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The purpose of this paper is to build a novel data envelopment analysis (DEA) model to evaluate the efficiencies of decision making units (DMUs).

Using the Choquet integrals as aggregating tool, the authors give a novel DEA model to evaluate the efficiencies of DMUs.

It extends DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form. At last, the authors use the numerical examples to illustrate the performance of the proposed model.

The proposed DEA model can be used to evaluate the efficiency of the DMUs with multiple interactive inputs and outputs.

This paper introduce a new DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form.

Saturated core type superconducting fault current limiter (SFCL) can effectively limit the short-circuit current in power system. However, the high induced voltage will occur between the terminals of DC superconducting bias winding caused by the variation of magnetic flux linked by DC winding due to the increasing short-circuit current. The DC source may be damaged. Thus, the induced voltage should be considered in DC winding design. The paper aims to discuss these issues.

Three-dimensional finite element method coupled with electric circuit.

The short-circuit current flowing through AC windings and induced voltage of DC winding are analyzed by using three-dimensional finite element method coupled with electric circuit for a 220-kV three-phase SFCL. Several circuit elements, such as a capacitor connected with DC winding in parallel, an additional short-circuit winding wound around DC core column and an energy-released piezoresistor, are, respectively, used for induced voltage reduction. These methods aim to save magnetic coupled energy in DC winding, or oppose the variation of magnetic flux, or limit the voltage of DC winding by using a resistor with low resistance.

The different methods for reduction of induced voltage of superconducting DC winding are studied and discussed. The decreased induced voltage may benefit the safety of superconducting DC winding and the source.

Involvement plays a crucial role in understanding consumer behavior. In recent years, the concept of social innovation has gained momentum, resulting in the development of eco-friendly products and initiatives to tackle societal issues. This trend is driven by consumers, who are increasingly aware of the social benefits of the products they buy. The present study aims to investigate how socially innovative, environmentally conscious consumers can influence their engagement with eco-friendly products.

Researchers aimed to investigate the “impact of social innovation on involvement in environmentally friendly products.” They selected active members of various environmental organizations operating in the country to conduct the study. Convenience sampling was used to reach out to these members, and the managers of these organizations sent an electronic questionnaire to all members' email addresses.

The study found that socially innovative, environmentally conscious consumers tend to be more interested in the symbolic meaning and pleasure of products, leading to a decrease in perceived risk and risk importance.

There are limited studies examining the relationship between social innovation and product innovation. Therefore, the novelty of this research lies in its exploration of the relationship between these two concepts. Unlike previous studies, this research found a negative relationship between the dimensions of risk importance and risk probability. This result was interpreted as environmentally friendly products being sensitive to public welfare and not being perceived as risky by environmentalists.

To endure and cope in the rapidly changing environment, it is required of firms to gain a deeper acquisition of knowledge on market dynamics and subsequently concentrate on corporations' capacity to create, restructure and integrate their internal and external competences. Hence, the objective of this study is to investigate the influence of eco-dynamic capability (EDC) on the sustainability performance of small and medium-sized enterprises (SMEs).

Structured questionnaires were used to obtain primary data. The data were solicited from 500 employees and owner-managers of SMEs. The study’s hypotheses were tested using standard multiple regression through IBM SPSS Statistics (version 24).

The study revealed that EDC has a substantial positive effect on the economic, social and environmental sustainability performance dimensions.

The focus of this study is on EDC. Thus, although dynamic capability has been the subject of substantial study, little is known regarding the effect of EDC on the economic sustainability performance (ESP) (financial), environmental sustainability performance (ENSP) and social sustainability performance (SSP) of SMEs, predominantly amongst SMEs in emerging economies.

Based on the dynamic capability theory, our study tries to explore the mediator mechanism of service supply chain dynamic capability between market orientation and service innovation performance, as well as the boundary conditions in which service supply chain dynamic capability plays a role, in order to reveal the key elements and their mechanisms for manufacturing enterprises to improve service performance.

With a total of 317 valid questionnaires, structural equation modeling (SEM) was used to test the research model and hypotheses.

