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This study presents evidence of the role of performance measurement and management (PMM) in sustainable supply chain governance. This study tests a model hypothesizing whether it is the PMM itself or the mediating effect of supply chain governance that is essential for both business and sustainability performance.

This study builds on a survey of 274 SMEs in Finland.

The findings indicate that PMM does not directly contribute to SMEs’ business or sustainability performance. Supply chain governance mediates the relationship between PMM and business performance. Business performance also enhances sustainability.

These findings can guide managers in managing company relationships with customers and suppliers. The mediating role of supply chain governance highlights the potential of PMM to enhance performance. Without supply chain governance, the PMM, while efficient in traditional business practices, may lose its effectiveness because of the pressure to advance sustainability values within firm operations.

The role of PMM in enhancing supply chain sustainability is frequently overlooked in the existing research, necessitating an empirical evaluation of PMM’s impact on supply chain sustainability. This study addresses this gap by focusing on the SME context, where the pressure to adopt sustainable practices is increasing, yet SMEs employ PMM less frequently than larger firms.

This study aims to examine the influence of big data analytics (BDA) on environmental performance (ENP) in the post-COVID-19 context in Vietnam, as a developing country. In which, this study considers environmental process integration in accounting reports as a mediator variable. Furthermore, digital learning orientation (DLO) and environmental strategy (ES) are proposed as the moderator variables for relationships in the proposed model.

Data was collected by survey method via email with convenient sampling method. In total, 611 emails, including the survey, were sent to executive managers of Vietnamese manufacturing companies listed on stock exchanges. The final sample of 419 responses was used for analysis.

By using the partial least squares structural equation modeling, this study’s results elucidate that BDA positively affects ENP. Moreover, DLO positively moderates the nexus between BDA and environmental process integration in accounting reports, while ES plays a positive moderating role on the nexus between environmental process integration and ENP.

In terms of managerial implications, this paper mentions pretty attractive features of using modern technique and ENP. This research emphasizes the key role of the BDA for both reporting and accounting performance (e.g. environmental process integration and ENP) of the company. Thus, managers should examine implementing BDA when necessary to make accounting reports more transparent and modern, thereby enhancing the organization's ENP. Particularly, managers should focus on improving the organization's ENP indicators.

This study complements the ENP literature by showing a positive effect of BDA and environmental process integration on ENP. Additionally, this study’s results determine the efficacy of DLO and ES as well as their regulatory roles. Finally, this study was conducted to supplement empirical evidence on ENP in the post-COVID-19 context in developing countries, specifically Vietnam.

This study aims to examine various factors influencing the inclination of students toward Green Entrepreneurial Intention (GEI), including University Support (USP), Family Support (FSP), Religiosity (REL), Commitment to Environment (CEN) and Green Entrepreneurial Motivation (GEM), as well as Attitude towards Green Entrepreneurship (AGM).

Data were collected through an online survey of Muslim students at Indonesian Islamic universities. A five-point Likert scale was used in the online questionnaire, with 419 processed data. Partial least squares structural equation modeling was used to analyze the data and test the relationship between the variables.

The results showed that AGM, CEN and REL impacted GEM. AGM was influenced by FSP but not by USP while GEI was significantly influenced by AGM, FSP and USP.

The limitation of the study is the composition of the sample, consisting solely of Islamic university students. Another limitation is the variables used. Future studies should analyze other factors, such as role models, green knowledge or family background.

This study provided fresh perspectives by empirically establishing a framework for assessing GEI, considering REL variables, an unexplored area conceptually. Practically, it helped to advance sustainable entrepreneurship education, particularly in Islamic universities. Accordingly, it provided several practical contributions for universities to develop curricula that better support green entrepreneurship among students.

This study represented the first investigation into the influence of REL on GEI, specifically among university students. Furthermore, Stimuli, Organism and Response theory was used as a foundation for the development of the diverse variables under investigation.

This study aims to revisit the empirical debate about the asymmetric relationship between oil prices, energy consumption, CO₂ emissions and economic growth in a panel of 184 countries from 1981 to 2020.

