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The robust appraisal of exploration drilling concepts is essential for establishing the economic viability of a prospective recovery field. This study evaluates the different concept selection methods that were considered for drilling operations at the Trym field in Norway. The construction of drilling rigs is a capital-intensive process, and it involves high levels of economic risk. These risks can be broadly categorised as aleatoric (i.e. those related to chance) and epistemic (i.e. those related to knowledge). Evaluating risks in the investment appraisal process tends to be a complicated process. Project risks are evaluated using Monte Carlo simulation (MCS) and are based on the fuzzy analytic hierarchy process (AHP). MCS provides a useful means of evaluating variabilities (i.e. aleatoric risks) in oil drilling operations. However, many of the economic risks in oil drilling processes are unanticipated, and, in some cases, are not readily expressible in quantitative values. The fuzzy AHP is therefore used to appraise the qualitatively defined indirect revenues comprising risks that affect future flexibilities, schedule certainty and health and safety performance. Both the Monte Carlo technique and the fuzzy AHP technique found that a cumulative revenue variation of up to 30% is possible in any of the considered drilling options. The fuzzy AHP technique estimates that the chances of profitability being less than NOK 1 billion over a five-year period is 0.5%, while the Monte Carlo technique estimates suggest a more conservative proportion of 10%. Overall, the fuzzy AHP technique is easy to use and flexible, and it demonstrates increased robustness and improved predictability.

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.

Contractor prequalification is a typical multiple criteria decision‐making problem that includes both quantitative and qualitative criteria. The conditions surrounding the prequalification decision are often imprecise, subjective and uncertain; assessments are consequently made using linguistic approximations. Fuzzy set theory is specifically designed to handle qualitative and linguistic data based on approximations and provides a method of representing in numerical form the linguistic approximations used to describe the decision‐maker judgments. However, fuzzy set theory has a weakness in identification of the relative weights of the decision criteria. On the other hand, one of the most accurate and easy methods for identifying the relative weights is the analytic hierarchy process (AHP). This paper seeks to address these issues.

The main objective of this paper is to develop a new integrated decision model composed of fuzzy set theory and analytic hierarchy process (AHP) methodologies approach that takes full advantages of the fuzzy set theory and the AHP. Two fuzzy approaches are considered, namely Chang's extent analysis and Jaskowski aggregated group decision analysis.

Both approaches are applied and validated on actual contractors in the Egyptian construction market. A software tool is developed to automate the calculations and a case study is provided.

This research produced a new integrated decision model composed of fuzzy‐AHP methodology approach that takes full advantages of the fuzzy set theory and AHP for tackling the uncertainty and imprecision of contractor prequalification during the prequalification stage, where the decision‐makers comparison judgments are represented as fuzzy triangular numbers. The default criteria used in this model had been collected through the literature review and experts’ opinion for building projects.

Purpose of study: Indian fibre cement industry is at crossroads on account of the dropping margins attributed to the dynamic internal and external challenges faced by it. The ever-changing technology, the increasing availability of substitutes and changing demographic consumption profiles have questioned the survival of this industry. Internal and external factors affecting an organization provide inputs to the strategic decision-making. Diversity of factors and prioritization is a major challenge encountered for developing a strategy for the organization.

Strategic analysis in the paper proposes to rank important key variables through SWOT-AHP methodology affecting a fibre cement company. Computed priorities of SWOT factor could help in formation of management approach to key decisions facing the firm. It is a descriptive research design. The problem itself has multiple SWOT criteria that have been evaluated in three phases with the help of industry experts and AHP criteria.

SWOT-AHP analysis has been a strategic fit for qualitative analysis of factors. The important ranked factors affecting the organization have been found to be brand name, capability of both the management and technical, quality of the product, and the efficient customer service and marketing reach/distribution.

Ranking of key SWOT factors found through AHP methodology will help the firm under study to develop and plan strategic alternatives to counter all challenges faced by them.

The management of the firm under study shall be benefited in fine-tuning the overall strategy of the organization.

This paper proposes a hybrid SWOT-AHP strategic analysis first time in this sector. The affecting factors have been quantified and ranked to identify priority factors for the firm to focus.

Advanced digitalization techniques combined with artificial intelligence and automated robotic systems have created “Smart” organizations resulting in a new revolution in the industrial production systems as Industry 4.0 (I4.0). The research is aimed to do a meticulous scanning of internal and external environment pertaining to I4.0 implementation in the manufacturing industry in India.

