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The purpose of this study is to look at the structure of the interactions between the board of directors’ chairman qualities such as chairman independence, tenure, ethnicity, age- and impression management (IM).

The research population consists of non-financial Malaysian companies listed on Bursa Malaysia’s Main Market, using data gathered via annual reports and DataStream. The study relies on the ordinary least square regression to test the direct relationships between the directors’ chairman characteristics and IM. Moreover, robustness and sensitivity tests were used to examine the effectiveness of chairman characteristics with IM. Furthermore, the results rely on the FGLS regression as an additional test. The study found that chairman independence, chairman ethnicity and chairman age have a significant impact on IM.

The results reveal that chairman independence has a negative association with qualitative IM (IMSC1). Moreover, chairman ethnicity has a positively significant relationship with qualitative IM (IMSC1) and quantitative IM (IMSC2). Also, the effectiveness of chairman characteristics has a negative and significant association with IMSC1.

The primary goal of this paper is to fill a gap in the literature and to open up opportunities for more in-depth research on the subject. So far, there has been no research into the impact of the board chairman’s (BC) personality on IM. This study serves as a warning to policymakers, businesses and their stakeholders, as well as researchers, about the importance of BC characteristics, which may impede the effectiveness of corporate governance mechanisms. The paper provides a framework for investigating these characteristics in the context of IM.

This study reveals the green building development path and analyzes the optimal government subsidy equilibrium through evolutionary game theory and numerical simulation. This was done to explore the feasible measures and optimal incentives to achieve higher levels of green building in China.

First, the practice of green building in China was analyzed, and the specific influencing factors and incentive measures for green building development were extracted. Second, China-specific evolutionary game models were constructed between developers and homebuyers under the market regulation and government incentive mechanism scenarios, and the evolutionary paths were analyzed. Finally, real-case numerical simulations were conducted, subsidy impacts were mainly analyzed and optimal subsidy equilibriums were solved.

(1) Simultaneously subsidizing developers and homebuyers proved to be the most effective measure to promote the sustainability of green buildings. (2) The sensitivity of developers and homebuyers to subsidies varied across scenarios, and the optimal subsidy level diminished marginally as building greenness and public awareness increased. (3) The optimal subsidy level for developers was intricately tied to the building greenness benchmark. A higher benchmark intensified the developer’s responsiveness to losses, at which point increasing subsidies were justified. Conversely, a reduction in subsidy might have been appropriate when the benchmark was set at a lower level.

The expeditious advancement of green buildings holds paramount importance for the high-quality development of the construction industry. Nevertheless, the pace of green building expansion in China has experienced a recent deceleration. Drawing insights from the practices of green building in China, the exploration of viable strategies and the determination of optimal government subsidies stand as imperative initiatives. These endeavors aim to propel the acceleration of green building proliferation and materialize high-quality development at the earliest juncture possible.

The model is grounded in China’s green building practices, which makes the conclusions drawn more specific. Furthermore, research results provide practical references for governments to formulate green building incentive policies.

This paper aims to synthesize the diverse literature on nomination and remuneration committees and provide avenues for future research.

This study provides a comprehensive literature review of theoretical and empirical studies published in reputable international journals indexed by Scopus.

The literature review reveals several aspects of the nomination and remuneration committee. These aspects have been classified into the definition of the nomination and remuneration committee, dimensions of the nomination and remuneration committee, measurement and research review results, reasons for conflict empirical findings, company dynamics and research on moderators, as well as recommending future research.

Our literature review shows that nomination and remuneration committees play a role in improving board performance and company performance, reducing agency conflicts and improving corporate governance to provide implications for companies, regulators and investors and pave the way for future research.

This paper identifies issues related to nomination and remuneration committees, their theoretical and practical implications and avenues for future research.

The purpose of this research is to examine the impact of audit committee financial experts on the risk of financial corruption in public companies.

A time-lagged, matched-pairs sample of 352 corporations was utilized to test the study's hypotheses (176 financially corrupt firms plus 176 compliant firms). To uncover financially corrupt firms, 2,895 Accounting and Auditing Enforcement Releases from the Securities and Exchange Commission were thoroughly evaluated.

The results show that financial experts on audit committees generally increased financial corruption. However, the impact was reversed when audit committees had three or more financial experts, showing that having at least three financial experts reduced financial corruption.

The study's findings call into question the long-held practice of appointing at least one financial expert to audit committees. This study offers a novel approach to improve corporate oversight and reduce financial corruption by having at least three financial experts on audit committees.

In the continuous development of high-speed railways, ensuring the safety of the operation control system is crucial. Electromagnetic interference (EMI) faults in signaling equipment may cause transportation interruptions, delays and even threaten the safety of train operations. Exploring the impact of disturbances on signaling equipment and establishing evaluation methods for the correlation between EMI and safety is urgently needed.

