In contemporary workplaces, organizational safety is not just a regulatory obligation but a critical determinant of sustainable success. With the evolving technological advancements in industries, understanding the factors that influence occupational safety becomes paramount. This study examines the multifaceted structure of occupational safety criteria, recognizing its importance in ensuring not only the physical well-being of workers but also the organizational resilience. Utilizing the Interval-Valued Picture Fuzzy Analytic Hierarchy Process (IVPF-AHP) method, this research aims to prioritize the most crucial factors influencing safety performance. Through a comprehensive analysis of 20 sub-criteria under five main categories - Organization, Safety Climate, Regulatory Characteristics, Workplace Environment, and Individual Characteristics - the study reveals insights into the nuanced interplay of organizational, managerial, and individual factors that shape safety outcomes. The findings underscore the prominence of factors such as Workload Pressure, Management and Supervisor Commitment to Safety, Sanctions and Auditing, Number of Subcontractors, and Equipment Conditions in enhancing safety performance.

Sorting-based multiple attribute decision-making (MADM) methods address managerial challenges in the hypercompetitive contemporary business life effectively by facilitating efficient organization and retrieval of data, thereby enhancing analysis, optimization, and user experience. Among others, the additive ratio assessment sorting method (ARASsort) is a highly preferable one due to its capacity to offer a dependable sorting mechanism for multi-attribute assessment, characterized by a notable degree of practicality. While experts traditionally assign attribute weights subjectively in sorting methods, robust and objective tools like criteria importance through intercriteria correlation (CRITIC) offer scientific approaches to balance subjectivity. The originality of this study is threefold: First of all, this study is the first one proposing a CRITIC-ARASsort hybrid algorithm to mitigate subjectivity in sorting. Secondly, to address uncertainty in human judgment more comprehensively, it introduces the integration of fuzzy logic, particularly intuitionistic fuzzy sets (IFSs), into ARASsort and thus to the hybrid algorithm, resulting in the development of IF-CRITIC-ARASsort. Furthermore, a new intuitionistic fuzzy standard deviation formula is proposed to overcome the early defuzzification problem in previously proposed versions of IF-CRITIC method in the literature. The applicability of this method is demonstrated in a credit rating scenario, showcasing its utility in complex decision-making processes.

Failure Modes and Effects Analysis (FMEA) is a widely used method to define the failure modes those give harm to a system the most. However, it falls short in decreasing the total risk in the system at the maximum level possible at once, since it focuses on conducting only one corrective action at a time for curing the highest risk failure mode. Although it can still decrease the total risk significantly, since it is done via several iterations, it can be considered slow and costly. Considering the hyper competitive environment in contemporary business life, to overcome this important shortcoming, this study proposes a novel approach which includes the combination of FMEA and quality function deployment (QFD) under decomposed fuzzy environment. There are many studies in the literature combining FMEA with QFD, yet this is the only one to the best of the authors' knowledge that starts with FMEA and feeds QFD with its findings. This significantly original approach lets the practitioners define the technical characteristics those decrease the overall risk of the system the most at once, in only one iteration. Then, improvement activities can be defined for the highest priority technical characteristics. To deal with uncertainty and ambiguity in the decision process, and varying perspectives of decision makers, decomposed fuzzy sets are used to provide the decision makers with the ability to use an optimistic and a pessimistic expression for each evaluation they make.

This study aims to evaluate the sustainability of various decarbonization strategies for building heating to support the Paris Agreement’s target of limiting global warming to 1.5°C. The selected strategies include district heating, air source heat pumps, hybrid heat pumps, and hydrogen, with natural gas as a baseline. The assessment focuses on economic, environmental, social, and technical performances and the availability of each strategy based on 16 sub-criteria. These sub-criteria include costs, environmental impacts, public health, employment, public acceptance, safety, heating performance, process control, scalability, building upgrades, street works, and deployment. The results highlight that while district heating and hydrogen offer strong sustainability potential, they face specific challenges in deployment and infrastructure changes. This comprehensive evaluation provides insights for decision-makers to prioritize strategies that balance sustainability with practical implementation challenges.

