Psychological traits and loan repayment behaviors among microfinance borrowers in Tanzania

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Using the Theory of Planned Behavior (TPB), these traits are conceptualized as determinants of repayment intention and behavior. Data were collected through a structured survey in three major Tanzanian cities and analyzed with structural equation modelling (SEM). Results indicate that optimism negatively and significantly affects repayment behavior, while self-control and deliberative thinking have positive and significant effects. The findings extend TPB by demonstrating the predictive role of psychological traits in financial behavior and emphasize their importance in assessing credit risk. Practically, the study recommends integrating behavioral screening and into microfinance services. At the policy level, it highlights the need for psychologically informed lending practices to strengthen repayment performance and guarantee the financial sustainability of microfinance institutions. Figures Figure 1 1. Introduction Microfinance institutions (MFIs) were established to bridge the financial inclusion gap by providing capital to low-income communities, with the aim of supporting small-scale business activities, and reducing poverty (Kasoga, 2020 ). MFIs assist individuals excluded from formal financial systems due to limited credit histories, and lack of collateral (Bhawe & Jha, 2025 ). MFIs have contributed significantly to the economic growth of developing countries such as Tanzania; however, loan repayment remains a main challenge (Endris, 2022 ; Tegambwage & Kasoga, 2022 ). Studies have indicated that high default rates threaten the sustainability and outreach of MFIs, which in turn undermine efforts toward achieving financial inclusion (Mishra & Choudhury, 2025 ; Lahnech & Chami, 2025 ; Tegambwage & Kasoga, 2025 ). Historically, socioeconomic, institutional, and demographic determinants such as income levels, asset ownership, education level, household size, gender, marital status, household income, financial literacy, business experience, credit history, loan size, lending model, and interest rate have been the main focus of the literature on loan repayment (Endris, 2022 ; Endris & Kassegn, 2022 ; Garomsa, 2017 ; Jote, 2018 ; Yibrie & Ramakrishna, 2017 ). While these factors offer insights into how external factors influence repayment behavior; they do not capture the internal, psychological dimensions that underlie financial decision-making and behavior. Recently, there has been growing acknowledgement that individual psychological traits play a vital role in building financial behaviors (Kasoga & Tegambwage, 2022b ; Kimball & Shumway, 2009 ; Peng & Ismail, 2025 ; Sekścińska et al., 2021 ; Strömbäck et al., 2017 ; Tegambwage & Kasoga, 2024 ). In particular, psychological constructs like self-control, optimism, and deliberative thinking are increasing associated with prudent credit use and sound financial management (Sekścińska et al., 2021 ; Strömbäck et al., 2017 ). Accordingly, this study expects psychological traits to influence borrowers’ loan repayment behavior. Self-control, for instance, reflects an individual’s capacity to regulate desires and delay satisfaction (Tegambwage & Kasoga, 2022 ; Strömbäck et al., 2017 ), which may boost loan repayment intentions behavior. Optimism trait is an expectancy for positive outcomes (Puri & Robinson, 2007 ), may enhance borrowers’ confidence in their future financial capacity, thereby influencing repayment intentions behavior. Deliberative thinking, the tendency to engage in thoughtful and analytical decision-making (Moxley et al., 2012 ), can further support prudent financial behavior by enabling individuals to foresee long-term consequences and balance financial commitments against conflicting needs. Despite their theoretical importance, these psychological traits have not been integrated into loan repayment behavior within the microfinance context. The present study addresses this gap by employing the theory of planned behavior (TPB) by Ajzen, ( 1991 ). The TPB posits that attitudes, subjective norms, and perceived behavioral control shape behavioral intentions, which in turn influence actual behavior. This study specifically examines the extent to which psychological traits influence borrowers’ loan repayment behavior. Understanding the way psychological traits enhance loan repayment behavior is important to fill the knowledge gap, and developing strategies for improving loan repayment behavior. The findings inform the policy makers and MFIs on the interventions required to improve loan repayment behavior that account for borrowers’ psychological characteristics. The remainder of the paper is structured as follows. Section 2 reviews the relevant literature to develop the study’s hypotheses. Section 3 outlines the research methodology, while Sections 4 and 5 present and discuss the findings, respectively. Section 6 provides the study’s conclusions and implications, and Section 7 offers suggestions for future research. 2. Literature review 2.1 Theoretical framework This study use the Theory of Planned Behavior (Ajzen, 1991 ) to explain how psychological characteristics can enhance loan repayment behavior. According to TPB, three key factors - attitudes toward the behavior, subjective norms, and perceived behavioral control influence behavioral intentions, which in turn lead to actual behavior. According to the TPB, these factors capture the cognitive and motivational components that drive individuals to act in particular ways. Specifically, self-control is regarded as a trait that strengthens perceived behavioral control, enhancing an individual’s confidence to perform the behavior (Baumeister et al., 2007 ). Based on the TPB, this study expects that borrowers with high self-control are more likely to manage their spending, adhere to repayment plans, and avoid imprudent financial decisions, thereby increasing the likelihood of repaying their loans on time. Deliberative thinking is characterized by a rational and reflective cognitive way (Baumeister et al., 2007 ), which aligns closely with the attitudinal component of TPB. Borrowers with strong deliberative thinking are likely to form thoughtful and reasoned assessments of the benefits and consequences of loan repayment. These assessments contribute to the development of positive attitudes toward fulfilling financial obligations, thus strengthening the intention to repay. Optimistic individuals tend to expect positive outcomes and believe in their capacity to achieve financial success (Kasoga & Tegambwage, 2022b ). Based on the TPB, this study expects optimism to influence repayment intention behavior. The use of TPB in this study is relevant to Tanzania, where microfinance services are crucial for the poor, who are excluded by traditional financial institutions due to lack of collateral and low financial literacy (Kasoga & Tegambwage, 2022a ). By integrating psychological traits within the TPB framework, this study explores how borrowers’ internal and cognitive tendencies inform loan repayment behavior Thus, TPB not only supports the theoretical framework of this study, but also enhances its practical relevance by identifying cognitive and motivational factors that may be targeted to improve loan repayment outcomes. 2.2 Empirical review and hypothesis development This section presents the empirical review and hypotheses development. 2.2.1 Self-control and loan repayment behavior Self-control is the ability to manage one’s thoughts, feelings, and actions in order to achieve long-term objectives (He et al., 2023 ). In the context of loan repayment and based on TPB, this study contends that people with strong self-control are more likely to prioritize financial responsibilities, successfully manage their money, and withstand temporary temptations, all of which increase the likelihood that they would repay their loans. As per self-regulation theory (Baumeister & Vohs, 2007 ), self-control facilitates goal-directed behavior, which is essential for financial discipline. Prior research revealed a positive correlation between sound financial behavior and self-control. (Kasoga & Tegambwage, 2022b ; Kimball & Shumway, 2009 ; Peng & Ismail, 2025 ; Sekścińska et al., 2021 ; Strömbäck et al., 2017 ). Other previous studies found over-indebted borrowers exhibiting unfavorable financial behaviors like unnecessary borrowing, poor investment decisions, irresponsible spending, and poor saving habits due to low self-control (Kasoga & Tegambwage, 2021 ). Likewise, Gathergood ( 2012 ) stated that those who lack self-control are more prone to incur unanticipated costs, which could have a detrimental impact on their capacity to repay loans. In the Tanzanian context, where borrowers often face competing demands from family and social networks (Tegambwage & Kasoga, 2025 ), self-control enables individuals to stay committed to repayment schedules despite financial pressures. Additionally, the trait is consistent with the TPB’s perceived behavioral control construct, suggesting that borrowers are more likely to act responsibly when repaying debt if they think they can control their impulses. Accordingly, based on the explanation above, the study proposes the following hypothesis: H1. Self-control is positively and significantly associated with loan repayment behavior among microfinance borrowers in Tanzania. 2.2.2 Optimism and loan repayment behavior Optimism is the broad belief that positive things will occur in the future (Peterson, 2000 ). Based on the TPB (Ajzen, 1991 ), this study argues that optimism contributes to the formation of favorable attitudes toward behavior, influencing the intention to perform actions like loan repayment. Optimistic individuals tend to believe in their capacity to overcome obstacles and succeed, making them more likely to follow through on their financial commitments (Duque et al., 2025 ). Empirical studies (e.g., Hirvonen, 2018 ; Kasoga & Tegambwage, 2022b ; Khan et al., 2017 ; Mawad, 2022 ; Strömbäck et al., 2017 ) reinforce this connection, showing that optimism influences positive financial behaviors. Mohammad et al. ( 2025 ) found that pessimistic investors tend to exhibit unfavorable financial behaviors in terms of poor borrowing, investing, spending and saving decisions, which may lead to poor loan repayment behavior. In environments like Tanzania, where economic challenges and uncertainty are prevalent among the poor, optimism can serve as a psychological buffer, helping borrowers maintain positive expectations and persevere in repaying their loans even during periods of hardship. Consequently, the research hypothesizes that: H2. Optimism is positively and significantly related to loan repayment behavior among microfinance customers in Tanzania. 