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The purpose of this study is to address a critical gap in enterprise resource planning (ERP) implementation process for small and medium-sized enterprises (SMEs) by acknowledging and countering cognitive biases through a cognitive bias awareness matrix model. Cognitive biases such as temporal discounting and optimism bias often skew decision-making, leading SMEs to prioritize short-term benefits over long-term sustainability or underestimate the challenges involved in ERP implementation. These biases can result in costly missteps, underutilizing ERP systems and project failure. This study enhances decision-making processes in ERP adoption by introducing a matrix that allows SMEs to self-assess their level of awareness and proactivity when addressing cognitive biases in decision-making.

The design and methodology of this research involves a structured approach using the problem-intervention-comparison-outcome-context (PICOC) framework to systematically explore the influence of cognitive biases on ERP decision-making in SMEs. The study integrates a comprehensive literature review, empirical data analysis and case studies to develop the Cognitive Bias Awareness Matrix. This matrix enables SMEs to self-assess their susceptibility to biases like temporal discounting and optimism bias, promoting proactive strategies for more informed ERP decision-making. The approach is designed to enhance SMEs’ awareness and management of cognitive biases, aiming to improve ERP implementation success rates and operational efficiency.

The findings underscore the profound impact of cognitive biases and information asymmetry on ERP system selection and implementation in SMEs. Temporal discounting often leads decision-makers to favor immediate cost-saving solutions, potentially resulting in higher long-term expenses due to the lack of scalability. Optimism bias tends to cause underestimating risks and overestimating benefits, leading to insufficient planning and resource allocation. Furthermore, information asymmetry between ERP vendors and SME decision-makers exacerbates these biases, steering choices toward options that may not fully align with the SME’s long-term interests.

The study’s primary limitation is its concentrated focus on temporal discounting and optimism bias, potentially overlooking other cognitive biases that could impact ERP decision-making in SMEs. The PICOC framework, while structuring the research effectively, may restrict the exploration of broader organizational and technological factors influencing ERP success. Future research should expand the range of cognitive biases and explore additional variables within the ERP implementation process. Incorporating a broader array of behavioral economic principles and conducting longitudinal studies could provide a more comprehensive understanding of the challenges and dynamics in ERP adoption and utilization in SMEs.

The practical implications of this study are significant for SMEs implementing ERP systems. By adopting the Cognitive Bias Awareness Matrix, SMEs can identify and mitigate cognitive biases like temporal discounting and optimism bias, leading to more rational and effective decision-making. This tool enables SMEs to shift focus from short-term gains to long-term strategic benefits, improving ERP system selection, implementation and utilization. Regular use of the matrix can help prevent costly implementation errors and enhance operational efficiency. Additionally, training programs designed around the matrix can equip SME personnel with the skills to recognize and address biases, fostering a culture of informed decision-making.

The study underscores significant social implications by enhancing decision-making within SMEs through cognitive bias awareness. By mitigating biases like temporal discounting and optimism bias, SMEs can make more socially responsible decisions, aligning their business practices with long-term sustainability and ethical standards. This shift improves operational outcomes and promotes a culture of accountability and transparency. The widespread adoption of the Cognitive Bias Awareness Matrix can lead to a more ethical business environment, where decisions are made with a deeper understanding of their long-term impacts on employees, customers and the broader community, fostering trust and sustainability in the business ecosystem.

This research introduces the original concept of the Cognitive Bias Awareness Matrix, a novel tool designed specifically for SMEs to evaluate and mitigate cognitive biases in ERP decision-making. This matrix fills a critical gap in the existing literature by providing a structured, actionable framework that effectively empowers SMEs to recognize and address biases such as temporal discounting and optimism bias. Its practical application promises to enhance decision-making processes and increase the success rates of ERP implementations. This contribution is valuable to behavioral economics and information systems, offering a unique approach to integrating cognitive insights into business technology strategies.

