Debadrita Panda

Work place: MAKAUT, India



Research Interests:


Debadrita Panda is an Assistant Professor of Business Analytics and Statistics at School of Management Sciences, MAKAUT (Govt. of WB), India having more than 4.5 years of academic experience and 2 years of industry experience. She has completed her graduation in Computer Science and Engineering and MBA from IISWBM with Business Analytics and System specialization. She had served companies like IMRB and had associated with JIS University, Techno India and IISWBM. She has keen interest in BoP segment, quantitative techniques, neuromarketing domain.


Author Articles
BoPMLPIP: Application of Classification Techniques to Explore the Impact of PIP among BoPs

By Debadrita Panda Sabyasachi Mukhopadhyay Rajarshi Saha

DOI:, Pub. Date: 8 Dec. 2022

This study tries to gain insight into the effect of demographic and psychological variables on the Bottom of the Pyramid (BoP) consumers for making Packaging Influenced Purchase (PIP) decisions by focusing on two specific consumer behaviour theories - compensatory consumption and consumers’ resistance. Being the product's face, packaging contributes heavily to the above mentioned two streams of consumption behaviour. A collection of ten demographic variables and four psychological variables have been administered on a sample of 1400 BoP consumers to explore their effect behind making PIP of selected FMCG products. Various classification techniques have been deployed to capture the impact of these variables. This experimental research design revealed that both demographic and psychological variables affect the PIP. The comparison between urban and rural BoPs potentially comes with the guidelines for practical marketing implications.

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BoPCOVIPIP: Capturing the Dynamics of Marketing Mix Among Bottom of Pyramid Consumers during COVID-19

By Debadrita Panda Sabyasachi Mukhopadhyay Rajarshi Saha Prasanta K. Panigrahi

DOI:, Pub. Date: 8 Aug. 2022

The behaviour of consumers mostly follows the guidelines derived from marketing theories and models. But under some unavoidable circumstances, the consumers show a complete deviation compared to their existing consumption pattern, purchase behaviour, decision-making and so on. Under similar circumstances, this study aims to capture both urban and rural Bottom of the Pyramid (BoP) consumers’ perceptions of various marketing mixes during the COVID-19 pandemic situation. With a sample size of 378 and 282, the perception towards different marketing mixes has been captured for Pre-COVID and During-COVID periods, respectively. The adopted quantitative analysis indicates a difference in perception towards marketing mix During COVID compared to Pre-COVID. Moreover, the selection of West Bengal, India, as an area of research fulfills the BoP literature’s existing prominent research gap. This study also comes with the potential to assist marketers and the Fast-Moving Consumer Goods (FMCG) industry in framing strategies to target BoP consumers.

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Multi Criteria Decision Making based Approach to Assist Marketers for Targeting BoPs Regarding Packaging Influenced Purchase during Covid-19

By Debadrita Panda Sabyasachi Mukhopadhyay Amit Kumar Bachhar Moumita Roy

DOI:, Pub. Date: 8 Jun. 2022

This study has a novel approach to capture the attitude of Bottom of the Pyramid (BoP) consumers towards Packaging Influenced Purchase (PIP) during the Covid-19 crisis. Over the years, BoPs consumers have established themselves as an emerging market with ample growth and opportunities. The authors suggested a Multiple-Criteria Decision-Making (MCDM) based framework to assist marketers in targeting both urban and rural BoP consumers regarding PIP. Packaging elements and influence of family, extended family, peers have been included in the framework for gaining in-depth understanding. With a sample size of 100 from West Bengal, this focus group-based study can fulfil the BoP literature’s existing prominent research gap. Results indicate the difference in attitude for urban and rural BoPs towards PIP during this crisis. The fusion of MCDM based approach and relevant machine learning-based technique aims to assist marketers in identifying, formulating, and redefining an action plan.

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Other Articles