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Assessing a measure of sustainable supply chain management (SSCM) performance is currently a key challenge. The literature on SSCM is very limited and performance measures need to have a systematic framework. The recently developed balanced scorecard (BSC) is a measurement system that requires a balanced set of financial and non-financial measures. The purpose of this paper is to evaluate the SSCM performance based on four aspects i.e. sustainability, internal operations, learning and growth, and stakeholder.

This paper developed a BSC hierarchical network for SSCM in a close-loop hierarchical structure. A generalized quantitative evaluation model based on the Fuzzy Delphi Method (FDM) and Analytical Network Process (ANP) were then used to consider both the interdependence among measures and the fuzziness of subjective measures in SSCM.

The results of this study indicate that the top-ranking aspect to consider is that of stakeholders, and the top five criteria are green design, corporate sustainability, strategic planning for environmental management, supplier cost-saving initiatives and market share.

The main contributions of this study are twofold. First, this paper provides valuable support for supply chain stakeholders regarding the nature of network hierarchical relations with qualitative and quantitative scales. Second, this paper improves practical performance and enhances management effectiveness for SSCM.

This paper first aims to examine how business process change decisions (BPCDs) were implemented in a government organisation bound by tightly coupled temporal constraints (TTCs). Second, it focuses on how to achieve optimal and efficient BPCDs that require tight compliance with regulators’ temporal constraints. Finally, it formulates a rigorous framework that can facilitate the execution of optimal BPCDs with maximum efficiency and minimal effort, time and cost.

Decision-making biases by individuals or groups in organisations can impede optimal BPC implementation; to demonstrate this, a case study is investigated and the formulated framework is applied to tackle these failings.

The case study analysis shows 76 per cent of the BPCDs implemented were inefficient, mostly because of poor decisions, and these resulted in negative ripple effects. In response, the newly developed hierarchical change management structure (HCMS) framework was used to empower organisations to execute high-velocity BPCDs, enabling them to handle any temporal constraints imposed by regulators or other exogenous factors. The HCMS framework was found to be highly effective, scoring an average improvement of more than 100 per cent when measured using decision quality dimensions. This paper would be of value for business executives and strategic decision makers engaging with BPC.

The HCMS framework has been applied in a single case study as a proof of concept. Future research could extend its application to broader domains that have multi-attribute structures and environments. The evaluation processes of the proposed framework are based on subjective metrics. Causal links from the framework to business process metrics will provide a more complete performance picture.

The outcome of this research assists in formulating a systematic BPCD framework that is otherwise unavailable. The practical use of the proposed framework would potentially impact on quality outcomes for organisations. The model is derived from decision trees and analytical hierarchical processes and is tailored to address this problematic area. The proposed HCMS framework would help organisations to execute efficient BPCDs with minimal time, effort and cost. The HCMS framework contributes to the academic literature on BPCD that leverages diverse stakeholders to engage in BPC initiatives.

The research presents a novel framework –HCMS – that provides a platform for organisations to easily determine and solve hierarchical decision structure problems, thereby allowing them to efficiently automate and institutionalise optimal BPCDs.

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.

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.

Technology transfer becoming an important area especially in developing and less developed countries. The purpose of this paper is to address issue of supply chains’ benchmarking based upon their capability to mange technology transfer critical barriers mitigation efforts toward making technology transfer process implementation successful.

The present paper is based on two research stages. Initially, extensive literature review has been made to identify critical barriers. In total, 20 technology transfer critical barriers have been identified from literature review and categorized in to six criteria. In second stage, analytics hierarchy process has been utilized to rank the critical barriers of technology transfer in supply chain and provide a benchmarking framework.

Political barriers (PB) have been analyzed most significant criteria of critical barriers to technology transfer followed by socio-cultural barriers (SO) and economic barriers (EB). “Political instability,” “Difficulty in transfer and diffusion,” “Too expensive,” “Inappropriate/incompetent technology and resource wastage in technologies imported,” “Inactive role of SC members and resistance to change” and “Management attitude” have been found most hindering barrier in their respective category/criterion of technology transfer barriers.

Scope of the present study has been limited to propose framework to benchmark supply chains by analyzing 20 critical barriers of technology transfer grouped in to six dimensions using analytical hierarchy approach based on “ratings provided by experts,” which may be biased.

Benchmarking process has been proposed to calculate value of total of overall weights to a particular supply chain named as “Technology Transfer Barriers Mitigation Index (TTBMI)” useful to present capability of supply chains to manage technology transfer barriers by a single numeric value. From “provider” developed county’s view point, present benchmarking framework may be further applied to compare developing countries’ ability to absorb and diffuse new technology.

Benchmarking procedure has been dealt with using well-established methodology- analytical hierarchy process toward providing single numeric value index (TTBMI) indicating ability of supply chains to manage/mitigate technology transfer barriers.

The Analytical Hierarchy Process (AHP), a multicriteria decision support system that has been successfully applied to numerous decision-making situations, has been applied to patient assessment. The AHP was used with Timeslips™, a group storytelling program that encourages creative expression among dementia patients, to determine the optimal scale for pre and post assessment among the nine most common agitation and anxiety scales. The AHP used the six criteria identified by qualitative assessment of the nine scales: (1) validity/reliability, (2) observation period, (3) training required, (4) time to administer, (5) most appropriate administrator, and (6) accessibility/cost. The AHP indicated that the Overt Agitation & Anxiety Scale was optimal for use with Timeslips; the process and results are discussed.

The purpose of this paper is to demonstrate the use of two general purpose decision‐making techniques in selecting the most appropriate maintenance strategy for organizations with critical production requirements.

The Analytical Hierarchical Process (AHP) and the Analytical Network Process (ANP) are used for the selection of the most appropriate maintenance strategy in a local newspaper printing facility in Turkey.

The two methods were shown to be effective in choosing a strategy for maintaining the printing machines. The two methods resulted in almost the same results. Both methods take into account the specific requirements of the organization through its own available expertise.

The techniques demonstrated in this paper can be used by all types of organizations for selecting and adopting maintenance strategies that have higher impact on maintenance performance and hence overall business productivity. The two methods are explained in a step‐by‐step approach for easier adaptation by practitioners in all types of organizations.

The value of the paper is in applying AHP and ANP decision‐making methodologies in maintenance strategy selection. These two methods are not very common in the area of maintenance, and hence add to the pool of techniques utilized in selecting maintenance strategies.

Decreasing sources of fossil fuels has caused an increase in importance of the renewable energy resources and systems that directly utilize renewable energy are even more important. The purpose of the paper is to compare the most common solar cooling technologies against the most important requirements.

A multi-criteria decision methodology, analytical hierarchical process, has been used to prioritize these technologies with respect to each other.

The findings of this study are the priorities of selected solar cooling concepts against performance affecting criteria. The solar vapour adsorption cooling system has been found to be the optimum solar cooling concept with practically the highest performance number compared with the other cooling systems.

This study can be used in the future development of solar cooling technologies to benefit from the best collective features of the specific technologies.

The use of Analytical Hierarchy Process (AHP) is an effective way to deal with qualitative decision areas of operations management. Four published applications of AHP are briefly reviewed in forecasting, supplier selection, facility location, and choice of technology. Furthermore, four more potential applications are suggested in other areas of operations management, including product design, plant layout, maintenance frequency selection, and choice of logistic carrier. In addition, suggestions for other areas of research are discussed.

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.