IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v196y2025ics0148296325002693.html

Growth hacking capability: Conceptualization, survey instrument development, and empirical study of its impact on firm performance

Author

Listed:
  • Gupta, Manjul
  • Ghafoori, Arman
  • Kim, Eunyoung
  • Merhi, Mohammad I.
  • Filieri, Raffaele

Abstract

Growth hacking has emerged as a novel approach for organizations. This trend is accompanied by a rising acknowledgment among business academics and practitioners of growth hacking’s ability to achieve rapid consumer growth and enhanced performance. Despite its frequent mention in contemporary business and marketing dialogues, to the best of our knowledge, there are no measurement instruments to quantitatively assess a firm’s growth hacking capability. This study not only develops a survey instrument to measure growth hacking capability but also proposes and empirically validates the relationship between growth hacking capability and firm performance.

Suggested Citation

  • Gupta, Manjul & Ghafoori, Arman & Kim, Eunyoung & Merhi, Mohammad I. & Filieri, Raffaele, 2025. "Growth hacking capability: Conceptualization, survey instrument development, and empirical study of its impact on firm performance," Journal of Business Research, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:jbrese:v:196:y:2025:i:c:s0148296325002693
    DOI: 10.1016/j.jbusres.2025.115446
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296325002693
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2025.115446?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Bazi, Saleh & Filieri, Raffaele & Gorton, Matthew, 2023. "Social media content aesthetic quality and customer engagement: The mediating role of entertainment and impacts on brand love and loyalty," Journal of Business Research, Elsevier, vol. 160(C).
    2. Ryoo, Yuhosua & Jeon, Yongwoog Andy & Kim, WooJin, 2024. "The blame shift: Robot service failures hold service firms more accountable," Journal of Business Research, Elsevier, vol. 171(C).
    3. Nusrat, Farhana & Huang, Yanliu, 2024. "Feeling rewarded and entitled to be served: Understanding the influence of self- versus regular checkout on customer loyalty," Journal of Business Research, Elsevier, vol. 170(C).
    4. Kannan, P.K. & Li, Hongshuang “Alice”, 2017. "Digital marketing: A framework, review and research agenda," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 22-45.
    5. Hasan, Rajibul & Shams, Riad & Rahman, Mizan, 2021. "Consumer trust and perceived risk for voice-controlled artificial intelligence: The case of Siri," Journal of Business Research, Elsevier, vol. 131(C), pages 591-597.
    6. Olabode, Oluwaseun E. & Boso, Nathaniel & Hultman, Magnus & Leonidou, Constantinos N., 2022. "Big data analytics capability and market performance: The roles of disruptive business models and competitive intensity," Journal of Business Research, Elsevier, vol. 139(C), pages 1218-1230.
    7. Shamim, Saqib & Zeng, Jing & Khan, Zaheer & Zia, Najam Ul, 2020. "Big data analytics capability and decision making performance in emerging market firms: The role of contractual and relational governance mechanisms," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    8. Liu, Xia & Shin, Hyunju & Burns, Alvin C., 2021. "Examining the impact of luxury brand's social media marketing on customer engagement​: Using big data analytics and natural language processing," Journal of Business Research, Elsevier, vol. 125(C), pages 815-826.
    9. Jarvis, Cheryl Burke & MacKenzie, Scott B & Podsakoff, Philip M, 2003. "A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(2), pages 199-218, September.
    10. Erevelles, Sunil & Fukawa, Nobuyuki & Swayne, Linda, 2016. "Big Data consumer analytics and the transformation of marketing," Journal of Business Research, Elsevier, vol. 69(2), pages 897-904.
    11. Dean A. Shepherd & Marc Gruber, 2021. "The Lean Startup Framework: Closing the Academic–Practitioner Divide," Entrepreneurship Theory and Practice, , vol. 45(5), pages 967-998, September.
    12. Bargoni, Augusto & Santoro, Gabriele & Messeni Petruzzelli, Antonio & Ferraris, Alberto, 2024. "Growth hacking: A critical review to clarify its meaning and guide its practical application," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    13. Ghafoori, Arman & Gupta, Manjul & Merhi, Mohammad I. & Gupta, Samrat & Shore, Adam P., 2024. "Toward the role of organizational culture in data-driven digital transformation," International Journal of Production Economics, Elsevier, vol. 271(C).
    14. Sanasi, Silvia, 2025. "Structuring experimentation: Implementing Growth Hacking in new ventures," Journal of Business Research, Elsevier, vol. 188(C).
    15. Christian Homburg & Dominik M. Wielgos, 2022. "The value relevance of digital marketing capabilities to firm performance," Journal of the Academy of Marketing Science, Springer, vol. 50(4), pages 666-688, July.
    16. Elisabetta Raguseo & Claudio Vitari, 2018. "Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects," International Journal of Production Research, Taylor & Francis Journals, vol. 56(15), pages 5206-5221, August.