2.2.3 Deliberative thinking and loan repayment behavior Deliberative thinking is characterized by analytical, conscious, and forward-looking decision-making (Moxley et al., 2012 ). In other words, it is the capacity to deliberate and make thoughtful decisions. Within the TPB framework Ajzen ( 1991 ), deliberative thinking enhances the intention-behavior by enabling individuals to form well-considered attitudes and assess the feasibility of repayment actions. Such cognitive competence helps borrowers make informed borrowing decisions, develop repayment plans, and avoid impulsive financial behavior. Empirical research provides support for this link. Dhar and Gorlin ( 2013 ) showed that individuals with a deliberative thinking style demonstrated more prudent financial decision-making. Hashmi et al. ( 2021 ) found that prudent financial behaviors like investing and saving are positively related with deliberative thinking, which may lead to good loan repayment performance. Kasoga & Tegambwage ( 2022b ) discovered that investors make bad investing choices, employ a lot of heuristics, and only partially participate in deliberative thought. In the Tanzanian context, where formal financial education is limited among microfinance customers, deliberative thinking may enable borrowers to critically evaluate loan terms, forecast future cashflows, and make calculated repayment decisions, enhancing loan repayment behavior. Hence, the following hypothesis is suggested: H3. Deliberative thinking is positively and significantly related to loan repayment behavior among MFI customers in Tanzania. 3. Research Methodology 3.1 Research design and instrument This study used explanatory research design to explain how psychological traits- self-control, deliberative thinking, and optimism influence loan repayment behavior. This design assists in explaining the causal relationships among the variables. The Existing, experimentally verified items were used to optimize the constructs’ validity and reliability. The psychological trait items were sourced from Kasoga and Tegambwage ( 2022b ) and adapted to the microfinance context. Validated scales for loan repayment behavior were adapted from Tegambwage and Kasoga ( 2022 ). The generated questionnaire was pre-tested among 40 MFI customers before conducted the final survey, in order to evaluate the validity and reliability of the items as well as the wording of the questions. A five-point Likert-type scale, with 1 denoting “strongly disagree” and 5 denoting “strongly agree,” was used to probe all issues except the demographic questions. 3.2 Ethical compliance and consent procedures Before taking part in the study, all participants received an information sheet explaining the purpose, procedures, and intended use of the data. They were assured that their responses would remain confidential and anonymous. Written informed consent was secured from each respondent prior to data collection. The study did not involve human experiments or the use of biological samples; however, it complied fully with established ethical research principles and was approved by the Institutional Research Review Ethical Committee of the University of Dodoma, Tanzania. All research activities were conducted in line with relevant ethical guidelines. To safeguard participants, strict measures were observed to ensure voluntary participation, protect confidentiality and anonymity, and respect the right to withdraw from the study at any point without consequences. Every precaution was taken to preserve the privacy, dignity, and rights of those involved. 3.3 Study population, data-collection procedure, and sample characteristics The study’s population consisted of all MFIs borrowers in the three main Tanzanian cities of Dodoma, Mwanza, and Dar es Salaam. The majority of Tanzania’s MFIs borrowers reside in these cities (Kasoga, 2020 ; Rwamuhuru & Tegambwage, 2021 ). Research assistants used a methodical sampling technique to approach MFIs borrowers as they were leaving the MFIs. A questionnaire was supplied to borrowers who consented to participate. Nine hundred (900) surveys were gathered and examined. Respondents were asked to keep their answers secret and were given the assurance that they would be kept completely confidential. Table 1 displays sample characteristics. The finding show that the majority of MFIs borrowers in Tanzania are women (Kasoga & Tegambwage, 2022a ; Tegambwage, 2025 ), who comprise 58.1% of the respondents. Respondents ranged in age from 18 to 50, with the majority (51.3%) lying between the ages of 31 and 40. The majority of respondents (69.9%) were married and 35.4% had finished their elementary schooling. Table 1 Demographic Characteristics Variable Description Frequency Percent Gender Male 377 41.9 Female 523 58.1 Age 18–30 117 13.0 31–40 462 51.3 41–50 321 35.7 Education Primary 319 35.4 Secondary 273 30.3 Tertiary 174 19.3 University 134 15.0 Marital status Single 183 20.3 Married 629 69.9 Divorced 88 9.8 3.3 Data analysis The measurement and structural models were evaluated using structural equation modelling (SEM). SEM makes it possible to evaluate numerous construct correlations at once and gauge the model’s overall robustness (Anderson & Gerbing, 1988 ). 4. Results 4.1 Measurement model A rotating component matrix served as the basis for the factor analysis (Anderson & Gerbing, 1988 ). To ascertain whether the sample size was adequate for factor analysis, the data was subjected to the Keiser-Meyer-Olkin (KMO) and Bartlett tests. The findings demonstrate that the sample size was enough for factor analysis because the KMO value was 0.612 (Table 2 ), above the suggested value of 0.5 (Sarstedt et al., 2019 ). Furthermore, a significant (p < 0.001) Bartlett's test of sphericity was used to demonstrate the adequacy of the sample size (Hair Jr et al., 2019 ). Hair Jr et al. ( 2019 ) state that factor analysis, when KMO and Bartlett tests are computed, can yield distinct and dependable factors. Factor loadings with a weight larger than 0.5 and Cronbach's alpha coefficients (α), which are higher than the recommended threshold of 0.7, attest to the measures' reliability (Sarstedt et al., 2023 ), as shown in Table 2 . Convergent validity was confirmed by statistically significant (p < .001) of all factor loadings for indicators assessing the same construct (Anderson and Gerbing, 1988 ). Correlations between the constructs and the extracted square root of their average variance (AVE) were used to establish discriminant validity (Anderson & Gerbing, 1988 ). Discriminant validity was confirmed where by the square root of AVE for each construct was greater than the correlations between them (Table 4 ) (Anderson & Gerbing, 1988 ). Estimated pair-wise correlations between the components, which were significantly less than one and did not exceed 0.85, provided support for this (Sarstedt et al., 2023 ). Potential common method variance was reduced by using pre-existing measures and ensuring respondents’ anonymity (Podsakoff et al., 2003 ). Furthermore, Table 4 demonstrates that there were no exceptionally significant correlations (r > 0.80) among the constructs, suggesting that our results were not seriously jeopardized by common method bias(Podsakoff et al., 2003 ). The variance inflation factor (VIF) for each construct (Table 6 ) were below the conventional cut-off value of 5 (Hair Jr et al., 2019 ), suggesting that there is no multicollinearity between the explanatory measurement constructs. Table 2 CFA results bad Construct Item label Item description Factor Loading T-value Self-control (SEC) α = 0.798; AVE = 0.784 SEC1 I find it difficult to break harmful habits. 0.783 122.861*** SEC2 I get distracted easily. 0.950 197.247*** SEC3 I can withstand temptation well. 0.788 81.363*** SEC4 I make decisions that I subsequently regret even if they feel nice at the time. 0.702 112.830*** SEC5 I frequently take action without considering all of my options. 0.886 237.574*** Optimism (OPT) α = 0.837; AVE = 0.831 OPT1 I usually hope for the best when things are unclear. 0.702 89.303*** OPT2 If there's anything that might go wrong with me, it will. 0.808 151.672*** OPT3 I always have hope for the future. 0.896 87.158*** OPT4 I almost never hope for the best. 0.761 58.536*** OPT5 I seldom ever rely on favorable circumstances to come my way. 0.618 60.089*** Deliberative thinking (DET) α = 0.858; AVE = 0.818 DET1 Creating a well-defined strategy is crucial to me. 0.822 174.316*** DET2 I enjoy problem-solving. 0.824 205.808*** Loan repayment behavior (LRB) α = 0.736; AVE = 0.768 LRB1 I always make full loan repayment as agreed with MFI. 0.729 286.361*** LRB2 I have never missed a scheduled loan repayment. 0.727 269.850*** LRB3 I keep track of my repayment schedule and stay on track. 0.719 283.604*** KMO 0.612 Bartlett’s Test of Sphericity 158.886*** 4.2 Descriptive statistics and correlations between the constructs Borrowers reported high loan repayment behaviors (M = 4.46), supported by strong self-control (M = 3.89) and deliberative thinking (M = 4.11) (Table 3 ), indicating disciplined and thoughtful financial behaviors. However, optimism was relatively low (M = 2.96), suggesting limited confidence in future financial prospects. This pattern implies that repayment is driven more by self-regulation and careful planning than by positive expectations. Drawing on TPB, high perceived control and deliberate decision-making may compensate for lower optimism, sustaining favorable repayment behaviors despite modest future outlook. All constructs have modest standard deviations in relation to their mean values, suggesting that the statistical means fit the observed data well (Field, 2024 ). The recommended ranges for skewness and kurtosis values are met (Matore & Khairani, 2020 ). Specifically, Table 3 's values of skewness and kurtosis, which are neither less than − 1 nor larger than + 1 nor less than − 2 nor more than + 2, respectively, show that there is no cause for alarm over the sample's non-normal distribution. Table 3 Descriptive statistics Constructs Min Max Mean SD Skewness Kurtosis Self-control 3.00 4.80 3.89 0.401 -0.084 0.215 Optimism 1.60 3.60 2.96 0.560 -0.638 -0.319 Deliberative thinking 2.50 5.00 4.11 0.541 -0.939 1.060 Loan repayment behavior 4.00 5.00 4.46 0.317 0.320 -0.816 A Pearson correlation analysis was done to see if there were any linear relationships between the constructs (Field, 2024 ). The results in Table 4 show that there is a positive and significant association between loan repayment behavior and self-control (r = 0.259, p < 0.001), and between loan repayment behavior and deliberative thinking (r = 0.132, p < 0.001). However, the association between repayment behavior and optimism was found to be negative and significant (r = -0.468, p < 0.001). The results suggest that unfavorable loan repayment behaviors are more common with borrowers who are more optimistic, having little self-control, and low deliberative thinking. These findings underscore the importance of complementing microfinance services with behavioral interventions that strengthen self-regulation and decision-making skills, especially in low-resource settings like Tanzania. It is important to acknowledge that the correlation analysis result provides an initial indication of the validity of the study’s hypothesis. Consequently, more investigation (path analysis) is done to validate the study’s premise. Table 4 Correlations analysis results Constructs SEC OPT DET LRE Self-control (SEC) 0.885 Optimism (OPT) -0.230*** 0.912 Deliberative thinking (DET) -0.250*** -0.167*** 0.904 Loan repayment behavior (LRB) 0.259*** -0.468*** 0.132*** 0.876 Notes: Diagonal elements are the square root of AVE between the constructs and their measures. The off-diagonal elements are correlations between the constructs. ***p < 0.001. 