Abstract
Purpose
The study aims to map the links between Industry 4.0 (I-4.0) technologies and circular economy (CE) for sustainable operations and their role to achieving the selected number of sustainable development goals (SDGs).
Design/methodology/approach
The study adopts a systematic literature review method to identify 76 primary studies that were published between January 2010 and December 2020. The authors synthesized the existing literature using Scopus database to investigate I-4.0 technologies and CE to select SDGs.
Findings
The findings of the study bridge the gap in the literature at the intersection between I-4.0 and sustainable operations in line with the regenerate, share, optimize, loop, virtualize and exchange (ReSOLVE) framework leading to CE practices. Further, the study also depicts the CE practices leading to the select SDGs (“SDG 6: Clean Water and Sanitation,” “SDG 7: Affordable and Clean Energy,” “SDG 9: Industry, Innovation and Infrastructure,” “SDG 12: Responsible Consumption and Production” and “SDG 13: Climate Action”). The study proposes a conceptual framework based on the linkages above, which can help organizations to realign their management practices, thereby achieving specific SDGs.
Originality/value
The originality of the study is substantiated by a unique I-4.0-sustainable operations-CE-SDGs (ISOCES) framework that integrates I-4.0 and CE for sustainable development. The framework is unique, as it is based on an in-depth and systematic review of the literature that maps the links between I-4.0, CE and sustainability.
Keywords
Citation
Patyal, V.S., Sarma, P.R.S., Modgil, S., Nag, T. and Dennehy, D. (2022), "Mapping the links between Industry 4.0, circular economy and sustainability: a systematic literature review", Journal of Enterprise Information Management, Vol. 35 No. 1, pp. 1-35. https://doi.org/10.1108/JEIM-05-2021-0197
Publisher
:Emerald Publishing Limited
Copyright © 2021, Vishal Singh Patyal, P.R.S. Sarma, Sachin Modgil, Tirthankar Nag and Denis Dennehy
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Sustainability issues concerning economic, environmental and social dimensions are a major threat to organizations in the 21st century (Bag and Pretorius, 2020; Dantas et al., 2021; Gupta et al., 2021). It requires optimization of resources through recycling, reusing the components and products and restoration of the energy inputs for a longer duration, transforming the world's economies to be more sustainable and environment friendly (Rajput and Singh, 2019). In response, policymakers worldwide make claims about their commitment to reduce greenhouse gas emissions, global warming, address the shortage of resources and manage waste disposal and recycling (Dantas et al., 2021; Nerini et al., 2019; Zhang et al., 2019). Further, governments are grappling with the need to devise rigorous environmental regulations and increase awareness about clean technologies and sustainable practices (Ambekar et al., 2019). International bodies are also advocating for more stringent laws and directives that support sustainability as a prerequisite for awarding contracts as prescribed in the United Nations (UN) Agenda (Dantas et al., 2021; Filippini et al., 2019; Juste Ruiz, 2020; Rashed and Shah, 2020; United Nation Agenda, 2015).
In 2015, the United National General Assembly approved the “2030 Agenda for Sustainable Development” with a clear mandate concerning the planet, people, peace, prosperity and partnerships. The SDGs aim to eradicate poverty, protect the earth and strengthen universal peace as mentioned in 17 SDGs and 169 targets to be part of millennium development goals. These goals emphasize three sustainability dimensions: economic, social and environmental (Rodriguez-Anton et al., 2019). Sustainable performance cannot be achieved holistically without digital transformations (Silvestre and Ţîrcă, 2019).
The adoption and integration of I-4.0 technologies and CE facilitates the achievement of SDGs (Hidayatno et al., 2019; Saucedo-Martnez et al., 2018; Dantas et al., 2021; Gupta et al., 2021; Rajput and Singh, 2019; Schroeder et al., 2019). The importance of integrating CE practices and I-4.0 technologies has been recognized by the academic community (Govindan and Hasanagic, 2018; Pham et al., 2019; Dantas et al., 2021). For example, a study by de Sousa Jabbour et al. (2018) integrated I-4.0 and CE principles using the “ReSOLVE” framework. The ReSOLVE framework provides six action areas that enable organizations to move towards the CE (MacArthur, 2015a, b; MacArthur et al., 2015), namely (1) support regenerating capacity of eco-system through reclaiming, retaining and restoring the health of ecosystems; (2) extend the life of products through creating a design for durability and upgradability; (3) removal of waste in the production and supply chain processes; (4) extract bio-chemicals from organic waste; (5) dematerialize directly or indirectly and (6) implement I-4.0 technologies [e.g. (3D) printing].
Belaud et al. (2019) report the benefits of combining big data and sustainability assessment for the agriculture supply chain. Verdouw et al. (2016) have developed reference architecture for Internet of Things (IoT)-based logistic information systems in closed loop agri-food supply chains. Rajput and Singh (2019) highlight the enablers and barriers to CE and I-4.0 in designing value chains. Chauhan et al. (2021) have developed a smart healthcare waste-disposal system driver of I-4.0 and CE. Therefore, emerging I-4.0 technologies can be adopted to overcome these barriers. I-4.0 is a smart technology based on a production and manufacturing system powered by information communication technology and data storage (Lasi et al., 2014). However, Cwiklicki and Wojnarowska (2020) raise a concern that the connections between I-4.0 technologies and CE implementation are not well understood, creating a quandary in understanding these linkages. The motivation of this study is the increased usage of I-4.0 technologies (Schwab, 2016) and growing importance of reuse, recycling and refurbishing of input materials (CE practices) in the process of sustainable production and consumption (Khanzode et al., 2021; Kirchher et al., 2017). Dantas et al. (2021) claim that a combination of novel technologies and circular production models is critical in achieving SDGs targets.
A contribution of this study is the linking of I-4.0 technologies and CE and their application to specific SDGs through a proposed ISOCES framework. More specifically, the study aims to answer the following questions through a systematic review of literature:
How will I-4.0 technologies help organizations to achieve sustainable operations?
