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The purpose of this paper is to develop a theoretical model that explains the impact of big data analytics capabilities (BDAC) on company's supply chain innovation capabilities and sustainable supply chain performance. BDAC is represented through two dimensions of big data technological capabilities (BDTC) and big data personal capabilities (BDPC). Moreover, the relationships between BDTC and BDPC with sustainable supply chain performance through the mediation effect of supply chain innovation capabilities are examined.

The study used a quantitative research approach. A survey of 400 Jordanian manufacturing companies was carried out to conduct this research. However, the responses of 207 managers were valid to be used in the analysis. In this study, the SmartPLS software was used to perform structural equation modeling using a partial least squares approach (PLS-SEM) and to examine the measurement and structural model's validity and reliability.

According to the results of this study, BDPC has a significant positive impact on supply chain innovation capabilities. Furthermore, the findings indicate that supply chain innovation capabilities are the most influential predictor of sustainable supply chain performance and act as a positive significant mediator in the relationship between BDPC and firm sustainable performance. Surprisingly, the study found that BDTC had no significant effect on supply chain innovation capabilities. Besides that, no significant relationship exists between BDTC and firm sustainable performance via the mediation effect of supply chain innovation capabilities.

This study provides an integrated research model that incorporates BDAC, supply chain innovation capabilities, and sustainable supply chain performance in order to analyze supply chain innovation and sustainable supply chain performance. This suggests that the scope of the study is broader in terms of predicting sustainable supply chain performance. As a result, the study intends to fill a gap in the literature by explaining how BDAC affects supply chain innovation capabilities and firms sustainable performance. In addition, the role of supply chain innovation capabilities as a mediator between BDAC and sustainable supply chain performance is investigated.

The Sustainable Lean Six Sigma (SLSS) adoption approach, advancements in Internet technologies and the use of Industry4.0 technologies has resulted in faster customer need fulfilment. The Industry4.0 technologies have resulted in a new paradigm where strategic and operational decisions are in favour of profitability and long-term viability. The purpose of this study is to identify Industry4.0-SLSS practices and sustainable supply chain performance metrics, as well as to develop a framework for decision-makers and managers to make supply chains more sustainable.

The 33 Industry4.0-SLSS practices and 24 performance metrics associated with the sustainable supply chain are shortlisted based on extensive literature review and expert opinion. The Pythagorean Fuzzy Analytical Hierarchy Process (PF-AHP) approach is used to evaluate the weights of Industry4.0-SLSS practices after collecting expert panel opinions. The Weighted Aggregated Sum Product Assessment (WASPAS) methodology used these weights to rank performance metrics.

According to the results of PF-AHP, “Product development competencies (PDC)” are first in the class of major criteria, followed by “Advanced technological competencies (ATC)” second, “Organisational management competencies (OMC)” third, “Personnel and sustainable competencies (PSC)” fourth and “Soft Computing competencies (SCC)” fifth. The performance metric “Frequency of NPD” was ranked first by the WASPAS method.

The proposed paradigm helps practitioners to comprehend Industry4.0 technology and SLSS practices well. The identified practices have the potential to boost the sustainability and supply chain's performance. Organizational effectiveness will benefit from practices that promote a sustainable supply chain and the use of developing technology. Managers can evaluate performance using performance metrics that have been prioritized.

The present study is one of the unique attempts to establish a framework for enhancing the performance of the sustainable supply chain. The idea of establishing Industry4.0-SLSS practices and performance measures is the authors' original contribution.

The purpose of this paper is to introduce a methodology to identify sustainable supply chain key performance indicators (KPI) that can then be used for sustainability performance evaluation for suppliers.

Initially the complexity of sustainable supply chain performance measurement is discussed. Then, a two-stage method utilizing neighborhood rough set theory to identify KPI and data envelopment analysis (DEA) to benchmark and evaluate relative performance using the KPI is completed. Additional analysis is performed to determine the sensitivity of the KPI set formation and performance results.

The results show that KPI can be determined using neighborhood rough set, and DEA performance results provide insight into relative performance of suppliers. The supply chain sustainability performance results from both the neighborhood rough set and DEA can be quite sensitive parameters selected and sustainability KPI sets that were determined.

The data utilized in this study are illustrative and simulated. Only one model for the neighborhood rough set and DEA was utilized. Additional investigations using a variation of rough set and DEA models can be completed.

This tool set is valuable for managers to help identify sustainable supply chain KPI (from among hundreds of potential measures) and evaluate sustainability performance of various units within supply chains, including supply chain partners, departments, projects and programs.

Sustainability incorporates many business, economic and social implications. The methods introduced in this paper can help organizations and their supply chains become more strategically and operationally sustainable.

