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Managing complex construction projects is a challenging task because it involves multiple factors and decision-making processes. A systematic evaluation of these complex factors is imperative for achieving project success. As most of these factors are qualitative or intangible in nature, decision makers often rely on subjective judgements when comparing and evaluating them. The hybrid techniques that integrate fuzzy set theory and the analytic hierarchy process (AHP) are able to deal with such problems. This chapter discusses various hybrid techniques of the fuzzy AHP and presents an application of these techniques to the evaluation of transportation project complexity, which is essential for prioritising resource allocation and assessing project performance. Project complexity can be quantified and visualised effectively with the application of the fuzzy AHP. This chapter enhances the understanding of construction project complexity and fuzzy hybrid computing in construction engineering and management. Future research should address the calibration of fuzzy membership functions in pairwise comparisons for each individual decision maker and develop computational tools for solving optimisation problems in the constrained fuzzy AHP. In the area of construction project complexity, future research should investigate how scarce resources are allocated to better manage complex projects and how appropriate resource allocation improves their performance.

To provide customer‐oriented group decision methodology for designers or developers in using quality function deployment which is based on voice of customer.

Technical importance rating in house of quality (HoQ) should be evaluated considering both the roof and relationship matrix. Since the roof is generally irreducible, all of relationships between customer attribute (CA) and engineering characteristic (EC) are evaluated. A customer‐oriented evaluating method is proposed and empirical test is issued.

The phenomenon of inconsistency which is frequently found in HoQ is easily protected by proposed approach which focuses on the view of customer.

The proposed evaluating method is appropriate for the time when the number of ECs or CAs are greater than nine. If the number of alternatives is less than nine, analytic hierarchical process is usually used. However, 1‐9 scaling pairwise comparison is not suitable for customers such as non‐experts, housewives, or even children.

Especially, the proposed evaluating method could be widely used for organizations depending on customers.

In various fields, this paper supports the customer‐centered environment.

Most industries have become increasingly competitive nowadays, and a good supply chain relationship is essential for a company to survive and to acquire reasonable profit. Therefore, supplier selection is very important. The purpose of this paper is to propose a novel model for evaluating the performance of suppliers.

A supplier performance evaluation model based on analytic hierarchy process (AHP) and data envelopment analysis (DEA) is constructed. DEA is applied first to evaluate quantitative factors, and the results are transformed into pairwise comparison values for AHP analysis. Qualitative factors are also evaluated through AHP analysis, and a final ranking of suppliers can be obtained by combining the quantitative and qualitative results.

The proposed model can be applied to evaluate and select the most appropriate integrated circuit packaging company for outsourcing. With the incorporation of experts' opinions and the consideration of qualitative and quantitative factors, the model can provide a both subjective and objective supplier performance ranking.

The proposed model can be tailored and applied to supplier evaluation and selection in other industries.

Although many models are available for supplier evaluation, this paper considers both the subjective and objective performance characteristics simultaneously in the evaluation process.

The purpose of this study is to measure the supply chain competitiveness of the e-commerce industry in Indonesia.

The study used a multi-criteria decision-making model based on the analytic hierarchy process. Four main criteria are used to measure the supply chain competitiveness, i.e. cost, differentiation, sustainability and infrastructure.

The findings of this study show that cost is the most important criterion with a degree of importance of 33.19%, followed by infrastructure of 29.40%, differentiation of 27.96% and sustainability of 9.45%. It shows that the internally controlled strategy contributes about 70% of supply chain competitiveness. The internal infrastructure criterion that consists of software and hardware contributes 65.92% to the whole infrastructure criterion. The internal infrastructure then contributes 19.38% to supply chain competitiveness. Therefore, the internally controlled strategies and internal infrastructure contribute up to 90.08% to the supply chain competitiveness of e-commerce in Indonesia. This result implies that to attain the supply chain competitiveness, the company must carry out strategies focusing on the performance such as cost, differentiation, sustainability as well as on the internal infrastructure such as software and hardware.

In this paper, the authors limited their study to the business to business (B2B) and business to consumer (B2C) players because these two platforms have been experiencing a very rapid growth. While e-commerce business can take many platforms besides B2B and B2C, the future research should include other platform such as consumer to consumer as well. Because the focus in this study is more the information and material flows, it will be of great interest if the future research covers the platform of mobile payment as well that guarantee the ease of cashflows within supply chains. Also, with the occurrence of the Covid-19 pandemic when this paper was written, in the near future, it is then of great interest to incorporate the pandemic context into the proposed model used in this study. The further study should analyze long-term changes happened as the result of pandemic such as behavioral changes of online shopping from customer side or shift in e-commerce supply chain infrastructure and inventory practice.

With this study, it is expected that it can be determined which criteria contribute the most to the supply chain competitiveness of the e-commerce industry in Indonesia that will be useful for industry player.

E-commerce development in Indonesia is still facing serious challenges. The multi-criteria decision making approach used in this research lays a foundation of how supply chain competitiveness is determined based on the judgment of experts coming from major companies within the supply chain.

The decision to disclose an illness is a difficult choice for many individuals. Despite national laws such Americans with Disabilities Act that protect workers with disabilities from discrimination in the workplace, the stigmas around certain illnesses, fears of being judged by others using different standards, and concerns about a lack of support regardless of legal requirements are all reasons why someone may hesitate to disclose a health condition in the workplace.

