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The aim of this paper is to systematically review the literature published in recognized journals focused on recognition-based heuristics and their effect on investment management activities and to ascertain some substantial gaps related to them.

For doing research synthesis, systematic literature review approach was applied considering research studies published within the time period, i.e. 1980–2020. This study attempted to accomplish a critical review of 59 studies out of 118 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioural finance domain-related explicitly to recognition-based heuristics and their effect on investment management activities.

The survey and analysis suggest investors consistently rely on the recognition-based heuristic-driven biases when trading stocks, resulting in irrational decisions, and an investment strategy constructed by implementing the recognition-based heuristics, would not result in better returns to investors on a consistent basis. Institutional investors are less likely to be affected by these name-based behavioural biases in comparison to individual investors. However, under the context of ecological rationality, recognition-based heuristics work better and sometimes dominate the classical methods. The research scholars from the behavioural finance community have highlighted that recognition-based heuristics and their impact on investment management activities are high profile areas, needed to be explored further in the field of behavioural finance. The study of recognition-based heuristic-driven biases has been found to be insufficient in the context of emerging economies like Pakistan.

The skilful understanding and knowledge of the recognition-based heuristic-driven biases will help the investors, financial institutions and policy-makers to overcome the adverse effect of these behavioural biases in the stock market. This article provides a detailed explanation of recognition-based heuristic-driven biases and their influence on investment management activities which could be very useful for finance practitioners’ such as investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/ broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making its financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on recognition-based heuristic-driven biases displayed by investors. The current study is original in discussing the role of recognition-based heuristic-driven biases in investment management activities by means of research synthesis. This paper is useful to researchers, academicians, and those working in the area of behavioural finance in understanding the role that recognition-based heuristics plays in investment management activities.

As public awareness of the concept of sustainable development has increased, a new investor market has appeared. These investors will only make investments in sustainable financial instruments. Yet, how corporate managers can effectively exploit this new financing concept to make their companies risk resilient remains unaddressed. This study, a conceptual research, aims to examine the impact of sustainable finance (SF) on business risk resilience (BR) and the impact of SF on risk management infrastructure (RI). It also addresses the impact of RI on BR and the mediating effect of the former between SF and BR in the corporate world. Finally, this research explores the moderating effect of managerial capability (MC) and firm technology-focused innovation capability (IC) between SF and RI.

This study incorporates both theoretical and empirical works in the sustainability, innovation, risk management and HRM fields. Afterwards, it constructs a conceptual model alongside suppositions that can be tested in further studies.

This study proposes that SF will enhance BR and RI. Moreover, RI will promote BR and positively intervene between SF and BR. Furthermore, MC and IC will reinforce the SF–RI impact such that the SF–RI impact will be strengthened for companies whose MCs and ICs are high than low.

This research affords suggestions for researchers in multidisciplinary fields. It reinforces BR and RI by introducing SF, MC and IC as tactical devices. It also serves as a reference point for forthcoming academics to investigate this conceptual model, empirically, in diverse industries worldwide.

Practical lessons for finance, investment and risk managers, as well as corporate investors are discussed.

This study provides a new research model that demonstrates how SF can be exploited to promote BR and build RI. It also shows how RI can bolster BR and how RI can connect SF to BR. This new model also exhibits how MC and IC moderate the impacts of SF and RI. Thus, it attempts to advance existing knowledge and theoretical frameworks.

Turnover in high-tech companies has long been a concern for managers and executives. Recent meta-analyses from the general turnover literature consistently show that job satisfaction is a major attitudinal antecedent to turnover intention and turnover behavior. Additionally, the available research on information technology (IT) employees focuses primarily on turnover intentions and not on a risky decision-making perspective and actual turnover (turnover behavior). The paper aim is to focus on that.

This study uses hierarchical ordinary least squares, process (Preacher and Hayes, 2004) and logistic regression.

The main predictor of actual turnover is risky decision-making, whereas job satisfaction is the main predictor of turnover intention.

The joint effects of risk and job satisfaction on turnover intention and behavior have not been studied in the IT domain. Hence, this study extends our understanding of turnover in general and particularly among IT employees by studying the combined effect of risk and job satisfaction on turnover intentions and turnover behavior. The study’s theoretical and practical implications are likewise discussed.

