Application of the analytic hierarchy process (AHP) in multi-criteria analysis of the selection of intelligent building systems

The availability of innumerable intelligent building (IB) products, and the current dearth of inclusive building component selection methods suggest that decision makers might be confronted with the quandary of forming a particular combination of components to suit the needs of a specific IB project. Despite this problem, few empirical studies have so far been undertaken to analyse the selection of the IB systems, and to identify key selection criteria for major IB systems. This study is designed to fill these research gaps. Two surveys: a general survey and the analytic hierarchy process (AHP) survey are proposed to achieve these objectives. The first general survey aims to collect general views from IB experts and practitioners to identify the perceived critical selection criteria, while the AHP survey was conducted to prioritize and assign the important weightings for the perceived criteria in the general survey. Results generally suggest that each IB system was determined by a disparate set of selection criteria with different weightings. ‘Work efficiency’ is perceived to be most important core selection criterion for various IB systems, while ‘user comfort’, ‘safety’ and ‘cost effectiveness’ are also considered to be significant. Two sub-criteria, ‘reliability’ and ‘operating and maintenance costs’, are regarded as prime factors to be considered in selecting IB systems. The current study contributes to the industry and IB research in at least two aspects. First, it widens the understanding of the selection criteria, as well as their degree of importance, of the IB systems. It also adopts a multi-criteria AHP approach which is a new method to analyse and select the building systems in IB. Further research would investigate the inter-relationship amongst the selection criteria.

Interactive management control via analytic hierarchy process (AHP). An empirical study in a public university hospital

Management control in public university hospitals is a challenging task because of continuous changes due to external pressures (e.g. economic pressures, stakeholder focuses and scientific progress) and internal complexities (top management turnover, shared leadership, technological evolution, and researcher oriented mission). Interactive budgeting contributed to improving vertical and horizontal communication between hospital and stakeholders and between different organizational levels. This paper describes an application of Analytic Hierarchy Process (AHP) to enhance interactive budgeting in one of the biggest public university hospital in Italy. AHP improved budget allocation facilitating elicitation and formalization of units' needs. Furthermore, AHP facilitated vertical communication among manager and stakeholders, as it allowed multilevel hierarchical representation of hospital needs, and horizontal communication among staff of the same hospital, as it allowed units' need prioritization and standardization, with a scientific multi-criteria approach, without using complex mathematics. Finally, AHP allowed traceability of a complex decision making processes (as budget allocation), this aspect being of paramount importance in public sectors, where managers are called to respond to many different stakeholders about their choices.

An application of the analytic hierarchy process and fuzzy logic inference in a decision support system for forage selection

Forage selection plays a prominent role in the process of returning cultivated lands back into grasslands. The conventional method of selecting forage species can only provide attempts for problem-solving without considering the relationships among the decision factors globally. Therefore, this study is dedicated to developing a decision support system to help farmers correctly select suitable forage species for the target sites. After collecting data through a field study, we developed this decision support system. It consists of three steps: (1) the analytic hierarchy process (AHP), (2) weights determination, and (3) decision making. In the first step, six factors influencing forage growth were selected by reviewing the related references and by interviewing experts. Then a fuzzy matrix was devised to determine the weight of each factor in the second step. Finally, a gradual alternative decision support system was created to help farmers choose suitable forage species for their lands in the third step. The results showed that the AHP and fuzzy logic are useful for forage selection decision making, and the proposed system can provide accurate results in a certain area (Gansu Province) of China.

Incorporating community objectives in improved wetland management: the use of the analytic hierarchy process

Wetlands in Australia provide considerable ecological, economic, environmental and social benefits. However, the use of wetlands has been indiscriminate and significant damage to many Australian wetlands has occurred. During the last 150 years one third of the wetlands in Victoria have been lost. A conspicuous problem in wetland management is the paucity of involvement by stakeholders. This paper uses the Analytic Hierarchy Process (AHP) to incorporate stakeholder objectives in the ‘Wonga Wetlands’ on the Murray River. The study shows that the AHP can explicitly incorporate stakeholder preferences and multiple objectives to evaluate management options. The AHP also provides several approaches for policy makers to arrive at policy decisions.

Assessment of wilderness quality using the analytic hierarchy process

Wilderness is a unique environmental resource that provides a multitude of use and non-use benefits. The use and management of wilderness depend on the assessment of wilderness quality. Current wilderness assessment in Australia is based on two broad criteria, the remoteness and naturalness of the wilderness, determined using geographic information systems. This paper discusses a complementary assessment method using the Analytic Hierarchy Process (AHP). The AHP can be used to incorporate additional criteria, such as social and cultural criteria, to improve the quality of wilderness assessment. It provides a flexible and compatible method for large-scale wilderness assessments with multiple criteria. The weighting factors for the different criteria can be obtained from expert panels and focus groups.

