Modelling and analysing the impact of Circular Economy; Internet of Things and ethical business practices in the VUCA world: Evidence from the food processing industry

D. Jinil Persis, V.G. Venkatesh, V. Raja Sreedharan, Yangyan Shi and Bathrinath Sankaranarayanan
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D. Jinil Persis: NITIE - National Institute of Industrial Engineering [Mumbai]
V.G. Venkatesh: Métis Lab EM Normandie - EM Normandie - École de Management de Normandie = EM Normandie Business School
V. Raja Sreedharan: UIR - Université Internationale de Rabat
Yangyan Shi: SXU - Shanxi University, Macquarie University [Sydney]

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Abstract: As the business ecosystem is very becoming volatile with uncertainty accompanied with poor process centric practices leading to complexity and contributing to ambiguous decision making. Such a scenario constitutes a Volatile, Uncertain, Complex and Ambiguous world known as VUCA world. To manage the business in VUCA world, companies have started adopting emerging technologies such as Circular Economy (CE) and Internet of Things (IoT). These technologies combined with a proactive decision-making process promote Ethical Business Practices (EBP) that can lead a sustainable business operation in the market. Therefore, the present study assesses the impact of CE; IoT and EBP (CE-IoTEBP) in the food processing industry. Here, the factors that are influencing the company's preference towards the CE-IoTEBP were analysed. Further to evaluate CE-IoTEBP, an evaluation model was developed. Using, Churchill approach, exhaustive list of factors (79 factors) relevant to the model were identified. Then, Ant colony optimisation was used to reduce the number of factors (39 factors) to make the model robust and apt for the evaluation of CE-IoTEBP. This was followed by using the Fuzzy ANN system for classifying the factors based on the level of contributions to assess the level of adoption intention of CE-IoTEBP in the industry. Through, fuzzy decoding (FANN) the final value for the CE-IoTEBP adoption intention was obtained. Additionally, this research proposes a deployment model for evaluating the CE-IoTEBP in the food processing industry to improve the low contributing factors. The use of Ant Colony Optimisation (ACO) method makes the decision making significantly robust and the ANN system improves its efficiency. The deployment model can be a reference for both academicians and practitioners to emulate in different industries.

Date: 2021-06-10
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Published in Journal of Cleaner Production, 2021, 301, pp.126871. ⟨10.1016/j.jclepro.2021.126871⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05013799

DOI: 10.1016/j.jclepro.2021.126871

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