Hospitality firms adopted diverse hiring policies and public declarations of support for LGBTQ+ causes through brand activism. The impact of activism on LGBTQ+ employees’ workplace experiences has been ambiguous. This study aims to examine the hospitality and tourism employees’ perceptions of gay and lesbian leaders as token-hires among hospitality employees and the spillover effect on company’s motives for hiring the leaders. This study further explores LGBTQ+ employees’ reactions to token-hiring as a form of activism, and how workplace interactions as passing/revealing LGBTQ+ individuals shaped their career development.

This research adopted a sequential mixed-methods design. An experiment examines how employees judge gay vs lesbian hospitality leaders as token hires, contingent on their own gender identity. It further tests the conditional mediation of tokenism on company’s egoistic motives for activism. A qualitative study explores the reactions to token-hiring as activism from the perspective of LGBTQ+ leaders who reflect on their own careers and workplace experiences.

Tokenism in the hospitality workplace is recognized as the phenomenon attributed to groups at the intersection of identities (e.g. gay men). Findings demonstrate the spillover effect of tokenism perceptions of gay male leaders by other men on company’s egoistic motives for activism. This effect is not observed for a lesbian female leader. Results from interviews suggest that hospitality and tourism LGBTQ+ employees predominantly take the post-gay vs political approach when managing their sexual identities at work and feel ambivalent toward token-hiring as LGBTQ+ brand activism.

This research contributes to understanding workplace challenges of LGBTQ+ employees and how they are perceived by others contingent on gender identity. It also explores the role of tokenism in their experiences.

This study aimed to understand better what makes esports fans engage with streamers' live-streaming of esports gameplay. This study used the Theory of Planned Behavior (TPB) and additionally adopted streamer identification and esports game identification as moderating variables.

Data were collected from streamers' esports content streaming viewers over 18 years of age using an online survey in Amazon M-Turk (N = 307). Based on past esports live-streaming weekly watching hours, which range from 1 to 45 h, the participants were divided into lower (n = 152) and higher (n = 155) frequency groups. PLS-SEM and bootstrapping techniques were used to test the moderated mediation relationships among the constructs.

This study found a negative moderating effect of past watching experience on the relationship between attitudes and behavioral intention, and it positively moderated the path between perceived behavioral control and behavioral intention. Also, it was found statistically significant direct impacts of streamer identification (STI) and esports game identification (EGI) on attitude and subjective norms. While the indirect impact of STI on behavioral intention through attitude was statistically significant, there were no significant indirect impacts of EGI on attitude and behavioral intention through subjective norms.

Theoretically, this study extends the TPB model by exploring the two identifications (i.e. streamers and esports games) as antecedents of the focal TPB factors (i.e. attitudes, subjective norms and perceived behavioral control) and the moderating effect of prior experience based on high/low weekly watching frequencies. Practically, content creators of esports live-streaming and live-streaming platform managers can use the study’s findings to develop strategies to nurture their current and future viewership.

This research investigates the impact of customer rule violation issues on frontline employees' (FLEs’) burnout due-to-customers. A model and hypotheses are developed using COR theory and past literature on misbehaving customers and their effects on customer-facing employees.

The proposed model was assessed using a survey of 840 frontline retail, restaurant, service and caregiving employees and their reactions to the issue of misbehaving customers (i.e. rule breaking and/or rude customers).

FLEs' perceived frequency of customer rule violations, FLEs' concerns with misbehaving customers and FLEs' concerns with enforcing rules with these customers increased FLEs' burnout due-to-customers, while FLEs' customer orientation decreased it. Interactions among several antecedents were found relative to their effects on burnout. Burnout due-to-customers decreased FLEs' organizational commitment and increased quitting intentions. Additionally, this burnout mediated the relationships between our studied antecedents and job outcome variables (either partially or fully), with organizational commitment also mediating the relationship between burnout and quitting intentions.

