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This study aims to explore and clarify the mechanism by which cognitive heuristics influence strategic decision-making during the coronavirus disease 2019 (COVID-19) pandemic in an emerging economy.

Data collection was conducted through a survey completed by 213 top-level managers from firms located in the twin cities of Pakistan. A convenient, purposively sampling technique and snowball method were used for data collection. To examine the relationship between cognitive heuristics and strategic decision-making, hypotheses were tested by using correlation and regression analysis.

The article provides further insights into the relationship between cognitive heuristics and strategic decision-making during the COVID-19 pandemic. The results suggest that cognitive heuristics (under-confidence, self-attribution and disposition effect) have a markedly negative influence on the strategic decision-making during the COVID-19 pandemic in an emerging economy.

The article encourages strategic decision-makers to avoid relying on cognitive heuristics or their feelings when making strategic decisions. It provides awareness and understanding of cognitive heuristics in strategic decision-making, which could be very useful for business actors such as managers and entire organizations. The findings of this study will help academicians, researchers and policymakers of emerging countries. Academicians can formulate new behavioural models that can depict the solutions to dealing with an uncertain situation like COVID-19. Policymakers and strategic decision-making teams can develop crisis management strategies based on concepts from behavioral strategy to better deal with similar circumstances in the future, such as COVID-19.

The paper’s novelty is that the authors have explored the mechanism by which cognitive heuristics influence strategic decision-making during the COVID-19 pandemic in an emerging economy. It adds to the literature in strategic management, explicitly probing the impact of cognitive heuristics on strategic decision-making; this field is in its initial stage, even in developed countries, while little work has been done in emerging countries.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-10-2021-0636.

The main aim of this paper is to empirically test at market level, the investors' differential reaction to information, contribution of their confidence level and adaptive behaviour to excessive market volatility in Indian stock market.

The Bivariate Vector Autoregression and Impulse Response Analysis are used to study whether investors over/under-react to private and public information. EGARCH models are used to study the contribution of investors' over/under-confidence and adaptive behaviour to excessive market volatility.

The investors over-react to private information and under-react to public information during pre-crash period, become overconfident and contribute to excessive volatility. They under-react to both private and public information during after-crash period, become under-confident and also conform to adaptive market hypothesis (AMH).

The empirical results of the study can help investors to minimize the negative impact of over/under-confidence on their expected utility.

The investors shall perform a post-analysis of investment, become aware of their past behavioural mistakes and start adapting to changing market conditions. This shall move the markets towards a new equilibrium in long run thus conforming AMH. However, the investors sometimes display an apparently irrational behaviour during this process.

To the best of the author's knowledge, this is the first study at market level data examining investors' over/under-reaction, over/under-confidence and adaptive behaviour in the context of stock market crash.

People are increasingly responsible for making sound financial decisions to foster their financial satisfaction and well-being, which magnifies the importance of financial literacy, and this concept and measurement is still not yet crystallized in the literature, specifically capturing different behavior perceptions. Moreover, there is not a distinction based on different classifications of behavior, such as over or underconfidence, to understand the relation between literacy and decision process. To fill this gap, this paper aims to investigate whether the financial literacy conceptual model proposed applies similarly to every group independently of their previous self-confidence perception. For this purpose and quality control, OECD (2016) data were used with a final sample of 1,487 Brazilian citizens. Quantitative analysis technique using partial least squares structural equations path modeling and differences between groups using multi-group analysis was applied. In line with general studies, when analyzing the financial literacy usual model for the group as a whole, financial knowledge construct positively influences self-confidence, and both together positively affect financial behavior. However, for individuals with low financial knowledge and low self-confidence, as well as for those with too much or too little confidence, the model did not hold. Therefore, self-confidence perception influences the way financial knowledge is used for financial decisions and should be addressed in financial education and training to be more effective.

To operationalize the variables and test the paper’s hypotheses, the authors used the methodology developed in OECD (2016), based on the research instrument’s Brazilian application adapted from the questionnaire developed in OECD (2015), with data initially used and made available by Garber and Koyama (2016). Based on the recommendations of Hair Jr et al. (2017a, 2017b), the authors used partial least squares modeling PLS-PM (SmartPLS 3.2.6) to estimate the structural models.

