percentage variance is lower than the cutoff point (i.e., below 50%). It means that there is no problem of common method bias in our sample data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Confirmatory Factor Analysis (CFA)\u003c/h2\u003e \u003cp\u003eWe assessed the measurement model with Smart PLS 4 to cross-validate the theoretical model. First, we conducted Exploratory Factor Analysis (EFA) to confirm adapted items from different domains. All the items retained had EFA factor loadings of between 0.670 to 0.938 (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) well above the 0.5 threshold (Gebremedhin et al., 2022), confirming no items were misaligned with their parent constructs. Next, we looked at Confirmatory Factor Analysis (CFA) item loadings for each factor were found to be above the threshold of 0.5; however, we removed some items from the scale because their values were not satisfactory (below 0.5). The remaining items had outer loadings ranging from 0.664 to 0.914, which were considered sufficient to include every item in the model. Researchers (Asghar et al., 2021) suggest that a Cronbach's alpha and composite reliability (CR) greater than 0.7 indicate a sufficient level of reliability for the constructs. The Cronbach's alpha and CR values were above 0.7, demonstrating the high reliability of the constructs. The range of these values was from 0.750 to 0.924, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAdditionally, the average variance extracted (AVE) and the square root of the average variance extracted were used to measure the convergent and discriminant validity of all the constructs. The AVE scores and the square root of AVE (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) for all constructs exceeded the recommended thresholds of AVE\u0026thinsp;\u0026gt;\u0026thinsp;0.50 and the square root of AVE\u0026thinsp;\u0026gt;\u0026thinsp;0.70, as specified by reference (Hair et al., 2019).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactor Loading, Validity, and Reliability\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables and items\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEFA Factor\u003c/p\u003e \u003cp\u003eLoading\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCFA Factor\u003c/p\u003e \u003cp\u003eLoading\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCronbach's\u003c/p\u003e \u003cp\u003ealpha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC.R\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAVE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDV\u003c/p\u003e \u003cp\u003e\u0026radic; AVE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDesire For Learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.497\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edl1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edl2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edl3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edl4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlow Experience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efe1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efe2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efe3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ess1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ess2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ess3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersonal Saving\u003c/p\u003e \u003cp\u003eOrientation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.805\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epso1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epso2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epso3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epso4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInvestment Decision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.699\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eid1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eid2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eid3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: DL: Desire for Learning, FE: Flow experience, SS: Social Support, PSO: Personal Saving orientation, ID: Investment decision. Edu: Education, M. status: Material Status\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Correlations\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e provides the correlation coefficient between the constructs. The coefficient values demonstrate a substantial positive relationship between desire for learning (r\u0026thinsp;=\u0026thinsp;0.125), flow experience (0.074), and social support (r\u0026thinsp;=\u0026thinsp;0.317) with investment decisions. Similarly, there is a substantial positive association between desire for learning (r\u0026thinsp;=\u0026thinsp;0.166), experience (r\u0026thinsp;=\u0026thinsp;0.191), social support (r\u0026thinsp;=\u0026thinsp;0.216), and personal saving orientation. In addition, there is a substantial relationship between personal saving orientation (r\u0026thinsp;=\u0026thinsp;0.184) and investment decisions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiscriminant validity through HTMT\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. DL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. FE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. SS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. PSO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. ID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: DL: Desire for Learning, FE: Flow experience, SS: Social Support, PSO: Personal Saving orientation, ID: Investment decision.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Structural model\u003c/h2\u003e \u003cp\u003eThe study sought to examine how personal saving orientation mediates the relationship between the desire for learning, social support, flow experience, and investment decision-making.