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The purpose of this study is to evaluate and address the energy efficiency prevalent within the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) countries, a diverse group that constitutes a significant portion of the global gross domestic product. By assessing energy efficiency, the study aims to inform strategies that foster sustainable economic growth and environmental sustainability within these nations.

This research uses a three-stage slacks-based measure data envelopment analysis (SBM-DEA) model, enhanced by stochastic frontier analysis (SFA), to assess the energy efficiency of CPTPP countries over the period from 2000 to 2015. The three-stage SBM-DEA model allows for a comprehensive analysis by first measuring energy efficiency, then adjusting for external environmental factors and statistical noise through SFA, and finally, reevaluating efficiency with adjusted inputs.

The analysis reveals significant disparities in energy efficiency among CPTPP nations, identifying both high-performing countries and those needing considerable improvements. Developed countries within the CPTPP generally exhibit higher energy efficiency levels, which can be attributed to their adoption of advanced technologies and strong policy frameworks. In contrast, developing nations demonstrate greater vulnerability to external environmental factors affecting their energy efficiency.

The research fills a gap in the literature by providing a nuanced and comprehensive evaluation of energy efficiency across a significant and economically diverse group of nations, offering valuable insights for sustainable development within the CPTPP framework.

Today’s one of the most important difficulties is tackling climate change and its effects on the environment. The Paris Agreement states that nations must balance the amount of greenhouse gases they emit and absorb until 2050 to contribute to the mitigation of greenhouse gases and to support sustainable development. According to the agreement, each country must determine, plan and regularly report on its contributions. Thus, it is important for the countries to predict and analyze their net zero performances in 2050. Therefore, the aim of this study is to evaluate European Continent Countries' net zero performances at the targeted year.

The European Continent Countries that ratified the Paris Agreement are specified as decision making units (DMUs). Input and output indicators are specified as primary energy consumption, freshwater withdrawals, gross domestic product (GDP), carbon-dioxide (CO₂) and nitrous-oxide (N₂O) emissions. Data from 1980 to 2019 are obtained and forecasted using autoregressive integrated moving average (ARIMA) until 2050. Then, the countries are clustered based on the forecasts of primary energy consumption and freshwater withdrawals using k-means algorithm. As desirable and undesirable outputs arise simultaneously, the performances are computed using Pure Environmental Index (PEI) and Mixed Environmental Index (MEI) data envelopment analysis (DEA) models.

It is expected that by 2050, CO₂ emissions of seven countries remain constant, N₂O emissions of seven countries remain stable and five countries’ both CO₂ and N₂O emissions remain constant. While it can be seen as success that many countries are expected to at least stabilize one emission, the likelihood of achieving net zero targets diminishes unless countries undertake significant reductions in emissions. According to the results, in Cluster 1, Turkey ranks last, while France, Germany, Italy and Spain are efficient countries. In Cluster 2, the United Kingdom ranks at last, while Greece, Luxembourg, Malta and Sweden are efficient countries.

In the literature, generally, CO₂ emission is considered as greenhouse gas. Moreover, none of the studies measured the net-zero performance of the countries in 2050 employing analytical techniques. This study objects to investigate how well European Continent Countries can comply with the necessities of the Agreement. Besides CO₂ emission, N₂O emission is also considered and the data of European Continent Countries in 2050 are estimated using ARIMA. Then, countries are clustered using k-means algorithm. DEA models are employed to measure the performances of the countries. Finally, forecasts and models validations are performed and comprehensive analysis of the results is conducted.

This study aims to employ the componential theory and interactionist perspective of creativity to explore how cognitive and affective transformations foster creativity. It investigates the influence of dispositional factors (cultural intelligence, ambiguity tolerance, social awareness) and contextual factors (international learning experiences) on students’ self-efficacy and subsequently on creative process engagement (CPE). Additionally, it examines the moderating role of cultural distance in the relationship between self-efficacy and CPE.

A survey was conducted with 1,829 Indonesian students involved in international student mobility (ISM). The hypotheses were tested using partial least square structural equation modeling.

The study found that dispositional factors (cultural intelligence, ambiguity tolerance, social awareness) and the contextual factor of international learning experience significantly enhance self-efficacy. In turn, self-efficacy significantly promotes creative process engagement. Specifically, self-efficacy fully mediates the relationships between cultural intelligence and CPE, as well as international learning experience and CPE. It also partially mediates the relationships between ambiguity tolerance and CPE, and social awareness and CPE, with both being complementary mediations. However, cultural distance did not moderate the relationship between self-efficacy and CPE.