The empirical results confirm that the three types of service supply chain dynamic capability (environment insight capability, resource integration capability and resource reconfiguration capability) can partially mediate the relationship between firm market orientation (responsive and proactive market orientations) and service innovation performance. In addition, supply chain collaboration has different types of moderator effects on the relationship between the three types of service supply chain dynamic capability and service innovation performance.

This research discovers that market orientation and dynamic capability are the key factors leading to high service performance and reveals the mediating role of service supply chain dynamic capability between market orientation and service innovation performance. Moreover, this research explores the moderating role of supply chain collaboration in service supply chain resource reconfiguration capability and service innovation performance.

The green innovation behavior of construction enterprises is the key to reducing the construction industry's carbon emissions and realizing the green transformation of the construction industry. The purpose of this study is to reveal the evolutionary mechanism of green innovation behavior in construction enterprises.

This study is based on resource-based theory, Porter's hypothesis and signaling theory. First, a measurement model of the green innovation behavior of construction enterprises was constructed from three aspects: environmental regulation, enterprise resources and public opinion through hierarchical analysis. Then, the state values of the measurement model of green innovation behavior of construction enterprises were calculated through the time series data from 2011–2018. Finally, the Markov chain model was used to predict the evolutionary trend of green innovation behavior of construction enterprises, and the accuracy of the prediction effect of the Markov chain model was verified using the time series data of 2019.

The Markov chain model of green innovation behavior of construction enterprises constructed in this study has high accuracy. This model finds that the transition of the growth state of green innovation behavior in China's construction industry is fluid and predicts the evolution trend of the innovation behavior of construction enterprises. In the future, the green innovation behavior of construction enterprises has a probability of 70.17% to be in a continuous growth state and 40.27% to be in a rapid growth state.

Based on the Markov chain model of green innovation behavior of construction enterprises, this study finds that the transition of the growth state of green innovation behavior of construction enterprises in China has the characteristics of liquidity. In addition, it reveals the development process of the green innovation behavior of construction enterprises from 2011–2018 and predicts the evolution trend of the green innovation behavior of construction enterprises.

This study attempts to explore the linkages between reliable big and cloud data analytics capabilities (RB&CDACs) and the comparative advantage (CA) that applies in the manufacturing sector in the countries located in North Africa (NA). These are considered developing countries through generating green product innovation (GPI) and using green process innovations (GPrLs) in their processes and functions as mediating factors, as well as the moderating role of data-driven competitive sustainability (DDCS).

To achieve the aim of this study, 346 useable surveys out of 1,601 were analyzed, and valid responses were retrieved for analysis, representing a 21.6% response rate by applying the quantitative methodology for collecting primary data. Convergent validity and discriminant validity tests were applied to structural equation modeling (SEM) in the CB-covariance-based structural equation modeling (SEM) program, and the data reliability was confirmed. Additionally, a multivariate analysis technique was used via CB-SEM, as hypothesized relationships were evaluated through confirmatory factor analysis (CFA), and then the hypotheses were tested through a structural model. Further, a bootstrapping technique was used to analyze the data. We included GPI and GPrI as mediating factors, while using DDCS as a moderated factor.

The empirical findings indicated that the proposed moderated-mediation model was accepted due to the relationships between the constructs being statistically significant. Further, the findings showed that there is a significant positive effect in the relationship between reliable BCDA capabilities and CAs as well as a mediating effect of GPI and GPrI, which is supported by the proposed formulated hypothesis. Additionally, the findings confirmed that there is a moderating effect represented by data-driven competitive advantage suitability between GPI, GPrI and CA.

One of the main limitations of this study is that an applied cross-sectional study provides a snapshot at a given moment in time. Furthermore, it used only one type of methodological approach (i.e. quantitative) rather than using mixed methods to reach more accurate data.

This study developed a theoretical model that is obtained from reliable BCDA capabilities, CA, DDCS, green innovation and GPrI. Thus, this piece of work bridges the existing research gap in the literature by testing the moderated-mediation model with a focus on the manufacturing sector that benefits from big data analytics capabilities to improve levels of GPI and competitive advantage. Finally, this study is considered a road map and gaudiness for the importance of applying these factors, which offers new valuable information and findings for managers, practitioners and decision-makers in the manufacturing sector in the NA region.

