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Corporate social responsibility (CSR) practices frequently result in increased costs for Chinese international contractors (CICs), where profitability is the primary objective; therefore, internal corporate drivers and external pressures play a crucial role in encouraging them to engage in sustainable CSR practices. This study systematically examines the dynamic impact of internal and external stakeholders on the CSR practices of CICs.

This study adopted a structural equation model (SEM) to identify and validate a correlation between stakeholders and CSR practices. Standardized causal coefficients estimated in SEM were used to construct a fuzzy cognitive map (FCM) model to illustrate the effect of stakeholders on CSR practices with linkage direction and weights. Predictive, diagnostic, and hybrid analyses were performed to dynamically model the variation in stakeholders on the evolution of CSR practices.

The empirical results demonstrate that (1) employee participation in CSR has the greatest impact on CSR practices, followed by CSR strategies, partner and customer expectations, and finally government regulations. (2) In the early stage of CSR fulfillment, CSR strategies have the greatest influence on CSR practices; in the later stage of CSR fulfillment, employee participation in CSR has the greatest influence on CSR practices. (3) In the long run, the most effective and economical integrated interventions are those that address employee participation in CSR, partner expectations and customer expectations, and intervention in CSR strategies is needed if the level of CSR practice needs to be improved in the short term.

This study contributes to the research on the influence mechanisms of CSR practices of CICs and systematically analyzes their dynamic influence on CSR practices of CICs from the perspective of stakeholders.

This study examines and estimates the relationship among identified factors or determinants for the adoption of water ionizers by customers.

To this end, the questionnaire is prepared to have the preferences of customers based on the factors or enablers identified for the analysis of customers' perceptions toward the adoption of water ionizers. Recipients are identified to collect their preferences for the factors responsible for the adoption. The convenience sampling method is used in administering the questionnaire for the study. The structural equation modeling (SEM) technique is used to construct the model for defining the relationship between measured and latent variables using the lavaan, haven, psych and semPlot libraries in R software.

The study reveals that product features, which include pH value, oxidation-reduction potential (ORP) and micro-clustering (MC), are influenced by environmental sustainability (ES), and as a result, product features and product outcomes (brand value (BV), customer recommendation (CR) and perceived usefulness (PU)) together influence the adoption of water ionizers by customers.

Water ionizers have appeared as consumer electronic appliances designed to alter the pH and ORP of water through an electrolysis process. There are proven benefits to improved water quality across different pHs for its health benefits (HB) and other commercial and household uses. The study recommends that potential HB perceived through water ionizers and product features, which are supported by ES, and helps customers decide on the adoption of water ionizers.

The study supports comprehending the relationships between consumer behavior, sustainable practices and innovative technologies like water ionizers as society places a greater emphasis on environmentally conscious living and sustainable living. This study aims to clarify the elements affecting the adoption and perception of water ionizers from a sustainability perspective through an extensive assessment of the literature and empirical analysis.

There are two purposes in this paper. The first one is to explore the impact mechanisms and paths of service-oriented manufacturing (SOM) on the sustainability performance of green manufacturing firms and to pay particular attention to the mediating role of enterprise costs in the relationship between the two. The second one is to reveal the dynamic process and laws of SOM influencing on the sustainability performance of green manufacturing enterprises.

This paper employs a combination of dynamic and static research from two aspects. On the one hand, based on 495 green manufacturing firms in China, the authors verify the SEM of SOM, enterprise cost and sustainability performance of green manufacturing firms through empirical research, analyze the path relationship and mediation effect, and demonstrate its complex impact mechanism. On the other hand, the authors use agent-based modeling and simulation to reveal the dynamic influence of SOM on the sustainability performance of green manufacturing enterprises and explore its dynamic laws and future development trends.

The study results indicate that (1) SOM has a direct positive effect on firm sustainability performance. (2) Reducing firm costs has a positive effect on firm sustainability performance, and firm costs play a partial mediating role in the mechanism by which SOM influences firm sustainability performance. (3) The dynamic impact of SOM on sustainability performance increases significantly over time. (4) Significant firm heterogeneity exists in the process by which SOM improves sustainability performance. (5) There are differences in the promotion of SOM for economic performance, environmental performance and social performance.

This paper makes two main contributions. First, compared with previous research on sustainability performance focusing on a certain dimension, this paper organically integrates the three dimensions of sustainability performance, regards them as a whole and considers the paths to improve sustainability performance. Second, this paper focuses on the complex relationship among SOM, enterprise costs and sustainability performance and reveals different sustainability performance improvement paths and dynamic impact processes, thereby expanding and deepening previous research on sustainability on the subject. These contributions lead to a better understanding of the driving forces and realization path for green manufacturing firms' sustainability performance from an integrated static and dynamic perspective.

