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Ports are the key elements of maritime transportation, which is crucial for world trade. Approximately 180 port facilities are located in Turkey. After 2007, 5 of the ports, which are formerly owned by Turkish Republic Railways Administration (TRRA), are privatized. The aim of the study is to evaluate the performance of these privatized ports by multi-criteria decision-making (MCDM) approach.

The application process is performed by a MCDM model. This model includes both criteria (dry bulk, liquid bulk, general cargo, container, RO-RO capacity, total port area, total berth, total berths length and depth) and alternatives (Mersin, Samsun, Bandirma, Iskenderun and Derince Ports). It determines the weights of the criteria by entropy and ranks the alternatives by ARAS and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods.

The results of entropy, ARAS and TOPSIS methods are compared. According to these results, “container” is the most important criteria while Mersin port has the best performance.

In the literature, most of the studies about this subject were analyzed by data envelopment analysis (DEA) and there are no studies had been taken into consideration ports that are owned by TRRA, in Turkey. Moreover, few of these studies used integrated MCDM models, and this is the first study that integrates entropy, ARAS and TOPSIS methods in this field.

This study aims to determine the ranking of the 81 provinces at the NUTS-3 level in Turkey with respect to the personal satisfaction and public services satisfaction by applying Fuzzy Multi-Criteria Decision-Making methods to the Life Satisfaction Survey Results.

Fuzzy TOPSIS, Fuzzy MULTIMOORA and Fuzzy ARAS are implemented to assess life satisfaction of the individuals who lived in provinces, based on Life Satisfaction Survey 2013 for Turkey’s national comparison. In the solution process, 14 indicators for personal satisfaction and 38 indicators for public services satisfaction were considered.

The results showed that personal health satisfaction, earnings from work satisfaction and monthly income satisfaction are the most important criteria in terms of personal satisfaction. Also, healthcare services satisfaction, judicial services satisfaction and education services satisfaction have the highest importance in terms of public services satisfaction. The final ranking of the 81 provinces is obtained by considered methods. According to the ranking results, there is no significant difference between the east and the west part of Turkey in terms of personal satisfaction, whereas there is a distinct difference between them in terms of satisfaction with public services.

This study is the first research for evaluating the ranking of the provinces at the NUTS-3 level in Turkey according to the Life Satisfaction Survey 2013 results considering 14 indicators for personal satisfaction and 38 indicators for public services satisfaction by using FMCDM approaches that have not been applied before.

With the rapid advancement of technology, companies use new technologies to produce their products and services to maintain a competitive advantage. As companies alone cannot research and develop their technologies, they should use knowledge sources outside the organization that may exist throughout the world; hence, organizations need technology transfer. Because the success rate of technology transfer projects is low, the need to accurately assess and investigate the critical success factors of technology transfer projects is felt. In this regard, this study aims to identify and prioritize the critical success factors in technology transfer projects.

In this research, 56 critical success factor (CSF) were extracted from the context of the articles and were adjusted using experts’ opinions in different phases, as well as the fuzzy-Delphi approach. Finally, 15 factors were categorized in the form of steps of the technology transfer model: STAGE-GATE. In the next step, the set of criteria needed to prioritize CFSs was extracted from the literature and finalized with the help of the experts. Then, how each of the CSF influences the identified criteria was scored according to the organization’s export opinions. Finally, the priority of each key success factor was calculated using the additive ratio assessment (ARAS) method.

The results obtained for prioritization of the critical success factors show that experience in technology transfer in the transferee company, the existence of experienced technology transfer managers, sufficient organizational infrastructure and documenting project problems, achievements and experiences are four critical success factors of the technology transfer projects. Considering the long-term and short-term specific goals of the technology transfer process and the choice of technology in line with the company’s commercial strategy are also the critical success factors with the next priorities.

The combination of ARAS and step-wise weight assessment ratio analysis methods for identifying and prioritizing managerial decisions in the high-tech industries is a value of this research. Also, a combination of novel multi-attribute decision-making methods by the older framework of new product development is another contribution of this research.

Outsourcing is a crucial tool for an organization to focus on its core business operations. The purpose of this study is to find critical success factors (CSFs) of outsourcing and to prioritize the performance outcomes of outsourcing because of the adoption of its CSFs.

