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While cost allocation decisions attract considerable attention in the management accounting literature, many studies are contradicting and inconclusive. They often seek to develop product or service weights in order to make operating decisions with the sole objective of maximizing the firm’s profitability. But before developing these weights, the studies must first rank these products – which is a complex endeavor that is often driven by many hierarchical financial and nonfinancial goals and objectives. Ranking is also difficult due to using such complex concepts as time, uncertainty, cost, and interdependencies between accounting systems and manufacturing systems and among the products of the product mix. These concepts are inherently fuzzy and coextensively applied often with a confluence of variables operating simultaneously.

This paper applies an advanced mathematical model to account for a hospital cost allocation decisions in treating spinal cord injuries (SCI). The model combines the powers of fuzzy set theory (Zadeh, 1965) and the analytic hierarchy process (Saaty, 1978). The precise ratings required in the conventional analytic hierarchy process but practically hard to obtain are replaced by naturally semantic variables by using the fuzzy set concept. de Korvin and Kleyle’s (1999) fuzzy-analytic-hierarchical process (FAHP) then develop these ambiguous variables. FAHP can help to optimize decisions involving ambiguous variables and the web of prioritized strategies and goals of cost leadership, product differentiation, financial objectives of earnings, cash flows, and market share and nonfinancial goals such as tradition and owners’ convictions and philosophies.

We use data from seven Michigan SCI facilities in applying the FAHP model to rank and otherwise develop more optimal strategies and goals and compare our results to the decisions of hospital management.

The main aim of this study is to identify and prioritize the factors that influence the adoption of big data analytics (BDA) within the supply chain (SC) of the food industry in India.

The study is carried out in two distinct phases. In the first phase, barriers hindering BDA adoption in the Indian food industry are identified. Subsequently, the second phase rates/prioritizes these barriers using multicriteria methodologies such as the “analytical hierarchical process” (AHP) and the “fuzzy analytical hierarchical process” (FAHP). Fifteen barriers have been identified, collectively influencing the BDA adoption in the SC of the Indian food industry.

The findings suggest that the lack of data security, availability of skilled IT professionals, and uncertainty about return on investments (ROI) are the top three apprehensions of the consultants and managers regarding the BDA adoption in the Indian food industry SC.

This research has identified several reasons for the adoption of bigdata analytics in the supply chain management of foods in India. This study has also highlighted that big data analytics applications need specific skillsets, and there is a shortage of critical skills in this industry. Therefore, the technical skills of the employees need to be enhanced by their organizations. Also, utilizing similar services offered by other external agencies could help organizations potentially save time and resources for their in-house teams with a faster turnaround.

The present study will provide vital information to companies regarding roadblocks in BDA adoption in the Indian food industry SC and motivate academicians to explore this area further.

Recent corporate failures such as Enron, WorldCom, Global Crossing and K‐Mart and auditing failures such as Arthur Andersen have sparked great public concern, including the passage of the Sarbanes‐Oxley Act of 2002. This paper aims to address the development of accounting standards.

The approach is to use the fuzzy‐analytical‐hierarchical‐process (FAHP), recently developed by de Korvin and Klyele. Uncertainty in assigning priorities and the use of semantic variables lead naturally to the inclusion of fuzzy sets in the structure of the AHP paradigm. The hierarchy of decisions, constructed sequentially, consists of three levels of attributes.

The paper shows that applying the highly sophisticated mathematical FAHP model is needed to select the optimum mechanism for establishing accounting and auditing standards. The FAHP application results lead to a rational ranking of the four bases to develop accounting standards.

This paper helps to explain the ambiguous and vague nature of the attributes of financial reporting and to apply a recently developed mathematical methodology to help accounting policy makers select the optimum mechanism for developing accounting standards.

The purpose of this paper is to develop a systematic and comprehensive project selection model utilizing fuzzy multi-objective linear programming (FMOLP) that deals with the imprecise data in IS projects and uncertain judgment of decision makers.

First, projects are prioritized by considering both quantitative and qualitative factors. A fuzzy analytical hierarchical process (FAHP) is used in order to obtain weights of each project that indicates their priorities. At the second step, project selection decision is completed by using FMOLP. Then, the sensitivity analysis is performed to evaluate the robustness of the proposed integrated model.

The result of this study indicates that an integrated approach utilizing FAHP and FMOLP can be used as a supportive tool for project selection in IS context. It decreases the uncertainty caused from uncertain judgment of decision makers.

Future studies are suggested to design models having fuzzy constraints such as budget and resources. Moreover, for future studies, non-linear membership functions can be used.

Actual projects are provided from the Turkish IS company for prioritizing process and a hypothetical mathematical model is demonstrated using illustrative data.

This study contributes to the relevant literature by proposing a comprehensive model considering many conflicting ideas of decision makers on quantitative and qualitative criteria, and evaluating projects in an integrated way including FAHP and FMOLP.

