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Blood availability is critical for saving lives in various healthcare services. Ensuring blood availability can only be achieved through efficient management of the blood supply chain (BSC). A key component of the BSC is bloodmobiles, which are responsible for a significant portion of blood donation collections. The most crucial factor affecting the efficacy of bloodmobiles is their location selection. Therefore, detailed decision analyses are essential for the location selection of bloodmobiles. This study proposes a comprehensive approach to bloodmobile location selection for resilient BSCs.

This study provides a novel integration of the spherical fuzzy analytical hierarchy process (SF-AHP) and spherical fuzzy complex proportional assessment (SF-COPRAS) methodologies. In this framework, the criteria are weighted using SF-AHP. The alternatives are then evaluated using SF-COPRAS, employing criteria weights obtained from SF-AHP without defuzzification.

The results show that supply conditions and resilience are the most important criteria for a bloodmobile location selection. Additionally, the validation analyses confirm the stability of the solution.

This study presents several managerial implications that can aid mid-level managers in the BSC during the decision-making process for bloodmobile location selection. The critical factors revealed, along with their importance in choosing bloodmobile locations, serve as a comprehensive guide. Additionally, the framework proposed in this study offers decision-makers (DMs) an effective method for ranking potential bloodmobile locations.

This study presents the first application of multi-criteria decision-making (MCDM) for bloodmobile location selection. In this manner, several aspects of bloodmobile location selection are considered for the first time in the existing literature. Furthermore, from the methodological aspect, this study provides a novel SF-AHP-integrated SF-COPRAS methodology.

Agricultural sector not only meets the nutritional requirements of all living creatures but also generates the primary source of the raw material provided by various branches of industry to fulfill their functions. It is of great importance to increase studies on oilseeds which have an important role in Turkey's agricultural products. They are grown in almost all of the country, which are vital for the nutrition and many sectors. The main purpose of the study is to offer an integrated approach to determine potential warehouse locations for oilseeds.

This is the first study that integrates Delphi, analytical hierarchical process (AHP), technique for order preference by similarity to ideal solution (TOPSIS), P-Median and Panel data analysis in a real case. This integrated approach consists of the following steps, respectively: (1) The criteria were determined by the Delphi method. (2) The weights of the criteria were calculated by AHP and the provinces with the highest oilseed warehouse potential in seven regions of Turkey were specified by TOPSIS. (3) Oilseed warehouse numbers and locations were obtained by P-Median. (4) In order to answer whether the distribution network is profitable in the future with the determined center locations, a forecast model based on panel data analysis was created. (5) Regional representatives were determined for 2030, and the distribution network was analyzed again. (6) The costs that arose in 2018 and 2030 were computed and compared by cost analysis. (7) The effect of the change in criteria weights on the alternative results was tested by scenario analysis.

The findings indicated that oilseed crop production potential and oilseed crop production area turned out to be the most important criteria. Furthermore, the results showed that this model is robust and suitable for warehouse location selection studies.

The study can serve as a guide for local and central policy makers with both the criteria it uses and the model it develops.

The main contribution of this study is that the integrated approach has been used for the first time in location selection in a real case.

The purpose of this paper is to focus on selection of a location which can widely influence business strategy planning and operation profit.

In this paper, the relationship between location strategy and clustering is primarily shown by obtaining location decision criteria and the impact of high‐tech firms with the decision‐making trial and evaluation laboratory (DEMATEL) method. Then, analytic network process (ANP) method is used to explain the value and benefits from cluster location.

The authors study decision‐making for location selection of high‐tech firms in Hsinchu Science Park. The example is based on two dimensions including network effect and transaction cost. Network effect plays a more significant role than transaction cost for this example location selection of high‐tech firms in Hsinchu Science Park. The Science Park is surrounded by entrepreneurial spirit, a significant talent pool, and support infrastructure.

This paper explores how high‐tech managers make their decisions on location strategy in Science Park.

The authors found that cost and benefit factors of network effect dominate the major decision‐making in selection of location and has direct impact on strategic intent. They also have shown that the DEMATEL and ANP approaches are valuable for evaluating this situation.