    17. Cacciolatti, Luca & Lee, Soo Hee, 2016. "Revisiting the relationship between marketing capabilities and firm performance: The moderating role of market orientation, marketing strategy and organisational power," Journal of Business Research, Elsevier, vol. 69(12), pages 5597-5610.
    18. Kuratko, Donald F. & Holt, Harrison L. & Neubert, Emily, 2020. "Blitzscaling: The good, the bad, and the ugly," Business Horizons, Elsevier, vol. 63(1), pages 109-119.
    19. Elia, Gianluca & Margherita, Alessandro & Passiante, Giuseppina, 2020. "Digital entrepreneurship ecosystem: How digital technologies and collective intelligence are reshaping the entrepreneurial process," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    20. Bargoni, Augusto & Smrčka, Luboš & Santoro, Gabriele & Ferraris, Alberto, 2024. "Highway to hell or paradise city? Exploring the role of growth hacking in learning from innovation failure," Technovation, Elsevier, vol. 131(C).
    21. Parra, Carlos M. & Gupta, Manjul & Cadden, Trevor, 2022. "Towards an understanding of remote work exhaustion: A study on the effects of individuals’ big five personality traits," Journal of Business Research, Elsevier, vol. 150(C), pages 653-662.
    22. Neil A. Morgan & Douglas W. Vorhies & Charlotte H. Mason, 2009. "Market orientation, marketing capabilities, and firm performance," Strategic Management Journal, Wiley Blackwell, vol. 30(8), pages 909-920, August.
    23. Ozkaya, H. Erkan & Droge, Cornelia & Hult, G. Tomas M. & Calantone, Roger & Ozkaya, Elif, 2015. "Market orientation, knowledge competence, and innovation," International Journal of Research in Marketing, Elsevier, vol. 32(3), pages 309-318.
    24. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    25. Ian Fillis & Ruth Rentschler, 2010. "The Role Of Creativity In Entrepreneurship," Journal of Enterprising Culture (JEC), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 49-81.
    26. Mikalef, Patrick & Boura, Maria & Lekakos, George & Krogstie, John, 2019. "Big data analytics and firm performance: Findings from a mixed-method approach," Journal of Business Research, Elsevier, vol. 98(C), pages 261-276.
    27. Sun, Yuan & Chen, Jin & Sundar, S. Shyam, 2024. "Chatbot ads with a human touch: A test of anthropomorphism, interactivity, and narrativity," Journal of Business Research, Elsevier, vol. 172(C).
    28. Wu, Chih-Wen, 2016. "The performance impact of social media in the chain store industry," Journal of Business Research, Elsevier, vol. 69(11), pages 5310-5316.
    29. Aydiner, Arafat Salih & Tatoglu, Ekrem & Bayraktar, Erkan & Zaim, Selim & Delen, Dursun, 2019. "Business analytics and firm performance: The mediating role of business process performance," Journal of Business Research, Elsevier, vol. 96(C), pages 228-237.
    30. Olavarrieta, Sergio & Friedmann, Roberto, 2008. "Market orientation, knowledge-related resources and firm performance," Journal of Business Research, Elsevier, vol. 61(6), pages 623-630, June.
    31. Bohnsack, René & Liesner, Meike Malena, 2019. "What the hack? A growth hacking taxonomy and practical applications for firms," Business Horizons, Elsevier, vol. 62(6), pages 799-818.
    32. Rizvanović, Belma & Zutshi, Aneesh & Grilo, Antonio & Nodehi, Tahereh, 2023. "Linking the potentials of extended digital marketing impact and start-up growth: Developing a macro-dynamic framework of start-up growth drivers supported by digital marketing," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    33. Manjul Gupta & Sushil Gupta, 2019. "Influence of National Cultures on Operations Management and Supply Chain Management Practices—A Research Agenda," Production and Operations Management, Production and Operations Management Society, vol. 28(11), pages 2681-2698, November.
    34. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    35. Irina Heimbach & Daniel Kostyra & Oliver Hinz, 2015. "Marketing Automation," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 57(2), pages 129-133, April.
    36. Heimbach, Irina & Kostyra, Daniel S. & Hinz, Oliver, 2015. "Catchword Marketing Automation," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77136, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    37. Krishen, Anjala S. & Dwivedi, Yogesh K. & Bindu, N. & Kumar, K. Satheesh, 2021. "A broad overview of interactive digital marketing: A bibliometric network analysis," Journal of Business Research, Elsevier, vol. 131(C), pages 183-195.
    38. Maurer, Joshua D. & Creek, Steven A. & Allison, Thomas H. & Bendickson, Joshua S. & Sahaym, Arvin, 2024. "Getting to know someone in ten seconds: Social role theory and perceived personality in entrepreneurial pitch videos," Journal of Business Research, Elsevier, vol. 174(C).
    39. Streukens, Sandra & Leroi-Werelds, Sara, 2016. "Bootstrapping and PLS-SEM: A step-by-step guide to get more out of your bootstrap results," European Management Journal, Elsevier, vol. 34(6), pages 618-632.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aftab, Junaid & Wei, Feng & Srivastava, Mohit & Abid, Nabila & Ishaq, Muhammad Ishtiaq, 2025. "Intermediating mechanisms and market conditions in big data knowledge management for enhanced market performance," Technological Forecasting and Social Change, Elsevier, vol. 219(C).
