Addressing the Challenges to Sustainable Initiatives in Value Chain Flexibility: Implications for Sustainable Development Goals
TL;DR: In this article, the authors proposed a framework for challenges to sustainable initiatives in value chain flexibility and an integrated model is developed to identify the potential challenges to sustainability initiatives in the value chain.
Abstract: The value chain refers to the source of competition to facilitate organizations to maximize and sustain value for their consumers. Value chain flexibility is necessary to build sustainable initiatives in addressing ambiguity. In the literature, there is a lack of framework to highlight the challenges to sustainable initiatives in value chain flexibility. This study fills this research gap by suggesting a framework for challenges to sustainable initiatives in value chain flexibility. In this study, thirteen potential challenges to sustainable initiatives in value chain flexibility are identified and an integrated model is developed. It adopts the modified Total Interpretive Structure Model and the Cross-Impact Matrix Multiplication Applied to Classification methodology. The mixed approach is used as the modified Total Interpretive Structure Model organizes the binary interactions among the challenges, while Cross-Impact Matrix Multiplication Applied to Classification analysis organizes specific precise assessments of the driving power and dependence of the challenges. The results of the study reflect that (i) lack of supplier commitment to sustainable products and (ii) lack of knowledge toward sustainability in value chains are the challenges that achieved the highest driving power. The challenge ‘inadequate communication among the suppliers in the value chain’ is at the highest level in the analysis. The proposed framework could help government and non-government bodies to formulate policies to efficiently address challenges to sustainable initiatives in value chain flexibility.
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TL;DR: In this article , the authors considered 35 indicators related to the economic SDGs (SDG 7, SDG 8, SDD 9, SDGs 11 and SDG 12) considering available data from 27 European countries in order to identify an aggregate value of sustainability in accordance with the multicriteria analysis.
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TL;DR: In this article , the authors propose a reference model for service-based collaboration processes among digital innovation hubs (DIHs) based on their service portfolio analysis and support the modelling of Collaborative Networks 4.0, in which DIHs are a strategic player.
Abstract: Abstract Nowadays, to remain competitive, manufacturing companies must address the Industry 4.0 paradigm, particularly the cyber-physical system (CPS) revolution, following sustainable challenges. Digital innovation hubs (DIHs), as ecosystems that provide technical knowhow, experimental skills, and specialist knowledge, are progressively gaining a strategic role in supporting such a transition, especially in European small and medium enterprises (SMEs). Several projects have been funded by the European Commission to support the growth and action of DIHs. However, which among the four main functionalities (networking, skills and training, test before investing, and access to funding) each DIH is capable of addressing in its daily support action to companies is still unclear. Thus, it is important to configure the service portfolios of DIHs (i.e. the set of services that each DIH can provide based on its characterising assets, knowledge, and capabilities). In this paper, the data-driven business–ecosystem–skills–technology (D-BEST) reference model is proposed and then tested through a survey. The model triggers the identification and materialisation of service-based collaboration processes among DIHs based on their service portfolio analysis and supports the modelling of Collaborative Networks 4.0, in which DIHs are a strategic player because of their ‘by-design’ innovation characteristics. Finally, through the extended adoption of the models developed by different emerging DIH networks, flexibility and interoperability can be reached, fostering the adoption of a unique digital platform to showcase and offer assets, triggering the creation of multiple inter- and intra-communications and collaborations among stakeholders belonging to the DIH ecosystems, and favouring the exchange and development of joint services.
19 citations
TL;DR: In this article , the authors developed a model to investigate the influence of TQM and I4.0 on sustainability performance of ready-made garment (RMG) industries in Bangladesh.
Abstract: Abstract Business organizations may be able to improve their Sustainability Performance (SP) by adopting Total Quality Management (TQM) concepts combined with Industry 4.0 (I4.0) technologies. This research has developed a model to investigate the influence of TQM and I4.0 on SP. It also analyzes the mediating role of TQM in the relationship between I4.0 and SP. A survey was conducted among 240 respondents employed in ready-made garment (RMG) industries in Bangladesh. A Structural Equation Modelling (SEM) technique was used to analyze the collected data. Research findings show that both TQM and I4.0 technologies have a significant impact on the sustainable growth of the Bangladeshi RMG sector. Moreover, it is observed that TQM mediates the relationship between I4.0 and SP. The findings show that TQM helps to explain the relationship between I4.0 and sustainable performance. This study will provide a guideline for industrial executives on securing sustainability through the adoption of TQM concepts and I4.0 technologies. We are not aware of any additional studies that look at the possible link between TQM, I4.0, and SP, as well as the mediating role of TQM between I4.0 and SP.
