Search results

In the context of the digital age, this study aims to investigate the impact of citizens' digital participation on the scientific and democratic decision-making processes of the government. Specifically, the authors focus on the factors influencing citizens' digital participation, with a particular emphasis on their digital skills.

Exploring the influence of citizens' digital skills on their digital participation is of great practical significance for eliminating the digital divide and for promoting a life characterized by enriched digital interactions with the public. This study selected the social consciousness survey database of Chinese netizens in 2017, used ordered Probit and OLS models, and comprehensively used the instrumental variable method (IV), causal stepwise regression method and bootstrap method to empirically verify and construct a mechanism model of the influence of digital skills on citizens' digital participation.

The empirical findings indicate a noteworthy positive association between citizens' proficiency in digital skills and their active engagement in digital activities. This relationship is positively mediated by factors such as political interest and attention to social issues, underscoring their role in encouraging greater digital participation. Conversely, national identity exhibits a counteractive influence on this mechanism, potentially discouraging digital engagement. Notably, the impact of digital skill mastery on digital participation is more pronounced among non-elderly individuals and those residing in metropolitan areas, highlighting the significance of demographic characteristics in this context.

These research results can help the government and other organizations make better decisions and facilitate improvement of citizens' digital participation by promoting their mastery of digital skills.

The primary aim of this study is to examine the decision-making process of a reverse supply chain within a cooperative-competitive environment, with a particular emphasis on the incorporation of Internet of Things (IoT) technology in the recycling process.

The impact of IoT on recycling effectiveness, RF (refurbished) product demand and remanufacturing expenses is analyzed. The game-theoretic models are constructed to incorporate the co-competitive relationship between a IR (Internet Recycler) and a remanufacturer, with specific attention paid to the IR's application of IoT technology.

The results indicate that the use of IoT reduces the costs associated with remanufacturing, leading to an increase in the transfer price of pre-owned items procured from IRs. The efficacy of the reverse supply chain depends not only on its cost-saving capabilities but also on consumer preferences toward RF and remanufactured (RM) items.

IoT technology can benefit Internet recycling and remanufacturing by enhancing transparency, quality monitoring and automation of processes. It can also help reduce operating costs, improve customer engagement and incentivize cooperation between organizations.

This study examined the strategic decision-making processes in the context of cooperation and competition between IR and remanufacturers. In addition, this research makes a valuable contribution to the literature by elucidating the optimal conditions for the effective implementation of Internet of Things (IoT) technology in recycling operations.

Establishing and developing digital science and education evaluation platforms (DSEEPs) have several practical implications for the development of China's science, technology and education. Identifying and analyzing the key factors influencing DSEEP user experience (UX) can improve the users' willingness to use the platform and effectively promote its sustainable development.

First, a literature survey, a five-element model of UX and semi-structured interviews were used in this study to develop a DSEEP UX-influencing factor model, which included five dimensions and 22 influencing factors. Second, the model validity was verified using questionnaire data. Finally, the key influencing factors were identified and analyzed using a fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) method.

Fourteen influencing factors, including diverse information forms and comprehensive information content, are crucial for the DSEEP UX. Its optimization path is “‘Function Services’ → ‘Information Resources’ → ‘Interaction Design’ → ‘Interface Design’ and ‘Visual Design’.” In this regard, platform managers can take the following measures to optimize UX: strengthening functional services, improving information resources, enhancing the interactive experience and considering interface effects.

This study uses a combination of qualitative and quantitative research methods to determine the key influencing factors and optimization path of DSEEP UX. Optimization suggestions for UX are proposed from the perspective of platform managers, who provide an effective theoretical reference for innovating and developing a DSEEP.

The desire of international retail brands to implement sustainable supply chain practices in the fashion value chain and improve suppliers' sustainability efforts; this research paper elucidates the relationship between blockchain technology and sustainability to impact apparel firms' triple bottom line.