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHypotheses\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaths\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ-values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSTDEV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et-values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDecision\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDirect Effect\u003c/b\u003es\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL -\u0026gt; ID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL -\u0026gt; PSO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFE -\u0026gt; ID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eInsignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFE -\u0026gt; PSO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSO -\u0026gt; ID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSS -\u0026gt; ID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSS -\u0026gt; PSO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMediating Effects\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDL -\u0026gt; PSO -\u0026gt; ID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eInsignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFE -\u0026gt; PSO -\u0026gt; ID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSS -\u0026gt; PSO -\u0026gt; ID\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSignificant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: DL: Desire for Learning, FE: Flow experience, SS: Social Support, PSO: Personal Saving orientation, ID: Investment decision.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe used structural equation modeling (SEM) analysis with the PLS bootstrapping approach to examine our study hypotheses. We measured the results using t-statistics, standardized path (Beta coefficient) values, and p-statistics. The results, presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, indicated that there were significant relationships between the variables Desire for Learning with values (β\u0026thinsp;=\u0026thinsp;0.204, p \u0026lt;\u0026thinsp;.05) and social Support with values (β\u0026thinsp;=\u0026thinsp;0.216, p \u0026lt;\u0026thinsp;.05), which had a positive impact on investment decisions. whereas the flow experience with values (β = -0.015, p \u0026gt;\u0026thinsp;.05) did not have a significant impact on investment decisions. We accepted hypotheses H1 and H2 but rejected H3. Furthermore, Learning motivation with values (β\u0026thinsp;=\u0026thinsp;0.118, p \u0026lt;\u0026thinsp;.05), social support with values (β\u0026thinsp;=\u0026thinsp;0.144, p \u0026lt;\u0026thinsp;.05), and experience with values (β\u0026thinsp;=\u0026thinsp;0.144, p \u0026lt;\u0026thinsp;.05) showed significant positive effects on personal saving orientation. Additionally, the Personal Savings Orientation (β\u0026thinsp;=\u0026thinsp;0.121, p \u0026lt;\u0026thinsp;.05) had a positive impact on investing decisions.\u003c/p\u003e \u003cp\u003eTo assess the robustness of these core findings and rule out the influence of confounding factors, we conducted a series of tests in Smart PLS-4, following the methodology outlined by Baron and Kenny (Baron \u0026amp; Kenny, 1986). We expanded the model to include control variables employment status (emps), material status (m. status), education (Edu), gender, income, Year of investment, type of investment, and re-examined the key relationship with investment decisions (id) (see Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e06\u003c/span\u003e). These checks confirmed the stability of our main results: core variable effects persisted, with Desire for learning (dl) remaining a significant positive predictor of id (β\u0026thinsp;=\u0026thinsp;0.167, p\u0026thinsp;=\u0026thinsp;0.001) and social support (ss) maintaining a significant positive impact (β\u0026thinsp;=\u0026thinsp;0.162, p\u0026thinsp;=\u0026thinsp;0.000), consistent with our initial findings. Flow experience (fe) still showed no statistically significant effect on id (coefficient = -0.035, p\u0026thinsp;=\u0026thinsp;0.416), further validating our decision to reject H3. Control variables\u0026rsquo; influence included employment status (emps), having a significant negative effect on id (β = -0.0164, p\u0026thinsp;=\u0026thinsp;0.005), and material status (m. status), exerting a significant positive effect (coefficient\u0026thinsp;=\u0026thinsp;0.468, p\u0026thinsp;=\u0026thinsp;0.017), additional insights that do not alter our core conclusions. All other controls (age: p\u0026thinsp;=\u0026thinsp;0.602; education: p\u0026thinsp;=\u0026thinsp;0.805; gender: p\u0026thinsp;=\u0026thinsp;0.659; income: p\u0026thinsp;=\u0026thinsp;0.458; type of investment: p\u0026thinsp;=\u0026thinsp;0.312; year of investment: p\u0026thinsp;=\u0026thinsp;0.431) had no significant impact on id, confirming our main results are not driven by these factors. The relationship between PSO and id was marginally significant (p\u0026thinsp;=\u0026thinsp;0.063) in robustness checks, aligning with its significant positive effect in our main analysis (β\u0026thinsp;=\u0026thinsp;0.121, p \u0026lt;\u0026thinsp;.05) and suggesting a consistent directional trend.\u003c/p\u003e \u003cp\u003eIn terms of mediation analysis, the relationship between the knowledge-seeking behavior and investment decisions was found to have an insignificant mediation effect due to personal saving orientation (β\u0026thinsp;=\u0026thinsp;0.014, p \u0026gt;\u0026thinsp;.05). However, personal saving orientation positively mediated the relationships between social support (β\u0026thinsp;=\u0026thinsp;0.017, p\u0026lt;.05). and flow (β\u0026thinsp;=\u0026thinsp;0.017, p \u0026lt;\u0026thinsp;.05) with investment decisions. In conclusion, we accepted hypotheses H5 and H6, rejecting H4. The results highlight the significance of personal saving orientation as a mediator in comprehending the impact of socio-psychological factors on investment decision-making.