18 citations
TL;DR: In this paper , a multi-criteria decision analysis (MCDA) is presented to compare the sustainability of 103 Italian cities through the evaluation of 45 SDGs indicators, ranking cities on the base of their performance.
17 citations
TL;DR: In this article , the authors discuss Industry 4.0 and its Flexible Manufacturing System (FMS) capability and its practices for improving FMS performance are studied, and then several flexible approaches using Industry4.0 technologies are discussed.
Abstract: The implementation of Industry 4.0 technologies has improved the flexibility of the entire manufacturing system. These technologies are the Internet of Things (IoT), big data, Artificial Intelligence (AI), Additive Manufacturing (AM), advanced robotics, virtual reality, cloud computing, simulation, and among others, have arisen to improve the flexibility in the entire manufacturing system. Industry 4.0 is becoming recognised as a unique industrial paradigm. It is predicated on the widespread adoption of communication and information technology, which would lead to improved organisational performance and flexibility. The incorporation of Industry 4.0 is the true game-changer in terms of flexibility and customisation. Manufacturers may utilise this technology to build digital twins of items used by consumers in the real world. The digital twin gets real-time information from sensors on the actual objects. Manufacturers benefit from digital twin and simulation technology, including predictive maintenance and making errors easier and faster to rectify. This paper discusses Industry 4.0 and its Flexible Manufacturing System (FMS) capability. Different dimensions and technologies of Industry 4.0 Practices for improving FMS performance are studied,d and then discusses several flexible approaches using Industry 4.0 technologies are. One of the most significant benefits of adopting virtual infrastructure maintained by a service provider is improved flexibility. Cloud services allow auto-scaling, which means that the underlying computer resources automatically adjust to changing utilisation rates. Industry 4.0 increases production flexibility, allowing a facility to respond to market changes quickly. A plant control system automatically varies output depending on shifting utility rates, lowering production costs. Industry 4.0 offers some incredible benefits and has gone a long way in the last several years.
17 citations
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TL;DR: The literature available on IT in SCM has been classified using suitable criteria and then critically reviewed to develop a framework for studying the applications of IT inSCM and some future research directions are indicated.
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TL;DR: In this article, the authors applied a qualitative case study design involving 26 semi-structured interviews with leading members of firms, including chief digital officers and chief executive officers, and found that management desire to increase control and enable real-time performance measurement is a significant driving force behind Industry 4.0, alongside production factors.
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TL;DR: In this paper, the authors identify key challenges to Industry 4.0 initiatives and analyze the identified key challenges in order to prioritize them for effective Industry4.0 concepts for supply chain sustainability in emerging economies.
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TL;DR: This paper is an attempt to interpret the links in the interpretive structural models using the tool of Interpretive Matrix and leads to evolve the framework and methodology of totalinterpretive structural modeling (TISM).
Abstract: Interpretive structural modeling (ISM) is a process that transforms unclear and poorly articulated mental models of systems into visible, well-defined models useful for many purposes. The interpretation of links is comparatively weak in ISM; the interpretation of the directed link in terms of how it operates is lacking. This paper is an attempt to interpret the links in the interpretive structural models using the tool of Interpretive Matrix and leads to evolve the framework and methodology of total interpretive structural modeling (TISM). First, an overview of ISM is provided. This is taken-up further by highlighting the need of interpretation of interpretive structural models. In order to evolve the framework of TISM, the tool of Interpretive Matrix is briefly introduced, which is integrated into the methodology of TISM. The basic process of TISM is presented in a step-by-step manner with indicative directions for scaling-up this process. Some tests for validating total interpretive structural models are also proposed. Finally, the basic process of TISM is illustrated with the help of an example in the context of organizational change. This process can be used for conceptualization and theory building in organizational research.
489 citations