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This paper aims to analyze how judgment bias (optimism vs pessimism) and temporal distance influence self-control decisions. This research also analyzes the mediating role of perceived control on judgment bias and temporal distance.

Three studies (one laboratory and two online experiments) analyze how judgment bias and temporal distance influence self-control decisions on consumers’ willingness to pay.

The findings uncover an important boundary condition of temporal distance on self-control decisions. In contrast to previous research, the findings indicate that individuals exposed to optimism (vs pessimism) bias display more self-control in the future and make choices that are more indulgent in the present. The findings also reveal that perceived control mediates the effects of judgment bias and temporal distance.

The findings help managers to adapt short- and long-term marketing efforts, based on consumers’ momentary judgment biases and on their chronic judgment bias orientation.

This research contributes to the literature on self-control and temporal distance, showing that judgment bias reverses previous research findings on self-control decisions.

The purpose of this paper is to examine how upstream social marketing can benefit from using social media commentary to identify cognitive biases. Using reactions to leading media/news publications/articles related to climate and energy policy in Australia, this paper aims to understand underlying community cognitive biases and their reasonings.

Social listening was used to gather community commentary about climate and energy policy in Australia. This allowed the coding of natural language data to determine underlying cognitive biases inherent in the community. In all, 2,700 Facebook comments were collected from 27 news articles dated between January 2018 and March 2020 using exportcomments.com. Team coding was used to ensure consistency in interpretation.

Nine key cognitive bias were noted, including, pessimism, just-world, confirmation, optimum, curse of knowledge, Dunning–Kruger, self-serving, concision and converge biases. Additionally, the authors report on the interactive nature of these biases. Right-leaning audiences are perceived to be willfully uninformed and motivated by self-interest; centric audiences want solutions based on common-sense for the common good; and left-leaning supporters of progressive climate change policy are typically pessimistic about the future of climate and energy policy in Australia. Impacts of powerful media organization shaping biases are also explored.

Through a greater understanding of the types of cognitive biases, policy-makers are able to better design and execute influential upstream social marketing campaigns.

The study demonstrates that observing cognitive biases through social listening can assist upstream social marketing understand community biases and underlying reasonings towards climate and energy policy.

The purpose of this paper is to investigate how counterfeit users estimate the probability of being detected and how this probability affects their counterfeit consumption behaviour. Specifically, it addresses three questions: do perceived social consequences influence counterfeit users’ probability estimate of being detected? What is the psychological mechanism underlying the estimation of this probability? And how does this probability estimate affect counterfeit purchase and usage intentions?

The authors used three scenario-based experimental studies with university students in Hong Kong, a place where counterfeit products are widely available. First study used a factitious brand of jeans as the stimulus and the other two studies used a Ralph Lauren polo shirt. In each study, the authors measured participants’ responses towards counterfeit purchase and the probability of being detected after they read the relevant brand information and had a close-up view of the attributes in the genuine and counterfeit versions.

The authors found that counterfeit users are susceptible to a pessimism bias such that they estimate a higher probability of being detected when they judge the outcome of being detected as more severe and this bias is driven by the spotlight effect in that counterfeit users judging the outcome as more severe tend to perceive that others pay more attention to their counterfeit usage. Moreover, this pessimism bias is mitigated when the target user is another person instead of oneself, thus suggesting the egocentric nature of the bias.

The authors used undergraduate students and scenario-based experimental approach in all the studies that may limit the generalisability of the findings.

The results suggest that brand managers should emphasise the importance of negative social consequences and highlight the role of outcome severity and egocentric bias in their advertising and communication programmes in order to curb counterfeit consumption.

The research contributes to the growing literature on counterfeit consumption by studying the process underlying estimation of the probability of being detected by others, an important but often neglected factor that influences counterfeit purchase decision. The authors also highlight the role of outcome severity and egocentric bias in this process.

Purpose: Risk is a multifaceted concept, and its identification requires complex approaches that are often misunderstood. The consequence is that decisions are based on limited perception rather than the full value and meaning of what risk is, as a result, the way it is being tackled is incorrect. The individuals are often limited in their perceptions and ideas and do not embrace the full multifaceted nature of risk. Regulators and individuals want to follow norms and checklists or overuse models, simulations, and templates, thereby reducing responsibility for decision-making. At the same time, the wider use of technology and rules reduces the critical thinking of individuals. We advance the automation process by building robots that follow protocols and forget about the part of risk assessment that cannot be programed. Therefore, with this study, the objective of this study was to discover how people define risk, the influencing factors of risk perception and how they behave toward this perception. The authors also determine how the perception differed with age, gender, marital status, education level and region. The novelty of the research is related to individual risk perception during COVID-19, as this is a new and unknown phenomenon. Methodology: The research is based on the analysis of the self-administered purposely designed questionnaires we distributed across different social media platforms between February and June 2020 in Europe and in some cases was carried out as a interview over communication platforms such as “Skype,” “Zoom” and “Microsoft Teams.” The questionnaire was divided into four parts: Section 1 was designed to collect demographic information from the participants; Section 2 included risk definition statements obtained from literature and a preliminary discussion with peers; Section 3 included risk behavior statements; and Section 4 included statements on risk perception experiences. A five-point Likert Scale was provided, and participants were required to answer along a scale of “1” for “Strongly Agree” to “5” for “Strongly Disagree.” Participants also had the option to elaborate further and provide additional comments in an open-ended box provided at the end of the section. 466 valid responses were received. Thematic analysis was carried out to analyze the interviews and the open-ended questions, while the questionnaire responses were analyzed using various quantitative methods on IBM SPSS (version 23). Findings: The results of the analysis indicate that individuals evaluate the risk before making a decision and view risk as both a loss and opportunity. The study identifies nine factors influencing risk perception. Nevertheless, it must be emphasized that we can continue to develop models and rules, but as long as the risk is not understood, we will never achieve anything.

