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Article
Publication date: 23 August 2018

Yigit Kazancoglu and Yesim Deniz Ozkan-Ozen

The purpose of this paper is threefold: first, to present a structural competency model; second, to remark new criteria for personnel selection in Industry 4.0…

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Abstract

Purpose

The purpose of this paper is threefold: first, to present a structural competency model; second, to remark new criteria for personnel selection in Industry 4.0 environment; and third, to contribute to the operations management literature by focusing on recruitment process in Industry 4.0 environment and supporting human resources activities with Industry 4.0 related criteria and point out a new research field in Industry 4.0.

Design/methodology/approach

Fuzzy DEMATEL has been used in the implementation. The study is conducted in a high-tech firm, which has started to modify its processes according to Industry 4.0, and introduces a new specific department that is responsible of this transformation. In total, 11 personnel selection criteria were presented and then assessed by experts through a fuzzy linguistic scale. Both importance order and causal relation between criteria are presented at the end of the study.

Findings

According to the results, the most important criteria in the selected firm are the ability of dealing with complexity and problem solving, thinking in overlapping process, and flexibility to adapt new roles and work environments. While cause group includes criteria such as knowledge on IT and production technologies, awareness of IT security and data protection, and ability of fault and error recovery, effect group includes flexibility to adapt new roles and work environments, organizational and processual understanding, and the ability to interact with modern interfaces.

Practical implications

Analytical thinking and system approach are the key topics for new supporting personnel selection criteria, which lead to the need for the skills and qualifications in decision making and process management. Results of the cause group criteria also indicate the importance of technical abilities such as coding, IT security and human-machine interfaces. On the other hand, effect group of the study emphasizes on the flexibility and interdisciplinary working structure that suggests the suitability of matrix organization in the companies which follow the Industry 4.0 trends. Moreover, team work comes forward as another key concept for organizations transforming to Industry 4.0.

Originality/value

The originality of this study appears on modeling of a competency structural model for Workforce 4.0 which is proposed as a road map, including the suggested set of related criteria and the fuzzy MCDM-based methodology for companies which alter their organizations according to Industry 4.0.

Details

Journal of Enterprise Information Management, vol. 31 no. 6
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 12 March 2018

Yigit Kazancoglu, Ipek Kazancoglu and Muhittin Sagnak

Performance assessment of green supply chain management (GSCM) requires a systematic approach because of its interdisciplinary and multi-objective nature. The purpose of…

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Abstract

Purpose

Performance assessment of green supply chain management (GSCM) requires a systematic approach because of its interdisciplinary and multi-objective nature. The purpose of this paper is to propose a model to the performance assessment of GSCM.

Design/methodology/approach

A model is proposed, grounded on a literature review on GSCM performance, after which the causal relationships and prioritization of the sub-criteria are analyzed by fuzzy Decision Making Trial and Evaluation Laboratory technique in a company operating in the cement industry.

Findings

An integrated holistic performance assessment model incorporating specifically six criteria and 21 sub-criteria is applied, which represents causal relationships and prioritization of sub-criteria.

Research limitations/implications

The proposed model can be generalized, because an integrative framework can be used in future empirical studies to analyze performance of GSCM. However, the causal relationships and prioritization among sub-criteria are analyzed based on the needs and capabilities of the individual company; therefore, the causal relationships found are company specific.

Practical implications

The proposed model can be hired and implemented by companies striving for GSCM. This model allows companies to assess their current GSCM performance, analyze causal relationships, and prioritize sub-criteria.

Originality/value

Several studies have analyzed performance assessment in green supply chains; however, to the best of the authors’ knowledge, no study has taken an approach to performance assessment in GSCM that combines environmental, economics/financial, logistics, operational, organizational and marketing in the same framework. In addition, the cause-effect relationships identified will be the base for performance improvement.

Details

Industrial Management & Data Systems, vol. 118 no. 2
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 13 February 2019

Yigit Kazancoglu and Yesim Deniz Ozkan-Ozen

This research aims to investigate and define the eight wastes of lean philosophy in higher education institutions (HEIs) by proposing a multi-stage model.