A relatively new research method, the PVAR system GMM, is applied.

The outcome of the PVAR system GMM model at the group level in the study suggests that oil prices exert a positive but statistically insignificant effect on economic growth. Energy consumption is inversely related to economic growth but statistically significant, and the correlation between CO₂ emissions and economic growth is negative but statistically insignificant. The Granger causality test indicates that oil prices, CO₂ emissions, oil rents, energy consumption and savings jointly Granger-cause economic growth. A unidirectional causality runs from energy consumption, savings and economic growth to oil prices. At countries’ income grouping levels, oil prices, oil rent, CO₂ emissions, energy consumption and savings jointly Granger-cause economic growth for the high-income and upper-middle-income countries groups only, while those variables did not jointly Granger-cause economic growth for the low-income and lower-middle-income countries groups. The modulus emanating from the eigenvalue stability condition with the roots of the companion matrix indicates that the model is stable. The results support the asymmetric impacts of oil prices on economic growth and aid policy formulation, particularly the cross-country disparities regarding the nexus between oil prices and growth.

From a methodological perspective, to the best of the author’s knowledge, the study is the first attempt to use the PVAR system GMM and such a large sample group of 184 economies in the post-COVID-19 era to examine the impacts of oil prices on countries’ growth while controlling for other crucial variables, which is noteworthy. Two, using the World Bank categorisation of countries according to income groups, the study adds another layer of contribution to the literature by decomposing the 184 sample economies into four income groups: high-income, low-income, upper-middle-income and lower-middle-income groups to investigate the potential for asymmetric effects of oil prices on growth, the first of its kind in the post-COVID-19 period.

The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.

This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.

According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.

In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.

Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.

Sustainable urban rail transit requires noise barriers. However, these barriers’ durability varies due to the differing aerodynamic impacts they experience. The purpose of this paper is to investigate the aerodynamic discrepancies of trains when they meet within two types of rectangular noise barriers: fully enclosed (FERNB) and semi-enclosed with vertical plates (SERNBVB). The research also considers the sensitivity of the scale ratio in these scenarios.

A 1:16 scaled moving model test analyzed spatiotemporal patterns and discrepancies in aerodynamic pressures during train meetings. Three-dimensional computational fluid dynamics models, with scale ratios of 1:1, 1:8 and 1:16, used the improved delayed detached eddy simulation turbulence model and slip grid technique. Comparing scale ratios on aerodynamic pressure discrepancies between the two types of noise barriers and revealing the flow field mechanism were done. The goal is to establish the relationship between aerodynamic pressure at scale and in full scale.

The aerodynamic pressure on SERNBVB is influenced by the train’s head and tail waves, whereas for FERNB, it is affected by pressure wave and head-tail waves. Notably, SERNBVB's aerodynamic pressure is more sensitive to changes in scale ratio. As the scale ratio decreases, the aerodynamic pressure on the noise barrier gradually increases.

A train-meeting moving model test is conducted within the noise barrier. Comparison of aerodynamic discrepancies during train meets between two types of rectangular noise barriers and the relationship between the scale and the full scale are established considering the modeling scale ratio.

Given the significance of innovation in enabling firms to maintain a long-term competitive edge and secure excess profits, this paper aims to investigate whether and how stakeholders’ attention to innovation (SATI) influences corporate innovation.

This paper introduces a novel variable, SATI, which is achieved by segmenting stakeholders’ attention into two categories: attention to innovation and attention to other facets, using textual analysis methods. Subsequently, this paper empirically examines the influence of SATI on corporate innovation.

This paper finds that SATI positively affects corporate innovation input, and the result remains true after addressing possible endogeneity issues using instrumental variable regression. Furthermore, the positive effect of SATI on corporate innovation is stronger in firms facing greater financing constraints, thus verifying the financing constraints hypothesis. The positive effect is also stronger in firms with lower risk-taking levels, thus confirming the innovation failure tolerance hypothesis. Further analysis suggests that SATI increases both corporate innovation output and efficiency, thus ruling out the catering hypothesis.