How will sustainable operations lead to CE practices?
How integration of the three verticals of review, namely I-4.0-sustainable operations-CE helps in achieving select SDGs through an ISOCES framework?
The remainder of this paper is organized as follows. The theoretical background to I-4.0, CE and SDGs is presented. Next, the research methodology is outlined. Then, analysis of the links between I-4.0-SO-CE-SDGs through an ISOCES framework is discussed. Followed by contributions of the study, limitations and future research, the paper ends with a conclusion.
2. Background literature
This section presents the theoretical background essential for review. Initially, it explores the relationship between I-4.0 and CE based on the available literature. Further, it assesses the linkages between CE and SDGs.
2.1 Circular economy
CE is an economic business model based on minimizing finite consumption of limited resources by replacing the “end of life” concept and by emphasizing the design of materials, products and systems (Kirchherr et al., 2017). CE aims to provide actions and practices like reuse, recycle, repair, eco-design, refurbishment, remanufacturing, recover product sharing for sustainable production and consumption (Chertow and Ehrenfeld, 2012; Ferrara et al., 2014; Lombardi and Laybourn, 2012; Nasr and Thurston, 2006; Rodriguez-Anton et al., 2019; Yao et al., 2013). MacArthur (2015b) asserts that CE is based on three fundamental principles, namely “preserve and enhance natural capital,” “optimize resource yields” and “foster systems effectiveness.” The adoption of these principles can be at diverse levels, e.g. micro: relates to products and firms view; meso: corresponding to a network of companies and macro: signifies the actions undertaken by cities, regions and nations (Acerbi and Taisch, 2020; Caner and Tyler, 2015; Ghisellini et al., 2016). CE is inflexibly rooted in the triple bottom line's environmental sphere that suggests a pathway to sustainable development (Athanasiadis et al., 2011; Whalen et al., 2018; Vinante et al., 2020). CE's goal is to concentrate on businesses and economic performance, while sustainable development addresses environmental and social problems to help future generations to sustain (Kirchherr and Piscicelli, 2019). CE has received a lot of attention in recent years, with numerous reviews examining various aspects of its design and implementation. Moreover, it is also appreciated as a critical solution to the global problems because of the considerable adverse effects of the current linear economic models on our ecosystem (Kravchenko et al., 2019; Rodriguez-Anton and Alonso-Almeida, 2019; Vinante et al., 2020). The CE enablers have been reviewed in the domains such as textile and apparel (Jia et al., 2020), procurement practices (Sonichsen and Clement, 2020), supply chains (Lahane et al., 2020), product-service systems (Da Costa Fernandes et al., 2020) and manufacturing (Acerbi and Taisch, 2020; Akmal and Batres, 2013).
2.2 Fourth Industrial revolution
The fourth revolution of industry started from a project of the German Government with a strategic manufacturing roadmap to promote the digitalization in 2011. The term “Industry 4.0” was publicly declared in the year 2011 at the Hannover Fair. Due to I-4.0, most manufacturing systems are supported by advance information systems (Lasi et al., 2014; O'Leary, 2014). It involves smart factories and intelligent technologies to achieve better efficiency in the value chain moving from dominant machine manufacturing to digital manufacturing (Haleem and Javaid, 2019; Oztemel and Gursev, 2020; Patil et al., 2020; Shrouf et al., 2014; Stock and Seliger, 2016; Tiwari, 2020). I-4.0 makes use of advanced technologies to transform manufacturing systems (Formentini and Romano, 2011; Shwartz-Asher et al., 2020) with digital technologies (Kang et al., 2016; Pullan et al., 2011). I-4.0 aims to provide real-time information on production status, energy consumption, customer orders, machines and flow of materials with the help of technologies like 3D printing, artificial intelligence (AI), Big Data, IoT and robotics that facilitate managerial decision-making (Carnabuci and Operti, 2013; de Sousa Jabbour et al., 2018; Farooq, 2020; Jorro-Aragoneses et al., 2019; Kyriakou et al., 2017; Lin, 2014; Lu, 2017; Mareea and Belkhatirb, 2015). Previous literature lacks in agreement among researchers and practitioners about the technologies categorized under the ambit of I-4.0 (Pacchini et al., 2019; Rosa et al., 2020). This study refers to the most frequently cited literature to identify the most relevant technologies for I-4.0 (see Table 1). See Appendix 1 for explanation of the acronyms used in Table 1.
2.3 Linkages between Industry 4.0 and circular economy
In recent years, I-4.0 and CE continued to show rapid growth and help achieve sustainable operations through sustainable products and production/processes (see Table 1). Logistics decisions (Gunasekaran et al., 2014) and integration of I-4.0 and CE help transform the linear economy into a CE-based sustainable supply chain (Geng and Doberstein, 2008; Mont, 2002). Further, the integration of supply chains through data collection and sharing helps contribute to sustainable operations management through the connection between CE and I-4.0 technologies (De Man and Strandhagen, 2017; de Sousa Jabbour et al., 2018; Sauerwein et al., 2019; Stock and Seliger, 2016). Table 2 indicates a detailed mapping of CE and I-4.0 with supporting references.
Existing literature highlights the strong linkage between CE and I-4.0; for example, Nascimento et al. (2019) suggest that I-4.0 could help reusable scrap electronic devices' circularity. Further, the impact of AI, service and policy framework establishes a strong relationship between I-4.0 and CE (Alstete and Meyer, 2020; Pradana et al., 2017; Quintana-Amate et al., 2015; Rajput and Singh, 2019; Vitharana et al., 2012).
