A multi-criteria framework for comparing dividend pay capabilities: Evidence from Indian FMCG and consumer durable sector

  • Sanjib Biswas Department of Management Studies, National Institute of Technology, India https://orcid.org/0000-0002-9243-2403
  • Gautam Bandyopadhyay Department of Management Studies, National Institute of Technology, India
  • Jayanta Nath Mukhopadhyaya Finance Area, Army Institute of Management, India
Keywords: Dividend payment, investment decision making, LOPCOW, EDAS, Borda count, Copeland method


In this paper, we aim to carry out a comparative analysis of the Dividend Pay Capabilities (DPC) of the selected organizations belonging to the Fast Moving Consumer Goods (FMCG) and Consumer Durables (CD) sectors listed in BSE, India during the period FY 2013-14 to FY 2019-20. We select top 25 companies from FMCG group and top 5 firms from the CD sector on the basis of average market capitalization. For comparison purpose, we have considered six aspects (grounded on the extant theories on dividend policy) such as ownership, size, profitability, growth, liquidity and risk. We have used a new integrated Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) and Evaluation based on Distance from Average Solutions (EDAS) framework for our analysis. The result shows that companies do not show consistent performance over the years. We further have noticed that FMCG organizations show comparatively better capabilities that CD firms vis-à-vis dividend payment. Since, there are considerable variations in the ranking, we apply aggregation methods like Borda Count (BC), Copeland method (CM) and Simple additive weighting (SAW). We use two other popular Multi-Criteria Decision Making (MCDM) methods like MABAC and COPRAS for comparison with our framework to ascertain the reliability of our result.


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How to Cite
Biswas, S., Bandyopadhyay, G., & Mukhopadhyaya, J. N. (2022). A multi-criteria framework for comparing dividend pay capabilities: Evidence from Indian FMCG and consumer durable sector. Decision Making: Applications in Management and Engineering, 5(2), 140-175. https://doi.org/10.31181/dmame0306102022b