Browsing by Author "Kazancoglu, Yigit"

Now showing 1 - 20 of 166

Citation - WoS: 9
Citation - Scopus: 19
A circular business cluster model for sustainable operations management
(TAYLOR & FRANCIS LTD, 2024) Erhan Ada; Muhittin Sagnak; Sachin Kumar Mangla; Yigit Kazancoglu; Ada, Erhan; Sagnak, Muhittin; Mangla, Sachin Kumar; Kazancoglu, Yigit
Ecological pollution scarcity of resources climate change and population growth have forced organisations to transform from a linear to a circular economy. Hence the need arises to redesign value chains and traditional business models. Thus the aim of this study is to develop a new conceptual eco-cluster model called 'Circular Business Cluster Model' to combine the advantages of both clustering and a circular economy. This paper seeks to establish a framework and provide guidelines for policy-makers such as governments local authorities and organised industrial zone administrators. The contribution of this paper is to highlight and emphasise the crucial role of circular economy principles to transform a classical business model into an eco-business model. Circular Business Cluster Model includes the conceptual framework network structure interactions between cluster components and 6R activities. A case study was conducted to check the applicability of the proposed Circular Business Cluster Model. Eleven centres in this model were evaluated. Fuzzy Best-Worst Method (BWM) was used to find the relative weights. Based on the Circular Business Cluster Model theoretical and managerial implications have been presented.
Citation - WoS: 168
Citation - Scopus: 198
A conceptual framework for barriers of circular supply chains for sustainability in the textile industry
(WILEY, 2020) Ipek Kazancoglu; Yigit Kazancoglu; Emel Yarimoglu; Aysun Kahraman; Yarimoglu, Emel; Kazancoglu, Ipek; Kazancoglu, Yigit; Kahraman, Aysun
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 (g) lack of integration and collaboration (h) cost and (i) technical infrastructure.
Citation - WoS: 102
Citation - Scopus: 145
A conceptual framework for blockchain-based sustainable supply chain and evaluating implementation barriers: A case of the tea supply chain
(WILEY, 2022) Sachin Kumar Mangla; Yigit Kazancoglu; Abdullah Yildizbasi; Cihat Ozturk; Ahmet Calik; Calik, Ahmet; Yildizbasi, Abdullah; Ozturk, Cihat; Mangla, Sachin Kumar; Kazancoglu, Yigit
The increasing population and income inequality in the last decades have made it necessary to focus on the concept of sustainability. In the changing world order with economic crises instabilities pandemics and social media sustainability awareness differs significantly from past years. In addition developing new technologies and concepts (big data blockchain IoT robotic etc.) plays a crucial role in meeting social awareness in terms of sustainability. Food sustainability is also one of the most important pillars in this concept. The integration of new technologies in agriculture and food chains will enable the current world population to use resources more efficiently and sustainably. Blockchain one of the technologies that emerged with the arrival of Industry 4.0 is a technology that can be used effectively in many sectors. Particularly in supply chain networks it is seen as a technology that supports the sustainability concept due to its features such as decentralization reliability transparency consensus standards and traceability. However since blockchain is an immature and new technology there are some challenges with integrating it into existing conventional systems. This study aims to present a conceptual framework for the integration of blockchain technology to establish a sustainable tea supply chain define possible actions and prioritize the possible risks that may arise in this integration process, this will be done through the Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) approach. In this context initially the current tea supply chain will be considered and the activities carried out will be defined in terms of technological environmental and strategic sustainability. Then the design that includes the integration of all activities with blockchain technology is presented. The proposed design covers the entire tea supply chain from end to end and is considered with regard to all sustainability dimensions. In the proposed framework barriers that may be encountered and risks that may arise at each stage of the tea supply chain process are identified, managerial implications are then presented to eliminate these risks. To enhance the use of the recommendations made risks and barriers are prioritized with SF-AHP management. Thus the problems that need to be solved primarily in the technological transformation process can be evaluated more clearly. The proposed theoretical framework is expected to extend to all agricultural practices and support technological advances throughout the agricultural sector.