2.4 The role of CE and Industry 4.0 in achieving the SDGs
In 2015, the COP21 (Conference of the Parties) Paris Agreement, together with the emergence of the resolution “Transforming our World: the 2030 Agenda for Sustainable Development” (UN, 2015), put forward the essential step toward achieving sustainable, inclusive development across geographies (del Río Castro et al., 2020). International affairs in the 21st century should be based on fundamental principles and the millennium development goals (Saito et al., 2017; Sachs, 2012). International relationships should be built on three strong pillars of sustainable development, namely economic, social and environmental, which needs to be action oriented, indivisible, multi-disciplinary, inclusive and universally applicable (Biermann et al., 2017; Cheong, 2017; Galvão et al., 2018; Kanie and Biermann, 2017; Osburg and Lohrmann, 2017; del Río Castro et al., 2020). The United Nations' member states have adopted SDGs to take specific actions to eradicate poverty, protect climate and ensure peace and prosperity. It comprises 17 goals, 169 targets and 231 indicators supported over five pillars (planet, people, peace, prosperity and partnerships) combined such that action in one domain helps achieve outcomes in the other (UN Development Program). According to Mohan et al. (2019), 11 SDGs are vital to the CE. SDGs 1, 2, 3 and 8 are socio-economic targets, while SDGs 6, 13, 14 and 15 are ecological targets. Hygienic industry and economic goals are covered by SDGs 7, 9 and 12 (Heimann, 2019). Further, Rodriguez-Anton et al. (2019) conducted an empirical study that reports that CE directly correlates with SDG 8, 9, 11 and 12 and has an indirect relationship with SDG 13 and 14. In contrast, Schroeder et al. (2019) assert that the most vital relationship between CE practices and SDGs is linked with SDG 6, 7, 8, 12 and 15; however, SDG 1, 2 and 14 do impact CE practices indirectly.
There are numerous ways to integrate I-4.0 solutions with the SDGs. For example, Bonilla et al. (2018) find that I 4.0 can strongly impact SDGs 7, 9, 12 and 13. Further, Modgil et al. (2020) suggest that I 4.0 influences SDGs 7, 8, 9, 10 and 11. Additionally, Oláh et al. (2020) prove that I-4.0 is a crucial technological driver for achieving the SDGs 7, 8, 12 and 13. Fatimah et al. (2020) argue that the use of information and communication technology (ICT) and IoT improves the efficiency and effectiveness of the waste management system covering governance, economic, social and environmental dimensions and helps achieve SDGs 3, 6, 12 and 13. Dantas et al. (2021) establish that applying I-4.0 technologies in circular systems can support the achievement of SDGs.
3. Review methodology
This section outlines the stages adopted in the present study. The study follows the structured practices proposed by Ahmad et al. (2018) and Kitchenham et al. (2011). Figure 1 outlines the three phases and ten steps that were followed to achieve the aim of this systematic literature review.
3.1 Planning the mapping
This section of the study presents the stages 1, 2 and 3 of Figure 1. The study's primary objective is to organize and thematically analyze the literature on I-4.0 technologies, CE and selected SDGs (Ahmad et al., 2018; Kitchenham et al., 2011, p. 640). Therefore, the motive for conducting this review is to explore the I-4.0 technologies and CE in SDGs between 2010 and 2020 (Stage 1). The main objective of the study (Stage 2) is to (1) provide a comprehensive overview of I-4.0, CE and SDGs literature; (2) synthesize the claimed benefits of I-4.0, CE and SDGs and (3) identify opportunities for future research in the areas of I-4.0, CE and SDGs. To achieve these research objectives, the research questions stated at the end of the introduction section are answered through this study (Stage 3).
3.2 Conducting the planned mapping
This section executes the stages four, five, six and seven of the mapping procedures. In this study, a search string is developed based on the scope of the study which is confined to I-4.0, CE and SDGs. The search string presented in Table 3 is developed around the “or” and “and” operators. Scopus was used to find and shortlist 76 papers (Step 4) presented in four stages in Table 3.
The records were imported in the Microsoft excel sheet format from Scopus. The basic format includes (1) publication type, (2) title, (3) author, (4) year and (5) abstract. Further, filtration of the identified articles (Stage 5) was done on the basis of best practices of I-4.0 and CE for achieving SDGs. The article selection process is illustrated in Figure 2.
3.3 Inclusion and exclusion criteria
Articles offering empirical and non-empirical perspectives on I-4.0, CE and SDGs (e.g. systematic mapping study and systematic literature review) were selected for the review on the condition of sufficient rigor in research. The inclusion criteria used were as follows: (1) the study should be written in English; (2) the study should be published between January 2010 and December 2020; (3) the study directly answers one or more of the research questions of this study; (4) the study should clearly state its focus on I-4.0, CE and SDGs and (5) the study should describe the application of I-4.0 technologies and the approach used to study its use or implementation.
Studies were excluded if the focus was not explicitly on I-4.0, CE and SDGs or if they did not provide academic rigor or industry relevance. The exclusion criteria used were as follows: (1) duplicate articles, (2) not written in English, (3) studies not specifically focused on I-4.0, CE and SDGs and (4) non-peer-reviewed articles (i.e. books, book chapters and experience reports).
The search string on Scopus was used via advanced search facility. Scopus was chosen over other search engines due its wide collection and range of topics. Additionally, the choice of Scopus favors integrity in conducting research. Scopus also makes available the metrics that indicate top researchers, institutions and journals for a particular topic. The developed query was executed by two independent authors. Papers published from year 2010–2020 were considered and there was much focus on advanced technologies of I-4.0, CE and SDGs during the period as it is evident from the literature. The integrated search of three areas at first led to 4,614 articles. Further, the search was restricted only to articles, articles in press and review papers in the related domain, which resulted in 121 articles. Articles from 2021 were excluded from the shortlisted articles as the year had just started; this led to 77 articles. Each article was read, and finally, 76 articles identified as primary articles for the review [see references – primary sources by symbol *(P)].
