A proposed hierarchical framework for Prioritizing Industry 4.0 technologies to improve environmental performance of manufacturing companies and environmental SDGs

Badroos, Ywana Maher Lamey Article A proposed hierarchical framework for Prioritizing Industry 4.0 technologies to improve environmental performance of manufacturing companies and environmental SDGs Cogent Business & Management Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Badroos, Ywana Maher Lamey (2024) : A proposed hierarchical framework for Prioritizing Industry 4.0 technologies to improve environmental performance of manufacturing companies and environmental SDGs, Cogent Business & Management, ISSN 2331-1975, Taylor & Francis, Abingdon, Vol. 11, Iss. 1, pp. 1-23, https://doi.org/10.1080/23311975.2024.2422561 This Version is available at: https://hdl.handle.net/10419/326661 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Cogent Business & Management ISSN: 2331-1975 (Online) Journal homepage: www.tandfonline.com/journals/oabm20 A proposed hierarchical framework for Prioritizing Industry 4.0 technologies to improve environmental performance of manufacturing companies and environmental SDGs Ywana Maher Lamey Badroos To cite this article: Ywana Maher Lamey Badroos (2024) A proposed hierarchical framework for Prioritizing Industry 4.0 technologies to improve environmental performance of manufacturing companies and environmental SDGs, Cogent Business & Management, 11:1, 2422561, DOI: 10.1080/23311975.2024.2422561 To link to this article: https://doi.org/10.1080/23311975.2024.2422561 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 01 Nov 2024. Submit your article to this journal Article views: 824 View related articles View Crossmark data Citing articles: 2 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oabm20 Accounting, corporAte governAnce & Business ethics | reseArch Article Cogent Business & ManageMent 2024, VoL. 11, no. 1, 2422561 A proposed hierarchical framework for Prioritizing Industry 4.0 technologies to improve environmental performance of manufacturing companies and environmental SDGs Ywana Maher lamey Badroos accounting Department, Faculty of Commerce, tanta university, tanta, egypt ABSTRACT this study draws insights from the dynamic capabilities theory about industry 4.0 and sustainability as critical issues for maintaining firms’ competitiveness in international markets. there is still a scarcity of literature about the environmental impacts of adopting industry 4.0 technologies (i4.0t) and their contribution towards enhancing environmental management accounting systems and attaining sustainable development goals (sDgs). Although companies’ managers are aware of environmental issues which have forced them to adopt i4.0t, they hesitate to invest in these technologies because of limited financial resources. the research objectives are exploring the positive environmental impacts of i4.0t and their contribution towards the environmental sDgs and developing a hierarchical framework to prioritize i4.0t. to achieve these objectives, three phases of research methodology were followed. First, we review the extant literature to identify commonly utilized i4.0t, their positive environmental impacts, and their contribution towards attaining sDgs. second, a hierarchical framework using an analytical hierarchical process was proposed. third, the proposed framework is applied to five leather firms to test its applicability. the findings indicate that waste management is the most important environmental aspect, and the internet of things is the most important technology, followed by big data and cloud computing technologies. this study offers significant theoretical and practical implications, and significant opportunities for future research. 1. Introduction industries face many challenges in meeting customer demands and minimizing negative social and environmental impacts (pour et al., 2023). the business world witnessed many industrial revolutions that resulted in significant technological changes, such as the Fourth industrial revolution ‘industry 4.0’ (i4.0). however, it also has negative environmental impacts that result in paying significant attention to ep (Bai et al., 2020). recently, companies’ managers are aware of environmental issues such as climate change, resource scarcity, and pollution, which have forced companies to work on corporate social and environmental responsibility, set proactive environmental strategies such as pollution prevention, eco-efficiency, product development, and corporate social responsibility, and adopt appropriate environmental management accounting (eMA) systems to enhance their environmental performance (ep) and attain a sustained competitive advantage (Bresciani, 2022; solovida & latan, 2017). eMA is considered a valuable tool to provide environmental accounting information (eAi) about material, energy, and water usage, emissions, and waste resulting from firms’ activities. eAi is required for implementing different environmental strategies and supporting managers to make decisions (nguyen, 2022). so, it is confirmed that eMA systems can overcome the limitations of conventional management © 2024 the author(s). Published by informa uK Limited, trading as taylor & Francis group CONTACT Ywana Maher Lamey Badroos [email protected]  accounting Department, Faculty of Commerce, tanta university, tanta 31521, egypt. https://doi.org/10.1080/23311975.2024.2422561 this is an open access article distributed under the terms of the Creative Commons attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. the