Citation - WoS: 37
Citation - Scopus: 39
A decision framework for incorporating the coordination and behavioural issues in sustainable supply chains in digital economy
(Springer, 2023) Patanjal Kumar; Sachin Kumar Kumar Mangla; Yigit Kazancoglu; Ali Emrouznejad; Kumar, Patanjal; Emrouznejad, Ali; Mangla, Sachin Kumar; Kazancoglu, Yigit
Global warming climate change and social problems are the worst human-induced sustainability issues that economies across the globe have witnessed. Water pollution greenhouse effect poor working conditions child labour and lack of coordination among channel partners have caused the considerable interruptions in the supply chain network. The purpose of the paper is to identify critical factors affecting behavioural and sustainable supply chain coordination and evaluate strategies for risk reduction in the supply chain coordination in the context of digitization. This study purposes a novel supply chain coordination framework which consists of four themes such as system actor objective and action on which the success or the failure of supply chain can be contingent. Our study integrates multi-criteria decision approach using Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) to investigate factors that affected the behavioural and sustainable supply chain coordination in the context of digitization. The Fuzzy-AHP method qualified to hierarchically rank the factors based on the relative fuzzy weightage while Fuzzy-DEMATEL established the inter-relationships among the factors and classified them into cause and effect groups. The findings of our study identified the Environmental performance and decarbonization as the most significant factor and the speed to market as the least important factor in developing behavioural and sustainable supply chain coordination in the context of digitization. Our analysis from Fuzzy AHP-DEMATEL approach reveal that the social preferences (power balance reciprocity fairness) is a significant causal factor which can effectively abolish the issues plaguing behavioural and sustainable supply chain coordination in the context of digitization. The results from our study aim to facilitate decision makers in cultivating a sustainable supply chain framework that can boost trust among the channel partners environmental performance social performance and channel efficiency of the supply chain thereby ensuring sustainability and socio welfare of all the supply chain. © 2023 Elsevier B.V. All rights reserved.
Citation - WoS: 24
Citation - Scopus: 27
A Framework for Evaluating Information Transparency in Supply Chains
(IGI GLOBAL, 2021) Erhan Ada; Muhittin Sagnak; Yigit Kazancoglu; Sunil Luthra; Anil Kumar; Luthra, Sunil; Kumar, Anil; Ada, Erhan; Sagnak, Muhittin; Kazancoglu, Yigit
Private public profit and non-profit organizations and society as a whole currently face a significant reliable information necessity problem. Especially supply chains need trustworthy information to perform their activities successfully. This study aims to propose a framework and identify how reliability of information can be evaluated and measured through the concept of transparency. In this context dimensions such as comprehensiveness regularity timeliness content scope and user-friendliness are the pillars of the proposed framework. Selected criteria have been used as inputs to develop the information transparency level. The fuzzy analytic network process (ANP) is used to obtain weights of these inputs and data envelopment analysis (DEA) is used for the determination of the efficiency ranking for transparency. Results demonstrated that content scope and comprehensiveness dimensions have 75% impact on the transparency of data. The remaining 25% is affected by timeliness regularity and user-friendliness.
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: 48
Citation - Scopus: 61
A Green Dual-Channel Closed-Loop Supply Chain Network Design Model
(ELSEVIER SCI LTD, 2022) Yigit Kazancoglu; Damla Yuksel; Muruvvet Deniz Sezer; Sachin Kumar Mangla; Lianlian Hua; Yuksel, Damla; Sezer, Muruvvet Deniz; Hua, Lianlian; Kazancoglu, Yigit; Mangla, Sachin Kumar
Environmental considerations have become a significant issue in the design of supply chain networks due to today's increasing globalization trends. Therefore supply chain network design needs to be managed in an efficient way to deal with the complex networks involved. The aim of this article is to present a multi-objective optimization model for a green dual-channel supply chain network that handles economic and environmental objectives to optimize network flow. A complex mixed-integer linear programming model (MILP) has been proposed in a green dual-channel and closed-loop supply chain (CLSC) network design. The main objective of the generated MILP model is to investigate the optimal selection of echelons and the optimal selection of transportation alternatives between these echelons in a CLSC network that includes an e-commerce channel structure based on economic and environmental considerations. Environmental aims are achieved by decreasing CO2 emissions and by reducing PM (particulate matter) concentration throughout the network. In addition economic aims are also met by minimizing the overall cost. The validity of the presented model is supported by a case study in the home appliances industry. The results indicate that this model provides valuable knowledge and various alternatives to managers and policymakers depending on the different weight combinations.