4.3 Structural model and testing the hypothesis By using SEM, the hypothesized associations' validity was confirmed. The goodness-of-fit indices were analyzed and found to be well within the recommended ranges (Table 5 ), indicating that the structural model provided an adequate fit to the data (Hair & Alamer, 2022 ). Table 5 Model fit indices CMIN RMR GFI AGFI NFI RFI IFI TLI CFI RMSEA PCLOSE 10.040, df 5, p = 0.074; CMIN/df = 2.008 0.007 0.997 0.980 0.998 0.987 0.999 0.994 0.999 0.033 0.790 Notes: χ 2 , chi-square; df, degrees of freedom RMR, root mean square residual; GFI, the goodness of fit index; AGFI, adjusted goodness of fit index; NFI, normed fit index; RFI, relative fit index; IFI, incremental fit index; TLI, Tucker–Lewis’s index; CFI, comparative fit index; RMSEA, root mean square error of approximation; PCLOSE, parsimony close. By analyzing the connections between the constructs using the path coefficients, the study hypotheses were put to the test. According to the results in Table 6 and Fig. 1 , loan repayment behaviors are influenced by psychological traits. Specifically, the results show that self-control (β = 0.007, p < 0.001) and deliberative thinking (β = 0.211, p < 0.001) have positive and significant effects on loan repayment behavior. However, contrary to expectations, optimism exhibited a negative and significant effect on repayment behavior (β = -0.255, p < 0.001). Table 6 Hypothesis testing results Regression path Path coefficient S.E. C.R. P VIF Loan repayment behavior (LRB) <--- Self-control 0.007 0.027 0.264 *** 1.160 Loan repayment behavior (LRB) <--- Optimism -0.255 0.014 -17.701 *** 1.119 Loan repayment behavior (LRB) <--- Deliberative thinking 0.211 0.017 12.141 *** 1.131 Loan repayment behavior (LRB) <--- Age -0.161 0.023 -6.899 0.792 Loan repayment behavior (LRB) <--- Gender -0.352 0.033 -10.610 0.081 Loan repayment behavior (LRB) <--- Education 0.204 0.019 10.969 *** Loan repayment (LRB) <--- Marital status 0.324 0.022 15.043 *** Adjusted R 2 = 0.512; F = 135.493*** Notes: BL stands for borrower’s loyalty. LO stands for loan officer. MFI stands for microfinance institution. ***p 0.05) and gender (β = -0.352, p > 0.05) do not significantly affect loan repayment behavior (Table 6 and Fig. 1 ). Nonetheless, there are notable impacts on repayment behavior due to marital status (β = 0.324, p < 0.001) and educational status (β = 0.204, p < 0.001). This implies that, despite these sociodemographic variables, the impact of psychological traits on loan repayment behavior is still significant. 5. Discussion The findings of this study offer insight into how psychological traits influence loan repayment behavior in the Tanzanian microfinance context. Based on the TPB (Ajzen, 1991 ), the findings confirm that self-control and deliberative thinking enhance borrowers’ loan repayment behavior, whereas optimism was found to be negatively associated with loan repayment behavior. Specifically, self-control positively and significantly influenced repayment behavior (Table 6 ). This aligns with TPB’s concept of perceived behavioral control, which reflects an individual’s ability to perform a certain behavior. Borrowers with high self-control are able to delay satisfaction, resist imprudent spending, and maintain discipline in loan consumption, leading to good repayment behavior. These results are supported by Kimball and Shumway ( 2009 ), Peng and Ismail ( 2025 ), Sekścińska et al. ( 2021 ), Strömbäck et al. ( 2017 ), who found that self-control is a key predictor of financial behavior in developing economies. In the Tanzanian setting, where financial stress and social demands are common among MFI clients (Kasoga and Tegambwage 2022b ), high self-control enables borrowers to pass through the competing priorities without defaulting. Deliberative thinking was also positively and significantly associated with loan repayment behavior (Table 6 ). This aligns with the attitude toward the intentions and behavior in the TPB. This finding is in line with the conceptualization of this study that borrowers with deliberative thinking attitude are more likely to engage in analytical thinking, carefully consider loan terms, plan for contingencies, and budget effectively. This finding is consistent with Dhar and Gorlin ( 2013 ), Hashmi et al. ( 2021 ), and Kasoga and Tegambwage ( 2022b ) who demonstrated that individuals with deliberative cognitive engage in prudent financial decisions. Considering the fact that most of low income people in Tanzania have low financial literacy, and operate in informal business environment (Rwamuhuru et al., 2023 ; Ringo et al., 2023 ), deliberative thinking is important cognitive asset for compensating limited financial literacy. Contrary to expectations, optimism show a negative and significant effect on loan repayment behavior (Table 6 ). While optimism typically enhances attitudes toward behavior in TPB, excessive or unrealistic optimism can lead to overconfidence, underestimation of risk, or poor financial planning (Puri and Robinson, 2007 ). Optimistic borrowers may overestimate future income or the success of business, leading to over-borrowing or less urgency when it comes to repayments. This aligns with (Coelho, 2010 ), who cautioned that extreme optimism can undermine financial responsibility. This finding suggests that in the Tanzanian context, where economic shocks and uncertainty are frequent (Kasoga & Tegambwage, 2024 ), high optimism may be dangerous. 6. Conclusion and implications This study examined the effect of psychological traits on loan repayment behaviors of MFI customers in Tanzania. The findings reveal that psychological traits significantly influence loan repayment behavior among MFI clients in Tanzania. Specifically, self-control and deliberative thinking positively influence loan repayment behavior, supporting TPB’s that behavioral intention, control and, good attitude are key drivers of actual behavior. However, extreme optimism, was found to affect negatively repayment behaviors, due to overconfidence and misjudgment of financial risks. These findings highlight the importance of psychological traits in financial decision-making and behavior. The findings contribute to the TPB by linking psychological traits namely, self-control, deliberative thinking, and optimism to the loan repayment behaviors in microfinance contexts. Practically, this study informs the MFIs to consider psychological traits in screening to identify which trait is important in explaining repayment behavior. The finding of this study suggests the importance of financial knowledge to address the risks of extreme optimism, which actually affects negatively loan repayment behavior. To policy makers, the findings of this study suggest the importance of adopting psychological traits such as self-control and deliberative thinking in their strategies in informing lending procedures, and repayment behavior. These traits can assist in identifying borrowers who are at the risk of defaulting. 7. Recommendations for future research This study has limitations, just like any other studies. First, because of its cross-sectional design, it was not possible to establish changes over time. Future studies should use longitudinal designs to establish changes over time, and investigate moderating factors such economic shocks, social norms, financial literacy, and trust in MFIs. Second, the study was conducted in Tanzania, and among MFIs borrowers, the results might not apply to other cultural settings. Future studies should be conducted in other contexts to enhance generalizability of the findings. Declarations Ethical Approval This study was reviewed and approved by the Institutional Research Review Ethical Committee of the University of Dodoma, Tanzania. The study complied with all established ethical research standards. The committee approval number (for animal and human studies) is not applicable. Clinical Trial Number: Not applicable Consent to Participate All participants were provided with detailed information regarding the study’s objectives, procedures, and the intended use of the data. Written informed consent was obtained from every participant prior to data collection. Participation was voluntary, and participants were free to withdraw at any stage without consequences. Consent to Publish Participants were assured that all data would remain confidential and anonymous. As such, consent to publish anonymized data and findings derived from the study was obtained. No identifiable information is included in this manuscript. Availability of data and materials: Available upon request. Competing interests The authors declare no competing interests. Funding: The study was funded by the University of Dodoma through the Benjamin William Mkapa Research Grants, under the category of Senior Academic Staff. Authorship statement The corresponding author affirms that all listed authors have reviewed the manuscript, approved its final version, and agreed to be accountable for their respective contributions. Furthermore, the authors confirm that the submission complies with the journal’s policies on authorship and author responsibilities. Acknowledgement We would like to sincerely acknowledge the University of Dodoma through the Benjamin William Mkapa Research Grants, under the category of Senior Academic Staff, for providing the financial support that made this study possible. 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Journal of Human Behavior in the Social Environment , 1–26. Mohammad, S. J., Sial, M. S., Jo, H., & Comite, U. (2025). Assessing the impact of emotion on investors’ behavior and decision-making. Review of Behavioral Finance . Moxley, J. H., Ericsson, K. A., Charness, N., & Krampe, R. T. (2012). The role of intuition and deliberative thinking in experts’ superior tactical decision-making. Cognition , 124 (1), 72–78. Peng, C. S., & Ismail, S. (2025). Assessment of Investment Intention Based on Financial Literacy, Personality Traits, Behavioral Biases, Investor Traits and Financial Self-Efficacy. 12th International Conference on Business, Accounting, Finance and Economics (BAFE 2024) , 294–308. Peterson, C. (2000). The future of optimism. American Psychologist , 55 (1), 44. Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology , 88 (5), 879. Puri, M., & Robinson, D. T. (2007). Optimism and economic choice. Journal of Financial Economics , 86 (1), 71–99. Ringo, D. S., Kazungu, I., & Tegambwage, A. (2023). The multidimensional implications of entrepreneurial orientation on export performance: empirical evidence from manufacturing SMEs in Tanzania. European Journal of Management Studies , 28 (1), 69–87. Rwamuhuru, M. A., Magai, P. S., & Tegambwage, A. G. (2023). Social business environment and transnational corporations’ loyalty: the executives’ perceptions in Tanzania. African Business Management Journal , 1 (1), 16–28. Rwamuhuru, M. A., & Tegambwage, A. G. (2021). Commercialization of innovations in Tanzania: An empirical investigation. In Handbook of research on nurturing industrial economy for Africa’s development (pp. 99–121). IGI Global. Sarstedt, M., Hair Jr, J. F., Cheah, J.-H., Becker, J.-M., & Ringle, C. M. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian Marketing Journal , 27 (3), 197–211. Sarstedt, M., Hair Jr, J. F., & Ringle, C. M. (2023). “PLS-SEM: indeed a silver bullet”–retrospective observations and recent advances. Journal of Marketing Theory and Practice , 31 (3), 261–275. Sekścińska, K., Rudzinska‐Wojciechowska, J., & Jaworska, D. (2021). Self‐control and investment choices. Journal of Behavioral Decision Making , 34 (5), 691–705. Strömbäck, C., Lind, T., Skagerlund, K., Västfjäll, D., & Tinghög, G. (2017). Does self-control predict financial behavior and financial well-being? Journal of Behavioral and Experimental Finance , 14 , 30–38. Tegambwage, A. G. (2025). Multilevel relationships and loyalty in the microfinance industry: evidence from Tanzania. Journal of Business and Socio-Economic Development , 5 (1), 71–83. Tegambwage, A. G., & Kasoga, P. S. (2022). Loan repayment among group borrowers in Tanzania: the role of relationship quality. Future Business Journal , 8 (1), 37. Tegambwage, A. G., & Kasoga, P. S. (2024). Relationship quality and customer loyalty in the Tanzanian microfinance sector. Journal of Financial Services Marketing , 29 (1), 138–153. Tegambwage, A. G., & Kasoga, P. S. (2025). The role of individual dimensions of business relationship quality and business customer value in building loyalty in microfinance. Journal of Innovation and Entrepreneurship , 14 (1), 1–19. Yibrie, O., & Ramakrishna, R. (2017). Determinants of loan repayment performance in ACSI. International Journal of Advanced Research in Management and Social Sciences , 6 (4), 151–169. Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":275586,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAMOS picture with path coefficients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7641542/v1/b35ebf261e23cd457e3985d2.png"},{"id":94095140,"identity":"957f87e0-0bc3-4205-9aba-c69a48b721d1","added_by":"auto","created_at":"2025-10-22 09:45:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1328612,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7641542/v1/97c04792-a6af-4c67-85e8-024092b1a3f3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Psychological traits and loan repayment behaviors among microfinance borrowers in Tanzania","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMicrofinance institutions (MFIs) were established to bridge the financial inclusion gap by providing capital to low-income communities, with the aim of supporting small-scale business activities, and reducing poverty (Kasoga, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). MFIs assist individuals excluded from formal financial systems due to limited credit histories, and lack of collateral (Bhawe \u0026amp; Jha, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). MFIs have contributed significantly to the economic growth of developing countries such as Tanzania; however, loan repayment remains a main challenge (Endris, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tegambwage \u0026amp; Kasoga, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Studies have indicated that high default rates threaten the sustainability and outreach of MFIs, which in turn undermine efforts toward achieving financial inclusion (Mishra \u0026amp; Choudhury, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Lahnech \u0026amp; Chami, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Tegambwage \u0026amp; Kasoga, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHistorically, socioeconomic, institutional, and demographic determinants such as income levels, asset ownership, education level, household size, gender, marital status, household income, financial literacy, business experience, credit history, loan size, lending model, and interest rate have been the main focus of the literature on loan repayment (Endris, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Endris \u0026amp; Kassegn, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Garomsa, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Jote, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yibrie \u0026amp; Ramakrishna, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). While these factors offer insights into how external factors influence repayment behavior; they do not capture the internal, psychological dimensions that underlie financial decision-making and behavior. Recently, there has been growing acknowledgement that individual psychological traits play a vital role in building financial behaviors (Kasoga \u0026amp; Tegambwage, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e; Kimball \u0026amp; Shumway, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Peng \u0026amp; Ismail, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Sekścińska et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Str\u0026ouml;mb\u0026auml;ck et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Tegambwage \u0026amp; Kasoga, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In particular, psychological constructs like self-control, optimism, and deliberative thinking are increasing associated with prudent credit use and sound financial management (Sekścińska et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Str\u0026ouml;mb\u0026auml;ck et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccordingly, this study expects psychological traits to influence borrowers\u0026rsquo; loan repayment behavior. Self-control, for instance, reflects an individual\u0026rsquo;s capacity to regulate desires and delay satisfaction (Tegambwage \u0026amp; Kasoga, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Str\u0026ouml;mb\u0026auml;ck et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), which may boost loan repayment intentions behavior. Optimism trait is an expectancy for positive outcomes (Puri \u0026amp; Robinson, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), may enhance borrowers\u0026rsquo; confidence in their future financial capacity, thereby influencing repayment intentions behavior. Deliberative thinking, the tendency to engage in thoughtful and analytical decision-making (Moxley et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), can further support prudent financial behavior by enabling individuals to foresee long-term consequences and balance financial commitments against conflicting needs.\u003c/p\u003e\u003cp\u003eDespite their theoretical importance, these psychological traits have not been integrated into loan repayment behavior within the microfinance context. The present study addresses this gap by employing the theory of planned behavior (TPB) by Ajzen, (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). The TPB posits that attitudes, subjective norms, and perceived behavioral control shape behavioral intentions, which in turn influence actual behavior. This study specifically examines the extent to which psychological traits influence borrowers\u0026rsquo; loan repayment behavior.\u003c/p\u003e\u003cp\u003eUnderstanding the way psychological traits enhance loan repayment behavior is important to fill the knowledge gap, and developing strategies for improving loan repayment behavior. The findings inform the policy makers and MFIs on the interventions required to improve loan repayment behavior that account for borrowers\u0026rsquo; psychological characteristics.\u003c/p\u003e\u003cp\u003eThe remainder of the paper is structured as follows. Section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e reviews the relevant literature to develop the study\u0026rsquo;s hypotheses. Section \u003cspan refid=\"Sec8\" class=\"InternalRef\"\u003e3\u003c/span\u003e outlines the research methodology, while Sections \u003cspan refid=\"Sec13\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Sec18\" class=\"InternalRef\"\u003e5\u003c/span\u003e present and discuss the findings, respectively. Section \u003cspan refid=\"Sec19\" class=\"InternalRef\"\u003e6\u003c/span\u003e provides the study\u0026rsquo;s conclusions and implications, and Section \u003cspan refid=\"Sec20\" class=\"InternalRef\"\u003e7\u003c/span\u003e offers suggestions for future research.\u003c/p\u003e"},{"header":"2. Literature review","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Theoretical framework\u003c/h2\u003e\u003cp\u003eThis study use the Theory of Planned Behavior (Ajzen, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) to explain how psychological characteristics can enhance loan repayment behavior. According to TPB, three key factors - attitudes toward the behavior, subjective norms, and perceived behavioral control influence behavioral intentions, which in turn lead to actual behavior. According to the TPB, these factors capture the cognitive and motivational components that drive individuals to act in particular ways. Specifically, self-control is regarded as a trait that strengthens perceived behavioral control, enhancing an individual\u0026rsquo;s confidence to perform the behavior (Baumeister et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Based on the TPB, this study expects that borrowers with high self-control are more likely to manage their spending, adhere to repayment plans, and avoid imprudent financial decisions, thereby increasing the likelihood of repaying their loans on time.\u003c/p\u003e\u003cp\u003eDeliberative thinking is characterized by a rational and reflective cognitive way (Baumeister et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), which aligns closely with the attitudinal component of TPB. Borrowers with strong deliberative thinking are likely to form thoughtful and reasoned assessments of the benefits and consequences of loan repayment. These assessments contribute to the development of positive attitudes toward fulfilling financial obligations, thus strengthening the intention to repay. Optimistic individuals tend to expect positive outcomes and believe in their capacity to achieve financial success (Kasoga \u0026amp; Tegambwage, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e). Based on the TPB, this study expects optimism to influence repayment intention behavior.\u003c/p\u003e\u003cp\u003eThe use of TPB in this study is relevant to Tanzania, where microfinance services are crucial for the poor, who are excluded by traditional financial institutions due to lack of collateral and low financial literacy (Kasoga \u0026amp; Tegambwage, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e). By integrating psychological traits within the TPB framework, this study explores how borrowers\u0026rsquo; internal and cognitive tendencies inform loan repayment behavior Thus, TPB not only supports the theoretical framework of this study, but also enhances its practical relevance by identifying cognitive and motivational factors that may be targeted to improve loan repayment outcomes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Empirical review and hypothesis development\u003c/h2\u003e\u003cp\u003eThis section presents the empirical review and hypotheses development.