terms on which this article has been published allow the posting of the accepted Manuscript in a repository by the author(s) or with their consent. ARTICLE HISTORY received 4 February 2024 revised 18 July 2024 Accepted 18 october 2024 KEYWORDS industry 4.0 technologies; environmental management accounting; environmental accounting information; corporate social responsibility; circular economy; analytical hierarchical process; sustainable developments goals SUBJECTS Accounting; Management Accounting; corporate social responsibility & Business ethics 2 Y. M. l. BADroos accounting, quantify environmental issues for making decisions, and support organizations in achieving sustainable competitive advantage (Burritt & schaltegger, 2010). Although organizations implement eMA systems to improve their ep, these systems do not provide sufficient real-time eAi to help managers in their decision-making process, as stated by solovida and latan (2017), Deb et al. (2023), and gunarathne et al. (2023). consequently, companies consider the importance of the transition towards i4.0 to modify eMA systems and provide real-time eAi, as recommended by luoma et al. (2023) and chen and hao (2022). i4.0 was introduced by the german government in 2011 (chiarini, 2021), involving integrated technologies such as the internet of things (iot), cyber physical systems (cps), cloud computing (cc), big data and analytics (BDA), additive manufacturing (AM), virtual reality (vr) and augmented reality (Ar), intelligent robotics, and simulation (Beltrami et al., 2021; Jamwal et al., 2021). recently, the environmental impacts of industry 4.0 technologies (i4.0t) have gained significant attention, such as resource efficiency, reduction of pollution levels, waste, and emissions (el Baz etal., 2022; Malik et al., 2024). regarding the potential impacts of i4.0t adoption on sustainability dimensions, i4.0t can contribute to the achievement of sustainable development goals (sDgs). Kluczek etal. (2023) and indana and pahlevi (2023) highlighted that Agenda 2030 has 17 goals, 169 targets, and 231 indicators. only sDgs 7, 8, 12, and 13 will be the focus of this study, as they are related to ep. this study focuses on addressing the potential impacts of i4.0t adoption on manufacturing companies’ ep for several reasons. First, significant attention is currently paid to ep owing to the consequences of industrialization, such as air and water pollution, emissions, and waste generation (Malik et al., 2024). second, chen et al. (2020) stated that manufacturing companies are required to prioritize environmental impacts’ reduction because they contribute more than 35% of co2 emissions and utilize one-third of the energy on a large scale. third, the application of eMA systems could not provide sufficient real-time eAi to support companies’ managers in making decisions and improving their ep. Moreover, the intersection of ep and digitalization, involving the availability and utilization of eAi to modify eMA systems, has received significant attention (cardinali & De giovanni, 2022; chen & hao, 2022; luoma etal., 2023; nguyen, 2022). Fourth, Brozzi etal. (2020) stated that manufacturing companies prioritize economic aspects over environmental issues. in addition, oláh et al. (2020) and Maisiri et al. (2021) have referred to the negative environmental impacts resulting from adopting i4.0t, such as increasing resource usage and emissions. therefore, the environmental impacts of i4.0t remain unclear and require further research (chen & hao, 2022). Fifth, understanding the impact of adopting i4.0t on ep is crucial for managers, especially when capital investment decisions are made (Bai et al., 2020) given limited financial resources (hughes et al., 2022). thus, it can be concluded that i4.0t should be prioritized based on its impact on manufacturing companies’ ep to adopt the most crucial technologies within a reasonable environmental budget. Although the literature addresses the relationship between i4.0 and ep, it remains unclear due to the following reasons: First, Khan and gupta (2023); solovida and latan (2017); and gunarathne et al. (2023) only explored the conventional role of eMA systems in enhancing ep. to modify eMA systems and set appropriate environmental strategies, the environmental impacts of adopting i4.0t should be investigated. second, oláh et al. (2020), sartal et al. (2020), ghobakhloo (2020), Brozzi et al. (2020), and Bai et al. (2020) highlighted i4.0 as a general concept rather than as an umbrella of many diversified technologies. third, because of the novelty of i4.0t, some authors have reported that the impacts of i4.0t on ep may be positive (Jena etal., 2020; Mourtzis etal., 2020; tozanli etal., 2020) or negative (chiarini, 2021; nascimento etal., 2019). consequently, the environmental impacts of i4.0t adoption are still unclear and require further research. Fourth, Kluczek et al. (2023) and indana and pahlevi (2023) only demonstrated the connection between i4.0 and sustainability at the industry level. Fifth, there is a scarcity of literature regarding the contribution of individual i4.0t toward attaining the sDgs. sixth, due to the novelty of the i4.0 context, no studies have attempted to identify the intensity of the influence of each technology on the manufacturing firms’ ep. therefore, further research is required to identify this influence through the use of multi-criteria decision-making (McDM) tools. According to the above discussion, two research questions have been raised. First, what are the positive impacts of adopting i4.0t on the ep of