Browsing by Author "Pala, Melisa Ozbiltekin"

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Citation - WoS: 48
Citation - Scopus: 69
A fuzzy based hybrid decision framework to circularity in dairy supply chains through big data solutions
(Elsevier Inc., 2021) Yigit Kazancoglu; Muhittin Saǧnak; Sachin Kumar Kumar Mangla; Muruvvet Deniz Sezer; Melisa Ozbiltekin-Pala; Sezer, Muruvvet Deniz; Pala, Melisa Ozbiltekin; Kazancoglu, Yigit; Sagnak, Muhittin; Mangla, Sachin Kumar
This study determines the potential barriers to achieving circularity in dairy supply chains, it proposes a framework which covers big data driven solutions to deal with the suggested barriers. The main contribution of the study is to propose a framework by making ideal matching and ranking of big data solutions to barriers to circularity in dairy supply chains. This framework further offers a specific roadmap as a practical contribution while investigating companies with restricted resources. In this study the main barriers are classified as ‘economic’ ‘environmental’ ‘social and legal’ ‘technological’ ‘supply chain management’ and ‘strategic’ with twenty-seven sub-barriers. Various big data solutions such as machine learning optimization data mining cloud computing artificial neural network statistical techniques and social network analysis have been suggested. Big data solutions are matched with circularity focused barriers to show which solutions succeed in overcoming barriers. A hybrid decision framework based on the fuzzy ANP and the fuzzy VIKOR is developed to find the weights of the barriers and to rank the big data driven solutions. The results indicate that among the main barriers ‘economic’ was of the highest importance followed by ‘technological’ ‘environmental’ ‘strategic’ ‘supply chain management’ then ‘social and legal barrier’ in dairy supply chains. In order to overcome circularity focused barriers ‘optimization’ is determined to be the most important big data solution. The other solutions to overcoming proposed challenges are ‘data mining’ ‘machine learning’ ‘statistical techniques’ and ‘artificial neural network’ respectively. The suggested big data solutions will be useful for policy makers and managers to deal with potential barriers in implementing circularity in the context of dairy supply chains. © 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 68
Citation - Scopus: 79
Drivers of implementing Big Data Analytics in food supply chains for transition to a circular economy and sustainable operations management
(Emerald Publishing, 2025) Yigit Kazancoglu; Melisa Ozbiltekin-Pala; Muruvvet Deniz Sezer; Sunil Luthra; Anil Kumar; Sezer, Muruvvet Deniz; Pala, Melisa Ozbiltekin; Luthra, Sunil; Kumar, Anil; Kazancoglu, Yigit; Ozbiltekin Pala, Melisa
Purpose: The aim of this study is to evaluate Big Data Analytics (BDA) drivers in the context of food supply chains (FSC) for transition to a Circular Economy (CE) and Sustainable Operations Management (SOM). Design/methodology/approach: Ten different BDA drivers in FSC are examined for transition to CE, these are Supply Chains (SC) Visibility Operations Efficiency Information Management and Technology Collaborations between SC partners Data-driven innovation Demand management and Production Planning Talent Management Organizational Commitment Management Team Capability and Governmental Incentive. An interpretive structural modelling (ISM) methodology is used to indicate the relationships between identified drivers to stimulate transition to CE and SOM. Drivers and pair-wise interactions between these drivers are developed by semi-structured interviews with a number of experts from industry and academia. Findings: The results show that Information Management and Technology Governmental Incentive and Management Team Capability drivers are classified as independent factors, Organizational Commitment and Operations Efficiency are categorized as dependent factors. SC Visibility Data-driven innovation Demand management and Production Planning Talent Management and Collaborations between SC partners can be classified as linkage factors. It can be concluded that Governmental Incentive is the most fundamental driver to achieve BDA applications in FSC transition from linearity to CE and SOM. In addition Operations Efficiency Collaborations between SC partners and Organizational Commitment are key BDA drivers in FSC for transition to CE and SOM. Research limitations/implications: The interactions between these drivers will provide benefits to both industry and academia in prioritizing and understanding these drivers more thoroughly when implementing BDA based on a range of factors. This study will provide valuable insights. The results from this study will help in drawing up regulations to prevent food fraud implementing laws concerning government incentives reducing food loss and waste increasing tracing and traceability providing training activities to improve knowledge about BDA and focusing more on data analytics. Originality/value: The main contribution of the study is to analyze BDA drivers in the context of FSC for transition to CE and SOM. This study is unique in examining these BDA drivers based on FSC. We hope to find sustainable solutions to minimize losses or other negative impacts on these SC. © 2025 Elsevier B.V. All rights reserved.
Citation - Scopus: 2
Facility Layout Design for Dangerous Goods Containers in the Warehouse
(Springer Science and Business Media Deutschland GmbH, 2023) Bernis Biçer; Elif Sayılı; Müge Ağaçhan; Batuhan Dündar; Sabri Can Doğantay; Yigit Kazancoglu; Melisa Ozbiltekin-Pala; Dündar, Batuhan; Ağaçhan, Müge; Biçer, Bernis; Kazancoglu, Yigit; Sayılı, Elif; Doğantay, Sabri Can; Pala, Melisa Ozbiltekin; N.M. Durakbasa , M.G. Gençyılmaz
Technological innovations and the variety of customers’ requirements have increased competitiveness lately. Facility layout design also became critical for gaining a competitive advantage in terms of service time and operational efficiencies. A facility layout design is a term used to describe the process of arranging sections and distributing them in a facility. Inappropriate facility layout design causes cost and time waste in organizations. As a result, this research created an implementation for a container cleaning firm with facility layout design issues. This research aims to identify factors influencing facility layout planning through decision-making methodologies redesign the company's warehouse plan and select the optimum warehouse placement. In-warehouse layout design methodologies will be employed to achieve an optimal in-warehouse settlement. SWARA (Step-wise Weight Assessment Ratio Analysis) a method for formulating multi-criteria decisions was used first and foremost. Then using BLOCPLAN one of the heuristic improvement methodologies a new layout was given based on the information received from the firm. The improvement obtained as a result of the suggested new settlement was detected aafter the investigation and it was observed that it delivered better results. © 2023 Elsevier B.V. All rights reserved.
Citation - WoS: 13
Citation - Scopus: 16
REDUCING FOOD WASTE THROUGH LEAN AND SUSTAINABLE OPERATIONS: A CASE STUDY FROM THE POULTRY INDUSTRY
(FUNDACAO GETULIO VARGAS, 2021) Yigit Kazancoglu; Esra Ekinci; Yesim Deniz Ozkan-Ozen; Melisa Ozbiltekin Pala; Pala, Melisa Ozbiltekin; Ekinci, Esra; Ozen, Yesim Deniz Ozkan; Kazancoglu, Yigit
The growing need for solving the problem of food waste for tackling the survival of the planet and humankind is encouraging researchers to seek sustainable operations that alter the conventional methods that are currently in use in the food industry. Lean thinking has been used in this study to propose sustainable operations that incorporate social economic and environmental aspects and to handle the multidisciplinary and complex nature of reducing food waste. The value stream mapping methodology has been employed to explain food waste and generate drivers and to observe the end-to-end system flow. Since most of the waste is observed in upstream operations in emerging economies one of the biggest meat-processing companies in Turkey is studied for illustrating the proposed methodology. As a result of the model lean and sustainable food operations are suggested considering social economic and environmental aspects.