C. Deep Prakash
  •  deep.prakash@spjimr.org

C. Deep Prakash

Assistant Professor, Information Management & Analytics

Prof. C. Deep Prakash has a background in Information Systems and 1.5 years of R&D experience in the industry. He has completed his Ph.D. in Information Systems at the Indian Institute of Management, Ahmedabad, focusing on enhancing social media strategies for stakeholders in the Indian sports ecosystem, including organisations, influencers, sports clubs, and athletes.

Deep’s research expertly merges marketing theories and data analytics to tackle sports marketing challenges, exploring areas like social media strategies, user engagement, consumer preferences, and firm performance. His work has received over 140 citations and extends into how national culture affects social media use and the development of machine learning models to predict user engagement. He has contributed to reputed journals such as the International Journal of Information Management and the Journal of Retailing and Consumer Services. He has also been recognised at international and national conferences.

Before joining SPJIMR, he was an Assistant Systems Engineer at Tata Consultancy Services.

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EDUCATION

Indian Institute of Management, Ahmedabad  

Ph.D. Focus: Information Systems

Dayalbagh Educational Institute, Agra

B.Tech in Electrical Engineering with specialisation in Computer Science

  • RESEARCH INTERESTS

    User Engagement

    Sports Marketing

    Text Mining

  • SELECTED PUBLICATIONS (2023 - 2018)

    Deep Prakash, C., & Majumdar, A. (2023). Predicting sports fans’ engagement with culturally aligned social media content: A language expectancy perspective. Journal of Retailing and Consumer Services, 75 (November 2023), 103457. https://doi.org/10.1016/j.jretconser.2023.103457 (ABDC A).

    Deep Prakash, C., & Majumdar, A. (2021). Analyzing the role of national culture on content creation and user engagement on Twitter: The case of Indian Premier League cricket franchises. International Journal of Information Management, 57 (October 2020), 102268. https://doi.org/10.1016/j.ijinfomgt.2020.102268 (ABDC A*).

    Link to Google Scholar

  • CONFERENCES

    Deep Prakash, C., & Verma, S. (2023, May 5-6). Using fans’ motivational factors to boost social media engagement: Examining how sports clubs can prioritize social identity creation [Conference Presentation]. Vipanan (Marketing 5.0) International Marketing Conference 2023, Indian Institute of Management, Visakhapatnam, Andhra Pradesh, India.

    Deep Prakash, C., & Verma, S. (2022, June 1-4). Strategizing content generation for enhanced social media engagement: Empirical evidence from Indian Premier League 2021 tweets [Conference Presentation]. North American Society for Sport Management (NASSM) 2022 conference, Atlanta, Georgia, USA.

    Deep Prakash, C., & Verma, S. (2021, November 19). Understanding the effect of tweeter’s geo-location on user engagement: An empirical study of Indian Premier League tweets [Virtual Conference Presentation]. European Association of Sport Management (EASM) 2021: Festival of sport management research and practise conference, Nicolaus Copernicus University, Toran, Poland.

    Deep Prakash, C., & Waychal, N. (2019, December 15-18). DEEP-NIX (Neo-Integrated X) Model: Decision Trees with Bias Correction Validated through 2- pronged Regression for Prediction Interval [Conference Presentation]. 52nd Annual Convention of Operational Research Society of India and International Conference, Indian Institute of Management, Ahmedabad, Gujarat, India

  • PERIODICALS

    Majumdar, A., & Deep Prakash C. (2021). Social media engagement in Indian Premier League: Is cultural alignment valuable? ETBrandEquity. Link: https://brandequity.economictimes.indiatimes.com/news/digital/social-media-engagement-in-indian-premier-league-is-cultural-alignment-valuable/86669319

  • WORKING PAPERS

    From stadiums to tweets: Redefining fan typology in an online sporting realm.

    In-Sync or Out of Bounds: Demographic Homophily and its Significance in Sports-driven Social Media Engagement.

    A comprehensive framework to examine the impact of Information System resources on firm performance: A Resource Based View of the firm.

    Unveiling the heart of a social movement: Analyzing the drivers of user engagement on social media for #BlackLivesMatter tweets.

  • TEACHING INTEREST

    IT Strategy

    Data Visualization

    Text Analytics and Natural Language Processing

    Business Intelligence & Analytics

    Sports Marketing & Analytics

  • AWARDS & HONOURS

    Alberto Madella Scholarship for attending the 11th European Association of Sport Management (EASM) summer school on International Sports Marketing: Value-creation through engagement, 12-14 May 2021. Awarded an ECTS Grade 1 (Excellent) in the final examination, demonstrating a high level of competency.

    Acknowledged as an exceptional learning enabled during the ILP at Tata Consultancy Services Gandhinagar, Gujarat, 2017, receiving both a Certificate of Appreciation and the ILP Kudos Award for outstanding contributions to the organization.

  • PROFESSIONAL POSITIONS

    Tata Consultancy Services (Jan 2017 – May 2018)

    Designation: Assistant Systems Engineer

  • REVIEWER EXPERIENCE

    Ad Hoc Reviewer for distinguished academic journals, including SN Business & Economics (ISSN: 2662-9399), Journal of Sports Analytics (ISSN: 2215-0218) and Vikalpa: The Journal of Decision Makers (ISSN: 0256-0909).

    Nominated by a Conference Track Chair for the honor of reviewing submissions at prestigious conferences, including the India Strategy Conference 2023 (ISC2023), IEEE International Symposium on Technology and Society (ISTAS23) and 6th International Conference on Information Systems and Management Science (ISMS2023).

  • PROFESSIONAL MEMBERSHIPS

    North American Association of Sport Management

  • LICENSURES AND CERTIFICATIONS

    Google Data Analytics Professional Certificate (Coursera)

    Foundation Sports Marketing Program (Rajasthan Royals & Deakin University Co-Branded Certificate)

    Machine Learning (Coursera)

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