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Evaluating the key factors affecting productivity in the manufacturing sector: a hybrid decision-making framework with evidence from north of Iran

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Zarepour, Mahdi, Hojat Shemami, Niloufar and Avakh Darestani, Soroush (2025) Evaluating the key factors affecting productivity in the manufacturing sector: a hybrid decision-making framework with evidence from north of Iran. Management of Environmental Quality: An International Journal. ISSN 1477-7835

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Abstract

Purpose
In today’s world, one of the most important factors of the country’s economic development is improving the productivity of manufacturing industries. Identifying factors affecting the productivity of manufacturing industries and prioritizing them is effective in promoting productivity and can promise to achieve organizational and national productivity. The purpose of this research is to identify the effective factors in improving the productivity of manufacturing industries.

Design/methodology/approach
The present research method is a descriptive-survey and the data collection tool is a questionnaire. In the first step, according to the studies conducted by reviewing the research literature using a comparative method, library studies and asking opinions from experts, potential factors affecting the productivity of industries were identified and analyzed. Then the factors were divided into four main categories, and the selected factors were determined by using a questionnaire and combining the opinions of experts. Then, the importance of the selected factors was determined using the Fuzzy SWARA decision-making method, and the final ranking of the selected industries of the province was done using the MOORA method.

Findings
The results of this research showed that the factors “profit margin,” “The ratio of sales on current assets” and “The ratio of exports to sales,” respectively, have the highest importance, among the pharmaceutical and household appliances industries of the province that are present in the stock exchange, Caspian Tamin Company has the highest productivity with a productivity score of 0.437.

Originality/value
Looking at the background of the research, no comprehensive research has been conducted to identify indicators that affect productivity in the manufacturing industry, and only a few studies have evaluated productivity indicators for small, specialized industries. Therefore, in the current research, considering the uncertainty in experts' opinions, a hybrid model is presented to identify and comprehensively evaluate the productivity indicators of manufacturing industries using the decision-making method of Fuzzy SWARA and MOORA, which is unique in its turn.

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