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Motivated by the real-world practice that the boom of the online selling induces a higher product return as well, selecting which online channel mode indicates who takes ownership over the product and thus bears the loss of the product return. This paper aims to seek the optimal online channel modes for the two members in a platform supply chain in the presence of product returns.

This study aims to develop a platform supply chain that consists of one platform company and one supplier. Along with an offline distribution channel, the supplier can choose two alternative online selling modes (i.e. the reselling and agency modes) to sell its product through the online marketplace. This paper applies Stackelberg game to derive the equilibrium with different business scenarios and selects the optimal online channel modes for two parties, respectively. Moreover, this paper extends to a different supply chain with a reverse channel leadership and a different product return policy for testing the robustness.

Several interesting and important results are derived in this paper. Firstly, it is found that the relative pricing are largely relied on the costs of two channels. Secondly, the platform supply chain may benefit from a pure channel rather than the dual-channel when this channel enjoys a relatively low cost and/or a sufficiently high consumer preference. Then, the platform and the supplier act contradictorily when selecting their optimal online channel modes. To be specific, the platform motivates to choose the online reselling mode when both the commission rate and the slotting fee are relatively low, whereas the supplier is likely to select the online agency mode under this circumstance. Finally, a win-win situation in regards to the optimal online channel mode for two parties is achievable with numerical experiments.

Based on the analytical studies, the results derived in the authors’ work can provide managerial insights to assist the supplier and the platform company in determining the operational decision and selecting the optimal online channel mode to deal with consumer returns. In addition, appropriate commission rate along with slotting fee will make both parties achieve a win-win situation in determining their optimal online channel mode.

To the authors’ best knowledge, this paper makes the first move to determine the optimal online channel mode in the content of consumer returns and study how it is affected by different product return policies.

Internal knowledge transfer is crucial for firms to improve their employees’ abilities and improve their work performance. However, there is still a gap in the knowledge management field regarding whether internal knowledge transfer can leverage employee personality traits and service performance in service-oriented organizations. To address this gap, this study aims to validate a multilevel model of the mediating (i.e. internal knowledge transfer as a mediator) and moderating (i.e. task interdependence as a moderator) mechanisms underlying personality traits and employee service performance.

Multilevel structural equation modeling was applied for model validation using an original data set from 45 team leaders and 333 employees working in Chinese hotels.

Internal knowledge transfer mediated the link between extraversion and employee service performance and the link between openness to experience and employee service performance. Task interdependence played a moderating role that strengthened both the impacts of extraversion and openness to experience on internal knowledge transfer.

Through the use of an original data set, this study advances the knowledge management discipline by investigating the mediating impact of internal knowledge transfer between personality traits and employee service performance and revealing the moderating impact of task interdependence that underlies the links between personality traits and internal knowledge transfer.

Starting from intention–behaviour models and building upon the growing evidence that aggregated internet search query data represent a good proxy of human interests and intentions. The purpose of this study is to demonstrate that the internet search traffic information related to the selected key terms associated with establishing new businesses, reflects well the dynamics of entrepreneurial activity in a country and can be used for predicting entrepreneurial activity at the national level.

Theoretical framework is based on intention–behaviour models and supported by the knowledge spillover theory of entrepreneurship. Monthly data on new business registration from 2018 to 2021 is derived from the open database of the Russian Federal Tax Service. Terms of internet search interest are identified through interviews with the recent founders of new businesses, whereas the internet search query statistics on the identified terms are obtained from Google Trends and Yandex Wordstat.

The results suggest that aggregated data about web searches related to opening a new business in a country is positively correlated with the dynamics of entrepreneurial activity in the country and, as such, may be useful for predicting the level of that activity.

The results may serve as a starting point for a new approach to measure, monitor and predict entrepreneurial activities in a country and can help in better addressing policymaking issues related to entrepreneurship.

To the best of the authors’ knowledge, this study is original in its approach and results. Building on intention–behaviour models, this study outlines, to the best of the authors’ knowledge, the first usage of big data for analysing the intention–behaviour relationship in entrepreneurship. This study also contributes to the ongoing debate about the value of big data for entrepreneurship research by proposing and demonstrating the credibility of internet search query data as a novel source of quality data in analysing and predicting a country’s entrepreneurial activity.

The authors argue that privacy is integral to the well-being of consumers and an essential component in not only corporate social responsibility (CSR) but what they term uniquely as social media responsibility (SMR). A conceptual framework is proposed that delineates the privacy issues companies should pay attention to in artificial intelligence (AI)-fueled social media environments.

The authors review literature on privacy issues in social media and AI in the academic and practitioner literatures. Based on the review, arguments focus on the need for an SMR framework, proposing responsible use of consumer data that is attentive to consumers' privacy concerns.

