Behavioral biases and personal indebtedness: a systematic literature review

Behavioral biases and personal indebtedness: a systematic literature review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Behavioral biases and personal indebtedness: a systematic literature review Emmanuel Marques Silva, Daniel Fonseca Costa, Patricia Maria Bortolon This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4510972/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective The level of indebtedness of individuals has increased significantly in recent decades. The objective of this study was to analyze the scientific literature that evaluates the interrelationships between behavioral biases and personal indebtedness, with a view to investigating the intellectual structure of publications on the influence of behavioral biases on the level of personal indebtedness. Methodology Bibliometric analysis of scientific publications carried out until October 2023 in the "Web of Science" and "Scopus" databases and which analyze determinants of personal indebtedness from the perspective of behavioral sciences was used. Results The results reveal works with global and local relevance, how indebtedness has been discussed from a behavioral perspective and the main cognitive biases associated with it, research clusters that can serve as a reference for researchers, trends and research gaps in this field of knowledge, and that combining constructs from the field of behavioral sciences with other areas of knowledge, especially education/knowledge and psychology/behavior, tends to expand the literature related to personal indebtedness. Originality Based on the content analysis of the articles, an innovative scheme illustrating the possible definitions of indebtedness from an economic and psychological perspective is presented, which is an important contribution to the literature. Behavioral Economics personal indebtedness behavioral biases behavioral sciences systematic literature review bibliometric analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction In recent decades, the world economy has witnessed a persistent increase in individuals' levels of indebtedness, making debt a persistent feature of household balance sheets at all stages of life (Leandro & Botelho, 2022 ). As it is an important aspect in many countries and, in extreme situations, constitutes a threat not only to the financial stability of families, but also a precursor to economic and financial crises, understanding issues related to indebtedness is a relevant aspect for companies, the economy, governments and society (Gutiérrez-Nieto et al., 2017 ; Almenberg et al., 2021 ; Šubová et al., 2021 ). Indebtedness is the process in which individuals commit a significant portion of their income in order to honor it in the future and which, in more extreme situations (excessive indebtedness), can generate a situation in which the individual becomes unable to pay their debts with the income they receive, characterizing over-indebtedness (Pacheco et al., 2018). An interesting feature about indebtedness emerges from this concept: there is a significant difference between the accounting concept of indebtedness and its cognitive (mental) recognition. From an accounting point of view, indebtedness consists of assuming obligations (debts) in the present which are expected to be paid off in the future. On the other hand, there are cognitive aspects that assume that the individual will only recognize debt when there is difficulty in honouring the obligation. At this point, indebtedness is influenced by the level of coupling between consumption and payment and by the psychological ownership of borrowed money (Prelec & Loewenstein, 1998 ; Sharma et al., 2021 ). Finance has always played a critical role in economies, as it is at the center of consumption, savings and investment decisions by individuals, companies and governments (Claus & Krippner, 2018 ). In this context, the scientific literature has been trying over the years to understand what leads individuals into debt and how to mitigate it using traditional economic approaches (Zerrenner, 2007 ; Keese, 2012 ), and to understand how behavioral economics, whose approach combines psychological, cognitive and behavioral foundations with economic factors (Costa et al., 2019 ) influences the individual's behavior when taking on and managing debt (Flores & Vieira, 2014 ; Swacha-Lech & Solarz, 2019 ; Sharma et al., 2021 ). Since individual over-indebtedness is an interdisciplinary, complex and multifaceted phenomenon, where no single set of characteristics is sufficient to explain it worldwide (Blázquez et al., 2020; Leandro & Botelho, 2022 ), and behavioral finance serves as a complement to classical finance, introducing behavioral aspects into decision-making (Aguirre & Aguirre, 2024 ), studies that analyze the determinants of personal indebtedness from the perspective of the behavioral sciences (economics and behavioral finance) bring valuable insights and expand the literature, with a strong contribution to the field of public policy. In view of the above, this research aims to investigate the intellectual structure of publications on the influence of behavioral biases on the level of personal indebtedness, in order to expand knowledge on the subject. As a result, we hope to answer the following questions: (i) which are the main works and authors with significant contributions to this area of knowledge?; (ii) how are the studies concentrated (clusters)?; (iii) how has indebtedness been discussed from a behavioral perspective?; (iv) what are the main cognitive biases associated with indebtedness? and; (v) what are the trends and research gaps in this field of knowledge? This is a descriptive study, using a structured and systematized bibliometric approach using the "Proknow-C" tool, which tends to minimize the use of randomness and subjectivity in the literature review process (Afonso et al., 2011 ). The relevance of this study is based on the fact that (i) it investigates a problem (indebtedness) that directly affects people's lives; (ii) the importance of studies that examine the factors that influence the increase in indebtedness (Gathergood, 2012 ); (iii) the growing increase in levels of indebtedness seen in Brazil and worldwide (Leandro & Botelho, 2022 ) and; (iv) for exploring the contribution of behavioral economics and finance in this field of knowledge. Theoretical Background Debt can be understood as an amount of money lent between parties, with the condition that the amount lent by the creditor is later repaid by the debtor. It is a financial device commonly used when current savings or income are inadequate for desirable purchases or for urgent payments and survival (Hiilamo, 2020 ). Debt can be conceptualized in various ways. Under an economic lens, it is shown as an instrument whose purpose is to balance consumption over time, which under certain assumptions, has a positive effect on one's "well-being" (Zinman, 2015 ). Under a sociological lens, it can be understood as an unbalanced and distinct social arrangement between a creditor and a debtor, characterized by an obligation to repay in the future (Hiilamo, 2020 ). Debt is a planned and rational decision that allows for the intertemporal redistribution of consumption (Gutiérrez-Nieto et al., 2017 ). It refers to the financial situation resulting from the act of taking on or contracting debts, i.e. it is the sum of the amount of money that a person or company owes to third parties (accumulated debts). It differs from the concept of debt in that, while debt, from a financial point of view, represents a specific monetary value that a person has to pay someone for an obligation; indebtedness is a broader measure of the total debts that an entity has in relation to some financial parameter, such as revenue or equity (Betti et al., 2007 ; Leandro & Botelho, 2022 ). Thus, according to the ratio (debt/revenue or debt/equity, for example), the degree of indebtedness of an entity (company or individual) can be considered low, medium or high. On another point, excessive indebtedness can result in default, which occurs when indebted individuals are unable to pay their debts on time. The continuous increase in indebtedness has an impact on individuals' ability to pay and, at its most advanced stage, can result in them being unable to pay their current credit repayments and other commitments without reducing their spending below the normal minimum levels, a situation which characterizes over-indebtedness (Brennan & Gallagher, 2007 ). Overall, people are considered over-indebted if they are having difficulties meeting (or are falling behind with) their household commitments, whether these relate to servicing secured or unsecured borrowing, or to payments of rent, utility or other household bills (Blázquez et al., 2020). According to Katona ( 1975 ) there are three reasons why individuals spend more than they earn: (i) low income, so they can't even cover essential expenses; (ii) high income, combined with a strong desire to spend; and (iii) a lack of desire to save (regardless of income). This illustrates that the "spending function" goes far beyond subjective expected utility, but is influenced by other factors, especially behavioral ones. In this context, it can be seen that behavioral economics can be useful both for identifying the causes of excessive indebtedness and for dealing with it (Daura, 2018 ). Previous studies evaluating the determinants of personal indebtedness have shown that the pain of paying plays an important role in consumer self-regulation (Prelec & Loewenstein, 1998 ); that individuals with present bias are more likely to have credit card debt (Meier & Sprenger, 2010 ); that successful money management reduces the willpower needed to control financial behavior and helps prevent and combat over-indebtedness (Kamleitner et al., 2011 ), 2011 ); that individuals' impulsiveness when making decisions has a significant influence on indebtedness (Ottaviani & Vandone, 2011 ); that a lack of self-control and financial illiteracy are positively associated with excessive indebtedness (Gathergood, 2012 ); that there is a significant difference in the level of indebtedness according to age, gender, marital status, education, religion, religious principles, occupation, household income, credit card and credit addiction (Flores & Vieira, 2014 ); that impulsivity fully mediates the impact of financial literacy on debt (Ottaviani & Vandone, 2018 ); that overconfidence has been associated with a series of negative financial behaviors and outcomes (Atlas et al., 2019); and that people who are overconfident in their financial abilities tend to borrow more than less confident individuals (Hauff & Nilsson, 2020 ). In the field of the psychology of money, Webley & Nyhus ( 2001 ) show that while economic variables alone predict debt very well, psychological factors (especially current orientation, self-control and attitudes towards debt) improve the ability to predict debt. Hershfield et al. ( 2015 ) examined three psychological barriers to the responsible use of credit and debt and pointed to the tendency for consumers to categorize debt and savings in separate mental accounts. Corroboratively, Sussman & O'Brien (2016) also point out people's tendency to preserve savings by borrowing from a credit option with a high interest rate. In this context, Swacha-Lech & Solarz ( 2019 ) indicate that the strongest determinants of mental accounting attitude are: having debt, having savings, debt aversion and the amount of monthly net income achieved. Sharma et al. ( 2021 ) introduce the concept of psychological ownership of borrowed money, which represents the extent to which consumers feel that borrowed money is theirs, and report that framing debt using language with lower psychological ownership can reduce consumers' propensity to borrow. These papers illustrate how the psychology of money and mental accounting can influence the propensity for and maintenance of personal indebtedness. With regard to systematic literature reviews, the results of Leandro & Botelho ( 2022 ) point out that (i) over-indebtedness is an interdisciplinary, complex and multifaceted phenomenon; (ii) the antecedents of over-indebtedness can be related to the consumer, creditors or the macro-environment; and (iii) over-indebtedness is multi-causal and the associated problems rarely manifest themselves in isolation. Finally, they propose directions for future research through questions aimed at analyzing topics that interrelate indebtedness with (i) antecedents, (ii) results, (iii) theoretical foundations, (iv) methods, (v) personal bankruptcy, (vi) regulation and (vii) prevention and mitigation. Methods This research uses an exploratory, descriptive and bibliographical approach to explore the intellectual structure of publications that analyze the determinants of personal indebtedness from the perspective of behavioral sciences. The main aim is to understand the current state of research on the subject, gaps and trends, and to identify, according to the results of the studies analyzed, which behavioral biases are most aligned with the propensity to personal indebtedness. To this end, we used the systematic literature review (SLR) strategy through bibliometric analysis, using a combination of three instruments: the "Proknow-C" methodology, the "VOSviewer" software together with the bibliometrix programming language package applied to the "R" software, and the Microsoft Excel spreadsheet. Bibliometric research is a variant of systematic literature reviews that involves applying quantitative and statistical techniques to bibliographic data, characterizing it as an appropriate method to demonstrate the research shape and activity, volume and growth in a specific discipline (Donthu et al., 2021 ; Alam et al., 2021 ; Mukherjee et al., 2022 ). Bibliometric analyses aim to uncover the intellectual heritage of a field and depict temporal trends based on the distribution of publications in a scientific discipline (Eulerich et al., 2022 ). It is used to identify emerging trends in the performance of articles and journals, patterns of collaboration and research constituents, and to explore the intellectual structure of a specific domain in the existing literature. In this way, the bibliometric technique proves to be a suitable instrument for the objectives of this work. In the case of the tools used, their choice is justified by three main reasons. Firstly, the "Proknow-C" methodology was chosen because it is a structured and systematic process which tends to minimize the use of randomness and subjectivity in the literature review process (Afonso et al., 2011 ), and which helps to select and critically review the literature according to the researcher's perceptions and delimitations (Valmorbida, 2016 ). Secondly, in the case of “VOSviewer” and bibliometrix, the choice was made due to the high degree of adaptability in changing and updating these tools, allowing the import of input data from various sources, including Scopus and Web of Science, and their potential to offer complete data processing for use in a variety of network analysis tools as they are tools that aim to assist bibliometric and network analysis, and for these reasons are widely used in bibliometric research (Jain et al., 2022 ; Silva et al., 2023). VOSviewer stands out for its ease of use and multiple features, which include specific clustering and natural language processing techniques (Orduña-Malea & Costas, 2021 ); bibliometrix, for being an open source tool that allows the visualization of networks and has features that provide support for carrying out a comprehensive analysis of scientific mapping (Aria & Cuccurullo, 2017 ; Donthu et al., 2021 ). In addition, the Microsoft Excel spreadsheet was used as a tool for generating specific figures (graphs). The search process was carried out in the scientific databases "Scopus" and "Web of Science", as they are two prominent databases for peer-reviewed published research articles widely used in bibliometric analysis (Aria and Cuccurullo, 2017 ; Alam et al., 2021 ), delimiting it in the areas of knowledge: (i) Economics, Econometrics and Finance, (ii) Business, Management and Accounting, (iii) Psychology, Multidisciplinary, Applied, Experimental and Social Psychology; and (iv) Neurosciences and Behavioral Sciences. Finally, to quantify the scientific relevance of each publication, we used the "google scholar" tool, a platform that has an automatic tracking algorithm that extracts bibliographic data, citations and other information on academic articles from various sources, which can be used for metrics relating to publications, citations, among other information (Singh et al., 2022 ). It was used because, although the databases used to search for articles (Scopus and Web of Science) also provide information on the number of citations separately, it would not be possible to assess the concurrence of citations between them, or even citations with other databases (Silva et al., 2023 ). Procedures for selecting articles aligned with the research theme and forming the BP The procedures described in the selection stage of the publications that will make up the bibliographic portfolio (BP) for this research were carried out in October 2023. The selection of scientific articles began with the definition of the main "thematic axes" ("personal indebtedness" and "behavioral sciences") and the search period, which encompassed all scientific production up to October 2023. Once the thematic axes had been defined, we unfolded the keywords to be used to carry out the searches in the "Scopus" and "Web of Science" databases: on the debt axis, the term "*debt"; on the behavioral sciences axis, including behavioral biases, the terms "behavioral finance"; "behavioral economics*"; "behavioral bias"; "anchoring"; "confirmation"; "endowment effect"; "framing"; "herding"; "impulsivity"; "loss aversion"; "mental account*"; "optimism bias"; "overconfidence"; "present bias"; "recency"; "regret aversion"; "representativeness"; "self-control" and "sunk costs". The combinations used in the search and the filtering process up to the formation of the BP are illustrated in Fig. 1 . As illustrated in Fig. 1 , the criteria used for the initial search generated a "raw article database" with 1,268 publications. The time horizon of the search includes all publications up to October 2023. With the insertion of additional filters, the number of publications changed in the following proportion: when inserting the area of knowledge ( "Economics", "Econometrics and Finance", "Social Sciences", "Business", "Management and Accounting", "Psychology Multidisciplinary, Applied, Experimental and Social"; "Decision Sciences", "Neurosciences" and "Behavioral Sciences" ), 1,027 publications; and when inserting the type of publication (articles only), 881 publications. Once the 881 articles aligned with the theme of this research had been selected, screening was carried out. From this number, it was possible to identify that the interaction between the search parameters used returned 194 duplicate items, which were excluded from the database. Next, the titles of the 687 articles in the updated database (with no duplicates) were read to see if they were aligned with the subject under investigation. This procedure showed that, although the descriptors used in the search were aligned with the scope of the research, many articles dealt with different topics, such as "real estate performance", "capital structure decisions", "cost of debt", "accounting conservatism", "accrual and debt", among others. Once these were excluded, the process returned 145 articles that were highly related to the object of study. Once we had the 145 articles, we searched for the number of citations using the Google Scholar platform, sorting them in descending order. The purpose of this process was to verify the scientific relevance of each article, based on the "number of citations" parameter. Once the search had been carried out, the sample was divided into two large groups using the Pareto Principle: (i) 20% of the articles with high representativeness in terms of number of citations, which became "K Repository"; and (ii) 80% of the articles with a low number of citations, forming "P Repository". Of the 33 abstracts in "K Repository", 23 articles were selected to form the core of the BP on the subject of "behavioral biases and personal indebtedness", as they were aligned with the objective of this research. These became "A Repository", made up of articles that have three main characteristics: (i) their abstract is aligned with the research topic; (ii) they have a relevant volume of citations that places them among the 80% most cited; and (iii) their abstract is accessible. The articles in "A Repository" were used as criteria for evaluating the other 112 less cited articles ("P Repository"). The next step was to analyze the articles in "P Repository" according to the criteria set out in the Proknow-C methodology. To be selected for the BP, the articles in "Repository P" must meet two requirements: (i) they must have been published less than 2 years before the analysis (for this item, the years 2021 and 2022 were considered, including the months of 2023) and; (ii) if they were published more than 2 years ago, they must necessarily be by a researcher whose authorship is present in the group of articles selected for "A Repository". Analyzing the articles in "P Repository", it was found that 47 articles were published less than 2 years ago and, of the 65 articles published before 2021 in this repository, 15 are by authors in "Repository K". Thus, 62 articles were selected for the "reweighting" stage, forming "Repository B". After reading the articles in the latter repository, only 27 abstracts were found to be aligned with the research topic. As a final procedure, "Repositories" A (23 articles) and B (27 articles) were combined to form a BP with 50 articles. Results Bibliometric Analysis of the Bibliographic Portfolio (BP) In this section, we present the results of the bibliometric analysis of the BP, divided into two large blocks: analysis of the articles in the BP and analysis of the articles in the BP references. Analysis of BP articles Analysis of the most prominent articles in the BP in terms of number of global citations The summary of the results of the articles selected to make up the BP in descending order of the number of global citations ( google scholar ), their representativeness and their temporal stratification can be seen in Fig. 2 . Based on the results illustrated in Fig. 2 , a first analysis shows that most of the articles in the BP (76%) were published in the last decade. This is mainly due to the growing interest of researchers in investigating the topic of "behavioral biases and personal indebtedness" in recent years. With regard to the representativeness of the BP articles, Fig. 2 shows the prominence of some articles, considering the number of overall citations. Taking the 50 BP articles as a basis, it can be seen that the 5 most cited articles represent more than half (59.2%) of the total number of citations; and the 12 most cited, more than 80.5%. This shows the relevance of these works to the study of the subject. Table 1 illustrates a summary of the main findings of these studies. Table 1 Main results of the most prominent works on indebtedness based on the number of global citations. Summary with main results Authors It proposes a "double entry" theory of mental accounting that describes the nature of these reciprocal interactions between the pleasure of consuming and the pain of paying and highlights their implications for the consumer. Prelec & Loewenstein ( 1998 ) Points out that gift-biased individuals are more likely to have credit card debt and to have significantly higher credit card debt, controlling for disposable income, other sociodemographic data and credit constraints Meier & Sprenger ( 2010 ) It reports that lack of self-control and financial illiteracy are positively associated with non-payment of consumer credit and excessive financial debt burdens. Lack of self-control plays a more important role in explaining consumer over-indebtedness than financial illiteracy Gathergood ( 2012 ) It proposes an alternative approach to incorporate experimental evidence related to time preferences regarding the exponential discounting phenomenon. They argue that increasing the preference for commitment while keeping self-control constant increases the capital premium. Gul e Pesendorfer (2004) Explores the relationships between financial attitudes, impulsivity, locus of control, life satisfaction and stress and their effects on credit card debt levels in university students. Indicates that personality variables are generally not related to the level of debt, although they are related to attitudes towards money. Norvilitis et al. ( 2003 ) Explores the links between self-control, compulsive buying and debt. They indicate that self-control is negatively related to debt, while compulsive buying is positively related to debt, where the link between self-control and debt is completely mediated by compulsive buying. Achtziger et al. ( 2015 ) Analyzes, in a sample of consumers who use credit counseling services, the relationship between positive financial behaviors and the level of economic and non-economic resources, stress and financial satisfaction. They suggest that positive financial behaviors are positively associated with the level of economic and non-economic resources, reduce financial stress and increase financial satisfaction. Xiao et al. ( 2006 ) It shows that psychological factors (especially current orientation, self-control and attitudes towards debt) improve the ability to predict indebtedness. In contrast, dynamic analyses suggest that many of the differences in psychological variables between debtors and non-debtors may be a consequence of being in debt rather than a cause of it Webley & Nyhus ( 2001 ) nalyzes the influence of complementary cognitive abilities on four measures of economic decision-making (temporal discounting, loss aversion, financial literacy and debt literacy) in older vs. younger participants. Older participants' higher crystallized intelligence compensated for their lower levels of fluid intelligence for temporal discounting, financial literacy and debt literacy, but not for loss aversion. Li et al. ( 2013 ) Analyzes consumer credit card debt behavior. Personality factors of self-control, self-esteem, self-efficacy, gratification delay, internal locus of control and impulsivity were significantly correlated with the use of revolving credit; on the other hand, sensation-seeking, impulsivity and gratification delay were correlated with the use of small installments. Wang, Lu, & Malhotra ( 2011 ) They report that financial innovation and overconfidence in the risk of new financial products were key factors behind the 2008 credit crisis in the US. Boz & Mendonça (2014) Analyzes the role of emotional factors in determining household participation in the debt market. In addition to confirming the role played by the traditional explanatory variables used as determinants of household indebtedness, the results revealed the significant influence of individuals' impulsiveness on debt decision-making. Ottaviani & Vandone ( 2011 ) Analyzing the results of the first twelve articles presented in Table 1 , it can be seen that terms such as "attitudes towards money", "financial literacy", "mental accounting", "hyperbolic discounting", "life satisfaction and financial stress", "impulsiveness" and "self-control" are potential predictors of indebtedness, with special emphasis on the last two (impulsiveness and self-control). Page rank analysis Page rank analysis makes it possible to verify the link between articles and their influence, measured by the size of the circle and the cluster formed by them, illustrated by the shade of the circle (Silva et al., 2023 ). This is a combination of eminence, based on the number of citations, and the prestige of the scientific work (Ma et al., 2008 ; Brin & Page, 1998 ). To form the network map, the parameters used were the number of citations or "link strength" different from zero. The results obtained allowed the articles to be classified into 5 distinct clusters, made up of 45 articles, given that the others had a number of citations or link strength equal to zero. Figure 3 shows the network map formed by the articles, illustrated by the shade of the circle and the lines connecting them, and their level of influence, evidenced by the size of the circle containing it. The analysis of the network map of the articles points to the work of Prelec and Loewenstein ( 1998 ), Meier and Sprenger ( 2010 ); Gathergood ( 2012 ); Gul and Pesendorfer ( 2004 ); Norvilitis, Szablicki, and Wilson ( 2003 ); Li et al. ( 2013 ); Achtziger et al. ( 2015 ) and Webley and Nyhus ( 2001 ) as the most prominent in terms of number of local citations, and can be distributed into 5 distinct clusters (gray, blue, orange, yellow and purple). In the first cluster with the highest concentration of works (17 items), represented by the color gray, there are studies that analyze issues related to mental accounting, framing of debt or supply (psychological property of money), coupling between consumption and payment, temporal contiguity and mode of payment. These include the work of Prelec and Loewenstein ( 1998 ) and Li et al. ( 2013 ). The second cluster in terms of the number of papers (9 items), represented by the color blue, is made up of studies that evaluate the relationship between credit and indebtedness, relating them to self-control, impulsiveness, optimism and financial literacy. This cluster includes the work of Webley and Nyhus ( 2001 ), Norvilitis et al. ( 2003 ) and Achtziger et al. ( 2015 ). Next, we have the cluster represented by the color orange (8 items), made up of research that analyzes the relationships between financial literacy, money management and impulsivity and their influence on debt and credit card payments. In this cluster, the works of Gathergood and Weber ( 2017 ) and Atlas et al. ( 2019 ) stand out. In the cluster represented by the color blue, there are studies that evaluate the influence of self-control on spending control, savings, time preference and loan repayment behavior. Ponchio et al. ( 2019 ) stands out as the most relevant of these. Finally, the last cluster, represented by the color purple, is made up of works that analyze the relationship between time preferences in credit and consumer indebtedness. This cluster is formed by the works of Meier and Sprenger ( 2010 ); Gathergood ( 2012 ) and Gul and Pesendorfer ( 2004 ). Finally, the analysis of "total link strength", considering all the articles in the BP, highlighted the works by Frigerio, Ottaviani, and Vandone ( 2020 ), Lea ( 2021 ), Goyal et al. ( 2022 ), Hamid and Loke ( 2021 ), Gathergood and Weber ( 2017 ) and Ponchio et al. ( 2019 ), the latter two also being prominent in terms of the number of citations in the orange and yellow clusters, respectively. Keyword analysis Bibliographic coupling is a well-established approach for measuring documents’ shared intellectual background (Aparicio et al., 2023 ). Bibliographic coupling combined with the cluster method and content analysis of BP articles was applied to identify the intellectual structure of research on behavioral biases and personal indebtedness. The analysis of the descriptors of the papers allows us to expand on these results, since the keywords of an article reflect its main content, and the frequency of their occurrence and co-occurrence represent the most significant themes addressed by papers in a research area and how they are linked to each other (Hemrajani et al., 2023 ). The main assumption of a co-occurrence analysis is that the authors' keywords constitute an adequate proxy for the content of the articles or the relationship that the article establishes between the problems, and their interrelationships can provide reasonable details about the intellectual structure of a given field of knowledge, research patterns and trends (Strozzi et al., 2017 ). Trends in the keywords displayed in various studies can be used to determine the main direction of the study for future investigations (Osei et al., 2023 ; Pesta et al., 2018 ). According to Aria and Cuccurullo ( 2017 ), interpretations based on the network map must take into account the relative position of the points and the distribution of these points in relation to the size of the graph. In addition, the topics that are closest to the center are more relevant to research than the others. To explore the analysis of the co-occurrence of keywords in BP articles, those that occurred more than four times were selected, using VOSviewer's "all keywords" analysis unit. The results obtained in the co-occurrence analysis of the descriptors illustrate three points that can be used in analysis, as suggested by Silva et al. ( 2023 ): (i) the frequency of occurrence of the keywords, measured by the size of the circle; (ii) the strength of association between them, represented by their proximity; and (iii) bibliographic coupling, evidenced by the color of the cluster, shown in Fig. 4. Figura 4. BP Conceptual Structure Map. The parameters used to analyze the co-occurrence of keywords returned 18 descriptors, distributed in 3 distinct clusters, highlighted by gray, blue and orange tones. The gray cluster, formed by 8 items, is composed of works that analyze the interrelationships between credit and credit card, money management, liquidity restrictions, consumer behavior and finances and impulsivity and its influence on personal debt and in the consumption relationship. The blue cluster, formed by 5 items, is composed of works that analyze determinants of debt considering the influence of financial literacy, financial behavior, self-control and materialism. Finally, the last cluster (in orange) is composed of works that analyze debt from the perspective of mental accounting. The analysis of the articles that make up each cluster using the descriptors is presented in Table 2 . Table 2 Analysis of the BP articles based on the bibliographic coupling formed. Cluster color Descriptor Related work Gray Credit and credit card Norvilitis et al. ( 2003 ) explored the relationships between financial attitudes, impulsivity, locus of control, life satisfaction and stress and their effects on levels of credit card debt in university students. It indicates that personality variables are generally not related to the level of debt, although they are related to attitudes towards money. Wang et al. ( 2011 ) points out that personality factors, self-control, self-esteem, self-efficacy, delay of gratification, internal locus of control and impulsivity are significantly correlated with the use of revolving credit. Hodson et al. ( 2014 ), when analyzing the relationship between unpaid consumer debt and emotional pressure, point out that for individuals with average incomes, unpaid debt increases depressive symptoms, while for others (lower and higher incomes), the emotional costs of consumer credit only manifest themselves with the onset of recession. Kuchler & Pagel ( 2021 ) report that the sensitivity of spending to the receipt of paychecks reflects the short-term impatience of agents who are biased towards the present, a behavior best explained by the present bias. Hamid & Loke ( 2021 ), when studying the relationship between socio-economic factors, financial literacy, money management skills, overspending and impulsiveness in credit card repayment decisions, identified that financial literacy and money management skills have a positive effect on the decision-making of credit card holders. George & Leszczyszyn ( 2021 ) point to consumers' overconfidence in their financial knowledge as a new explanation for the phenomenon of simultaneously holding credit card debt and liquid assets. Aydin ( 2022 ) points out that optimism, intuition and materialism have a significant effect on the responsible handling of credit card debts. Other studies mentioned in the clusters also provide results on the influence of credit and credit cards on indebtedness, such as Webley and Nyhus ( 2001 ); Wang et al. ( 2011 ); Atlas et al. ( 2019 ); Frigerio et al. ( 2020 ); Sharma et al. ( 2021 ); Lea ( 2021 ); Jia et al. ( 2023 ) and Moorhouse et al. ( 2023 ). Money management Lea ( 2021 ) analyzed psychological studies on the actual use of credit, debt and over-indebtedness, identifying three groups of factors that lead to indebtedness: dispositional factors (in particular, low conscientiousness and lack of self-control), attitudinal factors (for example, excessive optimism and materialism) and cognitive factors (for example, lack of parental financial guidance and low levels of financial literacy). Other studies mentioned in the previous clusters also provide results on the influence of money management on indebtedness, such as Ottaviani & Vandone ( 2011 ); Ottaviani & Vandone ( 2018 ); Ponchio et al. ( 2019 ); Hamid & Loke ( 2021 ) and Singh & Malik ( 2022 ). Liquidity constraints Meier & Sprenger ( 2010 ) indicate that individuals with a gift bias are more likely to have credit card debt. Baugh et al. ( 2021 ) found that households increase consumption when they receive expected tax refunds, behavior consistent with a life-cycle model of mental accounting. Other studies mentioned in the clusters also provide results on the influence of liquidity constraints on indebtedness, such as Ottaviani & Vandone ( 2011 ) and Sussman & O'Brien (2016). Consumer behavior and finances and Consumer Debt Keys & Wang ( 2019 ) analyze the impact of changing minimum payment formulas on credit cards, finding that anchoring to a contact term has a significant impact on repayment decisions. Hendy et al. ( 2021 ) studied how behavioral factors affect credit card debt minimum payment behavior. It shows that although counseling and anchoring interventions have significant effects on increasing repayments. Lukas & Nöth ( 2022 ) analyze the heterogeneity of borrowers in their debt response to interest rate reductions and credit limit increases in revolving consumer credit. Landa-Blanco (2022) indicates that subjects with higher scores in Attitudes towards Debt and Money (low financial control), Irrational Happiness and Materialistic Values have a greater tendency to Impulsive Buying. Moorhouse et al. ( 2023 ), when conducting a field experiment to examine the effectiveness of a behaviour change course, identified that individuals who anticipated stigmatization and formed new social connections in a community condition reduced their consumer debt. Other works mentioned in the clusters also provide results on the interrelationships between consumer behavior, consumer finances and debt, such as Gathergood ( 2012 ); Achtziger et al. ( 2015 ); Hershfield et al. ( 2015 ); Ponchio et al. ( 2019 ); Atlas et al. ( 2019 ) and Sharma et al. ( 2021 ). Impulsiveness Ottaviani & Vandone ( 2011 ), when analyzing the role of emotional factors as determinants of household debt, report the significant influence of individuals' impulsiveness on debt decision-making. Ottaviani & Vandone ( 2018 ) examined the role of impulsivity and financial literacy as predictors of debt burden finding that impulsivity fully mediated the impact of financial literacy on debt, even after controlling for financial wealth, showing its significant influence on debt decision-making. Frigerio et al. ( 2020 ) carried out a meta-analysis of existing studies to assess whether higher levels of impulsivity are associated with greater indebtedness, finding a significant positive association between them; and that type of over-indebtedness and professional status significantly moderated this association. Singh & Malik ( 2022 ), in proposing a financial vulnerability index, indicate that greater financial knowledge, better money management skills and lower impulsivity in financial behavior can reduce vulnerability Other studies mentioned in the previous clusters also provide results on the influence of impulsivity on indebtedness, such as Wang et al. ( 2011 ); Achtziger et al. ( 2015 ); Hamid & Loke ( 2021 ) and Ma & Yao ( 2023 ). Blue Financial literacy Li et al. ( 2013 ) analyzed the influence of complementary cognitive abilities on four measures of economic decision-making (temporal discounting, loss aversion, financial literacy and debt literacy) in older vs. younger participants, pointing out that the former performed as well or better than the latter in these decision-making measures. Gathergood and Weber ( 2017 ), when analyzing the interaction between financial literacy, present bias and choices about the type of mortgage repayment, point out that financial literacy increases the probability of choosing an adjustable-rate mortgage compared to a fixed-rate mortgage. Ganbat et al. ( 2021 ) when analyzing whether an individual's credit risk can be predicted on the basis of psychometric tests, found that positive scores on the tests of effective financial decision-making, self-control, conscientiousness, altruism and giving attitude, and attitude towards money enable individuals to access debt. Sekita et al. ( 2022 ) when analyzing the effects of five different types of financial literacy on wealth, indicates that deposit literacy, risk literacy and debt literacy have positive effects; inflation literacy and insurance literacy do not have significant effects; and several behavioral economics variables, such as overconfidence, self-control, myopia and risk aversion, are also significant determinants of wealth. Other studies mentioned in the cluster analysis also consider the influence of financial literacy on indebtedness or treat it as a control variable, such as Gathergood ( 2012 ); Li et al, ( 2013 ); Ottaviani & Vandone ( 2018 ); Ponchio et al. ( 2019 ); Atlas et al. ( 2019 ); Frigerio et al. ( 2020 ); Hamid & Loke ( 2021 ); Lea ( 2021 ); George & Leszczyszyn ( 2021 ); Singh & Malik ( 2022 ) and Fernández-López et al. ( 2023 ). Financial behavior Xiao et al. ( 2006 ) suggests that positive financial behaviors are positively associated with the level of economic and non-economic resources, reduce financial stress and increase financial satisfaction Atlas et al. ( 2019 ) examining how confidence in financial knowledge relates to credit card behaviors and financial satisfaction, finds that confidence is more strongly associated with credit card use and overall financial satisfaction as knowledge increases. Other studies mentioned in the cluster analysis also provide results on the influence of financial behavior on indebtedness, such as George & Leszczyszyn ( 2021 ); Rey-Ares et al. ( 2021 ); Vuković & Pivac ( 2021 ); Goyal et al. ( 2022 ) and Singh & Malik ( 2022 ). Self Control Webley & Nyhus ( 2001 ) show that psychological factors (especially current orientation, self-control and attitudes towards