This study aims to adapt analytical hierarchy process (AHP) for choosing the optimal location for sport facilities. The location of a sports facility contributes significantly to its potential success or failure. Therefore, factors affecting such location-related decisions must be carefully studied and prioritized in a systematic fashion.

This study develops a seven-step framework which may be used to decide on a location from among several alternatives. Through an extensive literature review, this study first determines the factors affecting sports facility location selection and then applies AHP steps by asking several sports facility owners and managers to assess importance of the criteria.

This study determined the sport facility location selection factors as “ease of access,” “facility features,” “financial issues,” “neighborhood” and “market,” and further divided each factor into its subfactors. To illustrate the framework of using AHP as a tool to select the right location for sport facilities, we chose three candidate locations and scored them according to the calculated weight scores of the criteria, identifying the strengths and weaknesses of each location.

This study provides several managerial implications that may guide sport facility investors in choosing the right location.

This study presents a method to evaluate different factors for different actors of sport industry in a systematic way. Private investors can use the method for securing sufficient number of potential customers in a well-selected location. Government institutions and public policymakers can use the method, possibly with different sets of factors, to decide on the location of public sports facilities to maximize the number of visitors or to reach disadvantaged or underserved populations.

This framework of AHP method can help private and public investors and policymakers evaluate and make the optimal decision for choosing sports facility locations. This study contributes both to sport management theory and practice as well as to operation management literature. This study also refined the scattered factors in the literature of selecting a sport facility site in a more understandable and adaptable way.

The purpose of this paper is to propose a disaster logistics center location selection decision support system, based on analytic hierarchy/fuzzy analytic hierarchy process methods, which will serve to fulfill the needs of disaster victims and rescue teams after a possible earthquake, and to implement the proposed systems for Istanbul.

Determining the appropriate location from among the possibilities by taking many sophisticated and inter‐related processes and parameters into consideration under stringent constraints is one of the keystones of logistics. Disaster logistics center location selections are extremely complex and vital. In this paper, analytic hierarchy/fuzzy analytic hierarchy process methods are used to compose a decision support system for determining the location of disaster logistics centers. The criteria and the weighting for the criteria that are used are determined via a questionnaire technique applied to specialists working in the Istanbul Center of Disaster Coordination.

Results gathered from the implementation of the proposed models to the chosen case illustrate that systems successfully determine the location, and both models point out the same result with different weights.

The paper introduces two disaster logistics center location selection decision support systems (fuzzy and crisp) and presents an empirical case study of the proposed models for Istanbul. The proposed model and outcomes from the application may shed light on future work, especially in the field of disaster logistics management.

Instead of reacting to requests for space, CRE executives should be included in any location selection decision‐making process in order to understand the drivers for the action, and to ensure that the real estate solution prpoerly serves the business need. A comprehensive site selection process is one which works from the strategic goals of the company through identifying the business need for the new or consolidated operation, through the tactical tasks of identifying appropriate candidate areas, evaluating those areas, determining the fiscal impact of the move, and on through the implementation of any resulting action.

Locating disaster response centers is one of the key elements of efficient relief operations. The location and infrastructure of the candidate facilities usually conform to the required criteria at different levels. This study aims to identify the criteria for the main and local distribution center location problem separately and prioritize each candidate distribution center using a hybrid multiple criteria decision-making approach.

The proposed model incorporates analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) under interval type-2 fuzzy sets (IT2FSs) to overcome the uncertainty of experts` judgments and expressions in the evaluations of candidate distribution centers. In the proposed approach, weights of the criteria are determined using type-2 fuzzy AHP and the candidate distribution centers are prioritized using type-2 fuzzy TOPSIS.

Transportation, cost, infrastructure and security are determined as the main criteria for the main distribution center location criteria. Cost, warehouse facilities and security are the main criteria for local distribution center location selection. Prioritization enables decision-makers to assess each alternative accordingly to be able to select the best locations/facilities for efficient disaster response operations.