For studying the impact of sustainable supply chain practices on the triple bottom line, a survey questionnaire was chosen and sent out to 500 garment companies simultaneously, of which 371 responded. The data collected is cross-sectional. The questionnaire survey was developed keeping in mind a few demographic elements such as experience, age and qualification to generalize the findings. For analysis, SmartPLS is used to run model structuring and regression analysis.

Test runs on model structure confirm the instrument's validity and reliability. Bootstrapping on the theoretical model to test developed hypotheses suggests that supply chain sustainability practices positively affect social, environmental and economic performance in a direct relationship. Further, indirect relation testing conducted to test blockchain technology's moderation influences only the constructs' relations.

The clubbing of sustainable supply chain practices and blockchain technology is a novel idea in the apparel industry; however, there are more constructs in the context of practice-based theory and supply chain which impact firm performance. Also, the research limits itself from discussing IT infrastructure and smart contract types that impact the technology's performance.

The study provides a framework for interpreting the synergetic influence of SSCP on firm social, environmental and economic performances, which is demanded both by consumers and regulators in an industry. The results suggest that managers sustainably design the production ecosystem, thus eliminating any discrepancy or slackness in the complete chain. Usually, suppliers are ignored, which are precursors in implementing SSCP.

The paper studies sustainability problems through ecological modernization theory and practical-based theory giving a unique perspective on the issue faced by the apparel industry and combining sustainable supply chain practices and blockchain.

A rapid increase in traditional industries is creating social and environmental problems through extensive usage of natural resources and polluting the environment. A circular economy provides curative and renewing lines of action about these problems. Therefore, this study aims to examine the factors that lead toward sustainable performance in a circular economy context and empirically test the relationships between green technology adoption (GTA), circular economy principles (CEP), sustainable supply chain practices (SSCM) and sustainable performance (SP).

Using the well-developed governmental databases, data from 435 small and medium enterprises (SMEs) in the textile sector of Pakistan were collected and tested through AMOS using a structural equation model.

The results disclosed that GTA, CEP and SSCM have significant and positive direct relationships and facilitate improving SMEs’ SP. Circular economy entrepreneurship (CEE) and customer pressure (CP) were found to have a significant and positive influence on the relationships of GTA and CEP with SSCM.

The role of GTA in circular economy and the moderating effect of CEE and CP is an addition to the literature. SMEs’ GTA allows them to reuse, reduce and recycle natural resources rather than obtain new ones from the ecosystem.

This study investigates the integration of information technology (IT) competencies with organizational inclusion initiatives and its impact on firm performance. It examines the role of organizational inclusion in promoting knowledge management capability (KMC) and the moderating effect of approach and avoidance motivation on the relationship between KMC and operational performance.

The study is grounded in the resource orchestration theory (ROT), which conceptualizes the integration of IT competencies and organizational inclusion. It employs hierarchical regression analysis on data collected from 204 firms and 374 managerial respondents to test the proposed hypotheses.

The results indicate that IT competencies enhance the relationship between organizational inclusion and KMC. Additionally, the relationship between KMC and operational performance is weaker when employees exhibit higher levels of avoidance motivation.

This study offers theoretical and managerial insights for integrating IT competencies into organizational inclusion initiatives, providing guidance for organizations seeking to enhance their performance, with a specific focus on the relevance of China as the research context.

This study enriches the scholarly discourse by examining the underexplored integration of IT competencies with organizational inclusion, notably in the context of China. It illuminates the moderating role of motivation in the KMC-operational performance relationship, benefiting both academia and practitioners. Furthermore, this work extends the literature by demonstrating how combining organizational inclusion and IT competencies can enhance workplace KMC, connecting it to internal knowledge resources. Theoretical implications extend beyond organizational inclusion and IT to show the broader application potential of ROT in management and information systems.

Government organizations often store large amounts of data and need to choose effective data governance service to achieve digital government. This paper aims to propose a novel multi-attribute group decision-making (MAGDM) method with multigranular uncertain linguistic variables for the selection of data governance service provider.

