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1 – 4 of 4Andrei Bonamigo, Andrezza Nunes, Lucas Ferreira Mendes, Marcela Cohen Martelotte and Herlandí De Souza Andrade
This study aims to examine the impact of Lean 4.0 practices on value co-creation in the dairy ecosystem.
Abstract
Purpose
This study aims to examine the impact of Lean 4.0 practices on value co-creation in the dairy ecosystem.
Design/methodology/approach
Data collection were carried out through a questionary application with 126 professionals linked to the dairy ecosystem, including milk producers, milk cooperatives and milk transporters. The data were analyzed using Cluster Analysis, Mann-Whitney test and Chi-Square test.
Findings
A strong relation was found between the use of Lean 4.0 tools and the increase in operational performance, in addition to milk quality. Moreover, it can be noted that the use of digital technologies from Industry 4.0 has a strong relation with dairy production optimization, in other words, it is possible to be more efficient in the dairy process via Lean 4.0 adoption.
Research limitations/implications
The study is limited to analyzing the Brazilian dairy ecosystem. The results presented may not reflect the characteristics of the other countries.
Practical implications
Once the potential empirical impacts of the relation between Lean 4.0 and value co-creation are elucidated, it is possible to direct strategies for decision-making and guide efforts by researchers and professionals to deal with the waste mitigation present in the dairy sector.
Social implications
Lean 4.0 proves to be a potential solution to improve the operational performance of the dairy production system. Lean 4.0, linked to value co-creation, allows the integration of the production sector with consumers, through smart technologies, so new services and experiences can be provided to the consumer market. Additionally, the consumer experience can be stimulated based on Lean 4.0, once the quality specification is highlighted based on data science and smart management control.
Originality/value
To the best of the authors’ knowledge, this is the first study that analyzes the interrelationship between the Lean 4.0 philosophy and the value co-creation in the dairy ecosystem. In this sense, the study reveals the main contributions of this interrelation to the dairy sector via value co-creation, which demonstrates a new perspective on the complementarity of resources, elimination of process losses and new experiences for the user through digital technologies integrated with the Lean Thinking approach.
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Vishal Ashok Wankhede, Rohit Agrawal, Anil Kumar, Sunil Luthra, Dragan Pamucar and Željko Stević
Sustainable development goals (SDGs) are gaining significant importance in the current environment. Many businesses are keen to adopt SDGs to get a competitive edge. There are…
Abstract
Purpose
Sustainable development goals (SDGs) are gaining significant importance in the current environment. Many businesses are keen to adopt SDGs to get a competitive edge. There are certain challenges in realigning the present working scenario for sustainable development, which is a primary concern for society. Various firms are adopting sustainable engineering (SE) practices to tackle such issues. Artificial intelligence (AI) is an emerging technology that can help the ineffective adoption of sustainable practices in an uncertain environment. In this regard, there is a need to review the current research practices in the field of SE in AI. The purpose of the present study is to comprehensive review the research trend in the field of SE in AI.
Design/methodology/approach
This work presents a review of AI applications in SE for decision-making in an uncertain environment. SCOPUS database was considered for shortlisting the articles. Specific keywords on AI, SE and decision-making were given, and a total of 127 articles were shortlisted after implying inclusion and exclusion criteria.
Findings
Bibliometric study and network analyses were performed to analyse the current research trends and to see the research collaboration between researchers and countries. Emerging research themes were identified by using structural topic modelling (STM) and were discussed further.
Research limitations/implications
Research propositions corresponding to each research theme were presented for future research directions. Finally, the implications of the study were discussed.
Originality/value
This work presents a systematic review of articles in the field of AI applications in SE with the help of bibliometric study, network analyses and STM.
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