manufacturing firms? second, to what extent does the selected i4.0t impact the manufacturing firms’ ep? Accordingly, the research objectives of this study are to identify the positive environmental impacts of the most commonly utilized i4.0t in the cogent Business & MAnAgeMent 3 literature and to use analytical hierarchical process (Ahp) to develop a hierarchical framework to prioritize i4.0t. Additionally, this study focuses on dynamic capabilities theory (Dct) to identify and prioritize the environmental impacts of i4.0t in the setting of manufacturing companies. the Dct offers insights into how the adoption of new dynamic capabilities can enhance a firm’s ep (teece, 2007). it can be noted that technological innovation like i4.0t can act as a dynamic capability, supporting firms to enhance their ep. to fill the research gaps and achieve the research objectives, the related literature review is studied and analyzed to explore only the positive environmental impacts of adopting i4.0t and to what extent these technologies contribute to the environmental sDgs (7, 8, 12, and 13) that will be presented in section 2.3 for answering the first research question. then, to answer the second research question, a proposed hierarchical framework using Ahp is constructed to rank i4.0t according to their relative importance toward enhancing ep, which will be presented in section 3.2. then, a case study methodology is utilized to assess the applicability of the proposed framework to a manufacturing company, which will be presented in section 4. the main contribution of this study is summarized as follows: first, this study answers the call of several scholars for more research on the environmental impacts of i4.0t adoption to enhance the understanding of the relationship between i4.0t and ep, extending the role of eMA in enhancing firms’ ep; second, this study sheds light on how i4.0t adoption contributes to the sDgs agenda; and third, this study provides a novel framework for prioritizing i4.0t, aiding academics and practitioners to undertake substantial investments to adopt i4.0t, particularly for manufacturing companies with limited financial resources. the rest of the paper is organized as follows: the theoretical background and literature review are presented in section 2. section 3 presents the research methodology and proposed hierarchical framework. A case study is conducted in section 4. the study’s findings are discussed and summarized in section 5. Finally, conclusions, theoretical and practical implications, limitations, and future research are outlined in section 6. 2.Theoretical background and literature review this section presents the building blocks that support our investigation and provides a comprehensive exploration of fundamental concepts. reviewing the literature aims at outlining the connection between i4.0t and ep of manufacturing companies, considering dynamic capability theory (Dct). this section starts with a general background about Dct, i4.0t, and the impact of adopting i4.0t on manufacturing companies’ ep and their contribution towards attaining environmental sDgs. 2.1. Theories foundation there are few studies that consider theories and viewpoints such as practice-based view (Bag et al., 2021b; Kamble & gunasekaran, 2023), Dct (Kamble & gunasekaran, 2023), and eMt (tang etal., 2024). Dct is utilized by several researchers, particularly for making strategic choices or decisions in the light of different business scenarios (Bag etal., 2021b). thus, to achieve the research objectives, it is relevant to consider Dct as a theoretical framework to identify and prioritize the environmental impacts of i4.0t in the setting of manufacturing companies. teece (2007) stated that dynamic capabilities help firms address the challenges and issues associated with achieving the firms’ sustainable goals. in the current study, i4.0t is considered as a set of valuable organizational resources providing a significant capability to integrate products and production processes. thus, i4.0t acts as a dynamic capability that provides the ability to build and integrate internal and external competencies to cope with rapid changes in the business environment. lahti etal. (2018) referred to the high implementation costs and uncertainty of adopting i4.0t. therefore, the main objective of the current study is to advance the literature about Dct by identifying the potential impact of new dynamic capabilities such as i4.0t on firms’ ep. 4 Y. M. l. BADroos 2.2. Environmental performance in manufacturing scope ep is gaining significant attention because of external regulations and stakeholder demands. customers desire environmentally friendly products, investors ask for more transparency and eAi, and regulators seek compliance with environmental regulations. Furthermore, these external pressures force manufacturing firms to adopt sustainable environmental strategies and implement eMA systems to enhance their ep (luoma etal., 2023; nguyen, 2022). gunarathne et al. (2023) referred to the role of the eMA in managing, measuring, and improving companies’ operating aspects to improve their ep and facilitate eAi collection and communication to support managers’ decision-making processes. latifah and soewarno (2023) stated that eMA systems provide eAi about pollution and emissions from production and transportation, resource usage, renewable energy utilization, waste management, and circular economy practices (cep) that are examples of ep aspects. According to Dct, the literature reveals the role of technology in improving the ep of manufacturing companies and modifying their eMA systems. Jabbour etal. (2018) and Brozzi et al. (2020) claimed that i4.0t offers significant environmental benefits through providing efficient solutions for controlling emissions, saving resources, and real-time monitoring. therefore, understanding the relationship between i4.0t and ep is worthwhile, which is explored in the following section. 