Researchers looking for ways to change the insecure behaviour that results in phishing have considered multiple possible reasons for such behaviour. Therefore, the purpose of this paper is to understand the role of optimism bias (OB – defined as a cognitive bias), which characterises overly optimistic or unrealistic individuals, to ensure secure behaviour. Research that focused on issues such as personality traits, trust, attitude and Security, Education, Training and Awareness (SETA) was considered.

This study built on a recontextualized version of the theory of planned behaviour to evaluate the influence that optimism bias has on phishing susceptibility. To model the data, an analysis was performed on 226 survey responses from a South African financial services organisation using partial least squares (PLS) path modelling.

This study found that overly optimistic employees were inclined to behave insecurely, while factors such as attitude and trust significantly influenced the intention to behave securely.

Our contribution to practice seeks to enhance the effectiveness of SETA by identifying and addressing the optimism bias weakness to deliver a more successful training outcome.

Our study enriches the Information Systems literature by evaluating the effect of a cognitive bias on phishing susceptibility and offers a contextual explanation of the resultant behaviour.

In this paper, the authors investigate the impact of the confirmation bias on returns, expectations and hedging of optimistic and pessimistic traders in the cryptocurrencies, commodities and stock markets before and during COVID-19 periods.

The authors investigate the impact of the confirmation bias on the estimated returns and the expectations of optimistic and pessimistic traders by employing the financial stochastic model with confirmation bias. Indeed, the authors compute the optimal portfolio weights, the optimal hedge ratios and the hedging effectiveness.

The authors find that without confirmation bias, during the two sub periods, the expectations of optimistic and pessimistic trader’s seem to convergence toward zero. However, when confirmation bias is particularly strong, the average distance between these two expectations are farer. The authors further show that, with and without confirmation bias, the optimal weights (the optimal hedge ratios) are found to be lower (higher) for all pairs of financial market during the COVID-19 period as compared to the pre-COVID-19 period. The authors also document that the stronger the confirmation bias is, the lower the optimal weight and the higher the optimal hedge ratio. Moreover, results reveal that the values of the optimal hedge ratio for optimistic and pessimistic traders affected or not by the confirmation bias are higher during the COVID-19 period compared to the estimates for the pre-COVID period and inversely for the optimal hedge ratios and the hedging effectiveness index. Indeed, either for optimists or pessimists, the presence of confirmation bias leads to higher optimal hedge ratio, higher optimal weights and higher hedging effectiveness index.

The findings of the study provided additional evidence for investors, portfolio managers and financial analysts to exploit confirmation bias to make an optimal portfolio allocation especially during COVID-19 and non-COVID-19 periods. Moreover, the findings of this study might be useful for investors as they help them to make successful investment decision in potential hedging strategies.

First, this is the first scientific work that conducts a stochastic analysis about the impact of emotional biases on the estimated returns and the expectations of optimists and pessimists in cryptocurrency and commodity markets. Second, the originality of this study stems from the fact that the authors make a comparative analysis of hedging behavior across different markets and different periods with and without the impact of confirmation bias. Third, this paper pays attention to the impact of confirmation bias on the expectations and hedging behavior in cryptocurrencies and commodities markets in extremely stressful periods such as the recent COVID-19 pandemic.

Aim of this study is to examine how environmental concern and perceived consumer effectiveness (PCE) mediate the effect of consumer optimism and pessimism on Generation Z's intention to purchase sustainable clothes.

A survey was administered to 247 Gen Z students using a quantitative methodology. Structural equation modeling was used for hypothesis testing.

The examination of findings provides support for the idea that both optimism and pessimism have a direct impact on environmental concerns and perceived consumer effectiveness. Additionally, it reveals that environmental concerns and perceived consumer effectiveness play a positive role in influencing sustainable clothing purchases.

This study is one of the first marketing studies to explore the relationship between personality traits, environmental concerns and the intention to purchase sustainable clothing, providing insight into their relationship.

Some methodological limitations impact the contributions of this cross-sectional investigation. It only tested a few variables predicting the intention to purchase sustainable clothing.

This research provides decision-makers, including marketers, with insights on leveraging dispositional traits to increase consumers' purchase intention of sustainable clothing.