The primary articles were analyzed based on parameters such as type of paper, methodology used, domain, publication location and relevance and rigor of the study. The primary papers were reviewed by each author and then a combined peer-review was done. In case of disagreement, input was sought from author five. Finally, the lead author, who has a broad understanding of the study, evaluated each aspect of it to ensure that the results are consistent.
Quality of the 76 primary papers was assessed against 11 criteria (Dyba and Dingsøyr, 2008). Using a binary system, each criterion was evaluated to answer the questions in Table 4. A value of 1 indicates a “Yes” response, while a value of 0 indicates a “No” response. These 11 criteria present a measure of quality assessment for these 76 studies (see Table 5). To limit the degree of subjectivity in quality assessment, authors 1 and 2 independently reviewed the 76 articles. The outcome of these independent assessments was considered as an objective quality assessment. The results were validated by authors 3 and 4.
3.4 Results
This section presents a summary of the review carried out based on parameters such as (1) number of publications per year, (2) spread of domain and (3) publication sources (see Figure 3). The year-wise number of publications is presented in Figure 4. The trend indicates that after the announcement of SDGs in 2015, research picked up and it shows a clear rise from 2017 onward. Figure 5 indicates a considerable percentage of articles from business, management and accounting areas (29%) followed by computer science (17%) and decision sciences (16%). A total 76 research articles published in 29 journals, and year-wise publications from these journals are presented in Table A2 (see Appendix 2).
4. Analysis and findings
This section discusses the research questions and proposed framework.
4.1 Integration of technologies under I-4.0 helps organizations to achieve sustainable operations
Managing sustainable operations was conceptualized during the process of advising businesses on how to design their operations to benefit society, the economy and the environment. This involves operations starting from the concept, product design and process design, focusing on eco-friendly designs in full compliance with the three objectives of sustainable operations management (Walker et al., 2014). Operations of any organization can be environmentally sustainable only when they (1) consume resources at rates that do not exceed their rate of regeneration and (2) pollute at levels that do not exceed the environment's assimilation capacity (Toffel, 2014).
Tracking the origin of sustainability in 1987, the World Commission on Environment and Development (WCED) report defines sustainability as “meeting the needs of the present without compromising the ability of future generations to meet their own needs.” Previous research reported by Karlusch et al. (2018) and Rockström et al. (2009) has made an effort to tackle sustainability issues. Several scholars have looked at many aspects of I-4.0, such as real-time information sharing, modern age internet-based technology advances and their usefulness, product/service distribution speed with decreased errors at no extra expense and so on (Pacheco et al., 2016; Thoben et al., 2017; Zhong et al., 2017a, b). Bernon et al. (2018) present an exploratory framework that aligns reverse logistics activities in the retail sector with CE principles. It can be viewed as a link between CE and long-term sustainability. Ellen MacArthur Foundation (MacArthur, 2015a, b; MacArthur et al., 2015) has created a vision based on designing out “waste and pollution,” keeping products and materials in use and regenerate natural systems. Firms' operations driving profitability and their linkage with people and the planet at large are increasingly connected to sustainability (Kleindorfer et al., 2005).
The ReSOLVE framework proposed by MacArthur (2015b) includes Regenerate – all operations with a focus on earth's biocapacity; Share – sharing the total utility of resources, thereby eliminating wastage and duplication; Optimize – operations involving wastage of energy and materials and shall use technologies to maximize resource usage; Loop – reuse/recycle/re-manufacture of the products, thereby looping them back into the economy before they are released for landfill; Virtualize – participation in virtualization of the economy using more technologies and Exchange – allowing operations for using or upgrading new technologies for completing the existing processes.
de Sousa Jabbour et al. (2018), in their study, have integrated I-4.0 and CE principles using the ReSOLVE model by MacArthur (2015b) in which all the phases are benefited by the components of I-4.0 (CPS, IoT, cloud computing and Big Data). Regenerate – IoT under I-4.0 creates real-time data of certain operations, helping production decisions resulting in sustainable operations, i.e. reducing wastages in resource usage, thereby supporting the earth's regenerating capacity of resources. Share – Technologies under I-4.0 increase manufacturing productivity via connected devices and a rapid interchange of information, resulting in a shift in economics (Rüßmann et al., 2015). Optimize – I-4.0, according to Hofmann and Rüsch (2017), will aid in greatly customized production, real-time coordination and optimization of supply chains, as well as the elimination of complexity costs. This will result in the reduction of waste of resources. Loop – according to Despeisse et al. (2017), additive manufacturing (AM), IoT and new materials under I-4.0 are accelerating the industry's landscape in many ways. Another advantage of AM, according to Matsumoto et al. (2016), is the potential to apply a new material to existing surfaces to restore and remanufacture used and worn parts and components. Gao et al. (2015) have identified another benefit of AM that it will support remanufacturing of products independent of the value chain. Virtualize – As “digital twin” delineates mirroring product to virtual space reproduction, these data generated from several IoT sensors is transmitted to a virtual replica of the system, creating a digital twin covering the entire production process. This term originally referred to the act of mirroring a product. Simultaneously, it enables processes (manufacturing, electricity storage, etc.) to facilitate virtual space reproduction (twinning) to reap the same benefits (Stock et al., 2018). Exchange – Autonomation of systems under I-4.0 are replacing the passive manufacturing systems (Stock et al., 2018). The present study also depicts the mapping of the ReSOLVE framework (MacArthur, 2015a, b; MacArthur et al., 2015) with the I-4.0 technologies and helps identify the interdependencies of I-4.0 and sustainable operations resulting in CE.