A survey was conducted among the manufacturing managers and information technology professionals about the factors affecting I4.0 application, and 20 such internal and external factors were identified. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were executed for factor analysis, and four dimensions in terms of strengths, weaknesses, opportunities and threats (SWOT) factors were determined from the variables. The analytical hierarchy process (AHP) methodology was then applied.

Results show that increased productivity and efficiency appeared to be the biggest strength of I4.0 while the biggest weakness is the need for specialized training and skills. The biggest opportunity is found to be increasing trust of customers in Internet transactions and employee resistance to adopting new technologies turned out to be the biggest threat.

Organizations will be able to evaluate the strengths, work upon weakness, exploit the opportunities and protect against external challenges and threats beforehand while implementing I4.0 technologies.

The four dimensions in terms of SWOT pertaining to manufacturing industry have been identified by collecting original data from the manufacturing industry, and AHP and CFA were then carried out to prioritize and verify them.

The main intention of this paper is to analyze various factors hindering the growth of the agricultural supply chain and several industry 4.0 technologies to eliminate the same. In addition to a detailed assessment on the implementation of these technologies in agriculture, this manuscript also presents a priority list providing a rank to them based on the relative efficiency of these advancements in addressing these obstacles.

This research proceeds with a two-step process. The particular barriers in the agriculture supply chain and industry 4.0 technologies are determined in the first step. Next, the proposed framework, a combination of data envelopment analysis (DEA) and analytic hierarchy process (AHP), i.e. DEA-AHP, is used to determine a hierarchical structure for the factors and the relative productive efficiencies of the alternatives. The DEA methodology gives a performance analysis of various decision-making units. At the same time, AHP helps in evaluating alternatives weights based on numerous criteria, allowing us to categorize their importance further.

This study reveals how the involvement of technological advancements in agriculture can help manage the supply chain more efficiently. It also justifies how the large quantities of data generated can handle these increasing challenges in the agricultural supply chain.

The results of this study provide a priority list of alternatives based on their final weights. This ranking system can help farmers and the government select the best-suited technology for bringing automation into the agricultural supply chain.

This research is unique as it analyes the general factors hindering the development of the agriculture supply chain while simultaneously providing a list of alternatives based on their relative efficiencies. The study enriches existing literature by providing an analytic approach to determine the weightage of various critical success factors that can help improvise and entrust the real and undeniable requirements of consumers, suppliers and producers.

The purpose of this paper is to develop an analytic hierarchy planning-based framework to establish criteria weights and to develop a school performance system commonly called school inspections.

The analytic hierarchy process (AHP) model uses pairwise comparisons and a measurement scale to generate the weights for the criteria. The validity of the approach is confirmed by comparing the outputs of school inspection and the outputs of the model in a sample of schools.

The framework proposed enables school management to address several issues pertaining to its competitive advantage with other schools, the two most important being establishing its performance ranking in the marketplace and identifying the service elements that most require improvement. This study develops a cohesive approach to identify which quality attributes or dimensions require attention.

For school inspections, the data collection and computational problems would increase with the increase in the number of criteria and sub-criteria, as well as the number of schools considered in the selection. Although the range of reported AHP applications is extensive in many disciplines, examples in school quality and inspection remain still rare; as a result, this study could not compare its results with other AHP applications in school inspection or assessment.

The AHP method has the distinct advantage that it decomposes a decision problem into its constituent parts and builds hierarchies of criteria. AHP enables assessors to capture both subjective and objective evaluation measures of school quality. By providing a useful mechanism for assessing the consistency of the evaluation measures and alternatives, the AHP reduces bias in decision making.

The AHP model also provides a more systematic evaluation of a given school’s qualitative performance criteria. The proposed AHP model is attractive to assessors and decision makers because its pairwise comparison procedure enables them to offer a relative (rather than absolute) individual criterion assessment on those qualitative factors.

The AHP model could become a sustainable component of overall school system quality improvement by maturing over time. The AHP annual scores could be used as realistic and measureable gauges for measuring school improvement.

