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Build-operate-transfer (BOT) contracts are widely used in the construction and operation of charging piles for new energy vehicles worldwide and stipulate that governments grant charging pile operators franchises for a certain period of time to invest in the construction and operation of the charging piles. The charging piles are then transferred to governments when the concession expires. To encourage charging pile operators to build and operate charging piles, governments usually provide two kinds of subsidies, namely construction and operating subsidies.

The authors establish a typical game model to study the optimal BOT contract between a government and a charging pile operator and their preferences for the two kinds of subsidies.

First, the authors show that there are substitution and complementarity effects between the concession period and the subsidy level. Second, the operator prefers the construction subsidy (operating subsidy) when the additional operating cost is low (high). The government prefers the operating subsidy (construction subsidy) when consumer sensitivity to the number of charging piles is low (high) and the concession period is short or long (moderate). Finally, the adjusted joint subsidy can not only improve social welfare but also that the charging pile operator can obtain the same profit as under the operating subsidy at a lower subsidy amount.

This work develops the first analytical model to study two subsidies in the construction and operation of charging piles and investigate the optimal BOT contract and subsidy preferences. The insights are compelling not only for the charging pile operator but also for policymakers in practice from a circular economy perspective.

The power battery is the core of a new energy vehicle and plays a vital role in the rise of the new energy vehicle industry. As the number of waste batteries increases, firms involved in the industry need to properly dispose them, but what party is responsible remains unclear. To reduce environmental impacts, governments introduce two subsidy policies, i.e. collection subsidies, which are provided to the collecting firms, and dismantling subsidies, which are provided to the dismantling firms.

Based on the different characteristics of the subsidies, we develop a stylized model to examine the collection strategies and the preferences over the subsidies.

We derive several insights from analysis. First, the collection strategies depend on the fixed collection cost. Second, the key factor determining the firm's subsidy preference is the efficiency of dismantling. Finally, if the primary target is the collection rate, governments prefer to provide collection subsidies. If consider the environmental impact, the choice of subsidies has to do with the efficiency of dismantling. Moreover, from a social welfare perspective, the raw material cost and the efficiency of dismantling are core indicators of decision.

This work develops the first analytical model to study two power battery subsidies and investigate the optimal collecting strategies and subsidy preferences. The insights are compelling not only for the manufacturer and the third party but also for policymakers.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IMDS-08-2019-0450

This study aims to explore the adverse impacts of abusive supervision on helping behaviors among employees, as mediating by intention to leave and moderating by Islamic work ethics (IWE).

A quantitative approach was employed, and the sample consisted of 283 nurses working in various public sector hospitals in Pakistan. The data analysis was conducted using SPSS and AMOS with the PROCESS macro.

The results suggest that abusive supervision diminishes helping behavior among nurses. Additionally, the study reveals that intention to leave mediates the relationship of abusive supervision and nurses' helping behavior. Moreover, the introduction of IWE as a boundary condition reveals that the mediated link is weaker when IWE is higher, and vice versa.

This study provides valuable insights for hospital authorities to develop intervention strategies and policies aimed at reducing abusive supervision in hospitals. Hospital management should also be aware of the detrimental effects of abusive supervision on nurses' helping behaviors, which can be mitigated by promoting ethical values aligned with IWE.

This study makes a valuable contribution to the limited research on the link between abusive supervision and helping behaviors in hospital settings. It offers new perspectives by incorporating the Conservation of Resources theory, particularly within the healthcare sector. Furthermore, this research expands the current knowledge by investigating the mediating influence of intention to leave and the moderating effect of IWE in mitigating the adverse impact of abusive supervision on nurses' helping behavior in Pakistan's public sector hospitals.

This study, based on the conservation of resource theory, aims to investigate the negative impacts of abusive supervision on helping behaviors among employees by examining the mediating role of rumination and the moderating role of psychological flexibility.

A total sample of 282 reliable questionnaires are collected from 282 employees working in education and banking sectors of Pakistan. SPSS and AMOS are used for data analysis of the proposed model.

The findings reveal that rumination mediates the relationship between abusive supervision and employees’ helping behavior. In addition, the results show that higher levels of psychological flexibility negatively moderate the relationship between abusive supervision and employees’ helping behaviors through mediation.

This study elucidates how and when abusive supervision deters helping behavior among employees and provides useful guidelines for banking/university’s administration to understand harmful consequences of abusive supervision and take appropriate policy measures to lessen their harmful effects upon employees.