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 Self-control and loan repayment behavior\u003c/h2\u003e\u003cp\u003eSelf-control is the ability to manage one\u0026rsquo;s thoughts, feelings, and actions in order to achieve long-term objectives (He et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In the context of loan repayment and based on TPB, this study contends that people with strong self-control are more likely to prioritize financial responsibilities, successfully manage their money, and withstand temporary temptations, all of which increase the likelihood that they would repay their loans. As per self-regulation theory (Baumeister \u0026amp; Vohs, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), self-control facilitates goal-directed behavior, which is essential for financial discipline. Prior research revealed a positive correlation between sound financial behavior and self-control. (Kasoga \u0026amp; Tegambwage, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e; Kimball \u0026amp; Shumway, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Peng \u0026amp; Ismail, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Sekścińska et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Str\u0026ouml;mb\u0026auml;ck et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOther previous studies found over-indebted borrowers exhibiting unfavorable financial behaviors like unnecessary borrowing, poor investment decisions, irresponsible spending, and poor saving habits due to low self-control (Kasoga \u0026amp; Tegambwage, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Likewise, Gathergood (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) stated that those who lack self-control are more prone to incur unanticipated costs, which could have a detrimental impact on their capacity to repay loans. In the Tanzanian context, where borrowers often face competing demands from family and social networks (Tegambwage \u0026amp; Kasoga, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), self-control enables individuals to stay committed to repayment schedules despite financial pressures. Additionally, the trait is consistent with the TPB\u0026rsquo;s perceived behavioral control construct, suggesting that borrowers are more likely to act responsibly when repaying debt if they think they can control their impulses. Accordingly, based on the explanation above, the study proposes the following hypothesis:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH1.\u003c/em\u003e Self-control is positively and significantly associated with loan repayment behavior among microfinance borrowers in Tanzania.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Optimism and loan repayment behavior\u003c/h2\u003e\u003cp\u003eOptimism is the broad belief that positive things will occur in the future (Peterson, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Based on the TPB (Ajzen, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), this study argues that optimism contributes to the formation of favorable attitudes toward behavior, influencing the intention to perform actions like loan repayment. Optimistic individuals tend to believe in their capacity to overcome obstacles and succeed, making them more likely to follow through on their financial commitments (Duque et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Empirical studies (e.g., Hirvonen, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kasoga \u0026amp; Tegambwage, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e; Khan et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Mawad, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Str\u0026ouml;mb\u0026auml;ck et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) reinforce this connection, showing that optimism influences positive financial behaviors. Mohammad et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) found that pessimistic investors tend to exhibit unfavorable financial behaviors in terms of poor borrowing, investing, spending and saving decisions, which may lead to poor loan repayment behavior. In environments like Tanzania, where economic challenges and uncertainty are prevalent among the poor, optimism can serve as a psychological buffer, helping borrowers maintain positive expectations and persevere in repaying their loans even during periods of hardship. Consequently, the research hypothesizes that:\u003c/p\u003e\u003cp\u003e\u003cem\u003eH2.\u003c/em\u003e Optimism is positively and significantly related to loan repayment behavior among microfinance customers in Tanzania.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.2.3 Deliberative thinking and loan repayment behavior\u003c/h2\u003e\u003cp\u003eDeliberative thinking is characterized by analytical, conscious, and forward-looking decision-making (Moxley et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In other words, it is the capacity to deliberate and make thoughtful decisions. Within the TPB framework Ajzen (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), deliberative thinking enhances the intention-behavior by enabling individuals to form well-considered attitudes and assess the feasibility of repayment actions. Such cognitive competence helps borrowers make informed borrowing decisions, develop repayment plans, and avoid impulsive financial behavior. Empirical research provides support for this link. Dhar and Gorlin (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) showed that individuals with a deliberative thinking style demonstrated more prudent financial decision-making. Hashmi et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that prudent financial behaviors like investing and saving are positively related with deliberative thinking, which may lead to good loan repayment performance. Kasoga \u0026amp; Tegambwage (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e) discovered that investors make bad investing choices, employ a lot of heuristics, and only partially participate in deliberative thought. In the Tanzanian context, where formal financial education is limited among microfinance customers, deliberative thinking may enable borrowers to critically evaluate loan terms, forecast future cashflows, and make calculated repayment decisions, enhancing loan repayment behavior. Hence, the following hypothesis is suggested:\u003c/p\u003e\u003cp\u003eH3. Deliberative thinking is positively and significantly related to loan repayment behavior among MFI customers in Tanzania.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"3. Research Methodology","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Research design and instrument\u003c/h2\u003e\u003cp\u003eThis study used explanatory research design to explain how psychological traits- self-control, deliberative thinking, and optimism influence loan repayment behavior. This design assists in explaining the causal relationships among the variables. The Existing, experimentally verified items were used to optimize the constructs\u0026rsquo; validity and reliability. The psychological trait items were sourced from Kasoga and Tegambwage (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e) and adapted to the microfinance context. Validated scales for loan repayment behavior were adapted from Tegambwage and Kasoga (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The generated questionnaire was pre-tested among 40 MFI customers before conducted the final survey, in order to evaluate the validity and reliability of the items as well as the wording of the questions. A five-point Likert-type scale, with 1 denoting \u0026ldquo;strongly disagree\u0026rdquo; and 5 denoting \u0026ldquo;strongly agree,\u0026rdquo; was used to probe all issues except the demographic questions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Ethical compliance and consent procedures\u003c/h2\u003e\u003cp\u003eBefore taking part in the study, all participants received an information sheet explaining the purpose, procedures, and intended use of the data. They were assured that their responses would remain confidential and anonymous. Written informed consent was secured from each respondent prior to data collection. The study did not involve human experiments or the use of biological samples; however, it complied fully with established ethical research principles and was approved by the Institutional Research Review Ethical Committee of the University of Dodoma, Tanzania. All research activities were conducted in line with relevant ethical guidelines. To safeguard participants, strict measures were observed to ensure voluntary participation, protect confidentiality and anonymity, and respect the right to withdraw from the study at any point without consequences. Every precaution was taken to preserve the privacy, dignity, and rights of those involved.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Study population, data-collection procedure, and sample characteristics\u003c/h2\u003e\u003cp\u003eThe study\u0026rsquo;s population consisted of all MFIs borrowers in the three main Tanzanian cities of Dodoma, Mwanza, and Dar es Salaam. The majority of Tanzania\u0026rsquo;s MFIs borrowers reside in these cities (Kasoga, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Rwamuhuru \u0026amp; Tegambwage, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Research assistants used a methodical sampling technique to approach MFIs borrowers as they were leaving the MFIs. A questionnaire was supplied to borrowers who consented to participate. Nine hundred (900) surveys were gathered and examined. Respondents were asked to keep their answers secret and were given the assurance that they would be kept completely confidential. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays sample characteristics. The finding show that the majority of MFIs borrowers in Tanzania are women (Kasoga \u0026amp; Tegambwage, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e; Tegambwage, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), who comprise 58.1% of the respondents. Respondents ranged in age from 18 to 50, with the majority (51.3%) lying between the ages of 31 and 40. The majority of respondents (69.9%) were married and 35.4% had finished their elementary schooling.\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\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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=\"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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDescription\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e41.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e523\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e58.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18\u0026ndash;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41\u0026ndash;50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e35.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e35.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e273\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTertiary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e174\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUniversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e629\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e69.