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Selecting an appropriate partner is a vital and strategic decision-making process in any supply chain collaboration initiative. The purpose of this paper is to introduce and explore the key factors considered by manufacturers in the selection of an appropriate retailer(s) for collaboration and collaborative planning, forecasting and replenishment (CPFR) implementation and the relationships between these factors.

A comprehensive literature review and experts’ views are applied to identify the main retailer selection and evaluation factors for CPFR implementation. A fuzzy decision-making trial and evaluation laboratory approach is then used to rank and analysis the interaction among identified factors. The findings are finally evaluated using a case study from a high-tech industry.

The most important partner selection factors comprising of five dimensions and 24 factors are introduced. Of the identified criteria, three factors: manufacturer’s familiarity with the retailer, workforce skills and training and customer service orientation and capability have been identified as critical when selecting retailers for CPFR implementation. The technological capabilities dimensions are identified as the only net cause dimension which affects all other dimensions and its importance and role in simplifying and enhancing the speed and flexibility of CPFR implementation.

The paper identifies practical retailer selection factors for CPFR implementation and the causal relationships between factors. Developed retailer selection dimensions and criteria will assist manufacturers and retailers in understanding the role these factors play in CPFR implementation. This will also assist in appropriate retailer(s) selection by manufacturers.

This paper contributes to the literature on CPFR and tackles the important issue of selecting appropriate partners by developing retailer selection dimensions and criteria in CPFR implementation.

The purpose of this paper is to efficiently assist the decision makers in evaluating and selecting the most appropriate third-party logistics (3PL) provider from environmental sustainability perspective using a two-phase model based on data envelopment analysis (DEA) and analytic network process (ANP).

The study uses an integrated approach of DEA and ANP as an evaluation and selection methodology to select an efficient and requisite 3PL. The integrated model is a sound technique for 3PL evaluation and selection. DEA effectively screens the maximally efficient 3PLs, whereas ANP easily performs the cumbersome process of weighting diverse criteria and ranks various alternatives according to their performance on the basis of these criteria. This study lists the prominent evaluation and selection criteria taking into consideration the environmental sustainability. Finally, a real-life industrial application is presented to demonstrate the proposed method.

The current research work is devoted to the emerging research topic of environmental sustainability in logistics industry and supply chain management. The results of study indicate that eco-efficient transportation and 3PLs lead better transportation planning, better inventory and warehouse management, lower inventory cost and sustainable supply chain operations. Also, the applied approach enables the decision makers to better understand the complex relationships of the relevant criteria in the decision-making process.

This study does not investigate the relationships between environmental performances and differentiation advantage from the perspective of 3PLs. Also, sensitivity analysis is not performed.

The developed integrated model enables decision analysts to better understand the complete evaluation process of 3PL evaluation and selection considering environmental sustainability perspective. Furthermore, the developed approach provides a more flexible, simple, accurate, effective, and systematic decision support tool for 3PL evaluation and selection.

The current study is first of its kind to use the integrated approach in evaluation and selection of 3PLs from environmental sustainability perspective considering the inter-dependencies among the evaluation and selection criteria.

Third-party logistics (3PL) plays a main role in supply chain management and, as a result, has experienced remarkable growth. The demand for 3PL providers has become a main approach for companies to offer better customer service, reduce costs, and gain competitive advantage. This paper identifies important criteria for 3PL provider selection and evaluation, and the purpose of this paper is to select 3PL providers from the viewpoint of firms which were already outsourcing their logistics services.

This study utilized the grey decision-making trial and evaluation laboratory (DEMATEL) method to develop 3PL provider selection criteria. Because human judgments are vague and complicated to depict by accurate numerical values, the grey system theory is used to handle this problem.

The findings revealed the structure and interrelationships between criteria and identified the main criteria for 3PL provider selection. The most important criteria for 3PL provider selection are on time delivery performance, technological capability, financial stability, human resource policies, service quality, and customer service, respectively.

The paper’s results help managers of automotive industries, particularly in developing countries, to outsource logistics activities to 3PL providers effectively and to create a significant competitive advantage.

The main contributions of this paper are twofold. First, this paper proposes an integrated grey DEMATEL method to consider interdependent relationships among the 3PL provider selection criteria. Second, this study is one of the first studies to consider 3PL provider selection in a developing country like Iran.

Numerous research articles and industry reports are currently available that deal with global sourcing, however, few articles and reports can be specifically found on sourcing packaging materials in the consumer packaged food (CPF) industry. The purpose of this paper is to understand and develop the supplier selection process and overall cost modeling that facilitates the selection of a high‐quality global supplier for low‐cost packaging materials used in large quantities for CPF products.

To gain information relating to packaging material sourcing, a comprehensive literature search was conducted. Additionally, interviews with packaging material sourcing managers and directors were performed at a major global CPF products manufacturer. Knowledge gained from literature, industry interviews and available business data was used to develop a generic strategic outsourcing model and a closed loop business framework for selection of global suppliers of packaging material. This framework utilizes the proposed total cost of ownership model for global sourcing and weighted qualitative criteria matrix demonstrating how it is used in global supplier selection.