By proposing a moderated mediation model, this study discovers rumination as a key mediator that links abusive supervision to employees’ helping behaviors and identifies the role of psychological flexibility in diminishing the negative impacts of abusive supervision upon employees’ helping behaviors through rumination.

Mobile social apps permeate every facet of daily life through the pervasive use of smartphones. Customer retention with mobile social apps has become extremely important for app-related companies. The purpose of this paper is to explore why experienced users in mobile social apps (e.g. WeChat) are likely to continue using the app.

This study proposed a conceptual model to identify key determinants of continuance intention of WeChat users and highlight the effects of individual experience. Data were collected from WeChat users, which is one of the most popular mobile social apps in China. The study employed partial least squares regression to test the research model based on a survey of 295 valid responses.

Results showed that trust, which was driven by user satisfaction and perceived critical mass, played a critical role in influencing the continuance intention of WeChat users. Moreover, tie strength exerted a negative moderating effect on the relationship between trust and continuance intention. Specifically, tie strength and perceived critical mass had strong impacts on the continuance intention of low-experience users. In addition, the effect of frequency was closely associated with the continuance intention of high-experience users.

This study addressed the issue of mobile social app continuance intention by providing an innovative means to explore the key antecedents of user continuance intention from the experience perspective. The findings not only prove that trust plays a central role in influencing the continuance intention of experienced users but also reveal that the determinants of continuance intention vary among users with different experience. The results provide insights into the key antecedents of experienced WeChat user continuance intention and contribute to the literature on mobile social apps and individual differences.

The results provide suggestions for mobile social app practitioners to effectively plan mobile social app retention practices and to set up appropriate incentive mechanisms for retaining users with different experiences.

Although abundant studies have focused on the adoption of media users, few studies have investigated the post-adoption behavior of experienced users in the context of mobile social apps. This study revealed the key determinants of the continuance intention of WeChat users and pinpointed the different impacts of these antecedents on users with different levels of experience. It also provides useful guidelines for practitioners to effectively retain users with different levels of experience.

This study, based on social exchange theory, aims to explore knowledge hiding behavior in relation to shared goals of individuals working in teams and trust (cognitive-based trust and affective-based trust) as a boundary condition on shared goals and knowledge hiding relationship.

A total sample of 270 reliable questionnaires are collected from university students in China. SPSS and AMOS are employed for the data analysis of the proposed model.

Findings of the study have indicated that shared goals are negatively associated with knowledge hiding behavior. Furthermore, trust (cognitive-based trust and affective-based trust) moderates the relationship between shared goals and knowledge hiding behavior.

This study has provided empirical proof and in-depth understanding and recommendations for supervisors and administrative authorities to form the culture of groups/teams with shared goals to reduce the undesirable individual behaviors.

This study, among the first empirical studies investigating the relationship between shared goals and knowledge hiding behavior, trust as a moderator, enriches the existing academic literature of and provides valuable insight into the research on knowledge hiding and knowledge management.

The purpose of this study is to contribute to empirical research on individual ambidexterity drivers. This paper analyzes the relationships between inclusive leadership, team knowledge acquisition, team knowledge sharing, digital tools usage and individual ambidexterity.

This study conducted a questionnaire survey of high-tech and manufacturing enterprises in China and obtained 75 leader questionnaires and 365 employee questionnaires. The hypotheses were tested using hierarchical and cross-level regressions.

The research indicates that inclusive leadership improves team knowledge acquisition and sharing. However, only team knowledge sharing significantly boosts individual ambidexterity, and not team knowledge acquisition. Thus, inclusive leadership fosters individual ambidexterity primarily through team knowledge sharing. Digital tools usage strengthens the impact of inclusive leadership on team knowledge sharing, thereby intensifying its effect on individual ambidexterity. However, digital tools usage weakens the effect of inclusive leadership on team knowledge acquisition.

First, this study addresses the call for research on ambidexterity at different levels, revealing the heterogeneous impact of team knowledge acquisition and sharing on individual ambidexterity. Second, this study developed a theoretical model to explore how leadership affects individual ambidexterity. Third, this study responds to the question that digitalization has won, but has leadership lost by investigating the role of digital tools usage in the relationship between inclusive leadership and team knowledge integration.