This paper elaborates on the necessity and significance of studying the impact of EMI as an unavoidable and widespread risk factor in the external environment of high-speed railway operations and continuous development. The current status of research methods and achievements from the perspectives of standard systems, reliability analysis and safety assessment are examined layer by layer. Additionally, it provides prospects for innovative ideas for exploring the quantitative correlation between EMI and signaling safety.

Despite certain innovative achievements in both domestic and international standard systems and related research for ensuring and evaluating railway signaling safety, there’s a lack of quantitative and strategic research on the degradation of safety performance in signaling equipment due to EMI. A quantitative correlation between EMI and safety has yet to be established. On this basis, this paper proposes considerations for research methods pertaining to the correlation between EMI and safety.

This paper overviews a series of methods and outcomes derived from domestic and international studies regarding railway signaling safety, encompassing standard systems, reliability analysis and safety assessment. Recognizing the necessity for quantitatively describing and predicting the impact of EMI on high-speed railway signaling safety, an innovative approach using risk assessment techniques as a bridge to establish the correlation between EMI and signaling safety is proposed.

The purpose of this paper is to determine the ultra-high cycle fatigue behavior and ultra-slow crack propagation behavior of selective laser melting (SLM) AlSi7Mg alloy under as-built conditions.

Constant amplitude and two-step variable amplitude fatigue tests were carried out using ultrasonic fatigue equipment. The fracture surface of the failure specimen was quantitatively analyzed by scanning electron microscope (SEM).

The results show that the competition of surface and interior crack initiation modes leads to a duplex S–N curve. Both manufacturing defects (such as the lack of fusion) and inclusions can act as initially fatal fatigue microcracks, and the fatigue sensitivity level decreases with the location, size and type of the maximum defects.

The research results play a certain role in understanding the ultra-high cycle fatigue behavior of additive manufacturing aluminum alloys. It can provide reference for improving the process parameters of SLM technology.

External stakeholder risks (ESRs) caused by unfavorable behaviors hinder the success of project portfolios (PPs). However, due to complex project dependency and numerous risk causality in PPs, assessing ESRs is difficult. This research aims to solve this problem by developing an ESR-PP two-layer fuzzy Bayesian network (FBN) model.

A two-layer FBN model for evaluating ESRs with risk causality and project dependency is proposed. The directed acyclic graph (DAG) of an ESR-PP network is first constructed, and the conditional probability tables (CPTs) of the two-layer network are further presented. Next, based on the fuzzy Bayesian network, key variables and the impact of ESRs are assessed and analyzed by using GeNIe2.3. Finally, a numerical example is used to demonstrate and verify the application of the proposed model.

The proposed model is a useable and effective approach for ESR assessment while considering risk causality and project dependency in PPs. The impact of ESRs on PP can be calculated to determine whether to control risk, and the most critical and heavily contributing risks and project(s) in the developed model are identified based on this.

This study extends prior research on PP risk in terms of stakeholders. ESRs that have received limited attention in the past are explored from an interaction perspective in the PP domain. A new two-layer FBN model considering risk causality and project dependency is proposed, which can synthesize different dependencies between projects.

Drawing on anthropomorphism and the stereotype content model, this study aims to explore the impacts of robot anthropomorphism on hotel guests’ word of mouth and continuous usage intention through perceived warmth and competence. This study also investigates the moderating effects of guests’ expertise.

A total of 524 valid data was collected with Chinese hotel guest through an online survey. Data were analyzed by using structural equation modeling.

The results indicate that robot anthropomorphism positively affects perceived warmth and competence. Perceived warmth positively affects guests’ word of mouth and continuous usage intention, while perceived competence only positively influences guests’ continuous usage intention. The findings further show that guest expertise weakens the positive relationship between robot anthropomorphism and perceived warmth and competence.

This study advances robot service literature by integrating the stereotype content model with robot anthropomorphism in exploring hotel guests’ perceptions on service robots. This study also discovers the vital boundary role of guest characteristics in human–robot interaction. This study provides valuable information for hoteliers to design and adopt better robots for optimal guest experiences.

基于拟人化和刻板印象内容模型, 本研究探讨了机器人拟人化通过感知温暖和感知能力对酒店客人的口碑和持续使用意向的影响。此外, 本研究也探讨了客人专业知识的调节作用。

通过在线调查问卷, 我们共收集了来自中国酒店客人的524份有效数据, 并采用结构方程模型对这些数据进行了分析。

研究结果表明, 机器人拟人化积极影响感知温暖和感知能力。感知温暖会对客人的口碑和持续使用意向产生积极影响, 而感知能力只对客人的持续使用意向产生积极影响。研究结果进一步表明, 客人的专业知识会削弱机器人拟人化与感知温暖和能力之间的积极关系。

为了探索酒店客人对服务机器人的感知（状况/情况）, 本研究将机器人拟人化因素整合到刻板印象内容模型中, 其结果推动了机器人服务研究的发展。本研究还发现了客人特征在人机互动中的重要边界作用。本研究为酒店经营者设计和采用更好的机器人以获得最佳的客人体验提供了有价值的参考。

Se recopiló datos válidos de un total de 524 clientes de hoteles chinos mediante una encuesta en línea. Los datos fueron analizados mediante un modelo de ecuaciones estructurales.

