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Supply chain is the area that requires effective and integrated means of communication, shared risk, collaboration and orchestration in order to work successfully and the cloud computing has lot to offer to this domain. Cloud computing has appeared as a modern paradigm in supply chain networks for creating intelligent industries of future. The purpose of this paper is to propose a framework that can transform supply chain stakeholders toward Industry 4.0.

Cloud computing is attributed with increasing competitiveness by focusing on cost reduction, greater elasticity, flexibility and maximum utilization of resources which results in successfully achieving business goals. This paper proposes a Hybrid Supply Chain Cloud model, which integrates the infrastructure, the resources and the configurations of platforms.

This research paper is aimed at proposing a hybrid cloud that essentially helps in integrating the supply chain network with the flexibility and efficiency. It is important that a supply chain network adds value to ensure customer satisfaction and this can be best achieved by collaborating it with hybrid cloud.

This research provides a consistent central management and comprehensive view of all computing resources, which gives organizations the knowledge they need to optimize workload placement.

The findings derived from this research aim to facilitate policy makers and practitioners to develop effective courses of action in current and future supply chain management. Therefore, upon implementation, this model can provide long-term benefits for the organizations by improving the overall efficiency of its supply chain network.

The proposed hybrid cloud will provide deep level of integration in Industry 4.0 situation and thereby brought up portable comprehensive infrastructure based on resources and required configuration in real-time environment.

The digital revolution has brought many challenges and opportunities for the manufacturing firms. The impact of Industry 4.0 technology adoption on sustainable manufacturing and circular economy has been under-researched. This paper aims to review the latest articles in the area of Industry 4.0, sustainable manufacturing and circular economy and further developed a research framework showing key paths.

Qualitative research is performed in two stages. In the first stage, a review of the extant literature is performed to identify the barriers, drivers, challenges and opportunities. In the second stage, a research framework is proposed to integrate Industry 4.0 technology (big data analytics powered artificial intelligence) adoption, sustainable manufacturing and circular economy capabilities.

This research extends the knowledge base by providing a detailed review of Industry 4.0, sustainable manufacturing, and circular economy and proposes a research framework by integrating these three contemporary concepts in the context of supply chain management. Through an exploration of this integrative research framework, the authors propose a future research agenda and seven research propositions.

It is important to understand the interplay between institutional pressures, tangible resources and human skills for Industry 4.0 technology (big data analytics powered artificial intelligence) adoption. Industry 4.0 technology (big data analytics powered artificial intelligence) adoption can positively influence sustainable manufacturing and circular economy capabilities. Managers must also put more attention to sustainable manufacturing to develop circular economic capabilities.

Factory workers and the local communities generally suffer from various adverse effects resulting from the traditional manufacturing process. The quality of the environment is deteriorating to such an extent that people even staying miles away from the factory are also affected due to environmental pollution that is generated from factory operations. Hence, sustainable manufacturing is the only choice left to manufacturers that can help in the transition to a circular economy. The research framework can help firms to enhance circular economy capabilities.

This review paper contains the most updated work on Industry 4.0, sustainable manufacturing and circular economy. It also proposes a research framework to integrate these three concepts.

Theorising from the intersection of supply chain and information systems (IS) literature, this study aims to investigate supply chain integration (SCI) as a multidimensional construct in the context of cloud-based technology and explores the effect of cloud-enabled SCI on supply chain performance, which will eventually improve firm sustainability from a resource-based view (RBV). In addition, the moderating effect of top management is explored.

Using cross-sectional survey data collected from a sample of 105 Australian retail firms, this study used structural equation modelling to test the hypothesised relationship of cloud-enabled SCI with performance in a theoretical model.

Results show that cloud-based technology has positive effect on SCI, and the cloud-enabled SCI is positively related to supply chain performance which eventually influenced firm sustainability. Further, top management intervention moderates the relationship between supplier and internal integration with supply chain performance. But it is found to have no moderating effect on the relationship between customer integration and supply chain performance.

Recognising the potential benefits of emerging cloud-based technologies reported in this study, retail managers need to understand that higher order SCI requires the support of cloud-based technology to improve supply chain performance and firm sustainability.

This research extends prior research of information and communication technologies-enabled SCI and its effect on supply chain performance which overly remains inconsistent. In addition, IS literature abounds with discussion on cloud computing technology per se, and its adoption in supply chain is overly rhetoric. This study fills this gap by conceptualising the multiple dimensions of SCI enabled by cloud-based technology and the way it affects supply chain and firm sustainable performance. Investigating SCI in context of cloud-based technology is a unique contribution in this study. The moderating effect of top management in this decision also adds to the current body of literature.

Big data is relevant to the supply chain, as it provides analytics tools for decision-making and business intelligence. Supply Chain 4.0 and big data are necessary for organisations to handle volatile, dynamic and global value networks. This paper aims to investigate the mediating role of “big data analytics” between Supply Chain 4.0 business performance and nine performance factors.