This study addresses the research gap by focusing on creativity as a process in the context of ISM. By integrating a comprehensive perspective of creativity, this study provides new insights into how dispositional and contextual factors interact to shape self-efficacy and creative engagement, especially in the context of emerging economies such as Indonesia. The findings underscore the importance of self-efficacy in fostering creative engagement among university students who experience ISM and offer valuable implications for educational practices and policies aimed at enhancing creativity in higher education.

Knowledge is a vital strategic resource for multinational enterprises (MNEs). As MNEs expand internationally, knowledge transfer through expatriates is a crucial part of the value proposition of outward foreign direct investment. However, this is undermined if knowledge is hidden rather than shared. Given the scarcity of research on knowledge hiding in MNEs, this paper aims to investigate this phenomenon among expatriates and develops a new framework to analyze knowledge hiding.

Survey data from 201 Chinese MNE expatriates is collected and analyzed using Partial Least Squares – Structural Equation Modeling to test the relationships between knowledge hiding, organizational practices, cultural intelligence and job embeddedness. Relevant organizational practices based on the ability-motivation-opportunity enhancing framework were identified, based on 24 semi-structured qualitative interviews which guided the quantitative analysis.

The direct effects of organizational practices on all types of knowledge hiding are limited. However, organizational practices’ influence on knowledge hiding is mediated by the cultural intelligence of expatriates, and this relationship is moderated by job embeddedness.

The research advances current thinking about knowledge management and outlines both theoretical and practical implications at organizational and societal levels. It explores the mechanisms for remedying knowledge hiding through organizational practices, including the interactive effects of cultural intelligence and job embeddedness among expatriates. Organizational knowledge management strategies in MNEs need to recognize cultural differences and improve job embeddedness to form the basis of successful knowledge transfer.

This study intends to explore whether green transformational leadership is effective in promoting employee green performance. What role do moral reflectiveness and green crafting play in the impact of green transformational leadership on employee green performance?

This study collected research data from a series of questionnaire surveys using a multisource and time-lagged design. We collected 582 completed questionnaires from 97 groups in chemical firms.

The analysis showed that (1) green transformational leadership positively affected employee green performance and (2) moral reflectiveness and green crafting sequentially mediated the relationship between green transformational leadership and employees’ green performance.

The 2-1-1 multilevel mediation model clarified how the perspectives of leaders and employees are associated, confirming that green transformational leadership successfully promotes the green performance of subordinates through value communication and resource provision. Chemical companies need green transformational leaders passionate about environmental issues to encourage employee engagement in sustainability initiatives, ultimately enhancing employees’ green performance and achieving sustainable development of the chemical organization.

Financial misappropriation is a significant challenge to China’s innovation-driven growth model. This paper investigates the impact of regional-level financial misappropriation on innovation efficiency across 30 provinces and administrative municipalities in China.

The paper uses the Data Envelopment Analysis method to estimate the innovation efficiency at regional level, then, employs panel Tobit and indirect-transmission-channel models to analyze the direct and indirect impact of financial misappropriation on regional innovation efficiency in China.

The findings of the paper suggest that financial misappropriation significantly reduces regional innovation efficiency in China both directly and indirectly. Financial misappropriation hinders the transformation of scientific and technological achievements and, at the same time, it retards high-tech industrial development.

The research adopted the non-parametric approach over the parametric approach due to limitations of data availability. Both approaches have their own criticisms. However, the focus in this generates the efficiency scores that could be used for the analysis principal question of this research.

The results show if the innovation efficiency issues are not addressed at regional levels the national efficiency objecting may achieve suboptimal results.

The benefits of innovation may not flow on to regional economies creating social disparity.

This paper is the first of its nature empirically testing the direct and indirect effects of financial misappropriation on regional innovation efficiency in China by using regional financial corruption data of 30 Chinese provinces and administrative cities.

This paper examines the influence of geopolitical tensions—operationalized as political divergence between governments—on firms’ foreign supply bases and the resulting effects on supply base complexity and sub-tier supplier sharing.

The authors conduct panel data regression analyses over the period 2003–2019 to investigate whether political divergence affects foreign supply bases for 2,858 US firms sourcing from 99 countries and to examine how political divergence exposure impacts the supply network structures of 853 US firms.