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.8\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=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Data analysis\u003c/h2\u003e\u003cp\u003eThe measurement and structural models were evaluated using structural equation modelling (SEM). SEM makes it possible to evaluate numerous construct correlations at once and gauge the model\u0026rsquo;s overall robustness (Anderson \u0026amp; Gerbing, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1988\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Measurement model\u003c/h2\u003e\u003cp\u003eA rotating component matrix served as the basis for the factor analysis (Anderson \u0026amp; Gerbing, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). To ascertain whether the sample size was adequate for factor analysis, the data was subjected to the Keiser-Meyer-Olkin (KMO) and Bartlett tests. The findings demonstrate that the sample size was enough for factor analysis because the KMO value was 0.612 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), above the suggested value of 0.5 (Sarstedt et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Furthermore, a significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) Bartlett's test of sphericity was used to demonstrate the adequacy of the sample size (Hair Jr et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Hair Jr et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) state that factor analysis, when KMO and Bartlett tests are computed, can yield distinct and dependable factors.\u003c/p\u003e\u003cp\u003eFactor loadings with a weight larger than 0.5 and Cronbach's alpha coefficients (α), which are higher than the recommended threshold of 0.7, attest to the measures' reliability (Sarstedt et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Convergent validity was confirmed by statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;.001) of all factor loadings for indicators assessing the same construct (Anderson and Gerbing, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). Correlations between the constructs and the extracted square root of their average variance (AVE) were used to establish discriminant validity (Anderson \u0026amp; Gerbing, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). Discriminant validity was confirmed where by the square root of AVE for each construct was greater than the correlations between them (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) (Anderson \u0026amp; Gerbing, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). Estimated pair-wise correlations between the components, which were significantly less than one and did not exceed 0.85, provided support for this (Sarstedt et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Potential common method variance was reduced by using pre-existing measures and ensuring respondents\u0026rsquo; anonymity (Podsakoff et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Furthermore, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e demonstrates that there were no exceptionally significant correlations (r\u0026thinsp;\u0026gt;\u0026thinsp;0.80) among the constructs, suggesting that our results were not seriously jeopardized by common method bias(Podsakoff et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The variance inflation factor (VIF) for each construct (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) were below the conventional cut-off value of 5 (Hair Jr et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), suggesting that there is no multicollinearity between the explanatory measurement constructs.\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\u003eCFA results bad\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=\"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\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\u003eItem label\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eItem description\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFactor Loading\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eT-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-control (SEC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eα\u0026thinsp;=\u0026thinsp;0.798; AVE\u0026thinsp;=\u0026thinsp;0.784\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSEC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI find it difficult to break harmful habits.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.783\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e122.861***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSEC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI get distracted easily.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.950\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e197.247***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSEC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI can withstand temptation well.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.788\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e81.363***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSEC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI make decisions that I subsequently regret even if they feel nice at the time.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e112.830***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSEC5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI frequently take action without considering all of my options.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e237.574***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOptimism (OPT)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eα\u0026thinsp;=\u0026thinsp;0.837; AVE\u0026thinsp;=\u0026thinsp;0.831\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOPT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI usually hope for the best when things are unclear.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e89.303***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOPT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIf there's anything that might go wrong with me, it will.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.808\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e151.672***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOPT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI always have hope for the future.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.896\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e87.158***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOPT4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI almost never hope for the best.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.761\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e58.536***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOPT5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI seldom ever rely on favorable circumstances to come my way.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.618\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60.089***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeliberative thinking (DET)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eα\u0026thinsp;=\u0026thinsp;0.858; AVE\u0026thinsp;=\u0026thinsp;0.818\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDET1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCreating a well-defined strategy is crucial to me.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e174.316***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDET2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI enjoy problem-solving.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e205.808***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoan repayment behavior (LRB)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eα\u0026thinsp;=\u0026thinsp;0.736; AVE\u0026thinsp;=\u0026thinsp;0.768\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLRB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI always make full loan repayment as agreed with MFI.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.729\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e286.361***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLRB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI have never missed a scheduled loan repayment.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.727\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e269.850***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLRB3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI keep track of my repayment schedule and stay on track.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.719\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e283.604***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eKMO 0.612\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eBartlett\u0026rsquo;s Test of Sphericity 158.886***\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=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Descriptive statistics and correlations between the constructs\u003c/h2\u003e\u003cp\u003eBorrowers reported high loan repayment behaviors (M\u0026thinsp;=\u0026thinsp;4.46), supported by strong self-control (M\u0026thinsp;=\u0026thinsp;3.89) and deliberative thinking (M\u0026thinsp;=\u0026thinsp;4.11) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), indicating disciplined and thoughtful financial behaviors. However, optimism was relatively low (M\u0026thinsp;=\u0026thinsp;2.96), suggesting limited confidence in future financial prospects. This pattern implies that repayment is driven more by self-regulation and careful planning than by positive expectations. Drawing on TPB, high perceived control and deliberate decision-making may compensate for lower optimism, sustaining favorable repayment behaviors despite modest future outlook. All constructs have modest standard deviations in relation to their mean values, suggesting that the statistical means fit the observed data well (Field, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The recommended ranges for skewness and kurtosis values are met (Matore \u0026amp; Khairani, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Specifically, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e's values of skewness and kurtosis, which are neither less than \u0026minus;\u0026thinsp;1 nor larger than +\u0026thinsp;1 nor less than \u0026minus;\u0026thinsp;2 nor more than +\u0026thinsp;2, respectively, show that there is no cause for alarm over the sample's non-normal distribution.\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\u003eDescriptive statistics\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=\"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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstructs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSkewness\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eKurtosis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-control\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.401\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.215\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOptimism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.560\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.638\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-0.319\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeliberative thinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.939\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.060\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoan repayment behavior\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.317\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.320\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-0.816\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\u003eA Pearson correlation analysis was done to see if there were any linear relationships between the constructs (Field, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The results in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e show that there is a positive and significant association between loan repayment behavior and self-control (r\u0026thinsp;=\u0026thinsp;0.259, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and between loan repayment behavior and deliberative thinking (r\u0026thinsp;=\u0026thinsp;0.132, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, the association between repayment behavior and optimism was found to be negative and significant (r = -0.468, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The results suggest that unfavorable loan repayment behaviors are more common with borrowers who are more optimistic, having little self-control, and low deliberative thinking. These findings underscore the importance of complementing microfinance services with behavioral interventions that strengthen self-regulation and decision-making skills, especially in low-resource settings like Tanzania. It is important to acknowledge that the correlation analysis result provides an initial indication of the validity of the study\u0026rsquo;s hypothesis. Consequently, more investigation (path analysis) is done to validate the study\u0026rsquo;s premise.