The purpose of this paper is to capture the presence and impact of optimism in the Indian equity market.

The data set comprises the daily values of the Nifty 50 index, index options and Treasury-bill index for a period of five years (2006-2011). The focus of this paper is two pronged. It first investigates the presence of optimism (pessimism) using the pricing kernel technique suggested by Barone-Adesi et al. (2012). Second, it tries to analyze the relationship of this bias with stock market indicators like risk premium, market return and volatility using time series regression.

The findings indicate that the Indian equity market has been predominantly pessimistic from the period 2006 to 2011. The interaction of this bias with market indicators also unveils some interesting insights. The study shows that high past volatility can lead to pessimism in the Indian equity market and vice versa. It further explores that when the investors are rational, their risk and return relationship is positive while it tends to be negative when they are irrational. The impact of investors’ irrationalities on asset valuation has also been accounted by Brown and Cliff (2005).

The findings of the paper have significant implications for fund managers and asset management companies. It is recommended that they should try to identify behavioral biases in their clients before designing their portfolios.

This study is one of the very few attempts to capture the presence and impact optimism (pessimism) in the Indian equity market.

This study examines the role of behavioural factors, such as confidence, optimism, pessimism and rational expectation, in affecting investment decisions in the Pakistani stock market.

Using daily trading data of Karachi Stock Exchange-100 index from January 2012 to December 2015, different regression models, including descriptive statistics and stationarity tests, are performed.

Results indicate that stock market trading has suffered from pessimistic behaviour of investors. In the first model, the authors find a positive sign of confidence and negative sign of optimism with the trading volume. The second model shows a positive role of confidence and rational expectations in affecting the trading volume in daily, Monday and Friday samples. The results of the third model show a negative sign of both optimism and rational expectation with the trading volume. Furthermore, the next model shows a negative sign of confidence combined with pessimism while testing their relationship with the trading volume. Finally, results of the final model suggest that optimism negatively affects the trading volume, and on the other hand, pessimism has a positive impact on the trading volume.

The method and empirical testing of behavioural biases and their relationship with economic variable used in this study seem to be a promising way to better understand the role of psychology in deriving financial decisions for academics and policymakers.

This study uses secondary data for measuring behavioural biases and decomposes the effect between rational expectation and behavioural biases.

The purpose of this paper is to examine the presence the behavioral biases in Indian investors specifically, overconfidence, excessive optimism (pessimism), herd behavior and the disposition effect. It further investigates the role of demographics and investor sophistication in influencing the biases. Finally, it reveals which bias is most prevalent in the Indian context.

For this purpose, a survey has been conducted on the investors of the Delhi/NCR area. The data have been collected with the help of a structured questionnaire that is analyzed with the help of relevant statistical tools.

The survey evidence shows that behavioral biases are dependent on investors’ demographics and their trading sophistication with highest influencing factors being age, profession and trading frequency. Each bias corresponds to a specific set of investor characteristics and overconfidence comes out to be the most important bias in the Indian context.

The potential limitations of the present survey can be ascribed to socially desirable responses and their difference with actual market behavior. Further, due to time and resource constraint, the data set is limited to investors of only Delhi/NCR.

This study is most relevant for financial advisors, as it facilitates them in gaining a better understanding of their clients’ psychology. It can aid them in developing behaviorally modified portfolio, which best suits their clients’ predisposition.

The paper gives a unique insight on the investors’ profile corresponding to each bias under consideration. It not only updates the evidence on behavioral biases but also highlights which bias is the most influential in the Indian context.

The literature documents a shortage in the supply of external funding to small- and medium-sized enterprises (SMEs) in general and to innovative SMEs in particular. This study separates cognitive from financial constraints on innovative SMEs’ growth opportunities. Using data gathered through in-depth interviews with the CEOs of 115 SMEs, we reveal that over and above a problem with supply, there exists a twofold problem on the demand side. Specifically, we document that there is a tendency for these companies to avoid approaching external funding sources, especially ones that gear their investments toward innovation. Our results reveal a cognitive bias (over-pessimism) affecting the entrepreneurs’ (lack of) demand for external financing over and above other firm-specific factors. CEO tenure — our proxy for human and social capital — is significantly lower (higher) in firms that did (did not) pursue external funding. This finding may provide some support for our hypothesis regarding the cognitive bias and over-pessimism of the more veteran CEOs who have had negative experiences regarding recruiting external resources. The impact of this entrepreneurial cognition is shown to be economically detrimental to the enterprise. Nevertheless, the negative effects are not limited to the micro level, but have implications at the macro level as well, due to under-realization of the potential for employment, productivity, and growth of the firms comprising the vast majority of the economy.

The current study aims to investigate the impacts of two behavioral biases, namely, loss aversion and overconfidence on the performance of US companies. First, the impact of loss aversion on the economic performance of companies was assessed. Second, the impact of overconfidence on market performance was discussed.

This study used around 6,777 quarterly observations on the population of US-insured industrial and services companies over the 2006-2016 period. Ordinary least squares (OLS) regression in two panel data models were used to test the hypotheses formulated for the study.

It was documented that the loss-aversion bias negatively affects the economic performance of companies and this is achieved for both sectors. In contrast, the findings suggest that overconfidence positively affects market performance of industrial firms but negatively affects market performance in service firms. Further robust evidence was found that overconfidence bias seems to be dominant, and hence, investors may tend to be more overconfident rather than more loss-averse.

This research can be extended by focusing on the following question: What is the impact of the contradictory (positive and negative) effects of an investor's loss aversion and overconfidence on the US company performance in case of realization of a stock market crisis or stock market crash?