Basándose en el antropomorfismo y en el modelo de contenido estereotipado, este estudio explora el impacto del antropomorfismo de los robots en el boca a boca de los clientes del hotel y en la intención de uso continuado a través de la calidez y la competencia percibidas. El estudio investiga también los efectos moderadores de la experiencia de los huéspedes.

Los resultados indican que el antropomorfismo del robot afecta positivamente a la calidez y a la competencia percibidas. La calidez percibida influye positivamente en el boca a boca y en la intención de uso continuado de los huéspedes, mientras que la competencia percibida sólo influye positivamente en la intención de uso continuado de los huéspedes. Los resultados muestran, además, que la experiencia del cliente debilita la relación positiva entre el antropomorfismo del robot y la percepción de calidez y de competencia.

Este estudio supone un avance en la literatura sobre robots de servicio al integrar el modelo de contenido estereotipado con el antropomorfismo de los robots, en la exploración de las percepciones de los huéspedes de hoteles sobre los robots de servicio. Este estudio también muestra el papel vital que desempeñan las características de los huéspedes en la interacción humano-robot. El estudio proporciona información valiosa para que los hoteleros diseñen y adopten mejores robots para ofrecer experiencias óptimas a los huéspedes.

New generation of construction workers (NGCWs) who were born in the 1980s and later have gradually become the main workforce of Chinese construction industry. They may behave differently when dealing with knowledge-related activities due to divergent characteristics caused by generational discrepancy. To provide a theoretical foundation for construction companies and safety managers to improve safety management, this research explores the factors and paths impacting the NGCWs' ability to share their safety knowledge.

Based on literature review, main factors that influence the safety knowledge sharing of the NGCWs were identified. Decision-Making Trial and Evaluation Laboratory and Interpretive Structural Modeling were applied to identify the hierarchical and contextual relations among the factors influencing the safety knowledge sharing of the NGCWs.

The results showed that sharing atmosphere ranked first in centrality and had a high degree of influence and being influenced, indicating itself an extremely important influencing factor of safety knowledge sharing of NGCWs. Six root influencing factors were identified, including individual characteristics, work pressure, sharing platform, incentive mechanism, leadership support and safety management system.

The number of influencing factors of safety knowledge sharing of the NGCWs identified in this study is limited, and the data obtained by the expert scoring method is subjective. In future studies, the model should be further developed and validated by incorporating experts from different fields to improve its integrity and applicability.

The influencing factors identified in this paper can provide a basis for construction companies and safety managers to improve productivity and safety management by taking relevant measures to promote safety knowledge sharing. The research contributes to the understanding knowledge management in the context of the emerging market. It helps to answer the question of how the market can maintain the economic growth success through effective knowledge management.

This paper investigates the influencing factors of NGCWs' safety knowledge sharing from the perspective of intergenerational differences, and the 13 influencing factor index system established expands the scope of research on factors influencing safety knowledge sharing among construction workers and fills the gap in safety knowledge sharing research on young construction workers. Furthermore, this paper establishes a multi-layer recursive structure model to clarify the influence path of the influencing factors and contributes to the understanding of safety knowledge sharing mechanism.

Digitalization is revolutionizing the retail sector as today's consumers prefer a seamlessly integrated, fluid and irritation-free shopping experience enhanced with artificial intelligence (AI)-powered technologies. Literature highlights gaps in the understanding of the shopping experience in an omnichannel context, involving aesthetic, cognitive and affective experience dimensions. This research highlights the direct effects and the mechanism triggered in the presence of such device.

A sample of 259 consumers was interviewed at the point of sale. Data have been collected after a shopping experience in two concept stores belonging to the same fashion brand: (1) not equipped with AI-powered technology and (2) equipped with these tools. The measurement scales were validated through ANCOVA analysis and causal relationship analysis with structural equation modeling.

The results show that the presence of an in-store AI-powered technologies in a connected store generates a higher aesthetic reaction when visiting the store, a higher absorption when shopping through the flow and a higher intent to purchase. The authors further investigate the underlying mechanism triggered by the presence of this technology, which enables the authors to outline their consequences regarding purchase intention.

The study, conducted within an actual connected store in France, explores the impact of AI technology in connected retail environments on consumer responses. It is an early research in this field, shedding light on a rarely explored area. The authors’ research addresses a significant gap, providing insights into AI-driven retail experiences.