Sustainable industrial and operation engineering trends and challenges Toward Industry 4.0: a data driven analysis

Tseng, Ming‐Lang; Tran, Thi Phuong Thuy; Hà, Hiền Minh; Bui, Tat-Dat; Lim, Ming K.

doi:10.1080/21681015.2021.1950227

Cited by 212 publications

(123 citation statements)

References 76 publications

Supporting

Mentioning

121

Contrasting

Unclassified

Order By: Relevance

“…Nevertheless, challenges exist in building DSCs due to the accuracy of the information, but the required data need to be collected from various sources. Therefore, to achieve sustainable development, a wellestablished SC should be extended to the application of digital technology and integrated into a firm's SC [15,17,25]. Hence, there is a need for firms to reimagine their SC process as a DSC network to reach development goals.…”

Section: Digitalization In Supply Chainmentioning

confidence: 99%

A Cause and Effect Model for Digital Sustainable Supply Chain Competitiveness under Uncertainties: Enhancing Digital Platform

et al. 2021

Self Cite

View full text Add to dashboard Cite

This study provides insights into digitalization in sustainable supply chain management by establishing a structural set of attributes with causal interrelationships among them, as well as by reporting empirical findings on successful criteria for footwear supply chain practices in Indonesia. Sustainable supply chain management and digitalization are mutual benefits. However, there are unclear cause and effect interrelationships. This study aims to critically pinpoint digitalization to approach sustainability and is designed to help firms achieve supply chain competitiveness. The fuzzy Delphi method and fuzzy decision-making trial and evaluation laboratory are utilized, due to the fuzziness associated with human decision making and the complexity and uncertainty in the supply chain. Five aspects and seventeen criteria are validated. The findings indicate that four aspects, including digital platform effectiveness, digital communication belonging to the supply chain digitalization perspective, labour conditions, and manufacturing processes, are important to sustainable supply chain management. The top causal criteria, including logistics integration, logistics optimization, delivery speed, proactive action, and real-time inventory, are considered to assist firms in implementing better practices.

show abstract

Section: Digitalization In Supply Chainmentioning

confidence: 99%

A Cause and Effect Model for Digital Sustainable Supply Chain Competitiveness under Uncertainties: Enhancing Digital Platform

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…Other recommendations have also been developed according to the considered industrial sector, such as the ones developed for the textile industry, for avoiding "overuse of resources, waste generation, environmental pollution and unethical labour condition" [76]. In the same way, the bibliometric analysis of Tseng et al [77] shows that Industry 4.0 allows the company to avoid such waste but also to ensure "a safe and secure environment that encourages more ethical and moral behaviors that can increase sustainability through mutual cooperation". However, the authors underline that even if "the socio-ethical features of CPSs .…”

Section: Ethics In Industrymentioning

confidence: 99%

Industrial Performance: An Evolution Incorporating Ethics in the Context of Industry 4.0

et al. 2021

View full text Add to dashboard Cite

This article addresses the issue of the industrial performance model and its evolution to cope with the context of Industry 4.0. With its digitalisation, intelligent/autonomous systems and wealth of data, Industry 4.0 offers opportunities that can achieve objectives better. It also presents risks and uncertainties that question the autonomy of the systems, their interaction with humans and the use of available data. The hypothesis put forward in this work is that the efficiency–effectiveness–relevance performance triangle can no longer guarantee long-term performance under these conditions and needs to be associated with an ethical dimension that allows for the risks and uncertainties relating to Industry 4.0 to be considered. Ethics is therefore considered to extend the triangle to a tetrahedron. A brief analysis of current performance management will first show the limits of the current practice in the context of Industry 4.0. The frameworks that could overcome these limits in light of new needs are then recalled and discussed, leading to the choice of ethics, whose main definitions and use in the engineering field are also introduced. The proposed (efficiency–effectiveness–relevance–ethics tetrahedron-based methodology is illustrated through a case study related to an aeronautical supplier, regarding the consequences of the implementation of a MES (Manufacturing Execution System) in terms of product traceability and operator autonomy. The discussion and prospects finally conclude this study.

show abstract

“…In particular, Feil et al [2] emphasized that product quality acts as a motivator to strengthen consumers' SCI because of the benefit of health improvements. In different studies, other product features, such as availability and variety, have been found to affect consumption intention to purchase the product [7,30]. These works indicate the importance of economic considerations in consumption intentions.…”

Section: Sustainable Product Purchasing Featuresmentioning

confidence: 91%

How Is the Sustainable Consumption Intention Model in Food Industry under Preference Uncertainties? The Consumer Willingness to Pay on Recycled Packaging Material

et al. 2021

Self Cite

View full text Add to dashboard Cite

Food packaging is costly to consumers and generates a huge volume of packaging waste, especially in Indonesia. Prior studies have neglected to construct a causal sustainable consumption intention model in food industry and link to the consumer willingness to pay under preference uncertainties. To address the gaps, this study explores consumer attributes to build a causal sustainable consumption intention model and takes the model to address the consumer willingness to pay under preference uncertainties. This study proposes a causal model that integrates five aspects of sustainable consumption intention model: (1) sustainable consumption knowledge, attitudes, and behaviors; (2) government policy and regulation on sustainable consumption; (3) recycled packaging eco-labeling certification; (4) supply chain innovation and infrastructure; and (5) sustainable product purchasing features. This study uses the fuzzy Delphi method to confirm the reliability and validate the criteria and applies cause and effect model to address the causal model. In addition, this study collects 428 valid responses to address the willingness to pay for causal sustainable consumption intention model and a cognitive best-worst choice experiment to confirm the model in the food industry. The result reveals that recycled packaging eco-labeling certification is the major aspect for enhancing the model, followed by government policy and regulation and supply chain innovation and infrastructure. In practice, consumers incur inconvenience in purchasing sustainable food products but prefer recycled packaging material at a standardized price.

show abstract

Sustainable industrial and operation engineering trends and challenges Toward Industry 4.0: a data driven analysis

Cited by 212 publications

References 76 publications

A Cause and Effect Model for Digital Sustainable Supply Chain Competitiveness under Uncertainties: Enhancing Digital Platform

A Cause and Effect Model for Digital Sustainable Supply Chain Competitiveness under Uncertainties: Enhancing Digital Platform

Industrial Performance: An Evolution Incorporating Ethics in the Context of Industry 4.0

How Is the Sustainable Consumption Intention Model in Food Industry under Preference Uncertainties? The Consumer Willingness to Pay on Recycled Packaging Material

Contact Info

Product

Resources

About