A two-stage hybrid model of statistical analysis and artificial neural network analysis is used for analysing the data. Data gathered from 321 responses from 40 Indian manufacturing organisations are collected for the analysis.

Statistical analysis results show that performance factors of organisational and top management, sustainable procurement and sourcing, environmental, information and product delivery, operational, technical and knowledge, and collaborative planning have a significant effect on big data adoption. Furthermore, the results were given to the artificial neural network model as input and results show “information and product delivery” and “sustainable procurement and sourcing” as the two most vital predictors of big data adoption.

This study confirms the mediating role of big data for Supply Chain 4.0 in manufacturing organisations of developing countries. This study guides to formulate management policies and organisation vision about big data analytics.

For the first time, the impact of big data on Supply Chain 4.0 is discussed in the context of Indian manufacturing organisations. The proposed hybrid model intends to evaluate the mediating role of big data analytics to enhance Supply Chain 4.0 business performance.

The purpose of this paper is to analyze the effects of two technologies, cloud computing and Web 2.0, on a firm’s operational performance, examining the relationship between these two technologies and operational performance, and the mediating role played by supply chain integration.

A random sample of 394 companies taken from the DUNS 50,000 database in Spain is used to test the paper’s hypotheses. The data were gathered by telephone survey using the CATI computerized system to manage interviewees’ answers, obtaining a 19.36 percent response rate. Factorial analyses and structural equation modeling were used to test the hypotheses.

The results suggest that cloud computing requires the mediating support of supply chain integration. However, there is no concluding evidence that Web 2.0 has a positive effect on either supply chain integration or operational performance. A positive, significant relationship was found between supply chain integration and operational performance in all the models used.

Further research and longitudinal analyses should be carried out in a range of industrial and geographical settings to confirm the findings of this study. Further analyses could also extend the scope and generalizability of results by analyzing the assimilation of supply chain integration-related inter-organizational information systems, such as the effect of ERP systems on performance. Another future direction for research is a study of the impact of the joint assimilation of internal and external integration practices on operational performance.

Managers should be aware of the key role that trust plays in the information-sharing process in conjunction with supply chain management. Trust and information-sharing are two inextricably linked elements that enable greater supply chain integration to translate into better operational performance. This paper can also make managers more aware of the powerful tools that exist in the cloud computing universe and those that come under the umbrella of Web 2.0. Companies can use the findings of this paper to create new applications to facilitate supply chain integration. Some examples are also given of how cloud applications can be applied to better integrate the supply chain and, ultimately, to improve overall operational performance.

This is one of the first attempts to disentangle the effects exerted by cloud computing on company performance through the mediating role of a higher supply chain integration. The value of this study relies in that academics and practitioners may have a supporting evidence on the role played by a new, disruptive technology such us cloud computing in, internal, operationally linked structures such as supply chain integration and how this combination transforms into better operational outcomes.

Cloud computing is one of the technologies that improves performance and reduces costs in companies through flexible and easy access to computational resources. Supply chain management is one of the widespread and unlimited computing resources. Applying cloud computing to the green supply chain will eliminate constraints and speed up the implementation of various chain processes. Therefore, this paper aims to present a model and framework for assessing the impact of cloud computing on green supply chain management, which improves the performance of the resulting system in comparison with previous systems.

In this study, a self-made questionnaire containing 38 questions was used to collect data. The questions were compiled based on the variables identified in previous studies. Besides, the answers to the questions were based on the five-point Likert scale (strongly disagree, disagree, no opinion, agree and strongly agree). By reviewing the subject literature, the factors that affect the green supply chain management have been identified, which include cost of services, user-friendly software, energy consumption, subscription and collaboration capabilities and self-service ability.

The findings confirmed the fitness of the proposed model and showed the impact of cloud computing on green supply chain management. In addition, results showed that considered variables (service cost, user-friendly applications, energy consumption, sharing and collaboration and self-service) significantly affect the success management of green supply chain.

The results of this research show that, to help effective management of the complexity of the supply chain, many companies have adopted an advanced IT strategy to increase the flow of information and, in turn, to increase their competitive advantage.

The development of a cloud computing-based green supply chain management system can lead to improved system performance compared to traditional systems, which can revolutionize a wide range of industries and businesses by clarification of businesses and making the processes smart. It can also reduce costs and improve performance of micro- and macro-business firms. Therefore, the purpose of this study is to provide a model for investigating the impact of cloud-based IT systems on green supply chain management.

Digital transformation using Industry 4.0 technologies can address various challenges in food supply chains (FSCs). However, the integration of emerging technologies to achieve digital transformation in FSCs is unclear. This study aims to establish how the digital transformation of FSCs can be achieved by adopting key technologies such as the Internet of Things (IoTs), cloud computing (CC) and big data analytics (BDA).