    2. Dignity Paradza & Olawande Daramola, 2021. "Business Intelligence and Business Value in Organisations: A Systematic Literature Review," Sustainability, MDPI, vol. 13(20), pages 1-27, October.
    3. Brewis, Claire & Dibb, Sally & Meadows, Maureen, 2023. "Leveraging big data for strategic marketing: A dynamic capabilities model for incumbent firms," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    4. Oesterreich, Thuy Duong & Anton, Eduard & Teuteberg, Frank & Dwivedi, Yogesh K, 2022. "The role of the social and technical factors in creating business value from big data analytics: A meta-analysis," Journal of Business Research, Elsevier, vol. 153(C), pages 128-149.
    5. Giordino, Daniele & Troise, Ciro & Bresciani, Stefano & Camilleri, Mark Anthony, 2025. "Growth hacking capability: Antecedents and performance implications in the context of SMEs," Journal of Business Research, Elsevier, vol. 192(C).
    6. Joshi, Yatish & Bodhi, Rahul & Chatterjee, Sheshadri & Mariani, Marcello, 2025. "The impact of growth hacking on firm performance under environmental turbulence: A moderated-mediation analysis," Journal of Business Research, Elsevier, vol. 191(C).
    7. Kumar, Vinod & Kumar, Sachin & Chaudhuri, Ranjan & Chatterjee, Sheshadri & Thrassou, Alkis & Sakka, Georgia, 2025. "From insight to impact: Unravelling the dynamics of big data-backed growth hacking," Journal of Business Research, Elsevier, vol. 188(C).
    8. Alexandra RADU & Mihaela HERCIU, 2025. "Data Analytics, Decision-Making Process And Business Performance: A Bibliometric Analysis," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 20(2), pages 292-313, August.
    9. Rialti, Riccardo & Zollo, Lamberto & Ferraris, Alberto & Alon, Ilan, 2019. "Big data analytics capabilities and performance: Evidence from a moderated multi-mediation model," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    10. Jia, Xingping, 2025. "Digital marketing and brand competitiveness: The mediating role of marketing capability and operational capability," Journal of Retailing and Consumer Services, Elsevier, vol. 87(C).
    11. Fouzia Atlas & Yuan Yitong & Kashif Ullah Khan, 2025. "The financial and market impact of big data analytics and big data talent analytics capability: a knowledge management perspective," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-11, December.
    12. Huynh, Minh-Tay & Nippa, Michael & Aichner, Thomas, 2023. "Big data analytics capabilities: Patchwork or progress? A systematic review of the status quo and implications for future research," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    13. Kim, Jaemin & Dibrell, Clay & Kraft, Ellen & Marshall, David, 2021. "Data analytics and performance: The moderating role of intuition-based HR management in major league baseball," Journal of Business Research, Elsevier, vol. 122(C), pages 204-216.
    14. Mehrbakhsh Nilashi & Abdullah M. Baabdullah & Rabab Ali Abumalloh & Keng-Boon Ooi & Garry Wei-Han Tan & Mihalis Giannakis & Yogesh K. Dwivedi, 2025. "How can big data and predictive analytics impact the performance and competitive advantage of the food waste and recycling industry?," Annals of Operations Research, Springer, vol. 348(3), pages 1649-1690, May.
    15. Ghasemaghaei, Maryam & Calic, Goran, 2020. "Assessing the impact of big data on firm innovation performance: Big data is not always better data," Journal of Business Research, Elsevier, vol. 108(C), pages 147-162.
    16. Mehrbakhsh Nilashi & Abdullah Baabdullah & Rabab Ali Abumalloh & Keng-Boon Ooi & Garry Wei-Han Tan & Mihalis Giannakis & Yogesh Dwivedi, 2023. "How can big data and predictive analytics impact the performance and competitive advantage of the food waste and recycling industry?," Post-Print hal-05081422, HAL.
    17. Raguseo, Elisabetta & Vitari, Claudio & Pigni, Federico, 2020. "Profiting from big data analytics: The moderating roles of industry concentration and firm size," International Journal of Production Economics, Elsevier, vol. 229(C).
    18. Wamba, Samuel Fosso & Dubey, Rameshwar & Gunasekaran, Angappa & Akter, Shahriar, 2020. "The performance effects of big data analytics and supply chain ambidexterity: The moderating effect of environmental dynamism," International Journal of Production Economics, Elsevier, vol. 222(C).
    19. Korayim, Diana & Chotia, Varun & Jain, Girish & Hassan, Sharfa & Paolone, Francesco, 2024. "How big data analytics can create competitive advantage in high-stake decision forecasting? The mediating role of organizational innovation," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    20. Ludivine Ravat & Aurélie Hemonnet-Goujot & Sandrine Hollet-Haudebert, 2023. "Data-driven innovation capability of marketing: an exploratory study of its components and underlying processes," Post-Print hal-04151199, HAL.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbrese:v:196:y:2025:i:c:s0148296325002693. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.