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The aim of this study is to evaluate the potential geographic locations for ecotourism activities and to select the best one among alternatives.

The proposed model consists of four sequential phases. In the first phase, different geographic criteria are determined based on existing literature, and data are gathered using GIS. On equal criteria weighing, alternative locations are determined using GIS in the second phase. In the third phase, the identified criteria are weighted using analytical hierarchy process (AHP) by various stakeholders of potential ecotourism sites. In the fourth phase, the PROMETHEE method is applied to determine the best alternative based on the weighted criteria.

A framework including four sequential steps is proposed. Using real data from the Black Sea region in Turkey, the authors test the applicability of the evaluation approach and compare the best alternative obtained by the proposed method for nine cities in the region. Consequently, west of Sinop, east of Artvin and south of the Black Sea region are determined as very suitable locations for ecotourism.

The first limitation of the study is considered the number of included criteria. Another limitation is the use of deterministic parameters that do not cope with uncertainty. Further research can be conducted for determining the optimum locations for different types of tourism, e.g. religion tourism, hunting tourism and golf tourism, for effective tourism planning.

The proposed approach can be applied to all area that cover the considered criteria. The approach has been tested in the Black Sea region (nine cities) in Turkey.

Using the proposed approach, decision-makers can determine locations where environmentally responsible travel to natural areas to enjoy and appreciate nature that promotes conservation have a low visitor impact and provide for beneficially active socioeconomic involvement of local individuals.

To the best knowledge of the authors, this is the first study which applies a GIS-based multi-criteria decision-making approach for ecotourism site selection.

The main objective of this paper is to integrate quality with triple bottom line dimensions as well as economic, social and environmental concerns within a disassembly line balancing problem.

This study presents a new disassembly line balancing model to maintain the triple bottom line. This proposed model applies a hybrid MCDM considering social, environmental, quantitative and qualitative business and quality dimensions. In this research, fuzzy AHP prioritizes the dimensions and fuzzy TOPSIS ranks the disassembly operations.

The findings show that the disassembly line’s cycle time decreased from 36 s to 32 s, with the main and sub-criteria considered. Therefore, this study reveals that integrating sustainability dimensions with quality may not result in sacrificing cycle time.

Globalization, the increase in demand, the complexity of supply chains and the environmental, economic and social dimensions should be examined together for these operations to be sustainable. Not only these dimensions but also the perception of quality, an essential aspect of production, must be reflected in the disassembly line balancing. There is a need for sustainability issues in disassembly line balancing, which is becoming increasingly important due to environmental concerns, resource conservation, corporate social responsibility and potential cost savings. However, a significant gap in the literature points to the need to cover all three dimensions of the triple bottom line and other production-related dimensions in the disassembly line balancing problem.

Personnel selection is an important process in management due to the high cost of unfavorable employee procurement. The multi criteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. The purpose of this paper is to propose a grey theory‐based hybrid approach to solve personnel selection problems in uncertain environments.

The work procedure is as follows: first, grey analytic network process (GANP) is applied to calculate selection criteria weights and then candidates are ranked by using grey possibility degrees. Finally, an example of a selection problem of sniper for a military unit was used to illustrate the proposed approach.

The analyses of the results show that grey theory‐based methods have enormous chance of success for personnel selection problems in uncertain situations.

Although there are some applications for personnel selection problems that used grey system theory in the literature, the combination of GANP and grey possibility degrees is used for personnel selection problem in this study.

The relationship between energy consumption (EC) and economic growth is a well-known and more studied subject in literature. In this study, Turkey's EC and gross domestic product (GDP) relation is analyzed. The aim of this study is to find out the relative importance of energy components on GDP for Turkey. Hence, the authors can make some strategic implications up to the importance of energy components on GDP.

In this study, two methods are used to find out the importance of energy types on economic growth for Turkey. First, grey relational analysis (GRA) is used to determine the most influential energy types on GDP. Then regression analysis is used to compare outcomes which are yielded by GRA.

The analyses of the results show that the most important energy sources are oil and renewables for Turkey. Both energy sources have equal importance with economic growth. However, it is implied that this balance should be destabilized for the sake of renewable production and usage to have less carbon footprint.

