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This paper aims to investigate if, under which conditions, and with which consequences, nonfamily members have the perception of being discriminated against as a consequence of nepotism and adverse selection practices. This research also aims to investigate whether the carried-out role influences the perception of being discriminated against among nonfamily member employees.

A quantitative approach was carried out by adopting a structural equation model (SEM) analysis. The survey investigated a sample of Italian family SMEs (participating companies N = 186, total questionnaires collected N = 838).

Drawing on the multiple identities theory, findings show that role salience (RS) effectively contributes to reducing the unwanted effects of perceived discrimination (PD) among nonfamily member employees. In doing so, this study deepens the knowledge of nonfamily member employment conditions and their consequences on strategic outcomes such as organizational commitment (OC), organizational justice (OJ) and intention to quit (ITQ).

By adopting a self-categorization approach, this study also advances current theoretical literature, as this methodological lens could help scholars further understand diversity in family business.

This study suggests it would be advisable to implement human resource management practices based on job rotation to promote cohesion and reduce perceived distances.

SMEs are the most widespread type of firm in the world; as a consequence, avoiding PD among nonfamily member employees has general ethical relevance.

This study expands current literature by showing that RS plays an important role in determining levels of PD. This study also advances current literature by focusing on the impact of multiple identities on fairness and commitment at individual and group levels of analysis of family businesses.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.

The present study examines the effect of supervisor incivility on service employee creativity and the mediating mechanism of negative affect state on the said relationship with the aid of Affective Events Theory (AET) and Social Power Theory. Additionally, the study explores the mitigating role of core self-evaluation in the dual stage of the moderated mediation model.

Survey data were collected from 420 frontline employees working in four-star and five-star hotels across India and PROCESS macro in SPSS 23.0 was employed to test the hypotheses proposed in the study.

The study findings observe that frontline employees experiencing supervisor incivility face a negative affect state and it further diminishes service employee creativity. Also, the indirect effect gets attenuated at dual stages when frontline employees are equipped with a high level of core self-evaluation.

The study findings provide various insights to the managers to understand the deleterious effect of supervisor incivility at work and to develop interventions to manage supervisor incivility and the negative affect state among frontline hotel employees.

The present study is the first and unique attempt to investigate the role of supervisor incivility experienced by frontline hotel employees in India with reference to their creativity towards customers and mediating mechanism of negative affect state. The study adds value to the literature by establishing the role of core self-evaluation in the moderated mediation model. Further, the study also provides a unique contribution to the management of frontline hospitality employees.

Pandemics are frequent events, and the impact of each pandemic makes a strong and long-term effect on companies and markets. Given the potential impact of the COVID-19 pandemic, it is important to investigate the crisis from a different perspective to know how companies have sustained growth in markets. The purpose of this paper is to understand how profit-oriented customer-centric companies (small, medium and large) have responded and adapted to COVID-19 crisis, using the complexity theory.

Drawing upon the complexity theory, a humble attempt is made to develop theoretical propositions by conceptualizing companies as complex adaptive systems. The paper examines companies from three dimensions (i.e. internal mechanism, environment and coevolution).

Companies self-organize, emerge into new states and become adaptive to the changing environment. Companies create knowledge to understand the dynamic anatomy and design survival and growth strategies during and post COVID-19 era. Complex adaptive systems perspective provides companies with insights to deal with complex issues raised due to COVID-19 pandemic. They can handle the impact of pandemic efficiently with complex adaptive systems by developing and implementing appropriate strategies post-COVID-19.

The study reveals how companies evolve and emerge into as complex adaptive systems to adapt themselves to the highly dynamic environment, which are uncertain, unpredictable, nonlinear and multifaceted, in the context of COVID-19. Implications for theory and practice of viewing companies as complex adaptive systems and coevolving structures in the COVID-19 context are discussed.

The purpose of this study is to explore from a place attachment (PA) theory perspective the extent to which and how, a fully immersive virtual reality (VR) experience enhances tourists’ attachment level on-site at a rural destination.

This study applied an exploratory mixed method approach. Respondents were tourists visiting the Lake District National Park who were asked to try a VR experience. In Study 1, interviews were conducted to explore new themes and to develop an enhanced PA framework in VR. Study 1 confirmed existing variables from the literature and highlighted new variables (themes) to be included in the new framework on how PA is formed. In Study 2, surveys were conducted, and the proposed framework analyzed using structural equation modelling (PLS-SEM). To fully understand how VR had an impact on enhancing PA, the moderating effect of tourists’ pre-existing PA was considered.

The findings revealed “Accessibility”, “Memories” and “Increased Place Knowledge” as new themes (variables) and confirmed that these and established variables “Aesthetics” and “Presence” enhance PA, leading to increased loyalty. Significant moderating effects of existing PA were found.

VR serves as a complementary and substitutional tool for tourism. Tailored VR experiences for diverse tourist needs may enhance destination marketing and competitiveness. For tourists with low PA, destinations should focus on promoting activities and highlights to enhance engagement and the experiential understanding of the destination. For tourists with high PA, VR experiences should focus on providing a comprehensive view of the destination and unveiling new places. In both cases, the VR experience leads to deeper engagement with the destination and an increase in PA.

