Papers by Yiğit Kazançoğlu
International journal of food science & technology, Mar 17, 2024
Lecture notes in mechanical engineering, 2024
Journal of Cleaner Production, Dec 31, 2023
Lecture notes in mechanical engineering, Oct 1, 2023
Sustainability, Sep 24, 2023
Business Strategy and The Environment, Jan 29, 2022
International journal of logistics, Apr 7, 2021
E3S web of conferences, 2023
ISAHP proceedings, Dec 1, 2020
Technological Forecasting and Social Change, Nov 1, 2021
Abstract Prior research and practices of Industry 4.0 mostly centered on the intelligent transfor... more Abstract Prior research and practices of Industry 4.0 mostly centered on the intelligent transformation of the manufacturing industry from a technical perspective. However, it remains unclear how social and environmental factors can improve companies' performance in their digital transformation under Industry 4.0. Our research addresses this gap by exploring how companies undergoing digital transformation can leverage their relationship capital and green management initiatives to improve their financial performance, benefiting the entire supply chain. Specifically, we developed a conceptual model that captures the relationship between supply chain relationship capital, enterprise green management, and financial performance and used structural equation modeling and SPSS PROCESS to empirically test the hypotheses with data collected from 308 Chinese manufacturing companies. The findings indicate that for companies in the digital transformation of Industry 4.0, supply chain relationship capital positively affects enterprise green management, which subsequently enhances financial performance. Meanwhile, supply chain relationship capital also indirectly improves companies’ financial performance by leveraging their green management initiatives. Our findings contribute to the literature by enriching the implications of relational capital in supply chains and strengthening the viability of green management. We also provide practical guidance for companies to effectively implement green management programs and exploit their relationship capital.
Journal of Cleaner Production, Apr 1, 2021
Information Systems Frontiers
Industrial revolutions often seek to strengthen the separation of human and machine labor by goin... more Industrial revolutions often seek to strengthen the separation of human and machine labor by going one step further, toward automation and digitalization, and the transfer of tough and dangerous occupations to robots. As it strives to include robots in people's daily activities and work, the introduction of concepts such as I5.0 is a step forward in enhancing human-machine interaction and provides some possibilities and challenges for firms. Therefore, this article mainly focuses on studying and concretely examining the challenges faced by businesses transitioning from I4.0 to I5.0 by providing case examples from the textile and apparel supply chain. After a detailed review of the current literature related to the I5.0 challenges, the I5.0 challenges were listed in general. Then, the fuzzy Decision-making trial and evaluation laboratory approach has adopted into the challenges to reveal causal interactions between them thus, prioritizing the substantial challenges to be focused on to influence the entire textile and apparel supply chain.
Lecture notes in mechanical engineering, 2023
Annals of Operations Research
Journal of Business Research
Clean Technologies and Environmental Policy, 2020
Sustainable Production and Consumption, 2021
Annals of Operations Research, 2021
Advances in smart technologies (Industry 4.0) assist managers of Micro Small and Medium Enterpris... more Advances in smart technologies (Industry 4.0) assist managers of Micro Small and Medium Enterprises (MSME) to control quality in manufacturing using sophisticated data-driven techniques. This study presents a 3-stage model that classifies products depending on defects (defects or non-defects) and defect type according to their levels. This article seeks to detect potential errors to ensure superior quality through machine learning and data mining. The proposed model is tested in a medium enterprise—a kitchenware company in Turkey. Using the main features of data set, product, customer, country, production line, production volume, sample quantity and defect code, a Multilayer Perceptron algorithm for product quality level classification was developed with 96% accuracy. Once a defect is detected, an estimation is made of how many re-works are required. Thus, considering the attributes of product, production line, production volume, sample quantity and product quality level, a Multilayer Perceptron algorithm for re-work quantity prediction model was developed with 98% performance. From the findings, re-work quantity has the highest relation with product quality level where re-work quantities were higher for major defects compared to minor/moderate defects. Finally, this work explores the root causes of defects considering production line and product quality level through association rule mining. The top mined rule achieves a confidence level of 80% where assembly and material were identified as main root causes.
Sustainable Development, 2020
Circular economy is a contemporary concept including usage of renewable materials and technologie... more Circular economy is a contemporary concept including usage of renewable materials and technologies. The transition to the circular economy creates value through closed‐loop systems, reverse logistics, eco‐design, product life cycle management, and clean production. The aim of the study was to propose a holistic conceptual framework for barriers of circular supply chain for sustainability in the textile industry. Within this aim, an in‐depth literature review on barriers was conducted by covering all supply chain stages and circular initiatives in textile industry. Then, a focus group study was implemented. In the focus group study, barriers related to supply chains that prevent companies to implement the circular economy were discussed and validated. As a result, a total of 25 barriers were classified under nine main categories such as (a) management and decision‐making, (b) labour, (c) design challenges, (d) materials, (e) rules and regulations, (f) lack of knowledge and awareness,...
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Papers by Yiğit Kazançoğlu