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For construction organisations to be effective at implementing an integrated safety, health and environmental (SHE) management system, they require the right level of organisational capability. This capability includes the policies, systems and resources of the organisation. However, within the academic literature, it is unclear which organisational attributes of construction companies are important for implementing integrated SHE management. This study aims to explore the organisational attributes that determine integrated SHE management capability and their relative priorities.

The study used a literature review supported by expert verification and a subsequent three-round expert Delphi technique accompanied by applying the voting analytical hierarchy process.

The study identified 20 attributes grouped under five main thematic categories. These are strategy (the organisation’s vision and top management commitment); process (the organisation’s procedures and processes for SHE management); people (organisation’s human resources, their competence, roles, responsibilities and involvement in SHE management); resources (organisation’s physical and financial resources for SHE management) and information (SHE related documents, data, records and their communication across an organisation). While these thematic categories and the attributes within carry different weights of importance, the strategy-related attributes are the most important, followed by the people-related attributes.

The results of this study should enable construction companies and key industry stakeholders to understand construction companies’ capability to successfully implement an integrated SHE management system. Furthermore, construction companies should be able to prioritise efforts or investments to enhance their SHE management capability.

The field of supply chain management (SCM) needs to attract and retain workers to solve the current talent shortage. The purpose of this research is to identify and evaluate factors that influence career advancement in SCM and compare male and female supply chain experts' perceptions of the importance of those factors.

First, 32 factors perceived as affecting career advancement in SCM were identified by conducting a literature review and consulting 36 experts. Those factors were grouped into four categories: “environmental and structural”, “human capital”, “individual” and “interpersonal”. Those factors were validated via the Delphi method, and ten factors were retained for further study. Second, the voting analytical hierarchy process was used to determine the priority weights experts assigned to these factors. The weights assigned by male and female experts were compared to determine if there were differences between the women's and men's perceptions of the factors' importance.

The findings reveal that the category of human capital factors is the most important, followed by individual factors and the least important is interpersonal factors. The experts consulted for this research emphasized “skills”, “a good fit between an individual and an organization” and “self-confidence” as important factors for career advancement. There were two unexpected results. First, the experts rejected all the environmental and structural factors. Second, no significant difference was found between the male and female groups' evaluations.

Prior to this study, no integrated approach to identify and evaluate the factors perceived which affect career advancement in SCM had been developed. This research is a single empirical and integrative study in France that provides valuable insights for academics and practitioners.

The purpose of this paper is to present a detailed literature review of the recent applications of the analytic hierarchy process (AHP) and analytic network process (ANP) group decision‐making methodologies.

Among more than 600 related papers published in the period 2005‐2009, a total of 232 application articles published in highly reputed international academic journals were selected and referenced in this paper. Papers were categorized according to application areas, subject titles, publication date, country of origin, academic journals, and integrated methodologies, and are summarized herein by various tables and charts.

The findings show that during the years 2005‐2009, use of the AHP technique has continued to increase exponentially. Moreover, it is expected that ANP will gain more popularity in the future, as the benefits of ANP become better understood. Applications of AHP have been dominant in manufacturing, followed by the environmental management and agriculture field, power and energy industry, transportation industry, construction industry, and healthcare. Other remarkable application fields include education, logistics, e‐business, IT, R&D, telecommunication industry, finance and banking, urban management, defense industry and military, government, marketing, tourism and leisure, archaeology, auditing, and the mining industry.

The study does not consider theoretical based AHP or ANP articles. Also the search excluded conference proceedings, masters' theses, and doctoral dissertations.

It is hoped that this study will guide practitioners in future work towards advancement of these techniques and will help the managers to select better decisions by making use of these methodologies.

The paper presents a comprehensive literature review of recent applications of AHP, and also ANP decision tools over the period 2005‐2009. Furthermore, the paper covers fuzzy AHP and fuzzy ANP extensions that are becoming popular methods in some application areas of traditional AHP and ANP.

