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The purpose of this paper is to form propositions about the relationship between top management team (TMT) heterogeneity and peer effects in investment decision-making and explore the mediating role of social learning processes.

To investigate the correlations between TMT heterogeneity and investment peer effects, we considered the TMT heterogeneity category, team process and contextual factors. With a sample of 8,467 firm-year observations from Chinese listed companies, we used the mean linear model and instrumental variable method to empirically examine their relationships. To identify the mediating role of social learning processes, we introduced a social learning model to find out the contextual factors influencing corporate social learning demands from three aspects and subsequently used comparative statics analysis to explore the variations in the main effect under these contextual factors.

For task-oriented heterogeneity (e.g. functional background, education and tenure heterogeneity), the opposite effects of information elaboration and social categorization processes make it a nonlinear multiplex correlation with investment peer effects. For relation-oriented heterogeneity (e.g. age and gender heterogeneity), the sole effect of social categorization processes leads to a negative linear correlation. Further, we identify the mediating role of social learning processes. In summary, we established a connection from the TMT heterogeneity, to information elaboration theory or social categorization theory, to social learning processes and ultimately to investment peer effects.

The results of this study provide a comprehensive perspective to predict the decision-making outcomes of team heterogeneity and contribute to heterogeneity research and practice.

This paper aims to propose mechanisms of the dark side of interorganizational relationships from a social psychological perspective. The purpose is to understand the role of boundary spanners’ social psychological processes that may trigger the dark side effects.

Multple mechanisms are developed through three social psychological theories, namely, social identity theory, system justification theory and social learning theory.

Boundary spanners’ social psychological processes can trigger the dark side of interorganizational relationships via mechanisms such as excessive cooperation, reification, system justification and path dependence in learning.

This paper concludes with a discussion that offers a new perspective on research on dark side effects and the managerial implications of the present analysis.

This paper contributes to the current literature by extending the interpersonal social psychological processes that could explain the dark side of interorganizational relationships. This paper is a step forward to answer the calls for multilevel considerations of the dark side effects and inspire future research on the role of social psychological processes in dark side effects.

The purpose of this study is to explore the comparative effects of mainstream celebrities and social media influencers on consumer advocacy and relationship intentions. The study also examines the direct and serial mediation effects on those relationships.

The survey questionnaire was used to collect data from 718 respondents throughout Malaysia, with convenience and snowball sampling techniques employed. The data were analyzed based on the structural equation modeling (SEM) approach through the AMOS version 24. The PROCESS MACRO v-4.20 was applied to evaluate mediating effects in the model.

The results reveal that celebrity endorsers' involvement in social media significantly influences the uses of social media, which also impacts the attitudes and, subsequently, consumer relationship and advocacy intentions. The study found that mainstream celebrities and social media influencers effectively promote brands, and it discovered insignificant differences in their effects on the analyzed relationships.

This study has been conducted on consumers in Malaysia; it may have different effects on consumers in other countries.

Brand managers and policymakers may benefit from following the study's guidelines for making consumer relationship and advocacy intentions by celebrity endorsers and uses of social media.

The brand community can benefit from tightening their social bondage by sharing and managing crucial information from celebrities and using social media.

The study explores the effects of mainstream celebrities on consumer relationship and advocacy intentions using social media networks and managing consumer attitudes.

This study aims to reveal the constituents of seafaring service quality (physical and social environment) and their effects on seafarer employee satisfaction (job satisfaction and turnover intention) and analyse any differences among seafarer ranks. Literature on service quality has overlooked the transportation sector and seafaring in particular.

Seafaring service quality is measured by the workplace environment constituted of physical and social environments. Two types of employee (job) satisfaction were explored: overall job satisfaction and turnover intention. This study is based on a unique, large survey based on the Existence-Relatedness-Growth (ERG) needs theory. An exploratory factor analysis revealed four physical environment factors (Ship conditions, Communication facilities, Nautical health and Living conditions) and four social environment factors (Social fit, Team cohesion, Ship company support and Intercultural environment). Multi-group regression analysis assessed the effects of seafaring service quality on employee satisfaction.

The social environment has stronger effects than the physical environment on job satisfaction but not on employee retention. Team cohesion has strong effects on employee retention, while social fit has stronger effects on overall job performance. Seafarer ranks showed significant variations. The physical environment matters for 2nd engineers' and cadets’ job satisfaction but not for ratings, masters and chief officers. Team cohesion is significant to master, chief officer, engineer and cadet ranks but not for junior officers and ratings. Social fit has stronger effects on overall job performance than employee retention, particularly for ratings, cadets, master, chief officer and chief engineer ranks. Ship company support has the stronger effect on overall job satisfaction among all workplace factors; this is also observed across all ranks.

Motivation theories like the ERG theory can help understand service quality and employee satisfaction in the maritime sector; future studies should examine more behaviour variables/constructs from these theories.

Maritime companies can offer better services to seafarers, who are considered as key workers, by customising their interventions to specific seafarer ranks and developing a supportive culture that improves seafarer well-being.

This study examined the overlooked topic of maritime service quality based on a large-scale survey grounded on ERG theory and reveals how the physical and social environment has different effects on seafarer job satisfaction and retention.

Joint research is pointed out by the literature as a potentially virtuous cooperation scheme to generate learning in the public sphere and beneficial effects in society. The purpose of this study, based on the Argentine experience in the COVID-19 pandemic, is to analyze the network of capacities, relationships and effects generated, over time, by a series of projects financed by the State in 2010, to clarify the link between learning effects and social effects.

A qualitative methodology focused on the multiple case study method was used. Each case covers joint R&D projects financed 10 years ago by the state that subsequently led to different solutions for COVID-19.