This research proposes the hybrid framework of fuzzy Delphi, fuzzy analytic hierarchy process (F-AHP) and fuzzy additive ratio assessment (F-ARAS) to fulfill the research objectives. Fuzzy Delphi is used to finalize the CSFs of outsourcing and F-AHP provides the relative weights to it. F-ARAS is used to prioritize the outsourcing performance indicators with respect to CSFs. The empirical case investigation of three Indian large-scale public sector process industries is conducted to demonstrate the applicability of the proposed framework.

The result shows that increased dominance in core activity, ability to increase or decrease capacity, improved financial performance, optimized resource utilization and increased market share are the top five performance outcomes because of the adoption of outsourcing CSFs.

Factors such as cultural, political, environmental and size of the organization may have a significant implication on the research results.

This is a novel approach towards the prioritization of performance outcomes of outsourcing. Moreover, the present research is a helpful tool to manage outsourcing and choosing which performance outcome of outsourcing ought to be used to measure implementation. This will help to recognize potential opportunities and preparing strategic planning for both short-term and long-term goals.

The present study is aimed to develop a firm export performance measurement model. Increased levels of globalization are forcing firms, especially SMEs (i.e. small and medium-sized enterprises) and entrepreneurial firms, to enter new markets and increase their exports. Consequently, export performance measurement has become a vital tool for achieving competitive advantages, and this type of measurement is considered an important topic of research in the field of international marketing. However, the literature lacks a comprehensive framework for measuring export performance, even though many criteria for gauging this performance's parameters have been discovered and applied.

A literature review was conducted, and the most important criteria for export performance measurement was identified using weights obtained by stepwise weight assessment ratio analysis method. Then, the export performance of five firms was evaluated using the additive ratio assessment method with interval-valued triangular fuzzy numbers.

The 15 most significant criteria were identified and categorized into three dimensions: economic, strategic, and other. The strategic dimension was identified as the most important, while the criteria “strategic goals achievement” and “return on investment” were found to be the most relevant.

A comprehensive framework including a definitive set of the most prominent, useful evaluation criteria was established which enables both scholars and practitioners to assess export performance.

The current study attempts to fill the gaps in the literature by presenting a comprehensive framework for export performance measurement.

In recent years, determining the effective and suitable supplier in the supply chain management (SCM) has become a key strategic consideration to the success of any manufacturing organization in terms of business intelligence (BI), as many quantitative and qualitative critical factors are measured from big data. In today’s competitive business scenario, the main purpose of this study is to determine suitable and sustainable suppliers during supplier selection process is to reduce the risk of investment along with maximize overall value to the customer and develop closeness and long-term relationships between customers and suppliers to build a resilient SCM to mitigate uncertainty for automotive organizations.

As these types of decisions generally involve more than a few criteria and often necessary to compromise among possibly conflicting factors, the multiple-criteria decision-making becomes a useful approach to solve this kind of problem. Considering both tangible and intangible criteria, the aim of this paper is the presentation of a new integrated fuzzy analytic hierarchy process and fuzzy additive ratio assessment method with fuzzy entropy using linguistic values to solve the supplier selection problem to build the resilient SCM under uncertain data. Fuzzy entropy is used to obtain the entropy weights of the criteria.

Organizations gather massive amounts of information known as BD on the basis of historical records of uncertainties from several internal and external sources to manage uncertainty to improve the overall performance of organizations using BI strategy for analyzing and making effective decision to support the managements of automotive manufacturing organizations in an information system.

Although this study tries to represent a full analysis on suitable and resilient global supplier selection under various types of uncertainty, still there are some improvements that can be made in the future by developing a more refined and more sophisticated approach to further enhance the performance of the proposed scheme to calculate overall rating scores of the alternatives.

The novelty of this paper is to propose a framework of BI in SCM to determine a suitable and resilient global supplier where all the meaningful information, relevant knowledge and visualization retrieved by analyzing the huge and complex set of data or data streams, i.e. BD based on decision-making, to develop any manufacturing organizational performance worldwide.

This paper proposes an integrated IT2F-FMEA model under a group decision-making setting. In risk assessment models, experts' evaluations are often aggregated beforehand, and necessary computations are performed, which in turn, may cause a loss of information and valuable individual opinions. The proposed integrated IT2F-FMEA model aims to calculate risk priority numbers from the experts' evaluations and then fuse experts' judgments using a novel integrated model.