debt) improve the ability to predict indebtedness. Gul and Pesendorfer ( 2004 ), by extending the analysis of self-control in decision problems from two periods to an infinite horizon (a phenomenon they characterize as dynamic self-control preferences), conclude that increasing commitment while maintaining constant self-control increases the capital premium. Gathergood ( 2012 ), when investigating the relationship between self-control, financial literacy and over-indebtedness, points out that lack of self-control plays a more important role in explaining over-indebtedness than financial illiteracy. Achtziger et al. ( 2015 ) when investigating the links between self-control, compulsive buying and actual debts, reports that self-control is negatively related to debts and compulsive buying is positively related to debts. Vuković & Pivac ( 2021 ) report that people with greater self-control are more likely to save money and less likely to get into debt, and that there is a significant mediating effect of financial behavior on the relationship between self-control and financial security; Rey-Ares et al. ( 2021 ) point out that self-control influences individuals' financial attitudes regardless of generation, and that only millennials with higher levels of self-control are affected by it when deciding between a savings account or a personal loan, showing a potentially dangerous overconfidence in their financial management skills. Goyal et al. ( 2022 ) analyzed the association between personal financial management behavior and six psychological factors and identified, in the overall results, a significant positive association between personal financial management and self-control, and in the subgroup analysis, self-control (positively) and materialism (negatively) were significantly associated with personal financial management behavior among adults. Jia et al. ( 2023 ), when examining how extreme debtors evaluate their capacity for self-control, revealed that they have a low capacity to regulate their behavior, but maintain an illusory perception of high capacity, which may expose them to greater debt accumulation. Fernández-López et al. ( 2023 ) indicate that self-control problems lead to greater indebtedness, and its influence differs between credit options, where a lack of self-control increases the likelihood of taking out unsecured personal loans, loans from family or friends and credit card use. Other studies mentioned in the cluster analysis also provide results on the influence of self-control on indebtedness, such as Ponchio et al. ( 2019 ); Wang et al. ( 2011 ); Ganbat et al. ( 2021 ); Lea ( 2021 ) and Ma & Yao ( 2023 ). Materialism Ponchio et al. ( 2019 ) when investigating the impact of consumer spending self-control, personal savings orientation, materialism, financial knowledge and time perspective on the perception of financial well-being, found that time perspective moderates the effect of materialism on the current stress of money management and spending self-control mediates this relationship. Ma & Yao ( 2023 ), when investigating the factors influencing the use of Internet credit services among young adults considering reflexive and impulsive decision-making processes, indicate that immediate gratification and materialism positively affect the impulse to use, while self-control was identified as an impulse inhibitor. Other studies mentioned in the previous clusters also provide results on the influence of materialism on indebtedness, such as Goyal et al. ( 2022 ); Lea ( 2021 ); Landa-Blanco (2022) and Aydin ( 2022 ). Orange Mental Accounting Hirst et al. ( 1994 ) investigates the role that temporal contiguity (the co-occurrence of multiple outcomes) plays in mental accounting for consumer borrowing decisions. Prelec & Loewenstein ( 1998 ) propose a "double entry" theory of mental accounting that describes the nature of these reciprocal interactions between the pleasure of consuming and the pain of paying and highlights their implications for the consumer. It reports that the pain of paying plays an important role in consumer self-regulation. Hershfield et al. ( 2015 ) in examining three psychological barriers to the responsible use of credit and debt, discuss consumers' tendency to make wrong predictions about future consumption habits, rely too much on the figures shown on invoice statements and categorize debt and savings in separate mental accounts. Sussman & O'Brien (2016) point out that there is a tendency for people to preserve savings by taking out loans through a credit option with high interest rates. Swacha-Lech & Solarz ( 2019 ) indicate that the strongest determinants of mental accounting attitude are: having debt, having savings, debt aversion and the amount of monthly net income achieved. Both debt and high monthly net income increase the likelihood of adopting mental accounting attitudes, while the other factors have the opposite effect. Quispe-Torreblanca et al. ( 2019 ) found that repayment of debt contracted for non-durable goods is 10% more likely than repayment of debt contracted for durable goods. Argyle et al. ( 2020 ) when investigating three phenomena that he calls "monthly payment target", points out that many consumers (i) tend to manage the size of the payment when making decisions about debt; (ii) seem to use segregated mental accounts and; (iii) group themselves into round numbers of monthly payments, consistent with the budget heuristic. Sharma et al. ( 2021 ) introduce the concept of psychological ownership of borrowed money and show that framing debt using language lower in psychological ownership can reduce the propensity to take out loans. Silva et al. ( 2023 ) analyzed scientific production on the influence of mental accounting bias on decision-making processes, reporting numerous impacts on decisions related to savings, consumption, investment and debt. Other studies mentioned in the clusters also provide results on the influence of mental accounting on indebtedness, such as Baugh et al. ( 2021 ) and Rey-Ares et al. ( 2021 ). Not clustered Optimism Seaward & Kemp ( 2000 ) report that the tendency to overestimate future income is positively correlated with an individual's level of real debt. Overconfidence Boz & Mendoza ( 2014 ) point out that financial innovation and overconfidence in the risk of new financial products were key factors behind the 2008 credit crisis in the US. Framing Caetano et al. ( 2019 ) reports that debt aversion, the unwillingness to enter into a financial contract framed or labeled as debt, distorts household investment and financing decisions. Bauer et al. ( 2021 ), when investigating how interest-free financing promotions influence consumer behavior, shows that framing an economically equivalent financing offer in a way that makes it clear that it is interest-free increases consumer demand for credit to finance experiential, but not material, goods. Anchoring Porto et al. ( 2021 ), in examining the association between past borrowing experience and borrowing decisions, suggest what influences people's perception of how much to borrow to finance education: anchoring. Individuals suggest higher amounts to others based on their previous borrowing Analysis of the references of the articles in the BP Analyzing the references of the BP makes it possible to determine the historical roots of research areas or the works of decisive importance in a field (Marx & Bornmann, 2016 ). It makes it possible to identify seminal works, highly recognized by the literature and with a major impact on the study of the subject, prominent authors and their interrelationships. Figure 5 shows the network map of the most cited researchers in the BP references. As can be seen in Fig. 5 , the analysis of the relationship network between the works in the BP references showed that the studies by Gathergood ( 2012 ), Meier & Sprenger ( 2010 ), Achtziger et al. ( 2015 ), Wang et al. ( 2011 ), Norvilitis et al. ( 2003 ) and Lea et al. ( 1995 ), which are among the 12 most cited articles in the BP (Table 1 ), are also relevant in the BP references, demonstrating their relevance to research on indebtedness. In addition, the results obtained from the network map of the references made it possible to group them into three large clusters, highlighted by the colors gray, orange and blue. The gray cluster is made up of 5 papers investigating the interrelationships between financial literacy and indebtedness. Gathergood ( 2012 ) investigates the relationship between self-control, financial literacy and over-indebtedness in consumer credit debt, finding a greater role for lack of self-control than for financial illiteracy in explaining over-indebtedness. Lea et al. ( 1995 ) investigated various psychological variables as causes or effects of debt. Their results suggest that a complex of psychological and behavioral variables affect debt and are affected by it, that economic and demographic factors predicted the debt category well, that debtors had less money management facilities and shorter time horizons than non-debtors. Norvilitis et al. ( 2006 ) explored factors related to the causes and effects of credit card debt in university students. Their results indicate that lack of financial knowledge, age, number of credit cards, delay in gratification, and attitudes toward credit card use were related to indebtedness, and that students who reported greater debt reported greater stress and decreased financial well-being. Fernandes, Lynch, and Netemeyer ( 2014 ) analyzes the relationship between financial literacy and financial education with financial behaviors, concluding that interventions to improve financial literacy explain only 0.1% of the variance in the financial behaviors studied, with weaker effects in low-income samples and which decrease dramatically when controlling for psychological traits. Lusardi and Tufano ( 2015 ) analyzed the relationship between literacy and debt, pointing out that average literacy is low, a phenomenon that contributes to individuals carrying out high-cost transactions and excessive indebtedness. The orange cluster is made up of 4 studies that analyze self-control and its influence on indebtedness. Ameriks et al. ( 2007 ) analyzed self-control problems in a sample of adults with a high level of education, identifying that they tended to be smaller in scale in older interviewees than in younger ones. Wang et al. ( 2011 ) studied consumer credit card debt behavior in correlation with demographic factors, attitude, personality and credit card characteristics. Their results indicate that personality factors, self-control, self-esteem, self-efficacy, gratification postponement, internal locus of control and impulsivity are significantly correlated with the use of revolving credit; and that some credit card characteristics lead to an "illusion of income", facilitating debt behavior. Achtziger et al. ( 2015 ) investigates the links between self-control, compulsive buying and actual debt finding that self-control is negatively related to debt, compulsive buying is positively related to debt and the link between self-control and debt was fully mediated by compulsive buying. In the last paper in this cluster, Strömbäck et al. ( 2017 ) explored the effect of individual differences in self-control and other non-cognitive factors on financial behavior and financial well-being. Their results indicate that people with good self-control are more likely to save money in each paycheck, have better overall financial behavior, feel less anxious about financial matters and feel more secure in their current and future financial situation. The blue cluster is made up of 6 studies investigating aspects linked to the behavioral life cycle and intertemporal consumption. It includes the work of Shefrin & Thaler ( 1988 ), which incorporates the concepts of self-control, mental accounting and framing, introducing the concept of the Behavioral Life Cycle; and Laibson ( 1997 ), who, by analyzing hyperbolic discount functions, suggests that financial innovation may have caused the continuous decline in savings rates in the USA, since financial innovation increases liquidity, eliminating opportunities for compromise. Tangney et al. ( 2004 ) when analyzing individual differences in self-control, reported that higher self-control scores correlated with a higher grade point average, higher self-esteem, better relationships and interpersonal skills, reporting that low self-control is a significant risk factor for a wide range of personal and interpersonal problems. Meier & Sprenger ( 2010 ) test whether present-biased time preferences correlate with credit card borrowing. Their results indicate that present-biased individuals are more likely to have credit card debt and to have significantly higher credit card debt. Finally, Heidhues & Kőszegi ( 2010 ) analyzed loan repayment behavior considering individuals with preferences for immediate gratification. Their results indicate that unsophisticated individuals take out excessive loans, pay the fines and delay repayment, suffering large welfare losses. Therefore, in view of the importance of these studies for the study of the subject, it is suggested that they be consulted for the development of future work. Mapping the Evolution and Trends of Research on the Theme Mapping the Evolution of Research on the Theme In this section we present the evolution of the keywords used in studies investigating the interrelationships between behavioral biases and personal indebtedness that make up the BP. A preliminary analysis of the data using the bibliometrix indicates that terms such as "self-control", "impulsivity" and "mental accounting" have continued over the last 10 years, showing themselves to be recurring themes; and terms such as "determinants", "materialism" and "life cycle" have appeared in the last 5 years, showing themselves to be emerging themes. A complementary analysis can be carried out using the results illustrated in Fig. 6 . Figure 6 illustrates, based on BP data, the main topics covered by researchers in the last 10 years (2014 to 2023) and the average frequency of their occurrence over the period analyzed, which can be seen by the shade of the circle that makes it up. The higher the red shade, the closer its relative frequency is to the current years (2023), and the bluer it is, the closer it is to 2014. Based on the results presented in Fig. 6 , it can be seen that themes such as "determinants", "materialism", "life-cycle", "financial literacy", "overconfidence", "self-control" and "mental accounting" are quite current in research related to analyzing the influence of behavioral biases on personal indebtedness, three of them ("life-cycle", "self-control" and "mental accounting") are related to the behavioral life-cycle theory (BLC) proposed by Shefrin & Thaler ( 1988 ), previously reported in the preliminary analysis as an emerging theme. Terms such as "personality" and "liquidy constraints" appear shortly afterwards. These results suggest that future work could analyze issues related to indebtedness by combining some of these descriptors with others from different areas of knowledge. In particular, combinations of terms such as "life-cycle", "overconfidence", "self-control", "mental accounting" and "materialism" (from the field of behavioral sciences), with terms such as "financial literacy" (from the field of education/knowledge), and "personality" (from the field of psychology/behavior) could make interesting contributions to the literature that seeks to investigate aspects related to personal indebtedness. Discussions The results found in the previous sections, together with the characteristics of this research, provide important information on the state of the art and interesting insights for future research on the subject. Firstly, with regard to the main works in this area of knowledge, our results show that the research by Prelec & Loewenstein ( 1998 ), Gul and Pesendorfer ( 2004 ), Norvilitis et al. ( 2003 ), Meier & Sprenger ( 2010 ) and Gathergood ( 2012 ) make an important contribution to the study of the subject, with the latter two also featuring prominently in BP references. At another point, the network analysis between the keywords (Fig. 4) illustrates that studies on the topic are concentrated in three clusters: (i) works that analyze the interrelationships between debt, credit, money management, restriction liquidity, consumer behavior and finances and impulsivity; (ii) works that analyze the interrelationships between debt, financial literacy, financial behavior, self-control and materialism and; (iii) works that analyze the interrelationships between debt and mental accounting; in addition to works that analyze the interrelationships between debt and behavioral biases, such as optimism, overconfidence, framing and anchoring.. A third point, and perhaps the most important contribution of this research to the literature investigating issues related to indebtedness, is to understand how indebtedness (and its levels) has been discussed and the main metrics for measuring it (degree of indebtedness). The analysis of the content of the articles allowed us to identify that there are many approaches to defining and measuring indebtedness and over-indebtedness: the economic dimension (the ability to repay the debt); the temporal dimension (medium or long-term time horizon); the social dimension (the need to substantially reduce the expenses that have to be paid before the debt is repaid); and the psychological dimension (stress caused by over-indebtedness). It also showed that, as it is a complex and multidimensional phenomenon, there is no agreed definition of over-indebtedness in the literature, and likewise, there is no consensus on how to measure it (Blázquez et al., 2020; Wałęga & Wałęga, 2021 ; Leandro & Botelho, 2022 ). Thus, based on the results of the content analysis of the articles analyzed, inspired by Betti et al. ( 2007 ); Gathergood ( 2012 ); Wałęga & Wałęga ( 2021 ); Leandro & Botelho ( 2022 ), we present Fig. 7 , which illustrates, in a pictographic scheme, the possible definitions of indebtedness from an economic and psychological perspective (dimension). Looking at the concepts of indebtedness listed in Fig. 7 , it can be seen that the recognition of indebtedness, from an economic and accounting point of view, is related to the existence of future obligations, and as its representativeness in relation to some financial parameter (such as revenue or equity, for example) rises to an increasingly higher result (index), there is a shift from a situation of indebtedness to the recognition of a situation of over-indebtedness. Looking at it from a psychological point of view, a person usually tends to consider themselves in debt as the level of difficulty in paying off the debt rises, i.e. it is positively related to the inability to pay and the pain (feeling) and realization of default. It can be seen that there is a dissonance between the idea of indebtedness based on the two points of view. In this sense, a person with their accounts up to date, when questioned about the existence of debt, would tend to refute this possibility, unless there is some overdue commitment. People tend to consider themselves indebted not if they have high debts, but if they have commitments that are difficult to pay (default). This dissonance between economic and psychological (mental) recognition of debt can be quite disastrous. Take, for example, an individual who, from an economic point of view, has a high amount of debt (financial commitments) and a high "debt/income" ratio, and has no contingency reserve; and psychologically, has a low recognition of the debt situation, provided by their ability to pay their commitments when they fall due (high current liquidity). This profile brings with it a strong vulnerability, especially in a situation of economic crisis or imminent job loss. This shows the importance of the assumptions of the behavioral sciences and cognitive biases, especially the mental accounting bias, self-control, overconfidence and optimism, in studies on indebtedness. The literature reviewed highlights Mental Accounting as a prominent cognitive bias in relation to individuals' indebtedness. This bias causes a dissonance between the pleasure of consuming and the pain of paying (Prelec & Loewenstein, 1998 ), leading people to make mistaken predictions about future consumption (Hershfield et al., 2015 ), mainly due to the fact that they can accumulate savings and get into debt at the same time (Sussman & O'Brien, 2016). In this sense, the decision to consume and go into debt is influenced by the mental accounting bias (Argyle et al., 2020 ), which can lead to errors in judgment and financial losses. In addition, in a less clustered way, optimism, overconfidence, framing and anchoring appear as biases that influence indebtedness. Optimism can lead to an overestimation of income and therefore increase the level of debt (Seaward & Kemp, 2000 ). On the other hand, overconfidence can lead individuals to allocate their resources to risky assets, increasing their indebtedness (Boz & Mendoza, 2014 ). Framing influences indebtedness based on the way in which debt contracts are presented (Caetano et al., 2019 ), causing the individual to make mistaken decisions due to the fact that the embedded interest does not materialize (Bauer et al., 2021 ). Finally, the anchoring bias causes people to anchor themselves in past experiences in order to take on current debts (Porto et al., 2021 ), which