Search results

This conceptual, multi-voiced paper aims to collectively explore and theorize family entrepreneuring, which is a research stream dedicated to investigating the emergence and becoming of entrepreneurial phenomena in business families and family firms.

Because of the novelty of this research stream, the authors asked 20 scholars in entrepreneurship and family business to reflect on topics, methods and issues that should be addressed to move this field forward.

Authors highlight key challenges and point to new research directions for understanding family entrepreneuring in relation to issues such as agency, processualism and context.

This study offers a compilation of multiple perspectives and leverage recent developments in the fields of entrepreneurship and family business to advance research on family entrepreneuring.

Researchers continue to address the concept of self-disclosure because it is foundational for helping social networking sites (SNS) function and thrive. Nevertheless, the authors' literature review indicates that uncertainty remains around the underlying mechanisms and factors involved in the self-disclosure process. The purpose of this research is to better understand the self-disclosure process from the lens of dual-process theory (DPT). The authors consider both the controlled factors (i.e. self-presentation and reciprocity) and an automatic factor (i.e. social influence to use an SNS) involved in self-disclosure and broaden The authors proposed a model to include the interactive facets of enjoyment.

The proposed model was empirically validated by conducting a survey among users of WeChat Moments in China.

As hypothesized, this research confirms that enjoyment and automatic processing (i.e. social influence to use an SNS) are complementary in the SNS self-disclosure process and enjoyment negatively moderates the positive relationship between controlled factor (i.e. self-presentation) and self-disclosure.

Theoretically, this study offers a new perspective on explaining SNS self-disclosure by adopting DPT. Specifically, this study contributes to the extant SNS research by applying DPT to examine how the controlled factors and the automatic factor shape self-disclosure processes and how enjoyment influences vary across these processes – enriching knowledge about SNS self-disclosure behaviors. Practically, the authors provide important design guidelines to practitioners concerning devising mechanisms to foster more automatic-enjoyable value-added functions to improve SNS users' participation and engagement.

The study introduces a new approach to leverage-value relationship. Besides applying the classical regression models, the study deals with leverage as a continuous treatment variable implemented on the firm’s value using the dose-response function (DFR).

After proper model calibration and splitting the treatment (leverage) into ten doses, a response function is generated, which enables the realization of the dose level at which the firm’s value is maximized. Furthermore, the study tests the pecking order theory (POT) and the trade-off theory (TOT) using the threshold model to see whether firms are under or over-indebted. The analysis is carried out on panel data from small-medium enterprises (SMEs), providing more valuable insights than large and mature companies.

The study used two leverage measures: total liabilities ratio and bank debt ratio. Value is measured by the market capitalization and Tobin’s Q. In general, the study finds a positive relationship between leverage and value; POT is not strongly supported, firms are below their optimal leverage and there is a certain leverage dose that would maximize firms’ value.

Since the threshold model and DRF show that SMEs are under-indebted, firms could benefit from extra leverage doses without affecting the firm’s risk profile, especially in a low-interest rate regime, and the potential increase in public-private expenditure after Italy obtained the European Recovery Funds.

The study contributes to new knowledge and understanding of financial leverage from new methodological perspectives, offering valuable insights from SMEs using novel approaches.

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.

Previous studies have demonstrated that perceived job insecurity climate denotes an individual-level stressor. The present study reiterated this notion and investigated whether leadership responsibility moderated the association between perceived job insecurity climate and work-related strain about one year into the coronavirus disease (COVID-19) pandemic.

A sample of full-time workers (N = 1,399) in the USA was recruited, comprising 663 leaders and 763 non-leaders. Employing a cross-sectional design, the authors hypothesized that perceived job insecurity climate would be associated with work-related strain (i.e. burnout, absenteeism and presenteeism) and that these associations were stronger for employees with leadership responsibilities compared to non-leaders.

Findings revealed main effects of perceived job insecurity climate on burnout but not on absenteeism or presenteeism. Furthermore, leadership responsibility moderated the associations between perceived job insecurity climate and two out of three burnout measures in the hypothesized direction. The findings also revealed interaction effects regarding absenteeism and presenteeism, indicating that these associations are only positive and significant for employees with leadership responsibilities.

Perceptions of widespread job insecurity engender strain among leaders while simultaneously implying a heightened need for effective leadership. Organizations and practitioners should take the present findings into consideration when implementing preventive and restorative measures to address leaders' health and organizational competitiveness when job insecurity increases.

This study found that, as an individual stressor, perceived job insecurity climate is more detrimental to employees with leadership responsibility than to non-leaders.

This study aims to understand how traveling Instagrammers should be characterized by bridging socio-psychological concepts with Instagram usage and travel typologies.

Using analysis of variance, differences between non-Instagrammers and passive and active users were identified with regard to their personality traits and human values; traveling Instagrammers and their travel types were characterized in more detail using k-means clustering, and, finally, posting behavior was examined using multiple regression.

The results demonstrate significant differences between the user groups in terms of their personality traits, their human values and their travel behavior. The multiple regressions provide deeper insights into tourists’ Instagram posting.

This study was conducted on 1,100 German travelers, meaning that the results are only valid for this cultural context. All data were collected using an online panel and participants received incentives, and thus extrinsic rewards, instead of using merely intrinsic motivation to take part in the survey.

This study contributes to a better understanding of Instagram usage behavior when traveling and adds valuable insights to this field of research. At the same time, the results are relevant for tourism businesses wishing to optimize their communication and marketing strategies.

This study aims to investigate how firms of different sizes respond to competitive pressure from peers.

This study employs machine learning techniques to measure competitive pressure based on management discussion and analysis (MD&A) documents and then utilises the constructed pressure indicator to explore the relationship between competitive pressure and corporate risk-taking behaviours amongst firms of different sizes.

We find that firm sizes are positively associated with their risk-taking behaviours when firms respond to competitive pressure. Large firms are inclined to exhibit a high level of risk-taking behaviours, whereas small firms tend to make conservative decisions. Regional growth potential and institutional ownership moderate the relationships.

Utilising text mining techniques, this study constructs a novel quantitative indicator to measure competitive pressure perceived by focal firms and demonstrates the heterogeneous behaviour of firms of different sizes in response to competitive pressure from peers, advancing research on competitive market pressures.

This study aims to analyse how the collective processing of the #MeToo legacy in the form of community discourses and activism conceptualises organisational accountability for sexual misconduct at work and enhances the development of new accountability instruments.

The study draws on social movement theory and the intellectual problematics of accountability, together with the empirical insights from two research engagement projects established and facilitated by the author.

The study reveals multiple dimensions of how post-#MeToo community activism impacted the conceptualisation of organisational accountability for sexual misconduct at work. The movement enhanced discourses prompting a new societal sense of accountability for sexual wrongdoings. This in turn facilitated public demands for accountability that pressured organisations to respond. The accountability crisis created an opportunity for community activists to influence understanding of organisational accountability for sexual misconduct at work and to propose new accountability instruments advancing harassment reporting technology, as well as an enhancing the behavioural consciousness and self-assessment of individuals.

The study addresses a topic of social importance in analysing how community activism arising from a social movement has transformed accountability demands and thus both advanced the conceptualisation of organisational accountability for sexual misconduct at work and established socially desirable practices for it. The study contributes to theory by revealing the emancipatory potential of community activism to influence organisational accountability practices and to propose new instruments at a moment of organisational hesitation and crisis of accountability.

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.