The work identifies a public learning process that integrates both industry’s contributions and the intellectual dimension of economic benefits and their translation into specific capabilities; conceptualizes the capacities accumulation process as a multiplier of social effects (direct and indirect) that emerge as knowledge is reused; identifies the articulation between different schemes as a condition for learning effects and social effects to manifest over time.

An aspect not studied in the literature is addressed, the relationship between the learning process induced by joint research, in terms of capabilities, and the social effects specifically generated over time. This is taking place in a context, such as the COVID-19 pandemic, where calls from the scientific and academic community to promote science–industry cooperation are multiplying.

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.

This study examines the effect of social media marketing on voting intention applying a combination of fuzzy logic methodology and a multidimensional panel data model.

The study adopts a multidimensional panel data method that includes several fixed effects. The dependent variable is a multifaceted construct that measures the participants’ intention to vote. The independent variables are electronic word of mouth (eWOM), customisation (CUS), entertainment (ENT), interaction (INT), trendiness (TRD), candidate’s perceived image (CPI), religious beliefs (RB), gender and age. The grouping variables that signify fixed effects are employment status, level of education, mostly used social media and religion. First, the significance of said fixed effects was tested through an ANOVA process. Then, the main model was estimated, including the significant grouping variables as fixed effects.

Employment status and level of education were significant fixed effects. Also, eWOM, ENT, INT, CPI, RB and gender significantly affected participants’ voting intention.

Being based on a questionnaire that asked participants about how they perceive different aspects of social media, the present study is limited to their perceptions. Therefore, further studies covering the voters’ behaviour in action could be efficient complements to the present study.

The findings could guide the political parties into prioritizing the aspects of social media in forming an effective campaign resulting in being elected.

The findings have the potential to help the public in making better informed decisions when voting. Furthermore, the results of this study indicate applications for social media which are beyond leisure time fillers.

Fuzzy logic and multidimensional panel data estimates are this study’s novelty and originality. Structural equation modelling and crisp linguistic values have been used in previous studies on social media’s effect on voting intent. The former refines the data gathered from a questionnaire, and the latter considers the possibility of including different grouping factors to achieve a more efficient and less biased estimation.

The purpose of this research study was to understand the simultaneous competitive and social gains of machine learning (ML) and artificial intelligence (AI) usage in organizations. There was a knowledge hiatus regarding the contribution of the deployment of ML and AI technologies and their effects on organizations and society.

This study was grounded on the dynamic capabilities (DC) and ML and AI automation-augmentation paradox literature. This research study examined these theoretical perspectives using the response of 239 Indian organizational chief technology officers (CTOs). Partial least square-structural equation modeling (PLS-SEM) path modeling was applied for data analysis.

The results indicated that ML and AI technologies organizational usage positively influenced DC initiatives. The findings depicted that DC fully mediated ML and AI-based technologies' effects on firm performance and social performance.

This study contributed to theoretical discourse regarding the tension between organizational and social outcomes of ML and AI technologies. The study extended the role of DC as a vital strategy in achieving social benefits from ML and AI use. Furthermore, the theoretical tension of the automation-augmentation paradox was explored.

Organizations deploying ML and AI technologies could apply this study's insights to comprehend the organizational routines to pursue simultaneous competitive benefits and social gains. Furthermore, chief technology executives of organizations could devise how ML and AI technologies usage from a DC perspective could help settle the tension of the automation-augmentation paradox.

Increased ML and AI technologies usage in organizations enhanced DC. They could lead to positive social benefits such as new job creation, increased compensation to skilled employees and greater gender participation in employment. These insights could be derived based on this research study.

This study was among the first few empirical investigations to provide theoretical and practical insights regarding the organizational and societal benefits of ML and AI usage in organizations because of their DC. This study was also one of the first empirical investigations that addressed the automation-augmentation paradox at the enterprise level.

The growing number of firms leveraging social media ads highlight the urgent need for firms to understand social media ads and their effects on consumer perceptions and attitudes. This research examines whether and how different types of social media ads exert influences on ad engagement and how consumers’ psychological characteristics including regulatory orientation and lay rationalism moderate the influence of social media ads on ad engagement.

This research conducts three quasi experiments featuring two types of social media ads – interactive and transactional – to collect empirical evidence. Results are analyzed using ANOVA and Process in SPSS.

This research reveals that interactive ads lead to higher perceived enjoyment and perceived responsiveness, which further lead to higher ad engagement. Promotion focus moderates the effect of social media ads (interactive vs transactional ads) on perceived enjoyment and perceived responsiveness, and lay rationalism moderates the effect on perceived responsiveness, while prevention focus has no such effect.

First, this research establishes the connection between ad types and ad engagement in social media, which offers a new perspective to understand ad engagement. Second, it explores the underlying mechanisms of processing different types of social media ads. Third, it justifies the moderating effects of consumers’ regulatory orientation and lay rationalism on the effects of ad types on ad engagement, providing the first evidence on the moderating role of consumers’ lay rationalism in ad processing. This research helps firm marketers to fine-tune their social media ads according to consumer characteristics.

Social media networks make their services freely available to all users. Users pay for the service received with the time and attention taken by the advertisements. This chapter argues that social media platforms are a unique form of monopoly driven by “the more the merrier” effect (i.e., network effects) in users' consumption. These monopolies exercise market power, not by charging higher prices to users but by “tying” larger amounts of advertising to their content. Traditional antitrust instruments designed to address excessive pricing and reduced output by monopolies need to be reframed to tame the attention economy problems in the social media industry. This chapter discusses five antitrust instruments grouped in three categories: structural, behavioral, and market-based remedies. Market-based solutions are the least explored in the literature, despite being the most promising instruments to lower the attention costs imposed on users, while preserving the economies of scope in production and the network effects in consumption, and possibly maintaining free access to social media, as we know it today.