Concerning structural relationships, the final model showed knowledge with a positive influence on self-confidence, self-confidence with a positive effect on behavior and knowledge with a positive influence on behavior, both directly and, through its relationship with self-confidence, indirectly. This underscores that, for the total sample, the greater people’s knowledge and self-confidence, the better their behavior. The unexpected absence of attitude in the final model, even allowing for potential measurement problems, brings up an important reflection on the mediating effect that the self-control variable may exert between attitude and behavior. A person may believe that saving for the future is important (attitude) but whether they actually save (behavior) may depend on self-control, which is needed to prevent immediate gains from being prioritized in practice.

The findings reported so far concern the study’s total sample. However, as expected from the literature review that provides the basis for the sixth and the most important hypothesis, respondents were found to be heterogeneous in terms of knowledge and self-confidence levels. These differences were evaluated by means of multi-group analyses that indicated that the model does not apply to respondents with low knowledge and low self-confidence and to those who are over- and underconfident. This implies inferring that financial education programs may be of little use if they only address technical knowledge development and fail to consider behavioral aspects such as those related to self-confidence, as this paper points out, and others. This signals the importance of diagnosing people’s profiles to enable developing solutions capable of minimizing the presence of behavioral biases. This need to be studied further.

The results imply inferring that financial education programs may be of little use if they only address technical knowledge development and fail to consider behavioral aspects such as those related to self-confidence, as this paper points out, and others. Models must be reviewed in light of natural diferences of cognition and lead to customized financial education.

This signals the importance of diagnosing people’s profiles to enable developing solutions capable of minimizing the presence of behavioral biases. Therefore, not only training topics in personal finance but also a deeper education program since the kindergarden must be considered.

Its practical contribution is to suggest the development of financial education programs that also take account of the potential presence of behavioral biases, which may prevent the misallocation of (scarce) public- and private-sector funds stemming from a limited focus on developing the population’s actual financial knowledge.

This paper examines the effect of overconfident yield forecasting (optimism bias) on crop insurance coverage level choices across both yield and revenue insurance.

This study simulates a representative producer’s preferred coverage level for both yield and revenue insurance under three potential models of decision-making and four potential manifestations of overconfident yield forecasting. The study then uses this framework to examine how coverage level choices change as overconfidence increases (decreases).

As overconfidence increases, producers prefer lower levels of crop insurance coverage than they would otherwise prefer, with extreme overconfidence inducing farmers to buy no insurance at all. While overconfidence affects cross-coverage demand for revenue and yield insurance similarly, this effect is more pronounced for yield insurance. Cross-coverage level demand for revenue insurance is relatively stable across changes in the correlation between prices and yields.

This research has important implications for crop insurance subsidy design and crop insurance demand modeling.

There is a growing body of literature suggesting that producers are overconfident with regard to their future yield risk and that this bias reduces their willingness to pay for risk management tools such as crop insurance. This is the first study to look at how such overconfidence affects cross-coverage level demand for crop insurance.

Studies on consumer knowledge calibration have used different measures of calibration. The purpose of this paper is to undertake a comparative assessment of important measures. In addition, it seeks to identify the best performing measure.

The paper reports on three studies. The first study uses eight survey data sets. The second and third studies use experiments.

The study found that the Brier score component measure is most responsive to feedback and is the most suitable measure of knowledge calibration. The results also indicate that researchers should use measures that use item-level confidence judgements, as against an overall confidence judgement.

By documenting the relationship between the different measures of knowledge calibration, the study enables proper interpretation and accumulation of results of various studies that have used different measures. The study also provides guidance to researchers in psychology and education where this issue has been noted.

The study provides guidance to managers in knowledge intensive industries, such as finance and insurance, interested in understanding their consumers’ knowledge calibration.

This is the first study in consumer research that examines this issue.

This paper aims to identify changes in individual investors’ preferences, prominent sentiments in the market, behavioural tendencies and biases demonstrated as a result of the COVID-19 pandemic.

As the study is exploratory social research, the design is also structured as such. In total, 69 Securities and Exchange Board of India-registered investment advisors catering to investors of diverse profiles, experiences and locales are engaged through in-depth semi-structured interviews. The responses are categorised thematically using a data structure model.

Investors are guided by an inclination for safer and liquid asset classes and prefer fixed income securities. The authors observe various emotional reactions – inexperienced investors panic, experienced investors act maturely, while a few of both naïve and sophisticated investors are opportunistic contrarians. Lower valuations, ease of access to digital infrastructure for trading and social norms attract many first-time individual investors, causing a phenomenon identified as the “new investor boom”. Apart from the biases identified during the financial crisis, the authors also detect evidence of cognitive dissonance, bandwagon effect, fear-of-missing-out syndrome, disposition effect and others.

