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This paper aims to give a brief review on behavioral economics and behavioral finance and discusses some of the previous research on agents' utility functions, applicable risk measures, diversification strategies and portfolio optimization.

The authors also cover related disciplines such as trading rules, contagion and various econometric aspects.

While scholars could first develop theoretical models in behavioral economics and behavioral finance, they subsequently may develop corresponding statistical and econometric models, this finally includes simulation studies to examine whether the estimators or statistics have good power and size. This all helps us to better understand financial and economic decision-making from a descriptive standpoint.

The research paper is original.

The purpose of this paper is to empirically test the relationship between investors’ rationality and behavioural biases like self-attribution, overconfidence.

The study applies structural equation modelling to understand whether individual investors, besides being rational, are subjected to self-attribution bias and overconfidence bias.

The study shows the empirical evidence in the support of behavioural biases like self-attribution and overconfidence existing besides investors’ rationality. Moreover, there is a statistically significant positive covariance found between self-attribution and overconfidence, implying that an increase/decrease in self-attribution results in the increase/decrease in overconfidence and vice versa. It is also observed that the personal characteristics of an investor such as gender, age, occupation, annual income and their trading experience have an impact on behavioural biases.

The study focused on rational decision making, self-attribution and overconfidence biases using primary data. Further studies can be encouraged to test the existence of behavioural biases based on both market level and individual account data simultaneously.

Insights from the study suggest that the investors should perform a post-analysis of each investment, so that they become aware of past behavioural mistakes and stop continuing the same. This might help investors to minimise the negative impact of self-attribution and overconfidence on their expected utility.

To the best of the authors’ knowledge, this is the first study to examine the relationship among investors’ rationality, self-attribution and overconfidence in the Indian context using a comprehensive survey.

This paper investigated the extent to which the predictive power of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was robust against cultural variations and to what extent its predictive power could be improved by including face-valid individual differences (i.e. perceived risk and personal innovativeness) and cultural factors (i.e. individualism and uncertainty avoidance).

Data were collected from web surveys of Chinese, American and Belgian mobile Internet users (total n = 1,068).

The authors found that the UTAUT2 model was less predictive in the country where the adoption of mobile payment service (MPS) is high (i.e. China). In contrast, the UTAUT2 model was more predictive in countries where the adoption of MPS is lower (i.e. the United States and Belgium). The authors did not find additional variance explained by individual differences. Regarding the cultural variables, the authors found that individualism moderated the effect of social influence on behavioral intention to use MPS, such that the effect was more substantial among people with individualistic cultural traits. However, the authors found no moderation effect of uncertainty avoidance.

This research contributes to existing work on technology acceptance by exploring whether it is helpful to introduce individual and cultural factors into the UTAUT2 model when predicting technology adoption in different cultures. This research further examines the moderating role of cultural factors in predicting the adoption of MPS. The authors conclude that the UTAUT2 model is generally robust and appears to capture the predictive of face-valid individual and cultural factors.

This study aims to present a unique perspective on the application of the theory of planned behaviour (TPB) in the context of the green lodging industry via configurational modelling of three TPB dimensions in formulating hotel visitors’ behavioural responses. Attitude towards behaviour, subjective norms and perceived behavioural control are the three indicators of TPB used to predict guests’ continued intention to use and recommend green hotels on Cyprus, a Mediterranean island with a fragile ecological system.

A questionnaire-based survey is used to evaluate the study’s objectives. A total of 320 guests of green hotels were approached between June and July 2017 and invited to participate. Among them, 260 valid cases were obtained and used for data analysis. The structural model was tested using structural equation modelling (SEM), the configurational model was assessed using the fuzzy-set qualitative comparative analysis (fsQCA) and the necessary predictor was evaluated using the necessary condition analysis (NCA).

The SEM results revealed that attitudes regarding behaviour increased the continued intention to visit and recommend green hotels. Similarly, subjective norms enhanced the guests’ desired behavioural responses. Perceived behavioural control boosted their continued intention to visit, but this was insufficient for predicting green hotel guests’ intention to recommend. The fsQCA results indicated that two causal models explained the conditions of both high and low levels of behavioural responses. The NCA results showed that attitude towards behaviour was the only necessary condition of the two expected behavioural responses.

