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The purpose of this research is so that project managers can use a systemic approach to prioritizing the risks of outsourcing including an understanding of the external factors that could affect the prioritization.

A survey was designed by the authors and distributed to 2,500 outsourcing professionals from different organizations and the hypotheses were tested using the data from these surveys. The logic for forming the hypothesis is discussed for each hypothesis and so are the demographics of the respondents

External factors such as the type of technology involved, type of market targeted, location of outsourcing and the amount of experience the outsourcing professional had, did affect the prioritization of the outsourcing risks. Furthermore, trends were identified among the ranking of the outsourcing risks.

One of the constraining factors of this research, as in the majority of empirical research initiatives, was the limited sample size, which could potentially affect the rating. An increased sample size could have also provided the researchers with a more detailed insight into the interrelationships between the various outsourcing risks.

For the first time, the outsourcing risks have been prioritized using a systemic approach. The systemic approach has been used in the financial industry while analyzing risk but the authors have applied it to prioritization of outsourcing risks. This includes understanding the interrelationships between the risks and also the effect that external factors can have on the prioritization of those risks.

The purpose of this paper is to extend the body of knowledge on healthcare facilities management (FM) by investigating the risks associated with outsourcing of FM services in hospitals.

The paper relied on two strands of methodology common with pragmatic research. Questionnaire survey (QS) used data from 208 respondents representing ten hospitals while three out of the ten hospitals involved in the QS were selected based on their willingness to enter the case study (CS) interview. Data collected were analysed using descriptive and inferential statistics for QS and using narrative techniques by discussing themes, sub-themes for the CS.

Findings established 24 out of the 35 risk factors as critical, four factors as somehow critical, and five factors as not critical. Besides, nine risk factors were found to be significantly loaded on the five risk categories. The rank analysis also revealed that the top five critical risk factors are: inexperience and lack of requisite skills; possibility of fraud by vendor; financial failure of chosen vendor; vendor opportunism; and fall in morale of employees.

The study provides an unambiguous contribution to exiting body of knowledge on outsourcing risks as it relates to healthcare FM. It reinforces the theory that risks exist in any form of relationship but developed a distinct body of factors associated with outsourcing of FM services particularly from the context of Nigeria’s public healthcare sector.

This paper seeks to provide a tool for decision makers to make more informed decisions regarding their outsourcing decisions and selection of the appropriate supplier.

The method uses the Taguchi loss function for the inclusion of intangibles in the evaluation and selection of suppliers. Intangibles are defined as factors that have an impact on the selection of an appropriate supplier but are not easily quantified to be included in the financial evaluation. These intangibles are classified as the benefits and risks of using a supplier to perform the outsourcing function. A decision maker has certain expectations regarding these intangibles and a loss occurs when a supplier's performance does not meet the decision maker's expectations. The Taguchi loss function has been selected as a means of measuring the loss. The decision maker defines the target value and the specification limits for each benefit and risk category. The weighted loss scores are calculated where the weights are the importance ratings assigned to benefit/risk categories by the decision maker. Based on this analysis each supplier will receive a weighted loss score for all the pertinent benefit categories and one weighted loss score for all the risk categories. To achieve a single measure, the aforementioned weighted loss scores are combined to determine a single aggregate loss score for each supplier, which is then used to rank them. The supplier who receives the highest ranking (minimum loss score) will be selected to perform the outsourcing function.

The procedure proposed here can help companies to identify the best supplier to perform an outsourcing function.

The paper presents a phased decision model that begins with economic evaluation and then uses Taguchi functions to measure the impact of intangibles.

The purpose of this study is to analyse the risk factors associated with outsourcing of facilities management (FM) services.

The study administered questionnaires on 146 registered members of International Facilities Management Association (IFMA), Nigeria chapter, who carry out their professional practice in Lagos, Nigeria. The survey, conducted in February, 2011 targeted facilities managers, property managers, maintenance officers and procurement officers cutting across the three levels of management. A total of 61 of them returned valid questionnaires, giving a response rate of 41.8 percent.

