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Drawing upon psychological ownership theory, the aim of this study was to uncover the coexisting mediating effects of knowledge sharing and hiding on the relationship between employees’ organizational psychological ownership (OPO) and their innovative work behavior (IWB). The moderating role of organizational context in these mediating relationships was further examined to determine the moderated mediation paths.

This study mainly used a survey-based research method and collected data from 512 professionals from both public and private organizations in Pakistan to test our proposed hypotheses.

The results showed that coexisting knowledge sharing and hiding mediated the relationship between employees’ OPO and IWB. Furthermore, organizational context moderated the mediated relationships, providing support for the moderated mediation framework.

The results highlight the significance of fostering employees’ OPO to enhance their IWB by promoting knowledge sharing and preventing knowledge hiding. This study also urges managers to consider the contingency effect of organizational contexts when promoting employees’ IWB in emerging economies.

The results obtained in this study suggest that the knowledge behavior paradox occurs in organizations, and distinct organizational contexts play crucial but differential roles in intervening in the effect of employees’ OPO on their IWB. This study empirically validated this complex mechanism in an important emerging economy in Asia.

This study empirically investigates the impacts of technological innovation and operational efficiency on environmental performance and the moderating effects of environmental orientation.

We develop a conceptual framework based on the Porter Hypothesis. We collect a sample of 850 listed firms in China between 2010 and 2019. The fixed effect model was used to analyse the data.

The empirical findings reveal that technological innovation indirectly enhances environmental performance through operational efficiency and partially mediates this impact. We also find that environmental orientation strengthens the positive impacts of technological innovation and operational efficiency on environmental performance.

This study contributes to the literature by revealing that technological innovation is positively associated with operational efficiency and environmental performance, which suggests that technological innovation can simultaneously enhance business and environmental performance. Hence, this study provides empirical support for the Porter Hypothesis. The results also extend the Porter Hypothesis by revealing how technological innovation affects environmental performance and under what conditions technological innovation has a greater impact on environmental performance.

Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).

Using the dynamic simulation based on field test, stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers were tested. Stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to research the evolution law with running mileage of dynamic index of CR400BF EMU.

The results showed that stiffness and damping coefficient subjected to normal distribution, the mean and variance were computed and the evolution law of stiffness and damping coefficient with running mileage was obtained.

Firstly, based on the field test we found that stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers subjected to normal distribution, and the evolution law of stiffness and damping coefficient with running mileage was proposed. Secondly stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to the research to the evolution law with running mileage of dynamic index of CR400BF EMU.

Corporate social responsibility (CSR) is viewed as a differentiating strategy that wins over stakeholders’ confidence. Due to the potential strategic and positive effects on businesses, the study of CSR and its relationship to competitiveness has gained relevance. While studies have examined the impact of CSR activities on firm competitiveness, the findings so far remain contradictory. Further research on the underlying processes/mechanisms that explain how CSR contributes to competitiveness remains scarce. Accordingly, this study aims to look into the link between CSR and competitiveness with a focus on Asian business and management studies.

By using a bibliometric approach, this paper aims to provide a review of the state-of-the-art research on the linkage between CSR and competitiveness in Asian context. The sample for this research included all 538 studies from the period of 2001–2023 in the Scopus database. A bibliometric study included both co-occurrence and co-citation analysis.

The study’s findings made significant contributions by identifying seven distinct clusters of co-occurrences. Using co-citation, three journals-based co-citation clusters and another three authors-based co-citation clusters are identified. The findings show how processes/mechanisms such as – accountability, multi-stakeholder dialogue/engagement, resource generation, emphasizing sustainable development goals and emerging markets, redefining strategy, cultivating value/vision and CSR leadership – are increasing in importance.

Overall, the authors argue that CSR-led competitiveness is indeed one of the key drivers for improved sustainability performance of a firm.

Based on findings, a conceptual framework has been proposed highlighting different processes and mechanisms that influence the CSR-led competitiveness – outcomes relationship.

This study aims to investigate the relationship between digital financial inclusion and economic growth in specific Asian countries, emphasizing the exploration of how digital financial inclusion dynamics impact gross domestic per capita income.

The study creates a digital financial inclusion composite index (DFII) by incorporating essential metrics from the Global Findex report. Economic growth is measured using Gross Domestic Product per capita income in its natural logarithmic form (LnPCI), with three control variables– employment-to-population ratio; population growth and inflation. The analysis utilizes a fixed-effect dummy variable model to examine the relationship, considering unobserved country-specific heterogeneity. 30 Asian countries have been selected for the study for the periods 2014, 2017 and 2021 based on their availability, as outlined in Table 4.

The research revealed a robust positive correlation between the Digital Financial Inclusion Index (DFII) and logarithmic GDP per capita income (LnPCI), indicating higher per capita income with enhanced digital financial inclusion. Employment and population exhibited minimal influence, whereas inflation had a notable negative effect on per capita income. Population growth showed a limited impact. The model demonstrated a high explanatory power for the dependent variable (high R-squared), and the residuals displayed low autocorrelation (Durbin–Watson of 1.96).

This study adds to the existing literature by examining the intricate connection between digital financial inclusion (DFI) and economic growth in 30 Asian countries, employing a comprehensive composite index for analysis.