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The importance of the agri-food supply chain in both food production and distribution has made the issue of its development a critical concern. Based on configuration theory and congruence theory, this research investigates the complex impact of supply chain concentration on financial growth in agri-food supply chains.

The cluster analysis and response surface methodology are employed to analyse the data collected from 207 Chinese agri-food companies from 2010 to 2022.

The results indicate that different combination patterns of supply chain concentration can lead to different levels of financial growth. We discover that congruent supplier and customer concentration is beneficial for companies’ financial growth. This impact is more pronounced when the company is in the agricultural production stage of agri-food supply chains. Post-hoc analysis indicates that there exists an inverted U-shaped relationship between the overall levels of supply chain concentration and financial growth.

Our research uncovers the complex interplay between supply chain base and financial outcomes, thereby revealing significant ramifications for agri-food supply chain managers to optimise their strategies for exceptional financial growth.

This study proposes a combined approach of cluster analysis and response surface analysis for analysing configuration issues in supply chain management.

A new normal regarding teaching and learning has been established after COVID-19. The present study aims to examine the effectiveness of digital technology training on developing academics’ digital competence in higher education context. A conceptual model was developed using stimulus–organism–response (SOR) theory. Additionally, this study investigates the mediating effect of transfer of learning and the moderating effect of innovative climate in the relation between trainer capability and academics’ digital competence.

In total, 24 digital technology training sessions were organized. Data were collected from the 24 digital technology training sessions with 384 participants and analyzed using SPSS PROCESS macro.

The results indicated that digital technology training content and trainer capability were positively associated with academics’ digital competence. Mediation analysis indicated that transfer of learning mediated the relation between trainer capability and digital competence. Moderated mediated analysis revealed that the relationship between trainer capability and transfer of learning is stronger under a higher innovative climate.

This study contributes to the literature by applying the SOR theory in the context of digital technology training, providing a novel theoretical perspective on how digital training influences academics’ digital competencies. The study offers empirical evidence on the underlying process regarding the effect of digital technology training on academics’ digital competence. The findings revealed that transfer of learning as well as innovative climate play important intervening roles in enhancing academics’ digital competence. Higher education institutions can implement policies to promote the transfer of learning and innovative climate, allowing academics to learn innovative digital technology.

This study examines the complex array of impediments and potential advantages of the internet of things (IoT) associated with the shift towards enabling circular economy practices (CEP), motivated by the pressing necessity to address climate change and promote environmental sustainability. Based on an extensive review of scholarly sources, this study scrutinizes the technological, economic and societal challenges that ought to be addressed to attain a net-zero economy. Most outstandingly, it emphasizes the environmentally sustainable merits, potential for economic growth and improvements in societal well-being that can arise from this transition. It further depicts selected case studies to demonstrate sustainable empirical evidence and avails policy recommendations. The paradigm is to assist governments and other stakeholders in effectively managing human-associated challenges to attain increased sustainable value maximally. Finally, this highlights the utmost significance of tackling these challenges and capitalizing on opportunities to facilitate a sustainable, net-zero future that guarantees worldwide prosperity and ecological welfare.

This study aims to explore the traditional plant dyeing of Xinjiang Atlas silk fabrics, providing references for the comprehensive utilization of plant dyes in intangible cultural heritage.

The focus of this study is on dyeing experiments of Atlas silk fabrics using safflower extracts, constrained by regional resources. Safflower dry flowers grown in Xinjiang were selected, rinsed with pure water and rubbed. Yellow pigments were removed by adding edible white vinegar. Red pigments from safflower were extracted using an alkaline solution prepared with Populus euphratica ash, a special product of Xinjiang. The extraction rate was analyzed under varying material-to-liquor ratios, pH values, times and temperatures. Direct dyeing process experiments were conducted to obtain different colorimetric L, a, b and K/S values for comparison. Samples with good color development were selected to test the impact of dyeing immersions on color development, and their color fastness, UV protection and antibacterial effects were verified.