Citation - Scopus: 1
A Hybrid Decision Model for Balancing the Technological Advancement Human Intervention and Business Sustainability in Industry 5.0 Adoption
(Springer Science and Business Media Deutschland GmbH, 2024) Rahul Sindhwani; Sachin Kumar Kumar Mangla; Yigit Kazancoglu; Ayça Maden; Maden, Ayca; Sindhwani, Rahul; Mangla, Sachin Kumar; Kazancoglu, Yigit; Z. Şen , O. Uygun , C. Erden
In Industry 5.0 humans and machines work together using advanced technologies like Artificial Intelligence (AI) the Internet of Things (IoT) and automation to improve efficiency productivity and quality while also supporting sustainable practices and human values. There is a growing interest in learning about the challenges of Industry 5.0 and exploring these technologies to promote sustainability and responsible business practices. We need a hybrid decision model to strike a balance between technical progress human values and sustainable practices as we move toward Industry 5.0 which presents enormous challenges in the areas of technology the environment society and ethics and business and economics. Through a literature analysis guided by the PRISMA technique and the Delphi method the study highlighted challenges in the areas of technology the environment society and ethics and business and economics as well as solution measures to address them. The weightage of the challenges was determined using the Best Worst Method and the ranking of the potential solutions was prioritized using the Elimination and Choice Expressing Reality method. © 2023 Elsevier B.V. All rights reserved.
Citation - WoS: 4
Citation - Scopus: 7
A machine learning-based hybrid approach for maximizing supply chain reliability in a pharmaceutical supply chain
(PERGAMON-ELSEVIER SCIENCE LTD, 2025) Devesh Kumar; Gunjan Soni; Sachin Kumar Mangla; Yigit Kazancoglu; A. P. S. Rathore; Rathore, A. P. S.; Kumar, Devesh; Soni, Gunjan; Mangla, Sachin Kumar; Kazancoglu, Yigit
In today's interconnected global economy supply chain (SC) reliability is crucial particularly in sectors like the pharmaceutical industry where disruptions can significantly impact public health. SCs have become important to industries due to a customer-driven shift aimed at improving SC reliability especially in terms of delivery performance. It is crucial to define and find the best strategy for reaching the organizational objectives in SC. While designing a SC supplier selection (SS) and order allocation are two decisions that have to be made separately. This study addresses the critical challenges of SS and order allocation within pharmaceutical SCs. It proposes a novel two-phased hybrid approach the first phase integrates machine learning(ML) and multicriteria decision-making(MCDM) method for robust SS. The second phase develops a mathematical model to optimize order allocation while considering SC reliability. This work employs support vector machine (SVM) as the particular ML method in which the training data are historical corporate data that dictate parameters weights. These weights are then used in the measurement of alternatives and ranking according to compromise solution (MARCOS) method to rank the suppliers. A multi- objective mixed integer programming (MOMIP) model is then formulated to identify the right order quantity from the identified suppliers of a pharmaceutical SC in order to minimize SC cost and maximize SC reliability. The results indicate that by optimizing SC reliability and costs orders are directed to high-priority suppliers. This study provides a comprehensive data-driven decision-making framework to assure SC's reliability and cost-efficiency. The implications of the findings are also profound and contribute valuable insights for industry practitioners to improve the performance of SC. To illustrate the proposed methodology an SC example of a pharmaceutical industry is analyzed using the LINGO solver.