Implications from the framework are a path forward for social media companies to treat consumer data more fairly in this new environment. The framework has implications for companies to reduce potential harms to consumers and consider addressing their power and responsibility. With social media and AI transforming consumer behavior so profoundly, there are a variety of short- and long-term social implications.

Since AI tools are becoming integral to social media company activities, this research addresses the changing responsibilities social media companies have in securing consumers' data and enabling consumers the agency to protect their privacy effectively. The authors propose an SMR framework based on CSR research and AI tools employed by social media companies.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

At the moment, in terms of both research and commercial products, smart shoe technology and applications seem not to attract the same magnitude of attention compared to smart garments and other smart wearables such as wrist watches and wrist bands. The purpose of this study is to fill this knowledge gap by discussing issues regarding smart shoe sensing technologies, smart shoe sensor placements, factors that affect sensor placements and finally the areas of smart shoe applications.

Through a review of relevant literature, this study first and foremost attempts to explain what constitutes a smart shoe and subsequently discusses the current trends in smart shoe applications. Discussed in this study are relevant sensing technologies, sensor placement and areas of smart shoe applications.

This study outlined 13 important areas of smart shoe applications. It also uncovered that majority of smart shoe functionality are physical activity tracking, health rehabilitation and ambulation assistance for the blind. Also highlighted in this review are some of the bottlenecks of smart shoe development.

To the best of the authors’ knowledge, this is the first comprehensive review paper focused on smart shoe applications, and therefore serves as an apt reference for researchers within the field of smart footwear.

Although employee overqualification is a common occurrence in the workplace, most research has focused on overqualification at the individual level rather than at the team level. Drawing on social cognitive theory, this study aimed to uncover how leaders' perception of team overqualification influenced their cognition and follow-up behavior.

We performed two studies to test our model. In Study 1, we conducted an experiment to examine the causal relationship between leaders' perception of team overqualification and leadership self-efficacy. In Study 2, a two-wave field study was conducted to test the overall model based on a sample obtained from a steel company in China.

We found that leaders' perception of team overqualification reduced leadership self-efficacy, which in turn hindered leaders' empowering behavior. In addition, leaders' social face consciousness strengthened the negative relationship between leaders' perception of team overqualification and leadership self-efficacy, such that the relationship was more negative when leaders' social face consciousness was high rather than low.

Our study contributes to the literature on employee overqualification and its effects on leaders through investigation at the team level to show how leaders respond to overqualified teams.

The purpose of this study is to investigate the phenomenon of knowledge transfer between employees and coworkers. That is, when and why employees engage in knowledge seeking or knowledge sabotage when confronted with coworkers with higher relative overqualification.

This study collected survey data from 315 employee-coworker pairs in East China at three-time points.

The results showed that when the cooperative goal interdependence between employee and coworker is high, the perception of coworker’s relative overqualification will cause benign envy of employees, which in turn promote employees to engage in knowledge seeking from coworker. However, when the competitive goal interdependence between employee and coworker is high, the perception of coworker’s relative overqualification will cause malicious envy of employees, which in turn promote employees to engage in knowledge sabotage toward coworker.

This research not only expands the theoretical perspective and outcomes of relative overqualification but also enriches the mechanism of knowledge seeking and knowledge sabotage. Meanwhile, this study also provides practical guidance for enterprises to reduce knowledge sabotage.

This study aims to examine the relationship between abusive supervision and workplace incivility using a dual theoretical framework. First, it draws on the ego depletion theory to investigate the relationship between abusive supervision and incivility by exploring the mediating role of ego depletion. Second, it integrates the job demands–resources model with the ego depletion theory to examine how perceived co-workers’ support functions as a buffer in mitigating the effects of ego depletion on incivility.

The authors tested our moderated mediation model using hierarchical linear modeling through an experience-sampling study based on data collected from a participants across five consecutive workdays.

The findings reveal employees subjected to abusive supervision are more likely to experience a depletion of self-regulatory resources. Moreover, the authors found a positive association between ego depletion and workplace incivility, suggesting that diminished self-control resulting from abusive supervision contributes to a higher likelihood of engaging in uncivil workplace behaviors. In addition, perceived coworkers’ support emerged as a significant moderating factor that attenuates the indirect impact of abusive supervision on workplace incivility through ego depletion. Specifically, when perceived coworkers’ support is high, the negative influence of abusive supervision on ego depletion, and subsequently, on workplace incivility, is mitigated.

By exploring ego depletion as the underlying mechanism and boundary conditions imposed by perceived coworker support on the relationship between abusive supervision and workplace incivility, this research contributes to a nuanced understanding of the intricate dynamics of this relationship. Based on the research findings, the authors advocate that organizations should establish and integrate support services, such as counseling and employee assistance programs, to reduce the emotional turmoil caused by abusive supervision.