can negatively influence the relationship between consumption and indebtedness. Lastly, the network analysis of the keywords (Fig. 4) together with the temporal analysis of their occurrence (Fig. 5 ) made it possible to identify themes with greater continuity over the years and more recent research themes on the interrelationships between behavioral biases and individual indebtedness. We observed a trend of studies relating cognitive biases to indebtedness and, although the study of cognitive biases has been growing in the area of behavioral economics (Costa et al., 2017 ), the results point to gaps to be filled in relation to indebtedness. Thus, future work could analyze issues related to indebtedness by combining some of these descriptors with others from different areas of knowledge. In particular, combinations of terms such as "life-cycle", "overconfidence", "self-control", "mental accounting" and "materialism" (from the area of behavioral sciences), with terms such as "financial literacy" (from the area of education/knowledge), and "personality" (from the area of psychology/behavior) tend to expand the literature that seeks to investigate aspects related to personal indebtedness. As there are structural, economic and cultural disparities around the world (Tomar et al., 2021 ), future work could expand these analyses (combination of descriptors) by considering various regions, such as emerging countries vs. developed countries, investigating whether the factors identified in relation to the former are also relevant to the latter. Another interesting research gap would be to expand the findings on the interrelationships between mental accounting, financial literacy and indebtedness. Baker et al. ( 2019 ) shows that financial literacy has a positive relationship with mental accounting bias. Gathergood ( 2012 ); Flores & Vieira ( 2014 ); Mahdzan et al. ( 2023 ) point out that the level of financial literacy has an inverse relationship with indebtedness. It follows from this logic that mental accounting, since it has a positive relationship with financial literacy, would tend to have a negative impact on indebtedness. On the contrary, studies report the tendency of consumers to categorize debts and savings in separate mental accounts (Hershfield et al., 2015 ) and that adopting this narrow mental accounting attitude tends to favor indebtedness Swacha-Lech & Solarz ( 2019 ). Mental accounting has a significant positive influence on savings decisions (Tetteh & Boachie, 2021 ) and interacts in the process in which people take on debts with high interest rates while maintaining savings that yield low levels of interest (Sussman & O'Brien, 2016). In this context, adopting mental accounting attitudes tends to promote the achievement of savings goals, but in contrast, results in the need to take out loans, that is, to get into debt Swacha-Lech & Solarz ( 2019 ). Given the still inconclusive results regarding the influence of mental accounting on debt, and that people can group a set of decisions in a broad way (evaluating the possible consequences of all choices together) or in a restricted way (evaluating each decision separately), which Read et al. (1999) call “choice buckets” (Pleßner, 2017 ), future work could investigate determining and moderating factors in this relationship. Conclusions In view of the persistent increase in the levels of indebtedness of individuals seen in world economies, this work aimed to review the existing literature on the interrelationships between behavioral biases and personal indebtedness, with a view to learning about the current state of the literature on the subject, currents and main results, and identifying opportunities for future research. The bibliometric analysis of the selected articles indicates the influence of works such as Prelec & Loewenstein ( 1998 ); Meier & Sprenger ( 2010 ); Gathergood ( 2012 ); Gul and Pesendorfer ( 2004 ); Norvilitis et al. ( 2003 ); Achtziger et al. ( 2015 ); Xiao et al. ( 2006 ); Webley & Nyhus ( 2001 ); Li et al. ( 2013 ); Wang, Lu, & Malhotra ( 2011 ); Boz & Mendonça (2014) and Ottaviani & Vandone ( 2011 ) in research on the subject, which represent more than 80.5% of global citations. This shows the significant impact of these works on the literature on the relationship between behavioral biases and indebtedness. The analysis of the bibliographic coupling of the papers made it possible to identify 3 distinct clusters of research in the area: (i) papers analyzing the relationship between mental accounting, liquidity restrictions and the influence of credit cards on personal indebtedness; (ii) papers analyzing the determinants of indebtedness considering the influence of financial literacy, financial behavior, self-control and materialism, and; (iii) papers analyzing the relationship between impulsiveness, money management and indebtedness. In addition, the bibliometric analysis of the references of the articles that make up the BP revealed three major clusters of research investigating the relationship between personal indebtedness and (i) financial literacy; (ii) self-control and (iii) behavioral life cycle and intertemporal consumption. It also made it possible to verify that the studies by Meier & Sprenger ( 2010 ), Gathergood ( 2012 ), Achtziger et al. ( 2015 ), Wang et al. ( 2011 ), Lea et al. ( 1995 ), which are among the 12 most cited articles in the BP, also play a relevant role in the references of the BP, which is why they should also be considered in future research on the subject. An analysis of the content of the articles revealed that there are many approaches to defining, measuring and explaining indebtedness and over-indebtedness: the economic dimension; the temporal dimension; the social dimension; the psychological dimension and the behavioral dimension. As far as the behavioral dimension is concerned, some biases have stood out, such as mental accounting, optimism, overconfidence, framing and anchoring, bringing interesting results to the literature, such as the tendency of individuals to categorize debt and savings in separate mental accounts, to present dissonance between the pleasure of consuming and the pain of paying, to overestimate their income (and overconfidence in its maintenance/elevation) vs. underestimating or not considering their level of financial commitment and other aspects related to the psychological ownership of money.. The mapping of the evolution and trends of research on the subject pointed to themes such as "determinants", "materialism", "life-cycle", "financial literacy", "overconfidence", "self-control" and "mental accounting" as very current in related research, along with "personality". In view of these results, it is hoped that a fertile field for future work can emerge from combinations of terms from the field of behavioral sciences, such as "life-cycle", "overconfidence", "self-control", "mental accounting" and "materialism", together with terms from the field of education/knowledge and psychology/behavior, such as "financial literacy" and "personality". Investigating issues related to indebtedness by combining these descriptors, considering various regions, such as emerging countries vs. developed countries, is a fertile field for future study. Another research gap is to investigate the relationships between financial literacy, mental accounting and indebtedness, identifying moderating factors. Finally, the work has limitations in terms of its application, one of which concerns the choice of scientific databases used, which tends to have a huge influence on the final result of the mapping and subsequent analysis, as they reflect the characteristics of their underlying databases (Stahlschmidt & Stephen, 2022 ), the search criteria used, and the limitations of processing a very large amount of information by researchers, given the immensity of the number of publications. This implies that we may not have considered other studies that could complement our analysis. Future work could therefore seek to integrate various databases in order to mitigate this limitation. List Of Abbreviations BP: Bibliographic Portfolio (BP) Proknow-C: Knowledge Development Process - Constructivist. References Achtziger, A., Hubert, M., Kenning, P., Raab, G., & Reisch, L. (2015). Debt out of control: The links between self-control, compulsive buying, and real debts. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4510972","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":309241932,"identity":"434d32cd-00ae-4d3f-81c0-90860a808d42","order_by":0,"name":"Emmanuel Marques 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Costa","email":"","orcid":"https://orcid.org/0000-0001-6322-5280","institution":"IFMG","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"Fonseca","lastName":"Costa","suffix":""},{"id":309241934,"identity":"219f5013-dd40-4905-ac2a-1d05c799f69d","order_by":2,"name":"Patricia Maria Bortolon","email":"","orcid":"https://orcid.org/0000-0001-8087-3837","institution":"UFES","correspondingAuthor":false,"prefix":"","firstName":"Patricia","middleName":"Maria","lastName":"Bortolon","suffix":""}],"badges":[],"createdAt":"2024-05-31 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theme.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4510972/v1/77644eee9fd1c0787d1a6aeb.png"},{"id":57706305,"identity":"9ab655df-948f-4035-a2cd-c6b5c02cf1f1","added_by":"auto","created_at":"2024-06-04 14:55:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":113531,"visible":true,"origin":"","legend":"\u003cp\u003eComposition of BP articles ordered by number of global citations and their stratum by period\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4510972/v1/9582f6d434eb96cac2c6836b.png"},{"id":57706918,"identity":"08c32335-b389-47bf-918c-8e7958bab674","added_by":"auto","created_at":"2024-06-04 15:03:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":862768,"visible":true,"origin":"","legend":"\u003cp\u003eBP article network maps\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4510972/v1/f983e02934e792e613de5fbc.png"},{"id":57706313,"identity":"44c40f80-32c9-4907-89c4-9a01ec623f14","added_by":"auto","created_at":"2024-06-04 14:55:26","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1046672,"visible":true,"origin":"","legend":"\u003cp\u003eBP Conceptual Structure Map.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4510972/v1/7389415aaa28db0a865c5a67.png"},{"id":57706310,"identity":"2d3d2151-1cf0-4e4d-9c66-f8030323e212","added_by":"auto","created_at":"2024-06-04 14:55:26","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":575101,"visible":true,"origin":"","legend":"\u003cp\u003eArticles by the most prominent references in the BP and their network of relationships.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4510972/v1/6901431894294af200e01ac7.png"},{"id":57706307,"identity":"89f708df-0086-4417-87cb-14fbeb79c3f0","added_by":"auto","created_at":"2024-06-04 14:55:25","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":261525,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution and trends in the topics of interest in research on \"behavioral biases and personal indebtedness\".\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4510972/v1/22b53d8e534b72fc8ea65ad0.png"},{"id":57707485,"identity":"88cee91d-961f-40ea-8613-1224bfc8dbed","added_by":"auto","created_at":"2024-06-04 15:11:26","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":35256,"visible":true,"origin":"","legend":"\u003cp\u003eDebt frontier from an economic \u003cem\u003evs.\u003c/em\u003e psychological perspective\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-4510972/v1/d27212426229a4c584301f6b.png"},{"id":57708527,"identity":"a12baaf9-b1c5-4ec3-b874-7abddf92c8ce","added_by":"auto","created_at":"2024-06-04 15:19:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3597508,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4510972/v1/9b67af62-da43-4192-84d8-9f91a9b59b62.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eBehavioral biases and personal indebtedness: a systematic literature review\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn recent decades, the world economy has witnessed a persistent increase in individuals' levels of indebtedness, making debt a persistent feature of household balance sheets at all stages of life (Leandro \u0026amp; Botelho, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). As it is an important aspect in many countries and, in extreme situations, constitutes a threat not only to the financial stability of families, but also a precursor to economic and financial crises, understanding issues related to indebtedness is a relevant aspect for companies, the economy, governments and society (Guti\u0026eacute;rrez-Nieto et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Almenberg et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Šubov\u0026aacute; et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIndebtedness is the process in which individuals commit a significant portion of their income in order to honor it in the future and which, in more extreme situations (excessive indebtedness), can generate a situation in which the individual becomes unable to pay their debts with the income they receive, characterizing over-indebtedness (Pacheco et al., 2018).\u003c/p\u003e \u003cp\u003eAn interesting feature about indebtedness emerges from this concept: there is a significant difference between the accounting concept of indebtedness and its cognitive (mental) recognition. From an accounting point of view, indebtedness consists of assuming obligations (debts) in the present which are expected to be paid off in the future. On the other hand, there are cognitive aspects that assume that the individual will only recognize debt when there is difficulty in honouring the obligation. At this point, indebtedness is influenced by the level of coupling between consumption and payment and by the psychological ownership of borrowed money (Prelec \u0026amp; Loewenstein, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Sharma et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinance has always played a critical role in economies, as it is at the center of consumption, savings and investment decisions by individuals, companies and governments (Claus \u0026amp; Krippner, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this context, the scientific literature has been trying over the years to understand what leads individuals into debt and how to mitigate it using traditional economic approaches (Zerrenner, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Keese, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and to understand how behavioral economics, whose approach combines psychological, cognitive and behavioral foundations with economic factors (Costa et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) influences the individual's behavior when taking on and managing debt (Flores \u0026amp; Vieira, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Swacha-Lech \u0026amp; Solarz, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sharma et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSince individual over-indebtedness is an interdisciplinary, complex and multifaceted phenomenon, where no single set of characteristics is sufficient to explain it worldwide (Bl\u0026aacute;zquez et al., 2020; Leandro \u0026amp; Botelho, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and behavioral finance serves as a complement to classical finance, introducing behavioral aspects into decision-making (Aguirre \u0026amp; Aguirre, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), studies that analyze the determinants of personal indebtedness from the perspective of the behavioral sciences (economics and behavioral finance) bring valuable insights and expand the literature, with a strong contribution to the field of public policy.\u003c/p\u003e \u003cp\u003eIn view of the above, this research aims to investigate the intellectual structure of publications on the influence of behavioral biases on the level of personal indebtedness, in order to expand knowledge on the subject. As a result, we hope to answer the following questions: (i) which are the main works and authors with significant contributions to this area of knowledge?; (ii) how are the studies concentrated (clusters)?; (iii) how has indebtedness been discussed from a behavioral perspective?; (iv) what are the main cognitive biases associated with indebtedness? and; (v) what are the trends and research gaps in this field of knowledge?\u003c/p\u003e \u003cp\u003eThis is a descriptive study, using a structured and systematized bibliometric approach using the \"Proknow-C\" tool, which tends to minimize the use of randomness and subjectivity in the literature review process (Afonso et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The relevance of this study is based on the fact that (i) it investigates a problem (indebtedness) that directly affects people's lives; (ii) the importance of studies that examine the factors that influence the increase in indebtedness (Gathergood, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); (iii) the growing increase in levels of indebtedness seen in Brazil and worldwide (Leandro \u0026amp; Botelho, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and; (iv) for exploring the contribution of behavioral economics and finance in this field of knowledge.\u003c/p\u003e\n\u003ch3\u003eTheoretical Background\u003c/h3\u003e\n\u003cp\u003eDebt can be understood as an amount of money lent between parties, with the condition that the amount lent by the creditor is later repaid by the debtor. It is a financial device commonly used when current savings or income are inadequate for desirable purchases or for urgent payments and survival (Hiilamo, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDebt can be conceptualized in various ways. Under an economic lens, it is shown as an instrument whose purpose is to balance consumption over time, which under certain assumptions, has a positive effect on one's \"well-being\" (Zinman, \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Under a sociological lens, it can be understood as an unbalanced and distinct social arrangement between a creditor and a debtor, characterized by an obligation to repay in the future (Hiilamo, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDebt is a planned and rational decision that allows for the intertemporal redistribution of consumption (Guti\u0026eacute;rrez-Nieto et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It refers to the financial situation resulting from the act of taking on or contracting debts, i.e. it is the sum of the amount of money that a person or company owes to third parties (accumulated debts). It differs from the concept of debt in that, while debt, from a financial point of view, represents a specific monetary value that a person has to pay someone for an obligation; indebtedness is a broader measure of the total debts that an entity has in relation to some financial parameter, such as revenue or equity (Betti et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Leandro \u0026amp; Botelho, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Thus, according to the ratio (debt/revenue or debt/equity, for example), the degree of indebtedness of an entity (company or individual) can be considered low, medium or high.\u003c/p\u003e \u003cp\u003eOn another point, excessive indebtedness can result in default, which occurs when indebted individuals are unable to pay their debts on time. The continuous increase in indebtedness has an impact on individuals' ability to pay and, at its most advanced stage, can result in them being unable to pay their current credit repayments and other commitments without reducing their spending below the normal minimum levels, a situation which characterizes over-indebtedness (Brennan \u0026amp; Gallagher, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Overall, people are considered over-indebted if they are having difficulties meeting (or are falling behind with) their household commitments, whether these relate to servicing secured or unsecured borrowing, or to payments of rent, utility or other household bills (Bl\u0026aacute;zquez et al., 2020).