Citation - WoS: 25
Citation - Scopus: 30
A model for estimating the carbon footprint of maritime transportation of Liquefied Natural Gas under uncertainty
(Elsevier B.V., 2021) Saleh Aseel; Hussein Al-Yafei; Murat Küçükvar; Nuri Cihat Cihat Onat; Metin Türkay; Yigit Kazancoglu; Ahmed Al-Sulaiti; Abdulla Radi Al-Hajri; Kucukvar, Murat; Onat, Nuri C.; Turkay, Metin; Aseel, Saleh; Kazancoglu, Yigit; Al-Yafei, Hussein; Al-Hajri, Abdulla
The demand for Liquefied Natural Gas (LNG) in the global markets has changed significantly. As a result industries have been forced to consider investing significantly in supply chains to achieve an efficient distribution of LNG for cost efficiency and carbon footprint reduction. To minimize the contribution of LNG maritime transportation to global climate change there is a need to quantify the carbon footprints systematically. In this research we developed a novel and practical model for estimating the carbon footprint for LNG maritime transport. Using the MATLAB program an uncertainty-based carbon footprint accounting framework is created. The Monte Carlo simulation model is built to conduct a carbon footprint analysis while the main input parameters were changed within a reliable range. Later a multivariate sensitivity analysis is performed using the Risk Solver software to estimate the most significant parameters on the net carbon footprints. The sensitivity analysis results showed that that steam process day and steaming fuel consumption are found to be the most sensitive parameters for the overall carbon footprint for both Laden and Ballast trips. Furthermore it was found that the Q-Max vessel produces more carbon emissions when compared to the Q-Flex although both are traveling the same distance and are using the same fuel type. The type of fuel is also significantly affecting the emission values due to the relevant carbon content in the fuel. Like the case of the two conventional vessels the one that is running with the only LNG is found to have fewer emissions when compared to the one run with dual-mode. © 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 2
A multiphase acceptance sampling model by attributes to investigate the production interruptions in batch production within tobacco industry
(EMERALD GROUP PUBLISHING LTD, 2022) Damla Yuksel; Yigit Kazancoglu; P. R. S. Sarma; Yuksel, Damla; Kazancoglu, Yigit; Sarma, P. R. S.
Purpose This paper aims to create a new decision-making procedure that uses Lot-by-Lot Acceptance Sampling Plan by Attributes methodology in the production processes when any production interruption is observed in tobacco industry which is a significant example of batch production. Design/methodology/approach Based on the fish bone diagram the reasons of the production interruptions are categorized then Lot-by-Lot Acceptance Sampling Plan by Attributes is studied to overcome the reasons of the production interruptions. Furthermore managerial aspects of decision making are not ignored and hence acceptance sampling models are determined by an Analytical Hierarchy Process (AHP) among the alternative acceptance sampling models. Findings A three-phased acceptance sampling model is generated for determination of the reasons of production interruptions. Hence the necessary actions are provided according to the results of the proposed acceptance sampling model. Initially 729 alternative acceptance sampling models are found and 38 of them are chosen by relaxation. Then five acceptance sampling models are determined by AHP. Practical implications The current experience dependent decision mechanism is suggested to be replaced by the proposed acceptance sampling model which is based on both statistical and managerial decision-making procedure. Originality/value Acceptance sampling plans are considered as a decision-making procedure for various cases in production processes. However to the best of our knowledge Lot-by-Lot Acceptance Sampling Plan by Attributes has not been considered as a decision-making procedure for batch production when any production interruption is investigated.
Citation - WoS: 263
Citation - Scopus: 324
A new holistic conceptual framework for green supply chain management performance assessment based on circular economy
(Elsevier Ltd, 2018) Yigit Kazancoglu; Ipek Kazançoǧlu; Muhittin Saǧnak; Kazancoglu, Yigit; Kazancoglu, Ipek; Sagnak, Muhittin
In circular economy the Green Supply Chain Management (GSCM) provides the resource optimization and it is seen as a solution to solve environmental problems and consumption patterns within the whole supply chain. The GSCM implementation and performance assessment is relatively important for survival in an ever-increasingly competitive environment. Within the circular economy context, companies that aim to improve GSCM must constantly monitor their performance. In order to integrate the circular economy concept into GSCM it is required to achieve an optimal balance of environmental economic logistics organizational and marketing performance indicators. However in the literature these indicators were investigated separately in terms of GSCM performance assessment therefore to achieve this optimal balance it is necessary to assess these different indicators. Within this context the aim of this paper is to propose a new holistic conceptual GSCM performance assessment framework which integrates environmental economic logistics operational organizational and marketing performance. The framework has three-dimensional hierarchy which includes the main criteria sub-criteria and the measures for the GSCM performance assessment which have great significance to implement effective GSCM. © 2018 Elsevier B.V. All rights reserved.
