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The COVID-19 pandemic has resulted in significant changes in consumer behaviour, which has had a cascading effect on consumer-centric logistics. As a result, this study conducts a focused literature review of pandemic-related consumer behaviour research to address two research questions: 1) what are the pandemic's direct effects on consumer consumption behaviour, with an emphasis on changes in their basic and psychological needs? and 2) what are the consequences of behavioural changes on consumer-centric logistics?

The scientific procedure and rationales for systematic literature review (SPAR-4-SLR) protocol and the theory, context, characteristics and methodology (TCCM) framework were adopted as a guideline to map, refine, evaluate and synthesise the literature. A total of 53 research articles were identified for further analysis.

Using Maslow's hierarchy of human needs as a theoretical guide, this review synthesises the COVID-19 pandemic's effects on consumer behaviour into four categories: abnormal buying behaviour, changes in consumer preferences, digitalisation of shopping behaviour and technology-related behaviour. Furthermore, four consumer-centric logistics propositions are proposed based on the four aspects of consumer behavioural changes.

This study outlines the significant behavioural changes in consumers in the face of the COVID-19 pandemic and how these changes impact consumer-centric logistics, with implications for managing consumers' involvement in logistics and pointing out future research directions.

This paper aims to provide a comprehensive conceptual framework and strong arguments with an intent to examine the stock market variables (predictors) indicating the money laundering (ML) and terrorism financing (FT) proceeds.

This paper provides a comprehensive review of ML/FT through the stock market across developed, developing and emerging jurisdictions, sheds light on the existing literature and critically evaluates the gap in the relevant studies. Moving forward, this paper develops the conceptual framework and formulates hypotheses to explore the empirical relationship.

This paper advocates and finds a basis to carry out much-needed empirical research between the ML/FT and stock market keeping in view the growing criminal cases in the developing countries. This paper suggests mining proxies from the publically available stock market data and the results of existing seminal research as variables of the study. These data and results carry information about the ML determinants. After developing hypothetical research providing concepts, this paper also finds that using a suitable methodology, preferable Bayesian logistic and linear regression models, it is possible to find the typologies and factors that can indicate and endorse the use of the stock market for ML/FT. Broadly, it is found that the significance of this study will be two-pronged: empirical development and policy implications.

This paper mainly focuses on the developing region, a newly emerging market and, peculiarly, a grey-listed region by the Financial Action Task Force (FATF).

In light of the existing literature and to the best of the researchers’ knowledge, this study will bring into focus the new age of the action research on the ML regime in the securities markets of the developing countries, hence, the emerging markets. Moreover, this research shall have a sheer significance for the policy measures on FATF recommendations on ML and FT, especially for the countries listed as “grey”.

The research based on comprehensive review will help in controlling the social behaviours aiding the proceeds of ML.

This research is extremely novel to the best of the researcher's knowledge.

In this paper, we investigate the process by which social control agents define wrongdoing over time and the principles they employ in drawing the boundary between right and wrong. We empirically examine how Italian state actors sought over four decades to categorize behaviors in the so-called “gray area,” i.e., the conduct of individuals supportive of the mafia organization Cosa Nostra and its criminal aims, but not members of the organization. Based on an archival analysis of texts produced since the 1960s, we reconstruct how state actors started from a preliminary definition of wrongdoing, moved to stigmatize the behaviors in question on moral grounds, and ultimately criminalized them with legal sanctions. We conceptualize the main principles behind this evolving categorization as intentionality of conduct, freedom of choice, and scope of harm. The paper contributes to the debate on the factors and conditions shaping the definition of wrongdoing over time and the contribution that social control agents provide to this aim.

As convenience and anonymity, people with mental illness are increasingly willing to communicate and share information through social media platforms to receive emotional and spiritual support. The purpose of this paper is to identify the degree of depression based on people's behavioral patterns and discussion content on the Internet.