This paper highlights the importance of SATI in driving corporate innovation. It enriches the literature on the repercussions of stakeholders’ attention and determinants of corporate innovation. In addition, it provides practical suggestions for further implementing China’s national innovation-driven development strategy.

The lack of a direct link between business value and sustainability is a critical roadblock to truly embedding sustainability in business strategies. Before launching the sustainability journey, every organisation should answer the question: “What value would this strategy offer our organisation?” Conversely, when organisations are opportunistic toward quick profits, the negative consequences of one domain spill over to another. The desire to produce more may result in overproduction, overconsumption or environmental pollution.

To give a complete analysis of sustainable capabilities, this study combines current theoretical understanding from past literature, followed by exploratory interviews and a thorough case study. The case study ventured into uncharted territories, unveiling an exciting new sphere of value catalysed by the mechanisms of sustainable co-creation. Additionally, it exposed thought-provoking motives driving supply chain actors’ unwavering commitment to ethical decision-making, even amidst towering challenges.

Our empirical lens reveals the hidden mechanics of resource sharing and the genesis of newfound value, illuminating previously obscure corners of the sustainability field. Moreover, it sheds light on retailers striving to cultivate green retail supply chains. It delivers an actionable framework that bolsters business sustainability and fuels competitive edge, which is vital in the rapidly evolving landscapes of emerging economies.

This study offers insights into the sustainable value-creation mechanism in ALPHA, a Malaysian retailer, uncovering how supply chain actors’ business activities generate economic, social and environmental performance.

In the era of the digital economy, the digital innovation ecosystem is an important vehicle to alleviate enterprises' resource and capability constraints and thus improve their digital innovation performance. Embedding digital innovation ecosystems for survival and development opportunities has become a new strategic choice for enterprises. However, how digital innovation ecosystem embeddedness affects the digital innovation performance of complementary enterprises has not yet been fully revealed. This study examines whether digital innovation ecosystem embeddedness affects the digital innovation performance of complementary enterprises through ambidextrous capabilities (exploration and exploitation) and the moderating role of strategic flexibility.

A field survey was conducted in China, collecting survey data from 578 complementary enterprises in advanced manufacturing industries embedded in digital innovation ecosystems. This study applies multiple regression analysis to verify the relevant hypotheses.

The results confirmed that (1) digital innovation ecosystem embeddedness has a significant positive effect on complementary enterprises' digital innovation performance; (2) Ambidextrous capabilities play a partial mediating role in the relationship between digital innovation ecosystem embeddedness and complementary enterprises' digital innovation performance. (3) Strategic flexibility positively moderates the effect of digital innovation ecosystem embeddedness on ambidextrous capabilities and digital innovation performance.

The findings, intended to guide enterprises that complement the digital innovation ecosystem to achieve digital innovation and performance improvement, highlight the importance of eco-embedded strategies, ambidextrous capabilities and strategic flexibility.

The finding enriches antecedent research on digital innovation performance and provides practical insights for firms to embed themselves in digital innovation ecosystems to improve performance.

The purpose of this study is to investigate the influence of ambidextrous strategy on supply chain resilience and its impact on firm performance, employing the Dynamic Capabilities View.

Through a survey of 215 supply chain professionals, the research employs a structural equation modeling analysis to examine the relationships between ambidexterity, agile operations, resilience, and performance.

The findings demonstrate that the ambidextrous strategy significantly enhances both agile operations and supply chain resilience. In turn, agile operations and resilience positively impact firm performance. The study also reveals that agile operations and supply chain resilience partially mediate the relationship between ambidextrous strategy and firm performance.

This research contributes to the supply chain management literature by highlighting the importance of an ambidextrous approach in fostering agile operations and resilience, thereby improving firm performance. It extends the dynamic capabilities view framework by elucidating how ambidexterity acts as a pivotal mechanism for adapting to disruptions and securing competitive advantage in volatile markets. Finally, measurements of ambidextrous strategy and resilience are provided to further enhance practitioners’ understanding of building these important components in networks.