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ-values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSTDEV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et-values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-values\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge -\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDl -\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDl -\u0026gt; Pso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEdu-\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.805\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmp -\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFe-\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.416\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFe -\u0026gt; Pso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender -\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome -\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM.status -\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePso -\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.861\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSs -\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSs -\u0026gt; Pso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of Invetment -\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear of Invetment -\u0026gt; Id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: DL: Desire for Learning, FE: Flow experience, SS: Social Support, PSO: Personal Saving orientation, ID: Investment decision. Edu: Education, M. status: Material Status\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.6. Subgroup Analysis\u003c/h2\u003e \u003cp\u003eSubgroup analyses of participants stratified by gender (male vs female) and educational level (bachelor\u0026rsquo;s degree, diploma, high school, primary school, master's degree) reveal distinct patterns in the interactions between desire for learning, social support, flow experience, personal saving orientation, and investment decisions, with notable variations in statistical significance and effect magnitude. Among the educational subgroups, PhD-level participants were excluded due to a small size (n\u0026thinsp;=\u0026thinsp;12), which falls below the minimum threshold (n\u0026thinsp;\u0026ge;\u0026thinsp;30) for reliable subgroup testing in SmartPLS-4. Detailed gender-specific results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e; for educational-specific results, see Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFor the desire for learning and investment decisions, the relationship shows a significant positive association in males (β\u0026thinsp;=\u0026thinsp;0.166, p\u0026thinsp;=\u0026thinsp;0.002) but is non-significant for females, where the desire for learning does not reliably predict investment decisions. For the desire for learning and personal saving orientation, neither gender exhibits significance (females: p\u0026thinsp;=\u0026thinsp;0.651; males: p\u0026thinsp;=\u0026thinsp;0.074), confirming that desire for learning does not drive personal saving orientation across genders. The flow experience and investment decisions relationship is non-significant for both genders, meaning flow experience does not correlate with investment decisions. In the flow experience and PSO relationship, males exhibit a significant positive association (β\u0026thinsp;=\u0026thinsp;0.161, p\u0026thinsp;=\u0026thinsp;0.001), while the relationship is non-significant for females. The PSO and investment decisions relationship is non-significant for females but shows a significant positive association in males (β\u0026thinsp;=\u0026thinsp;0.181, p\u0026thinsp;=\u0026thinsp;0.001), indicating PSO does not predict investment decisions for females. The Social support and investment decisions relationship yields significant positive associations in both genders (females: β\u0026thinsp;=\u0026thinsp;0.201, p\u0026thinsp;=\u0026thinsp;0.031; males: β\u0026thinsp;=\u0026thinsp;0.211, p\u0026thinsp;=\u0026thinsp;0.000). Finally, the social support and PSO relationship is significant only in males (β\u0026thinsp;=\u0026thinsp;0.151, p\u0026thinsp;=\u0026thinsp;0.000) and non-significant for females.\u003c/p\u003e \u003cp\u003eBy education, the desire for learning and investment decisions shows significant positive associations in diploma (β\u0026thinsp;=\u0026thinsp;0.285, p\u0026thinsp;=\u0026thinsp;0.012) and primary school (β\u0026thinsp;=\u0026thinsp;0.484, p\u0026thinsp;=\u0026thinsp;0.044), while the relationship lacks significance for bachelor, high school, and master\u0026rsquo;s degree participants, where desire for learning does not reliably predict investment decisions. When examining the desire for learning and PSO relationship, significance is limited to high school (β\u0026thinsp;=\u0026thinsp;0.255, p\u0026thinsp;=\u0026thinsp;0.002) and primary school (β\u0026thinsp;=\u0026thinsp;0.266, p\u0026thinsp;=\u0026thinsp;0.033) subgroups, with modest positive effects observed, and non-significant results for bachelor's, diploma, and master\u0026rsquo;s degree participants. Regarding the flow experience and investment decisions relationship, no subgroup exhibits significance, indicating flow experience does not correlate with investment decisions. Within the flow experience and PSO relationship, significant positive associations are evident in bachelor's (β\u0026thinsp;=\u0026thinsp;0.258, p\u0026thinsp;=\u0026thinsp;0.003), diploma (β\u0026thinsp;=\u0026thinsp;0.285, p\u0026thinsp;=\u0026thinsp;0.02), and primary school (β\u0026thinsp;=\u0026thinsp;0.218, p\u0026thinsp;=\u0026thinsp;0.018) participants, while the relationship is non-significant for high school and Master's degree participants. The PSO and investment decisions relationship is non-significant across all education levels, meaning PSO does not predict investment decisions. For the social support and investment decisions relationship, significant positive associations are identified in diploma (β\u0026thinsp;=\u0026thinsp;0.228, p\u0026thinsp;=\u0026thinsp;0.015), high school (β\u0026thinsp;=\u0026thinsp;0.306, p\u0026thinsp;=\u0026thinsp;0.000), and Master's degree (β\u0026thinsp;=\u0026thinsp;0.222, p\u0026thinsp;=\u0026thinsp;0.011) participants, with non-significant results for bachelor's and primary school participants. Finally, the social support and PSO relationship is significant only in the high school subgroup (β\u0026thinsp;=\u0026thinsp;0.173, p\u0026thinsp;=\u0026thinsp;0.004) and not statistically reliable for all other subgroups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGender Subgroup Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOriginal (female)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOriginal (male)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value (female)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value (male)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edl -\u0026gt; id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edl -\u0026gt; pso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efe -\u0026gt; id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efe -\u0026gt; pso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epso -\u0026gt; id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ess -\u0026gt; id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ess -\u0026gt; pso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEducational Level Subgroup Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOriginal Bachelor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOriginal Diploma\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOriginal\u003c/p\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOriginal primary school\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOriginal Master's degree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value Bachelor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value Diploma\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value High school\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep-value primary school\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ep-value Master's degree\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edl -\u0026gt; id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edl -\u0026gt; pso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efe -\u0026gt; id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efe -\u0026gt; pso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epso -\u0026gt; id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSs -\u0026gt; id\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSs -\u0026gt; pso\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Discussion and Implications","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e5.1. Discussion\u003c/h2\u003e \u003cp\u003eThe Current study has thoroughly examined the relationship of psychological, social, and cultural factors in the context of investment behavior. Drawing on the Theory of Planned Behavior, (TPB) we have examined individuals\u0026rsquo; investment behavior in the context of Pakistan. Particularly, the current study emphasized how the desire for learning, flow experience, and social support effects the investment intentions. By embedding psychological constructs with social and cultural dimensions, this study further enlightens existing literature with a more comprehensive approach. Investigating such factors, in market of Pakistan, which has collectivist norms and family influences, provides better understanding of individuals\u0026rsquo; behavior. Such approach contributes to academia because the majority of existing studies are West context oriented, which often emphasize the individualistic investment decisions. Testing such psychological and social constructs in markets like Pakistan captures the realities of investors\u0026rsquo; cognitive behavior. The key significance of this study lies in extending TPB by incorporating motivational and cultural factors, in that way providing deep insights that are essential for policy makers, educators, and fintech firms that are interested in financial engagement in a culturally embedded society.\u003c/p\u003e \u003cp\u003eBuilding on TPB, our study reveals that the individuals\u0026rsquo; psychological and social dimensions are significantly related to their investment intentions. It suggests that the cognitive and social forces directly shape investors\u0026rsquo; financial choices in emerging markets. Moreover, it contributes to the behavioral finance literature by providing empirical evidence of the impact of psychological factors on the decision-making process. Our study shows that individuals' decisions are strongly influenced by their cognitive abilities and social and family support. Such effects are already reported in the literature (Chauhan et al., 2024; Ghouse et al., 2024; Ho et al., 2025; Mishra \u0026amp; Singh, 2024). Thus, our findings suggest that individuals with strong cultural support are emotionally strong through their social connectedness and familial trust, which in turn boost investment confidence and improve risk perception. In the context of Pakistan, it has a collectivist culture; therefore, individuals\u0026rsquo; decisions more often are driven from social validation. Thus, this reaffirms that investors\u0026rsquo; decisions are driven from social assurance.\u003c/p\u003e \u003cp\u003eOur study proposed that individuals\u0026rsquo; flow experience positively affects their investment decisions. However, results indicate that this relationship is insignificant. Number of previous studies have reported flow as a significant influencer of individuals\u0026rsquo; decisions (Aub\u0026eacute; et al., 2014; Feng et al., 2024; S. J. Shi et al., 2024), but our results show that these engagements do not necessarily convert into actual behavior. There are several possible reasons for this inconsistency. Firstly, literature has indicated the dual nature of flow, i.e. hedonic flow and cognitive flow. While hedonic flow depicts emotional enjoyment, the cognitive flow mirrors the focus and perceived control (Landh\u0026auml;u\u0026szlig;er \u0026amp; Keller, 2012; Ozkara et al., 2017). It is arguable that the hedonic element, particularly in uncertain financial markets may dilute behavioral transformations. This in turn can affect individuals\u0026rsquo; cognitive flow because of excessive risk and uncertainty. Moreover, another explanation for this anomaly could be that the psychological mechanisms such as financial trauma and decision discontinuity after losses from markets due volatility can suppress individuals\u0026rsquo; momentum of flow (Adil et al., 2023; Hoffmann et al., 2013). Based on this, it is arguable that market instability might be the reason for insignificance, rather than engagement itself.