2.3. Environmental impacts of industry 4.0 technologies adoption the first industrial revolution began in the 18th century with mechanical factories, followed by the ‘era of Mass production’ in the 1870s utilizing electricity in industrial processes (Malik et al., 2024; ng et al., 2022) and the ‘Digital revolution’ in the 1970s utilizing ‘electronics and information technology’ (Öztemel & gürsev, 2018). the german government introduced i4.0 in 2011 as a high-technology strategy, with the first application proposal developed by the i4.0 Working group in 2013 (oláh et al., 2020; Öztemel & gürsev, 2018). therefore, i4.0 is not a sudden revolution because its appearance was based on previous revolutions. the various stages of the industrial revolution’s progression are shown in Figure 1. i4.0 has gained significant attention from academic researchers. the alignment between i4.0 and firms’ strategic goals is essential to modify the eMA system through providing real-time eAi and improve their Figure 1. stages of industrial revolutions (Source: the author). cogent Business & MAnAgeMent 5 ep, as stated by Zheng et al. (2021) and latifah and soewarno (2023). According to Dct, ghobakhloo et al. (2021) defined i4.0 as the integration of new technologies in manufacturing processes to ensure real-time connections between people, machines, and objects. i4.0t are known as technology trends, which are a set of advanced technologies that are considered the building blocks of manufacturing firms. Although the literature highlights the ep of manufacturing firms in the i4.0 context, consensus on the environmental impacts of adopting technologies remains unclear (Malik et al., 2024; nascimento et al., 2019). the study by stock and seliger (2016) is the first to highlight the role of i4.0t in promoting ep. Adopting i4.0t results in optimizing resource usage (Jena etal., 2020), utilizing renewable energy, reducing waste and emissions (Brozzi et al., 2020; ching et al., 2022), and providing real-time eAi to modify the eMA system and set appropriate environmental strategies (hanif etal., 2023; indana & pahlevi, 2023). some studies have indicated a linkage between i4.0 and cep. Jabbour et al. (2018) proposed a road map to enhance ep through cep adoption. cep is adopted to improve ep by transitioning from a linear model to a maximized resource usage model, which also plays an essential role in attaining the sDgs (especially target 12.5) set by the united nations in the Agenda 2030 for sustainable Development (Dorado et al., 2022). Alayón et al. (2017) recommended reusing, recycling, and remanufacturing (3 r) practices to optimize production, reduce waste, emissions, and resource usage. chen et al. (2020) introduced a 6 r methodology (reuse, recycle, remanufacture, reduce, recover, and redesign) to maximize resource utilization. Additionally, Khan et al. (2021) referred to the role of BD analytics, cps, and AM technologies in supporting cep, like reusing waste generation during the manufacturing stage or recovering energy from scraps or rejections, which in turn enhance ep. Due to the novelty of the i4.0 context, this study focuses on Dct to identify the most utilized technologies in the literature to investigate their positive impacts on the ep of manufacturing firms such as iot/cps, BDA, cc, AM, simulation/digital twin, vr/Ar, and intelligent robotics on environmental aspects like resource usage, waste management, emissions and pollution, and cep. Furthermore, it is critical to present the contribution of each i4.0 technology toward attaining environmental sDgs (7, 8, 12, and 13) as presented in Figure 2. A summary of the literature review related to these technologies is shown in table 1 and analyzed as follows: 2.3.1. Internet of Things and cyber physical system Based on Dct, Zhou et al. (2016) and Beier et al. (2020) stated that the adoption of iot technologies improves ep through reducing resource usage, waste generation, and emission releases. Jamwal et al. (2021) and oláh et al. (2020) referred to the role of iot in facilitating transparency in manufacturing processes via real-time monitoring of resource usage to help production management and facilitate necessary improvements. As stated by chen etal. (2020), Beltrami etal. (2021), and ghobakhloo (2020), iot/ cps platforms enhance resource efficiency by enhancing communication with suppliers and customers, promoting eco-design, customizing products, reducing transportation frequency, and scheduling manufacturing resources flexibly. consequently, the reduction of materials, energy, and water usage, substitution of hazardous or chemical resources, promotion of cep, and reduction of waste and emissions can be achieved. Also, iot enables real-time data acquisition through sensors or rFiD tags, enabling manufacturers to monitor resource usage, waste, and emissions, set proactive environmental strategies, and make relevant decisions (Jamwal et al., 2021; vrchota et al., 2020). sartal et al. (2020) stated that smart machines facilitate monitoring and predicting machine failures, enabling preventive and predictive maintenance, and resource efficiency, and waste reduction. Furthermore, iot/cps platforms enhance transparency, traceability, resource monitoring, and enabling closed-loop systems to reduce waste (Malik et al., 2024), and promoting reusing or recycling materials to optimize resource usage (Mastos et al., 2021). 