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This study provides a systematic review on performance measurement of supply chains from a financial perspective.

This study systematically reviews the financial performance measures of supply chains. More specifically, this research reviews a total of 100 papers published in more than 50 peer-reviewed journals. The reviewed papers are categorized into three major areas of engineering, business and management. Additionally, the papers are investigated based on country, journal frequency, applied methods, publication date and research type (application or developmental).

According to the obtained results, cost, return on assets (ROA), sales, asset turnover, return on investment (ROI), market share, inventory turnover, profit margin, revenue growth, economic value added (EVA) and cash-to-cash cycle are the most common metrics of financial performance measurement. Next, a framework is developed based on different categories of performance measurement and decision levels of the supply chain. Finally, some research directions are suggested to be further investigated by other scholars.

Although available studies on supply chain performance measurement are very vast and comprehensive, the majority of the studies have neglected to highlight the importance of financial measures. In other words, with the advent of nonfinancial measures, however, the majority of supply chain managers still prefer to consider financial issues in their performance assessment process.

The purpose of this paper is to select the best maintenance policy for different types of equipment of a manufacturer integrating the fuzzy analytic hierarchy process (FAHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) models.

The decision hierarchy of this research includes three levels. The first level aims to choose the best maintenance policy for different types of equipment of an acid manufacturer. These equipment pieces include molten sulfur ponds, boiler, absorption tower, cooling towers, converter, heat exchanger and sulfur fuel furnace. The second level includes decision criteria of added-value, risk level and the cost. Lastly, the third level comprises time-based maintenance (TBM), corrective maintenance (CM), shutdown maintenance and condition-based maintenance (CBM) as four maintenance policies.

The best maintenance policy for different types of equipment of a manufacturer is the main finding of this research. Based on the obtained results, CBM policy is suggested for absorption tower, boiler, cooling tower and molten sulfur ponds, TBM policy is suggested for converters and heat exchanger and CM policy is suggested for a sulfur fuel furnace.

This research develops a novel model by integrating FAHP and an interval TOPSIS with concurrent consideration of added-value, risk level and cost to select the best maintenance policy. According to the highlights of the previous studies conducted on maintenance policy selection and related tools and techniques, an operative integrated approach to combine risk, added-value and cost with integrated fuzzy models is not developed yet. The majority of the previous studies have considered classic fuzzy approaches such as FAHP, FANP, Fuzzy TOPSIS, etc., which are not completely capable to reflect the decision makers’ viewpoints.

The purpose of this paper is to propose a framework to assess the agility of manufacturing companies.

Particularly, three supply chain logistic drivers (facility, transportation and inventory) along with three cross-functional drivers (information, sourcing and pricing) are selected as the main sets to classify all required activities of agility. In addition, supply chain contracts, as an important indicator of supply chain agility, is also considered to categorize the activities. These activities are ranked using an (AHP) and then categorized based on the major perspectives of agility. Finally, using a cycle view of supply chain, the developed activities are categorized as the major policies of supply chain’s echelons.

This study developed a framework to evaluate the agility of manufacturing companies. Operational activities of agile supply chain strategy (ASCS) in addition to supply chain contracts are determined and categorized with regard to supply chain drivers.

This study contributes to recognizing, ranking and classifying the operational activities of ASCS with regard to logistics and cross-functional drivers of supply chain. In addition, this study considers the supply chain contracts in conjunction with supply chain drivers. From the theoretic and methodological features, to the best of authors’ knowledge, this study contributes to offer new insights to this area as no similar research has been conducted before.