This study provides an integrative model that facilitates green product innovation (GPI) by adopting dynamic capabilities theory and the motivation-opportunity-ability (MOA) framework. Drawing on dynamic capabilities theory, this study emphasizes green supply chain integration (GSCI), consisting of internal and external integration, as a dynamic capability that drives GPI. Moreover, this study analyzes the environmental conditions that benefit the development of dynamic capabilities using the MOA framework and focuses specifically on government support (GS) and market greenness (MG) as precursors to GSCI.

Survey data were collected from 300 Chinese manufacturing firms. The proposed hypotheses were tested using hierarchical multiple regression analysis.

The regression analysis reveals that (1) GS and MG positively affect both internal and external integration and (2) internal and external integration positively affect GPI.

In explicating a model of GPI, this study extends the theoretical lens of dynamic capabilities beyond the intraorganizational level to the supply chain level. Moreover, this study enhances the understanding of dynamic capability development by considering the environmental conditions that represent motivation- and opportunity-based drivers of GSCI.

Prior research on green innovation has shown that institutional pressure stimulates enterprises to adopt green innovation. However, an institutional perspective does not explain why firms that face the same amount of institutional pressure execute different environmental practices and innovations. To address this research gap, the authors linked institutional theory with upper echelons theory and organization performance to build a comprehensive research model.

A total of 800 questionnaires were issued. The final usable questionnaires were 195, yielding a response rate of 24.38%. AMOS 23.0 was used to analyze the data and examine the relationships between the constructs in our model.

Institutional pressures affected both green innovation adoption (GIA) and the top management team's (TMT's) response. TMT's response influenced GIA. GIA was an important factor affecting firm performance. Furthermore, TMT's response mediated the relationship between institutional pressure and GIA. Institutional pressures indirectly affected green innovation performance but did not influence economic performance through GIA. Finally, TMT's response indirectly impacted firm performance through GIA.

The authors draw on institutional theory, upper echelons theory, and a performance-oriented perspective to explore the antecedents and consequences of GIA. This study has interesting implications for leaders and managers looking to implement green innovation and leverage it for firm performance to out compete with market rivals as well as to make the changes in collaboration with many other companies including market rivals to gain success in green innovation.

This study attempts to examine the relationship between reliable big and cloud data analytics capabilities (RB&CDACs) and comparative advantages (CA) of manufacturing firms (MFs) in the Middle East region as developing countries using green product innovation (GPI) and green process innovations (GPrI) mediating factors, further assess the role of data-driven competitive sustainability factor as a moderated factor.

436 useable online surveys were analyzed using the quantitative approach for the data-gathering process, applying structural equation modeling in the Smart-PLS program as an analysis tool. The sample unit for analysis included all middle- and senior-level managers and employees within MFs. The authors performed convergent validity and discriminant validity tests, bootstrapping also was applied. The authors included GPI and GPrI as mediating factors while using data-driven competitive sustainability as a moderated factor.

The findings of this study indicated that there is a positive significant effect in the relationship between reliable big and cloud data analytics capabilities and comparative advantages, which is supported by the formulated hypothesis. Furthermore, the findings confirmed that there was a positive and significant effect through the mediating factors (i.e. GPI and GPrI) on comparative advantage, additionally, it confirmed and supported that the moderating factor represented by data-driven competitive advantage suitability has significant effect as well.

This study has some limitations represented by using only one type of methodological approach (i.e. quantitative), further, it was conducted on only Asian countries in the Middle East region.

This piece of work improved the proposed conceptual research model and included several factors such as reliable big and cloud data analytics capabilities, comparative advantage, data-driven competitive sustainability, GPI and GPrI. This research offered new and valuable information and findings for managers, practitioners and decision-makers in the MFs in the Middle East region as a road map and gaudiness for the importance to apply these factors in their firms for enhancing the comparative advantages in their firms. Further, this research fills the gap in SCM literature and makes a bridge of knowledge and contribution to the existence of previous studies.