Findings reveal that “poor quality of services” was rated the most critical risk factor associated with facilities management outsourcing, while “security” and “inexperience” closely followed in that order. Also, there was no significant difference in the rankings of the stakeholders on more than 75 percent of the factors.

Most practitioners would have been left out of the survey due to non‐registration with IFMA due to the seeming novelty of facilities management practice in Nigeria.

This paper provides an unambiguous empirical‐based analysis of outsourcing risks from the perspective of facilities management practice in Nigeria.

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.

The objectives of this paper are to identify the critical factors that influence the decision to outsource maintenance services in public Saudi Arabian universities, and to investigate the relative importance of each of the identified factors based on the expressed opinions of the in‐house maintenance managers in the concerned maintenance departments in these universities.

The authors conducted a comprehensive review of the literature in the fields of maintenance management and outsourcing practices to achieve a thorough understanding of the issues involved, and identifying the crucial factors affecting the outsourcing decision of maintenance services. A questionnaire survey was developed to assess each factor influencing the decision to outsource maintenance services in the public Saudi Arabian universities. The survey included 38 factors grouped in six major groups. The respondents who have opted to outsource several of their maintenance services to specialty contractors were asked to indicate their perceived level of importance for each of the identified factors. The level of importance of the factors and the groups were measured. The factor groups were ranked according to the obtained mean rating values.

The findings show that Saudi universities generally value the importance of the quality, management and strategic factors when making outsourcing decisions. The most important three factors influencing the decision to outsource maintenance services in the public Saudi Arabia universities were identified as “increase the speed of implementation”, “improve quality requirements” and “risk sharing with contractors”.

The findings of the study provide practical value for facilities maintenance managers in institutions of higher education confronted with the decision of whether to outsource maintenance services in their campuses.

The paper is original in the sense that it identifies how in‐house maintenance managers rate the importance of the factors influencing outsourcing decisions.

The purpose of this paper is to develop a decision model to help decision makers with selection of the appropriate supplier.

Supplier selection is a multi‐criteria decision‐making process encompassing various tangible and intangible factors. Both risks and benefits of using a vendor in supply chain are identified for inclusion in the evaluation process. Since these factors can be objective and subjective, a hybrid approach that applies to both quantitative and qualitative factors is used in the development of the model. Taguchi loss functions are used to measure performance of each supplier candidate with respect to the risks and benefits. Analytical hierarchy process (AHP) is used to determine the relative importance of these factors to the decision maker. The weighted loss scores are then calculated for each supplier by using the relative importance as the weights. The composite weighted loss scores are used for ranking of the suppliers. The supplier with the smallest loss score is recommended for selection.

Inclusion of both risk and benefit categories in the evaluation process provides a comprehensive decision tool.

The proposed model provides guidelines for supply chain managers to make an informed decision regarding supplier selection.

Combining Taguchi loss function and AHP provides a novel approach for ranking of potential suppliers for outsourcing purposes.

The decision-making to outsource and select the most suitable global manufacturing outsourcing partner (MOP) is complex and uncertain due to multiple conflicting qualitative and quantitative criteria as well as multiple alternatives. Vagueness and variability exist in ratings of criteria and alternatives by group of decision-makers (DMs). The paper provides a novel Stochastic Fuzzy (SF) method for evaluation and selection of agile and sustainable global MOP in uncertain and volatile business environment.

Four main selection criteria for global MOP selection were identified such as economic, agile, environmental and social criteria. Total 16 sub-criteria were selected. To consider the vagueness and variability in ratings by group of DMs, SF method using t-distribution or z-distribution was adopted. The criteria weights were determined using the Stochastic Fuzzy-CRiteria Importance Through Intercriteria Correlation (SF-CRITIC), while MOP selection was carried out using Stochastic Fuzzy-VIseKriterijumskaOptimizacija I KompromisnoResenje (SF-VIKOR) in the case study of footwear industry. Sensitivity analysis was performed to test the robustness of the proposed model. A comparative analysis of SF-VIKOR and VIKOR was made.

