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The purpose of this paper is to provide an insight to the outsourcing decision-making through investigating if the old evaluation/selection criteria and methods still fit with current business priorities or not and, therefore, to identify the appropriate criteria and methods to develop a new selection framework. Since the economic recession of 2008, logistics outsourcing decisions have become more prominent to avoid high fixed costs and heavy investment requirements and to achieve competitive advantages.

This is a focused literature review prepared after analyzing 56 articles related to the logistics service provider (LSP) evaluation and selection methods and criteria during 2008-2013. The academic articles are analyzed based on research focus/area, evaluation and selection methodology/methods and evaluation and selection criteria. Then reviewed result is compared with previous literature studies for the periods (1991-2008) to identify any possible shifts.

The review reveals that: several problems in current LSPs literature have been identified; the reviewed papers can be categorized into seven groups, the usage and importance of evaluation and selection criteria fluctuate during different periods; 12 crucial criteria have been identified, increasing the importance of specific selection methods and the integrated models and fuzzy logic in logistics literature. Then, a comprehensive LSPs’ evaluation and selection framework has been developed.

To the best of our knowledge, this is the first focused logistics outsourcing study that reviews the 2008-2013 period in detail, comparing results with previous literature studies, identifies current LSPs literature problems/gaps, new trends and shifts in the way that LSPs are evaluated and selected, identifies crucial selection criteria and proposes a new holistic LSPs evaluation and selection framework. In addition, it identifies important issues for future research.

Most firms select their information technology outsourcing (ITO) vendors based on the two methods of the weighted-criteria evaluation technique – the “qualification score plus the lowest bid price for the highest price score (QS-LBHPS)” and the “qualification score plus the average bid price for the middle price score (QS-ABMPS).” This paper aims to understand whether these two methods provide the same or different results of vendor selection and how the proportional weights of a vendor's qualification and bid price affect the vendor selection results under the two methods.

–In total, 1,000 experimental tests were carried out using the developed spreadsheet template to examine vendor selection results of the two methods (QS-LBHPS and QS-ABMPS) and compare the vendor selection results under three conditions of vendors’ qualification and price weights. A correspondence analysis was also used to determine the proximal relationships among the selection results of the weighted criteria technique under the comparable methods.

The results indicate that, when using the two methods of the weighted criteria technique for a vendor selection, the selection results are significantly correspondent. In addition, the proportions of qualification and price weights affect the selection results under the two methods. The different proportions of qualification and price weights under the two methods yield the same selection results rather than different results.

This study fills the gap in ITO literatures concerning the vendor selection strategy. No empirical studies have been undertaken to compare the results of vendor selection under the two methods of the weighted-criteria evaluation technique. The findings enable a firm's selection team to apply the weighted-criteria evaluation technique effectively and realize that vendor selection results are altered based on the predefined proportions of qualification and price weights.

Most decision-making problems in construction are complex and difficult to solve, as they involve multiple criteria and multiple decision makers in addition to subjective uncertainties, imprecisions and vagueness surrounding the decision-making process. In many instances, the decision-making process is based on linguistic terms rather than numerical values. Hence, structured fuzzy consensus-reaching processes and fuzzy aggregation methods are instrumental in multi-criteria group decision-making (MCGDM) problems for capturing the point of view of a group of experts. This chapter outlines different fuzzy consensus-reaching processes and fuzzy aggregation methods. It presents the background of the basic theory and formulation of these processes and methods, as well as numerical examples that illustrate their theory and formulation. Application areas of fuzzy consensus reaching and fuzzy aggregation in the construction domain are identified, and an overview of previously developed frameworks for fuzzy consensus reaching and fuzzy aggregation is provided. Finally, areas for future work are presented that highlight emerging trends and the imminent needs of fuzzy consensus reaching and fuzzy aggregation in the construction domain.

The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry.

To address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers.

To exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust.

The proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry.

This study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

Today, customers are generally perceived to be demanding higher quality and better performing products, in shorter and more predictable development cycle-times and at a lower cost. These market pressures drive firms to collaborate with possible partners in product development (PD) processes. However, the selection of a suitable partner for an effective PD is not an easy decision and is associated with complexity. The purpose of this paper is to propose an integrated multi-criteria decision-making (MCDM) approach to effectively evaluate PD partners.

The proposed evaluation procedure consists of several steps. First, based on a literature review and expert validation, the strategic main and sub-criteria of the PD partner selection process that companies consider the most important are identified. After constructing the evaluation criteria hierarchy, the criteria weights are calculated by applying the Analytic Hierarchy Process (AHP) method. The VIKOR (a compromise ranking) method is used to obtain the final partner ranking results. A case study is given to demonstrate the potential of the methodology. In the last part of the study, a sensitivity analysis is performed to determine the influence of criteria weights on the decision making process.

The PD partner evaluation model contains three main criteria, namely, partner, collaboration and PD-oriented criteria, with 13 sub-criteria. The market position, competency of the partner, compatibility, technical expertise and complementarity are found as the most considerable evaluation criteria for the ABC case company. Results of the sensitivity analysis from different cases demonstrate that the integrated AHP-VIKOR model is quite sensitive to the weights assigned to the evaluation criteria. This finding underlines the importance of forming a capable, qualified group of experts for the decision-making procedure. The results of the empirical study show that the proposed evaluation framework is practical for solving partner selection problems.

