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As the Chinese economy has grown rapidly and as its container throughputs has demonstrated a stark increase in recent decades, companies worldwide have developed stronger financial connections with supply chain entities in China, a huge “Production Factory” in the world. This global economic trend arouses significant attention to distinct preference of individual entities in supply chain. The primary goal of the study is to establish statistical understanding on factors of logistics service preferences of each supply chain of each supply chain entity in China, especially Shandong Province. Ultimately, the study aims i) to establish the solid framework for proper evaluation of logistics services in supply chains, ii) to enhance the preferences of logistics services as a differentiating feature on behalf of entities. The study utilizes a holistic approach in analyzing logistics service attributes which affect overall logistics entities in an effort to overcome the limitations of previous studies which failed to provide integrating viewpoint of supply chain entities. In this study, AHP (Analytic Hierarchy Process) method is used as an analysis tool which allows an in-depth examination of the differences between factors and evaluations of customers regarding the logistics service attributes. The results clearly show distinctive service preferences for each four supply chain entities in Shandong Province of China such as 3PLs (forwarder, carrier, and warehouse), Customs (airport, seaport, and bonded area), Market channels (wholesaler, retailer, and e-retailer), and Manufacturers regarding the logistics service attributes.

Unforeseen events can disrupt the operational process and negatively impact emergency resources optimization and its supply chain. A limited number of studies have addressed risk management issues in the context of emergency supply chains, and this existing research lacks inbuilt and practical techniques that can significantly affect the reliability of risk management outcomes. Therefore, this paper aims to identify and practically analyze the specific risk factors that can most likely disrupt the normal functioning of the emergency supply chain in disaster relief operations.

This paper has used a three-step process to investigate and evaluate risk factors associated with the emergency supply chain. First, the study conducts a comprehensive literature review to identify the risk factors. Second, the research develops a questionnaire survey to validate and classify the identified risk factors. At the end of this step, the study develops a hierarchical structure. Finally, the research investigates the weighted priority of the validated risk factors using the fuzzy-analytical hierarchy process (FAHP) methodology. Experts were required to provide subjective judgments.

This paper identified and validated 28 specific risk factors prevalent in emergency supply chains. Based on their contextual meanings, the research classified these risk factors into two main categories: internal and external risk factors; four subcategories: demand, supply, infrastructural and environmental risk factors; and 11 risk types: forecast, inventory, procurement, supplier, quality, transportation, warehousing, systems, disruption, social and political risk factors. The most significant risk factors include war and terrorism, the absence of legislative rules that can influence and support disaster relief operations, the impact of cascading disasters, limited quality of relief supplies and sanctions and constraints that can hinder stakeholder collaboration. Therefore, emergency supply chain managers should adopt appropriate strategies to mitigate these risk factors.

This study will contribute to the general knowledge of risk management in emergency supply chains. The identified risk factors and structural hierarchy taxonomic diagram will provide a comprehensive risk database for emergency supply chains.

The research findings will provide comprehensive and systemic support for respective practitioners and policymakers to obtain a firm understanding of the different risk categories and specific risk factors that can impede the effective functioning of the emergency supply chain during immediate disaster relief operations. Therefore, this will inform the need for the improvement of practices in critical aspects of the emergency supply chain through the selection of logistics and supply chain strategies that can ensure the robustness and resilience of the system.

This research uses empirical data to identify, categorize and validate risk factors in emergency supply chains. This study contributes to the theory of supply chain risk management. The study also adopts the fuzzy-AHP technique to evaluate and prioritize these risk factors to inform practitioners and policymakers of the most significant risk factors. Furthermore, this study serves as the first phase of managing risk in emergency supply chains since it motivates future studies to empirically identify, evaluate and select effective strategies that can eliminate or minimize the effects of these risk factors.

This study aims to develop a decision support tool to improve planning for the rehabilitation of water distribution networks (WDN) using the analytical hierarchy process (AHP) method and the urgency level score.