The transition to a hydrogen-based economy necessitates a comprehensive evaluation of different hydrogen storage options, considering their sustainability performance. This study innovatively applies the Interval-Valued Intuitionistic Fuzzy Analytic Hierarchy Process (IVIF-AHP) to evaluate and compare four hydrogen storage options: Compressed Hydrogen Gas (CHG), Cryogenic Liquid Hydrogen (CLH), Metal Hydride (MH), and Underground Hydrogen (UH). The evaluation criteria are derived from four dimensions of sustainability: economic, environmental, social, and technical performance, each further decomposed into sub-criteria. The study's novelty lies in using a novel intuitionistic fuzzy AHP, offering a more nuanced and robust understanding of the trade-offs between the various options and effectively capturing the vagueness and subjectivity inherent in human decision-making. Through this methodology, CHG emerged as the most promising option with a preference score of 0.487, closely followed by UH with a score of 0.453. The lowest preference score was accorded to MH, with a score of 0.301. These quantitative insights underscore the relative sustainability performance of each technology under the defined criteria. The findings contribute to the growing body of literature on sustainable hydrogen storage, providing policymakers and practitioners with a multicriteria decision-making tool that captures the complexity of sustainability considerations. This study underlines the critical role of holistic, multicriteria evaluations in advancing sustainable hydrogen storage. It encourages further exploration and validation of its approach in different contexts and with updated technological advancements.

Fuel cells have been attracting many researchers and industry partners' attention due to their clean, quiet, modular, and flexible operation characteristics. As Power-to-Gas technologies evolve and get more sustainable, well-developed fuel cells will be needed to convert the chemical energy stored in the gas form to useful products such as power and heat. For that reason, a comprehensive sustainability investigation of fuel cells is conducted by taking their economic, environmental, social, and technical performance into account. The selected fuel cells are polymer electrolyte membrane, alkaline, phosphoric acid, molten carbonate, and solid oxide. These fuel cells’ performance is comparatively investigated based on four primary and 15 sub-criteria. The selected performance criteria are economic (initial and running costs), environmental (GHG emissions, land use, solid waste generation, and water discharge quality), social (employment and training opportunities, impact on public health, and public acceptance), and technical (energy and exergy efficiencies, process control, start-up time, and scalability). This study is the first in the literature to conduct an in-detail and very inclusive sustainability evaluation of fuel cells. It is expected to guide many professionals from academia and industry towards developing cleaner, safer, more affordable, and efficient fuel cells.

In today’s world, the joint impact of globalization and knowledge economy has been intensifying incessantly and consequently, many new concepts have been produced. In this sense, organizational capital is one of the prominent concepts that attracts the interests of both academicians and practitioners. Organizational capital is a component of the intellectual capital that is the collection of all assets that create the artistic ability of the organizations’ potentials. In order to regulate and manage such a very potent force, the businesses should know how to measure it. This study aims to provide a methodology for the prioritization of the criteria influencing organizational capital under unstable conditions. In order to achieve this goal, a novel fuzzy based multi criteria decision making (MCDM) tool named hesitant fuzzy analytic hierarchy process (HFAHP) is used. The proposed model consists of three main attributes; knowledge management, organizational structure and management influence. The sub-attributes of knowledge management involve knowledge creation, knowledge acquisition, knowledge sharing, knowledge utilization and store knowledge. The sub-attributes of organizational structure consist of span of control, departmentalization and the number of hierarchical levels. Similarly the sub-attributes of management influence comprise rules and governance, corporate culture and strategic leadership. To outline the relative priority of every attribute, preferences of specialists were collected by administering a questionnaire which was based on pair-wise comparisons of the criteria respectively. The results of the study indicated that “Knowledge Management” had the highest importance, but the weight of “Management Influence” was very close to it. The effect of “Organizational Structure” on organizational capital was very low. Among sub criteria, “Strategic Leadership” was found as the most vital attribute which influences organizational capital.

In contemporary business world, employees are one of the core competencies of organizations and to attract, retain, and engage talented employees is crucial for organizations for sustainable success. Understanding and leveraging employee experience is one of the tending topics for organizations because positive employee experience affects employees' attachment, engagement and loyalty to the organization. Human resource management departments and leaders can apply different strategic initiations to boost employee experience in their organizations. In this study, we aim to design an integrated model for leaders and organizations to guide them for creating positive employee experience to have engaging, enjoyable, and productive work environment. The integrated model includes two phases: (1) evaluation of criteria affecting positive employee experience by hesitant fuzzy analytic hierarchy process (HFAHP) and (2) developing a practical scoring procedure to help companies with their self-assessments by using fuzzy simple additive weighting (FSAW) method. In the first phase, four main and sixteen sub-criteria are taken into consideration. For the second phase, the application of the integrated model is demonstrated with a numerical example from real world. The results indicate that for positive employee experience, leadership has the highest importance followed by human capitals' development opportunity, positive organizational culture, and communication.