The objective of the work is to have an insight into the degree of the contemporary concept of greening the organization through human resource management (HRM) and to attempt to bridge the gap toward environmental awareness, as well as to observe the dimensions of green HRM (GHRM) practices and its impression toward environmental sustainability by using analytical hierarchy process (AHP) and FAHP.

The research was carried out in two phases; multi-method was employed. The first phase mainly includes a systematic review to convene comprehensive knowledge of widespread GHRM practices to leverage environmental sustainability. In the second phase, the AHP and fuzzy AHP (FAHP) were employed to examine the influence of the respective dimension of GHRM practices toward environmental sustainability.

This study emphasizes the status of GHRM practices such as green recruitment and green selection, green performance management, green training and development, green compensation and rewards, green welfare aspects as a way to aid environmental issues. The findings suggest that these initiatives help to leverage environmental sustainability. Further, this paper reveals that green compensation and rewards have the highest impact on leveraging environmental sustainability. However, this study also emphasizes the comparative study of GHRM dimensions through AHP and FAHP.

As existing studies reveal, there is least research carried on this field of study and no study was conducted using AHP and FAHP in this field. Thus, this study reveals the necessity to discover the degree of concern toward GHRM practices in context to India.

Khadi fabrics are known for their unique comfort properties which are attributed to their unique structural and functional properties. For getting optimal comfort from a collection of available Khadi fabrics, further exploration is needed. Ranking the Khadi fabrics from a competitive lot for optimal comfort is a challenging job, which has not been addressed so far by any researcher. The purpose of this study is to present one such selection problem using the multi-criteria decision-making (MCDM) technique, a popular branch of operations research, which can handle almost any decision problem involving a finite number of alternatives and multiple decision criteria.

Two widely popular methods/exponents of MCDM, namely, analytic hierarchy process (AHP) and multiplicative analytic hierarchy process (MAHP) have been deployed in this study for ranking a competitive lot of 15 Khadi fabrics and selecting the best alternative for optimal summer comfort based on three comfort attributes, namely, drape coefficient, thermal insulation value and air permeability.

Both the approaches yield a similar ranking pattern with Spearman’s rank correlation coefficient of 0.9857, Khadi fabric K1 achieving Rank 1 (best in terms of optimal comfort) and sample K6 acquiring Rank 15 (worst choice). Two-phase sensitivity analyses were performed subsequently to demonstrate the stability of the two approaches: sensitivity analysis by changing weightage levels of the criteria and sensitivity analysis in dynamic decision conditions by changing the elements of the initial decision matrix. During sensitivity analyses, no occurrence of rank reversal is observed for the best and worst alternatives in either of the two approaches. This corroborates the robustness of the two models.

Khadi fabrics are widely acclaimed for their intrinsic comfort properties for both summer and winter. Although the popularity of Khadi fabrics is increasing day by day, this domain is under-researched, and hence, needs to be explored further. The present approach demonstrates how the MCDM technique can serve as a useful tool for ranking the available Khadi fabrics in terms of optimal comfort in summer. The same approach can be extended to other domains of the textile industry, in general, as well.

This study is the first-ever theoretical approach/research on the selection of Khadi fabrics for optimal summer comfort using the MCDM tool. Another novelty of the present study is that the efficacy of AHP and MAHP approaches, in this study, has been validated through a two-phase sensitivity analysis. This validation part has been ignored in most of the hitherto published applications of AHP and MAHP in other domains.

The purpose of this paper is to propose a new integrated method for evaluating inventory of slow-moving items by introducing the application of fuzzy AHP method with interval Type-2 fuzzy sets (IT2FSs) and ABC analysis.

In the study, fuzzy analytic hierarchy process (AHP) method with IT2FSs is employed to set the importance of criteria. The weights obtained from IT2 fuzzy AHP are used to classify slow-moving items in ABC analysis. In the application part, a real-life case study is presented.

The result of this study indicates that an integrated approach utilizing IT2 fuzzy AHP and ABC analysis can be used as a supportive tool for classification of slow-moving items. The problem is solved under fuzzy environment to handle uncertainties and lack of information about slow-moving items.

Actual data are provided from an automotive company for prioritizing a various criteria to evaluate and classify stocks and a hypothetical model integrated with IT2 fuzzy AHP and ABC analysis is demonstrated.

Apart from inventory classification literature, the study integrates fuzzy AHP method by employing interval IT2FSs and ABC analysis to solve the real-life inventory classification problem.