Citation - WoS: 5
Citation - Scopus: 9
A new holistic conceptual framework for layout performance assessment
(EMERALD GROUP PUBLISHING LTD, 2019) Muhittin Sagnak; Erhan Ada; Yigit Kazancoglu; Sagnak, Muhittin; Ada, Erhan; Kazancoglu, Yigit
Purpose Performance assessment of layouts requires a systematic approach because of its multi-objective nature. The purpose of this paper is to propose a framework to the performance assessment of layout designs. Design/methodology/approach A layout performance assessment framework is proposed grounded on a literature review. Then the causal relationships and prioritization of the sub-criteria are analyzed by fuzzy Decision Making Trial and Evaluation Laboratory technique in an elevator and escalator-manufacturing firm. Findings An integrated holistic performance assessment framework specifically the 7 criteria 19 sub-criteria and 112 measures are studied in this model which represents causal relationships and prioritization of sub-criteria. Research limitations/implications The proposed framework can be generalized because an integrative framework can be used in future empirical studies to analyze performance of layout design. However the causal relationships and prioritization among sub-criteria are analyzed based on the needs and capabilities of the individual company, therefore the results of the causal relationships are company specific. Practical implications With this framework the companies may assess their current layout's performance may analyze causal relationships and prioritization of sub-criteria. Originality/value There are very few models or frameworks regarding the performance assessment of layout designs. In this paper a new conceptual holistic framework was proposed as three-dimensional hierarchy which includes the main criteria sub-criteria and the measures respectively. Cost flow flexibility surrounding environment environment quality time and characteristics are identified as the main criteria for the layout design performance assessment. In addition cause-effect relationships which will be the base for improvement of the performance are found.
Citation - WoS: 11
Citation - Scopus: 18
A New Holistic Conceptual Framework for Leanness Assessment
(RAM ARTI PUBL, 2020) Cansu Tayaksi; Muhittin Sagnak; Yigit Kazancoglu; Tayaksi, Cansu; Sagnak, Muhittin; Kazancoglu, Yigit
Lean principles aiming at eliminating waste and increasing efficiency at a company take their roots from the initiatives of Taiichi Ohno. After the implementation of the principles at the Toyota Motor Company for the first time businesses started to discover the benefits of lean implementation in terms of efficiency increase. As the adaptation of lean into the manufacturing sector is continuing the necessity of assessing the level of leanness at the firm-level maintains its importance. Taking systems approach as a basis the lean performance of an organization should be assessed as a whole. Therefore we propose a holistic leanness assessment framework which encapsulates various dimensions of the leanness assessment and we identify the importance and causal relationships between the sub-criteria. In order to identify the importance and causal relationships between the sub-criteria we used fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL). Our findings show that the most influencing factor in the cause group is 'technology and product design' which indicates the companies' necessity to focus on Industry 4.0 during their operations. The results also illustrate that the most influenced factor in the effect group is 'productivity' in which companies can investigate strategic competitive advantages. The design of a holistic framework and the implementation of fuzzy DEMATEL offers a way to identify the importance and the causal relationships between the sub-criteria. With the help of a case study conducted in the plastics industry of Turkey we offer managerial implications that could help managers to implement the proposed structural leanness assessment framework.