Against the backdrop of the contribution of design to the occurrence of occupational injuries and illnesses in construction, design for occupational safety and health (DfOSH) is increasingly becoming prominent in the construction sector. To ensure that design interventions are safe for construction workers to build and maintain, design firms need to have the appropriate organisational capability in respect of DfOSH. However, empirical insight regarding the attributes that constitute DfOSH organisational capability is lacking. The purpose of this paper, which trailblases the subject of DfOSH organisational capability in construction, is to address two key questions: what organisational attributes determine DfOSH capability? What is the relative priority of the capability attributes?

The study employed three iterations of expert focus group discussion and a subsequent three-round Delphi technique accompanied by the application of voting analytic hierarchy process.

The study revealed 18 capability attributes nested within six categories, namely: competence (the competence of organisation’s design staff); strategy (the consideration of DfOSH in organisation’s vision as well as the top management commitment); corporate experience (organisation’s experience in implementing DfOSH on projects); systems (systems, processes and procedures required for implementing DfOSH); infrastructure (physical, and information and communication technology resources); and collaboration (inter- and intra-organisational collaboration to implement DfOSH on projects). Whilst these categories and their nested attributes carry varying weights of importance, collectively, the competence-related attributes are the most important, followed by strategy.

The findings should enable design firms and other key industry stakeholders (such as the clients who appoint them) to understand designers’ DfOSH capability better. Additionally, design firms should be able to prioritise efforts/investment to enhance their DfOSH capability.

Supplier selection for defence procurement is a crucial function of a Ministry of Defence. The Ministry spends huge amounts of money each year to procure a vast array of equipment, goods and services. The ongoing financial crisis demands less subjective and more cost-saving methods for selecting a supplier. The approach advocated in this article integrates Analytic Hierarchy Process (AHP) with Goal Programming (GP) in order to combine conflicting criteria to select the best suppliers and allocate optimum order quantities among them. This paper presents a model close to real-world situations. Findings demonstrate that cost savings is a feasible result along with a viable combination of conflicting criteria in the suppliers' selection area.

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.

As the modern manufacturing twining seamlessly with logistics operations for value adding services, logistics service is becoming more and more significant. Under this research background, the purpose of this paper is to introduce an innovative evaluation model for customer satisfaction using fuzzy analytic hierarchy process (FAHP).

This model uses triangular fuzzy concept to determine the weight of each index so that subjective or objective weighting is addressed. A case study from two large express companies in China is used to demonstrate the feasibility and practicality of the proposed model for examining customer satisfaction.

One of the key findings is that Company B has higher customer satisfaction than Company A due to its quick response and flexible logistics strategy. This paper has several contributions. First, A FAHP-based customer satisfaction evaluation model is proposed for the logistics service. Second, the triangular fuzzy concept is introduced to determine the weight of each index so as to addresses the limitation of subjective or objective weighting method. Third, a case study demonstrates the implementation of the model.

First, this paper considers the fuzzy AHP for the customer satisfaction evaluation. Comparing with other multi-criteria decision-making methods like data envelopment analysis, evidential reasoning approach, and multi-attribute value theory will be carried out in the near future. Second, the manufacturing modes like make-to-order, make-to-stock, and mass-customized production may have different logistics support so that the final products may reach the final targets quickly. How to evaluate various mode-based logistics and their customer satisfactions have great significance. Finally, Big Data-enabled customer satisfaction evaluation approaches may be a possible solution.

Based on the data from questionnaire, it is found that, in practical applications, manufacturing enterprises should amend the index system according to the specific business scope and the production characteristics. Manufacturing enterprises need to collect large amounts of data through market research and conduct the measurement on the related coefficient between the measurement indicators and customer satisfaction degree. After that, they can make sorting and filtering on the measurement index according to the measurement results.

Customer satisfaction is very important to manufacturing and logistics enterprises due to its time constraints. The physical products with services like logistics are paid close attention to by the final customers.

