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Though each of the papers is unique, several common dimensions of the ethics in groups intersection were identified. These include the external influences on groups, the within-group processes, and the individual decision-making that occurs by a group member.¹ The following summary, and the volume itself, is organized around these dimensions.

This study aims to examine the effects of multidimensional factors of platform features, group effects and emotional attitudes on social media users’ privacy disclosure intention.

This study collected the data from 426 respondents through an online questionnaire survey and conducted two approaches of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) for theoretical hypothesis testing and configuration analysis of the data.

The results show that social media platform features (rewards of information disclosure, personalized service quality and data transparency), group effects (group similarity, group information interaction and network externality), individual emotional attitudes (trust and privacy concern) and control variable (gender) have a significant impact on privacy disclosure intention, as well as trust and privacy concern play mediating roles. Additionally, the fsQCA method reveals five causal configurations that explain high privacy disclosure intentions. Furthermore, the study reveals that male users pay more attention to platform features, while female users are more inclined to group effects.

This study attempts to construct a comprehensive model to examine the factors that affect users' intention to disclose their privacy on social media platforms. Drawing on the cognition-affect-conation model and multidimensional development theory, the model integrates multidimensional factors of platform features, group effects, trust and privacy concern to complement existing theoretical frameworks and privacy disclosure literature. By understanding the complex dynamics behind privacy disclosure, this study helps platform providers and policymakers develop effective strategies to ensure the vitality and momentum of the social media ecosystem.

The purpose of this paper is to validate the theoretical finding that digital MNEs avoid physical presence norms of permanent establishment and royalty characterization rules for business and royalty taxation, respectively, to escape tax incidence in the market economy, using information, communication and technology features and transfer pricing (TP) manipulations.

Multiple case studies of MNEs from technology sector, based on judicial decisions in 141 cases, over taxability of profits earned from Indian economic activities. Additional in-depth case study of the Uber Group to study the tax avoidance structures under platform economy, by routing of Indian profits through The Netherlands, a tax haven.

The study finds a significant number of digital MNEs earning profits from India and avoiding tax by defying physical presence and royalty characterization. In majority of the cases, demand-side business activities are discharged through incorporating and remunerating affiliates at cost plus low markup, thus avoiding tax incidence, using TP manipulations under the arm’s length principle applied by governments for benchmarking the intragroup transactions of the MNEs.

The research findings validate the view that digital features promote tax avoidance in the market economy.

The originality of the study lies in the validation of profit shifting through digital features from the developing market economy and portending that digital MNEs defy physical presence to avoid business taxation through TP manipulations.

The purpose of this study is to focus on, namely, the international financial reporting standards (IFRS) or local generally accepted accounting principles (GAAP) effects of financial reporting as a corporate governance mechanism on mergers and acquisitions (M&As) for banking institutions during the global financial crisis.

I investigate the characteristics of bank financial statements before the start of the global crisis, which helps to explain the relationships between the accounting standards and the global financial crisis. The observations, which are based on 3,178 deals in a sample period, are crucially important for corporate governance and bank performance. The results from our analysis are robust to a wide variety of modifications in our research design and are corroborated by descriptive statistics, one-way ANOVA and a two-sample t-test on a sample of banks that voluntarily adopted IFRS for M&As.

The find that IFRS-based monitoring of banks M&As in terms of higher quality financial reporting is negatively linked with bank performance, whereas local GAAP-based monitoring of banks’ M&A is positively associated with accounting performance. Finally, our main results for higher quality financial reporting under local GAAP or IFRS generally hold after controlling for various analyses and relationships between account standards and the financial crisis.

Financial reporting standards setting a corporate governance mechanism are considered since it was impacted recently during the global financial crisis and became a great matter of concern.

The value of this paper is determined by an empirical investigation of the relationships between bank performance and accounting and financial reporting standards in the context of the global economy.

The purpose of this study is to investigate the effect of perceived group inclusion on the innovative work behavior of consulting team members, as well as to analyze its subsequent impact on team performance. In addition, the authors investigate whether the effect of perceived group inclusion on innovative work behavior could be moderated by two aspects of team characteristics: team size and the gender composition of its members.

The authors collected questionnaire data from 229 team members from 24 consulting firms located in Bangkok, Thailand. Team performance was assessed by team leaders to prevent common method bias. Partial least squares-structural equation modeling was used for data analysis.