Firms reduce their supply bases in countries exposed to heightened geopolitical tensions. These supply chain adjustments are associated with increased supply base complexity and greater sub-tier supplier sharing.

This study highlights the importance of state relations in global supply chain reconfiguration. Political divergence between governments provides a dual-view of political risk (i.e. buyer–supplier countries), which can help firms anticipate geopolitical disruptions. While reducing supply bases in foreign countries facing heightened geopolitical tensions is intended to mitigate disruptions, these supply base adjustments are linked to increased supply base complexity and sub-tier supplier sharing, thereby exposing firms to other types of supply disruptions. Additionally, this research contributes to understanding the effects of geopolitical tensions on supply base complexity through the lenses of transaction cost economics and resource dependence theory.

This study proposes an integrated Machine Learning and simulated framework for a personalized learning system. This framework aims to improve the integrity of the provided tasks, adapt to each student individually and ultimately enhance students' academic performance.

This methodology comprises two components. (1) A simulation-based system that utilizes reinforcement algorithms to assign additional questions to students who do not reach pass grade thresholds. (2) A Machine Learning system that uses the data from the system to identify the drivers of passing or failing and predict the likelihood of each student passing or failing based on their engagement with the simulated system.

The results of this study offer preliminary evidence of the effectiveness of the proposed simulation system and indicate that such a system has the potential to foster improvements in learning outcomes.

As with all empirical studies, this research has limitations. A simulation study is an abstraction of reality and may not be completely accurate. Student performance in real-world environments may be higher than estimated in this simulation, reducing the required teacher support.

The developed personalized learning (PL) system demonstrates a strong foundation for improving students' performance, particularly within a blended learning context. The findings indicate that simulated performance using the system exhibited improvement when individual students experienced higher learning benefits tailored to their needs.

The research offers evidence of the effectiveness of personalized learning systems and highlights their capacity to drive improvements in education. The proposed system holds the potential to enhance learning outcomes by tailoring tasks to meet the unique needs of each student.

This study contributes to the growing literature on personalized learning, emphasizing the importance of leveraging machine learning in educational technologies to enable precise predictions of student performance.

The aim of this research is to examine the effect of corporate sustainability performance on financial performance and the role of agency costs and business risk in determining this effect.

This study uses the data of 83 non-financial Turkish firms listed on Istanbul Stock Exchange during the period 2014–2021. Two-step system GMM models are applied to examine the study’s hypotheses.

The results indicate a positive effect of corporate sustainability performance on financial performance, and that this effect is significant only for firms that are more likely to suffer agency costs of equity, firms with R&D expenditures and firms with lower business risk.

The results of this study confirm the importance of regulations introduced by regulators to support the sustainability initiatives for firms that have less ability to access funds required for their investments. In addition, the findings provide important insight into the role of the persistence of corporate sustainability performance in enhancing financial performance through mitigating managers' opportunistic behavior.

To the author’s knowledge, this research is one of few that examine the effect of agency costs and business risk on the corporate sustainability–financial performance relationship in emerging markets.

Prioritising economic, environmental and social requirements of society has become imperative for attaining a competitive edge in the global marketplace. This study examines how internal and external factors influence sustainable strategic orientations of Chinese small technology enterprises. It uses an initial framework grounded in institutional theory and resource-based view (RBV).

The study surveyed small technology enterprises using quantitative techniques. A combination of partial least squares structural equation modelling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) was used to analyse 402 valid samples with statistical significance.

The PLS-SEM results show that absorptive capacity, innovation culture and coercive pressure positively influence small enterprises’ sustainability orientation. Additionally, the fsQCA method identifies five complex combinations of causal antecedents that can facilitate small enterprises’ adoption of sustainability orientation.

The findings reaffirm the importance of maintaining ideal environmental cognition and external institutional pressure. Specifically, enterprises need to strategically allocate their limited resources to optimal levels and combinations to achieve sustainability orientation.

This study enhances the understanding of sustainability orientation by integrating the RBV and institutional theory, highlighting various factors that promote sustainability at the firm level. Furthermore, asymmetric research perspectives show the triggers of sustainability orientation from both symmetrical and asymmetrical perspectives. Set theory approaches represent a pioneering approach that captures the intricacies of sustainability orientation, advancing beyond previous variance-based findings by providing optimal mix solutions.