\u003c/p\u003e \u003cp\u003eAccording to Katona (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1975\u003c/span\u003e) there are three reasons why individuals spend more than they earn: (i) low income, so they can't even cover essential expenses; (ii) high income, combined with a strong desire to spend; and (iii) a lack of desire to save (regardless of income). This illustrates that the \"spending function\" goes far beyond subjective expected utility, but is influenced by other factors, especially behavioral ones. In this context, it can be seen that behavioral economics can be useful both for identifying the causes of excessive indebtedness and for dealing with it (Daura, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrevious studies evaluating the determinants of personal indebtedness have shown that the pain of paying plays an important role in consumer self-regulation (Prelec \u0026amp; Loewenstein, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1998\u003c/span\u003e); that individuals with present bias are more likely to have credit card debt (Meier \u0026amp; Sprenger, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); that successful money management reduces the willpower needed to control financial behavior and helps prevent and combat over-indebtedness (Kamleitner et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2011\u003c/span\u003e); that individuals' impulsiveness when making decisions has a significant influence on indebtedness (Ottaviani \u0026amp; Vandone, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e); that a lack of self-control and financial illiteracy are positively associated with excessive indebtedness (Gathergood, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); that there is a significant difference in the level of indebtedness according to age, gender, marital status, education, religion, religious principles, occupation, household income, credit card and credit addiction (Flores \u0026amp; Vieira, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e); that impulsivity fully mediates the impact of financial literacy on debt (Ottaviani \u0026amp; Vandone, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); that overconfidence has been associated with a series of negative financial behaviors and outcomes (Atlas et al., 2019); and that people who are overconfident in their financial abilities tend to borrow more than less confident individuals (Hauff \u0026amp; Nilsson, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the field of the psychology of money, Webley \u0026amp; Nyhus (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) show that while economic variables alone predict debt very well, psychological factors (especially current orientation, self-control and attitudes towards debt) improve the ability to predict debt. Hershfield et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) examined three psychological barriers to the responsible use of credit and debt and pointed to the tendency for consumers to categorize debt and savings in separate mental accounts. Corroboratively, Sussman \u0026amp; O'Brien (2016) also point out people's tendency to preserve savings by borrowing from a credit option with a high interest rate. In this context, Swacha-Lech \u0026amp; Solarz (\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) indicate that the strongest determinants of mental accounting attitude are: having debt, having savings, debt aversion and the amount of monthly net income achieved. Sharma et al. (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) introduce the concept of psychological ownership of borrowed money, which represents the extent to which consumers feel that borrowed money is theirs, and report that framing debt using language with lower psychological ownership can reduce consumers' propensity to borrow. These papers illustrate how the psychology of money and mental accounting can influence the propensity for and maintenance of personal indebtedness.\u003c/p\u003e \u003cp\u003eWith regard to systematic literature reviews, the results of Leandro \u0026amp; Botelho (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) point out that (i) over-indebtedness is an interdisciplinary, complex and multifaceted phenomenon; (ii) the antecedents of over-indebtedness can be related to the consumer, creditors or the macro-environment; and (iii) over-indebtedness is multi-causal and the associated problems rarely manifest themselves in isolation. Finally, they propose directions for future research through questions aimed at analyzing topics that interrelate indebtedness with (i) antecedents, (ii) results, (iii) theoretical foundations, (iv) methods, (v) personal bankruptcy, (vi) regulation and (vii) prevention and mitigation.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis research uses an exploratory, descriptive and bibliographical approach to explore the intellectual structure of publications that analyze the determinants of personal indebtedness from the perspective of behavioral sciences. The main aim is to understand the current state of research on the subject, gaps and trends, and to identify, according to the results of the studies analyzed, which behavioral biases are most aligned with the propensity to personal indebtedness. To this end, we used the systematic literature review (SLR) strategy through bibliometric analysis, using a combination of three instruments: the \"Proknow-C\" methodology, the \"VOSviewer\" software together with the bibliometrix programming language package applied to the \"R\" software, and the Microsoft Excel spreadsheet.\u003c/p\u003e \u003cp\u003eBibliometric research is a variant of systematic literature reviews that involves applying quantitative and statistical techniques to bibliographic data, characterizing it as an appropriate method to demonstrate the research shape and activity, volume and growth in a specific discipline (Donthu et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Alam et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mukherjee et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Bibliometric analyses aim to uncover the intellectual heritage of a field and depict temporal trends based on the distribution of publications in a scientific discipline (Eulerich et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It is used to identify emerging trends in the performance of articles and journals, patterns of collaboration and research constituents, and to explore the intellectual structure of a specific domain in the existing literature. In this way, the bibliometric technique proves to be a suitable instrument for the objectives of this work.\u003c/p\u003e \u003cp\u003eIn the case of the tools used, their choice is justified by three main reasons. Firstly, the \"Proknow-C\" methodology was chosen because it is a structured and systematic process which tends to minimize the use of randomness and subjectivity in the literature review process (Afonso et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), and which helps to select and critically review the literature according to the researcher's perceptions and delimitations (Valmorbida, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSecondly, in the case of \u0026ldquo;VOSviewer\u0026rdquo; and bibliometrix, the choice was made due to the high degree of adaptability in changing and updating these tools, allowing the import of input data from various sources, including Scopus and Web of Science, and their potential to offer complete data processing for use in a variety of network analysis tools as they are tools that aim to assist bibliometric and network analysis, and for these reasons are widely used in bibliometric research (Jain et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Silva et al., 2023). VOSviewer stands out for its ease of use and multiple features, which include specific clustering and natural language processing techniques (Ordu\u0026ntilde;a-Malea \u0026amp; Costas, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); bibliometrix, for being an open source tool that allows the visualization of networks and has features that provide support for carrying out a comprehensive analysis of scientific mapping (Aria \u0026amp; Cuccurullo, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Donthu et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In addition, the Microsoft Excel spreadsheet was used as a tool for generating specific figures (graphs).\u003c/p\u003e \u003cp\u003eThe search process was carried out in the scientific databases \"Scopus\" and \"Web of Science\", as they are two prominent databases for peer-reviewed published research articles widely used in bibliometric analysis (Aria and Cuccurullo, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Alam et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), delimiting it in the areas of knowledge: (i) Economics, Econometrics and Finance, (ii) Business, Management and Accounting, (iii) Psychology, Multidisciplinary, Applied, Experimental and Social Psychology; and (iv) Neurosciences and Behavioral Sciences.\u003c/p\u003e \u003cp\u003eFinally, to quantify the scientific relevance of each publication, we used the \"google scholar\" tool, a platform that has an automatic tracking algorithm that extracts bibliographic data, citations and other information on academic articles from various sources, which can be used for metrics relating to publications, citations, among other information (Singh et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). It was used because, although the databases used to search for articles (Scopus and Web of Science) also provide information on the number of citations separately, it would not be possible to assess the concurrence of citations between them, or even citations with other databases (Silva et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eProcedures for selecting articles aligned with the research theme and forming the BP\u003c/h2\u003e \u003cp\u003eThe procedures described in the selection stage of the publications that will make up the bibliographic portfolio (BP) for this research were carried out in October 2023. The selection of scientific articles began with the definition of the main \"thematic axes\" (\"personal indebtedness\" and \"behavioral sciences\") and the search period, which encompassed all scientific production up to October 2023.\u003c/p\u003e \u003cp\u003eOnce the thematic axes had been defined, we unfolded the keywords to be used to carry out the searches in the \u003cem\u003e\"Scopus\"\u003c/em\u003e and \u003cem\u003e\"Web of Science\"\u003c/em\u003e databases: on the debt axis, the term \u003cem\u003e\"*debt\";\u003c/em\u003e on the behavioral sciences axis, including behavioral biases, the terms \u003cem\u003e\"behavioral finance\"; \"behavioral economics*\"; \"behavioral bias\"; \"anchoring\"; \"confirmation\"; \"endowment effect\"; \"framing\"; \"herding\"; \"impulsivity\"; \"loss aversion\"; \"mental account*\"; \"optimism bias\"; \"overconfidence\"; \"present bias\"; \"recency\"; \"regret aversion\"; \"representativeness\"; \"self-control\"\u003c/em\u003e and \u003cem\u003e\"sunk costs\".\u003c/em\u003e The combinations used in the search and the filtering process up to the formation of the BP are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the criteria used for the initial search generated a \"raw article database\" with 1,268 publications. The time horizon of the search includes all publications up to October 2023. With the insertion of additional filters, the number of publications changed in the following proportion: when inserting the area of knowledge (\u003cem\u003e\"Economics\", \"Econometrics and Finance\", \"Social Sciences\", \"Business\", \"Management and Accounting\", \"Psychology Multidisciplinary, Applied, Experimental and Social\"; \"Decision Sciences\", \"Neurosciences\" and \"Behavioral Sciences\"\u003c/em\u003e), 1,027 publications; and when inserting the type of publication (articles only), 881 publications.\u003c/p\u003e \u003cp\u003eOnce the 881 articles aligned with the theme of this research had been selected, screening was carried out. From this number, it was possible to identify that the interaction between the search parameters used returned 194 duplicate items, which were excluded from the database. Next, the titles of the 687 articles in the updated database (with no duplicates) were read to see if they were aligned with the subject under investigation. This procedure showed that, although the descriptors used in the search were aligned with the scope of the research, many articles dealt with different topics, such as \"real estate performance\", \"capital structure decisions\", \"cost of debt\", \"accounting conservatism\", \"accrual and debt\", among others. Once these were excluded, the process returned 145 articles that were highly related to the object of study.\u003c/p\u003e \u003cp\u003eOnce we had the 145 articles, we searched for the number of citations using the Google Scholar platform, sorting them in descending order. The purpose of this process was to verify the scientific relevance of each article, based on the \"number of citations\" parameter. Once the search had been carried out, the sample was divided into two large groups using the Pareto Principle: (i) 20% of the articles with high representativeness in terms of number of citations, which became \"K Repository\"; and (ii) 80% of the articles with a low number of citations, forming \"P Repository\".\u003c/p\u003e \u003cp\u003eOf the 33 abstracts in \"K Repository\", 23 articles were selected to form the core of the BP on the subject of \"behavioral biases and personal indebtedness\", as they were aligned with the objective of this research. These became \"A Repository\", made up of articles that have three main characteristics: (i) their abstract is aligned with the research topic; (ii) they have a relevant volume of citations that places them among the 80% most cited; and (iii) their abstract is accessible. The articles in \"A Repository\" were used as criteria for evaluating the other 112 less cited articles (\"P Repository\").\u003c/p\u003e \u003cp\u003eThe next step was to analyze the articles in \"P Repository\" according to the criteria set out in the Proknow-C methodology. To be selected for the BP, the articles in \"Repository P\" must meet two requirements: (i) they must have been published less than 2 years before the analysis (for this item, the years 2021 and 2022 were considered, including the months of 2023) and; (ii) if they were published more than 2 years ago, they must necessarily be by a researcher whose authorship is present in the group of articles selected for \"A Repository\".\u003c/p\u003e \u003cp\u003eAnalyzing the articles in \"P Repository\", it was found that 47 articles were published less than 2 years ago and, of the 65 articles published before 2021 in this repository, 15 are by authors in \"Repository K\". Thus, 62 articles were selected for the \"reweighting\" stage, forming \"Repository B\". After reading the articles in the latter repository, only 27 abstracts were found to be aligned with the research topic. As a final procedure, \"Repositories\" A (23 articles) and B (27 articles) were combined to form a BP with 50 articles.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eBibliometric Analysis of the Bibliographic Portfolio (BP)\u003c/h2\u003e \u003cp\u003eIn this section, we present the results of the bibliometric analysis of the BP, divided into two large blocks: analysis of the articles in the BP and analysis of the articles in the BP references.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of BP articles\u003c/h2\u003e \u003cp\u003eAnalysis of the most prominent articles in the BP in terms of number of global citations\u003c/p\u003e \u003cp\u003eThe summary of the results of the articles selected to make up the BP in descending order of the number of global citations (\u003cem\u003egoogle scholar\u003c/em\u003e), their representativeness and their temporal stratification can be seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBased on the results illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, a first analysis shows that most of the articles in the BP (76%) were published in the last decade. This is mainly due to the growing interest of researchers in investigating the topic of \"behavioral biases and personal indebtedness\" in recent years.\u003c/p\u003e \u003cp\u003eWith regard to the representativeness of the BP articles, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the prominence of some articles, considering the number of overall citations. Taking the 50 BP articles as a basis, it can be seen that the 5 most cited articles represent more than half (59.2%) of the total number of citations; and the 12 most cited, more than 80.5%. This shows the relevance of these works to the study of the subject. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates a summary of the main findings of these studies.\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\u003eMain results of the most prominent works on indebtedness based on the number of global citations.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSummary with main results\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAuthors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIt proposes a \"double entry\" theory of mental accounting that describes the nature of these reciprocal interactions between the pleasure of consuming and the pain of paying and highlights their implications for the consumer.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrelec \u0026amp; Loewenstein (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1998\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoints out that gift-biased individuals are more likely to have credit card debt and to have significantly higher credit card debt, controlling for disposable income, other sociodemographic data and credit constraints\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMeier \u0026amp; Sprenger (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2010\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIt reports that lack of self-control and financial illiteracy are positively associated with non-payment of consumer credit and excessive financial debt burdens. Lack of self-control plays a more important role in explaining consumer over-indebtedness than financial illiteracy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIt proposes an alternative approach to incorporate experimental evidence related to time preferences regarding the exponential discounting phenomenon. They argue that increasing the preference for commitment while keeping self-control constant increases the capital premium.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGul e Pesendorfer (2004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExplores the relationships between financial attitudes, impulsivity, locus of control, life satisfaction and stress and their effects on credit card debt levels in university students. Indicates that personality variables are generally not related to the level of debt, although they are related to attitudes towards money.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNorvilitis et al. (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2003\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExplores the links between self-control, compulsive buying and debt. They indicate that self-control is negatively related to debt, while compulsive buying is positively related to debt, where the link between self-control and debt is completely mediated by compulsive buying.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAchtziger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnalyzes, in a sample of consumers who use credit counseling services, the relationship between positive financial behaviors and the level of economic and non-economic resources, stress and financial satisfaction. They suggest that positive financial behaviors are positively associated with the level of economic and non-economic resources, reduce financial stress and increase financial satisfaction.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eXiao et al. (\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2006\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIt shows that psychological factors (especially current orientation, self-control and attitudes towards debt) improve the ability to predict indebtedness. In contrast, dynamic analyses suggest that many of the differences in psychological variables between debtors and non-debtors may be a consequence of being in debt rather than a cause of it\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWebley \u0026amp; Nyhus (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2001\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enalyzes the influence of complementary cognitive abilities on four measures of economic decision-making (temporal discounting, loss aversion, financial literacy and debt literacy) in older vs. younger participants. Older participants' higher crystallized intelligence compensated for their lower levels of fluid intelligence for temporal discounting, financial literacy and debt literacy, but not for loss aversion.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLi et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnalyzes consumer credit card debt behavior. Personality factors of self-control, self-esteem, self-efficacy, gratification delay, internal locus of control and impulsivity were significantly correlated with the use of revolving credit; on the other hand, sensation-seeking, impulsivity and gratification delay were correlated with the use of small installments.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWang, Lu, \u0026amp; Malhotra (\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2011\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThey report that financial innovation and overconfidence in the risk of new financial products were key factors behind the 2008 credit crisis in the US.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoz \u0026amp; Mendon\u0026ccedil;a (2014)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnalyzes the role of emotional factors in determining household participation in the debt market. In addition to confirming the role played by the traditional explanatory variables used as determinants of household indebtedness, the results revealed the significant influence of individuals' impulsiveness on debt decision-making.