The use of analytic hierarchy process to incorporate stakeholder preferences into regional forest planning

Forest management decisions are often characterised by complexity, irreversibility and uncertainty. Much of the complexity arises from the multiple-use nature of forest goods and services, difficulty in monetary valuation of ecological services and the involvement of numerous stakeholders. Under these circumstances, conventional methods such as cost-benefit analysis are ill-suited to evaluate forest decisions. The Analytic Hierarchy Process (AHP), can be useful in regional forest planing as it can accommodate conflictual, multidimensional, incommensurable and incomparable set of objectives. The objective of this paper is to examine the scope and feasibility of the AHP in incorporating stakeholder preferences into regional forest planning. The Australian Regional Forest Agreement Programme is taken as an illustrative case for the analysis. The results show that the AHP can formalize public participation in decision making and increase the transparency and the credibility of the process.

Selecting the individual numerical scale and prioritization method in the analytic hierarchy process : a 2-tuple fuzzy linguistic approach

The validity of the priority vector used in the analytic hierarchy process (AHP) relies on two factors: the selection of a numerical scale and the selection of a prioritization method. The traditional AHP selects only one numerical scale (e.g., the Saaty scale) and one prioritization method (e.g., the eigenvector method) for each particular problem. For this traditional selection approach, there is disagreement on which numerical scale and prioritization method is better in deriving a priority vector. In fact, the best numerical scale and the best prioritization method both rely on the content of the pairwise comparison data provided by the AHP decision makers. By defining a set of concepts regarding the scale function and the linguistic pairwise comparison matrices (LPCMs) of the priority vector and by using LPCMs to unify the format of the input and output of AHP, this paper extends the AHP prioritization process under the 2-tuple fuzzy linguistic model. Based on the extended AHP prioritization process, we present two performance measure criteria to evaluate the effect of the numerical scales and prioritization methods. We also use the performance measure criteria to develop a 2-tuple fuzzy linguistic multicriteria approach to select the best numerical scales and the best prioritization methods for different LPCMs. In this paper, we call this type of selection the individual selection of the numerical scale and prioritization method. We also compare this individual selection with traditional selection by using both random and real data and show better results with individual selection.

The analytic hierarchy process to support decision-making processes in infrastructure projects with social impact

There is an increasing awareness among all kinds of organisations (in business,government and civil society) about the benefits of jointly working with stakeholders to satisfy both their goals and the social demands placed upon them. This is particularly the case within corporate social responsibility (CSR) frameworks. In this regard, multi-criteria tools for decision-making like the analytic hierarchy process (AHP) described in the paper can be useful for the building relationships with stakeholders. Since these tools can reveal decision-maker’s preferences, the integration of opinions from various stakeholders in the decision-making process may result in better and more innovative solutions with significant shared value. This paper is based on ongoing research to assess the feasibility of an AHP-based model to support CSR decisions in large infrastructure projects carried out by Red Electrica de España, the sole transmission agent and operator of the Spanishelectricity system.

Analytic hierarchy process helps select site for limestone quarry expansion in Barbados

Site selection is a key activity for quarry expansion to support cement production, and is governed by factors such as resource availability, logistics, costs, and socio-economic-environmental factors. Adequate consideration of all the factors facilitates both industrial productivity and sustainable economic growth. This study illustrates the site selection process that was undertaken for the expansion of limestone quarry operations to support cement production in Barbados. First, alternate sites with adequate resources to support a 25-year development horizon were identified. Second, technical and socio-economic-environmental factors were then identified. Third, a database was developed for each site with respect to each factor. Fourth, a hierarchical model in analytic hierarchy process (AHP) framework was then developed. Fifth, the relative ranking of the alternate sites was then derived through pair wise comparison in all the levels and through subsequent synthesizing of the results across the hierarchy through computer software (Expert Choice). The study reveals that an integrated framework using the AHP can help select a site for the quarry expansion project in Barbados.

Benchmarking project management practices of Caribbean organizations using analytic hierarchy process

Effective management of projects is becoming increasingly important for any type of organization to remain competitive in today’s dynamic business environment due to pressure of globalization. The use of benchmarking is widening as a technique for supporting project management. Benchmarking can be described as the search for the best practices, leading to the superior performance of an organization. However, effectiveness of benchmarking depends on the use of tools for collecting and analyzing information and deriving subsequent improvement projects. This study demonstrates how analytic hierarchy process (AHP), a multiple attribute decision-making technique, can be used for benchmarking project management practices. The entire methodology has been applied to benchmark project management practice of Caribbean public sector organizations with organizations in the Indian petroleum sector, organizations in the infrastructure sector of Thailand and the UK. This study demonstrates the effectiveness of a proposed benchmarking model using AHP, determines problems and issues of Caribbean project management in the public sector and suggests improvement measures for effective project management.