2.3.2. Big data and analytics and cloud computing BDA is a computing technology that analyzes vast amounts of data, enabling real-time monitoring of resource usage and predictive maintenance to avoid waste generation, breakdowns, or unscheduled downtimes and extend the life span of machines (indana & pahlevi, 2023). uriarte-gallastegi et al. (2022) asserted that BDA enables manufacturing firms to track production processes to avoid 6 Y. M. l. BADroos overproduction and reduce resource usage and waste generation. According to Beier et al. (2020), adoption of BDA and cc technologies results in reduction of resource usage, waste generation, and emission releases. Based on Dct, it was argued by Bonilla et al. (2018) and stock et al. (2018) that integration of iot/cps with BDA results in increasing renewable energy usage to meet increasing demand for energy and enhance ep. regarding cloud computing, it is a key enabler for adopting other technologies (Jamwal etal., 2021). cloud computing can be combined with BDA to store data gathering until it is analyzed by BDA tools (chen etal., 2020). As stated by Öztemel and gürsev, (2018), cloud computing significantly reduces toxic material usage through real-time data support, thereby increasing the use of environmentally friendly materials. Figure 2. Potential environmental impacts of industry 4.0 technologies and their linkage with sDgs (Source: the author). cogent Business & MAnAgeMent 7 BDA and cc can promote cep by utilizing real-time data. Based on Dct, these technologies can reduce resource usage and waste generation through reusing, recycling, and reducing materials and products, thereby reducing pollution and emissions (Beltrami et al., 2021; chiarini, 2021). 2.3.3. Additive manufacturing According to Dct, AM technology adoption has positive environmental impacts like reducing resource usage and enabling closed-loop material flows (Jamwal et al., 2021), reducing product weight, time-tomarket, waste, and emissions (ghobakhloo et al., 2021). Bonilla et al. (2018) and oláh etal. (2020) highlighted the role of AM in decreasing transportation and carbon footprints by purchasing the right quantity of raw materials and decentralizing production geographically for customers. Additionally, the adoption of AM technology promotes cep. uriarte-gallastegi et al. (2022) argued that AM is a relevant technology for reusing or recycling parts or components rather than disposing or replacing them. sartal etal. (2020) confirmed the role of AM technology in promoting cep, improving resource efficiency, and reducing waste generation through product customization. thus, the adoption of AM technology conserves natural resources and reduces emission releases, thereby enhancing ep. 2.3.4. Simulation/digital twin sartal et al. (2020) demonstrated that simulation systems can assess the consequences of changes in manufacturing variables, while Beltrami et al. (2021) highlighted their effectiveness in reducing energy usage and improving processes throughout the virtual simulation of new procedures or maintenance Table 1. a summary of literature review. authors Digital technologies Methodology study’s findings Qualitative Quantitative Resource optimization energy savings emissions reduction Waste reduction Promoting CeP Jena et al. (2020); saudi et al. (2019) iot/CPs, CC Case study ✓ ✓ ✓ ✓ Brozzi etal. (2020) i4.0 survey ✓ ✓ ✓ ✓ Khan et al. (2021) BD, CPs, aM survey ✓ ✓ ✓ Jamwal etal. (2021) i4.0 systematic literature review (sLR) ✓ ✓ ✓ ✓ oláh et al. (2020) i4.0 sLR ✓ ✓ Braccini and Margherita (2018) i4.0 Case study ✓ ✓ santos et al. (2019) iot/CPs, BD Case study ✓ ✓ Chiarini et al. (2020) aM, BD, CPs survey ✓ ✓ ✓ ✓ ✓ Zhang et al. (2019) i4.0 Case study ✓ ✓ nascimento et al. (2019) CPs, aM Case study ✓ ✓ ✓ stock et al. (2018) CPs, aM simulation ✓ ✓ tozanli et al. (2020) iot simulation ✓ Bonilla et al. (2018) i4.0 sLR ✓ ✓ ✓ ✓ ✓ Bag et al. (2021a) i4.0 survey ✓ ✓ ✓ ✓ ✓ Pour et al. (2023) i4.0t Case study and survey (mixed methods) this study proposed an industry 4.0 selection framework that focused on fuzzy analytical hierarchy process (FaHP) to rank different technologies towards enhancing three dimensions of sustainable performance of firms. evans et al. (2013) i4.0t Case study and survey (mixed methods) this study utilized a fuzzy decision tree approach to compute the certainty index for different technologies to rank these technologies and selecting the most suitable tools for implementation. 14 Y. M. l. BADroos Table 5. Comparison among industry 4.0 technologies under each performance aspect. a. Comparison among industry 4.0 technologies under Waste aspect average Weightsiot/CPs BDa CC iot/CPs 1 1 4 0.48 BDa 1 1 2 0.37 CC 0.25 0.5 1 0.15 λ max = 3.09; Ci = 0.04; CR = 0.045 b. Comparison among industry 4.0 technologies under Water aspect average Weightsiot/CPs BDa CC iot/CPs 1 2 5 0.55 BDa 0.5 1 5 0.35 CC 0.2 0.2 1 0.10 λ max = 3.09; Ci = 0.05; CR = 0.056 c. Comparison among industry 4.0 technologies under Material aspect average Weightsiot/CPs BDa CC iot/CPs 1 2 3 0.54 BDa 0.5 1 2 0.30 CC 0.33 0.5 1 0.16 λ max = 3.02; Ci = 0.01; CR = 0.028 d. Comparison among industry 4.0 technologies under emission aspect average Weightsiot/CPs BDa CC iot/CPs 1 4 4 0.66 BDa 0.25 1 2 0.20 CC 0.25 0.5 1 0.14 λ max = 3.03; Ci = 0.015; CR = 0.06 e. Comparison among industry 4.0 technologies under energy aspect average Weightsiot/CPs