The earth is under massive stress due to current level of consumption which has crossed the sustaining capacity of our planet. Thus, the need of the hour is to promote sustainable production and consumption. The purpose of this study is to identify the basic barriers of sustainable consumer behaviour which are hindering the adoption of sustainable consumption.

This article is divided into two parts. The first part consists of a literature review based on 128 articles (1995 to 2020), which are spread over a period of 25 years. Based on the literature review, nine barriers of sustainable consumer behaviour were identified and put into three categories. In the second part, fuzzy analytical hierarchy process has been used to know about the relative weight of each barrier so that benchmarking/prioritising of basic barriers of sustainable consumer behaviour can be done.

This article identifies critical barriers affecting the acceptance of sustainable electronic products. High price, a perception of no environmental impact, no benefit in personal image, lesser use by family and friends, lack of awareness about the products etc. emerged as the potential barriers which need prime attention. The relative weight of each of these barriers has also been arrived at in this article which is expected to be beneficial for policymakers to focus upon important barriers. Impact of many of these barriers can be reduced through innovative approaches and solutions.

This article will be helpful in future research in the field of sustainable consumer behaviour. Through the understanding of the barriers of sustainable consumer behaviour, companies, governments and industries can take suitable initiatives by modifying the policies and practices to reduce the impact of these barriers so that consumer behaviour can be made more sustainable.

The current article tries to identify the critical barriers to adoption of sustainable electronic products by the consumers. An extensive literature review, expert suggestions and consumer survey have been adopted to identify nine barriers. Although, multiple researches have been done in the field of sustainable consumer behaviour and adoption of sustainable electronic products, there is no research article which solely focuses on implementing Fuzzy analytical hierarchical process (AHP) approach to rank the barriers faced by consumers for adoption of sustainable electronic products. It has been concluded that high price of sustainable electronic products is the most critical barrier in adoption of sustainable consumer behaviour. Moreover, the relative ranking obtained with the help of Fuzzy AHP can be used by policymakers and organisations to promote and implement sustainability in consumer behaviour.

The purpose of this paper is to propose a holistic approach for supplier evaluation and purchasing order allocation among the ranked suppliers who meet acceptable levels of economic, environmental and social measures.

A mixed research method of case study and analytical approach is adopted in this research. A fuzzy analytical hierarchical process (FAHP) is applied for ranking of suppliers. Supplier ranks are validated using judgements from multiple decision makers. Purchasing order allocation among the ranked suppliers is determined using cost minimization subject to multiple criteria of economic, environmental and social conditions. A cement manufacturing case example demonstrates and validates the proposed approach.

The research shows that both economic and environmental considerations are significant when suppliers are evaluated for sustainable procurement within the best practice of supply management process. Ranking of suppliers, based on experts’ opinions, indicates varying degrees of importance for each criterion. Adoption of sustainable procurement criteria for evaluating supplier in a cement manufacturing organization is explained by three organizational theories including resource-based, institutional and dynamic capabilities theories. Preferred suppliers from FAHP method are confirmed by judgements from multiple decision-makers. The analysis reveals that purchasing order allocation is different when suppliers are evaluated based on their relative importance and overall ranking.

Currently, individual performance measures and decision-makers are selected from a limited set. The purchasing allocation among ranked suppliers, subjected to cost minimization, incorporates environmental objective of acceptable carbon dioxide emission and social perspective of health and safety of workers, and provides a new approach for dual supplier evaluation and purchasing allocation problem in cement industry. Adopting the proposed supplier evaluation and order allocation approach in practice needs to be guided by the operational principles and an overall methodology which is appropriate for the specific industry with sustainability objectives.

This research enables decision-makers to incorporate sustainability analysis in the supplier evaluation as the basis for best practice with an industry-friendly holistic approach. Using organizational theories, the research re-enforces the importance of not only the energy consumption and environmental management systems of environmental dimension as driving forces/factors from Institutional theory perspective, but also pollution controls and prevention as purchasing capabilities from resource-based theory perspective. The proposed approach is expected to motivate decision-makers to consider sustainable perspectives in supplier evaluation and order allocation processes in a global supply chain and can become a benchmarking tool.

Suppliers’ information on health and safety of their truck drivers are used in order allocation, thus emphasizing the importance of social dimension and encouraging better conditions and benchmarking for delivery drivers.

This paper extends the contribution to the literature by providing guidelines for managers to set strategies, benchmarks and policies within broader sustainable supply chain practices and demonstrates the applicability of the approach using a cement-manufacturing scenario in an emerging economy.

The study aims to facilitate the medical tourists visiting emerging countries for various kinds of ailments by ranking the possible destinations to avail medical treatments.