The results support the positive association between perceived group inclusion and innovative work behavior among consulting team members. Innovative work behavior also mediates the positive association between perceived group inclusion and team performance. Moreover, the authors found that the degree to which perceived group inclusion affects innovative work behavior is stronger in larger teams than smaller teams. However, the degree to which perceived group inclusion affects innovative work behavior tends to be weaker in teams that have a higher proportion of female members than in teams that have fewer female members.

Because employees are the most valuable asset contributing to the innovative performance of consulting firms, it is crucial to understand how members within a team should be properly managed so that the firms can maximize the benefits from their human capital. Essentially, management and practitioners in the consulting business can use the insight from this research regarding the essential roles of group inclusion and team composition to create a favorable and effective team environment that enhances collaboration and helps their firms to gain the full benefits of team synergy. In particular, group inclusion is the issue that management should emphasize. Moreover, the team should be large enough and have a decent level of gender diversity to strengthen the benefit of group inclusion.

The research extends the knowledge boundary in inclusion research, which still lacks evidence about the moderating role of team characteristics that might strengthen/weaken the effect of perceived group inclusion on innovative behaviors.

In large-scale group decision-making (LSGDM) situations, existing TODIM group decision-making methods often fail to account for the influence of social network relationships and the bounded rationality of decision-makers (DMs). To address this issue, a new TODIM-based group decision-making method is proposed that considers the current trust relationships among DMs in a large-scale trust relationship network.

This method consists of two main stages. In the first stage, the large-scale group is partitioned into several sub-clusters based on trust relationships among DMs. The dominance degree matrix of each sub-cluster is then aggregated into the large-scale group dominance degree. In the second stage, after aggregating the large-scale group dominance degree, the consensus index is calculated to identify any inconsistent sub-clusters. Feedback adjustments are made based on trust relationships until a consensus is reached. The TODIM method is then applied to calculate the corresponding ranking results. Finally, an illustrative example is applied to show the feasibility of the proposed model.

The proposed method is practical and effective which is verified by the real case study. By taking into account the trust relationships among DMs in the core process of LSGDM, it indeed has an impact on the decision outcomes. We also specifically address this issue in Chapter Five. The proposed method fully incorporates the bounded rationality of DMs, namely their tendency to accept the opinions of trusted experts, which aligns more with their psychology. The two-stage consensus model proposed in this paper effectively addresses the limitations of traditional assessment-based methods.

This study establishes a two-stage consensus model based on trust relationships among DMs, which can assist DMs in better understanding trust issues in complex decision-making, enhancing the accuracy and efficiency of decisions, and providing more scientific decision support for organizations such as businesses and governments.

Understanding group dynamics is essential for promoting institutional change. The purpose of this brief article is to introduce the use of Yule’s Q to quantify group dynamics in a way that allows an individual’s tendency to associate with others based on their shared attributes to be captured as they evolve.

Two academic departments at a large public urban university participated in ongoing meetings as part of the year-long change initiative. Field notes of these meetings were recorded for information on participants and the flow of conversations. Yule’s Q was calculated with responsive interaction network and attribute data coded from the field notes.

Yule’s Q can be used to quantify group dynamics with a visualization of interactions among group members. The differences in the triggered divisions or faultlines in organizational change initiatives by shared common attributes (e.g. levels of positions within departments) can be related to group interactions and/or disruptions in collaboration.

This study can contribute to broadening the research community’s analytic approaches to utilizing network and attribute data for understanding group dynamics and their patterns across meetings.

This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

This study aimed to identify subgroups of esports players based on their gaming behavior patterns across game genres and compare self-efficacy, social efficacy, loneliness and three dimensions of quality of life between these subgroups.

324 participants were recruited from prolific academic to complete an online survey. We employed latent profile analysis (LPA) to identify subgroups of esports players based on their behavioral patterns across genres. Additionally, a one-way multivariate analysis of covariance (MANCOVA) was conducted to test the association between cluster memberships and development and well-being outcomes, controlling for age and gender as covariates.

LPA analysis identified five clusters (two single-genre gamer groups, two multigenre gamer groups and one all-genre gamer group). Univariate analyses indicated the significant effect of the clusters on social efficacy, psychological health and social health. Pairwise comparisons highlighted the salience of the physical enactment-plus-sport simulation genre group in these outcomes.

This study contributes to the understanding of the development and well-being benefits experienced by various esports consumers, as well as the role of specific gameplay in facilitating targeted outcomes among these consumer groups.