Few tools and techniques exist in the sustainable supply chain literature to help develop KPIs and evaluate sustainability performance of suppliers and the supply chain. This paper is one of the first that integrates neighborhood rough set and DEA to address this important sustainable supply chain performance measurement issue.

The main objective of this paper is to study the role of supply chain performance (SCP) as a mediator between big data-driven supply chain (BDDSC) and firm sustainable performance. In addition, the role of firm age as a moderator between BDDSC and SCP as well as between SCP and firm sustainable performance has also been explored.

The 200 managers of medium or senior level positions in micro, small and medium enterprises (MSMEs) located at Delhi-NCR have been contacted. Further, collected data have been confirmed with confirmatory factor analysis (CFA). In this paper, structure equation modeling (SEM) has been employed to empirically check the proposed hypotheses and their relationships.

The findings confirmed that SCP mediates the link between BDDSC and firm sustainable performance. Additionally, firm age moderates the association between BDDSC and SCP as well as between SCP and firm sustainable performance.

The role of SCP and firm age between BDDSC and sustainable performance have been examined in the context of MSMEs in Delhi-NCR and thereby limit the generalization of results to other industries and country contexts.

The present study adds to the existing literature via recognizing the blackbox using SCP and firm age to comprehend BDDSC and firm sustainable performance relationship.

This study aims to investigate the impact of sustainable innovation and disruptive innovation on sustainable supply chain performance of manufacturing firms in Malaysia. The study also examined the moderating role of supply chain clockspeed in the relationship between sustainable innovation, disruptive innovation and sustainable supply chain performance.

The data were collected from 231 respondents in manufacturing firms in Malaysia. The data were analyzed using the partial least square-based structural equation modelling (PLS-SEM) technique.

The findings revealed that sustainable innovation and disruptive innovation had a significant and positive effect on sustainable supply chain performance. Supply chain clockspeed moderated the relationship between sustainable innovation and sustainable supply chain performance. The findings also identified that there was no moderating effect on the relationship between disruptive innovation and sustainable supply chain performance.

This study merely focuses on sustainable supply chain performance in Malaysian manufacturing firms. Samples from manufacturing firms in Malaysia were used in the current study, and the outcomes may vary for different nations.

To increase the firm’s commercial success, it is necessary to promote sustainable supply chain practices, including supply chain clockspeed, sustainable innovation and disruptive innovation.

This study adds to the body of knowledge by explaining the positive influence of sustainable innovation and disruptive innovation on sustainable supply chain performance in Malaysian manufacturing firms while also emphasizing the moderating role of supply chain clockspeed in this relationship. The contribution of this study could enable managers to develop sustainable supply chain performance in the manufacturing sector, based on sustainable innovation, disruptive innovation and supply chain clockspeed.

Big data analytics capabilities are the driving force and deemed as an operational excellence approach to improving the green supply chain performance in the post COVID-19 situation. Motivated by the COVID-19 epidemic and the problems it poses to the supply chain's long-term viability, this study used dynamic capabilities theory as a foundation to assess the imperative role of big data analytics capabilities (management, talent and technological) toward green supply chain performance.

This study was quantitative and cross-sectional. Data were collected from 374 executives through a survey questionnaire method by applying an appropriate random sampling technique. The authors employed PLS-SEM to analyze the data.

The findings revealed that big data analytics capabilities play a significant role in boosting up sustainable supply chain performance. It was found that big data analytics capabilities significantly contributed to supply chain risk management and innovative green product development that ultimately enhanced innovation and learning performance. Moreover, innovation and green learning performance has a significant and positive relationship with sustainable supply chain performance. In the post COVID-19 situation, organizations can enhance their sustainable supply chain performance by giving extra attention to big data analytics capabilities and supply chain risk and innovativeness.

The paper specifically emphasizes on the factors that result in the sustainability in supply chain integrated with the big data analytics. Additionally, it offers the boundary condition for gaining the sustainable supply chain management.

This paper aims to explore how the novel information technology (NIT) [1] affects three dimensions of sustainable supply chain performance (economic performance, environmental performance and social performance) and how two dimensions of IT alignment (IT infrastructure alignment and IT human resources alignment) mediate the relationship between them.

NIT is defined, the dimension of IT alignment is expanded, the theoretical hypotheses are proposed and are tested using survey data from 394 manufacturing enterprises using NIT in China.

The results indicate that NIT plays a positive role in improving sustainable supply chain performance, and IT alignment mediates the impact of NIT on sustainable supply chain performance.

This study highlights the impact of NIT on sustainable supply chain performance and demonstrates IT alignment as a mediator between them, it also provides a deeper understanding of how different dimensions of IT alignment affect sustainable supply chain performance

The purpose of this paper is to examine the concept of perishable food supply chain quality (PFSCQ) and to suggest a structural model that counts the influence of PFSCQ practices on organizational sustainable performance.