Firms in emerging economies are generally at a disadvantage in terms of resources, which may limit their digital transformation. The Chinese government has designed and promulgated a series of wind power policies from the perspectives of support and regulation. The former provides scarce resources for enterprises and thus alleviating financial constraints. While the latter increases the demands for advanced technologies, thereby triggering resource bricolages. This study aims to clarify the impact of industrial policy on the digital transformation of the Chinese wind power industry, and the role of financing constraint and resource bricolage in the above relationship.

Based on the data of listed companies in the Chinese wind power industry from 2006 to 2021, this study clarifies the impact and mechanism of industrial policy on firm digital transformation with fixed effect regression models.

Empirical results indicate that both supportive and regulatory policies are the cornerstone of the digital transformation of the Chinese wind power industry. Financial constraint and resource bricolage, respectively, mediate the impact of supportive and regulatory policies. However, the mix of supportive and regulatory policies inhibits digital transformation. Moreover, industrial policies are more effective for the digital transformation of state-owned enterprises, as well as enterprises in economically underdeveloped regions.

This study investigates the path of government intervention driving firm digital transformation from the resource-related perspective (i.e. financial constraint and resource bricolage), and its analytical framework can be extended based on other theories. The combined effects of cross-sectoral policies (e.g. wind power policy and digital infrastructure policy) can be further assessed. The marginal net benefit of government intervention can be calculated to determine whether it is worthwhile.

This study emphasizes the necessity of government intervention in the digital transformation of enterprises in emerging economies. The governments should align the policy targets, clarify policy recipients and modify policy process of different categories of industrial policies to optimize the effectiveness of policy mix. Given that the effectiveness of government intervention varies among different categories of enterprises, the competent agencies should design and promulgate differentiated industrial policies based on the heterogeneity of firms to improve the effectiveness and efficiency of industrial policies.

This is one of the earliest explorations of industrial policies’ effect on the digital transformation of the renewable energy sector in emerging economies, providing new evidence for institutional theory. Meanwhile, this study introduces financial constraint and resource bricolage into the research framework and attempts to uncover the mechanism of industrial policy driving the digital transformation of enterprises in emerging economies. Besides, to expand the understanding of the complex industrial policy system, this study assesses the effectiveness of the industrial policy mix.

Digital technologies open up unprecedented opportunities for the Chinese wind power industry to make rapid and comprehensive decisions. However, the relationship between digital technology adoption and radical and incremental innovations has not been empirically assessed. In addition, reconfiguration capability is the ability of firms to transform and respond to changes. How such an organizational capability influences the effectiveness of digital technology adoption is a black box. In response, this study aims to assess the relationship between digital technology adoption and radical and incremental innovations in the Chinese wind power industry and elucidate the moderating role of reconfiguration capability.

Based on the data of listed companies in the Chinese wind power industry from 2006 to 2020, this study constructs regression models and validates the hypotheses.

The correlation between digital technology adoption and incremental innovation in the wind power industry in China is significantly positive, but the relationship between digital technology adoption and radical innovation is not significant. In addition, reconfiguration capability significantly enhances the incentive effect of digital technology adoption on incremental innovation.

To the best of the authors’ knowledge, this study is one of the earliest to explore the heterogeneous relationships between digital technology adoption and radical and incremental innovations in emerging economies, advancing the theoretical insights into how digital transformation can foster different categories of technological innovations. Moreover, this study embeds dynamic capability theory into digital transformation research by exploring the boundary conditions for the effectiveness of digital technology adoption from the perspective of organizational dynamic capability, thereby expanding the boundaries of existing knowledge.

The purpose of this study is to investigate the key characteristics of artificial intelligence (AI) in organizational settings, analyze its capacity to reduce customer service jobs in favor of more advanced roles and analyze its efficacy in candidate screening by emphasizing performance.

A comprehensive analysis of 40 papers is performed using the PRISMA method based on data from Web of Science, Scopus, Emerald and Google Scholar.

The findings show optimized human resource management operations such as recruiting and performance monitoring, resulting in increased precision in hiring and decreased employee turnover. Customer service automation redistributes human labor to more intricate positions that need analytical reasoning and empathetic skills.

The study has two key implications. First, AI can streamline customer service, freeing up human workers for more complex tasks. Second, AI may increase candidate screening accuracy and efficiency, improving recruiting outcomes and organizational performance.

The study adds to the current literature by shedding light on the intricate relationships between AI and organizational performance and providing insights into the processes underpinning trust-building in AI technology.