Several previous studies have tried to modify, decompose or merge the TPB to provide theoretical support for proposed conceptual models indicating visitors’ behaviours. Beyond such attempts, pragmatic analytical approaches (e.g. set-theoretic method) should be applied to present a comprehensive perspective on the association of TPB indicators in decoding the complexity of customers’ behaviours. To the best of the authors’ knowledge, this study is among the first in hospitality research to use three TPB indicators and three analytical approaches to extend the knowledge of guests’ behaviours related to green hotels.

Extends the transactional‐transformational model of leadership by deductively developing four theoretical behavioral types of leadership based on a historical analysis of leadership literature. Then, in an exploratory empirical phase, uses two data sets to inductively develop alternative models of leadership types. Finally, with a third data set, tests several theoretically plausible typologies using second‐order confirmatory factor analysis (CFA). The results of the CFA generally support the existence of four leadership types: directive leadership, transactional leadership, transformational leadership, and empowering leadership.

This study aims to contribute to the ongoing debate on behavioral operational research (BOR), specifically discussing the potential of system dynamics (SD) models to analyze decision-making heuristics. In more detail, the study suggests using an SD model as an ex-post research tool adopted not only to mimic a role-playing game (RPG) – reproducing the whole physical structure, and the complete set of decision rules specified for a supply chain (SC) management game – but also, and specifically, to replicate and analyze the players’ in-game behavior and decision-making.

After presenting a brief literature review devoted to highlighting the key concepts of the emerging streams of research named BOR and behavioral system dynamics (BehSD), the study presents the characteristics and results of an SC management-based RPG and describes the SD model that was developed to mimic the game and provide the base-run. A triangulation of data sources (which included feedback questionnaires and reports drawn up by 86 participants, as well as notes collected through direct observation of one of the authors) was used to infer information about and in-game decisions. Subsequently, four alternative versions of the SD model were calibrated to reproduce, investigate and explain ex-post the players’ in-game behavior and decision-making heuristics; this study specifically refers to one of them.

The SD model can be considered as the first output of this research. The model was calibrated to mimic the game and subsequently used to develop a few alternative models, helpful to replicate players’ behavior and analyze decision-making heuristics. The findings reveal not fully rational decisions taken by the players and share common findings with previous literature on the emergence of sub-optimal strategies (e.g. phantom ordering and hoarding strategies). The data collected from questionnaires, reports and direct observation additionally revealed that stress and behavioral factors played a role in affecting in-game decision-making.

Considering a specific RPG setting, the SD model developed in this study replicated and captured the range of factors affecting decision-making heuristics, allowing an ex-post analysis of in-game decisions. Notably, the research design presented and used in this study can be considered a generic one, which could be applied subsequently in a variety of contexts, also in combination with simulation/gaming tools and techniques different from role-playing, and both for educational and training purposes, and for research validation.

This study builds on and makes a contribution to the debate related to the emerging stream of research of BOR and more specifically, provides insights and evidence for the yet growing field of BehSD, at the same time advocating and suggesting further research in this area. Overall, the research revealed that behavioral factors may play a relevant role in driving and affecting human decision-making in simulation/gaming contexts.

The purpose of this paper is to identify and examine the important factors that could affect consumers' behavioural intention and use behaviour towards mobile payment services during COVID-19.

The proposed model extends meta-Unified Theory of Acceptance and Use of Technology (meta-UTAUT) model with perceived severity and self-efficacy factors affecting consumers' behavioural intention and use behaviour towards mobile payment services. A convenient sampling technique has been utilized to gather data from a self-administered questionnaire. The data collection was restricted to the online mode to avoid any physical contact considering the COVID-19 situation.

The findings revealed that performance expectancy, effort expectancy and perceived severity have a significant positive impact on consumers' attitude; facilitating conditions has a significant positive impact on effort expectancy; self-efficacy has a significant positive impact on effort expectancy; attitude has a significant positive impact on behavioural intention; and behavioural intention has a significant positive impact on use behaviour. Social influence did not confirm any significant relationship.

The current research study has utilized a non-probability convenient sampling technique to gather data through a self-administered questionnaire. The data collection was restricted to the online mode to avoid any physical contact considering the COVID-19 situation. The respondents were adopters of mobile payment services. The scope of the study is the COVID-19 context or related chronic diseases context where major preventive mechanisms such as social distancing and avoidance of physical contacts are vital.