This paper presents a MAGDM method based on multigranular uncertain linguistic variables and minimum adjustment consensus. First, a novel transformation function is proposed to unify the multigranular uncertain linguistic variables. Then, the weights of the criteria are determined by building a linear programming model with positive and negative ideal solutions. To obtain the consensus opinion, a minimum adjustment consensus model with multigranular uncertain linguistic variables is established. Furthermore, the consensus opinion is aggregated to obtain the best data governance service provider. Finally, the proposed method is demonstrated by the application of the selection of data governance service provider.

The proposed consensus model with minimum adjustments could facilitate the consensus building and obtain a higher group consensus, while traditional consensus methods often need multiple rounds of modifications. Due to different backgrounds and professional fields, decision-makers (DMs) often provide multigranular uncertain linguistic variables. The proposed transformation function based on the positive ideal solution could help DMs understand each other and facilitate the interactions among DMs.

The minimum adjustment consensus-based MAGDM method with multigranular uncertain linguistic variables is proposed to achieve the group consensus. The application of the proposed method in the selection of data governance service provider is also investigated.

This study aims to investigate the relationships between the perceived neighborhood walkable environment (PNWE), neighborhood interaction (NI) and residents’ mental health, with a focus on examining differences among residents of different age groups.

Using an electronic survey questionnaire, data on PNWE, NI and mental health were collected from 1,159 residents across 205 communities in Shanghai, China. Our study utilized a structural equation modeling (SEM), employing the maximum likelihood estimation method. The structural equation model was fitted using the MPLUS software.

The mental health of young and middle-aged adults is generally poor, and they are at higher risk of depression than children and older adults. The effects of PNWE and NI on the mental health of residents varied among different age groups. As residents get older, their mental health is more affected by the PNWE. In addition, the influence of the PNWE on children and older adults’ mental health is direct and not mediated by NI. For young and middle-aged adults, the influence of the PNWE on their mental health needs to be mediated by NI.

This study marks the first examination of the relationship between PNWE, NI and mental health among different age groups of residents in China. The findings of this research can assist policymakers in gaining a deeper understanding of the underlying mechanisms by which PNWE affects mental health. Furthermore, it can contribute to the development of more targeted walkable environment designs aimed at enhancing mental health among various age groups.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

This study reviews scholarly work in sustainable green logistics and remanufacturing (SGLR) and their subdisciplines, in combination with bibliometric, thematic and content analyses that provide a viewpoint on categorization and a future research agenda. This paper provides insight into current research trends in the subjects of interest by examining the most essential and most referenced articles promoting sustainability and climate-neutral logistics.

For the literature review, the authors extracted and sifted 2180 research and review papers for the period 2008–2023 from the Scopus database. The authors performed bibliometric and content analyses using multiple software programs such as Gephi, VOSviewer and R programming.

The SGLR papers can be grouped into seven clusters: (1) The circular economy facets; (2) Decarbonization of operations to nurture a climate-neutral business; (3) Green sustainable supply chain management; (4) Drivers and barriers of reverse logistics and the circular economy; (5) Business models for sustainable logistics and the circular economy; (6) Transportation problems in sustainable green logistics and (7) Digitalization of logistics and supply chain management.

In this review, fundamental ideas are established, research gaps are identified and multiple future research subjects are proposed. These propositions are categorized into three main research streams, i.e. (1) Digitalization of SGLR, (2) Enhancing scopes, sectors and industries in the context of SGLR and (3) Developing more efficient and effective climate-neutral and climate change-related solutions and promoting more environmental-related and sustainability research concerning SGLR. In addition, two conceptual models concerning SGLR and climate-neutral strategies are developed and presented for managers and practitioners to consider when adopting green and sustainability principles in supply chains. This review also highlights the need for academics to go beyond frameworks and build new techniques and instruments for monitoring SGLR performance in the real world.

This study provides an overview of the evolution of SGLR; it also clarifies concepts, environmental concerns and climate change practices, particularly those directed to supply chain management.