The impact of FLEs' concerns relative to customers' rule breaking, which has not been previously addressed, is shown to increase FLEs' burnout due-to-customers, while FLEs' customer orientation buffered and reduced burnout, with frequency of violations interacting with several antecedents, and ultimately affecting burnout and several dependent variables—organizational commitment and quitting intentions. These FLE rule violation and enforcement concerns, captured at the height of the pandemic, are new variables to the literature. These issues have important implications for managers as to their treatment and training of FLEs in the future.

Research shows that postsecondary students are largely unaware of the impact of algorithms on their everyday lives. Also, most noncomputer science students are not being taught about algorithms as part of the regular curriculum. This exploratory, qualitative study aims to explore subject-matter experts’ insights and perceptions of the knowledge components, coping behaviors and pedagogical considerations to aid faculty in teaching algorithmic literacy to postsecondary students.

Eleven semistructured interviews and one focus group were conducted with scholars and teachers of critical algorithm studies and related fields. A content analysis was manually performed on the transcripts using a mixture of deductive and inductive coding. Data analysis was aided by the coding software program Dedoose (2021) to determine frequency totals for occurrences of a code across all participants along with how many times specific participants mentioned a code. Then, findings were organized around the three themes of knowledge components, coping behaviors and pedagogy.

The findings suggested a set of 10 knowledge components that would contribute to students’ algorithmic literacy along with seven behaviors that students could use to help them better cope with algorithmic systems. A set of five teaching strategies also surfaced to help improve students’ algorithmic literacy.

This study contributes to improved pedagogy surrounding algorithmic literacy and validates existing multi-faceted conceptualizations and measurements of algorithmic literacy.

This paper aims to establish a fundamental and comprehensive understanding of non-fungible tokens (NFTs) by identifying and structuring common characteristics within a taxonomy. NFTs are hyped and increasingly marketed as essential building blocks of the Metaverse. However, the dynamic evolution of the NFT space has posed challenges for those seeking to develop a deep and comprehensive understanding of NFTs, their features and their capabilities.

Utilizing common guidelines for the creation of taxonomies, the authors developed (over 3 iterations), a multi-layer taxonomy based on workshops and interviews with 11 academic and 15 industry experts. Through an evaluation of 25 NFTs, the authors demonstrate the usefulness of the taxonomy.

The taxonomy has 4 layers, 14 dimensions and 42 characteristics, which describe NFTs in terms of reference object, token properties, token distribution and realizable value.

The authors' framework is the first to systematically cover the emerging NFT phenomenon. This framework is concise yet extendible and presents many avenues for future research in a plethora of disciplines. The characteristics identified in the authors' taxonomy are useful for NFT- and Metaverse-related research in finance, marketing, law and information systems. Additionally, the taxonomy can serve as an information source for policymakers as they consider NFT regulation.

Research at the interface of marketing and entrepreneurship has emphasized digital entrepreneurship and how entrepreneurs pursue business opportunities centered on new technologies. However, a different type of entrepreneurship focused on opportunities involving consumers’ (re)adoption of displaced analog technologies when digital alternatives are dominant – analog entrepreneurship – is a trend and counter phenomenon to digital entrepreneurship that is receiving intense practitioner interest but limited scholarly attention. The purpose of this article is to present a theoretical framework that explains the role of analog entrepreneurship in technology revitalization.

In this conceptual paper, the authors use the microfoundations perspective to develop a multilevel theory of analog entrepreneurship. The authors define and delineate the “analog entrepreneurship” concept and formulate a midrange theory explaining how entrepreneurs influence the reemergence of analog technologies.

The theory’s main insight is that the renewal of analog technologies is not confined to consumers. Entrepreneurs are creating businesses that stimulate demand for analog technologies. As a result of entrepreneurs’ activities, legacy analog technologies do not fade into nonexistence in the face of rival digital technologies.

The theory of analog entrepreneurship contributes to research at the intersection of entrepreneurship and marketing by expanding its focus to consider the entrepreneurs who revitalize displaced analog technologies when digital alternatives are dominant. The authors provide insight into the potential trajectories of technologies after their initial displacement and the role entrepreneurs play in shaping the late stages of technology lifecycles. The theory draws attention to an underexplored phenomenon made increasingly prevalent by recent technological disruptions and suggests an agenda for studying how entrepreneurs renew analog technologies.