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOttaviani \u0026amp; Vandone (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAnalyzing the results of the first twelve articles presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, it can be seen that terms such as \"attitudes towards money\", \"financial literacy\", \"mental accounting\", \"hyperbolic discounting\", \"life satisfaction and financial stress\", \"impulsiveness\" and \"self-control\" are potential predictors of indebtedness, with special emphasis on the last two (impulsiveness and self-control).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePage rank analysis\u003c/h2\u003e \u003cp\u003ePage rank analysis makes it possible to verify the link between articles and their influence, measured by the size of the circle and the cluster formed by them, illustrated by the shade of the circle (Silva et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This is a combination of eminence, based on the number of citations, and the prestige of the scientific work (Ma et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Brin \u0026amp; Page, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1998\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo form the network map, the parameters used were the number of citations or \"link strength\" different from zero. The results obtained allowed the articles to be classified into 5 distinct clusters, made up of 45 articles, given that the others had a number of citations or link strength equal to zero. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the network map formed by the articles, illustrated by the shade of the circle and the lines connecting them, and their level of influence, evidenced by the size of the circle containing it.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe analysis of the network map of the articles points to the work of Prelec and Loewenstein (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), Meier and Sprenger (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); Gathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); Gul and Pesendorfer (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e); Norvilitis, Szablicki, and Wilson (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2003\u003c/span\u003e); Li et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); Achtziger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and Webley and Nyhus (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) as the most prominent in terms of number of local citations, and can be distributed into 5 distinct clusters (gray, blue, orange, yellow and purple).\u003c/p\u003e \u003cp\u003eIn the first cluster with the highest concentration of works (17 items), represented by the color gray, there are studies that analyze issues related to mental accounting, framing of debt or supply (psychological property of money), coupling between consumption and payment, temporal contiguity and mode of payment. These include the work of Prelec and Loewenstein (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) and Li et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe second cluster in terms of the number of papers (9 items), represented by the color blue, is made up of studies that evaluate the relationship between credit and indebtedness, relating them to self-control, impulsiveness, optimism and financial literacy. This cluster includes the work of Webley and Nyhus (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), Norvilitis et al. (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and Achtziger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Next, we have the cluster represented by the color orange (8 items), made up of research that analyzes the relationships between financial literacy, money management and impulsivity and their influence on debt and credit card payments. In this cluster, the works of Gathergood and Weber (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Atlas et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) stand out.\u003c/p\u003e \u003cp\u003eIn the cluster represented by the color blue, there are studies that evaluate the influence of self-control on spending control, savings, time preference and loan repayment behavior. Ponchio et al. (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) stands out as the most relevant of these. Finally, the last cluster, represented by the color purple, is made up of works that analyze the relationship between time preferences in credit and consumer indebtedness. This cluster is formed by the works of Meier and Sprenger (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); Gathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and Gul and Pesendorfer (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinally, the analysis of \"total link strength\", considering all the articles in the BP, highlighted the works by Frigerio, Ottaviani, and Vandone (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Lea (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Goyal et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Hamid and Loke (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Gathergood and Weber (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Ponchio et al. (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), the latter two also being prominent in terms of the number of citations in the orange and yellow clusters, respectively.\u003c/p\u003e \u003cp\u003e \u003cem\u003eKeyword analysis\u003c/em\u003e \u003c/p\u003e \u003cp\u003eBibliographic coupling is a well-established approach for measuring documents\u0026rsquo; shared intellectual background (Aparicio et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Bibliographic coupling combined with the cluster method and content analysis of BP articles was applied to identify the intellectual structure of research on behavioral biases and personal indebtedness. The analysis of the descriptors of the papers allows us to expand on these results, since the keywords of an article reflect its main content, and the frequency of their occurrence and co-occurrence represent the most significant themes addressed by papers in a research area and how they are linked to each other (Hemrajani et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe main assumption of a co-occurrence analysis is that the authors' keywords constitute an adequate proxy for the content of the articles or the relationship that the article establishes between the problems, and their interrelationships can provide reasonable details about the intellectual structure of a given field of knowledge, research patterns and trends (Strozzi et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Trends in the keywords displayed in various studies can be used to determine the main direction of the study for future investigations (Osei et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Pesta et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to Aria and Cuccurullo (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), interpretations based on the network map must take into account the relative position of the points and the distribution of these points in relation to the size of the graph. In addition, the topics that are closest to the center are more relevant to research than the others. To explore the analysis of the co-occurrence of keywords in BP articles, those that occurred more than four times were selected, using VOSviewer's \"all keywords\" analysis unit. The results obtained in the co-occurrence analysis of the descriptors illustrate three points that can be used in analysis, as suggested by Silva et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2023\u003c/span\u003e): (i) the frequency of occurrence of the keywords, measured by the size of the circle; (ii) the strength of association between them, represented by their proximity; and (iii) bibliographic coupling, evidenced by the color of the cluster, shown in Fig.\u0026nbsp;4.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFigura 4.\u003c/b\u003e BP Conceptual Structure Map.\u003c/p\u003e \u003cp\u003eThe parameters used to analyze the co-occurrence of keywords returned 18 descriptors, distributed in 3 distinct clusters, highlighted by gray, blue and orange tones. The gray cluster, formed by 8 items, is composed of works that analyze the interrelationships between credit and credit card, money management, liquidity restrictions, consumer behavior and finances and impulsivity and its influence on personal debt and in the consumption relationship. The blue cluster, formed by 5 items, is composed of works that analyze determinants of debt considering the influence of financial literacy, financial behavior, self-control and materialism. Finally, the last cluster (in orange) is composed of works that analyze debt from the perspective of mental accounting. The analysis of the articles that make up each cluster using the descriptors is presented in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\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\u003eAnalysis of the BP articles based on the bibliographic coupling formed.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster color\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescriptor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRelated work\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"23\" rowspan=\"24\"\u003e \u003cp\u003eGray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eCredit and credit card\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNorvilitis et al. (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) explored the relationships between financial attitudes, impulsivity, locus of control, life satisfaction and stress and their effects on levels of credit card debt in university students. It indicates that personality variables are generally not related to the level of debt, although they are related to attitudes towards money.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWang et al. (\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) points out that personality factors, self-control, self-esteem, self-efficacy, delay of gratification, internal locus of control and impulsivity are significantly correlated with the use of revolving credit.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHodson et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), when analyzing the relationship between unpaid consumer debt and emotional pressure, point out that for individuals with average incomes, unpaid debt increases depressive symptoms, while for others (lower and higher incomes), the emotional costs of consumer credit only manifest themselves with the onset of recession.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKuchler \u0026amp; Pagel (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) report that the sensitivity of spending to the receipt of paychecks reflects the short-term impatience of agents who are biased towards the present, a behavior best explained by the present bias.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHamid \u0026amp; Loke (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), when studying the relationship between socio-economic factors, financial literacy, money management skills, overspending and impulsiveness in credit card repayment decisions, identified that financial literacy and money management skills have a positive effect on the decision-making of credit card holders.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGeorge \u0026amp; Leszczyszyn (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) point to consumers' overconfidence in their financial knowledge as a new explanation for the phenomenon of simultaneously holding credit card debt and liquid assets.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAydin (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) points out that optimism, intuition and materialism have a significant effect on the responsible handling of credit card debts.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther studies mentioned in the clusters also provide results on the influence of credit and credit cards on indebtedness, such as Webley and Nyhus (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2001\u003c/span\u003e); Wang et al. (\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2011\u003c/span\u003e); Atlas et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); Frigerio et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); Sharma et al. (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Lea (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Jia et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and Moorhouse et al. (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMoney management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLea (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) analyzed psychological studies on the actual use of credit, debt and over-indebtedness, identifying three groups of factors that lead to indebtedness: dispositional factors (in particular, low conscientiousness and lack of self-control), attitudinal factors (for example, excessive optimism and materialism) and cognitive factors (for example, lack of parental financial guidance and low levels of financial literacy).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther studies mentioned in the previous clusters also provide results on the influence of money management on indebtedness, such as Ottaviani \u0026amp; Vandone (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e); Ottaviani \u0026amp; Vandone (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); Ponchio et al. (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); Hamid \u0026amp; Loke (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Singh \u0026amp; Malik (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLiquidity constraints\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeier \u0026amp; Sprenger (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) indicate that individuals with a gift bias are more likely to have credit card debt.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBaugh et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that households increase consumption when they receive expected tax refunds, behavior consistent with a life-cycle model of mental accounting.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther studies mentioned in the clusters also provide results on the influence of liquidity constraints on indebtedness, such as Ottaviani \u0026amp; Vandone (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and Sussman \u0026amp; O'Brien (2016).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eConsumer behavior and finances and Consumer Debt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKeys \u0026amp; Wang (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) analyze the impact of changing minimum payment formulas on credit cards, finding that anchoring to a contact term has a significant impact on repayment decisions.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHendy et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) studied how behavioral factors affect credit card debt minimum payment behavior. It shows that although counseling and anchoring interventions have significant effects on increasing repayments.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLukas \u0026amp; N\u0026ouml;th (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) analyze the heterogeneity of borrowers in their debt response to interest rate reductions and credit limit increases in revolving consumer credit.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLanda-Blanco (2022) indicates that subjects with higher scores in Attitudes towards Debt and Money (low financial control), Irrational Happiness and Materialistic Values have a greater tendency to Impulsive Buying.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMoorhouse et al. (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), when conducting a field experiment to examine the effectiveness of a behaviour change course, identified that individuals who anticipated stigmatization and formed new social connections in a community condition reduced their consumer debt.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther works mentioned in the clusters also provide results on the interrelationships between consumer behavior, consumer finances and debt, such as Gathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); Achtziger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e); Hershfield et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2015\u003c/span\u003e); Ponchio et al. (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); Atlas et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Sharma et al. (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eImpulsiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOttaviani \u0026amp; Vandone (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), when analyzing the role of emotional factors as determinants of household debt, report the significant influence of individuals' impulsiveness on debt decision-making.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOttaviani \u0026amp; Vandone (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) examined the role of impulsivity and financial literacy as predictors of debt burden finding that impulsivity fully mediated the impact of financial literacy on debt, even after controlling for financial wealth, showing its significant influence on debt decision-making.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrigerio et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) carried out a meta-analysis of existing studies to assess whether higher levels of impulsivity are associated with greater indebtedness, finding a significant positive association between them; and that type of over-indebtedness and professional status significantly moderated this association.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSingh \u0026amp; Malik (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), in proposing a financial vulnerability index, indicate that greater financial knowledge, better money management skills and lower impulsivity in financial behavior can reduce vulnerability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther studies mentioned in the previous clusters also provide results on the influence of impulsivity on indebtedness, such as Wang et al. (\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2011\u003c/span\u003e); Achtziger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e); Hamid \u0026amp; Loke (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Ma \u0026amp; Yao (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"20\" rowspan=\"21\"\u003e \u003cp\u003eBlue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eFinancial literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLi et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) analyzed the influence of complementary cognitive abilities on four measures of economic decision-making (temporal discounting, loss aversion, financial literacy and debt literacy) in older vs. younger participants, pointing out that the former performed as well or better than the latter in these decision-making measures.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGathergood and Weber (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), when analyzing the interaction between financial literacy, present bias and choices about the type of mortgage repayment, point out that financial literacy increases the probability of choosing an adjustable-rate mortgage compared to a fixed-rate mortgage.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGanbat et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) when analyzing whether an individual's credit risk can be predicted on the basis of psychometric tests, found that positive scores on the tests of effective financial decision-making, self-control, conscientiousness, altruism and giving attitude, and attitude towards money enable individuals to access debt.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSekita et al. (\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) when analyzing the effects of five different types of financial literacy on wealth, indicates that deposit literacy, risk literacy and debt literacy have positive effects; inflation literacy and insurance literacy do not have significant effects; and several behavioral economics variables, such as overconfidence, self-control, myopia and risk aversion, are also significant determinants of wealth.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther studies mentioned in the cluster analysis also consider the influence of financial literacy on indebtedness or treat it as a control variable, such as Gathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); Li et al, (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); Ottaviani \u0026amp; Vandone (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); Ponchio et al. (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); Atlas et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); Frigerio et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); Hamid \u0026amp; Loke (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Lea (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); George \u0026amp; Leszczyszyn (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Singh \u0026amp; Malik (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Fern\u0026aacute;ndez-L\u0026oacute;pez et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFinancial behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eXiao et al. (\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) suggests that positive financial behaviors are positively associated with the level of economic and non-economic resources, reduce financial stress and increase financial satisfaction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAtlas et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) examining how confidence in financial knowledge relates to credit card behaviors and financial satisfaction, finds that confidence is more strongly associated with credit card use and overall financial satisfaction as knowledge increases.