Citation - WoS: 8
Citation - Scopus: 10
A proposed circular-SCOR model for supply chain performance measurement in manufacturing industry during COVID-19
(Emerald Publishing, 2023) Melisa Ozbiltekin-Pala; Aydın Koçak; Yigit Kazancoglu; Ozbiltekin-Pala, Melisa; Kocak, Aydin; Kazancoglu, Yigit
Purpose: COVID-19 is a global event affecting supply chain operations and human health. With COVID-19 many issues in business models business processes and supply chains especially in the manufacturing industry have had to change. The ability to analyze supply chain performances and ensure circularity in supply chains has become one of the factors whose importance has increased rapidly with COVID-19. Therefore it aims to determine which supply chain performance criteria come to the fore for the company under consideration to accelerate the transformation into high performance and circularity in supply chains. Design/methodology/approach: In this study a new circular-SCOR model is proposed and 17 supply chain performance measurement criteria are prioritized for a manufacturing company in the context of circular economy principles during COVID-19 by using stepwise weight assessment ratio analysis and analytical hierarchy process method separately. Findings: As a result for both methods in the case study discussed the demand fulfillment rate is determined as the most prominent criterion in line with the circular economy principles in the COVID-19 period in manufacturing supply chains. Originality/value: It is expected that this study will contribute to managers and policy makers as it addresses the “new normal” that started after COVID-19 and the criteria to be considered in supply chain performance measurement and emphasizes the need to adopt circular supply chains especially in manufacturing industries. © 2023 Elsevier B.V. All rights reserved.
Citation - WoS: 31
Citation - Scopus: 44
A proposed sustainable and digital collection and classification center model to manage e-waste in emerging economies
(Emerald Group Holdings Ltd., 2020) Yigit Kazancoglu; Melisa Ozbiltekin-Pala; Yeşim Deniz Özkan-Özen; Muhittin Saǧnak; Ozbiltekin, Melisa; Kazancoglu, Yigit; Sagnak, Muhittin; Ozkan Ozen, Yesim Deniz
Purpose: This study aims to propose an electronic waste collection and classification system to enhance social environmental and economic sustainability by integrating data-driven technologies in emerging economies. Design/methodology/approach: GM (1 1) model under grey prediction is used in this study in order to estimate the trend of the amount of collected electronic waste in emerging economies. Findings: It is revealed that the amount of collected electronic waste is increasing day by day and within the framework of sustainability in the process of collecting and classification of electronic waste digital technologies were found to be lacking. It has been determined that this deficiency together with the increasing amount of electronic waste has caused environmental social and economic damage to emerging economies. Originality/value: The main originality of this study is integrating electronic waste collection and classification processes with data-driven technologies and sustainability which is a relatively new subject. © 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 7
Citation - Scopus: 7
A strategic and social analytics model for sustainable packaging in the cosmetic industry
(ELSEVIER, 2024) Idiano D'Adamo; Massimo Gastaldi; Rossella Giacalone; Yigit Kazancoglu; Gastaldi, Massimo; D'Adamo, Idiano; Giacalone, Rossella; Kazancoglu, Yigit
Every day we use cosmetic products that are not only focused on beauty but also with everything related to personal care and hygiene. The impact that these products have on sustainability cannot be overlooked. Many cosmetics contain unsustainable ingredients that can cause environmental damage and loss of biodiversity. In addition fossil-based packaging contributes greatly to environmental pollution and increases waste in the absence of a circular supply chain. This work has a dual objective. The first is to provide a strategic analysis based on a multi-criteria approach to evaluate the most sustainable alternatives to traditional packaging that manufacturers could adopt based on the opinions of experts from different categories of stakeholders. In this study the multi-criteria approach was employed as it has been widely recognized in the literature for its effectiveness in evaluating and comparing alternatives across multiple often conflicting criteria. The second is to provide a social analysis to assess consumers' views habits preferences and willingness to pay toward sustainable packaging. The results show divergence among experts who prefer refillable packaging while consumers prefer recyclable packaging. In contrast a convergence in selling price and production costs is verified highlighting the strategic importance of the economic dimension is for sustainable packaging and the willingness to pay for sustainable packaging is about twice that of traditional packaging. The implications of this work suggest that circular supply chains covering the entire life cycle of products based on a pragmatic approach can drive the convergence of consumption and production patterns toward sustainable development.