In contemporary business life, retention of talented employees is crucial for organizations to preserve created value. Considering their attitudes, behaviors and personality, millenials are different from former generations, and retaining them requires a distinct management approach. This study aims to provide the decision makers with a more effective and efficient tool for evaluating career management activity types leading to employee retention of millenials. A novel method, Spherical Fuzzy Analytic Hierarchy Process (SFAHP) is used in the study to; (i) define the importance levels of the criteria having impact on employee retention, and (ii) assess various career management activity types for employee retention. To ensure the practical use of the model, a numerical example from real world is presented. The results indicate that “leadership and management” is the most important factor, and “development-oriented career management activities” is the highest impact activity type in increasing the employee retention.

As energy security concerns push the countries to find more sustainable and renewable sources of energy, wind power became one of the fastest growing renewable energy source. As only a handful of wind turbine manufacturers established foothold in world markets, it is essential for managers to make right decisions regarding which wind turbines they will install in any given project. This study explores the literature on the wind turbine selection, solicits opinions of the industry experts to come up with a more realistic set of criteria and develops a decision making tool integrating hesitant fuzzy Analytic Hierarchy Process (AHP) with Technique-for-Order-Preference-by-Similarity-to-Ideal-Solution (TOPSIS). As wind turbine selection problem includes both quantitative and qualitative criteria, it is difficult to tackle with high uncertainty by using traditional techniques. Thus, hesitant fuzzy sets (HFS) which is an evolved fuzzy tool that deals with vagueness is utilized. In this study, hesitant fuzzy AHP is utilized to overcome the ambiguity, which occurs during criteria prioritization. In order to rank the alternatives, hesitant fuzzy TOPSIS is applied. By the help of this integrated approach, evaluation process becomes systematic and easy to deal with vagueness. The proposed method is demonstrated by a case study in Turkey.

ERP turned out to be one of the most valuable tools since it is a strong means to integrate the functions both within a company and among the companies within a supply chain. This study aims to propose a comprehensive model to evaluate alternative ERP packages and select the best one. The hierarchical model proposed in this study is applicable in any industry with minor modifications. However, considering the importance of automotive industry both for global and national economies, harsh competition, and many industry specific requirements, a dedicated full model is proposed. This industry specific nature together with the comprehensive model constitutes the major originality of the study. Fuzzy AHP is used to calculate the weights of criteria and sub-criteria within the model. Then, to illustrate the application of the model, fuzzy TOPSIS is utilized in a numerical example for ranking three alternative ERP systems.

Affordable, clean, efficient, flexible, and reliable energy storage is an important component of sustainable energy systems. There are several studies in the literature concentrating on improving the sustainability performance of energy storage systems from economic and technical perspectives. However, a comprehensive performance investigation of energy storage systems that take economic, environmental, social, and technical criteria into account is still needed. For that reason, in the present study, it is aimed to perform a complete assessment and analysis of the sustainability of energy storage systems for residential applications in communities and cities. Pumped hydro, conventional batteries, high-temperature batteries, flow batteries, and hydrogen are the selected energy storage systems. In order to handle the vagueness and ambiguity during the assessment and to eliminate the perceived hesitancy in the decision makers' preferences, an innovative method, a hybrid hesitant fuzzy multicriteria decision-making (MCDM) methodology composed of hesitant fuzzy analytic hierarchy process (HFAHP) and hesitant fuzzy technique for order preference by similarity to ideal solution (HFTOPSIS), is utilized to assess the sustainability of the selected systems. In this study, four different performance criteria: economic (power cost and energy cost), environmental (pollutant emissions, area requirement, wastewater quality, and solid waste production), social (safety, accessibility, ease of use, and public acceptance), and technical (efficiency, storage capacity, cycling limit, and performance degradation) are taken into consideration. The performance evaluation results indicate that technical performance has the highest influence and social performance has the lowest influence when evaluating the sustainability of the selected energy storage systems. And hydrogen has the highest sustainability performance compared with the other selected energy storage options.

The fundamental goal of any business is to create value for its owners. In shipping, the value is not only created with freight income, but also with the trade of the vessel itself. A ship has a limited lifetime and can be traded in different markets. The lowest value it will ever receive is its scrap price. An owner may decide to sell a vessel to scrap due to various reasons together with her physical condition and age. In this paper, a fuzzy Analytic Hierarchy Process based decision model is used to provide practitioners with a decision support tool for demolition sale versus further trading of a vessel. The usage of the tool is further illustrated with five actual cases.

