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Measuring dynamic capabilities in new ventures: exploring strategic change in US green goods manufacturing using website data

Author

Listed:
  • Sanjay K. Arora

    (Ernst & Young, LLP)

  • Yin Li

    (Fudan University)

  • Jan Youtie

    (Georgia Institute of Technology)

  • Philip Shapira

    (University of Manchester
    Georgia Institute of Technology)

Abstract

Entrepreneurial scholarship suggests that a small firm’s ability to grow is a function of its capacity to sense and respond to changes in the market as well as the broader environment for the firm’s goods and services. Developing detailed measures of internal capabilities at a large scale, however, is often hampered by limitations in the availability of data from conventional sources, low survey response rates and panel attrition. The emergence of new information sources, including big data sets derived from the online activities of firms, coupled with advanced computational approaches, raises fresh analytical possibilities. In this exploratory study, we turn to freely accessible website data to gauge internal capabilities, specifically for market sensing and responding. To operationalize the construct of seizing, the paper uses an application of topic modeling, a text mining approach commonly used in computer science, on archived website data from the Wayback Machine for two time periods, 2008–2009 and 2010–2011, to explain sales growth for green goods enterprises in two later time periods, from 2010 to 2012. We find an endogenous inverse U-shaped relationship exists between market seizing and sales growth. Increasing levels of focus on a firm’s local geographic area also predict sales growth. We consider these findings in light of the practitioner literature on firm agility and pivoting and discuss opportunities for future work using website data to study entrepreneurship and the strategic management of innovation.

Suggested Citation

  • Sanjay K. Arora & Yin Li & Jan Youtie & Philip Shapira, 2020. "Measuring dynamic capabilities in new ventures: exploring strategic change in US green goods manufacturing using website data," The Journal of Technology Transfer, Springer, vol. 45(5), pages 1451-1480, October.
    • Handle: RePEc:kap:jtecht:v:45:y:2020:i:5:d:10.1007_s10961-019-09751-y
    DOI: 10.1007/s10961-019-09751-y
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    2. Jessica Birkholz, 2023. "Do not judge a business idea by its cover: The relation between topics in business ideas and incorporation probability," The Journal of Technology Transfer, Springer, vol. 48(4), pages 1327-1358, August.
    3. Ashouri, Sajad & Hajikhani, Arash & Suominen, Arho & Pukelis, Lukas & Cunningham, Scott W., 2024. "Measuring digitalization at scale using web scraped data," Technological Forecasting and Social Change, Elsevier, vol. 207(C).
    4. Jessica Birkholz & Jutta Günther & Mariia Shkolnykova, 2021. "Using Topic Modeling in Innovation Studies: The Case of a Small Innovation System under Conditions of Pandemic Related Change," Bremen Papers on Economics & Innovation 2101, University of Bremen, Faculty of Business Studies and Economics.
    5. Schubert, Torben & Ashouri, Sajad & Deschryvere, Matthias & Jäger, Angela & Visentin, Fabiana & Cunningham, Scott & Hajikhani, Arash & Pukelis, Lukas & Suominen, Arho, 2023. "The role of product digitization for productivity," MERIT Working Papers 2023-004, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    6. Bottai, Carlo & Crosato, Lisa & Domenech, Josep & Guerzoni, Marco & Liberati, Caterina, 2024. "Scraping innovativeness from corporate websites: Empirical evidence on Italian manufacturing SMEs," Technological Forecasting and Social Change, Elsevier, vol. 207(C).

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    More about this item

    Keywords

    Dynamic capabilities; Entrepreneurship; SMEs; Big data; Website analytics; Text mining;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • L21 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Business Objectives of the Firm
    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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