The paper also discusses some noticeable behavioural tendencies displayed by the individual investors and compiles helpful strategies to successfully navigate any such financial crisis.

An individual investor is a least aware and most affected stakeholder in any crisis, so this study contributes newer insights to ensure their financial well-being.

The study’s originality lies in adopting a qualitative methodology that uses investment advisors’ professional experience to unveil the sub-structures of investor psychology and decision-making behaviour during COVID-19.

During the running of automobile, the stabilizer bar is frequently subjected to the impact of complex random loads, which is prone to fatigue failure and accident. In regard to this, the purpose of this paper is to study and discuss fatigue life of automobile stabilizer bar.

Durability bench test shows that failure is located at the joint of sleeve and stabilizer bar body. Based on the collection and compilation of micro-strain load spectrum of the stabilizer bar, the strain-life model is studied considering the influence of average stress and maximum stress at failure area. Seven-grade strain-life curves of the stabilizer bar are established. According to the principle of linear damage accumulation, the relationship between fatigue life and damage is discussed, then the fatigue life of stabilizer bar is predicted. Fatigue life evaluation is carried out from three aspects: reliability analysis, static analysis and fatigue life simulation.

The results show that the reliability of the test sample is 99.9 percent when the confidence is 90 percent and the durability is 1,073 load spectrum cycles; the ratios of predicted and simulated life to design life are 2.77 and 2.30, respectively.

Based on the road load characteristics of automobile stabilizer bar, the method of fatigue life prediction and evaluation is discussed, which provides a basis for the design and development of automobile chassis components.

The purpose of this paper is to provide an evaluation method for agricultural catastrophic risk.

Data on agricultural disaster loss are collected based on hectares covered by natural disasters, hectares affected by natural disasters, and hectares destroyed by natural disasters using the standard process. Peak over threshold (POT) approach based on the extreme value theory is used to model the distribution of agricultural catastrophic loss, and value at risk (VaR) is used to assess agricultural catastrophic risk.

This paper provides an approach for collecting agricultural loss data and modelling probability distribution of agricultural catastrophic loss, which is promising for agricultural catastrophic risk evaluating. As the quantified measurement of agricultural catastrophic risk, VaR is observed to be appropriate and feasible. Results of empirical research demonstrate that drought catastrophe negatively affects grain‐production in the northeast region of China; in particular, the drought catastrophic risk is severe within a 100‐year scenario and thus is expected to recur.

To provide an accurate agricultural catastrophic risk assessment, data collection based on disaster occurrence instead of crop yield, and VaR is used in this paper.

Although there are myriads of books on how children learn and can therefore be taught, those teaching in further and higher education, and indeed in training, are much more thinly serviced. And yet paradoxically it is in these areas of education that there are fewest ‘professionals’, most academics and trainees having to rely on short courses which are rarely mandatory. Student activism has only occasionally concerned itself with the actual learning situation, and generally classes are either too awed, polite or indifferent to provide the tutors with the feedback essential to their professional growth.

The purpose of this paper is to investigate differences in how men and women small- and medium-sized enterprise (SME) entrepreneurs make decisions regarding whether to invest in technologies for their firms. Answering recent calls for a gendered perspective in entrepreneurial decision-making, this study integrates premises from social identity theory and role congruity theory to help explain innovation investment decisions among male and female SME entrepreneurs.

Using data from 121 SME entrepreneurs in the dry cleaning industry, the authors employ a conjoint experimental methodology to capture decisions SME entrepreneurs make to adopt or reject an environment-friendly dry cleaning technology. The authors examine the role gender, firm revenue, technology price, and technology complexity play in entrepreneur investment decisions.

The authors find that gender indirectly impacts innovation purchase decisions through interactions with firm revenue and key innovation characteristics. Women SME entrepreneurs were less likely to purchase the technology than their male counterparts at low (and high) firm revenue, high innovation price, and high innovation complexity—all highly risky, masculine, choice contexts.

These findings suggest that men and women's entrepreneurial investment decisions might be shaped by gender stereotypes. Future research should sample additional industries and determine the norms guiding gendered decision-making.

Beyond the decision to launch a new venture, this multi-level analysis, using the lens of social identity and role congruity theories, helps illuminate how men and women SME entrepreneurs approach innovation investment decision-making in significantly different—and gender role consistent—ways.