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This study aims to investigate the relationship between chief executive officer (CEO) power and the level of tax avoidance of Tunisian listed companies. It also examines the moderating role of institutional ownership in this association.

The sample comprises 306 firm-year observations of companies listed on the Tunis Stock Exchange during the 2013–2020 period.

The results indicate that CEO power reduces tax avoidance levels. Moreover, the relationship between CEO power and tax avoidance is more pronounced in the presence of institutional ownership, suggesting that CEOs act less opportunistically when monitored by institutional investors, which results in a reduction in tax avoidance.

This study suggests that CEO power and institutional shareholders’ influence are important factors in determining firms’ avoidance behavior. This study has significant implications for shareholders and regulatory bodies. Indeed, shareholders apprehend the impact of appointing a powerful CEO on tax avoidance practices. This study may also provide regulators with new insights into the influence of CEO power dimensions and institutional ownership on tax aggressiveness.

This study fills the gap in the accounting literature by investigating how CEO power may impact tax avoidance behavior and provides empirical evidence on the moderating impact of institutional ownership on this relationship in an emerging economy context characterized by a weakly protected investor setting.

Value co-creation (VCC) helps platforms establish competitive advantages. Unlike their traditional counterparts, social attribute is a key concept of social e-commerce platforms. This study integrates VCC and social network theories, introduces relational embeddedness and divides this variable into economic and social relational embeddedness to explore its impact on VCC intention. This study also explores the mediating and moderating roles of customers' psychological ownership (CPO) and regulatory focus, respectively.

A questionnaire survey was conducted among users of mainstream social e-commerce platforms in China, and the relationship among the variables was revealed through a structural equation modeling of 464 valid responses.

The dimensions of relational embeddedness positively affect CPO and VCC intention, with social relational embeddedness exerting the strongest effect. CPO positively affects VCC intention and partially mediates the relationship between relational embeddedness and VCC intention. Promotion and prevention focus positively and negatively moderate the relationship between CPO and VCC intention, respectively.

This study expands the VCC research perspective and links the VCC concepts to social network dynamics. From the relational embeddedness perspective, this study identifies the type and intensity of relational embeddedness that promotes users' VCC intention and contributes to theoretical research on VCC and relational embeddedness. This study also introduces CPO as an intermediary variable, thus opening the black box of this mechanism, and confirms the moderating role of regulatory focus as the key psychological factor motivating users' VCC intention.

Inaction inertia occurs when people are less likely to act on a similar but inferior option after missing a superior opportunity, compared to if they had not missed out. This study aims to explore how promotional formats and their sequence affect the inaction inertia effect in online shopping, under the assumption of economic equivalence.

The authors performed two online experiments and analyzed the data by analysis of variance.

The findings indicate that, under the premise of economic equivalence: Monetary promotions exhibit a higher inaction inertia effect on consumers than nonmonetary promotions. When consumers miss a more favorable promotion and subsequently encounter a relatively less attractive one presented in a different promotional format, the inaction inertia effect is lower than when reencountering the same promotion format. When consumers miss a better monetary promotion and presently encounter a relatively less attractive nonmonetary promotion, the inaction inertia effect is lower than when they miss a superior nonmonetary promotion and currently encounter a relatively less attractive monetary promotion.

This study reveals the sequence effects of promotional formats, indicating that nonmonetary promotions following monetary ones effectively reduce inaction inertia. A strategically sequenced set of formats enhances consumer recommendations, mitigating inaction inertia. These findings open new research paths, providing insights into the impact of promotional format sequences on the inaction inertia effect. Consequently, this knowledge helps e-retailers in implementing effective promotional strategies and driving online purchases.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

This study looks to understand the opposing forces that would influence continuance intention. This is significant as users will take into account the positive and negative use experiences in determining their continuance intention. Therefore, this study looks to highlight the opposing forces of users’ continuance intention by proposing the Expectation-Confirmation-Resistance Model (ECRM).

Through an online survey, 411 responses were obtained from mobile payment users. Subsequently, a hybrid approach comprised of the Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) was utilized to analyze the data.

The results revealed that all hypotheses proposed in the ECRM are supported. More precisely, the facilitating and inhibiting variables were found to significantly affect continuance intention. In addition, the ECRM was revealed to possess superior explanatory power over the original model in predicting continuance intention.

This study successfully developed and validated the ECRM which captures both facilitators and inhibitors of continuance intention. Besides, the relevance and significance of users’ innovative resistance to continuance intention have been highlighted. Following this, effective business and research strategies can be developed by taking into account the opposing forces that affect users’ continuance intention.

Sharing patient health information (PHI) among hospitals has been much slower than the adoption of health record systems. This paper aims to investigate if privacy regulation (PR) or security measures (SMs) influence hospitals’ use of health information exchange (HIE) to share PHI with other providers (e.g. physicians, labs, hospitals). The study specifically focuses on how multiple PRs can impede and a strong national security infrastructure (NSI) can support HIE.

The study uses secondary data from a multi-national and multi-hospital survey administered by the European Union. The multi-level structure of the cross-sectional panel data is used to test the influence of both hospital-level (e.g. PR) and national-level variables (e.g. NSI) on HIE. A total of nine types of HIE, three types of PRs, nine SMs and other relevant control variables are considered. This study uses a two-level random intercept generalized linear model to test the hypothesis proposed in the study.