Research on the impact of VR on tourists’ PA is limited. To address this gap, this study’s theoretical contribution lies in developing and testing a PA framework within a VR and tourism context. This also includes the validation of new measurement items developed in relation to the new themes.

The empirical studies of the options market efficiency have reported contradictory results, which sometimes confuse practitioners and academicians. The aim of this study was to clarify several aspects of options market efficiency by exploring the answers to two main questions: Under what conditions is the options market more efficient? Are the discrepancies in the estimated efficiency due to the reality of efficiency or mismeasurement?

Using a meta-analysis approach, 54 studies have been analyzed, which included 1,315 tests. The sum of the observations for all of the tests is 3.7 m observation sets. The effect size (type r) has been used to compare the different statistics in different studies. The cumulative effect size and its diversification have been calculated by the random effects model and Q statistic, respectively.

The most interesting finding of the study was that the options market, in all circumstances, is significantly inefficient. Another important finding was that the heterogeneity of options market efficiency is due to the complexity of pricing relations, test time, violation index and price type. To overcome this heterogeneity and accuracy, future studies should test the no-arbitrage options pricing relations at different times and by different price types, using complex and simple pricing relations and either mean violation or violation ratio efficiency measures.

Public disagreement about the options market efficiency in past studies means that this variable is heterogeneous in different conditions. As a significant contribution, this study develops the literature by proposing the causes of options market efficiency heterogeneity.

The purpose of this research is to explore how an innovation organization's orientation toward the digital economy influences its position within R&D networks. By using institutional theory, the study aims to forecast market changes and understand how organizations can navigate the digital economy to secure essential resources and minimize dependencies.

This study employs a longitudinal panel dataset with 11,763 entries from 1995 to 2018, covering strategic emerging industries in China to analyze the impact of digital economy orientation on R&D networks. Utilizing advanced statistical models, it assesses the role of the legal environment as a moderator. This methodological approach facilitates a robust examination of the nexus between digital orientation and network dynamics within the context of institutional theory.

The study reveals that an organization's digital economy orientation enhances its centrality in R&D networks but reduces its control over structural holes. The legal environment negatively moderates the impact of digital economy orientation on network centrality, while positively influencing the relationship with network structural holes. These findings offer new insights into how institutional forces shape the strategic positioning of organizations in R&D collaborations.

This research offers a fresh perspective on the digital economy's impact on R&D networks, particularly in the Industry-University-Research (IUR) context. It extends the discourse by integrating institutional theory to elucidate the adaptation of R&D networks in the digital era. By identifying the legal environment as a moderator, the study provides a nuanced understanding of the strategic alignment within networks influenced by digital advancements. The unique focus on China's R&D networks presents a valuable contribution to the global discussion on digital integration and innovation ecosystems, highlighting the intersection of policy, academia, and industry in shaping research and development trajectories.

Amidst escalating sustainability challenges, product and brand managers face a pressing need to foster responsible consumption and marketing strategies. Guided by the theory of planned behavior, this paper aims to explore consumers’ motivation to purchase second-hand clothing, a type of product that contributes to Sustainable Development Goal (SDG) 12 on Responsible Consumption and Production by democratizing the brand, extending the life-cycle of the product, promoting a circular economy, while reducing economic costs for consumers and environmental costs for companies.

A two-stage study was conducted: 20 consumers were initially interviewed to identify the salient beliefs about second-hand clothing, and following that, a survey was conducted with 449 consumers to statistically analyze consumers’ motivation to purchase second-hand clothing. The data were analyzed using partial least squares-structural equation modeling (PLS-SEM) and necessary condition analysis (NCA).

From a “should-have” perspective (PLS-SEM), the study reveals that behavioral beliefs, injunctive normative beliefs, descriptive normative beliefs and control beliefs positively shape attitudes, injunctive norms, descriptive norms and perceived behavioral control toward second-hand clothing, whereas attitudes, injunctive norms, moral norms and perceived behavioral control positively influence consumers’ purchases of second-hand clothing. From a “must-have” perspective (NCA), the study shows that behavioral beliefs, injunctive normative beliefs and descriptive normative beliefs are necessary conditions to positively shape attitudes, injunctive norms and descriptive norms toward second-hand clothing, whereas attitudes, injunctive norms and perceived behavioral control are necessary conditions to stimulate second-hand clothing purchases.

The study offers a deep dive into consumers’ motivation to purchase second-hand clothing using a multimethod approach that enables not only the elicitation of salient beliefs (through interviews) but also the empirical examination of these beliefs alongside varying subjective norms in motivating consumers to purchase second-hand clothing (via survey). Given that beliefs are deeply rooted, the rigorous unfolding and validation of consumers’ beliefs about second-hand clothing, including the “should-haves” versus the “must-haves,” provide finer-grained insights that product and brand managers can strategically use to encourage consumers to purchase second-hand clothing.