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Understanding the Voice of Customers Using Artificial Neural Networks: A Study of Food Aggregators in the Cachar District of Assam

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Computational Intelligence in Communications and Business Analytics (CICBA 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1579))

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Abstract

The evolution of online food delivery system started in India in the late 2000’s and since then many Food Aggregators have come up with a variety of prospects for the customers. This process of Business to Customer services had found itself to be very popular especially in the last few years and after the COVID 19 attack the business had flourished to a large extent. People do not prefer to come out of their abodes and try to procure the eatables by maintaining proper social distancing. There have been a number of local Food Aggregators that have emerged in the Cachar District only recently and post 2020 especially in the lockdown phase they have accelerated their operations in the Valley by joining hands with a number of food outlets. These local entrepreneurial efforts are still in the growth phase and are trying to meet the customer demands to enhance their satisfaction level. Speaking of enhancing the satisfaction of the customers, there are many factors that work before meeting their overall satisfaction and these factors if are considered carefully would not only increase the customer loyalty towards the respective. Purposive Sampling was used in this study to get the responses from the online food buyers. It used Artificial Neural Networks to understand the pattern of the buying behavior of customers in this area and tried to create a model that would enhance the understanding of the Food Aggregators in regards to the buying frequency of the customers and take steps accordingly.

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Authors and Affiliations

  1. Faculty of Commerce and Management, Vishwakarma University, Pune, India

    Dhritiman Chanda

  2. Department of Business Administration, University of Science and Technology, Meghalaya, Baridua, India

    Nilanjan Mazumder

  3. Department of Business Administration, Assam University, Silchar, Silchar, India

    D. Ghosh

  4. CITI Bank, Chennai, India

    Deepjyoti Dutta

Authors
  1. Dhritiman Chanda
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  2. Nilanjan Mazumder
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  3. D. Ghosh
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  4. Deepjyoti Dutta
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Corresponding author

Correspondence to Dhritiman Chanda .

Editor information

Editors and Affiliations

  1. Assam University, Silchar, India

    Somnath Mukhopadhyay

  2. Assam University, Silchar, India

    Sunita Sarkar

  3. Visva-Bharati University, Santiniketan, West Bengal, India

    Paramartha Dutta

  4. University of Kalyani, Nadia, India

    Jyotsna Kumar Mandal

  5. Assam University, Silchar, India

    Sudipta Roy

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Chanda, D., Mazumder, N., Ghosh, D., Dutta, D. (2022). Understanding the Voice of Customers Using Artificial Neural Networks: A Study of Food Aggregators in the Cachar District of Assam. In: Mukhopadhyay, S., Sarkar, S., Dutta, P., Mandal, J.K., Roy, S. (eds) Computational Intelligence in Communications and Business Analytics. CICBA 2022. Communications in Computer and Information Science, vol 1579. Springer, Cham. https://doi.org/10.1007/978-3-031-10766-5_29

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  • DOI: https://doi.org/10.1007/978-3-031-10766-5_29

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  • Online ISBN: 978-3-031-10766-5

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