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PurposeThe aim of this paper is to identify and analyse workforce development challenges in the digital age by first, presenting these challenges and relationship between them, and then proposing a structural model that categorizes these challenges and proposes suggestions for managers to improve human resources practices and firm performance.Design/methodology/approachFuzzy total interpretive structural modelling (TISM) is used as the methodology, which gives an interpretive structural model by presenting direct and transitive relationship between workforce development challenges and categorizes them under autonomous, dependent, independent and linkage groups.FindingsIn total, 13 different workforce development challenges are presented in this study. Results showed that lack of IT/digital skills has a critical role in workforce development in terms of affecting other challenges. Dependent group includes requirements for longer learning time and specialized training, lack of analytical thinking and dealing with complexity, and lack of interdisciplinary thinking and acting. On the other hand, lack of ability in decentralized decision-making and shortage of workforce with adequate skillset within the labour market have more macro-impacts on others. Most of the challenges located in the linkage group, which means that most of the challenges are interrelated with each other.Originality/valueOriginality of this paper is presenting a systematic structure for workforce development in Industry 4.0 that considers challenges systematically.

PurposeThis 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/approachGM (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.FindingsIt 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/valueThe 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.

E-waste is a hazardous concept for human health, environment and businesses, and therefore, risk assessment is essential to eliminate or reduce the negative effects of e-waste in a circular economy. Decision-making plays an important role during the risk assessment in e-waste recycling. This study aims to develop a decision tool under uncertain and risky conditions for achieving sustainability in electronic waste (e-waste) recycling in circular economy. Prospect theory and its aspects are integrated with the sustainability risk assessment in e-waste recycling. In order to evaluate the irrationality and risk attitudes of decision makers in a risky and uncertain environment, the prospect theory-based TODIM (acronym in Portuguese for interactive and multicriteria decision-making, i.e. Tomada de Decisao Interativa Multicriterio) method for a previous computer disassembly problem is used. Using prospect theory, the relationship between loss aversion, reference point, framing and two selves effect, and sustainability dimensions is presented with a sustainability risk assessment point of view. Further, tasks of computer disassembly processes are prioritized by considering risk factors. The results showed that random access memory modules, motherboard and power supply are the highest priority risks based on the evaluation of listed twelve sustainability risks. In this study, it is suggested that prospect theory is suitable for decisions under risk and uncertainty, and it is applicable to integrate sustainability risk assessment and prospect theory in order to fulfil the gap of knowledge. Relationship between prospect theory and sustainability risk assessment.

PurposeThe 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/approachFuzzy 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.FindingsThe 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/valueThe 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.

This study focuses on the transformation of logistics centers in Industry 4.0. Aim is to reveal the important criteria for logistics centers in Industry 4.0 by considering link to traditional logistics centers practices and proposing a framework for new logistics centers. Initially, literature review to reveal criteria for logistics centers in Industry 4.0 is conducted. Secondly, fuzzy multi-criteria decision-making methodology is used to present the importance order, and the causal relationship between criteria to make recommendations for future implications. The results may be useful for logistics center’s professionals in transition process, and new research topics may be derived for academics.

Transition from Industry 3.0 to Industry 4.0, in other words Industry 3.5 stage, and moving to a circular economy are two significant concepts for organizations that need to make wholesale alterations to their current systems. In order to stay competitive, both these transitions need to follow sustainable resource management and digital transformation principles. However, there are barriers to these changes that organizations should consider. Both Industry 4.0 transition, in other words Industry 3.5, and circularity transition require great efforts to deal with these barriers; in the current environment, organizations need to deal with these barriers simultaneously for more sustainable resource management. This study focuses in particular on circular supply chains in the Industry 3.5 stage. There are some studies that suggest barriers to Industry 4.0 and circular supply chains separately, none of these studies consider them together. From this point of view, this study contributes to existing literature by presenting synchronized barriers that integrate circular supply chain and Industry 4.0 barriers. Firstly, pillars of circular supply chains in Industry 4.0 are explained; synchronized barriers are then presented. A decision-making method, Fuzzy Analytical Network Process, is used to prioritize the synchronized barriers, with theoretical and practical implications proposed according to the result of the implementation.

End of life (EOL) phase of a product is receiving more attention due to increase in environmental concerns, and many studies have been conducted for value creation in EOL, focusing on concepts as remanufacturing, reuse and recycling in sustainable product Engineering, Industrial; Engineering, Manufacturing; Operations Research & Management Science Engineering; Operations Research & Management Science

Environmental pollution leads a rise in sustainable development problems. Greenhouse gases(GHG) are one of the most important barriers against to sustainable development and greener cities. When the causes of GHG are investigated, human activities appeared as one of the main reasons. As one of the human activities, transportation has the highest impact on the increase in GHG emissions in green cities. Of the different transportation modes such as air, railways, and road, this study focused on road transportation due to its greater impact when compared to others in terms of GHG emissions. GHG emission estimation should be the initial step to evaluate current status of countries. Therefore, this study aims to make detailed analysis of GHG emissions in four European countries, due to different types of road transport vehicles. Grey prediction is used to estimate the amount of GHG emissions for each road transport vehicle for each country. In conclusion, implications are presented in order to reduce the GHG emissions and to meet sustainable development conditions according to the numerical results of the estimation and it is aimed to prepare a base for new studies about GHG emissions in road transportation.

PurposeThis 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/approachThe 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.FindingsThe 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 implicationsA 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/valueThis study proposes a multi-stage structure by applying multi-criteria decision-making to HEIs, focussing on wastes from a lean perspective.

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.

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.