The dyeing experiments on silk fabrics confirmed their UV protection capabilities and antibacterial properties, demonstrating effectiveness against E. coli and Staphylococcus aureus. As a major producer of safflower, Xinjiang underscores the significance of safflower as an essential plant dyes on the Silk Road. This study reveals its market potential and suitability for use in the plant dyeing process of Atlas silk, producing vibrant red and pink colors.

The experiments indicated that after removing yellow pigments, the highest extraction rate of red pigment from safflower was achieved at a pH value of 10–11, a temperature of 30°C and an extraction time of 40 min. The best bright red color effect with strong color fastness was obtained with a material-to-liquor ratio of 1:20, a temperature of 40°C and three immersions. The best light pink color effect with strong color fastness was a material-to-liquor ratio of 1:80, a temperature of 30°C and two immersions.

A review of sustainability challenges of flame retardants (FRs) for textiles has been conducted. Specifically, the purpose of this paper is to identify and recommend solutions to sustainability challenges emanating from the raw material, processing technology and performance of the FRs used for textiles.

The approach used in preparing this paper was based on the review of various scholarly databases about the subject matter. The review approach is designed to inform the readers about the sustainability challenges of FRs for textiles. The science of burning and FRs for synthetic and cellulosic fibres were reviewed. Both synthetic and natural biodegradable FRs for textiles has been identified. The obtained literature was then synthesised to get information about sustainable challenges of non-halogenated FRs both synthetic and natural biodegradable. Finally, possible approaches for mitigating the identified challenges have been recommended.

The sustainability challenges of the FRs in terms of raw material, processing, affordability and performance have been identified. Synthetic FRs suffer from sustainability challenges in terms of raw materials, processing and non-renewability. Despite the environmental friendliness and sustainability in terms of being renewability, processability and biodegradability, natural biodegradable FRs have poor performance compared to synthetic ones. Moreover, natural biodegradable FRs depend on geographical condition and lack economic variability data. Potentially, the challenges of FRs can be mitigated through eco-friendly synthesis, chemical modification and sustainable methods of applications. Because of its renewability and environmental friendliness, biodegradable FRs have a potential to becoming sustainable if researched more.

In this review, a collection of literature about sustainability challenges of FRs and the approaches to overcome the challenges has been provided. The collected information was analysed and synthesised to bring understanding of the science of burning, types and application of FRs for textiles and biodegradable FRs. Sustainability challenges have been identified, and mitigation approaches are provided.

This study examines the mediating and moderating effects of business regulatory compliance (BRC) on the association between sustainable supply chain management practices (SSCMP) and operational performance (PERFOP), and how corporate sustainability culture (CSC) serves as a boundary condition to BRC.

This research draws data from 245 firms operating in multiple industries in Ghana. Ordinary Least Square (OLS) was employed to test the direct effects, while Hayes Process Macros was employed to test the indirect and conditional effects among the study variables using a structural equation modelling approach.

The results showed that SSCMP has a direct positive effect on PERFOP. The study further revealed that BRC mediates the relationship between SSCMP and PERFOP. This study found that BRC negatively moderates the association between SSCMP and PERFOP, suggesting that high levels of BRC generate unintended adverse effect on the SSCMP- PERFOP link. However, the results revealed that CSC serves as a boundary condition to BRC.

To the best of our knowledge, this is the first study that emphasizes how the resource-based view and regulatory focus theory interact to explain how different degrees of CSC and BRC impact SSCMP performance outcomes. This study advances research in the sustainability literature, in response to calls for further research in this domain. This study draws decision-makers attention on the need to make sustainability practices an integral part of corporate culture in order to set a business tone that stimulates easy compliance to sustainability requirements.

This study aims to examine the effect of digitalization and sanitary measures during the COVID-19 pandemic on corporate social responsibility (CSR) in the African context. While CSR has traditionally been analyzed in developed markets, this paper explores how multinational subsidiaries can leverage CSR practices to create financial opportunities and market stability for themselves and their communities in Africa.

The authors use a panel of data from six listed African companies for the period ranking from January 2006–2022 to analyze the effect of financial performance (FP), digitalization and health measures on the social responsibility of these companies. The authors provide a robust test that improves the understanding of the impact of pandemics and innovation on CSR, using Machine Learning (ML) linear regression.