Based on the previous studies on depression, the severity of depression is divided into four categories: no significant depressive symptoms, mild MDD, moderate MDD and severe MDD, and defined each of them. Next, in order to automatically identify the severity, the authors proposed social media digital cues to identify the severity of depression, which include textual lexical features, depressive language features and social behavioral features. Finally, the authors evaluate a system that is developed based on social media digital cues in the experiment using social media data.

The social media digital cues including textual lexical features, depressive language features and social behavioral features (F1, F2 and F3) is the relatively best one to classify four different levels of depression.

This paper innovatively proposes a social media data-based framework (SMDF) to identify and predict different degrees of depression through social media digital cues and evaluates the accuracy of the detection through social media data, providing useful attempts for the identification and intervention of depression.

Abnormal behaviors such as rework, backlog, changes and claims generated by project organizations are unavoidable in complex projects. When abnormal behaviors emerge, the previously normal state of interactions between organizations will be altered to some extent. However, previous studies have ignored the associations and interactions between organizations in the context of abnormal organizational behaviors (AOBs), making this challenging to cope with AOBs. As a result, the objective of this paper is to explore how to reduce AOBs in complex projects at the organizational level from a network perspective.

To overcome the inherent limitations of a single case study, this research integrated two data collection methods: questionnaire survey and expert scoring method. The questionnaire survey captured the universal data on the influence possibility of AOBs between complex project organizations and the expert scoring method got the influence probability scores of AOBs between organizations in the case. Using these data, four organizational influence network models of AOBs based on a case were developed to demonstrate how to destroy AOBs networks in complex projects using network attack theory (NAT).

First, the findings show that controlling AOBs generated by key organizations preferentially and improving the ability of key organizations can weaken AOBs network, enabling more effective coping strategies. Second, the owners, government, material suppliers and designers are identified as key organizations across all four influence networks of AOBs. Third, change and claim behaviors are more manageable from the organizational level.

Project managers can target specific organizations for intervention, weaken the AOBs network by applying NAT and achieve better project outcomes through coping strategies. Additionally, by taking a network perspective, this research provides a novel approach to comprehending the associations and interactions between organizations in the context of complex projects.

This paper proposes a new approach to investigating AOBs in complex projects by simultaneously examining rework, backlog, change and claim. Leveraging NAT as a novel tool for managing the harmful effects of influence networks, this study extends the knowledge body in the field of organizational behavior (OB) management and complex project management.

This study aims to examine the behaviour of institutional and retail investors in response to news about industry leaders (peer firms) and to determine its impact on the stock prices of other firms (focal firms) within the same industry.

The study investigates the impact of peer news on investor behaviour of Chinese A-shares listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2019. The media coverage of industry leaders is sourced from prominent Chinese online financial outlets and the Chinese Financial Press. Support vector machine is applied to identify the positive, neutral and negative news within the articles. The study uses event study and logistic regression to examine the effects of peer news on focal firms’ investor behaviour.

The results show that both good and bad news about leaders cause peers’ stock prices to increase initially, but then reverse within one quarter. Further analysis reveals that when leaders’ shares receive positive news coverage, institutional investors tend to exert excessive abnormal buying pressure on peers’ shares, resulting in overreactions. Conversely, retail investors do not actively trade on peers on leaders’ news day due to limited attention. In addition, the study shows that short-selling constraint inhibits bad news from reflecting in the stock prices.

The study highlights differences in investor behaviour. The finding that institutional investors tend to overreact more to peer firms’ news when focal firms are smaller and have a lower frequency of information disclosure supports the salient theory. This is consistent with the previous framework that suggests overreaction is more pronounced when it is difficult to combine external sources of information to evaluate the focal firms. In contrast, retail investors do not engage in active trading on peers on leaders’ news day due to the limited attention theory.

This study aims to examine investor attention by exploring the trading behavior of investors in US-based exchange traded funds (ETFs) of countries active in the Federation Internationale de Football Association (FIFA) World Cups.

The present study employs event study methodology to measure abnormal returns and excess trading volume of country-specific ETFs during six FIFA World Cups. The sample of ETFs includes 19 participating countries.