PurposeDespite being a low-tech industry, woodwork manufacturing industry that includes furniture and cabinet making, witnessed technological leaps in production technologies due to technical developments in computer numerical control (CNC) machining processes. The managers of this industry have attached high importance to the selection of efficient machines as their decisions directly affect the quality and performance of products produced by the firms. Improper selection process can result in a significant decrease in productivity and flexibility. Therefore, a systematic decision-making procedure is needed to prevent inaccurate investments on machines. The purpose of this paper is to purpose a hesitant fuzzy analytic hierarchy process (HFAHP) based multi-criteria decision making (MCDM) system for CNC router selection in small- and medium-sized enterprises (SMEs) in woodwork manufacturing.Design/methodology/approachThe study proposes a hierarchical model consisting of 4 main criteria and 11sub-criteria for woodwork manufacturing. Technical, personnel, economic and vendor aspects constitute the main criteria. Because of the hierarchical structure of the model, HFAHP is utilized to define the importance weights of the criteria, and to select the most appropriate CNC alternative for a manufacturing company under focus. In a selection procedure, the judgments of decision makers may have vagueness to specify the importance of criteria affecting the decision process. In the literature, the fuzzy set theory has been utilized to deal with such uncertainties. However, when the ideas of the managers have high potential to fall into contradiction in pairwise comparisons, a novel approach is needed to overcome the obstacles. HFAHP allows the membership degree having a set of possible values. It is specifically useful in compromised decisions where experts cannot agree on a single value and prefer to come up with an interval of linguistic variables.FindingsIt is revealed that for SMEs in woodwork manufacturing, the most important criterion in selecting the CNC routers is the technical aspects. It may seem counter intuitive that they do not refrain finding the technical criteria superior to the economic aspects, even though they have limited budgets compared to large-scale firms. This demonstrates that in current competitive environment, SMEs understand the need for high-quality production strategy. The weights of the remaining two criteria (personnel and vendor aspects) are relatively low because they expect that they can easily overcome the problem of adapting the workers by training, and all vendors have quality standard qualifications so they can offer a satisfactory service and supplementary systems.Practical implicationsThe ready-to-use model proposed is specialized for SMEs in woodwork manufacturing. However, to make it an easily adaptable model for every company in the woodwork industry regardless of its size, the calculation process of the priority weights is illustrated in detail with a numerical example. Any company can follow the process using their own preferences to end up with a specific model that will perfectly reflect their own specific priorities. For demonstrating the application of the model, a case study is conducted in a woodwork manufacturing SME to select the best CNC router among three alternatives.Originality/valueThe originality and value of the paper is twofold. First, to the best of our knowledge, this is the first study that proposes a woodworking-specific CNC router selection for SMEs. Second, to handle the high uncertainty in the judgements, and to facilitate consensus among the experts during face to face meetings to develop compromised matrices, a very recently developed method, HFAHP is used.

Hydrogen is seen as the key component of energy systems for a sustainable future. In the literature, there has been extensive efforts on making hydrogen energy systems more sustainable. True sustainability of such systems requires hydrogen to be produced in clean, reliable, affordable, and safe manners without harming neither the environment nor the societies. In the literature, there is a lack of studies focusing on a complete technical, environmental, social, and economic evaluation of hydrogen production systems by taking availability and reliability into account. Therefore, the primary aim of this study is to provide a comprehensive review and investigation on sustainability of hydrogen production systems, which could potentially guide researchers, policy makers, different industries, and energy market customers. The selected hydrogen production methods are grid electrolysis (electricity from fossil fuels), wind electrolysis, PV electrolysis, nuclear thermochemical water splitting cycles, solar thermochemical water splitting cycles and photoelectrochemical cells. To deal with the ambiguity and vagueness in the evaluation process, and to overcome the observed hesitancy in decision makers’ preferences, a novel approach, hesitant fuzzy AHP, is used to evaluate sustainability of the selected hydrogen production methods. In the proposed model, five criteria; economic performance (initial cost and running cost), environmental performance (GHG emissions, land use, water discharge quality, and solid waste), social performance (impact on public health, employment and training opportunities, and public acceptance), technical performance (energy and exergy efficiencies, process control, and raw material input), and availability/reliability (dependence on imported resources, predictability, and scalability) are taken into account. The results show that grid electrolysis is expected to hold the key of sustainable hydrogen production in the near future while the technologies of other methods advance and their associated costs decrease.

Organizations, in their pursuit of accomplishing their vision and goals, need effective management of human resources. Performance Management, among other Human Resources Management (HRM) practices, is the central function, as it delivers the necessary data that complements and enables the other functions. Building an effective performance management system is a multicriteria problem that requires contribution from experts having diverse backgrounds. Moreover, performance management is an inherently vague concept since almost the whole process requires linguistic assessments rather than numerical ones. Hence, to handle all those issues, an intuitionistic fuzzy multi-criteria and multi-expert analytical hierarchy process (AHP) based management model is proposed in this paper. In the determination of the criteria weights of the model, both the aggregated and compromised assessments of the experts are used in order to observe the effects of these two methods on the results. A numerical application is given to illustrate the use of the model.