4.2 Integration of sustainable operations leads to CE practices
Smol et al. (2020) have developed a CE model framework in the water and wastewater sector, consisting of two additional aspects, “removal of pollutants” and “rethink,” to introduce systematic changes in the whole value chain. This part of CE practices has achieved target 6.3 (UN, 2015), supporting the SDG 6 to ensure availability of clean water and sanitation. Further, Taskhiri et al. (2014), in their study, developed an optimal waste-to-energy (WTE) network model for generation of energy through waste incineration, especially in eco-industrial parks (EIPs), resulting in heat recovery from industrial processes and industrial waste. This will help improve the industries' energy efficiency linking to Target 7.3 (see, UN, 2015). According to the “European Environment Agency (EEA) (EEA, 2016, 9),” the CE as “The concept can, in principle, be applied to all kinds of natural resources, including biotic and abiotic materials, water, and land. Eco-design, repair, reuse, refurbishment, remanufacture, product sharing, waste prevention, and waste recycling are all important in a CE.” Practices of CE will result in retrofitting industries, thereby enabling them to be more efficient in reusing, remanufacturing and reducing the waste of resources, linking to the Target 9.4 (see, UN, 2015). Additionally, Gheewala and Silalertruksa (2021) report that if more products can be produced from the same volume of raw materials and energy, then the production process would result in “cleaner production” and low levels of waste generation. CE practices of reducing wastage of virgin materials result in sustainable consumption and production linking to Target 12.2 (see, UN, 2015). Moreover, Toffel (2014) argue that sustainable operations pollute at levels that do not exceed the environment's assimilation capacity. Reduced pollution levels result in a reduced impact on the climate, reducing climate-related hazards and natural disasters, linking to Target 13.1. This study establishes that sustainable operations result in CE practices.
4.3 Linking I-4.0, sustainable operations and CE practices to specific SDGs
This study proposes a unique framework (see Figure 6) depicting a strong linkage among I-4.0, CE practices through sustainable operations and select SDGs. It is observed that the select technologies under I-4.0, namely IoT and AM, etc. support the objective of the ReSOLVE model leading to sustainability of operations leading to CE. Schroeder et al. (2019) find linkages between sustainability and CE, analyzing CE practices with a focus on the SDGs. Their study explores the relevance of CE practices for implementing the SDGs in the context of developing countries and links CE practices with select SDGs for establishing strong linkages between CE and SDGs. This study also depicts the CE practices resulting in select SDGs (“SDG 6: clean water and sanitation,” “SDG 7: affordable and clean energy,” “SDG 9: industry, innovation and infrastructure,” “SDG 12: responsible consumption and production” and “SDG 13: climate action”).
4.4 ISOCES framework
The study comprises a systematic literature review of selected articles indexed in Scopus for identifying the linkages between I-4.0 technologies and CE. I-4.0 and CE are the critical dimensions in recent years driving industry and academia (Alcayaga et al., 2019; Rosa et al., 2020; Suárez-Eiroa et al., 2019). An organization's sustainable operations are environmentally friendly when resource consumption exceeds resource regeneration and pollution does not exceed the environment's ability to absorb pollution (Toffel, 2014). I-4.0 involves a group of technologies like “IoT,” “simulation,”, “Internet of Service (IoS),” “cloud-based manufacturing,” “big data analytics,” “radio frequency identification (RFID)” focused on the digital transformation and interconnection across all production units in a given economic system (Aulawi and Amin, 2019; Cai et al., 2014; Lasi et al., 2014; Lin et al., 2011; Nascimento et al., 2019; Pacchini et al., 2019; Rezaee et al., 2017; Wilson et al., 2020). These technologies provide knowledge on machines, production and flow of material, integrating the information that helps in effective managerial decision-making and organizational competitiveness (Agaram, 2019; Lu, 2017; Meski et al., 2020; Romano et al., 2010; Tan et al., 2012; Sanya and Shehab, 2014; Zablith et al., 2016). The adoption of I-4.0 supports the usage of renewable energy and raw material to retain and restore the health of ecosystem and biosphere. Further, the I-4.0 adoption advocates the reuse and enhances maintainability and durability of resources which can be shared across business functions and even between organizations. The waste in the supply chain can be optimized through automation and big data analytics by adopting modern technologies. The recycling and extracting of biochemicals from organic waste can develop a closed loop system. In a closed loop system, organizations can cut-short the supply chain by reaching out to customer and virtualizing subscription-based models along with applying and exchanging the old system of manufacturing with technologies such as 3D printing. Hence, the study proposes as follows:
I-4.0 technologies can facilitate in achieving the objectives of the ReSOLVE framework.
CE is a new business model that replaces the “end of life concept” with reuse and eliminates waste organizations through better material design, assisting society in moving toward sustainable development (MacArthur, 2013; McDowall et al., 2017; Okorie et al., 2018; Powell et al., 2020). CE offers organizations innovative ways to minimize resource usage, waste management through disposal and recycling, leading to sustainable production and consumption (de Sousa Jabbour et al., 2018; Dantas et al., 2021). It provides economic, environmental and social benefits through a circular approach to energy and materials (Geissdoerfer et al., 2017; 2018). Countries like China, Japan and some European countries have implemented incentives related regulations to promote CE practices (de Sousa Jabbour et al., 2018; Ghisellini et al., 2016). This study has identified linkages between the adoption of I-4.0 and sustainable operations supported by the ReSOLVE framework (de Sousa Jabbour et al., 2018). The elements of the ReSOLVE framework focus on transforming our throwaway economy into one where waste is eliminated to the maximum; resources are fully circulated and nature is regenerated. In a way, the components of ReSOLVE facilitate to tackle the climate change and loss of biodiversity while fulfilling social needs. In short, the ReSOLVE framework offers opportunities to create more jobs, resilience and prosperity while reducing the greenhouse gas emissions, pollution and waste. Hence, the study proposes as follows:
The elements of the ReSOLVE framework are essential to achieve circular economy in most of aspects.