This paper presents a novel failure mode and effect analysis (FMEA) model by integrating the fuzzy inference system, best-worst method (BWM) and weighted aggregated sum-product assessment (WASPAS) methods under interval type-2 fuzzy (IT2F) environment. The proposed FMEA approach utilizes the Mamdani-type IT2F inference system to calculate risk priority numbers. The individual FMEA results are combined by using integrated IT2F-BWM and IT2F-WASPAS methods.

The proposed model is implemented in a real-life case study in the furniture industry. According to the case study, fifteen failure modes are considered, and the proposed integrated method is used to prioritize the failure modes.

Mamdani-type singleton IT2F inference model is employed in the FMEA. Additionally, the proposed model allows experts to construct their membership functions and fuzzy rules to capitalize on the experience and knowledge of the experts. The proposed group FMEA model aggregates experts' judgments by using IT2F-BWM and IT2F-WASPAS methods. The proposed model is implemented in a real-life case study in the furniture company.

As in line with eco benchmarking, the purpose of this paper is to solve a location selection problem in an emerging country by applying sustainability benchmarking principles.

A hybrid multi-criteria decision-making method, fuzzy AHP and Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE), is used as methodology to make sustainability benchmarking for logistics center location selection.

It is revealed that according to AHP and PROMETHEE calculations, Kemalpasa is determined as the most appropriate location from the sustainable perspectives. Torbali is specified as the worst location to construct a logistics center in terms of benchmarking criteria based on sustainability concerns. Based on these numerical results, managerial implications are presented with a sustainability benchmarking view.

The main originality of this study is integrating one of the relatively new topics, sustainability benchmarking, with a popular area, logistics center location selection.

This paper aims to assess and prioritize manufacturing companies in the healthcare industry based on critical success factors (CSFs) of their reverse logistics (RL). The research involves seven medical device companies located in the Tehran Province, Iran.

To identify and prioritize companies based on CSFs of RL, the study proposes a three-phase decision-making framework that integrates the Delphi method, the best-worst method (BWM) and the Additive Ratio Assessment (ARAS) method with Z-numbers. The weights required for this method are obtained by a variant of the BWM based on Z-numbers, denoted as Z-numbers Best-Worst Method, or ZBWM. Since decision-makers face an uncertain environment, Z-numbers, which are a kind of fuzzy numbers, are applied.

First, after customizing CSFs by the Delphi method and obtaining 15 CSFs of RL, these are ranked by the hybrid BWM-ARAS method with Z-numbers. Results reveal which company appears to perform best with respect to their RL implementations. Based on this result, healthcare device companies should choose the highest priority company based on the selected RL CSFs and results from using the BWM-ARAS method with Z-numbers.

The contribution of this paper is using a hybrid ARAS-BWM method based on Z-numbers. Each of these methods has some merits compared to other similar methods. The combination of these methods contributes a new approach for prioritizing companies based on RL CSFs with high accuracy and reliability.

The work on bridge resilience assessment includes quantitative and qualitative approaches to compare the multiple bridges based on their resilience. But still, the bridge resilience obtained by these assessment approaches is inefficient when prioritising multiple bridges to improve their resilience. Therefore, this study aims to develop a methodology for prioritising the bridges to improve their resilience.

The research methodology follows three sequential phases. In the first phase, criteria importance through intercriteria correlation (CRITIC) technique is used to compute the criteria weights. The criteria considered are age, area, design high flood level, finish road level FRL and resilience index of bridges. While 12 river-crossing bridges maintained by one bridge owner are considered as alternatives. Then, in the second phase, the prioritisation of each bridge is evaluated using five techniques, including technique for order of preference by similarity to ideal solution, VIKOR (in Serbian, Visekriterijumska Optimizacija I Kompromisno Resenje), additive ratio assessment, complex proportional assessment and multi-objective optimisation method by ratio analysis. Finally, in the third phase, the results of all five techniques are integrated using CRITIC and the weighted sum method.

The result of the study enables bridge owners to deal with the particular bridge that requires resilience improvement. The study concluded that it is not enough to consider only the bridge resilience index to improve its resilience. The prioritisation exercise should consider various other criteria that are not preferred during the bridge resilience assessment process.

The proposed methodology is a novel framework based on the existing multi-criteria decision-making (MCDM) techniques for contributing knowledge in the domain of bridge resilience management. It can efficiently overcome the pitfall of decision-making when two bridges have the same resilience index score.