This study proposes new multi-criteria decision support models for prioritizing disaster response distribution centers. IT2FSs are used to be able to reflect both the complexity and vagueness of disaster environment and expert opinions. Different support models are suggested for main and local distribution centers considering their different missions. The proposed methodology is applied in Istanbul city, Turkey, where a high-magnitude earthquake is expected.

The determination of the appropriate site for the location of a research institute represents a multi-criteria problem which requires a scientific approach for decision-making. The research centre in this study is an institute that intends to carry out the state-of-the-art research activities and provide the requisite skills to expedite and optimize the manufacturing of rail cars in South Africa. Hence, the selection of a suitable and conducive location capable of achieving these aforementioned objectives in an effective manner is a problem which requires scientific justification for the allocation of the weights and biases. In light of this, using various decision techniques, this paper aims to establish a suitable framework for the location selection of the research institute which is capable of meeting the short- and long-term objectives of the institute.

This aim was achieved by ascertaining the suitability of potential location alternatives using the factor rating (FR) and centre of gravity (CoG) technique.

The CoG revealed that any location within the longitude of 28.28 and latitude of −25.75 (with a Cartesian coordinate position of 5053.62; 2718.69) is suitable for the research institute, while the result of the FR/weighted score matrix revealed that location J₃ with a weighted score of 72.6% is the most suitable location for the research institute with the longitude of 5053.62 and latitude of 2718.69.

The results of this paper helped decision-makers in locating the given research institute which is currently operational.

The present study is focussed on the application of location decision techniques in the research institute scenario. The combination of FR and CoG techniques for the selection of the most suitable location for a research institute amidst conflicting criteria has not been widely reported by the existing literature.

The purpose of this paper is to show that there is a wealth of academic literature that qualitatively examines the outsourcing and offshoring from a go/no go perspective. The paper examines the complex “where to outsource” question by applying a quantitative approach called Analytic Hierarchy Process (AHP).

The authors examine a Fortune 500 company's real‐world decision about where to outsource and summarize the current selection process employed by the company. We then apply our AHP model to the company's decision and compare the results.

There are four major findings: the location selection decision is a component of the outsource supplier selection decision; the AHP model effectively manages the complexity of the decision making process, incorporating all decision criteria harmoniously; a method such as AHP, which is able to incorporate both qualitative and quantitative criteria into evaluations, would streamline the decision‐making process; and the AHP process allows firms to look at a portfolio of choices and determine which firms are basically equal in qualifications.

The research implies that: (AHP may be more applicable in these areas by providing a rigorous framework for assessment of qualitative and quantitative factors together; and AHP offers substantial flexibility to accommodate the variety and quantity of decision criteria set forth by the firm.

As firms are more active in pursuing opportunities in global markets, identifying the right offshoring location is critical. The selection process is complex, involving a set of qualitative and quantitative factors and requiring rigorous and careful analysis. Therefore, a scientific method that not only offers flexibility and simplicity, but also simultaneously accommodates a wide variety of decision criteria is invaluable. The research demonstrates that AHP provides these benefits and is an effective technique for analyzing the where‐to‐outsource decision.

The extensive literature review suggests that the majority of the existing works focus on analyzing the go/no‐go decision using a qualitative approach. This paper applies the AHP method to the “where to outsource” question to demonstrate one quantitative approach to this complex decision. Additionally, the paper provides a detailed description of how the AHP method is implemented in analyzing the decision by using a Fortune 500 company's data and information as an example.

This paper presents the employment of the analytic network process (ANP) to select the best site for a shopping mall. ANP is an innovative and robust multicriteria decision‐making (MCDM) method because it can produce a comprehensive analytic framework for solving societal, governmental, and corporate decision problems. Yet, there is a lack of published papers in the construction field demonstrating the method with illustrative examples. In the current paper, it is suggested that ANP is appropriate for shopping mall location selection. An example is therefore demonstrated. In order to explicate the difference between ANP and analytic hierarchy process (AHP), the findings obtained from the two methods are compared. Results of the comparison indicate that ANP is a powerful tool to solve the decision problem if interdependent relationships have substantial impacts in the decision model.