The results show that the social responsibility of African companies is highly dependent on FP and digitalization. On the other hand, the authors demonstrate that the moderating role of epidemic instability negatively affects social responsibility through FP, but on the other hand strengthens CSR in the presence of digitalization. The results of the initial analysis remain largely unchanged, demonstrating the validity and robustness of the empirical results through ML models. This article highlights some of the obstacles and opportunities for CSR adapted to the crisis context. The authors conclude that adjusting innovation strategies improves the forecasting performance of responsible companies, especially in a context of instability.

The paper clearly shows that CSR literature varies across different regions. Given that the financial market in Africa is characterized by a lack of opportunity for innovation as well as financial stability, this paper represents an important first step in the elaboration of a CSR development strategy. In light of the results presented above, the study makes an important contribution to the literature on CSR, in particular the CSR practices of multinationals in developing countries and also provides CSR managers with various insights into the types of support they will need to leverage and improve the internal underpinnings of their CSR strategies and collaboration.

The results of this study contribute to the understanding of digital transformation in responsible business, offering empirical evidence of its benefits in tackling the health crisis. In addition, the study highlights the role of an innovative approach in enhancing reputation and developing sustainable, trusting relationships with stakeholders.

This research pioneers the academic link between innovation and epidemic crisis in responsible business, filling a notable gap and introducing a new academic perspective. In concrete terms, it provides women entrepreneurs with actionable insights into the digital strategies essential to improving business performance in a context of instability. Methodologically, the study sets a benchmark for research innovation, using ML to provide a reproducible model for exposing robust results and for future research in this evolving field.

This study aimed to examine consumers’ impulse purchases of luxury products in the metaverse, specifically by exploring how consumers’ motivational and emotional experiences affect virtual luxury product purchases in the metaverse.

An online survey was administered to a total of 230 users of various metaverse platforms in China. The data were analysed using partial least squares structural equation modelling (PLS-SEM) disjoint two-stage approach.

The findings indicated that motivational experience (goal importance and goal interest) and positive emotion (fantasy, feeling and fun) have positive effects on impulse buying of luxury products in the metaverse, but none for negative emotions (loneliness and isolation).

This study indicated that understanding and leveraging consumers’ motivational experiences and positive emotions can drive their impulse buying behaviour of luxury products in the metaverse, hence providing virtual and brand retailers with a testbed for their products before they launch in the physical market.

This study enriches our comprehension of consumers’ metaverse luxury purchases by delving into the impacts of motivational and emotional experiences on impulse buying behaviours.

Unlike previous research that primarily utilized structural equation modelling (SEM) to evaluate safety hazards in subway projects, this research aims to utilize a hybrid approach to investigate and scrutinize the key indicators of safety hazards leading to accidents, thereby hindering the progress of subway projects in China, taking into cognizance the multiple stakeholder’s perspective.

By administering a survey questionnaire to 373 highly involved stakeholders in subway projects spanning Changsha, Beijing and Qingdao, China, our approach incorporated a four-staged composite amalgamation of exploratory factor analysis (EFA), confirmatory factor analysis (CFA), covariance-based structural equation modelling (CB-SEM) and artificial neural network (ANN) to develop an optimized model that determines the causal relationships and interactions among safety hazards in subway construction projects.

The optimized model delineated the influence of individual safety hazards on subway projects. The feasibility and applicability of the model developed was demonstrated on an actual subway project under construction in Changsha city. The outcomes revealed that the progress of subway projects is significantly influenced by risks associated with project management, environmental factors, subterranean conditions and technical hazards. In contrast, risks related to construction and human factors did not exhibit a significant impact on subway construction progress.

While our study provides valuable insights, it is important to acknowledge the limitation of relying on theoretical approaches without empirical validation from experiments or the field. In future research, we plan to address this limitation by assessing the SEM using empirical data. This will involve a comprehensive comparison of outcomes derived from CB-SEM with those obtained through SEM-ANN methods. Such an empirical validation process is crucial for enhancing the overall efficiency and robustness of the proposed methodologies.

The established hybrid model revealed complex non-linear connections among indicators in the intricate project, enabling the recognition of primary hazards and offering direction to improve management of safety in the construction of subways.