BDa CC iot/CPs 1 5 4 0.69 BDa 0.2 1 2 0.18 CC 0.25 0.5 1 0.13 λ max = 3.02; Ci = 0.01; CR = 0.07 f. Comparison among industry 4.0 technologies under Circular economy aspect iot/CPs BDa CC average Weights iot/CPs 1 3 4 0.62 BDa 0.33 1 2 0.23 CC 0.25 0.5 1 0.15 λ max = 3.11; Ci = 0.056; CR = 0.01 Table 6. synthesized aHP table for the selected leather tanning companies. importance of level one average Local Weights for Level two average global Weights Waste 0.437 iot/CPs 0.48 0.209 BDa 0.37 0.162 CC 0.15 0.065 Water usage 0.228 iot/CPs 0.55 0.126 BDa 0.35 0.08 CC 0.10 0.022 Material usage 0.078 iot/CPs 0.54 0.042 BDa 0.30 0.024 CC 0.16 0.012 emissions 0.137 iot/CPs 0.66 0.09 BDa 0.20 0.027 CC 0.14 0.02 energy usage 0.04 iot/CPs 0.69 0.028 BDa 0.18 0.007 CC 0.13 0.005 Ce practices 0.079 iot/CPs 0.62 0.048 BDa 0.23 0.018 CC 0.15 0.013 cogent Business & MAnAgeMent 15 Overall Priority of BDA: (. * . ) (. * . ) (. * .) (. * .) (. * . 0437 037 0228 035 0078 03 0137 02 004 0 + +++118 0 079 0 23 0 32 ) (. * . ) . += Overall Priority of CC: (. * . ) (. * . ) (. * . ) (. * . ) (. * 0 437 0 15 0 228 0 10 0 078 0 16 0 137 0 14 0 04 ++++00 13 0 079 0 15 0 14.)(. *.) .+= the final global weights for each technology and their corresponding rankings are presented in table 7. 5. Discussion and results oláh et al. (2020) referred to the importance of achieving sustainability for firms and communities because of the increasing environmental problems. i4.0 and its technologies are gaining popularity because they contribute to sustainable development, maintain organizations’ competitiveness, and capture new markets. Many studies have explored the implications of i4.0, such as the efficient utilization of resources (Bag etal., 2021a), reduction of harmful emissions and waste, and promotion of cep (ghobakhloo etal., 2021). to address the scarcity of literature and respond to the calls of chen and hao (2022), this study focused only on exploring the positive impacts of adopting common technologies in the literature on manufacturing firms’ ep and demonstrated their contribution toward attaining environmental sDgs. to answer the first research question, the findings of the literature review are summarized and presented in Figure 2, which also acts as a reference guide for companies’ manufacturers. consistent with nguyen (2022) and luoma et al. (2023), the study’s findings indicate that adopting i4.0t could provide relevant and real-time eAi to overcome the limitations of eMA systems, set appropriate environmental strategies, support capital investment decisions, and help stakeholders understand companies’ willingness in terms of environmental governance. the findings of this study confirm Dct that demonstrates i4.0t as new dynamic capabilities enhancing firms’ ep. the findings of this study are aligned with the current literature indicating that the adoption of iot/cps (Beltrami etal., 2021; Mabkhot etal., 2021), BDA/cc (gajdzik etal., 2020), and AM (oláh et al., 2020) can achieve sDgs (7, 8, 12, and 13). the adoption of iot/cps (Jena et al., 2020; tozanli etal., 2020), BDA/cc (Mourtzis etal., 2020; uriarte-gallastegi etal., 2022), and AM (nascimento etal., 2019) results in reducing resource usage, waste, emissions, toxic material usage, increasing usage of renewable and clean energy sources, and promoting cep. in addition, the study’s findings revealed that the adoption of simulation/digital twin technologies attains sDgs (8 and12), as presented in Figure 2, which is consistent with the findings of Mourtzis et al. (2020) and Mabkhot et al. (2021). these technologies improve ep by reducing resource usage and waste, as confirmed by chen et al. (2020) and chiarini (2021). Furthermore, the adoption of vr/Ar and intelligent robotics technologies attains sDg 8 and sDg 12 (target 12.4), as asserted by gajdzik et al. (2020). Waste and emission reduction, efficient utilization of resources, and promotion of cep resulted from adopting vr/Ar and intelligent robotics technologies (chiarini, 2021; uriarte-gallastegi etal., 2022). Additionally, manufacturing firms face critical challenges such as limited financial resources, which discourage them from investing in new technologies with uncertain costs or guaranteed returns (ghobakhloo et al., 2021). there is still a scarcity of literature on frameworks that support companies in adopting critical technologies, considering these challenges. therefore, to answer the second research question, this study proposes a hierarchical framework using Ahp, which acts as a reference guide for decision makers and manufacturers to prioritize i4.0t toward enhancing ep and modifying eMA systems. Table 7. overall priority for each industry 4.0 technology. industry 4.0 technology Priority Ranking iot/CPs 54% 1 BDa 32% 2 CC 14% 3 16 Y. M. l. BADroos then, the proposed framework was applied to five leather tanning companies to test the applicability of the proposed framework. According to the interview sessions, the leather companies’ managers decided to adopt iot/cps, BDA, and cc due to their expected environmental benefits. in the light of the Ahp survey, the overall average weights for criteria and alternatives are presented in table 6, and it was found that waste management is the most important performance aspect toward enhancing ep, with a weight of 43.7%. this result agrees with those obtained by chen et al. (2020) and Malik et al. (2024), who stated that reduction of all types of waste (solid or liquid) can enhance ep. According to table 7, iot/cps is the most important technology, with an average global weight of 