On the basis of comprehensive literature review, PFSCQ highly significant practices were examined and designated. These practices were classified into four dimensions: upstream quality (supplier quality), downstream quality (customer focus), internal quality (process and logistics quality) and support practices (top management leadership and commitment to quality, quality of human resource, quality of information and supply chain integration). The measurement instrument of organizational sustainable performance was also build on, containing three aspects: economic, environmental and social performance.

An inventive conceptual model that specifies a comprehensive image cover up core dimensions of PFSCQ and various aspects of organizational sustainable performance was suggested. This conceptual model can be used as “a directive” for theory developing and measurement instrument development of PFSCQ practices and organizational sustainable performance. More prominently, on the road to achieving additional insight, an extensive structural model that makes out direct and indirect relationships between PFSCQ practices and organizational sustainable performance was also developed. Practitioners can apply this model as “a path plan” for implementing PFSCQ practices to improve organizational sustainable performance.

The integration of quality and supply chain even now remains inadequate in the literature. Consequently, it is required to have a more focused approach in assessing quality issues inside the upstream, internal and downstream of the supply chain. This study concentrates on the practices which make better quality aspects of the supply chain, known as PFSCQ practices. Suggested research models in this paper contribute to conceptual frameworks for theory building in PFSCQ and sustainable organizational performance. It is also expected that this research can suggest a useful direction for determining and implementing PFSCQ practices as well as make possible further studies in this arena.

This paper aims to provide a framework which can assist focal companies in the development of sustainable supply chains. Sustainable development from an industrial perspective has extended beyond organisational boundaries to incorporate a supply chain approach.

The literature related to sustainable supply chain management is reviewed by incorporating concepts from four organisational theories, including the resource-based, institutional, stakeholder and social network perspectives, to illustrate key drivers and enablers of sustainability initiatives in the supply chain. A conceptual multidimensional framework is then developed that can be used for the initial assessment of supply chain sustainability.

Development and assessment of sustainability in supply chains are being increasingly incorporated as part of supply chain management today. This paper presents a multidimensional framework which can serve as a tool for research scholars and supply chain practitioners in identifying and assessing various economic, environmental and social performance indicators.

The framework and approach presented are conceptual, and require additional and broader validation. Additional theories, at differing levels, such as individual behaviour theory, should be utilised to further enhance and evaluate the framework. Developing and integrating analytical models for prescriptive and practical supply chain solutions can enhance the applicability of the framework.

The framework adopts a multidimensional approach to assessing and designing sustainable supply chains, as it not only incorporates economic and environmental dimensions but also provides a practical approach to quantifying and embedding the social dimension into decision-making. The framework helps industry practitioners in initial exploration of trade-offs among economic, environmental and social performance of supply chains, which, in turn, could assist them in creating a business case for sustainability.

The paper is one of few studies that incorporates some of the key aspects of all three dimensions of sustainability in a single overarching framework for supply chains and offers significant theoretical contribution and implications for sustainable supply chain management.

The purpose of this paper is to empirically assess the impact of integrated lean and green practices on the sustainable (environmental, economic and social) performance of a hotel supply chain.

Literature review and previous exploratory studies were used to develop a hypothesized model that characterizes the integrated lean and green (LeGreen) impact on supply chain sustainability. A case study of a large sample of the UAE hotels is used to collect and analyze empirical data, validate the measurement model and test study hypotheses using structural equation modeling (SEM).

The results showed that three major lean techniques (Kaizen, quality and productive maintenance) and three green techniques (health and safety, waste disposal and green certifications) have substantial impact on the sustainable performance of hotel supply chains. Further results revealed that LeGreen impacts are complementary. Lean techniques have the highest impact on the economic performance of the hotel supply chain and the least impact on the environmental performance. Green practices, on the other hand, have opposite impacts.

Although the study findings may vary in different contexts, study methodology and measurement model can be adapted to assess the LeGreen impact on the sustainable performance of hotel supply chains, as well as other service industries such as banking and health care.

The proposed assessment model is expected to be of great value toward the effective implementation of LeGreen practices across hotel supply chains in the UAE and globally. The study findings also provide guidelines for practitioners within the hospitality sector to undertake the proposed model and to adapt it for assessing and enhancing sustainable performance in other sectors of the service industry.

There is a growing emphasis by practitioners and academics on measuring the impact of LeGreen on the sustainable performance of service supply chains. However, the assessment of LeGreen impacts within the context of a hotel supply chain remains unexplored with a scarcity of comprehensive assessment frameworks. This study aims to fulfill this gap in literature and provide directions for researchers to expand the proposed model and to further analyze the integrated lean-green impact on the sustainability of supply chains of hotels and the service industry.