\u003c/p\u003e \u003cp\u003eSimilarly, results indicated an insignificant mediating role of personal saving behavior for leaning motivation and investment decision, thus rejecting H4. Conceptually, we expected that the desire for learning would foster financial knowledge acquisition which further could translate into improved personal saving behavior and subsequently investment decisions (CHOI et al., 2009). However, our results suggest that in culture embedded societies, the individuals\u0026rsquo; motivations can be overridden by strong social factors (Leigh, 1983). Several studies previously have shown that the behavior of an individual is driven from societal factors like peer influence, societal factors, and social expectations. For instance, (L\u0026ouml;ssbroek \u0026amp; Van Tubergen, 2024) revealed that family expectations significantly affect individuals saving behavior. Similarly, (Putri \u0026amp; Chandra Wijaya, n.d.) found that individual\u0026rsquo;s financial behavior is more peer influenced rather than from individual\u0026rsquo;s cognitions in collectivist societies. Notably, the current study utilized a measurement of desire that captured a general motivational tendency, instead of active financial literacy, that emphasize practical application of financial knowledge. The TPB perspective in this regard suggests that intentions arise from attitudes towards behavior, normative influences, and perceived behavioral control. Thus, learning motivation might enhance saving behavior but due to lack of its alignment with normative and social pressure, they might not translate into actual investment behaviors. Further operationalization of learning motivation that encapsulates the practical attitudes rather than mere desire might result in significance.\u003c/p\u003e \u003cp\u003eOur study also predicted the mediating role of PSO between social support and investment decisions. Our results show that the presence of a strong social environment positively contributes to individuals' saving behavior. This corroborates the study of (Sachdeva \u0026amp; Lehal, 2024), who found that contextual factors influence individuals\u0026rsquo; investment decisions. In particular, our study is in line with the study of (\u0026ldquo;The Influence of Social and Personal Factors in Individual Investment Decision Making,\u0026rdquo; 2022), who found investment decisions and social elements inter-connected in mutual markets. Our findings also correlate with the TPB. For instance, in theory, social support is viewed as a subjective norm which is supposed to spur positive financial behavior that is also consistent to society\u0026rsquo;s expectations. Therefore, when the individuals perceive strong encouragement and support from community members, they prefer to adopt such behaviors that are in accordance with societal values. Whereas number of studies have found culture, particularly in collectivist societies, a pivotal element that encourage saving behavior (Alshebami \u0026amp; Al Marri, 2022; Costa-Font et al., 2018). This saving behavior further motivates individual to invest in available opportunities.\u003c/p\u003e \u003cp\u003eThe supported mediation of PSO between social support and investment decisions reinforces the role of collective influence in shaping financial behaviors. Within the TPB, social support represents subjective norms, which motivate individuals to adopt positive financial orientations consistent with community expectations. When individuals perceive strong encouragement from family, peers, or social networks, they develop disciplined saving habits, which subsequently increase their willingness and ability to invest. Empirical evidence supports this mechanism (Lapner et al., 2023) found that social connectedness and family communication foster saving consistency, while (Pak et al., 2024) showed that social encouragement enhances long-term financial planning through improved saving behavior. Similarly, (K. B. Khan et al., 2024) reported that in collectivist societies, perceived social approval reinforces both financial self-regulation and investment commitment. Accordingly, the present findings indicate that in socially interdependent contexts like Pakistan, social norms enhance investment intentions indirectly by cultivating a strong saving orientation, the behavioral channel through which social support translates into concrete financial action (Ali et al., 2022).\u003c/p\u003e \u003cp\u003eAlthough, the direct relationship between flow and investment intentions was found insignificant; interesting, the relationship was found significant through Personal Saving Behavior. This suggests that the flow alone is not strong enough to transform into investment intentions. The indirect impact of flow through saving behavior suggests that individual\u0026rsquo;s focused cognitive engagement improves their self-discipline and future orientation, which in turn positively affects their investment behavior. This is confirmed by study of (Y. Shi \u0026amp; Qu, 2022) who found that the relationship between students\u0026rsquo; cognitive abilities and academic performance is mediated by self-discipline. Similarly, our findings are in line with the study of (Alshebami \u0026amp; Al Marri, 2022) who found saving behavior as bridge between financial literacy and entrepreneurial intentions. TPB also advocates that individual\u0026rsquo;s attitudinal readiness and behavioral control translate into intentions and behaviors.\u003c/p\u003e \u003cp\u003eCollectively, our findings provide a strong foundation to support the integration of motivational and cultural elements into the TPB. These results highlight the critical role of PSO that bridges the relationship between attitudes, motivations and culture. Further, our study demonstrates that in collectivist culture, saving behavior is valued as a virtue because of moral and social reasons which ultimately shapes the actual financial behavior.\u003c/p\u003e \u003cp\u003eIn collectivist societies like Pakistan, where saving is a socially valued virtue, this mediation pathway becomes even more prominent. Cultural norms emphasizing prudence, family stability, and financial responsibility reinforce saving as a moral and social behavior that precedes investment. Consistent with (Lusardi \u0026amp; Mitchell, 2023), cultures that prioritize saving cultivate long-term planning and investment readiness. Therefore, cognitive flow may enhance psychological control and confidence, but it is through personal saving orientation, shaped by cultural expectations and self-discipline, that these cognitive motivations are ultimately transformed into investment intentions. This reinforces TPB\u0026rsquo;s proposition that perceived behavioral control operates through behavioral regulators like saving, which concretize cognitive motivation into deliberate financial action.