The worker’s wages and welfare, product price, product quality, green manufacturing process and collaboration with partners are the most important criteria for MOP selection. The MOP3 was found to be the best agile and sustainable global MOP for the footwear company. In sensitivity analysis, significance level is found to have important role in MOP ranking. Hence, the study concluded that integrated SF-CRITIC and SF-VIKOR is an improved method for MOP selection problem.

In a group decision-making, ambiguity, impreciseness and variability are found in relative ratings. Fuzzy variant Multi-Criteria Decision-Making methods cover impreciseness in ratings but not the variability. On the other hand, deterministic models do not cover either. Hence, the stochastic method based on the probability theory combining fuzzy theory is proposed to deal with decision-making problems in imprecise and uncertain environments. Most notably, the proposed model has novelty as it captures and reveals both the stochastic perspective and the fuzziness perspective in rating by group of DMs.

The proposed multi-criteria group decision-making model contributes to the sustainable and agile footwear supply chain management and will help the policymakers in selecting the best global MOP.

To the best of the authors’ knowledge, SF method has not been used to select MOP in the existing literature. For the first time, integrated SF-CRITIC and SF-VIKOR method were applied to select the best agile and sustainable MOP under uncertainty. Unlike other studies, this study considered agile criteria along with triple bottom line sustainable criteria for MOP selection. The novel method of SF assessment contributes to the literature and put forward the managerial implication for improving agility and sustainability of global manufacturing outsourcing in footwear industry.

The purpose of this paper is to determine best practices of aid agencies for outsourcing logistics to commercial logistics service providers (LSPs) in disaster relief. Moreover, it evaluates the application of the Delphi method for research in humanitarian logistics.

The paper is based on a two-round Delphi study with 31 experts from aid agencies and a complementary full-day focus group with 12 experts from aid agencies and LSPs.

The study revealed 12 best practices for outsourcing logistics in disaster relief and a compilation of more than 100 activities for putting these practices into action. Experts consider a proper balance between efficiency and compliance, a detailed contract and a detailed service request most important. Additionally, the Delphi method was found to be a promising technique for research on humanitarian logistics.

By critically examining the Delphi method, this study establishes the basis for a wider application of the technique in the field of humanitarian logistics. Furthermore, it can help to prioritize future research as the ranking of practices reflects the priorities of practitioners.

The paper provides guidance to practitioners at aid agencies in charge of outsourcing logistics.

This research is one of the first in the field of humanitarian logistics to apply the Delphi method. Moreover, it addresses the lack of literature dealing with approaches for building successful cross-sectoral partnerships.

The purpose of this paper is to determine the criteria weights of outsourcing and their key role in ranking outsourcing suppliers.

A new hybrid multi-criteria decision-making approach merges three tools, namely, decision making trial and evaluation (DEMATLE), fuzzy analytic network process (FANP) and ordinal/cardinal data envelopment analysis (DEA) model. Afterwards, experts’ opinions were gathered from a Pipe and Fittings company. Finally, their opinions were incorporated in three-stage approach for outsourcing suppliers’ selection.

The findings of this study show that among the selective criteria for outsourcing, business development, focus on basic activities and order delays are the three most important criteria. Also, the proposed approach ranks suppliers to facilitate decision making for selection.

The number of suppliers, selection criteria and the number of members of the respondents’ team have been identified as some of the limitations of the present study.

The study has significant and practical implications for the managers and for the organizations which have to choose top suppliers, particularly in the case of dealing with numerous and qualitative/quantitative criteria.

This paper proposed a new three-stage approach that incorporates outputs of previous as inputs of next stage to increasing results accuracy. Also, it showed that by incorporating results of FANP method into DEA model, key role of experts’ opinions as a qualitative and quantitative criteria can be caused by increasing flexibility of decision process.