In this paper the AHP method was used to outclass the indicators having a strong influence on the deterioration of the pipes and the score of the level of urgency is calculated to establish the rehabilitation program (short, medium and long term). The proposed model was tested for the case of the city of Souk-Ahras in Algeria.

Based on the judgments of twenty-four experts, the relative weights of the three physical, operational and environmental criteria of the pipeline were calculated and found to be equal to 35.40%, 55.60% and 9.00%, respectively. The two indicators, number of failures and pressure, were found to have the highest overall weights. The results of this article can be used to improve decision-making in WDN rehabilitation planning in Algeria.

The main objective of water companies is to provide citizens with good quality drinking water in sufficient quantity. However, over time, WDN age, degrade and deteriorate. This degradation leads to a drop in the performance through the degradation of water quality and an increase in loss rates. WDN rehabilitation is one of the most widely adopted solutions to address these drawbacks.

Application of a hybrid method (AHP- Level of Emergency) for the planning of the rehabilitation of WDN in Algeria.

This study aims to set out to identify and evaluate potential obstacles to successfully implementing lean construction (LC) as a result.

Several indicators were recognized as major obstacles following an exhaustive assessment of the literature and a multicriteria decision analysis based on the analytic hierarchy process (AHP) of information obtained from a questionnaire survey that was directed to practitioners in the Indian construction industry.

The results of this AHP model suggest that “Managerial” and “Inadequate resources” categories with a priority weight of “0.361” and “0.309” have the highest levels of influence, respectively, while “Inadequate knowledge” and “just in time (JIT)” categories with a priority weight of “0.053” and “0.034” have the lowest levels of influence, respectively.

Construction companies can use the study’s findings as a guide to determine whether they are ready to embrace LC, learn more about the components needed for implementation or investigate any challenges that may arise. These businesses can then create plans to promote the adoption and application of the lean philosophy.

The Indian construction industry may see great success with LC management initiatives. LC concepts have been adopted by many nations, but during the past 20 years, there has only appeared to be a limited amount of lean implementation in the Indian construction industry. It seems that several structural and cultural barriers are preventing its effective implementation. Organizations will not be able to determine what improvement efforts are required, where these efforts should be directed or which initiatives could provide the best outcomes if they are unaware of the elements that influence the effective implementation of LC.

China is currently developing and promoting an industrial cluster policy at the government level. By enacting the ‘Opinion on promoting industrial cluster development’, China is supporting the development of industrial clusters. Building an industrial cluster is done by using a single factor but requires many additional factors like regional characteristics, competitiveness factors are also diversified. To evaluate the competitiveness of the Chinese automobile industry cluster, a competitiveness element index should be developed and a competitiveness evaluation method is needed to evaluate the importance of each element. To accomplish this objective, this research applied the analytic hierarchy process (AHP) and focused on the importance of the competitiveness elements.

This research investigated the character is tics regarding cases of clusters and also analyzed the competitiveness of the Changchun automobile cluster located in northeastern China. The purpose of this research is to help Korean enterprises who enter China in the hopes that Korea will emerge as a top automobile production country.

This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

The existing literature expresses a strong need to develop tools that support the manufacturing reshoring decision-making process. This paper aims to examine the suitability of analytical hierarchy process (AHP)-based tools for initial screening of manufacturing reshoring decisions.

Two AHP-based tools for the initial screening of manufacturing reshoring decisions are developed. The first tool is based on traditional AHP, while the second is based on fuzzy-AHP. Six high-level and holistic reshoring criteria based on competitive priorities were identified through a literature review. Next, a panel of experts from a Swedish manufacturing company was involved in the overall comparison of the criteria. Based on this comparison, priority weights of the criteria were obtained through a pairwise analysis. Subsequently, the priority weights were used in a weighted-sum manner to evaluate 20 reshoring scenarios. Afterwards, the outputs from the traditional AHP and fuzzy-AHP tools were compared to the opinions of the experts. Finally, a sensitivity analysis was performed to evaluate the stability of the developed decision support tools.