Using experimentally manipulated vignettes and a combination of theories on attribution and incivility, this study explores the dangers of not disclosing a disability/condition that can lead to behaviors that will engender judgments by coworkers.

The results of the study make clear that there are social benefits to disclosing a health condition rather than concealing. The findings clearly demonstrate that attributing an individual's negative behavior to their disposition will lead to more judgments of responsibility, and less sympathy and more anger compared to behaviors that can be explained by any health reason. Furthermore, more punishment, feelings of revenge and social distancing await individuals whose negative behavior cannot be explained by health issues.

This study combines issues of health, attributions, incivility in an experimental studies that illuminates issues surround disclosing a workplace disability that go beyond the typical focus of legal questions.

This paper aims to compare two groups of stocks to analyze the efficiency of an ethical portfolio in comparison with a conventional portfolio.

Efficiency test by second-order stochastic dominance (SSD) approach is applied on two groups, which consist of 12 stocks. Ethical portfolio is chosen from the stocks complying with the participation banking rules. Conventional portfolio is selected from Borsa Istanbul (BIST) with choosing the corresponding stocks for each ethical stock according to the sector and market capitalization. All the stocks of both groups are pairwise SSD compared.

Both groups of 12 stocks are inefficient portfolios; however, a group of 7 stocks constitute an efficient ethical portfolio with the total weight of 50.82 per cent among the set of 12 ethical stocks. On the other hand, a group of 6 stocks constitute an efficient conventional portfolio, with the total weight of 45.16 per cent among the set of 12 conventional stocks. By pairwise SSD comparison of corresponding stocks from both groups, despite none of the conventional stocks dominate ethical stocks, four ethical stocks dominated the conventional ones.

Back-testing and comparison with benchmark BIST 100 Index have been done for the selected portfolios. According to back-testing results, groups of SSD efficient stocks outperformed the groups, from which they were selected. Furthermore, both SSD efficient portfolios have higher returns than benchmark index, BIST 100.

Cloud computing is relatively a new type of technology demanding a new method of management techniques to attain security and privacy leading to customer satisfaction regarding “Business Protection” measure. As cloud computing businesses are usually composed of multiple colocation sites/departments, the purpose of this paper is to propose a benchmark operation to measure and compare the overall integrated people-process-performance (PPP) among different departments within cloud computing organization. The purpose of this paper is to motivate staff/units to improve the process performance and meet the standards in a competitive approach among business units.

The research method was conducted at Cirrus Ltd, which is a cloud computing service provider where a focus group consists of six IT professionals/managers. The objective of the focus group was to investigate the proposed technique by selecting the best practices relevant criteria, with the relevant sub-criteria as a benchmarking performance tool to measure PPP via an analytic hierarchy processing (AHP) approach. The standard pairwise comparative AHP scale was used to measure the performance of three different teams defined as production team, user acceptance testing team and the development team.

Based on best practice performance measurement (reviewed in this paper) of cloud computing, the proposed AHP model was implemented in a local medium-sized cloud service provider named “Cirrus” with their single site data center. The actual criteria relevant to Cirrus was an adaptation of the “Best practice” described in the literature. The main reason for the adaptation of criteria was that the principle of PPP assumes multiple departments/datacenters located in a different geographical area in large service providers. As Cirrus is a type of SMEs, the adaptation of performance measurement was based on teams within the same data center location. Irrelevant of this adaptation, the objective of measuring vendors KPI using the AHP technique as a specific output of PPP is also a valid situation.

This study provides guidance for achieving cloud computing performance measurement using the AHP technique. Hence, the proposed technique is an integrated model to measure the PPP under monitored cloud environment.

The proposed technique measures and manages the performance of cloud service providers that also implicitly act as a catalyst to attain trust in such high information-sensitive environment leading to organizational effectiveness of managing cloud organizations.

The purpose of this paper is to present the development of a methodology to evaluate suppliers using portfolio analysis based on the analytical network process (ANP) and environmental factors.

The authors develop a three‐step process, first by evaluating influence/power and performance scores of suppliers using ANP. They include environmental dimensions in this analysis, then map these suppliers onto a portfolio grid. Recommendations are also made on how to manage suppliers depending on what part of the portfolio they appear based on the scores.

The technique is useful and versatile. The paper clearly discerns various characteristics of the suppliers and produced recommendations on supplier management for an exemplary case scenario.

The technique was applied for an illustrative example. Validation and application in a real world setting is required. There are many additional opportunities to further integrate other modeling tools into this process.

Managers can use this technique to help them more effectively deal with suppliers. The portfolio is a good tool for operational and strategic management of suppliers.

This tool is the first to apply ANP to supplier portfolio analysis. It is also the first tool to integrate and apply the portfolio supplier management approach to an environmentally oriented decision environment.

Studies the justification problems of automated manufacturing systems (AMS) by using a multiple‐criteria decision making (MCDM) approach such as analytic hierarchy process (AHP). An example from Indian manufacturing has been studied. Strategic, technological and social impacts have been considered for justifying AMS and decomposing these factors into several possible attributes.