\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\u003eCorrelations analysis results\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=\"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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstructs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSEC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOPT\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDET\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLRE\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-control (SEC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.885\u003c/b\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOptimism (OPT)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.230***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.912\u003c/b\u003e\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeliberative thinking (DET)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.250***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.167***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.904\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoan repayment behavior (LRB)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.259***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.468***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.132***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.876\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNotes: Diagonal elements are the square root of AVE between the constructs and their measures. The off-diagonal elements are correlations between the constructs. ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\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\u003e4.3 Structural model and testing the hypothesis\u003c/h2\u003e\u003cp\u003eBy using SEM, the hypothesized associations' validity was confirmed. The goodness-of-fit indices were analyzed and found to be well within the recommended ranges (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), indicating that the structural model provided an adequate fit to the data (Hair \u0026amp; Alamer, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\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\u003eModel fit indices\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=\"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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCMIN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRMR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGFI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAGFI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNFI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRFI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eIFI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eTLI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eCFI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eRMSEA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003ePCLOSE\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10.040, df 5, p\u0026thinsp;=\u0026thinsp;0.074;\u003c/p\u003e\u003cp\u003eCMIN/df\u0026thinsp;=\u0026thinsp;2.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.980\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.987\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.790\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"11\"\u003eNotes: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e, chi-square; df, degrees of freedom RMR, root mean square residual; GFI, the goodness of fit index; AGFI, adjusted goodness of fit index; NFI, normed fit index; RFI, relative fit index; IFI, incremental fit index; TLI, Tucker\u0026ndash;Lewis\u0026rsquo;s index; CFI, comparative fit index; RMSEA, root mean square error of approximation; PCLOSE, parsimony close.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eBy analyzing the connections between the constructs using the path coefficients, the study hypotheses were put to the test. According to the results in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, loan repayment behaviors are influenced by psychological traits. Specifically, the results show that self-control (β\u0026thinsp;=\u0026thinsp;0.007, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and deliberative thinking (β\u0026thinsp;=\u0026thinsp;0.211, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) have positive and significant effects on loan repayment behavior. However, contrary to expectations, optimism exhibited a negative and significant effect on repayment behavior (β = -0.255, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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\u003eHypothesis testing results\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\u003eRegression path\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePath coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eS.E.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC.R.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\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\u003eLoan repayment behavior (LRB) \u0026lt;--- Self-control\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.160\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoan repayment behavior (LRB) \u0026lt;--- Optimism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-17.701\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.119\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoan repayment behavior (LRB) \u0026lt;--- Deliberative thinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.211\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.131\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoan repayment behavior (LRB) \u0026lt;--- Age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-6.899\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.792\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\u003eLoan repayment behavior (LRB) \u0026lt;--- Gender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.352\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-10.610\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.081\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\u003eLoan repayment behavior (LRB) \u0026lt;--- Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.969\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e***\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\u003eLoan repayment (LRB) \u0026lt;--- Marital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.324\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e***\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\u003eAdjusted R\u003csup\u003e2\u003c/sup\u003e = 0.512; F\u0026thinsp;=\u0026thinsp;135.493***\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\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNotes: BL stands for borrower\u0026rsquo;s loyalty. LO stands for loan officer. MFI stands for microfinance institution. ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Robustness checks\u003c/h2\u003e\u003cp\u003eAge (β = -0.161, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) and gender (β = -0.352, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) do not significantly affect loan repayment behavior (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Nonetheless, there are notable impacts on repayment behavior due to marital status (β\u0026thinsp;=\u0026thinsp;0.324, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and educational status (β\u0026thinsp;=\u0026thinsp;0.204, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This implies that, despite these sociodemographic variables, the impact of psychological traits on loan repayment behavior is still significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe findings of this study offer insight into how psychological traits influence loan repayment behavior in the Tanzanian microfinance context. Based on the TPB (Ajzen, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), the findings confirm that self-control and deliberative thinking enhance borrowers\u0026rsquo; loan repayment behavior, whereas optimism was found to be negatively associated with loan repayment behavior.\u003c/p\u003e\u003cp\u003eSpecifically, self-control positively and significantly influenced repayment behavior (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). This aligns with TPB\u0026rsquo;s concept of perceived behavioral control, which reflects an individual\u0026rsquo;s ability to perform a certain behavior. Borrowers with high self-control are able to delay satisfaction, resist imprudent spending, and maintain discipline in loan consumption, leading to good repayment behavior. These results are supported by Kimball and Shumway (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), Peng and Ismail (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), Sekścińska et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Str\u0026ouml;mb\u0026auml;ck et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), who found that self-control is a key predictor of financial behavior in developing economies. In the Tanzanian setting, where financial stress and social demands are common among MFI clients (Kasoga and Tegambwage \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e), high self-control enables borrowers to pass through the competing priorities without defaulting.\u003c/p\u003e\u003cp\u003eDeliberative thinking was also positively and significantly associated with loan repayment behavior (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). This aligns with the attitude toward the intentions and behavior in the TPB. This finding is in line with the conceptualization of this study that borrowers with deliberative thinking attitude are more likely to engage in analytical thinking, carefully consider loan terms, plan for contingencies, and budget effectively. This finding is consistent with Dhar and Gorlin (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), Hashmi et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and Kasoga and Tegambwage (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e) who demonstrated that individuals with deliberative cognitive engage in prudent financial decisions. Considering the fact that most of low income people in Tanzania have low financial literacy, and operate in informal business environment (Rwamuhuru et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ringo et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), deliberative thinking is important cognitive asset for compensating limited financial literacy.