A Fuzzy Analytical Hierarchical Process (FAHP) with a mixed-method approach is applied to analyze data collected from patients and substantiate it with medical tour operators in India to gain managerial insights on the choice-making patterns of the patients.

India is a preferred emerging market location due to the low cost and high medical staff quality. India offers value for money, whereas Singapore and Thailand are preferred destinations for quality and technology.

The study will facilitate the emerging markets' governments, hospitals and medical tourists to understand the importance of various determinants responsible for availing medical treatment outside their country.

The study recommends that cost and quality care are the patients' prime focus; government policies must provide clear guidelines on what the hospitals and country environment can offer and accordingly align the marketing strategies.

This study is the first attempt to rank various factors affecting medical tourism using the FAHP approach.

The study aims to assess and prioritise the enablers of manufacturing flexibility by evaluating the degree of environmental uncertainty and manufacturing flexibility in an uncertain environment.

The study proposes a methodological approach based on fuzzy quality function deployment (FQFD), fuzzy analytical hierarchical process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) to assess and prioritise enablers of manufacturing flexibility in an uncertain environment.

The study proposes a methodological approach that can facilitate firms to concentrate on preferred enablers and assist them in formulating a strategy to develop manufacturing flexibility. The empirical case study analysis of an Indian auto-air conditioning manufacturing firm was done to illustrate the effectiveness, flexibility and feasibility of the proposed approach.

The proposed approach is limited to manufacturing flexibility. This study does not consider inter-dependencies among environmental uncertainties.

The proposed methodological approach can assist practitioners in the identification and development of the preferred enablers to improve manufacturing flexibility. Thus, practitioners can invest strategically in the right resources to improve manufacturing flexibility.

The study proposes and validates a methodological approach that simultaneously addresses drivers and enablers of manufacturing flexibility; therefore, it aims to fill the gaps of earlier studies that have majorly studied flexibility concept in an isolated way.

The purpose of current analytical work is to identify the critical barriers in social isolation in India amid Coronavirus infection disease (COVID) outbreak using the fuzzy-analytical hierarchical process (AHP) method.

The conventional AHP is insufficient for tackling the vague nature of linguistic assessment. Fuzzy AHP had been developed to resolve the hierarchical fuzzy problems, avoiding its risks on performance. In AHP, all comparisons are not included; thus, to find the priority of one decision variable over other, triangular fuzzy numbers are used.

A total of eight critical barriers in social distancing in India during COVID-19 have been compared and ranked. Dense population has emerged as the most culpable barrier in social isolation in India amid COVID outbreak followed by compulsion for pecuniary earning and general incautiousness. A total of eight critical barriers in social distancing in India during COVID-19 in four categories (societal barriers, insufficient facilitation barriers, growth-related barriers and population related barriers) have been compared and ranked.

On the basis of the numeral values, “growth-related barriers” attained top position followed by “population-related barriers” and “insufficient facilitation barriers.” The current work has explored the possible factors which can become key game changers to control the pace of spread of the pandemic.

The study aims to analyze the barriers in the adoption of Industry 4.0 (I4.0) practices in terms of prioritization, cluster formation and clustering of empirical responses, and then narrowing them with identification of the most influential barriers for further managerial implications in the adoption of I4.0 practices by developing an enhanced understanding of I4.0.

For the survey-based empirical research, barriers to I.40 are synthesized from the review of relevant literature and further discussions with academician and industry persons. Three widely acclaimed statistical techniques, viz. principal component analysis (PCA), fuzzy analytical hierarchical process (fuzzy AHP) and K-means clustering are applied.

The novel integrated approach shows that lack of transparent cost-benefit analysis with clear comprehension about benefits is the major barrier for the adoption of I4.0, followed by “IT infrastructure,” “Missing standards,” “Lack of properly skilled manpower,” “Fitness of present machines/equipment in the new regime” and “Concern to data security” which are other prominent barriers in adoption of I4.0 practices. The availability of funds, transparent cost-benefit analysis and clear comprehension about benefits will motivate the business owners to adopt it, overcoming the other barriers.

The present study brings out the new fundamental insights from the barriers to I4.0. The new insights developed here will be helpful for managers and policymakers to understand the concept and barriers hindering its smooth implementation. The factors identified are the major thrust areas for a manager to focus on for the smooth implementation of I4.0 practices. The removal of these barriers will act as a booster in the way of implementing I4.0. Real-world testing of findings is not available yet, and this will be the new direction for further research.

The new production paradigm is highly complex and evolving. The study will act as a handy tool for the implementing manager for what to push first and what to push later while implementing the I4.0 practices. It will also empower a manager to assess the implementation capabilities of the industry in advance.

PCA, fuzzy AHP and K means are deployed for identifying the significant barriers to I4.0 first time. The paper is the result of the original conceptual work of integrating the three techniques in the domain of prioritizing and narrowing the barriers from 16 to 6.