Barriers for green supplier development programs in manufacturing industry

Bai, Chunguang; Şatır, Ahmet

doi:10.1016/j.resconrec.2020.104756

Cited by 75 publications

(57 citation statements)

References 58 publications

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“…DEMATEL is a preferred technique over AHP, TISM, ISM, or any MCDM techniques as it divides challenges into cause and effect group and indicates the severity of their effects also ( Singh et al., 2019 ). Policymakers can get observations with a quantifiable and ocular kinship among challenges through matrices or diagraphs ( Bai and Satir, 2020 ). It has a wide range to respond as (0, 1, 2, 3, and 4) to explore the cause-effect relationship among the challenges.…”

Section: Methodsmentioning

confidence: 99%

Application of industry 4.0 technologies in SMEs for ethical and sustainable operations: Analysis of challenges

Kumar

Singh

Dwivedi

2020

Journal of Cleaner Production

341

180

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In the era of Industry 4.0 and circular economy, small and medium enterprises (SMEs) are under huge pressure to make their manufacturing operations ethical and sustainable. Business with ethical and sustainable operations has become the need of the day in the present environment of Industry 4.0 and circular economy. It has been observed that the application of Industry 4.0 technologies may help in achieving the goal of ethical and sustainable operations. Although a lot of research has been done in context to larger enterprises, limited research is available on the application of Industry 4.0 technologies in SMEs for ethical and sustainable operations. The espousal of Industry 4.0 technologies is a challenging task for SMEs due to various operational and financial constraints. The problem is more acute, specifically in context to developing countries like India. Keeping in mind the role of technologies in ethical business and circular economy, we have identified fifteen challenges, impacting the application of Industry 4.0 technologies in SMEs. A questionnaire was designed for collecting the response from industry and academic experts. On the collected data, the DEMATEL approach has been applied to check the degree of influence and interrelationship among challenges. It has also helped in the categorization of factors as cause and effect. Sensitivity analysis is also performed to validate the results obtained from the DEMATEL approach. Authors have observed that lack of motivation from partners and customers on the application of I4.0 technologies is the leading challenge. Fear of failure of I4.0 technologies is the main effect group challenge. The findings of the study will help SMEs in formulating strategies for implementing Industry 4.0 technologies for ethical and sustainable business processes.

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Section: Methodsmentioning

confidence: 99%

Application of industry 4.0 technologies in SMEs for ethical and sustainable operations: Analysis of challenges

Kumar

Singh

Dwivedi

2020

Journal of Cleaner Production

341

180

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“…Most of the papers reviewed were based on empirical data (76%), including survey (32 papers; e.g., Rogers et al, 2019; Tong et al, 2012), case studies (27 papers; e.g., Karp, 2005; Yawar & Seuring, 2018), secondary data (public reports or databases; 3 papers; e.g., Lalwani et al, 2018; Tate et al, 2012) and a mix of methodologies (e.g., survey and cases study and modelling and case study; 9 papers; e.g., Bai & Satir, 2020; Zhu et al, 2007; Table 4). Eighteen papers were based on literature reviews (19%).…”

Section: Resultsmentioning

confidence: 99%

“…From these papers, keywords were identified and tested using the Scopus database. Recent publications found in the searching process were also considered to confirm the keywords (e.g., Bai & Satir, 2020; Lo et al, 2018; Yawar & Seuring, 2018). Moreover, to encompass a representative number of materials more closely related to the research question, two sets of keywords in line with environmental and social sustainability and supplier development (‘sustainab*’, ‘environment*’, ‘social responsibility’, ‘supply chain’, collaborat* and ‘supplier development’) were used to construct search strings.…”

Section: Research Approachmentioning

confidence: 99%

Supply chain environmental and social sustainability practice diffusion: Bibliometrics, content analysis and conceptual framework

Pimenta

Ball

Salonitis

2021

Corp Soc Responsibility Env

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The purpose of this paper is to uncover how environmental and social sustainability practices are diffused across the supply chain tiers through supplier development initiatives. In particular, the work seeks to uncover the initiatives developed directly or indirectly by manufacturing firms and the factors that enhance them. A systematic literature review is used to examine the breadth of the sustainable supply chain literature. The papers obtained are screened and analysed using established procedures to

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“…Let φij be connection weights and εi be thresholds. The genetic codes can be obtained as (φ 2 11, φ 2 6). The code length is L=N1*N2+N2*1+N2+1.…”

Section: Figure 5 the Vector Model Of Multi-layer Bpnnmentioning

confidence: 99%

“…More than half of them have their own learning and living space. With the differentiation of the furniture market, there is a growing demand for children's furniture [1][2][3]. Under the premise of practicality, the design of children's furniture must fully consider the special cognition and preference of children, highlight environmental friendliness and health, and benefit the physical and mental development of children [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

An Evaluation Model for Green Manufacturing Quality of Children’s Furniture Based on Artificial Intelligence

Huang¹

2020

IJDNE

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With the differentiation of the furniture market, there is a growing demand for children’s furniture. The design of children’s furniture must fully consider the special cognition and preference of children, highlight environmental friendliness and health, and benefit the physical and mental development of children. These design objectives are similar to those of green furniture. Therefore, it is necessary to accurately evaluate the quality of green manufacturing, the key link of green furniture production, with the aid of the excellent data processing technique of artificial intelligence (AI). Thus, this paper summarizes the AI applications in quality testing of children’s furniture and statistical analysis on its greenness, and constructs an evaluation model for green manufacturing quality of children’s furniture. Firstly, the authors introduced the architecture of the green manufacturing system for children’s furniture, and analyzed the product lifecycle and environmental pollutions. On this basis, a complete and scientific evaluation index system (EIS) was constructed. Next, the weight coefficients of the goal layer and criteria layer were determined by the entropy method, and the initial evaluation result were provided. Finally, a comprehensive evaluation model was established for the green manufacturing quality of children’s furniture, based on backpropagation neural network (BPNN), and genetic algorithm with adaptive mutation (AMGA). The proposed EIS and model were proved effective through experiments. The research results provide a reference for the quality evaluation in other fields.

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Barriers for green supplier development programs in manufacturing industry

Cited by 75 publications

References 58 publications

Application of industry 4.0 technologies in SMEs for ethical and sustainable operations: Analysis of challenges

Application of industry 4.0 technologies in SMEs for ethical and sustainable operations: Analysis of challenges

Supply chain environmental and social sustainability practice diffusion: Bibliometrics, content analysis and conceptual framework

An Evaluation Model for Green Manufacturing Quality of Children’s Furniture Based on Artificial Intelligence

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