\u003c/p\u003e\u003cp\u003eContrary to expectations, optimism show a negative and significant effect on loan repayment behavior (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). While optimism typically enhances attitudes toward behavior in TPB, excessive or unrealistic optimism can lead to overconfidence, underestimation of risk, or poor financial planning (Puri and Robinson, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Optimistic borrowers may overestimate future income or the success of business, leading to over-borrowing or less urgency when it comes to repayments. This aligns with (Coelho, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), who cautioned that extreme optimism can undermine financial responsibility. This finding suggests that in the Tanzanian context, where economic shocks and uncertainty are frequent (Kasoga \u0026amp; Tegambwage, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), high optimism may be dangerous.\u003c/p\u003e"},{"header":"6. Conclusion and implications","content":"\u003cp\u003eThis study examined the effect of psychological traits on loan repayment behaviors of MFI customers in Tanzania. The findings reveal that psychological traits significantly influence loan repayment behavior among MFI clients in Tanzania. Specifically, self-control and deliberative thinking positively influence loan repayment behavior, supporting TPB\u0026rsquo;s that behavioral intention, control and, good attitude are key drivers of actual behavior. However, extreme optimism, was found to affect negatively repayment behaviors, due to overconfidence and misjudgment of financial risks. These findings highlight the importance of psychological traits in financial decision-making and behavior. The findings contribute to the TPB by linking psychological traits namely, self-control, deliberative thinking, and optimism to the loan repayment behaviors in microfinance contexts. Practically, this study informs the MFIs to consider psychological traits in screening to identify which trait is important in explaining repayment behavior. The finding of this study suggests the importance of financial knowledge to address the risks of extreme optimism, which actually affects negatively loan repayment behavior. To policy makers, the findings of this study suggest the importance of adopting psychological traits such as self-control and deliberative thinking in their strategies in informing lending procedures, and repayment behavior. These traits can assist in identifying borrowers who are at the risk of defaulting.\u003c/p\u003e"},{"header":"7. Recommendations for future research","content":"\u003cp\u003eThis study has limitations, just like any other studies. First, because of its cross-sectional design, it was not possible to establish changes over time. Future studies should use longitudinal designs to establish changes over time, and investigate moderating factors such economic shocks, social norms, financial literacy, and trust in MFIs. Second, the study was conducted in Tanzania, and among MFIs borrowers, the results might not apply to other cultural settings. Future studies should be conducted in other contexts to enhance generalizability of the findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Institutional Research Review Ethical Committee of the University of Dodoma, Tanzania. The study complied with all established ethical research standards. The committee approval number (for animal and human studies) is not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants were provided with detailed information regarding the study’s objectives, procedures, and the intended use of the data. Written informed consent was obtained from every participant prior to data collection. Participation was voluntary, and participants were free to withdraw at any stage without consequences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were assured that all data would remain confidential and anonymous. As such, consent to publish anonymized data and findings derived from the study was obtained. No identifiable information is included in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e Available upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e The study was funded by the University of Dodoma through the Benjamin William Mkapa Research Grants, under the category of Senior Academic Staff.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe corresponding author affirms that all listed authors have reviewed the manuscript, approved its final version, and agreed to be accountable for their respective contributions. Furthermore, the authors confirm that the submission complies with the journal’s policies on authorship and author responsibilities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to sincerely acknowledge the University of Dodoma through the Benjamin William Mkapa Research Grants, under the category of Senior Academic Staff, for providing the financial support that made this study possible. We are also grateful to the research assistants for their dedication and effort in collecting the data, and to our colleagues whose encouragement and constructive support greatly contributed to the success of this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAjzen, I. (1991). The theory of planned behavior. \u003cem\u003eOrganizational Behavior and Human Decision Processes\u003c/em\u003e, \u003cem\u003e50\u003c/em\u003e(2), 179\u0026ndash;211.\u003c/li\u003e\n\u003cli\u003eAnderson, J. C., \u0026amp; Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. \u003cem\u003ePsychological Bulletin\u003c/em\u003e, \u003cem\u003e103\u003c/em\u003e(3), 411.\u003c/li\u003e\n\u003cli\u003eBaumeister, R. F., \u0026amp; Vohs, K. D. (2007). Self‐Regulation, ego depletion, and motivation. \u003cem\u003eSocial and Personality Psychology Compass\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(1), 115\u0026ndash;128.\u003c/li\u003e\n\u003cli\u003eBaumeister, R. F., Vohs, K. D., \u0026amp; Tice, D. M. (2007). The strength model of self-control. \u003cem\u003eCurrent Directions in Psychological Science\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(6), 351\u0026ndash;355.\u003c/li\u003e\n\u003cli\u003eBhawe, N., \u0026amp; Jha, S. K. (2025). MFIs and financial inclusion: The role of business models. \u003cem\u003eThe Journal of Development Studies\u003c/em\u003e, \u003cem\u003e61\u003c/em\u003e(1), 133\u0026ndash;151.\u003c/li\u003e\n\u003cli\u003eCoelho, M. P. (2010). Unrealistic optimism: Still a neglected trait. \u003cem\u003eJournal of Business and Psychology\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(3), 397\u0026ndash;408.\u003c/li\u003e\n\u003cli\u003eDhar, R., \u0026amp; Gorlin, M. (2013). A dual-system framework to understand preference construction processes in choice. \u003cem\u003eJournal of Consumer Psychology\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(4), 528\u0026ndash;542.\u003c/li\u003e\n\u003cli\u003eDuque, M., Lee, S. W., Bochkina, E., Lee, T. 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Loan repayment among group borrowers in Tanzania: the role of relationship quality. \u003cem\u003eFuture Business Journal\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(1), 37.\u003c/li\u003e\n\u003cli\u003eTegambwage, A. G., \u0026amp; Kasoga, P. S. (2024). Relationship quality and customer loyalty in the Tanzanian microfinance sector. \u003cem\u003eJournal of Financial Services Marketing\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(1), 138\u0026ndash;153.\u003c/li\u003e\n\u003cli\u003eTegambwage, A. G., \u0026amp; Kasoga, P. S. (2025). The role of individual dimensions of business relationship quality and business customer value in building loyalty in microfinance. \u003cem\u003eJournal of Innovation and Entrepreneurship\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(1), 1\u0026ndash;19.\u003c/li\u003e\n\u003cli\u003eYibrie, O., \u0026amp; Ramakrishna, R. (2017). Determinants of loan repayment performance in ACSI. \u003cem\u003eInternational Journal of Advanced Research in Management and Social Sciences\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(4), 151\u0026ndash;169.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"discpsy","sideBox":"Learn more about [Discover Psychology](https://www.springer.com/44202)","snPcode":"","submissionUrl":"","title":"Discover Psychology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7641542/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7641542/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examines the influence of psychological characteristics - self-control, optimism, and deliberative thinking on loan repayment among Tanzanian microfinance borrowers. Using the Theory of Planned Behavior (TPB), these traits are conceptualized as determinants of repayment intention and behavior. Data were collected through a structured survey in three major Tanzanian cities and analyzed with structural equation modelling (SEM). Results indicate that optimism negatively and significantly affects repayment behavior, while self-control and deliberative thinking have positive and significant effects. The findings extend TPB by demonstrating the predictive role of psychological traits in financial behavior and emphasize their importance in assessing credit risk. Practically, the study recommends integrating behavioral screening and into microfinance services. At the policy level, it highlights the need for psychologically informed lending practices to strengthen repayment performance and guarantee the financial sustainability of microfinance institutions.\u003c/p\u003e","manuscriptTitle":"Psychological traits and loan repayment behaviors among microfinance borrowers in Tanzania","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-22 09:29:37","doi":"10.21203/rs.3.rs-7641542/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-20T05:35:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-17T14:06:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-30T14:42:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"297894583866453401237192500791106432428","date":"2025-10-27T05:33:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31352893659965644921128748329323723290","date":"2025-10-14T05:51:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-09T06:21:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-09T06:13:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-01T10:08:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Psychology","date":"2025-10-01T09:56:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"discpsy","sideBox":"Learn more about [Discover Psychology](https://www.springer.com/44202)","snPcode":"","submissionUrl":"","title":"Discover Psychology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d1335327-435d-4a95-85b2-36c058e4d69f","owner":[],"postedDate":"October 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T09:24:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-22 09:29:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7641542","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7641542","identity":"rs-7641542","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}