54%. this result confirms the findings of previous studies (chen etal., 2020; Khan etal., 2021). According to the interviewees’ responses, they expected that adopting iot would result in utilizing resources more efficiently through deploying sensors to monitor each tanning process. As stated by indana and pahlevi (2023), one participant stated that sensors are used for waste management, identifying waste bins and their contents by categories like waste material or chemicals. in addition, sensors can monitor the conditions of the tanning process, such as the heat, temperature, and humidity, as stated by nagy et al. (2018). Moreover, smart sensors can aid real-time pollution monitoring systems to detect excessive pollution levels (chiarini, 2021) or leaks from tanning processes, such as amines, ammonia, and hydrogen sulfide. specifically, as stated by laskurain-iturbe et al. (2021), some participants expected that iot adoption would support reusing or recycling solid and liquid waste generated before becoming unusable. the BDA and cc technologies had global average weights of 32% and 14%, respectively, as presented in table 7. As stated by Jamwal etal. (2021) and uriarte-gallastegi etal. (2022), participants asserted that BDA could reduce environmental risks and optimize resource usage by analyzing a large data pool. in addition, all participants anticipated the BDA’s role in analyzing and predicting environmental problems, enabling real-time data collection, data analysis, and real-time decision-making for monitoring resource usage, emissions, waste generation, and promoting cep, as mentioned by chiarini (2021). consistent with chen et al. (2020) and chiarini (2021), participants confirmed that the data gathered will not lead to a reduction in resource usage or waste generation unless data analytics tools are used to analyze the data gathered and provide decision-makers with real-time eAi. Additionally, participants anticipated the role of cc technology in storing and retrieving environmental data from iot devices during tanning processes. thus, the participants expected the joint contribution of BDA and cc technologies toward enhancing ep. however, this result is not consistent with those obtained by Wang et al. (2015), who stated that cloud services do not align with external data storage. 6. Conclusion, implications, limitations and future research in the 21st century, technological advancements have necessitated manufacturing firms to adapt to changing business environments through transitioning toward i4.0 to address environmental problems resulting from traditional industrial activities (luoma etal., 2023). conventional eMA systems cannot consider environmental problems and should be modified to provide decision-makers with relevant and timely eAi by adopting i4.0t. recently, i4.0 has been considered a technological revolution that has significant environmental benefits, as stated by chen and hao (2022). companies face challenges such as limited financial resources, insufficient management support, and data security, which may hinder their i4.0 transition. high implementation costs and limited financial resources are identified as the most critical barriers (Kumar et al., 2021; prause, 2019), which should be considered before starting the i4.0 transition. literature on the environmental impacts of i4.0t and their contribution to attaining environmental sDgs is limited. Accordingly, this study aims to answer these research questions and identify future research paths by analyzing literature reviews and applying the proposed hierarchical framework. the results of analyzing the literature review are summarized in Figure 2, which would contribute to filling this research gap and answering the first research question by exploring the positive environmental impacts of adopting commonly utilized technologies and their contribution toward attaining the sDgs (7, 8, 12, and 13). cogent Business & MAnAgeMent 17 Additionally, this study underpins the lack of frameworks in the literature that can support manufacturing firms’ managers in making investment decisions in critical technologies. therefore, a novel hierarchical framework is developed in Figure 4 using Ahp to fill this research gap and answer the second research question. subsequently, the proposed framework was applied to five leather-tanning companies. the results revealed that waste management is the most important performance aspect, and iot/cps is the most important technology. Finally, the current study provides significant theoretical and practical implications, which are discussed in the following sections. 6.1. Theoretical implications this study provides significant theoretically implications as follows: first, this study contributes to the existing literature by addressing the ambiguity surrounding the contribution of i4.0t toward modifying eMA systems and enhancing the ep of manufacturing firms by endorsing principles of Dct Besides, the proposed alignment between each technology and the environmental sDgs is an additional theoretical contribution, second, no studies in literature have demonstrated the influence of each i4.0 technology on ep. to the best of our knowledge, this study is the first attempt to propose a hierarchical framework using Ahp to rank i4.0t toward enhancing ep and modifying eMA systems. researchers can use this framework to assess the importance of other technologies that do not exist in the framework, third, the simultaneous adoption of all i4.0t is difficult, thus, the proposed framework aids firm managers in determining the weights