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther studies mentioned in the cluster analysis also provide results on the influence of financial behavior on indebtedness, such as George \u0026amp; Leszczyszyn (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Rey-Ares et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Vuković \u0026amp; Pivac (\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Goyal et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Singh \u0026amp; Malik (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003eSelf Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWebley \u0026amp; Nyhus (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) show that psychological factors (especially current orientation, self-control and attitudes towards debt) improve the ability to predict indebtedness.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGul and Pesendorfer (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), by extending the analysis of self-control in decision problems from two periods to an infinite horizon (a phenomenon they characterize as dynamic self-control preferences), conclude that increasing commitment while maintaining constant self-control increases the capital premium.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), when investigating the relationship between self-control, financial literacy and over-indebtedness, points out that lack of self-control plays a more important role in explaining over-indebtedness than financial illiteracy.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAchtziger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) when investigating the links between self-control, compulsive buying and actual debts, reports that self-control is negatively related to debts and compulsive buying is positively related to debts.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVuković \u0026amp; Pivac (\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) report that people with greater self-control are more likely to save money and less likely to get into debt, and that there is a significant mediating effect of financial behavior on the relationship between self-control and financial security;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRey-Ares et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) point out that self-control influences individuals' financial attitudes regardless of generation, and that only millennials with higher levels of self-control are affected by it when deciding between a savings account or a personal loan, showing a potentially dangerous overconfidence in their financial management skills.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGoyal et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) analyzed the association between personal financial management behavior and six psychological factors and identified, in the overall results, a significant positive association between personal financial management and self-control, and in the subgroup analysis, self-control (positively) and materialism (negatively) were significantly associated with personal financial management behavior among adults.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJia et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), when examining how extreme debtors evaluate their capacity for self-control, revealed that they have a low capacity to regulate their behavior, but maintain an illusory perception of high capacity, which may expose them to greater debt accumulation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFern\u0026aacute;ndez-L\u0026oacute;pez et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) indicate that self-control problems lead to greater indebtedness, and its influence differs between credit options, where a lack of self-control increases the likelihood of taking out unsecured personal loans, loans from family or friends and credit card use.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther studies mentioned in the cluster analysis also provide results on the influence of self-control on indebtedness, such as Ponchio et al. (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); Wang et al. (\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2011\u003c/span\u003e); Ganbat et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Lea (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Ma \u0026amp; Yao (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMaterialism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePonchio et al. (\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) when investigating the impact of consumer spending self-control, personal savings orientation, materialism, financial knowledge and time perspective on the perception of financial well-being, found that time perspective moderates the effect of materialism on the current stress of money management and spending self-control mediates this relationship.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMa \u0026amp; Yao (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), when investigating the factors influencing the use of Internet credit services among young adults considering reflexive and impulsive decision-making processes, indicate that immediate gratification and materialism positively affect the impulse to use, while self-control was identified as an impulse inhibitor.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther studies mentioned in the previous clusters also provide results on the influence of materialism on indebtedness, such as Goyal et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); Lea (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Landa-Blanco (2022) and Aydin (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003eOrange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003eMental Accounting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHirst et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) investigates the role that temporal contiguity (the co-occurrence of multiple outcomes) plays in mental accounting for consumer borrowing decisions.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrelec \u0026amp; Loewenstein (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) propose a \"double entry\" theory of mental accounting that describes the nature of these reciprocal interactions between the pleasure of consuming and the pain of paying and highlights their implications for the consumer. It reports that the pain of paying plays an important role in consumer self-regulation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHershfield et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) in examining three psychological barriers to the responsible use of credit and debt, discuss consumers' tendency to make wrong predictions about future consumption habits, rely too much on the figures shown on invoice statements and categorize debt and savings in separate mental accounts.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSussman \u0026amp; O'Brien (2016) point out that there is a tendency for people to preserve savings by taking out loans through a credit option with high interest rates.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSwacha-Lech \u0026amp; Solarz (\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) indicate that the strongest determinants of mental accounting attitude are: having debt, having savings, debt aversion and the amount of monthly net income achieved. Both debt and high monthly net income increase the likelihood of adopting mental accounting attitudes, while the other factors have the opposite effect.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQuispe-Torreblanca et al. (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found that repayment of debt contracted for non-durable goods is 10% more likely than repayment of debt contracted for durable goods.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArgyle et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) when investigating three phenomena that he calls \"monthly payment target\", points out that many consumers (i) tend to manage the size of the payment when making decisions about debt; (ii) seem to use segregated mental accounts and; (iii) group themselves into round numbers of monthly payments, consistent with the budget heuristic.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSharma et al. (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) introduce the concept of psychological ownership of borrowed money and show that framing debt using language lower in psychological ownership can reduce the propensity to take out loans.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSilva et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) analyzed scientific production on the influence of mental accounting bias on decision-making processes, reporting numerous impacts on decisions related to savings, consumption, investment and debt.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther studies mentioned in the clusters also provide results on the influence of mental accounting on indebtedness, such as Baugh et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Rey-Ares et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eNot clustered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOptimism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSeaward \u0026amp; Kemp (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) report that the tendency to overestimate future income is positively correlated with an individual's level of real debt.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverconfidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBoz \u0026amp; Mendoza (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) point out that financial innovation and overconfidence in the risk of new financial products were key factors behind the 2008 credit crisis in the US.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFraming\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCaetano et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) reports that debt aversion, the unwillingness to enter into a financial contract framed or labeled as debt, distorts household investment and financing decisions.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBauer et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), when investigating how interest-free financing promotions influence consumer behavior, shows that framing an economically equivalent financing offer in a way that makes it clear that it is interest-free increases consumer demand for credit to finance experiential, but not material, goods.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnchoring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePorto et al. (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), in examining the association between past borrowing experience and borrowing decisions, suggest what influences people's perception of how much to borrow to finance education: anchoring. Individuals suggest higher amounts to others based on their previous borrowing\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=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of the references of the articles in the BP\u003c/h2\u003e \u003cp\u003eAnalyzing the references of the BP makes it possible to determine the historical roots of research areas or the works of decisive importance in a field (Marx \u0026amp; Bornmann, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). It makes it possible to identify seminal works, highly recognized by the literature and with a major impact on the study of the subject, prominent authors and their interrelationships. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the network map of the most cited researchers in the BP references.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs can be seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the analysis of the relationship network between the works in the BP references showed that the studies by Gathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), Meier \u0026amp; Sprenger (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), Achtziger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Wang et al. (\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), Norvilitis et al. (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and Lea et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), which are among the 12 most cited articles in the BP (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), are also relevant in the BP references, demonstrating their relevance to research on indebtedness. In addition, the results obtained from the network map of the references made it possible to group them into three large clusters, highlighted by the colors gray, orange and blue.\u003c/p\u003e \u003cp\u003eThe gray cluster is made up of 5 papers investigating the interrelationships between financial literacy and indebtedness. Gathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) investigates the relationship between self-control, financial literacy and over-indebtedness in consumer credit debt, finding a greater role for lack of self-control than for financial illiteracy in explaining over-indebtedness. Lea et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) investigated various psychological variables as causes or effects of debt. Their results suggest that a complex of psychological and behavioral variables affect debt and are affected by it, that economic and demographic factors predicted the debt category well, that debtors had less money management facilities and shorter time horizons than non-debtors.\u003c/p\u003e \u003cp\u003eNorvilitis et al. (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) explored factors related to the causes and effects of credit card debt in university students. Their results indicate that lack of financial knowledge, age, number of credit cards, delay in gratification, and attitudes toward credit card use were related to indebtedness, and that students who reported greater debt reported greater stress and decreased financial well-being. Fernandes, Lynch, and Netemeyer (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) analyzes the relationship between financial literacy and financial education with financial behaviors, concluding that interventions to improve financial literacy explain only 0.1% of the variance in the financial behaviors studied, with weaker effects in low-income samples and which decrease dramatically when controlling for psychological traits. Lusardi and Tufano (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) analyzed the relationship between literacy and debt, pointing out that average literacy is low, a phenomenon that contributes to individuals carrying out high-cost transactions and excessive indebtedness.\u003c/p\u003e \u003cp\u003eThe orange cluster is made up of 4 studies that analyze self-control and its influence on indebtedness. Ameriks et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) analyzed self-control problems in a sample of adults with a high level of education, identifying that they tended to be smaller in scale in older interviewees than in younger ones. Wang et al. (\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) studied consumer credit card debt behavior in correlation with demographic factors, attitude, personality and credit card characteristics. Their results indicate that personality factors, self-control, self-esteem, self-efficacy, gratification postponement, internal locus of control and impulsivity are significantly correlated with the use of revolving credit; and that some credit card characteristics lead to an \"illusion of income\", facilitating debt behavior.\u003c/p\u003e \u003cp\u003eAchtziger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) investigates the links between self-control, compulsive buying and actual debt finding that self-control is negatively related to debt, compulsive buying is positively related to debt and the link between self-control and debt was fully mediated by compulsive buying. In the last paper in this cluster, Str\u0026ouml;mb\u0026auml;ck et al. (\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) explored the effect of individual differences in self-control and other non-cognitive factors on financial behavior and financial well-being. Their results indicate that people with good self-control are more likely to save money in each paycheck, have better overall financial behavior, feel less anxious about financial matters and feel more secure in their current and future financial situation.\u003c/p\u003e \u003cp\u003eThe blue cluster is made up of 6 studies investigating aspects linked to the behavioral life cycle and intertemporal consumption. It includes the work of Shefrin \u0026amp; Thaler (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1988\u003c/span\u003e), which incorporates the concepts of self-control, mental accounting and framing, introducing the concept of the Behavioral Life Cycle; and Laibson (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), who, by analyzing hyperbolic discount functions, suggests that financial innovation may have caused the continuous decline in savings rates in the USA, since financial innovation increases liquidity, eliminating opportunities for compromise.\u003c/p\u003e \u003cp\u003eTangney et al. (\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) when analyzing individual differences in self-control, reported that higher self-control scores correlated with a higher grade point average, higher self-esteem, better relationships and interpersonal skills, reporting that low self-control is a significant risk factor for a wide range of personal and interpersonal problems. Meier \u0026amp; Sprenger (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) test whether present-biased time preferences correlate with credit card borrowing. Their results indicate that present-biased individuals are more likely to have credit card debt and to have significantly higher credit card debt.\u003c/p\u003e \u003cp\u003eFinally, Heidhues \u0026amp; Kőszegi (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) analyzed loan repayment behavior considering individuals with preferences for immediate gratification. Their results indicate that unsophisticated individuals take out excessive loans, pay the fines and delay repayment, suffering large welfare losses. Therefore, in view of the importance of these studies for the study of the subject, it is suggested that they be consulted for the development of future work.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMapping the Evolution and Trends of Research on the Theme\u003c/h2\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003eMapping the Evolution of Research on the Theme\u003c/h2\u003e \u003cp\u003eIn this section we present the evolution of the keywords used in studies investigating the interrelationships between behavioral biases and personal indebtedness that make up the BP. A preliminary analysis of the data using the bibliometrix indicates that terms such as \"self-control\", \"impulsivity\" and \"mental accounting\" have continued over the last 10 years, showing themselves to be recurring themes; and terms such as \"determinants\", \"materialism\" and \"life cycle\" have appeared in the last 5 years, showing themselves to be emerging themes. A complementary analysis can be carried out using the results illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e illustrates, based on BP data, the main topics covered by researchers in the last 10 years (2014 to 2023) and the average frequency of their occurrence over the period analyzed, which can be seen by the shade of the circle that makes it up. The higher the red shade, the closer its relative frequency is to the current years (2023), and the bluer it is, the closer it is to 2014.\u003c/p\u003e \u003cp\u003eBased on the results presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e, it can be seen that themes such as \"determinants\", \"materialism\", \"life-cycle\", \"financial literacy\", \"overconfidence\", \"self-control\" and \"mental accounting\" are quite current in research related to analyzing the influence of behavioral biases on personal indebtedness, three of them (\"life-cycle\", \"self-control\" and \"mental accounting\") are related to the behavioral life-cycle theory (BLC) proposed by Shefrin \u0026amp; Thaler (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e1988\u003c/span\u003e), previously reported in the preliminary analysis as an emerging theme. Terms such as \"personality\" and \"liquidy constraints\" appear shortly afterwards.