The results of this study show a standardized supplier selection process and the total cost of ownership model for a CPF manufacturer which incorporates the different logistic costs such as tariffs, duties, inventory carrying levels and cost of quality. These two models are then merged into a selection matrix to determine with which supplier to enter into a long‐term supply relationship.

The paper combines both the relevant closed loop supplier selection modeling framework and the total cost of ownership model in the selection of supplier for low‐cost high‐volume CPF materials. It adds rigor regarding cost of ownership and emphasizes the need for a strategic rationale when entering into long‐term global supply relationships between CPF products manufacturers and packaging material suppliers.

The purpose of this paper is to investigate how manufacturing strategies could affect the supplier selection criteria used by business firms.

Survey strategy was used to empirically understand the research argument. First, principal component factor analysis was employed to validate the underlying structure of the supplier selection criteria. Then, simple regression analysis was employed to test the research hypotheses.

Organizations pursuing lean strategies will emphasize factors that improve their efficiency when selecting their suppliers, while organizations pursuing agile strategies will assert factors that improve their ability to respond to customer unique requirements when selecting their suppliers.

This study provides new insight for researchers to understand the effect of manufacturing strategies on the classification of supplier selection criteria. However, the small sample size might limit the ability to generalize research findings. Further research is required to confirm the findings using a wider sample.

This research provides practitioners with useful insights into how to select their suppliers based on their manufacturing strategies.

This paper classifies supplier selection criteria into three distinct groups: lean, agile, and common capabilities. Lean capability refers to the list of criteria that are highly relevant in selecting suppliers for lean implementers. Agile capability refers to the list of criteria that are highly relevant in selecting suppliers for agile implementers. Finally, common capability refers to the list of criteria that have comparable relevance in selecting suppliers for both lean and agile implementers.

The purpose of this paper is to report a study in which analytical network process (ANP) was used for selecting the best concept from sustainability view point.

The concept selection in the sustainability viewpoint is a typical multi-criteria decision-making (MCDM) problem involving complex interrelationship among the decision criteria. The formulated MCDM problem of sustainable concept selection was solved using ANP. The sensitivity analysis was also being conducted to validate the results.

The interrelationship among the decision criteria was analyzed using ANP, and the best alternative was selected based on the computation of Product Sustainability Weighted Index (PSWI). The selected best alternative was subjected to implementation in the case organization.

The study deals with the formulation of sustainable concept selection as a typical MCDM problem and providing solutions using ANP. The best alternative “weight reduction” was subjected to implementation. The developed MCDM problem also could be solved using hybrid MCDM methods.

The study focuses on selecting the best sustainability concept for an Indian automotive component manufacturing organization. Hence, the inferences being derived from the study are practically feasible and contribute toward the improvement of product sustainability.

The formulation of a hierarchical model for sustainable concept selection as MCDM problem and generating solution using ANP is the contribution of the authors.

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.

Stakeholders affiliated with healthcare services should understand patient attitudes and criteria that are involved in selecting a personal physician. The purpose of this paper is to identify the factors that are significant to patients in selecting or deselecting physicians as providers of healthcare services.

The research structure was set to theorize the physician selection criteria (PSC) model into two phases. The first phase developed a conceptual model as revealed from healthcare consumer perceptions. The second phase was designed to test and validate the model through cause–effect statistical analysis underpinned by theoretical explanations through an empirical study.

Through an empirical study of benchmarking perceptions of people from 15 different countries, qualitative PSC were gathered and used to formulate an initial PSC model. Based on the proposed model, a validity test was conducted, and finally, the PSC model was developed, resulting in several interesting and self-explanatory outcomes.

The model was tested in only one (relatively cosmopolitan) city. For proper generalization, it should be tested in countries with differing healthcare service systems.

The results of this study are interesting, important and have potential values to academics and medical professionals. The study provides strong evidence that a physician’s external approach to patients is the most significant issue for patients seeking medical services. This does not refer to basic medical services, but rather the treatment process, where the physician’s behavior and positive attitude has the strongest effect on the patient’s decision to choose one physician over others.

Final PSC model has identified some significant theoretical explanations for academics and professional justifications for practitioners.

This chapter examines the limit properties of information criteria (such as AIC, BIC, and HQIC) for distinguishing between the unit-root (UR) model and the various kinds of explosive models. The explosive models include the local-to-unit-root model from the explosive side the mildly explosive (ME) model, and the regular explosive model. Initial conditions with different orders of magnitude are considered. Both the OLS estimator and the indirect inference estimator are studied. It is found that BIC and HQIC, but not AIC, consistently select the UR model when data come from the UR model. When data come from the local-to-unit-root model from the explosive side, both BIC and HQIC select the wrong model with probability approaching 1 while AIC has a positive probability of selecting the right model in the limit. When data come from the regular explosive model or from the ME model in the form of 1 + n^α/n with α ∈ (0, 1), all three information criteria consistently select the true model. Indirect inference estimation can increase or decrease the probability for information criteria to select the right model asymptotically relative to OLS, depending on the information criteria and the true model. Simulation results confirm our asymptotic results in finite sample.