Consistent with investor behavior that might be explained by attention effect, the study finds that country-specific ETFs from participating countries do indeed behave differently during FIFA World Cups events. The authors find significant evidence of abnormal trading volume and, albeit weaker, abnormal returns during cups.

This study contributes to the literature on investor behavior, linking investor attention with salient sports events.

This study aims to examine differences in regret between individuals with high vs low self-esteem that follows from negative appraisals for unsuccessful consumer decisions that are either congruent or not with perceived norms. This study also tested the mediating role of decision responsibility and the ability of psychological repair work in regulating regret.

Hypotheses were tested through four experimental studies using student and international panel samples across different consumer decision scenarios to generalize the findings of the study.

This study shows that high self-esteem individuals regret less a bad decision when it is congruent (normal) than when it is incongruent (abnormal) with the prevalent norms, while lower self-esteem individuals tend to regret equally both normal and abnormal decisions. This study further shows that this effect is driven by internal responsibility attributions. Finally, the results also suggest that high self-esteem people are more efficient than low self-esteem people in regulating regret, but only when the decision is abnormal.

The present research has important contributions to both regret and self-esteem literature. First, this study explored the role of self-esteem on regret, an individual variable that has been studied relatively little in regret literature. Second, this study has shown, consistent with recent findings, that decision congruence with the norms is a more suitable predictor of regret than whether the decision involves action or inaction. Finally, this study showed that stimulating individuals to self-enhance by engaging in psychological repair work led individuals to regulate regret, consistent with regret regulation theory.

This study aims to investigate the perspective of corporate philanthropy during the coronavirus disease 2019 (COVID-19) in China for firms with various levels of corporate social responsibility (CSR). Specifically, the study appraises the impact of the COVID-19 pandemic on the stock returns and sustainable development of Chinese-listed companies and determines the likelihood of paying donations vis-à-vis firm reputation.

The study used data from 117 Chinese-listed firms engaged in philanthropy during the COVID-19 pandemic. The authors also utilized the stock returns and cash donation data, and owing to the cross-sectional data and continuous nature of dependent variables, they employed the ordinary least squares regression to test the research hypotheses.

The results show that irresponsible actions have a positive relationship with donations. The study particularly reveals that irresponsible firms have significant negative abnormal returns during the first wave of the COVID-19 pandemic.

To the best of our knowledge, this is the first empirical study to explore the perspective of corporate philanthropy during the COVID-19 pandemic for companies with different CSR levels. This study contributes to the empirical research on CSR and provides insights for managerial-cum-financial decisions to encourage managers of irresponsible firms to pursue philanthropic behaviors after crisis events.

As a financial policy, dividend policy significantly affects firm value. This chapter analyzes how stock prices react to dividend decisions. First, a dividend payment is an extraction of value; therefore, stock price theoretically drops by the dividend amount on the ex-dividend day. In practice, the price drop and the dividend magnitude are not equal because of tax clientele, short-term trading, and market microstructure. Investors are indifferent in trading stocks before and after stocks go ex-dividend if they obtain equal marginal benefits from the two trading times. The difference in tax rates on dividends and capital gains leads to the gap between the price drop and the dividend amount. Moreover, if transaction costs are considerable, investors have high incentives to short-sell stocks until they cannot obtain more profits. The final outcome of this short-term trading is the difference between the price drop and the dividend amount. Furthermore, market microstructure factors such as limit orders, bid-ask spread, and price discreteness also create this gap. Second, dividend announcements convey valuable information to outsiders. When firms announce increases (decreases) in dividends, their stock prices tend to increase (decrease). Third, dividend policy is negatively related to stock price volatility. This negative relationship is explained by duration effect, rate of return effect, arbitrage realization effect, and information effect. Empirical evidence for this relationship is found in many countries. Finally, dividend smoothing is also considered as a signal about firms' future earnings. Consequently, firms with stable dividends have higher market value. In other words, dividend stability has a positive effect on stock prices.