\u003c/p\u003e \u003cp\u003eThese results suggest that future work could analyze issues related to indebtedness by combining some of these descriptors with others from different areas of knowledge. In particular, combinations of terms such as \"life-cycle\", \"overconfidence\", \"self-control\", \"mental accounting\" and \"materialism\" (from the field of behavioral sciences), with terms such as \"financial literacy\" (from the field of education/knowledge), and \"personality\" (from the field of psychology/behavior) could make interesting contributions to the literature that seeks to investigate aspects related to personal indebtedness.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussions","content":"\u003cp\u003eThe results found in the previous sections, together with the characteristics of this research, provide important information on the state of the art and interesting insights for future research on the subject.\u003c/p\u003e \u003cp\u003eFirstly, with regard to the main works in this area of knowledge, our results show that the research by Prelec \u0026amp; Loewenstein (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), Gul and Pesendorfer (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), Norvilitis et al. (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), Meier \u0026amp; Sprenger (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and Gathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) make an important contribution to the study of the subject, with the latter two also featuring prominently in BP references.\u003c/p\u003e \u003cp\u003eAt another point, the network analysis between the keywords (Fig.\u0026nbsp;4) illustrates that studies on the topic are concentrated in three clusters: (i) works that analyze the interrelationships between debt, credit, money management, restriction liquidity, consumer behavior and finances and impulsivity; (ii) works that analyze the interrelationships between debt, financial literacy, financial behavior, self-control and materialism and; (iii) works that analyze the interrelationships between debt and mental accounting; in addition to works that analyze the interrelationships between debt and behavioral biases, such as optimism, overconfidence, framing and anchoring..\u003c/p\u003e \u003cp\u003eA third point, and perhaps the most important contribution of this research to the literature investigating issues related to indebtedness, is to understand how indebtedness (and its levels) has been discussed and the main metrics for measuring it (degree of indebtedness). The analysis of the content of the articles allowed us to identify that there are many approaches to defining and measuring indebtedness and over-indebtedness: the economic dimension (the ability to repay the debt); the temporal dimension (medium or long-term time horizon); the social dimension (the need to substantially reduce the expenses that have to be paid before the debt is repaid); and the psychological dimension (stress caused by over-indebtedness). It also showed that, as it is a complex and multidimensional phenomenon, there is no agreed definition of over-indebtedness in the literature, and likewise, there is no consensus on how to measure it (Bl\u0026aacute;zquez et al., 2020; Wałęga \u0026amp; Wałęga, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Leandro \u0026amp; Botelho, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThus, based on the results of the content analysis of the articles analyzed, inspired by Betti et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2007\u003c/span\u003e); Gathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); Wałęga \u0026amp; Wałęga (\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Leandro \u0026amp; Botelho (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), we present Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e, which illustrates, in a pictographic scheme, the possible definitions of indebtedness from an economic and psychological perspective (dimension).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLooking at the concepts of indebtedness listed in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e, it can be seen that the recognition of indebtedness, from an economic and accounting point of view, is related to the existence of future obligations, and as its representativeness in relation to some financial parameter (such as revenue or equity, for example) rises to an increasingly higher result (index), there is a shift from a situation of indebtedness to the recognition of a situation of over-indebtedness.\u003c/p\u003e \u003cp\u003eLooking at it from a psychological point of view, a person usually tends to consider themselves in debt as the level of difficulty in paying off the debt rises, i.e. it is positively related to the inability to pay and the pain (feeling) and realization of default.\u003c/p\u003e \u003cp\u003eIt can be seen that there is a dissonance between the idea of indebtedness based on the two points of view. In this sense, a person with their accounts up to date, when questioned about the existence of debt, would tend to refute this possibility, unless there is some overdue commitment. People tend to consider themselves indebted not if they have high debts, but if they have commitments that are difficult to pay (default).\u003c/p\u003e \u003cp\u003eThis dissonance between economic and psychological (mental) recognition of debt can be quite disastrous. Take, for example, an individual who, from an economic point of view, has a high amount of debt (financial commitments) and a high \"debt/income\" ratio, and has no contingency reserve; and psychologically, has a low recognition of the debt situation, provided by their ability to pay their commitments when they fall due (high current liquidity). This profile brings with it a strong vulnerability, especially in a situation of economic crisis or imminent job loss. This shows the importance of the assumptions of the behavioral sciences and cognitive biases, especially the mental accounting bias, self-control, overconfidence and optimism, in studies on indebtedness.\u003c/p\u003e \u003cp\u003eThe literature reviewed highlights Mental Accounting as a prominent cognitive bias in relation to individuals' indebtedness. This bias causes a dissonance between the pleasure of consuming and the pain of paying (Prelec \u0026amp; Loewenstein, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), leading people to make mistaken predictions about future consumption (Hershfield et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), mainly due to the fact that they can accumulate savings and get into debt at the same time (Sussman \u0026amp; O'Brien, 2016). In this sense, the decision to consume and go into debt is influenced by the mental accounting bias (Argyle et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which can lead to errors in judgment and financial losses.\u003c/p\u003e \u003cp\u003eIn addition, in a less clustered way, optimism, overconfidence, framing and anchoring appear as biases that influence indebtedness. Optimism can lead to an overestimation of income and therefore increase the level of debt (Seaward \u0026amp; Kemp, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). On the other hand, overconfidence can lead individuals to allocate their resources to risky assets, increasing their indebtedness (Boz \u0026amp; Mendoza, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Framing influences indebtedness based on the way in which debt contracts are presented (Caetano et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), causing the individual to make mistaken decisions due to the fact that the embedded interest does not materialize (Bauer et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Finally, the anchoring bias causes people to anchor themselves in past experiences in order to take on current debts (Porto et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which can negatively influence the relationship between consumption and indebtedness.\u003c/p\u003e \u003cp\u003eLastly, the network analysis of the keywords (Fig.\u0026nbsp;4) together with the temporal analysis of their occurrence (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e) made it possible to identify themes with greater continuity over the years and more recent research themes on the interrelationships between behavioral biases and individual indebtedness. We observed a trend of studies relating cognitive biases to indebtedness and, although the study of cognitive biases has been growing in the area of behavioral economics (Costa et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), the results point to gaps to be filled in relation to indebtedness.\u003c/p\u003e \u003cp\u003eThus, future work could analyze issues related to indebtedness by combining some of these descriptors with others from different areas of knowledge. In particular, combinations of terms such as \"life-cycle\", \"overconfidence\", \"self-control\", \"mental accounting\" and \"materialism\" (from the area of behavioral sciences), with terms such as \"financial literacy\" (from the area of education/knowledge), and \"personality\" (from the area of psychology/behavior) tend to expand the literature that seeks to investigate aspects related to personal indebtedness.\u003c/p\u003e \u003cp\u003eAs there are structural, economic and cultural disparities around the world (Tomar et al., \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), future work could expand these analyses (combination of descriptors) by considering various regions, such as emerging countries vs. developed countries, investigating whether the factors identified in relation to the former are also relevant to the latter.\u003c/p\u003e \u003cp\u003eAnother interesting research gap would be to expand the findings on the interrelationships between mental accounting, financial literacy and indebtedness. Baker et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) shows that financial literacy has a positive relationship with mental accounting bias. Gathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); Flores \u0026amp; Vieira (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e); Mahdzan et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) point out that the level of financial literacy has an inverse relationship with indebtedness. It follows from this logic that mental accounting, since it has a positive relationship with financial literacy, would tend to have a negative impact on indebtedness.\u003c/p\u003e \u003cp\u003eOn the contrary, studies report the tendency of consumers to categorize debts and savings in separate mental accounts (Hershfield et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and that adopting this narrow mental accounting attitude tends to favor indebtedness Swacha-Lech \u0026amp; Solarz (\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Mental accounting has a significant positive influence on savings decisions (Tetteh \u0026amp; Boachie, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and interacts in the process in which people take on debts with high interest rates while maintaining savings that yield low levels of interest (Sussman \u0026amp; O'Brien, 2016). In this context, adopting mental accounting attitudes tends to promote the achievement of savings goals, but in contrast, results in the need to take out loans, that is, to get into debt Swacha-Lech \u0026amp; Solarz (\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Given the still inconclusive results regarding the influence of mental accounting on debt, and that people can group a set of decisions in a broad way (evaluating the possible consequences of all choices together) or in a restricted way (evaluating each decision separately), which Read et al. (1999) call \u0026ldquo;choice buckets\u0026rdquo; (Ple\u0026szlig;ner, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), future work could investigate determining and moderating factors in this relationship.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn view of the persistent increase in the levels of indebtedness of individuals seen in world economies, this work aimed to review the existing literature on the interrelationships between behavioral biases and personal indebtedness, with a view to learning about the current state of the literature on the subject, currents and main results, and identifying opportunities for future research.\u003c/p\u003e \u003cp\u003eThe bibliometric analysis of the selected articles indicates the influence of works such as Prelec \u0026amp; Loewenstein (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1998\u003c/span\u003e); Meier \u0026amp; Sprenger (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); Gathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); Gul and Pesendorfer (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e); Norvilitis et al. (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2003\u003c/span\u003e); Achtziger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e); Xiao et al. (\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2006\u003c/span\u003e); Webley \u0026amp; Nyhus (\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2001\u003c/span\u003e); Li et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); Wang, Lu, \u0026amp; Malhotra (\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2011\u003c/span\u003e); Boz \u0026amp; Mendon\u0026ccedil;a (2014) and Ottaviani \u0026amp; Vandone (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) in research on the subject, which represent more than 80.5% of global citations. This shows the significant impact of these works on the literature on the relationship between behavioral biases and indebtedness.\u003c/p\u003e \u003cp\u003eThe analysis of the bibliographic coupling of the papers made it possible to identify 3 distinct clusters of research in the area: (i) papers analyzing the relationship between mental accounting, liquidity restrictions and the influence of credit cards on personal indebtedness; (ii) papers analyzing the determinants of indebtedness considering the influence of financial literacy, financial behavior, self-control and materialism, and; (iii) papers analyzing the relationship between impulsiveness, money management and indebtedness.\u003c/p\u003e \u003cp\u003eIn addition, the bibliometric analysis of the references of the articles that make up the BP revealed three major clusters of research investigating the relationship between personal indebtedness and (i) financial literacy; (ii) self-control and (iii) behavioral life cycle and intertemporal consumption. It also made it possible to verify that the studies by Meier \u0026amp; Sprenger (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), Gathergood (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), Achtziger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Wang et al. (\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), Lea et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), which are among the 12 most cited articles in the BP, also play a relevant role in the references of the BP, which is why they should also be considered in future research on the subject.\u003c/p\u003e \u003cp\u003eAn analysis of the content of the articles revealed that there are many approaches to defining, measuring and explaining indebtedness and over-indebtedness: the economic dimension; the temporal dimension; the social dimension; the psychological dimension and the behavioral dimension. As far as the behavioral dimension is concerned, some biases have stood out, such as mental accounting, optimism, overconfidence, framing and anchoring, bringing interesting results to the literature, such as the tendency of individuals to categorize debt and savings in separate mental accounts, to present dissonance between the pleasure of consuming and the pain of paying, to overestimate their income (and overconfidence in its maintenance/elevation) vs. underestimating or not considering their level of financial commitment and other aspects related to the psychological ownership of money..\u003c/p\u003e \u003cp\u003eThe mapping of the evolution and trends of research on the subject pointed to themes such as \"determinants\", \"materialism\", \"life-cycle\", \"financial literacy\", \"overconfidence\", \"self-control\" and \"mental accounting\" as very current in related research, along with \"personality\". In view of these results, it is hoped that a fertile field for future work can emerge from combinations of terms from the field of behavioral sciences, such as \"life-cycle\", \"overconfidence\", \"self-control\", \"mental accounting\" and \"materialism\", together with terms from the field of education/knowledge and psychology/behavior, such as \"financial literacy\" and \"personality\". Investigating issues related to indebtedness by combining these descriptors, considering various regions, such as emerging countries vs. developed countries, is a fertile field for future study. Another research gap is to investigate the relationships between financial literacy, mental accounting and indebtedness, identifying moderating factors.\u003c/p\u003e \u003cp\u003eFinally, the work has limitations in terms of its application, one of which concerns the choice of scientific databases used, which tends to have a huge influence on the final result of the mapping and subsequent analysis, as they reflect the characteristics of their underlying databases (Stahlschmidt \u0026amp; Stephen, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the search criteria used, and the limitations of processing a very large amount of information by researchers, given the immensity of the number of publications. This implies that we may not have considered other studies that could complement our analysis. Future work could therefore seek to integrate various databases in order to mitigate this limitation.\u003c/p\u003e "},{"header":"List Of Abbreviations","content":"\u003cp\u003eBP: Bibliographic Portfolio (BP)\u003c/p\u003e\n\u003cp\u003eProknow-C: Knowledge Development Process - Constructivist.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAchtziger, A., Hubert, M., Kenning, P., Raab, G., \u0026amp; Reisch, L. (2015). Debt out of control: The links between self-control, compulsive buying, and real debts. \u003cem\u003eJournal of Economic Psychology\u003c/em\u003e, \u003cem\u003e49\u003c/em\u003e, 141\u0026ndash;149. https://doi.org/10.1016/j.joep.2015.04.003\u003c/li\u003e\n\u003cli\u003eAfonso, M. H. F., Souza, J. V. de, Ensslin, S. R., \u0026amp; Ensslin, L. (2011). Como construir conhecimento sobre o tema de pesquisa? 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Bresnahan (Orgs.), \u003cem\u003eAnnual Review of Economics, Vol 7\u003c/em\u003e, p. 251\u0026ndash;276.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"UFES","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"personal indebtedness, behavioral biases, behavioral sciences, systematic literature review, bibliometric analysis","lastPublishedDoi":"10.21203/rs.3.rs-4510972/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4510972/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe level of indebtedness of individuals has increased significantly in recent decades. The objective of this study was to analyze the scientific literature that evaluates the interrelationships between behavioral biases and personal indebtedness, with a view to investigating the intellectual structure of publications on the influence of behavioral biases on the level of personal indebtedness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBibliometric analysis of scientific publications carried out until October 2023 in the \"Web of Science\" and \"Scopus\" databases and which analyze determinants of personal indebtedness from the perspective of behavioral sciences was used.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results reveal works with global and local relevance, how indebtedness has been discussed from a behavioral perspective and the main cognitive biases associated with it, research clusters that can serve as a reference for researchers, trends and research gaps in this field of knowledge, and that combining constructs from the field of behavioral sciences with other areas of knowledge, especially education/knowledge and psychology/behavior, tends to expand the literature related to personal indebtedness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOriginality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the content analysis of the articles, an innovative scheme illustrating the possible definitions of indebtedness from an economic and psychological perspective is presented, which is an important contribution to the literature.\u003c/p\u003e","manuscriptTitle":"Behavioral biases and personal indebtedness: a systematic literature review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-04 14:55:21","doi":"10.21203/rs.3.rs-4510972/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1c6de584-44fe-42a7-9253-c0b26029f64e","owner":[],"postedDate":"June 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":32800002,"name":"Behavioral Economics"}],"tags":[],"updatedAt":"2024-06-04T14:55:21+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-04 14:55:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4510972","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4510972","identity":"rs-4510972","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}