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e5.2. Theoretical Implications\u003c/h2\u003e \u003cp\u003eThis study contributes significantly to the literature on investment decisions in several ways. Firstly, we use empirical methods to conduct an in-depth analysis of psychological and social factors, such as how the desire for learning and social support affects investment decisions. Previous studies have extensively researched behavioral, environmental, and demographic factors (Hossain et al., 2024; Liang et al., 2021), there remains a significant gap in addressing the investment process in developing countries. Based on TPB, introducing a psychological understanding of personal saving orientation, we offer a model to explain how a desire for learning and social sport can result in investment behaviors. These factors shape the curiosity of investors, known as the desire for learning, which enhances the professionalism of their investment behavior. An investment strategy supported by strong social networks can improve investors\u0026rsquo; decision-making, providing a more grounded and informed approach. This research provides empirical support for understanding investment behavior within the context of behavioral finance (Research \u0026amp; 2014, n.d.; Rice, 1999). To the best of our knowledge, this study is among the few that examine the mediating role of personal saving orientation in the context of investment decision-making in a developing country. We expand the current understanding of the mechanisms through which psychological factors, such as intrinsic motivations, such as the desire for learning and community assistance, affect saving and investment behaviors. Specifically, we examine how personal saving orientation mediates the relationship between psychological factors and investment decisions. In the (TPB) framework, studies have tended to examine the direct influence of variables like attitudes, subjective norms, and perceived behavioral control on behaviors, with less focus on mediation effects. Some studies (Ajzen, 1991) confirm these factors strongly predict intentions and behaviors, but did not examine mediators like saving orientation. Others have proposed a mediation effect, but focused on attitudes and intentions as mediators (Hasan \u0026amp; Rahman, 2023). However, few studies have explored how psychological motivations, such as the desire for learning and social backing, may mediate investment behaviors through a variable like personal saving orientation.\u003c/p\u003e \u003cp\u003eIn contrast to these studies, our research highlights a mediating role of saving orientation. We argue that inherent psychological motivators, such as the desire for learning and networks, influence investment behaviors indirectly through personal saving orientation, thus extending the TPB framework by incorporating a deeper psychological dimension to investment decision making. Our findings contribute to theory by showing that psychological factors shape investment choices via saving orientation in the context of developing countries where social and cultural factors may have a strong impact on behavior.\u003c/p\u003e \u003cp\u003eThis research contributes to the academic literature by filling gaps in the current understanding and providing practical insights for financial practitioners and policy makers in culturally diverse societies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e5.3. Practicing Implications\u003c/h2\u003e \u003cp\u003eThis study has important policy implications for policymakers and regulators of the stock market, as well as pragmatic recommendations to educators and fintech firms, based on all its empirical findings about the relationships between desire for learning, flow experience, social support, Personal Saving Orientation (PSO), and investment decisions among Pakistan Stock Exchange (PSE) investors. For policymakers, the results confirm that PSO mediates the positive association between social support and investment decisions, while Pakistan\u0026rsquo;s low financial literacy rate (26%, Standard \u0026amp; Poor\u0026rsquo;s Global) limits investors\u0026rsquo; capacity to leverage these factors (S. S. Shah et al., 2024). To address this gap, policymakers should prioritize community-based financial literacy programs that train local Inventors to facilitate peer discussions on saving goals. This recommendation directly builds on the finding that social support strengthens PSO, as such programs could help investors translate social guidance into the saving habits that underpin informed investment choices. Additionally, policymakers should implement regulatory nudges in the form of default saving schemes, for instance, automatic enrollment in low-risk PSE-linked savings accounts with opt-out options as per the published consultation rule book under the Security Act 2015 and Future Market Act 2016. The analysis demonstrates that PSO is a critical driver of investment decisions, reducing friction in saving processes, thus removing barriers to translating PSO into actionable investment behavior, particularly for new investors. policymakers could expand incentive programs for long-term savers. This aligns with the result that PSO exerts its strongest influence on sustained investment behavior, as rewards likely reinforce the consistent saving required for long-term investment success. For educators, the findings reveal that the desire for learning directly predicts investment decisions, unlike flow experience, which requires PSO as a mediator, and that hands-on engagement enhances PSO adoption. Educators, therefore, should redesign financial literacy curricula to explicitly link PSO to long-term investment literacy. For example, modules could integrate real PSE historical data to illustrate how monthly savings compound into stock market returns over 5\u0026ndash;10 years. This addresses the key result that PSO acts as a bridge between psychological factors and investment choices; without explicitly teaching this connection, learners may struggle to apply theoretical knowledge to real-world investment scenarios. Educators should also integrate interactive tools (e.g., PomPak games-initiated by SBP) into workshops to build flow experience alongside PSO. The data shows that flow enhances investment consistency when paired with PSO, and simulators create low-risk environments where learners can practice aligning their saving goals (grounded in PSO) with concrete investment decisions.