of various technologies to make investment decisions regarding their adoption, fourth, the proposed framework enhances its applicability by combining case study and McDM tools, unlike most frameworks in the literature that are validated only through case studies, and fifth, the case study results revealed that iopt/cps, BDA, and cc technologies would enhance the ep of the leather companies. these results vary significantly based on the technology adopted, industry type, and challenges of each firm. 6.2. Practical implications this study analyzes the literature and proposes a framework that provides practical implications. First, the proposed framework acts as a reference guide for practitioners and managers on the environmental impacts of i4.0t and their contribution toward environmental sDgs achievement. practitioners will recognize the significant role of i4.0t in driving sustainable trends within their organizations. second, identifying the major determinants of adopting i4.0t provides opportunities for managers to pay more attention to them. third, the proposed framework can support managers in many ways: (1) the proposed framework shows which technology can improve each environmental aspect, providing valuable insights, particularly for managers in polluting industries. (2) the proposed framework could help decision-makers prioritize and/or re-evaluate investments in i4.0t, considering limited financial resources. (3) the proposed framework can be used by companies in different industries by modifying its components based on their goals and policies. Fourth, public authorities and policymakers have established mechanisms of environmental governance monitoring to encourage firms to make their operations and processes environmentally sustainable and reward firms with modified eMA systems. 6.3. Limitations and future research this study has some limitations and offers opportunities for future research. First, the interrelationships among i4.0t were not considered. therefore, researchers could extend the present study by using an analytical network process to consider the interrelationships among them. second, the results of this study are only valid at the company level. therefore, future research should be conducted at an industrial level. third, future research should consider the impacts of other technologies such as blockchain, artificial intelligence, cybersecurity, and mobile technology. Fourth, future research should consider the cost-benefit analysis of applying the proposed hierarchical framework. 18 Y. M. l. 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BADroos Appendix A interview manuscript. interviewee Questions Managers and head of departments • What are the environmental strategies that are adopted by the firm (for example: pollution prevention, eco-efficiency, product development and corporate social responsibility? • What is eai provided by eMa system? • Does the eMa system adopted in the company provide real-time eai? • What are green practices adopted in the company (for example: natural and biodegradable materials, reduction of water and chemicals usage? • What is industry 4.0 technologies adopted/or in the process of adoption in the company? • in your opinion, what are the expected environmental benefits of industry 4.0 technologies adoption? • in your opinion, what are the potential contributions of industry 4.0 technologies towards environmental sDgs (7,8,12, and 13)? • are there challenges that hinder adoption of industry 4.0 technologies in your company? give me examples. • Does the company adopt circular economy practices like recycling, reducing, or remanufacturing? technologists and engineers • What is the flow of leather tanning processes? • What are the environmental problems resulting from tanning processes? • What industry 4.0 technologies are actually adopted to solve environmental problems? • in your recommendation, what other technologies can be adopted to enhance the company’s environmental performance? Appendix B Comparison among environmental performance aspects. Q1: what is more important environmental performance aspect to enhance environmental performance and modify EMA systems? 98765432123456789 Waste Management Water Usage Waste Management Material Usage Waste Management Emissions Waste Management Energy Usage Waste Management Circular Economy Practices Water usage Material Usage Water usage Emissions Water usage Energy Usage Water usage Circular Economy Practices Material usage Emissions Material usage Energy Usage Material usage Circular Economy Practices emissions Energy Usage emissions Circular Economy Practices energy usage Circular Economy Practices Comparison among industry 4.0 technologies under each Performance aspect. Q2: what is more important to waste reduction? 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 iot/CPs BDa iot/CPs CC BDa CC Q3: what is more important to reduce water usage? 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 iot/CPs BDa iot/CPs CC BDa CC Q4: what is more important to reduce material usage? 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 iot/CPs BDa iot/CPs CC BDa CC cogent Business & MAnAgeMent 23 Q5: what is more important to reduce emission releases? 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 iot/CPs BDa iot/CPs CC BDa CC Q6: what is more important to reduce energy usage? 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 iot/CPs BDa iot/CPs CC BDa CC Q7: what is more important to promote circular economy practices? 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 iot/CPs BDa iot/CPs CC BDa CC