The contribution of this paper is as follows: a FAHP-based customer satisfaction evaluation model is proposed for the logistics service; triangular fuzzy concept is introduced to determine the weight of each index so as to addresses the limitation of subjective or objective weighting method; a case study was used to demonstrate the implementation of the model. One of the key findings is that Company B has higher customer satisfaction than Company B due to its quick response and flexible logistics strategy.

The paper seeks to provide academic researchers and practitioners with a better understanding about purchasing strategies through an integrated approach to supplier selection and purchasing decisions.

This paper views supplier selection as a multi‐criteria problem. Through the analytical hierarchy process (AHP), in consideration of both quantitative and qualitative criteria, a set of candidate suppliers is identified. A multi‐objective linear programming (MOLP) model, with multiple objectives and a set of system constraints, is then formulated and solved to allocate the optimum order quantities to the candidate suppliers.

The paper provides tradeoffs among different objectives, which are more consistent with the complexity and nature of the real‐world decision‐making environment. It also offers better information and solutions supporting effective purchasing decisions.

The main concept of the proposed approach can be applicable to any organization with a purchasing function. However, its implementation will be very specific to a particular organization of interest, as each individual organization must define its own subjective criteria and constraints. The area of decision support system development, which automates (or computerizes) the input process of the proposed models and integrates with other databases in a company, will provide great opportunities for future research.

The paper provides practitioners with flexibility and effectiveness in their supplier selection and purchasing decision process and with a better understanding about their future purchasing strategies. The results from the application of the proposed models to the supplier selection problem at a high‐technology firm in Taiwan show that the models are effective and applicable.

This paper takes an integrated approach to problem analysis (i.e. multi‐objectives with both quantitative and qualitative information), uses a sound scientific methodology in model development (i.e. integrating AHP with MOLP), and provides practical use of the models. It offers additional knowledge and value to both academics and practitioners.

Data envelopment analysis (DEA) and analytical hierarchy process (AHP) are two widely applied methods to evaluate and rank suppliers in terms of sustainability. In this study, to investigate the extent to which potential differences in the outcomes of these two methods influence the benchmarking strategies, a comparative analysis based on a common set of data gathered from 19 logistics service providers is implemented.

As suppliers' sustainability cannot be improved in a single-step process due to several limitations, improvement needs to proceed gradually. Therefore, using the self-organising map method, the suppliers were classified into clusters within a novel framework for gradually improving their sustainability. Then, the two processes of gradual improvement based on the outcomes of DEA and AHP were compared.

The findings show that although the rankings of suppliers guided by the methods correlated to a high degree, the benchmarking strategies provided by the methods for gradually improving the sustainability of suppliers differed considerably. In particular, whereas AHP suggests a benchmarking policy better suited for unsustainable or less sustainable suppliers with limited access to resources, DEA proposes one for suppliers able to dramatically boost their sustainability with few quick, significant leaps in performance.

First, this study revealed a novel gradual improvement framework using the self-organising map method. Second, it clarified the extent to which the benchmarking policies are influenced by the type of evaluation method.

The aim of this paper is to identify the criteria that are used for vendor or supplier rating, prioritize these criteria based on the industry inputs and develop a vendor rating model. The data were collected from an Indian start-up working in product development using three-dimensional printing (3DP).

Factors of importance for vendor rating were identified through industry visits, and interacting with the industry experts from the start-up under consideration, substantiated by extensive review of relevant literature. A questionnaire-based survey was carried out to further narrow down the factors important to the industry, prioritizing them with a pairwise comparison analysis as envisaged in the analytical hierarchy process (AHP) technique along with the calculation of consistency ratios. Technique for order preference by similarity to ideal solution (TOPSIS) methodology was further used for data aggregation.

This research brought forward the criteria that are useful for rating vendors or suppliers with reference to 3DP sector.

This paper integrates AHP and TOPSIS to solve a multi-criteria vendor rating problem. The attempt was made to make vendor rating process universal so that it can encompass all the vendors of the firm.