Past literature highlights the significant barriers like a lack of awareness about a product's life cycle, inadequacy of advanced technologies for cleaner production and uncertainty about costs, returns on investments and implementation timelines in the overall adoption of CE in an organization and across value chains (Geng and Doberstein, 2008; de Sousa Jabbour et al., 2018; Su et al., 2013). The practices and models of CE have a direct impact on a few SDGs. For instance, the focus on regenerating the biosphere can ensure the availability of water and sanitation for all. Additionally, focus on renewables and renewables flow management can help in future to have access to clean, reliable and sustainable energy. The activities related to recycling and remanufacturing of CE impact the sustainable industrialization and lead to innovative ideas in that direction. Sharing and enhancing the use of products can have an impact on consumption and production patterns, which can help to address a variety of environment challenges. The integration of novel technologies, namely I-4.0 and circular business models are critical in achieving the select SDGs (Dantas et al., 2021). Therefore, the study proposes as follows:
The CE practices have a direct influence on select 6, 7, 9, 12 and 13 SDGs.
This study is unique as it strengthens and extends the connections between I-4.0 technologies and CE and leading to the achievement of select SDGs. It is the first study to conduct an in-depth and systematic review of the literature and mapping the links across I-4.0, CE and sustainability.
5. Contributions of the study
This study contributes to the body of knowledge on I-4.0, sustainable operations and CE mapping the linkages to specific SDGs by:
Creating an original conceptualization of strong linkages between the adoption of I-4.0 technologies and sustainable operations. This study highlights the role of AM, IoT, real-time monitoring in advancing their business operations in multiple ways (Rezaee et al., 2017; Verdouw et al., 2018; Wu et al., 2020; Zhao et al., 2018). This can help management to identify and re-examine the suitable technologies under I-4.0 to implement the CE practices within their organizations.
Developing a theoretical understanding of sustainable operations, resulting in CE practices. The systematic literature review has helped in the identification of strong linkage between the adoption of select technologies under I-4.0 and CE's sustainable operations and practices, depicting a vital role in adopting I-4.0 in the context to CE's sustainable operations environment (Carnabuci and Operti, 2013; DePalma et al., 2020).
Deriving an integrated framework for linking the practices of CE practices to select SDGs, namely “SDG 6: clean water and sanitation,” “SDG 7: affordable and clean energy,” “SDG 9: industry, innovation and infrastructure,” “SDG 12: responsible consumption and production,” and “SDG 13: climate action.” It is in line with the guidelines of SDGs suggested by the UN Developmental Program (Galvão et al., 2018; Verdouw et al., 2018; Zhou et al., 2020).
It identifies that there are implications related to re-aligning an organization's management practices with the proposed framework may contribute positively to the resultant sustainable operations, thereby achieving the select SDGs.
6. Limitations and future research
As with all research, this study has limitations, which also offer directions for future research. First, the data were collected from journal articles and literature published in the Scopus database, excluding conference publications and books. Some relevant databases remained outside the study's scope; therefore, future studies may collect data from other databases like Web of Science, Proquest, EbscoHost, or individual search engines like Google Scholar to analyze more studies leading to different conceptualizations. Moreover, the data collected with some specific keywords from the Scopus database were limited to research published in the English language only. Future research may use different keywords and studies published in other languages for more comprehensive results. The framework presented in this study is purely based on existing and published literature. Therefore, there is a need for substantial empirical work through a large-scale survey or a case study for statistical validation of the proposed framework. Future studies could test the propositions to validate their linkage. Additionally, the future research may include in-depth analysis of specific aspects of and linkage between CE and the SDGs while selecting more or all SDGs to extend and build on this exploratory review.
7. Conclusion
This study aimed to bridge a gap in the literature at the intersection between I-4.0 and sustainable operations in line with the ReSOLVE framework proposed by MacArthur (2015b), leading to CE practices and select SDGs. The literature review recognized 76 published articles and conceptual models related to this study's research theme, using systematic review methodology. Several models were scrutinized in terms of their components and relationships, resulting in a concise ISOCES framework. Further, the study has identified the relationship between sustainable operations and CE practices like reducing wastages in resource usage and remanufacturing of products. Finally, the study also depicted the CE practices resulting in select SDGs (“SDG 6: clean water and sanitation,” “SDG 7: affordable and clean energy,” “SDG 9: industry, innovation and infrastructure,” “SDG 12: responsible consumption and production,” and “SDG 13: climate action”). The proposed ISOCES framework herein represents the first attempt to “an in-depth and systematic review of the literature” integrating I-4.0, CE and SDGs to map the linkages among them.