The research demonstrates that AHP-based support tools are suitable for the initial screening of manufacturing reshoring decisions. With regard to the presented set of criteria and reshoring scenarios, both traditional AHP and fuzzy-AHP are shown to be consistent with the experts' decisions. Moreover, fuzzy-AHP is shown to be marginally more reliable than traditional AHP. According to the sensitivity analysis, the order of importance of the six criteria is stable for high values of weights of cost and quality criteria.

The limitation of the developed AHP-based tools is that they currently only include a limited number of high-level decision criteria. Therefore, future research should focus on adding low-level criteria to the tools using a multi-level architecture. The current research contributes to the body of literature on the manufacturing reshoring decision-making process by addressing decision-making issues in general and by demonstrating the suitability of two decision support tools applied to the manufacturing reshoring field in particular.

This research provides practitioners with two decision support tools for the initial screening of manufacturing reshoring decisions, which will help managers optimize their time and resources on the most promising reshoring alternatives. Given the complex nature of reshoring decisions, the results from the fuzzy-AHP are shown to be slightly closer to those of the experts than traditional AHP for initial screening of manufacturing relocation decisions.

This paper describes two decision support tools that can be applied for the initial screening of manufacturing reshoring decisions while considering six high-level and holistic criteria. Both support tools are applied to evaluate 20 identical manufacturing reshoring scenarios, allowing a comparison of their output. The sensitivity analysis demonstrates the relative importance of the reshoring criteria.

The aim of the research is to identify and prioritise the implementation challenges of blockchain technology and suggests ways for its implementation in supply chains.

Underlined by the technology, organisational, and external environment model, a conceptual framework with four challenge categories and sixteen challenges is proposed. Data collected from three stakeholder groups with experience in the implementation of blockchain technology in India is analysed by employing an analytical hierarchy process method-based case study. Further, a criticality–effort matrix analysis is performed to group challenges and suggest ways for implementation.

The analysis revels that all stakeholders perceive complexity challenge associated with the technology, organisational structure, and external environment, and issues of compatibility with existing systems, software, and business practices to be high on the criticality and effort scales, which thus require meticulous planning to manage. Likewise, top-management support issues related to insufficient understanding of how technology fits with the organisation’s policy and benefits offered by the technology requires high effort to address this challenge.

The results were obtained by focusing on the Indian context and therefore may not apply to other nations’ contexts.

By investigating the challenges that the developers, consultants, and client organisations need to address, this study assists managers in developing plans to facilitate coordination among these organisations for successful blockchain implementation.

To the authors’ knowledge this study is the first to identify and prioritise the challenges from the perspectives of multiple stakeholder groups with experience in blockchain technology implementation.

Considering the human factor, the quality of the personnel is vital to ensure especially the value creation in the ports. Therefore, employee quality stands out for withstanding the pressures that stem from global trade on its operational speed felt by ports in recent years. Accordingly, the selection of the qualified personnel at the ports is very critical and a tool based on dynamic capabilities is needed to manage this process well. The aim of this study is to develop a model based on dynamic capabilities for recruitment process of ports.

Port personnel should have dynamic capabilities detected from the literature. These capabilities were approached as criteria. In this study, Buckley's proposed fuzzy analytical hierarchy process (AHP) method was employed for weighting the whole criteria. After that, weights of the criteria were used to prioritize alternatives with the fuzzy TOPSIS method.

This model reflects port managers' priorities and port customers' evaluations. Thus, the model can also reflect the level of integration of ports' related department managers into the recruitment process. The analyses allow the evaluation of the attitudes of the human resources department in the related port while fulfilling the personnel recruitment function. As a result of analyses, differences between perceptions of port managers and customers served as a feedback to the human resource management department of the ports.

One of the originalities of this study was derived from its customer-oriented perspective. This is a unique study that gathers common personnel capabilities related to the operation, planning and customer relationship departments and evaluates the success of these capabilities from the customer perspective.