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Abstract

Purpose

This research aims to investigate and define the eight wastes of lean philosophy in higher education institutions (HEIs) by proposing a multi-stage model.

Design/methodology/approach

The authors have used a specific multi-criteria decision-making method, fuzzy decision-making trial and evaluation laboratory, to investigate the cause–effect relationships and importance order between criteria for wastes in HEIs. In total, 22 criteria were categorized under eight wastes of lean. The study was implemented in a business school with the participation of faculty members from different departments.

Findings

The results showed that the most important wastes in the business school selected were repeated tasks, unnecessary bureaucracy, errors because of misunderstanding/communication problems, excessive number of academic units and creation of an excessive amount of information. Another important result was that all the sub-wastes of talent were in the causes group, while motion and transportation wastes were in the effect group.

Practical implications

A road map to guide lean transformation for HEIs is proposed with a multi-stage model and potential areas for improvement in HEIs were presented.

Originality/value

This study proposes a multi-stage structure by applying multi-criteria decision-making to HEIs, focussing on wastes from a lean perspective.

Details

Quality Assurance in Education, vol. 27 no. 1
Type: Research Article
ISSN: 0968-4883

Keywords

Article
Publication date: 13 October 2021

Manish Mohan Baral, Rajesh Kumar Singh and Yiğit Kazançoğlu

Nowadays, many firms are finding ways to enhance the survivability of sustainable supply chains (SUSSCs). The present study aims to develop a model for the SUSSCs of small…

Abstract

Purpose

Nowadays, many firms are finding ways to enhance the survivability of sustainable supply chains (SUSSCs). The present study aims to develop a model for the SUSSCs of small and medium enterprises (SMEs) during the COVID-19 pandemic.

Design/methodology/approach

With the help of exhaustive literature review, constructs and items are identified to collect the responses from different SMEs. A total of 278 complete responses are received and 6 hypotheses are developed. Hypotheses testing have been done using structural equation modeling (SEM).

Findings

Major constructs identified for the study are supply chain (SC) performance measurement under uncertainty (SPMU), supply chain cooperation (SCCO), supply chain positioning (SCP), supply chain administration (SCA), supply chain feasibility (SCF) and the SUSSCs. From statistical analysis of the data collected, it can be concluded that the considered latent variables contribute significantly towardsthe model fit.

Research limitations/implications

The present study contributes to the existing literature on disruptions and survivability. The study can be further carried out in context to different countries and sectors to generalize the findings.

Practical implications

The research findings will be fruitful for SMEs and other organizations in developing strategies to improve survivability during uncertain business environments.

Originality/value

The study has developed a model that shows that the identified latent variables and their indicators contribute significantly toward the dependent variable, i.e. survivability. It contributes significantly in bridging the research gaps existing in context to the survivability of SMEs.

Details

The International Journal of Logistics Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 30 September 2021

Damla Yüksel, Yigit Kazancoglu and P.R.S Sarma

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…

Abstract

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.

Details

International Journal of Quality & Reliability Management, vol. 39 no. 3
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 5 July 2021

Kirti Nayal, Rakesh Raut, Pragati Priyadarshinee, Balkrishna Eknath Narkhede, Yigit Kazancoglu and Vaibhav Narwane

In India, artificial intelligence (AI) application in supply chain management (SCM) is still in a stage of infancy. Therefore, this article aims to study the factors…

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Abstract

Purpose

In India, artificial intelligence (AI) application in supply chain management (SCM) is still in a stage of infancy. Therefore, this article aims to study the factors affecting artificial intelligence adoption and validate AI’s influence on supply chain risk mitigation (SCRM).

Design/methodology/approach

This study explores the effect of factors based on the technology, organization and environment (TOE) framework and three other factors, including supply chain integration (SCI), information sharing (IS) and process factors (PF) on AI adoption. Data for the survey were collected from 297 respondents from Indian agro-industries, and structural equation modeling (SEM) was used for testing the proposed hypotheses.

Findings

This study’s findings show that process factors, information sharing, and supply chain integration (SCI) play an essential role in influencing AI adoption, and AI positively influences SCRM. The technological, organizational and environmental factors have a nonsignificant negative relation with artificial intelligence.

