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As the cost of completing a transaction, the green merger and acquisition (M&A) premium paid on mergers can influence whether the acquisition creates value or not. However, studies linking M&A premiums to firm value have had mixed results, even fewer studies have examined the effect of green M&A premiums on bidders’ firm value. The purpose of this paper is to investigate whether and how green M&A premiums affect firm value in the context of China’s heavy polluters.

Using 323 deals between 2008 and 2019 among China’s heavy polluters, this paper estimates with correlation analysis and multiple regression analysis.

Green M&A premiums are negatively associated with firm value. The results are more significant when firms adopt symbolic rather than substantive corporate social responsibility (CSR) strategies. Robustness and endogeneity tests corroborate the findings. The negative relation is stronger when acquiring firms have low governmental subsidy and environmental regulation, when firms have overconfident management, when firms are state-owned and when green M&A occurs locally or among provinces in the same region. This study also analyzes agency cost as an intermediary in the relationship between green M&A premium and firm value, which lends support to the agency-view hypothesis.

This study provides systemic evidence that green M&A premiums damage firm value through agency cost channel and the choice of CSR strategies from the perspective of acquirers. These findings enrich the literature on both the economic consequences of green M&A premiums and the determinants of firm value and provide a plausible explanation for mixed findings on the relationship between green M&A premiums and firm value.

Recycling and reuse of the electric vehicle (EV) batteries are ways to extend their limited lives. If batteries can be traced from production to recycling, it is beneficial for battery recycling and reuse. Using blockchain technology to build a smart EV battery reverse supply chain can solve the difficulties of lack of trust and data. The purpose of this study is to discuss the behavioural evolution of a smart EV battery reverse supply chain under government supervision.

This study adopts evolutionary game theory to examine the decision-making behaviours of the government, EV manufacturers with recycled used batteries and third-party EV battery recyclers lacking professional recycling qualification.

On the smart reverse supply chain integrated by blockchain technology, a cooperative recycling strategy of the third-party EV battery recycler is the optimal choice when the government tends to actively regulate. The probability of the EV manufacturer choosing the blockchain adoption strategy exceeds (below) the threshold, and the government prefers negative (positive) supervision. According to numerical analysis, in the mature stage in the EV battery recycling industry, when the investment cost of applying blockchain is high, EV manufacturers' willingness to apply blockchain slows down, the government accelerates adopting a negative supervision strategy and third-party EV battery recyclers prefer cooperative recycling.

The results of this study provide opinions on the strength of government supervision and the conditions under which EV manufacturers and third-party EV battery recyclers should apply blockchain and cooperate. On the other hand, this study provides theoretical analysis for promoting the application of blockchain technology in smart reverse supply chain.

Compared with previous research, this study reveals the relevance of government supervision, blockchain application and cooperation strategy in smart EV battery reverse supply chain. In the initial stage, even if the subsidy (subsidy reduction rate) and penalty are high and the penalty reduction rate is low, the EV manufacturer should rather give up the application of blockchain technology. In the middle stage in the EV battery recycling industry, the government can set a lower subsidy (subsidy reduction rate) combined with a penalty or a higher penalty (penalty reduction rate) combined with a subsidy to supervise it. The third-party EV battery recycler is advised to cooperate with the EV manufacturer when the subsidy is low or the penalty is high.

The purpose of this paper is to investigate remanufacturing operational strategies considering uncertain quality of end-of-life (EOL) products and differential consumers’ willingness-to-pay (WTP) for new products and provide suggestions on the remanufacturing mode selection for the original equipment manufacturer (OEM).

This study considers three remanufacturing modes, i.e. in-house, outsourcing and authorization modes. By establishing and comparing decision models of three modes from the perspectives of profit, consumer surplus and environment, the optimal remanufacturing mode is discussed.