Environmental concerns and PCE have a positive effect on sustainable clothing purchases, which are influenced by both optimism and pessimism.

The purpose of this paper is to analyse five biases in the valuation of financial investments using a mental time travel framework involving thought investments – with no objective time passing.

An investment’s initial value, together with any periodic funding cash-flows, are mentally projected forward (at an expected rate of return) to give the value at the investment horizon; and this projected value is mentally discounted back to the present. If there is a difference between the initial and present values, then this can imply a bias in valuation.

The study identifies (and gives examples of) five real-world valuation biases: biased funding cash-flow estimates (e.g., mega infrastructure projects); biased rate of return projections (e.g., market crises, tech stock carve-outs); biased discount rate estimates (e.g., dual-listed shares, dual-class shares, short-termism, time-risk misperception, and long-termism); time-duration misestimation or perception bias when projecting (e.g., time-contracted projections which lead to short-termism); and time-duration misestimation or perception bias when discounting (e.g., time-extended discounting which also leads to short-termism). More than one bias can be operating at the same time and we give an example of low levels of retirement savings being the result of the biased discounting of biased projections. Finally, we consider the effects of the different biases of different agents operating simultaneously.

The paper examines key systematic misestimation and psychological biases underlying financial investment valuation pricing anomalies.

The use of mobile digital devices requires secure behaviour while using these devices. To influence this behaviour, one should be able to adequately measure the behaviour. The purpose of this study is to establish a model for measuring secure behaviour, and to use this model to measure the secure behaviour of individuals while using mobile digital devices such as smartphones and laptops.

Based on a wide-ranging questionnaire (N = 1000), this study investigates the degree of influence that a relatively large number of factors have on secure behaviour while using mobile digital devices. These factors include knowledge and cognitive attitude, but also affective attitude, as well as several types of bias.

This study has provided a model for measuring secure behaviour. The results of the measurements show that knowledge, bias, cognitive attitude and affective attitude all have impact on secure behaviour while using mobile digital devices. Moreover, none of these factors is of minor importance.

This study shows that it is important to also consider previously undervalued factors, such as affective attitude and various types of bias, when designing interventions to improve secure behaviour while using mobile digital devices.

Most research on secure behaviour has only looked at a small number of influencing factors, usually limited to knowledge and cognitive attitude. This study shows that one needs a more elaborate model for measuring secure behaviour, and that previously undervalued factors have a clear influence on secure behaviour.

This study aims to explore what may have contributed to risk-taking travel behavior during the COVID-19 pandemic and what may be the drivers of satisfaction and intention to travel again. The study compares travelers based on their travel purposes (business, pleasure and visiting friends and relatives [VFR]) and explore the influence of subjective well-being received from their travel activities.

Data from a structured survey of 323 US residents who traveled during the COVID-19 pandemic were collected on MTurk. Respondents were asked travel behavior questions related to their favorite trips and to rate several multi-item scales measuring the benefits expected and received from their trip, the trip’s contribution to their positive mental and subjective psychological well-being, as well as their satisfaction with the trip and intention to travel in the future. In addition, personality measures focused on risk-taking, thrill-seeking and self-confidence, as well as additional risk-related concepts of optimism bias, probability neglect and proximity to self.

Data analysis revealed some differences among respondents who traveled for business, pleasure and VFR purposes. Business travelers were more risk takers and thrill seekers; pleasure travelers achieved more well-being benefits from their favorite trips during the pandemic; however, VFR travelers’ satisfaction and intention to go on similar trips were explained more by the benefits they received from their favorite trips.

Although several studies addressed consumers’ travel motivation during the COVID-19 pandemic, there is a lack of empirical research comparing the characteristics of travelers based on their travel purposes, as well as their sociodemographics, personality traits and the expected and perceived well-being benefits from traveling.

Cyberattacks have become a major threat to small and medium-sized enterprises. Their prevention efforts often prioritize technical solutions over human factors, despite humans posing the greatest risk. This article highlights the importance of developing tailored behavioral interventions. Through qualitative interviews, we identified three persona types with different psychological biases that increase the risk of cyberattacks. These psychological biases are a basis for creating behavioral interventions to strengthen the human factor and, thus, prevent cyberattacks.