\u003c/p\u003e \u003cp\u003eFor fintech firms, the results demonstrate that social support and PSO together can improve investment confidence. Fintech firms should incorporate auto-enrollment features into savings-investment tools, for instance, apps like Naypay and Easy paisa could automatically allocate a portion of users\u0026rsquo; income to PSE funds that align with their stated saving goals. This leverages the finding that reduced friction in saving processes strengthens the PSO investment link, as auto-enrollment eliminates barriers associated with manual action. Firms may also add peer-sharing forums within their platforms (e.g., in-app communities for exchanging saving strategies, PSE insights, and goal-tracking updates). The analysis shows that social support directly boosts PSO, so these forums will enable users to learn from peers and maintain consistent saving habits. Finally, firms should develop culturally tailored saving features. This aligns with the study\u0026rsquo;s contextual focus and the result that PSO is more impactful when tied to personal values, which will drive higher feature adoption and sustained user engagement.\u003c/p\u003e \u003c/div\u003e"},{"header":"6. Conclusion, Limitations, and Future Research","content":"\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e6.1. Conclusion\u003c/h2\u003e \u003cp\u003eThis study, grounded in the theory of planned behavior, examines the interaction between the desire for learning, flow experience, social support, and personal saving orientation, influencing investment decisions. Using sample data collected from 516 stakeholders, the findings reveal that learning motivation and social networks significantly influence and strongly impact investment decisions. while flow has no direct effect on investment decisions. Furthermore, the findings indicate that personal saving orientation plays a significant mediating role in the nexus between experience and investment decisions, as well as social support and investment decisions. Interestingly, personal saving orientation plays an insignificant mediating role between the learning motivation and investment. However, the crucial mediating role of personal saving orientation emphasizes its role in linking the learning intention, focused attention, social encouragement, and investment decisions.\u003c/p\u003e \u003cp\u003eThis research contributes both practically and theoretically to our understanding of effectiveness in the modern digital economy. By examining the roles of learning motivation, complete absorption, and social support, we can inform policy and practice to promote ethical investment behaviors. Educational programs and policy frameworks can help integrate these factors into investment decisions.\u003c/p\u003e \u003cp\u003eThis study strengthens the TPB by incorporating psychological influences, offering valuable insights for behavioral finance and guidance policies that encourage ethical investment behaviors across cultures. This research adds to the TBP literature by emphasizing the importance of optimal performance state, learning motivation, and social networks in personal saving and investment. These findings highlight how investors' experience, desire, and support from their social networks enable them to save for future investment.\u003c/p\u003e \u003cp\u003eWhile the research is limited to Pakistan\u0026rsquo;s stock market, future studies should replicate these findings in different countries and cross-cultural settings to better understand how psychological and social factors influence investment decisions. Comparative studies could further explore the role of subjective norms, PBC, and social engagement in shaping investment behavior, thereby contributing to cross-cultural research on TBP. Future researchers could also investigate key determinants of social support, flow experience, and learning intention in cultures, such as those in Europe, where individuals may play a different role in how investors approach saving and investing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e6.2. Limitations and Future Research\u003c/h2\u003e \u003cp\u003eThis research has its limitations that can be addressed through future research. Firstly, the data were gathered from investors trading on the Pakistan Stock Market. To assist in revealing the findings in other countries, future research can consider carrying out similar research in other countries. A comparative study will give a better assessment of the models in other countries. Second, we utilized primary data, and in the future, studies can incorporate secondary trading data to obtain more accurate results. The use of secondary data would reduce social desirability bias and produce more powerful policy implications for stock markets. Third, we analyzed personal saving orientation alone as an intermediary variable in investment decisions. In the future, studies should also explore other variables, such as the influence of social media, risk tolerance, and financial situations. These results would help policymakers to understand investor behavioral patterns to guide the creation of policies and programs that are consistent with cultural heritage and encourage economic growth. Another limitation of this study is the use of convenience sampling, which can limit the applicability of the results. While convenience sampling is an effective approach, it lacks guarantees of a representative sample of the broader population of investors as a whole. For example, it could lead researchers to study easy-to-access subjects rather than a more representative sample. An interesting related limitation is the gender imbalance in our sample (84% male, 16% female). This skew limits external validity in that conclusions about relationships between our key variables (flow experience, social support, personal saving orientation, desire to learn) could overrepresent male perspectives, even with our subgroup analyses. Future studies may use a more representative gender distribution (i.e., 50% male, 50% female or 60% male, 40% female) to detect subtle gender-specific patterns in these variables and increase generalizability to the broader population of Pakistani investors.\u003c/p\u003e \u003cp\u003eFuture research would be well advised to employ random sampling or other more representative forms of sampling to further enhance the external validity of the research. Future studies might also be improved by more precisely measuring financial literacy to detect active engagement in learning and applying financial knowledge, rather than assessing a general intent to learn. This modification may better clarify the relationship between motivation to learn, saving orientation, and investment decisions. Finally, by exploring more profound psychological or social factors and employing newer methods such as machine learning, future studies would better understand the variables influencing investment decisions. It will make long-term measures to shape sensible investors in developing countries more effective and enhance market efficiency.