Partner selection is critical to the success of a collaborative PD process. The main contribution of this paper is the definition and development of an effective evaluation framework to guide managers for suitable PD partner selection. In our knowledge, there exists no study in the literature that combines the established AHP VIKOR model for PD partner selection problem. This study can be useful to researchers to better understand PD partner selection problem theoretically, as well as to organizations in designing better satisfying PD partner evaluation systems.

Companies have to assess the benefit of supplier innovation before realization. The specific situation of supplier innovation differs from conventional innovation evaluation because a supplier innovation refers to a subproduct for which the supplier is responsible. To date, supplier innovation evaluation has not been comprehensively discussed in the literature. Therefore, the purpose of this paper is to focus on how supplier innovation should be evaluated.

For this purpose, a case study based on expert interviews has been conducted to identify how supplier innovation is evaluated in practice. On the basis of the empirical findings the specific situation of supplier innovation is discussed in relation to theoretical basics about the object, objective, time, reference, person, recipient, criteria, and methods of evaluation as well as the evaluation and selection process.

Results are recommendations for the special situation of supplier innovation evaluation before their realization in the purchasing company.

Based on the recommendations, a systematic and comprehensive approach with evaluation criteria and methods should be developed. Future research should address useful evaluation criteria and methods.

Managers can use the recommendations to evaluate supplier innovation in practice and to establish a systematic evaluation and selection process for supplier innovation.

The research findings contribute to the literature about innovation management and supplier management research by providing insights into the special situation of supplier innovation evaluation; in particular, this is the first paper which provides a systematic and comprehensive discussion about supplier innovation evaluation.

Over the last three decades, construction projects have increasingly been delivered through alternative delivery methods. As a result, many owners have a range of delivery methods to choose from and aim to use the right one for each of their projects. Researchers have developed several tools and decision-support processes to facilitate this selection procedure. The purpose of this study is to review and discuss differences and common themes across selection tools developed by academic researchers and project owners.

The study reviews prominent selection processes and tools used for infrastructure projects by conducting an in-depth literature review and using the content analysis method to elicit findings on the methodologies and criteria presented in the literature.

This study presents three principal findings. First, findings show three common themes emerge within the selection criteria—characteristics, goals and risks. Second, while academic studies most commonly suggest employing multi-attribute analysis, this study reveals that, in practice, selection tools most frequently employ a staged or gated evaluation based on the type of criteria and their importance to the decision. Finally, this review further highlights the importance of institutional context in decision-making.

This work contributes to the body of knowledge by providing guidance to practitioners and opening new directions for researchers around the way selection criteria are categorized in the relevant literature and the institutional context considerations when structuring or evaluating a selection process or tool.

Project selection is a critical decision for any organization seeking to commission a large-scale construction project. Project selection is a complex multi-criteria decision-making problem with significant uncertainty and high risks. Fuzzy set theory has been used to address various aspects of project uncertainty, but with key practical limitations. This study aims to develop and apply a novel Pythagorean fuzzy sets (PFSs) approach that overcomes these key limitations.

The study is particular to complex project selection in the context of increasing interest in resilience as a key project selection criterion. Project resilience is proposed and considered in the specific situation of a large-scale construction project selection case study. The case study develops and applies a PFS approach to manage project uncertainty. The case study is presented to demonstrate how PFS is applied to a practical problem of realistic complexity. Working through the case study highlights some of the key benefits of the PFS approach for practicing project managers and decision-makers in general.

The PFSs approach proposed in this study is shown to be scalable, efficient, generalizable and practical. The results confirm that the inclusion of last aggregation and last defuzzification avoids the potentially critical information loss and relative lack of transparency. Most especially, the developed PFS is able to accommodate and manage domain expert expressions of uncertainty that are realistic and practical.

The main novelty of this study is to address project resilience in the form of multi-criteria evaluation and decision-making under PFS uncertainty. The approach is defined mathematically and presented as a six-step approach to decision-making. The PFS approach is given to allow multiple domain experts to focus more clearly on accurate expressions of their agreement and disagreement. PFS is shown to be an important new direction in practical multi-criteria decision-making methods for the project management practitioner.

In this study, an integrated decision-making model consisting of decision-making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and a modified version of evaluation based on distance from average solution (EDAS) methods is proposed for supplier selection problem in a public procurement system considering sustainable development goals.

DEMATEL and BWM methods are used to determine weights of the criteria that are defined for the supplier selection problem. Weight aggregation method is applied to combine the weights obtained from these two methods. A modified version of EDAS method is then used in order to rank the alternative suppliers.

The proposed decision-making model is investigated for a supplier selection problem for a hospital in Spain. The validity of the results is checked using comparison with other decision-making methods and several performance analysis tests.

The proposed multi-criteria decision-making (MCDM) model contributes to the healthcare supply chain management (SCM) and aims to lead the policy makers in selecting the best supplier.

There is no such study that combines DEMATEL and BWM together for weight generation. The application of the modified EDAS method is also new. In real time situations, the decision experts may confront to the difficulty of using BWM while identifying the best and the worst criteria choices. The idea of using DEMATEL is to aid the experts to make them enable in distinguishing between the best/worst criteria and handle BWM easily.