In the digital era, the banking sector has transformed into a powerful intermediary, effectively connecting surplus and deficit units. This dynamic landscape empowers savers to secure their finances and generate returns, while simultaneously enabling businesses and individuals to access capital for investment and promoting economic growth. This study explores the relationships among banking development dimensions – represented by primary assets and liabilities, bank capital (core capital and required reserves) and economic growth as measured by components of gross domestic product (GDP).

The study consolidated monthly balance sheets from digital banks over a 20-year period, resulting in an aggregate monthly balance sheet that reflects the financial position of all digital banks in the Palestinian economy. The research employs both maximum likelihood and Bayesian structural equation modeling to measure the causal pathways of the consolidated balance sheet with the individual components of GDP.

The results revealed that bank main assets (investments and loans) and liabilities (deposits) collectively explain for 97% of bank capital. Investments and loans demonstrate significant negative correlations with bank capital, while deposits exhibit a positive impact. This leads to a fundamental conclusion that a substantial proportion of retained earnings within the banking sector is reinvested, fueling expansion and growth. Additionally, the results showed a significant relationship between bank capital and various GDP components, including private consumption, gross investment and net exports (p = 0.000). However, while the relationship between bank capital and government spending was insignificant in the maximum likelihood estimation, Bayesian estimation revealed a slight yet positive impact of bank capital on government spending.

This research stands out due to its unique exploration of the intricate relationship between bank sector development dimensions, primary assets and liabilities and their impact on bank capital in the digital era. It offers fresh insights by dividing this connection into specific dimensions and constructs, utilizing a comprehensive two-decade dataset covering the digital banks records.

The purpose of this study is to discuss the construction of a structural measurement model utilizing structural equation modelling (SEM) to confirm the link between Industry 4.0 technologies, sustainable manufacturing practices and organizational sustainable performance. Relationship among the paradigm has yet to be fully investigated, necessitating a more conceptual and empirical examination on what impact they have on organizational sustainable performance when used together.

Industry 4.0 and sustainable production practices aim to progress a company's business competitiveness, forming sustainable development that benefits manufacturing companies. The aim of the study is to analyze the relationship between constructs that lead to operational excellence in firms that use Industry 4.0 technologies and sustainable manufacturing techniques. Experts from diverse automotive industries, who are applying both Industry 4.0 and sustainable manufacturing practices, provided data for the study.

Statistical estimations (hypotheses) are created to substantiate the measurement model that has been developed. The structural model was analysed, and the findings were discussed. The statistical estimate is either approved or rejected based on the findings. According to the conclusions of this study, strong link exists between Industry 4.0 technologies and sustainable manufacturing practices that affect organizational sustainable performance environmentally, economically and socially.

The research was conducted in the framework of automobile component manufacturing companies in India. The outcomes of the study are practically feasible.

The authors' novel contribution is the construction of a structural model with Industry 4.0 technologies and sustainable manufacturing practices into account.

This study investigates augmented reality (AR) retailing and attempts to develop a profound understanding of consumer decision-making processes in AR-enabled e-retailing.

The study is grounded in rich informational cues and information processing mechanisms by incorporating the elaboration likelihood model (ELM) and trust transfer theory. This study employs a mixed analytic method that incorporates structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to provide a complete picture of individual information process mechanisms in AR retailing under the tenet of ELM.

The SEM analysis results confirm the relationships between the central and peripheral route factors, information processing outcomes and eventual behavioral intentions. Moreover, all configurations revealed by the fsQCA include both central and peripheral factors. Hence, the dual routes proposed in the ELM are verified by using two distinct analytical approaches.

This study is pioneering in validating and contextualizing ELM theory in AR retailing. In addition, this study offers a methodological paradigm by demonstrating the application of multi-analysis in exploring consumers’ information process mechanisms in AR retailing, which offers a holistic and comprehensive view to understand consumers’ decision-making mechanisms.

Considering the construction industry’s vital role in economic development and social consequences, this study seeks to pinpoint critical barriers hindering Turkey’s sustainable construction (SC). Although several studies highlighted the barriers to SC worldwide, none identified the critical factors. By identifying and understanding these barriers, the research aims to comprehensively understand practices and formulate strategic recommendations to promote sustainable construction.