A systematic literature review (SLR) resulted in 57 articles from 2008 to 2022. Following descriptive and thematic analysis, a conceptual framework based on the diffusion of innovation (DOI) theory and the context-intervention-mechanism-outcome (CIMO) logic is established, along with avenues for future research.

The combination of DOI theory and CIMO logic provides the theoretical foundation for linking the general innovation process to the digital transformation process. A novel conceptual framework for achieving digital transformation in FSCs is developed from the initiation to implementation phases. Objectives and principles for digitally transforming FSCs are identified for the initiation phase. A four-layer technology implementation architecture is developed for the implementation phase, facilitating multiple applications for FSC digital transformation.

The study contributes to the development of theory on digital transformation in FSCs and offers managerial guidelines for accelerating the growth of the food industry using key Industry 4.0 emerging technologies. The proposed framework brings clarity into the “neglected” intermediate stage of data management between data collection and analysis. The study highlights the need for a balanced integration of IoT, CC and BDA as key Industry 4.0 technologies to achieve digital transformation successfully.

Cloud-based enterprise resource planning (ERP) enables an organization to pay for the services they need and removes the need to maintain information technology infrastructure. The purpose of this paper is to empirically test the role of cloud-based ERP services on the performance of an organization. Here, the performance is categorized as supply chain performance and organizational performance that comprises of financial performance and marketing performance. Contingent resource-based view (RBV) theory was used to develop a theoretical framework in which supply base complexity (SBC) acts as a moderating variable on the relationship between cloud ERP and the performance.

Contingent RBV theory is used to explain the relationship between all identified variables in this paper. Partial least squares (PLS) based on structural equation modeling (SEM) is used to empirically test our theoretical framework.

The PLS-SEM analysis of 154 respondents supports the contingent RBV theory. Six hypotheses – out of the eight hypotheses formulated in this paper – are supported by data.

Given this study was conducted in India where the potential of cloud ERP has not been fully implemented yet, the results may reflect more of perceived usefulness of this technology. The authors have attempted to understand the effect of SBC as a moderator in the relationship between cloud ERP and organizational performance which may not be the only moderator affecting this relationship among other potential moderators.

This paper empirically validates the theoretical framework based on the contingent RBV theory as it mitigates the static nature of the resource-based view approach suggested in the seminal article of Barney (1991).

The purpose of this paper is threefold: to present internet of things (IoT)-based cyber-physical system (CPS) architecture framework to facilitate the integration of IoT and CPS; to implement an IoT-based CPS prototype based on the architecture framework for a PL application scenario of in a case study; and to devise evaluation methods and conduct experimental evaluations on an IoT-based CPS prototype.

The design research method, case study, emulation experiment method, and cost-benefit analysis are applied in this research. An IoT-based CPS architecture framework is proposed, and followed by the development of prototype system and testbed platform. Then, the emulation and experimental evaluation of IoT-based CPS are conducted on the testbed, and the experimental results are analyzed.

The emulation experiment results show that the proposed IoT-based CPS outperforms current barcode-based system regarding labor cost, efficiency, and operational adaptiveness. The evaluation of the IoT-based CPS prototype indicates significant improvements in PL tasks and reduced part inventory under a dynamic changing shop-floor environment.

The case study shows that the proposed architecture framework and prototype system can be applied to many discrete manufacturing industries, such as automobile, airplane, bicycle, home appliance, and electronics.

The proposed IoT-based CPS is among the first to address the need to integrate IoT and CPS for PL applications, and to conduct experimental evaluations and cost-benefit analysis of adopting IoT-based CPS for PL. This paper also contributes to the IoT research by using diverse research methods to offer broader insights into understanding IoT and CPS.

Disruptive technologies can significantly contribute to the sustainability of operations in the petroleum supply chain. The present study aims to identify the prime sustainable dimensions and disruptive technologies implementation in the supply chain of the petroleum industry. The authors used content analysis in the literature and experts input to explore the sustainable dimensions and disruptive technologies in the supply chain.

This study used a hybrid method of hesitant fuzzy set and regret theory to identify the prominent sustainability dimensions and prominent disruptive technologies. This method emphasizes the decision-makers psychological characteristics under uncertain environments.

The result indicates that social responsibility, labor practices, safety and technical standards hold the most prominent sustainable dimensions in the petroleum supply chain. Further, the result also depicts that when consider an equal degree of regret and rejoice, artificial intelligence and big data could significantly enhance operations sustainability in the petroleum industry.

This study considers only 11 sustainable dimensions and 43 sustainable factors, whereas other dimensions and factors could also be considered in future research. The research uses hesitant fussy set and regret set theory to identify the prominent sustainable dimensions and disruptive technologies, whereas other multiple-criteria decision-making (MCDM) techniques can also be used.

To the best of the authors’ knowledge, this is the first paper to explore the sustainable dimensions (environmental, social and economic) and disruptive technologies in the supply chain of the petroleum industry. This research intended to guide the practitioners, policymakers and academicians to emphasize their effort toward sustainable operations supply chain management.