The study finds that national-level PRs (NLPR) have the strongest positive influence on HIE in comparison to regional (RLPR) and hospital-level (HLPR) PRs. Moreover, the study finds evidence that the presence of RLPR and HLPR, on average, decreases the positive impact of NLPR by 264%. The SMs also have a significant and positive impact on HIE. Adoption of an additional SM can increase the odds of engaging in a certain type of HIE between 21% and 61%. On the other hand, a strong NSI can also amplify the positive impact of SM on certain types of HIE.

This study extends prior research on the role of PRs in enabling HIE by considering the complexities brought up by adopting multiple PRs. NLPRs have the strongest impact on HIE in comparison to RLPRs or HLPRs. Moreover, public infrastructure initiatives such as those related to secure communications can also complement SMs adopted by the providers by encouraging HIE.

We applied a true-experimental randomized control posttest design to collect and analyze quantitative and qualitative data to compare the effects of the AR and traditional board games on students’ SDG learning achievements.

We applied a true-experimental randomized control posttest design to collect and analyze quantitative and qualitative data to compare the effects of AR and traditional board games on students' SDG learning achievements.

Our analysis of the quantitative and qualitative data revealed that the effects of AR and traditional board games on the students' cognitive outcomes differed significantly, indicating the importance of providing a situated learning environment in SDG education. Moreover, the students perceived that the incorporation of the AR game into SDG learning improved their learning effectiveness – including both cognitive and affective dimensions – thus confirming its educational value and potential in SDG learning.

To the best of our knowledge, this is the first study to explore the effectiveness of different learning tools (AR and traditional board games) and to evaluate the importance of providing a situated learning environment through a true-experimental randomized control posttest design.

The purpose of this study is to examine the impact of technological diversification (TD) on enterprise innovation performance, meanwhile focusing on the moderating effects of various organizational slack (i.e. absorbed and unabsorbed slack) and ownership types (i.e. state-owned or privately-owned) in the context of Chinese listed firms.

This study formulates five hypotheses based on organization and agency theories. Our empirical analysis employs a fixed-effect regression estimator with a unique panel dataset of Chinese-listed manufacturing firms and 13,566 firm-year observations over 9 years from 2012 to 2020.

Our findings show that an inverted U-shaped relationship exists between TD and innovation performance, varying with different types of organizational slack and ownership. In state-owned enterprises (SOEs), unabsorbed slack negatively moderates the inverted U-shaped relationship; however, in privately-owned enterprises (POEs), this relationship is positively moderated. Although absorbed slack has negative moderating effects in both SOEs and POEs, its impact is only significant for POEs.

Our results imply that organizational slack has a contrasting impact on the relationship between TD and innovation performance when the type of ownership varies. Therefore, the managers that intend to achieve optimal innovation performance through TD should understand how organizational slack can be leveraged.

This study contributes to the existing literature by applying the relationship between TD and innovative performance to the transition economy, as well as examining the double-edged sword impact of state ownership on firm innovation performance.

Social commerce (s-commerce) has gained widespread popularity as a social platform where customers engage in resource-sharing activities such as information exchange, advice-seeking and expressing their opinions on mutual interests. However, existing studies have not fully comprehended the drivers of electronic customer-to-customer interaction (eCCI) and how such behavior contributes to the customer “stick” on s-commerce sites. This study develops the Motivation–Opportunity–Ability (MOA) theory and investigates the impact of MOA factors on eCCI, which in turn affects customer stickiness.

A survey was used to acquire data from 455 valid respondents, and the research employed a combination of fuzzy-set qualitative comparative analysis (fsQCA) and structural equation modeling.

The results revealed associations between perceived self-efficacy, intrinsic motivation, tie strength with other customers, eCCI and customer stickiness.

Considering the limited availability of complete eCCI frameworks in existing scholarly works, the authors present valuable perspectives on the role of consumer characteristics as both antecedents and consequences of eCCI. Additionally, this study proposes a research agenda for the field of eCCI on s-commerce sites.

This study aimed to propose a performance-oriented approach of automatically generative design and optimization of hospital building layouts in consideration of public health emergency, which intended to conduct reasonable layout design of hospital building to meet different performance requirements for both high efficiency during normal periods and low risk in the pandemic.

The research design follows a sequential mixed methodology. First, key points and parameters of hospital building layout design (HBLD) are analyzed. Then, to meet the requirements of high efficiency and low risk, adjacent preference score and infection risk coefficient are constructed as constraints. On this basis, automatic generative design is conducted to generate building layout schemes. Finally, multi-objective deviation analysis is carried out to obtain the optimal scheme of hospital building layouts.

Automatic generative design of building layouts that integrates adjacent preferences and infection risks enables hospitals to achieve rapid transitions between normal (high efficiency) and pandemic (low risk) periods, which can effectively respond to public health emergencies. The proposed approach has been verified in an actual project, which can help systematically explore the solution for better decision-making.

The form of building layouts is limited to rectangles, and future work can explore conducting irregular layouts into optimization for the framework of generative design.

The contribution of this paper is the developed approach that can quickly and effectively generate more hospital layout alternatives satisfying high operational efficiency and low infection risk by formulating space design rules, which is of great significance in response to public health emergency.