There are many econometric models used for defining EC and economic growth causality. But the authors could not come across any study which investigates relationship between economic growth and EC by GRA. The method that is newly used for this subject and applying analysis for a developing country is the importance of this study.

The purpose of the study is the evaluation of choosing the determined logistics centers’ (LCs’) locations via Multi-Criteria Decision-Making (MCDM) methods.

Since there is more than one criterion in the evaluation of LC location, MCDM methods are used. The Entropy and CRiteria Importance Through Intercriteria Correlation (CRITIC) methods are used to determine the main criteria and sub-criteria weights. The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method is used for ranking and evaluating 12 alternatives in Turkey and sensitivity analysis according to the threshold values of criteria and preference functions.

Possible LC alternatives in Turkey and 12 locations ranked. Changing the criteria weights at a significant level did not affect the ranking results much. In the sensitivity analysis of the criteria for which market data could not be obtained (scored by the experts) it is found that they either made no difference or made little difference in the ranking of the alternatives.

In terms of sustainability, economic factors along with environmental and social dimensions are important criteria for logistics companies and LC. The use of these variables in the LC location selection makes a difference.

This study focuses on LC location selection, via PROMETHEE with evaluated preference functions for criteria, taking into account nine scenarios that use variable criteria weight calculated via different MCDM methods. The results are evaluated by using sensitivity analysis and taking into account the sustainability aspect for LC. Multiple methods have been used effectively together in a way that support each other.

Considering the contribution of freight villages (FVs) to the economy and sector, transportation cost advantage, environmental externalities, labor costs, employment, etc. criteria evaluation is important in selecting FV location. Environmental sustainability and social dimensions are becoming important criteria for companies in logistics. The purpose of the study is to determine/model the criteria interaction and also determine the criteria priorities in the FV location selection process. Meanwhile, the study aims to evaluate these criteria and present information to researchers and decision makers.

Six main criteria and 29 sub-criteria are selected from related literature. Decision making trial and evaluation laboratory (DEMATEL) method is used for determining/modeling the criteria interaction and sketching interaction diagram, and the Analytical Hierarchy Process (AHP) method is used for determining the criteria priorities. One/two-way pairwise compared main/sub-criteria views are obtained from 48 experts for calculations.

“Trade potential”, “transportation networks” and “economic factors” have the highest priorities, respectively, out of six main criteria, and they have the most powerful interactions that put these criteria to the center of decision process. Sub-criteria of “foreign trade potential”, “proximity to the port”, “market opportunities” and “proximity to the railway” out of 29 have a total 36.42% priority, more than one-third of the importance.

Criteria are evaluated in FV location selection for FV sustainability using criteria interaction diagrams, affecting/being affected by the level of each criterion and their priorities. This study shows a hybrid derivation from DEMATEL-AHP usage methods together. High-volumed and qualified/experienced expert group judgments in Turkey are evaluated.

The present study aims to provide a practical and robust assessment technique for assessing countries' investability in global supply chains to practitioners. Thus, the proposed approach can help decision-makers evaluate and select appropriate countries in the expansion process of the global supply chains and reduce risks concerning country (market) selection.

The present study proposes a novel decision-making approach, namely the REF-Sort technique. The proposed approach has many valuable contributions to the literature. First, it has an efficient basic algorithm and can be applied to solve highly complicated decision-making problems without requiring advanced mathematical knowledge. Besides, some characteristics differentiate REF-Sort apart from other techniques. REF-Sort employs the value or value range that reflects the most typical characteristic of the relevant class in assignment processes. The reference values in REF-Sort and center profiles are similar in this regard. On the other hand, class references can be defined as ranges in REF-Sort. Secondary values, called successors, can also be employed to assign a value to the appropriate class. REF-Sort can also determine the reference and successor values/ranges independently of the decision matrix. In addition, the proposed model is a maximally stable and consistent decision-making tool, as it is resistant to the rank reversal problem.

The current papers' findings indicate that countries have different features concerning investment. Hence, the current paper pointed out that only 22% of the 95 countries are investable, whereas 19% are risky. Thus, decision-makers should make detailed evaluations using robust, powerful, and practical decision-making tools to make more reasonable and logical decisions concerning country selection.

The current paper proposes a novel decision-making approach to evaluate. According to the authors' information, the proposed model has been applied to evaluate investable countries for the global supply chains for the first time.