A systematic approach is adopted to achieve the research objectives. The study involves identifying potential barriers to SC with a systematic literature review. A questionnaire was organized and distributed via e-mail to architects, civil engineers, and contractors. The criticality of identified barriers was determined with normalized mean value analysis, and critical barrier factors (CBFs) to SC were isolated with exploratory factor analysis. Finally, the effect size of these factors was quantified through structural equation modeling.

This study identified 32 critical barriers hindering the SC in the Turkish construction industry among 49 barriers. Furthermore, this study revealed six CBFs to SC that are “inadequate supervision and control of SC,” “fear of transition to sustainable construction and disruptions in adoption,” “lack of educational opportunities,” “return on investment and financial bias,” “awareness and knowledge gap about SC,” and “lack of demand from stakeholders.” Among them, “awareness and knowledge gap about SC,” “fear of transition to SC,” “lack of educational opportunities,” “lack of demand from stakeholders,” and “inadequate supervision and control of SC” were determined as the very highly crucial CBFs hindering SC.

Although some studies have identified the barriers to SC qualitatively and quantitatively, studies have yet to provide insights into the critical barrier factors hindering SC. Therefore, this study comprehensively and quantitatively determines the relevant CBFs to SC using exploratory factor analysis and utilizes confirmatory factor analysis and structural equation modeling to present a structural model of how critical factors affect the SC.

In the existing era, international trade is boosted by maritime freight movement. The academicians and Government are concerned about environmental contamination caused by maritime goods that transit global growth and development. Digital technologies like blockchain help the maritime freight business to stay competitive in the digital age. This study aims to illuminate blockchain technology (BCT) adoption aspects to alleviate early industry adoption restrictions.

This study adopts a two-stage approach comprising of structural equation modeling (SEM) with artificial neural networks (ANN) to analyze critical factors influencing the adoption of BCT in the sustainable maritime freight industry.

The SEM findings from this study illustrate that social, organizational, technological and infrastructual and institutional factors affect BCT execution. Furthermore, the ANN technique uses the SEM data to determine that sustainability enabled digital freight training (S3), initial investment cost (O5) and trust over digital technology (G1) are the most essential blockchain deployment factors.

The hybrid approach aims to help decision-makers and policymakers examine their organizational blockchain adoption goals to construct sustainable, efficient and effective maritime freight transportation.

This paper aims to identify key factors influencing the development of advanced manufacturing clusters and propose governance pathways for their digital innovation ecosystems.

A quantitative analysis of the Tai-Xin Integrated Economic Zone in China is conducted using data collected through a questionnaire survey. An evaluation index for the development level of advanced manufacturing clusters is constructed, and a structural equation model is used to identify key influencing factors and governance pathways.

This paper reveals that factors such as industrial foundation, technological innovation capability, social institution environment and government policies have a significant positive impact on the development of digital innovation ecosystem in advanced manufacturing clusters. It constructs a governance model for the digital innovation ecosystem and proposes three major pathways: integration of heterogeneous innovation resources, enhancement of digital capabilities, and fostering digital collaborative governance. The crucial role of digital technology in improving data processing efficiency, optimizing resource allocation and promoting collaboration among entities is emphasized. These pathways can optimize resource allocation, boosting the competitiveness and innovation capacity of clusters.

By incorporating advanced manufacturing clusters into the digital innovation ecosystem framework, this paper enriches theoretical research on both fronts. It offers specific governance pathways and policy recommendations, providing valuable references and guidance for promoting the digital transformation and ecosystem construction of manufacturing clusters.

The present paper aims at the identification of the critical variables of risk-based auditing (RBA). The variables under examination are the internal audit (IA), the audit committee (AC) and the cooperation between the RBA and the stakeholders (audit committee, external auditors, internal auditors, board of directors, fraud investigators, chief risk manager) (COOP).

A questionnaire survey was conducted among 176 Greek companies. The questionnaires were addressed to accountants, internal auditors, managers, chief risk managers and the board of directors. A total of 96 questionnaires have been collected and analyzed. PLS-SEM modeling was used as a tool to test hypotheses and analyze the findings.

The results show that three variables, i.e. the internal audit, the audit committee and the RBA cooperation with stakeholders have a statistically significant and positive effect on risk-based auditing (RBA). Additionally, the existence of partial-complementary mediation of the internal audit in the audit committee-RBA interaction is confirmed.

This study is an original research that identifies the essential variables of risk-based auditing in Greek companies. It attempts to analyze the perceptions of all stakeholders in risk-based auditing, including the internal audit, the audit committee, etc. and is not restricted only on internal auditors. Furthermore, the analysis is conducted with PLS-SEM Modeling, which is an innovative tool of testing hypotheses and analyzing results.