The results suggest that if the OEM’s remanufacturing capability is high, the in-house mode brings to the highest environmental performance, OEM’s profit and consumer surplus. Otherwise, the outsourcing mode (authorization) is the best benefit to environment (consumers if the unit production cost of new products is not too high). As for the preference of two decision-makers to outsourcing and authorization modes, if the difference of consumers’ WTP for new products is low, the OEM prefers the outsourcing mode; otherwise, the OEM prefers the authorization mode. The preference of the third-party remanufacturer (TPR) to remanufacturing mode is affected by consumers’ WTP for remanufactured products, WTP difference for new products and remanufacturing quality level standard.

These results can provide operational insights into how to select remanufacturing mode when the quality of EOL products is uncertain and consumers’ WTP for new products is different under three remanufacturing modes.

This paper is among the first to investigate the joint effects of EOL products’ uncertain quality and differential consumers’ WTP for new products on the operational strategies and performance under different remanufacturing modes.

Artificial intelligence (AI) is experiencing growth and prosperity worldwide because of its convenience and other benefits. However, AI faces challenges related to consumer resistance. Thus, drawing on the user resistance theory, this study explores factors that influence consumers’ resistance to AI and suggests ways to mitigate this negative influence.

This study tested four hypotheses across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI’s “substitute” image leads to consumer resistance to AI; Study 2 focused on the role of perceived threat as an underlying driver of resistance to AI. Studies 3–4 provided process evidence by the way of a measured moderator, testing whether AI with servant communication style and literal language style is resisted less.

This study showed that AI’s “substitute” image increased users' resistance to AI. This occurs because the substitute image increases consumers’ perceived threat. The study also found that using servant communication and literal language styles in the interaction between AI and consumers can mitigate the negative effects of AI-substituted images.

This study reveals the mechanism of action between AI image and consumers’ resistance and sheds light on how to choose appropriate image and expression styles for AI products, which is important for lowering consumer resistance to AI.

This paper aims to present an unconditionally energy-stable scheme for approximating the convective heat transfer equation.

The scheme stems from the generalized positive auxiliary variable (gPAV) idea and exploits a special treatment for the convection term. The original convection term is replaced by its linear approximation plus a correction term, which is under the control of an auxiliary variable. The scheme entails the computation of two temperature fields within each time step, and the linear algebraic system resulting from the discretization involves a coefficient matrix that is updated periodically. This auxiliary variable is given by a well-defined explicit formula that guarantees the positivity of its computed value.

Compared with the semi-implicit scheme and the gPAV-based scheme without the treatment on the convection term, the current scheme can provide an expanded accuracy range and achieve more accurate simulations at large (or fairly large) time step sizes. Extensive numerical experiments have been presented to demonstrate the accuracy and stability performance of the scheme developed herein.

This study shows the unconditional discrete energy stability property of the current scheme, irrespective of the time step sizes.

Drawing on the perspective of trust and individual differences, this study developed and tested a model to identify the effect of leaders' demonstrated humility on employees' feedback-seeking processes. Specifically, it examined the role of feedback orientation and employees' trust in supervisors in the way humble leadership affects employees' feedback-seeking behavior (FSB).

The moderated mediation model was tested using matched surveys from 175 Chinese employees and their direct supervisors from various organizations.

The results revealed that humble leadership could predict employees' FSB through supervisor trust. Moreover, feedback orientation not only moderated the relationship between supervisor trust and employees' FSB but also moderated the indirect effect of humble leadership on employees' FSB via supervisor trust.

These findings can provide guidance to corporate organizations on how to motivate employees to actively seek feedback to improve their job performance.

In this study the authors examine the nature and contents of key audit matters (KAMs), and the consequences of KAMs reporting on audit quality in the context of a developing country, Bangladesh. The authors’ proxies of audit qualities are discretionary accruals, small positive earnings surprise, audit report lag, earnings management via below the line items and audit fees.

The authors use content analysis of the KAMs for the period 2018–2021 to understand the nature and extent of KAMs reported by auditors in Bangladesh. The authors then use multivariate regression analysis to examine the effect of the number and content characteristics of KAMs on audit quality by using multivariate regression analysis.

Auditors in Bangladesh disclose a higher number of KAMs compared to other countries, disclose short descriptions of KAMs and industry generic KAMs. The authors document significant cross-sectional variations in the number and content characteristics of KAMs reported by auditors in Bangladesh. The authors’ pre-post analysis suggest that audit quality has improved after the adoption of KAMs. Cross-sectional analysis suggests that KAMs number and content characteristics are related to audit quality.