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding and Acknowledgements This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Beijing University of Technology. All procedures were performed in accordance with the ethical standards of this committee and with the 1964 Helsinki Declaration. Written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all participants involved in the study. In line with national regulations and institutional guidelines, written informed consent was not required for this research. Instead, participants completed an online informed consent process. During this process, participants were informed about two key aspects: (i) confidentiality, ensuring that any personal information shared by participants would be kept confidential and not disclosed or published, and (ii) use of data, where it was emphasized that the data collected would only be used for academic research purposes and not for commercial purposes. To proceed with participation, participants had to explicitly acknowledge their understanding and agreement by clicking the \u0026ldquo;agree and continue\u0026rdquo; button, which served as their consent to participate and allowed them to access and complete the questionnaires.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIA: Writing the original draft, formal analysis, validation, writing review, editing, and methodology. TL: Conceptualization, critical insights. IA,TL, AA \u0026amp; MA: Formal analysis, validation, writing review. IA: Editing, project administration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbid, A., \u0026amp; Jie, S. (2023). 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Family or otherwise: Exploring the impact of family motivation on job outcomes in collectivistic society. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e. https://doi.org/10.3389/fpsyg.2023.889913\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-digital-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Digital Management](https://link.springer.com/journal/44362)","snPcode":"44362","submissionUrl":"https://submission.springernature.com/new-submission/44362/3","title":"Journal of Digital Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Personal saving orientation, learning attitude, social support, flow experience, investment decisions","lastPublishedDoi":"10.21203/rs.3.rs-8782383/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8782383/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIndividuals\u0026rsquo; economic conditions are always under the influence of psychological factors that are more prominent in unpredictable economic conditions, yet the impact of several key elements remains underexplored. Keeping in view the importance of psychological factors, our study examined the mediating role of Personal Saving Orientation (PSO) between psychological factors\u0026mdash;desire for learning, flow experience, and social support, and investment decisions. This study analyzed the roles of flow experience, social support, and desire for learning in shaping investment decisions in the context of the collectivist culture of Pakistan. Our study is grounded in the Theory of Planned Behavior (TPB) and collected data from 516 investors. Our analysis using the PLS-SEM technique shows that the Knowledge-seeking behavior and social support play a significant role in shaping investment decisions. However, flow experience did not have a significant effect. Moreover, the personal saving orientation acts as an intermediary variable that strongly influences the relationships of experience and support on investment decisions, except for knowledge-seeking behavior. These results enable investors to understand the influence of social behavior and psychological elements on investing choices and provide a mechanistic description of the mediating impact of personal saving orientation on this outcome. Further implications for practice are discussed.\u003c/p\u003e","manuscriptTitle":"Exploring Personal Saving Orientation’s Influence On Investment Decision-Making","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-02 16:46:01","doi":"10.21203/rs.3.rs-8782383/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-31T08:20:32+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-13T06:38:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-11T06:48:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188136989833548107094913060633213567685","date":"2026-03-07T13:52:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"83002132865025236831341758397066674445","date":"2026-03-03T16:08:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42874981755608833280154607868002368186","date":"2026-03-03T08:28:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"134998568506407800952042003740072444236","date":"2026-02-26T06:56:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173072154858200057254063280295176333210","date":"2026-02-26T06:27:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"21995565187000394359052456438581610931","date":"2026-02-26T06:23:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-26T06:18:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-09T09:33:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-09T09:25:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Digital Management","date":"2026-02-04T05:41:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-digital-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Digital Management](https://link.springer.com/journal/44362)","snPcode":"44362","submissionUrl":"https://submission.springernature.com/new-submission/44362/3","title":"Journal of Digital Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b7e9c3ef-d481-45cf-b63d-605570e568d2","owner":[],"postedDate":"March 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-27T08:53:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-02 16:46:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8782383","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8782383","identity":"rs-8782383","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}