We conducted structured, in-depth interviews with 44 employees, decision makers and IT service providers from small and medium-sized Swiss enterprises to understand insecure cyber behavior.

A thematic analysis revealed that, while knowledge about cyber risks is available, no one assumes responsibility for employees’ and decision makers’ behavior. The interview results suggest three personas for employees and decision makers: experts, deportees and repressors. We have derived corresponding biases from these three persona types that help explain the interviewees’ insecure cyber behavior.

This study provides evidence that employees differ in their cognitive biases. This implies that tailored interventions are more effective than one-size-fits7-all interventions. It is inherent in the idea of tailored interventions that they depend on multiple factors, such as cultural, organizational or individual factors. However, even if the segments change somewhat, it is still very likely that there are subgroups of employees that differ in terms of their misleading cognitive biases and risk behavior.

This article discusses behavior directed recommendations for tailored interventions in small and medium-sized enterprises to minimize cyber risks.

The contribution of this study is that it is the first to use personas and cognitive biases to understand insecure cyber behavior, and to explain why small and medium-sized enterprises do not implement behavior-based cybersecurity best practices. The personas and biases provide starting points for future research and interventions in practice.

The purpose of this paper is to highlight the prominent cognitive biases that influence Lean practices in organisations that have a multi-cultural work environment which will aid the organisational managers and academics in enhancing the understanding of the human thought process and mitigate them suitably.

A multiple case study was conducted in organisations that were previously committed to Lean practices and had a multi-cultural work environment. This research was conducted on five companies based on 99 in-depth semi-structured interviews and seven process observations that sought to establish the system-wide cognitive biases present in a multi-cultural Lean environment.

The novel findings indicate that nine new biases influence Lean implementation and practices in a multi-cultural environment. This study also found strong connectivity between Lean practices and 45 previously identified biases that could affect positively or negatively the lean methodologies and their implementation. Biases were resilient enough that their influence on Lean in multi-cultural workplaces, even with transient populations, did not demonstrate cultural differentiation.

Like any qualitative research, constructivism and narrative analyses are subjected to understanding based on knowledge gained on the subject, and data may have been interpreted differently. Constructivist co-recreation of process scenarios based result limitations is therefore acknowledged. The interactive participation in exploring the knowledge sought after and interaction that could have a probable influence on the participant need to be acknowledged. However, the research design, multiple methods of data collection, generalisation based on data collection and analysis methods limit the effects of these and findings are reliable to a greater extent.

The results can provide an enhanced understanding of biases and insights into a new managerial approach to take remedial steps on biases’ influence on Lean practices that can result in improved productivity and well-being from a business process perspective. Understanding and mitigating the prominent biases can aid Lean manufacturing processes and support decision makers and line managers in improving lean methodologies’ effectiveness and productivity. The biases can be negated and used to implement decisions with ease. The influence of biases and the model could be used as a basis to counter implementation barriers.

To the best of the authors’ knowledge, this is the first study that connects the cognitive perspectives of Lean business processes in a multi-cultural environment to identify the cognitive biases that influence Lean practices in organisations that were previously committed to Lean practices. The novel findings indicate that nine new biases and 45 previously identified biases influence Lean implementation and practices in a multi-cultural environment. The second novelty of this study shows the connection between cognitive biases, Lean implementation and practices in multi-cultural business processes.

The authors review the small but growing literature linking cognitive biases to food safety problems and foodborne illness outbreaks.

The authors conducted a search of peer-reviewed articles utilizing empirical methods published since the year 2000 focusing on food safety or foodborne illnesses/outbreaks and cognitive biases.

The authors find that most research is conducted at the consumer side of the food system, with few studies examining the potential problems that can arise in the production and processing of food. The authors also observe that most research tends to focus on a few cognitive biases.

This is the most comprehensive study to date examining insights from the literature on cognitive biases and the related discipline of behavioral economics to the specific problem of foodborne illness outbreaks and food safety problems.