Originality/value

This study provides an insight to researchers, academicians, policymakers, innovative project handlers, technology service providers, and managers to better understand the role of AI adoption and the importance of AI in mitigating supply chain risks caused by disruptions like the COVID-19 pandemic.

Details

The International Journal of Logistics Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0957-4093

Keywords

Content available
Article
Publication date: 15 February 2022

Yigit Kazancoglu, Sachin Kumar Mangla, Malin Song, Guo Li and Flavio Hourneaux Junior

179

Abstract

Details

International Journal of Productivity and Performance Management, vol. 71 no. 3
Type: Research Article
ISSN: 1741-0401

Article
Publication date: 29 April 2021

Lalit Bhagat, Gunjan Goyal, Dinesh C.S. Bisht, Mangey Ram and Yigit Kazancoglu

The 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…

Abstract

Purpose

The 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/approach

In 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.

Findings

The 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 implications

The 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/value

The 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.

Details

The TQM Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 3 April 2021

Rajesh Kumar Singh, Saurabh Agrawal, Abhishek Sahu and Yigit Kazancoglu

The proposed article is aimed at exploring the opportunities, challenges and possible outcomes of incorporating big data analytics (BDA) into health-care sector. The…

Abstract

Purpose

The proposed article is aimed at exploring the opportunities, challenges and possible outcomes of incorporating big data analytics (BDA) into health-care sector. The purpose of this study is to find the research gaps in the literature and to investigate the scope of incorporating new strategies in the health-care sector for increasing the efficiency of the system.

Design/methodology/approach

Fora state-of-the-art literature review, a systematic literature review has been carried out to find out research gaps in the field of healthcare using big data (BD) applications. A detailed research methodology including material collection, descriptive analysis and categorization is utilized to carry out the literature review.

Findings

BD analysis is rapidly being adopted in health-care sector for utilizing precious information available in terms of BD. However, it puts forth certain challenges that need to be focused upon. The article identifies and explains the challenges thoroughly.

Research limitations/implications

The proposed study will provide useful guidance to the health-care sector professionals for managing health-care system. It will help academicians and physicians for evaluating, improving and benchmarking the health-care strategies through BDA in the health-care sector. One of the limitations of the study is that it is based on literature review and more in-depth studies may be carried out for the generalization of results.

Originality/value

There are certain effective tools available in the market today that are currently being used by both small and large businesses and corporations. One of them is BD, which may be very useful for health-care sector. A comprehensive literature review is carried out for research papers published between 1974 and 2021.

Details

The TQM Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 24 April 2020

Muhittin Sagnak, Yigit Kazancoglu, Yesim Deniz Ozkan Ozen and Jose Arturo Garza-Reyes

The aim of the present study is to overcome some of the limitations of the FMEA method by presenting a theoretical base for considering risk evaluation into its assessment…

Abstract

Purpose

The aim of the present study is to overcome some of the limitations of the FMEA method by presenting a theoretical base for considering risk evaluation into its assessment methodology and proposing an approach for its implementation.

Design/methodology/approach

Fuzzy AHP is used to calculate the weights of the likelihood of occurrence (O), severity (S) and difficulty of detection (D). Additionally, the prospect-theory-based TODIM method was integrated with fuzzy logic. Thus, fuzzy TODIM was employed to calculate the ranking of potential failure modes according to their risk priority numbers (RPNs). In order to verify the results of the study, in-depth interviews were conducted with the participation of industry experts.

Findings

The results are very much in line with prospect theory. Therefore, practitioners may apply the proposed method to FMEA. The most crucial failure mode for a firm's attention is furnace failure followed by generator failure, crane failure, tank failure, kettle failure, dryer failure and operator failure, respectively.

Originality/value

The originality of this paper consists in integrating prospect theory with the FMEA method in order to overcome the limitations naturally inherent in the calculation of the FMEA's RPNs.

Details

International Journal of Quality & Reliability Management, vol. 37 no. 6/7
Type: Research Article
ISSN: 0265-671X

Keywords

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