The authors’ findings imply that the KAMs reporting has the potential to play significant monitoring role in reducing the opportunistic behavior of managers. Hence, KAMs reporting can play a significant role in reducing the agency problem. For regulators, shareholders and corporate managers, the authors’ findings imply that if the audit quality is to be increased, the audit effort should be supported by an appropriate amount of audit fee.

The content characteristics of KAMs significantly influence managerial reporting behavior and affect the level of audit efforts.

Unlike developed countries (Gutierrez et al., 2018; Lennox et al. 2022), this study supports that KAMs reporting improves audit quality and control opportunistic behavior of managers in developing countries. The authors show that even though the KAMs disclosure quality is poor, it has the potential to improve financial reporting quality.

Mobile phone payment is a significant advancement in e-commerce and retailing. This study aims to look at the influencing factors for the attainment or letdown of mobile payment systems (MPS). The coping theory (CP) and innovation resistance theory (IRT) components were applied in the tourism sector.

The data were gathered from 402 tourists who utilized MPS for the first time to book their vacation. In a longitudinal study, an online questionnaire was used to contact clients of several travel businesses to predict their intentions and behavior. Covariance-based structure equation modeling (CB-SEM) was applied using IBM-SPSS AMOS to analyze the data.

CP factors provided highly thought-provoking results, calling into question several apparent beliefs. At the same time, the relationships covering the aspects of the IRT were supported. It has also been found that intentions are a valid predictor of behavior.

The study's findings can be used by governments, media houses, hotels and travel and tourism agencies, particularly in developing countries like Malaysia.

This study adds to the existing literature by offering a complete model that demonstrates the influence of conceptualizations utilized from the most robust theories connected to technology toward MPS for trip reservations from the perspective of developing countries. Importantly, this study measures the consumers' continuous buying behavior by employing a longitudinal research design.

This research empirically investigates how service employees' ratings of technology readiness (TRI), negative attitudes towards robots (NARS), Big Five personality traits (BFI) and emotional demands (ED) affect their willingness to work with service robots (WTW).

One set of data is collected from 410 service employees expected to work with service robots in Study 1. Another set of field data is collected from 102 employees working with service robots in Study 2. Hierarchical regression is used to test hypotheses about the impact of technology readiness, negative attitudes towards robots and Big Five personality traits on WTW. Additionally, the interactions of emotional demands in the workplace are analysed.

TRI-optimism and TRI-insecurity significantly affect WTW in Study 2 but are nonsignificant in Study 1. The impacts of NARS-emotions in interaction with robots and NARS-interaction with robots situations on WTW are significant in Study 1 but nonsignificant in Study 2. Moreover, BFI-neuroticism negatively affected WTW in Study 1, while these effects were nonsignificant in Study 2. Finally, emotional demands significantly interact with three of eleven dimensions of IVs in Study 1, but all interactions are nonsignificant in Study 2.

This research provides a guiding framework for service companies to screen employees expected to cowork with service robots, to enhance newly hired employees' WTW and to improve existing employees' WTW.

Integrating the characteristics of service employees, service robots and jobs into a theoretical framework, this research is the first to empirically examine the effects of service employees' several critical characteristics (technology readiness, negative attitudes towards robots and Big Five personality) on WTW and the moderation of job characteristics (emotional demands).

This paper aims to comprehensively review the preparation methods of superhydrophobic surfaces (SHPS) for corrosion protection of Mg alloy in recent years.

The preparation methods, wettability and corrosion resistance of SHPS on Mg alloy in the past three years are systematically described in this paper.

Two types of SHPS, including single-layer and multilayer coatings for corrosion protection of Mg alloy are summarized. Preparing multilayered coatings with multifunction is the current trend in developing SHPS on Mg alloy.

This paper reviewed the preparation methods and corrosion resistance of SHPS on Mg alloys. It provides a valuable reference for researchers to develop highly durable SHPS with excellent corrosion resistance for Mg alloys.