Project risk management:a combined analytic hierarchy process and decision tree approach

Time, cost and quality achievements on large-scale construction projects are uncertain because of technological constraints, involvement of many stakeholders, long durations, large capital requirements and improper scope definitions. Projects that are exposed to such an uncertain environment can effectively be managed with the application of risk management throughout the project life cycle. Risk is by nature subjective. However, managing risk subjectively poses the danger of non-achievement of project goals. Moreover, risk analysis of the overall project also poses the danger of developing inappropriate responses. This article demonstrates a quantitative approach to construction risk management through an analytic hierarchy process (AHP) and decision tree analysis. The entire project is classified to form a few work packages. With the involvement of project stakeholders, risky work packages are identified. As all the risk factors are identified, their effects are quantified by determining probability (using AHP) and severity (guess estimate). Various alternative responses are generated, listing the cost implications of mitigating the quantified risks. The expected monetary values are derived for each alternative in a decision tree framework and subsequent probability analysis helps to make the right decision in managing risks. In this article, the entire methodology is explained by using a case application of a cross-country petroleum pipeline project in India. The case study demonstrates the project management effectiveness of using AHP and DTA.

Selection of power market structure using the analytic hierarchy process

Selection of a power market structure from the available alternatives is an important activity within an overall power sector reform programme. The evaluation criteria for selection are both subjective as well as objective in nature and the selection of alternatives is characterised by their conflicting nature. This study demonstrates a methodology for power market structure selection using the analytic hierarchy process (AHP), a multiple attribute decision-making technique, to model the selection methodology with the active participation of relevant stakeholders in a workshop environment. The methodology is applied to a hypothetical case of a State Electricity Board reform in India.

Integrated analytic hierarchy process and its applications:a literature review

Due to its wide applicability and ease of use, the analytic hierarchy process (AHP) has been studied extensively for the last 20 years. Recently, it is observed that the focus has been confined to the applications of the integrated AHPs rather than the stand-alone AHP. The five tools that commonly combined with the AHP include mathematical programming, quality function deployment (QFD), meta-heuristics, SWOT analysis, and data envelopment analysis (DEA). This paper reviews the literature of the applications of the integrated AHPs. Related articles appearing in the international journals from 1997 to 2006 are gathered and analyzed so that the following three questions can be answered: (i) which type of the integrated AHPs was paid most attention to? (ii) which area the integrated AHPs were prevalently applied to? (iii) is there any inadequacy of the approaches? Based on the inadequacy, if any, some improvements and possible future work are recommended. This research not only provides evidence that the integrated AHPs are better than the stand-alone AHP, but also aids the researchers and decision makers in applying the integrated AHPs effectively.

Combining analytic hierarchy process and goal programming for logistics distribution network design

Logistics distribution network design is one of the major decision problems arising in contemporary supply chain management. The decision involves many quantitative and qualitative factors that may be conflicting in nature. This paper applies an integrated multiple criteria decision making approach to design an optimal distribution network. In the approach, the analytic hierarchy process (AHP) is used first to determine the relative importance weightings or priorities of alternative warehouses with respect to both deliverer oriented and customer oriented criteria. Then, the goal programming (GP) model incorporating the constraints of system, resource, and AHP priority is formulated to select the best set of warehouses without exceeding the limited available resources. In this paper, two commercial packages are used: Expert Choice for determining the AHP priorities of the warehouses, and LINDO for solving the GP model. © 2007 IEEE.

Green supply chain performance measurement using the analytic hierarchy process:a comparative analysis of manufacturing organisations

The main purpose of this research is to develop and deploy an analytical framework for measuring the environmental performance of manufacturing supply chains. This work's theoretical bases combine and reconcile three major areas: supply chain management, environmental management and performance measurement. Researchers have suggested many empirical criteria for green supply chain (GSC) performance measurement and proposed both qualitative and quantitative frameworks. However, these are mainly operational in nature and specific to the focal company. This research develops an innovative GSC performance measurement framework by integrating supply chain processes (supplier relationship management, internal supply chain management and customer relationship management) with organisational decision levels (both strategic and operational). Environmental planning, environmental auditing, management commitment, environmental performance, economic performance and operational performance are the key level constructs. The proposed framework is then applied to three selected manufacturing organisations in the UK. Their GSC performance is measured and benchmarked by using the analytic hierarchy process (AHP), a multiple-attribute decision-making technique. The AHP-based framework offers an effective way to measure and benchmark organisations’ GSC performance. This study has both theoretical and practical implications. Theoretically it contributes holistic constructs for designing a GSC and managing it for sustainability; and practically it helps industry practitioners to measure and improve the environmental performance of their supply chain. © 2013 Copyright Taylor and Francis Group, LLC. CORRIGENDUM DOI 10.1080/09537287.2012.751186 In the article ‘Green supply chain performance measurement using the analytic hierarchy process: a comparative analysis of manufacturing organisations’ by Prasanta Kumar Dey and Walid Cheffi, Production Planning & Control, 10.1080/09537287.2012.666859, a third author is added which was not included in the paper as it originally appeared. The third author is Breno Nunes.