Citation - WoS: 43
Citation - Scopus: 53
A sustainable and preventative risk management model for ship recycling industry
(ELSEVIER SCI LTD, 2019) Yucel Ozturkoglu; Yigit Kazancoglu; Yesim Deniz Ozkan-Ozen; Ozkan-Ozen, Yesim Deniz; Ozturkoglu, Yucel; Kazancoglu, Yigit
When the dynamic environment of ship recycling is considered many different severe risks may occur. These risks affect different dimensions including people environment and economic. The aim of the study is give a framework to guide managers and even policy makers to strive a holistic view in their preventative risk management activities in ship recycling. In this framework which is proposed for sustainable risk management in ship recycling industry risk areas related to occupational safety working conditions fluctuations in steel industry economic cycles in construction sector and direct and indirect environmental impacts are suggested to be considered. In order to deal with aforementioned risk areas several preventative actions are proposed such as, for people related risks Occupational Health and Safety Assessment Series (OHSAS) implementation, for economic risks responsiveness as a competitive strategy and for environmental risks green supply chain management implementation is proposed. For each action different sub factors are defined from the literature and for an effective implementation fuzzy DEMATEL method is used to analyze causal link between these factors. Finally managerial implications for sustainable risk management in ship recycling industry are presented. (C) 2019 Elsevier Ltd. All rights reserved.
Citation - Scopus: 2
Advances in soft computing applications
(River Publishers, 2023) Shristi Kharola; Mangey Ram; Sachin Kumar Kumar Mangla; Yigit Kazancoglu; Kharola, Shristi; Ram, Mangey; Mangla, Sachin K.; Kazancoglu, Yigit
The proclivity of today's technology to think like humans may be seen in new developing disciplines such as neural computing fuzzy logic evolutionary computation machine learning and probabilistic reasoning. These strategies are grouped together into one main technique known as "soft computing." This book discusses the most recent soft computing and fuzzy logic-based applications and innovations in industrial advancements supply chain and logistics system optimization decision-making artificial intelligence smart systems and other rapidly evolving technologies. In today's competitive world the book provides soft computing solutions to help companies overcome the obstacles posed by sophisticated decision-making systems. © 2023 Elsevier B.V. All rights reserved.
Citation - WoS: 2
Citation - Scopus: 8
Air quality management using genetic algorithm based heuristic fuzzy time series model
(EMERALD GROUP PUBLISHING LTD, 2023) Lalit Bhagat; Gunjan Goyal; Dinesh C. S. Bisht; Mangey Ram; Yigit Kazancoglu; Bhagat, Lalit; Ram, Mangey; Goyal, Gunjan; Bisht, Dinesh C.S.; Kazancoglu, Yigit
PurposeThe purpose of this paper is to provide a better method for quality management to maintain an essential level of quality in different fields like product quality service quality air quality etc.Design/methodology/approachIn this paper a hybrid adaptive time-variant fuzzy time series (FTS) model with genetic algorithm (GA) has been applied to predict the air pollution index. Fuzzification of data is optimized by GAs. Heuristic value selection algorithm is used for selecting the window size. Two algorithms are proposed for forecasting. First algorithm is used in training phase to compute forecasted values according to the heuristic value selection algorithm. Thus obtained sequence of heuristics is used for second algorithm in which forecasted values are selected with the help of defined rules.FindingsThe proposed model is able to predict AQI more accurately when an appropriate heuristic value is chosen for the FTS model. It is tested and evaluated on real time air pollution data of two popular tourism cities of India. In the experimental results it is observed that the proposed model performs better than the existing models.Practical implicationsThe management and prediction of air quality have become essential in our day-to-day life because air quality affects not only the health of human beings but also the health of monuments. This research predicts the air quality index (AQI) of a place.Originality/valueThe proposed method is an improved version of the adaptive time-variant FTS model. Further a nature-inspired algorithm has been integrated for the selection and optimization of fuzzy intervals.