Due to intense competition of contemporary business life, companies need to achieve significant quality performance for survival. Considering this fact, this study aims to define the factors affecting the quality performance of manufacturing firms and their influence levels. To accomplish this aim, a thorough literature study was conducted to define the quality performance factors. A model was constructed with the yielded 12 factors. By using these, a survey was conducted in 200 large-scale manufacturing firms randomly selected from a list of 1000 most successful firms defined by the Istanbul Chamber of Commerce, Turkey. Data were collected and analyzed by Structural Equation Modeling (SEM) to determine the influence levels of the quality performance factors on the overall quality of the firms. Reliability, conformance of the product to the design specifications, and durability are found to be the three most highly influencing factors, respectively, whereas delivery lead-time of finished products/services to customers is found to be the least influencing factor. The results are expected to help managers in defining their priorities in their quest for quality.

Isletmeler, gunumuz is hayatinin getirdigi yogun rekabet ortaminda hayatta kalabilmek icin, islerini yuksek kalite duzeyinde yurutmek zorundadirlar. Bu noktadan hareketle bu calismanin amaci, mal ureten firmalarin kalite performansini etkileyen faktorleri ve bu faktorlerin kalite performansina etki derecelerini arastirmaktir. Bu amac dogrultusunda oncelikle, kalite performans faktorlerini belirlemek uzere bilimsel yayin arastirmasi yapilmistir. Arastirma sonucunda elde edilen 12 faktor kullanilarak olusturulan model dogrultusunda, Istanbul Sanayi Odasi’nin belirledigi ilk 1000 firma icinde yer alan rassal secilmis 200 mal ureten buyuk olcekli firmaya bir anket gonderilmistir. Toplanan veriler Yapisal Esitlik Modellemesi (Structural Equation Modeling - SEM) ile analiz edilerek, belirlenen kalite performans olcutlerinin firmalarin kalite performansini etkileme dereceleri belirlenmistir. Urunun guvenilirligi, urunun tasarim ozelliklerine (spesifikasyonlara) uygunlugu ve urunun dayanikliligi, kalite performansina en cok etki eden ilk uc degisken olarak bulunmustur. Kalite performansini en az etkileyen degisken ise biten urunlerin musteriye tam zamaninda teslimat orani olarak bulunmustur. Arastirmanin bulgulari kalite performansini arttirmalari icin firmalara yol gosterici olacaktir. Kalite performansini hizli bir sekilde arttirmak isteyen firmalar, oncelikle kalite performansina etki derecesi yuksek olan faktorleri dikkate alip bu faktorler ile ilgili gerekli iyilestirmeleri saglamalidirlar.

Landfill site selection is a multi-attribute decision problem, through which factors like available land area, soil conditions, climatological conditions, and economic considerations are investigated in detail. Frequently, it is a challenge to come up with “the one” solution while tackling such complex systems. Therefore, use of tools such as fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) should be preferred in order to emphasize pros and cons for each of the studied options. In this study, three possible landfill sites for the city of Istanbul are evaluated through expert opinion and by facilitating fuzzy AHP and fuzzy TOPSIS. Initially, the landfill site selection problem is presented in the framework of a model and then the model is mathematically solved by calculating the individual criterion weights. In conclusion, considering the rapid rate of urbanization for the city of Istanbul, the possible landfill sites convey similar overall results, but differ in specific criteria.

Purpose– The purpose of this paper is to develop a self-managed career model, in which protean and boundaryless careers were used.Design/methodology/approach– A hybrid methodology is proposed where Buckley’s fuzzy analytic hierarchy process (FAHP) method was used for prioritization of these criteria, sub-criteria, and indicators, and fuzzy TOPSIS method was used to select the most appropriate career path for a given individual.Findings– The hybrid model for self-managed career was tested with a real numerical example. Findings were congruent with the example’s current career and future career aspirations.Research limitations/implications– The model was tested with one numerical example. The model could be applied to individuals from various cultures, age groups and backgrounds to further discuss its validity.Originality/value– Career decisions are affected from individuals’ values and perceptions. New career orientations like Protean and Boundaryless Career are built upon this fact to include subjectivity. Because of the shortcomings of traditional methods to deal with uncertainty related to subjective evaluations, a FAHP and fuzzy TOPSIS based hybrid multi-attribute decision-support model was utilized to help individuals with their career decisions.