Figures
Industry 4.0 technologies
| Technologies | Description | Citation sources |
|---|---|---|
| Internet of things | The technology enables sensors, computers and human devices to communicate wirelessly, allowing data to be accessed anywhere. It can be viewed as a highly complex and widely distributed networked system made up of many smart objects that produce and consume information | Ahuett-Garza and Kurfess (2018), Pacchini et al. (2019), Pang et al. (2015), Zhang et al. (2016), Jang and Yu (2017) and Schott et al. (2020) |
| Big data analytics | It deals with large quantities of structured and unstructured data from several sources for application in predictive analytics, data mining and others for which helps in effective decision-making | Gilchrist (2016), Vaidya et al. (2018) and Guo and Zhang (2013) |
| Cloud computing | It facilitates remote access by providing a quick response to data stored elsewhere and offers various services over the Internet | Zhong et al. (2017a, b), Pacchini et al. (2019), Figueroa et al. (2016), Divya Sahithi et al. (2020), Chen (2010) and Sun et al. (2018) |
| Autonomous robots | Autonomous robots are intelligent, flexible and cooperative machines that interact with each other capable of performing tasks in the world by themselves, without explicit human control | Bekey (2005) and Pacchini et al. (2019) |
| Additive manufacturing | Additive manufacturing is a disruptive innovation based on manufacturing parts of products without dedicated, sophisticated tools. It is the process of joining materials to create a 3D model from a digital design, which helps to shorten development lead times and link designers, engineers and users | Holmström et al. (2016), de Sousa Jabbour et al. (2018), Powell et al. (2020) and Ravichandran et al. (2020) |
| Cyber-physical systems | CPS is a technological computing system that integrates cyberspace, physical processes, sensing, controlling to communicate between machines and components in the production line. It helps collect data on production order prioritization, task optimization and identifying maintenance needs on a real-time basis that allows decision-making | Agaram (2019), Ahmadov and Helo (2018), Lee et al. (2015), Neethirajan et al. (2017), Loh et al. (2018), Sharpe et al. (2018), Moisan (2010) and Pattuelli and Miller (2015) |
| Augmented reality | Augmented reality is a technology that allows users to combine real and virtual worlds, interact in real-time and accurately register virtual and real objects in three dimensions. It also gives the employees real-time data to help them make better decisions and function more efficiently | Alhogail (2020), Choudhary et al. (2011), Vaidya et al. (2018), Wu et al. (2013) and Banda-Sayco (2020) |
I-4.0 Technologies and CE practices
Note(s): Circular economy practices – REDS: redesign; REDU: reduce; RECO: recover; RECY: recycle; REUS: reuse; WTE: waste to energy; IDS: industrial Symbiosis; REG: regenerate; SH: share; L: Loop; VI: virtualize; EX: exchange; CBM: circular business models; REM: remanufacturing; REE: resource efficiency; LCM: life cycle management; DIS: disassembly; DT: digital transformation; SS: smart services; REL: reverse logistics; REEN: renewable energy; RET: rethink; REF: refuse; REP: repair; REFU: refurbish and REPU: repurpose. I-4.0 Technologies – IoT: Internet of Things; CPS: cyber-physical systems; CC: cloud computing; CM: cloud manufacturing; AM: additive manufacturing; BDA: big data analytics; SIM: simulation; AI: artificial intelligence; ARO: autonomous robots; ARE: augmented reality, RFID: radio frequency identification; BC: blockchain; HPM: high-performance microchips and NAN: Nanotechnology
Search string
| Industry 4.0 | Circular economy | UN sustainable development goals |
|---|---|---|
| “Industry 4.0” | “circular economy” | “UN Sustainable Development Goals” |
| “Internet of things” | “Circular business model” | “SDGs” |
| “IoT” | “Remanufacturing” | “No poverty” |
| “Additive manufacturing” | “Resource Recovery” | “Zero hunger” |
| “Smart manufacturing” | “Recycling” | “Good health and well-being” |
| “Cyber-Physical System” | “Reuse” | “Quality education” |
| “augmented reality” | “Environmental sustainability” | “Gender equality” |
| “3D printing” | “Sustainable supply chain” | “Clean water and sanitation” |
| “Knowledge based system” | “Green Logistics” | “Affordable and clean energy” |
| “Communication system” | “Decent work and economic growth” | |
| “Smart Factory” | “Industry, innovation and infrastructure” | |
| “Reduced inequalities” | ||
| “Sustainable cities and communities” | ||
| “Responsible consumption and production” | ||
| “Climate action” | ||
| “Life below water” | ||
| “Life on land” | ||
| “Peace, justice and strong institutions” | ||
| “Partnerships for the goals” |
Quality assessment criteria
| No | Question |
|---|---|
| 1 | Is this a research article or is it merely “lessons learned” report based on expert opinion? |
| 2 | Is there a clear purpose of research? |
| 3 | Is the context is same with the research being carried out? |
| 4 | Was the research design adequate to address the research purpose? |
| 5 | Was the respondent selection was appropriate for conducting the research? |
| 6 | Was there a control group to compare the treatment? |
| 7 | Was data collection done in a way to address research issue? |
| 8 | Was the data analysis was rigorous enough? |
| 9 | Was the relationship among researcher and participants considered to an appropriate degree? |
| 10 | Were the findings stated clearly? |
| 11 | Whether study presents any value for research or practice? |
Quality assessment of primary papers
| Code | Research | Purpose | Context | Design | Respondent selection | Control | Collection of data | Analysis | Reflexivity | Findings | Value | Overall |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| P1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P2 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P3 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P4 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |
| P5 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P6 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |
| P7 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P8 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P9 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 1 |
| P10 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P11 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P12 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P13 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P14 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P15 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P16 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |
| P17 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |
| P18 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P19 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P20 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 1 |
| P21 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P22 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P23 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P24 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |
| P25 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P26 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P27 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P28 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P29 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P30 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |
| P31 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P32 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 1 |
| P33 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P34 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P35 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P36 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P37 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P38 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P39 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P40 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P41 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P42 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P43 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P44 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P45 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 1 |
| P46 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P47 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P48 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P49 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P50 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P51 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P52 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P53 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |
| P54 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P55 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 1 |
| P56 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P57 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P58 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P59 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |
| P60 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |
| P61 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P62 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P63 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P64 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P65 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P66 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P67 | 1 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P68 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 1 |
| P69 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P70 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P71 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |
| P72 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P73 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P74 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P75 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
| P76 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |
Abbreviations
| I-4.0 Technologies | CE practices |
|---|---|
|
|
Publications by year
| Journal Title | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | Total |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Advances in Science, Technology and Engineering Systems | 1 | 1 | 2 | |||||||||
| Advances in Technology Innovation | 1 | 1 | ||||||||||
| Business Process Management Journal | 1 | 1 | ||||||||||
| Decision Support Systems | 1 | 1 | 2 | |||||||||
| Digital Signal Processing: A Review Journal | 1 | 1 | ||||||||||
| Engineering Economics | 1 | 1 | ||||||||||
| Enterprise Information Systems | 1 | 1 | 2 | |||||||||
| IEEE Communications Standards Magazine | 1 | 1 | ||||||||||
| IEEE Transactions on Engineering Management | 1 | 1 | ||||||||||
| IET Networks | 1 | 1 | ||||||||||
| Industrial Management and Data Systems | 1 | 1 | ||||||||||
| Information and Management | 1 | 1 | ||||||||||
| International Journal of Applied Systemic Studies | 1 | 1 | ||||||||||
| International Journal of Business and Management Science | 1 | 1 | ||||||||||
| International Journal of Computer Information Systems and Industrial Management Applications | 1 | 1 | ||||||||||
| International Journal of Enterprise Information Systems | 1 | 1 | ||||||||||
| International Journal of Healthcare Information Systems and Informatics | 1 | 1 | ||||||||||
| International Journal of Innovation Science | 1 | 1 | ||||||||||
| International Journal of Intelligent Information Technologies | 1 | 1 | ||||||||||
| International Journal of Precision Engineering and Manufacturing | 1 | 1 | ||||||||||
| International Journal of Production Economics | 1 | 1 | ||||||||||
| International Journal of Production Research | 2 | 2 | 1 | 1 | 1 | 1 | 8 | |||||
| International Journal of Scientific and Technology Research | 1 | 3 | 4 | |||||||||
| Journal of Advanced Manufacturing Technology | 1 | 1 | ||||||||||
| Journal of Civil Engineering and Management | 1 | 1 | ||||||||||
| Journal of Cleaner Production | 1 | 3 | 2 | 5 | 11 | |||||||
| Journal of Decision Systems | 1 | 1 | ||||||||||
| Journal of Information Technology | 1 | 1 | ||||||||||
| Journal of Japan Industrial Management Association | 1 | 1 | ||||||||||
| Journal of Knowledge Management | 1 | 1 | ||||||||||
| Journal of Management in Engineering | 1 | 1 | ||||||||||
| Journal of Manufacturing Technology Management | 1 | 1 | 1 | 3 | ||||||||
| Journal of Product Innovation Management | 1 | 1 | ||||||||||
| Knowledge-Based Systems | 1 | 3 | 2 | 1 | 1 | 8 | ||||||
| MIS Quarterly | 1 | 1 | ||||||||||
| Personal and Ubiquitous Computing | 1 | 1 | 1 | 3 | ||||||||
| Strategic Management Journal | 1 | 1 | ||||||||||
| Systems | 1 | 1 | ||||||||||
| Technology in Society | 1 | 1 | ||||||||||
| TEM Journal | 1 | 1 | ||||||||||
| VINE Journal of Information and Knowledge Management Systems | 2 | 2 | ||||||||||
| Total | 4 | 5 | 3 | 4 | 7 | 5 | 3 | 9 | 8 | 8 | 20 | 76 |
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Further reading
Li, G., Hou, Y. and Wu, A. (2017), “Fourth Industrial Revolution: technological drivers, impacts and coping methods”, Chinese Geographical Science, Vol. 27 No. 4, pp. 626-637.
Corresponding author
About the authors
Dr Vishal Singh Patyal is Faculty in Decision Sciences area at Indian Institute of Management Visakhapatnam and prior to that he was associated with NTPC School of Business (NSB) Noida and National Institute of Construction Management and Research, Pune. He is Fellow (PhD) in Operations Management from National Institute of Industrial Engineering (NITIE) Mumbai. His research interests include sustainable supply chain management, sustainable transportation, quality management, multi-criteria decision-making and statistical modeling. He has published his work in various scholarly peer-reviewed international journals and conferences.
Dr P.R.S. Sarma is currently associated with the Production and Operations Management area as an Associate Professor in Indian Institute of Management Visakhapatnam, India. Prior to joining he was working with Indian Institute of Management Raipur. Dr Sarma has PhD and MBA from Indian Institute of Technology, Delhi in the Department of Management Studies. Dr Sarma has more than 20 years of wide and varied Industry experience in the field of ICT in lean production systems, project execution, etc. He has visited more than 30 countries in connection with project executions including Austria, Algeria, Bangladesh, Benin, Botswana, Burkina-Faso, Denmark, Egypt, France, Ghana, Ivory-coast, Japan, Kenya, Kingdom of Saudi Arabia, Latvia, Malaysia, Mauritius, Morocco, Nepal, Norway, Russia, Singapore, Sri Lanka, Syria, Sweden, Togo, Tunisia and the USA. His research has been published in reputed journals namely, International Journal of Logistics Management, Journal of Cleaner Production, Production Planning and Control (PPC), Journal of Global Information Management and Business Process Management Journal etc.
Dr Sachin Modgil received the BSc degree (physics, chemistry and mathematics) from the Himachal Pradesh University, Shimla, India in 2003; the MBA degree in operations management from the Thapar Institute of Engineering and Technology (TIET), Patiala, India in 2010 and the FPM (PhD) degree in technology and operations management from the National Institute of Industrial Engineering, Mumbai, India in 2016. He is currently Assistant Professor with International Management Institute, Kolkata, India.
Professor Tirthankar Nag received BE in Electrical Engineering from Jadavpur University, India in 1996 and FPM (PhD) from Indian Institute of Ahmedabad, India in 2005. He has been a consultant for companies in the energy and water space on behalf of PWC, KPMG and SBICAPS, dealing with strategy, policy and regulatory advisory. Professor Nag teaches strategic management, research methods, managing consulting engagements and developing infrastructure businesses. He has been teaching as a visiting faculty for doctoral courses in the energy sector at IIM Ahmedabad and strategic management at IIM Calcutta. He has authored a book and several book chapters and peer-reviewed papers in international journals. He is currently associated as professor and dean (research and international relations) with International Management Institute, Kolkata, India.
Dr. Denis Dennehy is Associate Professor of Business Analytics at the School of Management, Swansea University, Wales, UK. His research primarily focuses on the mediating role of emerging technologies and analytics, in the context of information systems and its implications for people, organisations and society. This research has been published in leading journals including International Journal of Operations and Production Management; European Journal of Operational Research, Information Systems Frontiers, Information and Management, Information Technology and People, International Journal of Production Research, Government Information Quarterly, Journal of Systems and Software, and IEEE. He is a senior editor of Information Technology and People and has chaired many conferences in the field of information systems.