This study has extended the meta-UTAUT model with the COVID-19 context-specific constructs and relationships. The undertaken work has strengthened the explanability of the model. The inclusion of context relevant variables such as perceived severity and self-efficacy and their association with the existing meta-UTAUT framework have enriched the context of the study. The current study offers a holistic understanding of significant factors influencing Indian consumers’ adoption of mobile payment services in the COVID-19 context.

The purpose of the study is to identify certain behavioural and psychological traits of the borrowers which have the tendency to predict the credit risk of the borrowers. And the second objective is to draw a conceptual model that reveals the impact of those traits on credit default.

The study has adopted a systematic Literature Review approach to identify those behavioural and psychological traits of borrowers that reflect on the tendency to predict the credit default of borrowers.

The findings of this study have revealed that there are some non-financial factors, which can be looked into while granting a loan to a borrower. The identified factors can be used to develop a subjective credit scoring model that can quantify and verify the soft information (character and reliability) of debtors. Further, a behavioural credit scoring model will help in easing the assessment of those borrowers, who do not have an appropriate credit history and reliable financial statements.

The proposed model would help banks and financial institutions to evaluate those borrowers who lack substantial financial information. Further, a subjective credit scoring model would help to evaluate the credit worthiness of such borrowers who do not have any credit history. The model would also reduce the biasness of subjective scoring and would reduce the financial constraints of borrowers.

By reviewing the literature, it has been observed that there are very few studies that have exclusively considered the behavioural and psychological factors in credit scoring. Several studies have linked the psychological constructs with debts, but very few researchers have considered it while constructing a behavioural scoring model. Thus, it can be inferred that this area of behavioural finance is still unexplored and needs attention of researchers worldwide. In addition, most of the studies are carried out in European, African and American regions but are almost non-existent in the Asian markets.

The purpose of this paper is to explore the effect of inventory record inaccuracy due to behavioral aspects of workers on the order and inventory variance amplification.

The authors adopt a continuous-time analytical approach to describe the effect of inbound throughput on the inventory and order variance amplification due to the workload pressure and arousal of workers. The model is numerically solved through simulation and results are analyzed with statistical general linear model.

Inventory management policies that usually dampen variance amplification are not effective when inaccuracy is generated due to workers’ behavioral aspects. Specifically, the psychological sensitivity and stability of workers to deal with a given range of operational conditions have a combined and multiplying effect over the amplification of order and inventory variance generated by her/his errors.

The main limitation of the research is that the authors model workers’ behavior by inheriting a well-known theory from psychology that assumes a U-shaped relationship between stress and errors. The authors do not validate this relationship in the specific context of inventory operations.

The paper gives suggestions for managers who are responsible for designing order and inventory policies on how to take into account workers’ behavioral reaction to work pressure.

The logistics management literature does not lack of research works on behavioral decision-making causes of order and inventory variance amplification. Contrarily, this paper investigates a new kind of behavioral issue, namely, the impact of psycho-behavioral aspects of workers on variance amplification.

As the information society further develops, electronic services are created and physical distribution networks become sparse, it is important to analyse the determinants that inhibit or facilitate the ability to use these services. By focusing on the perceived behavioural control of computers, the purpose of this paper is to analyse how perceived physical restrictions, computer anxiety and ease of use influence the perceptions of control.

The authors examined older consumers (aged 60-79) in two cross-sectional studies conducted through mail surveys in 2004 and 2012. Randomized samples (n=1,000 in 2004 and n=3,000 in 2012) were drawn from the Finnish Population Register. The empirical research utilized structural equation modelling through multi-group analysis to explore the differences in the interrelationships between physical restrictions, computer anxiety, perceived ease of use and perceived behavioural control.

The results indicate that perceived behavioural control is directly influenced by ease of use and indirectly influenced by physical restrictions and computer anxiety. The eight-year time gap moderated only the relationship between physical restrictions and ease of use. Development seems to have been favourable, and device-related restrictions do not decrease ease of use as much as previously reported.

The present study starts a new discussion on how time moderates the relationship of technology perceptions in behavioural models that have been used to predict behavioural intent.