Impact of external stimuli and management control systems on radical innovation and startup performance

  • 41 Views
  • 7 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

The rapidly changing business environment and fierce competition necessitate startups to innovate continuously. External stimuli such as market trends, technological advancements, and competition are critical in influencing a startup’s ability to innovate and enhance performance. This study aims to explore the role of these external stimuli, along with management control systems, specifically diagnostic and interactive systems, in promoting radical innovations and improving startup performance. A quantitative approach using partial least squares structural equation modeling (PLS-SEM) was applied to data collected from 250 startup managers in Indonesia. The results show that external stimuli significantly influence diagnostic (p < 0.001, t = 3.647) and interactive control systems (p < 0.001, t = 5.452). Diagnostic and interactive systems positively affect radical innovation (p < 0.001, t = 3.362). Radical innovation significantly enhances performance (p < 0.001, t = 3.453). Such evidence shows that external stimuli and control systems should be aligned to facilitate radical innovation and increase startup performance. The study offers valuable information for managers on how to achieve operational control but retain strategic flexibility in rapidly changing situations. The findings present both theoretical and practical contributions to strategic management and innovation processes in startup companies.

view full abstract hide full abstract
    • Figure 1. Research framework
    • Figure 2. Factor loading
    • Table 1. Data collection
    • Table 2. Respondent data profile
    • Table 3. Demographics of respondents
    • Table 4. Average variance extracted, composite reliability, and Cronbach’s alpha
    • Table 5. Discriminant validity according to the Fornell–Larcker criterion
    • Table 6. Model validation results
    • Table A1. Questionnaire items
    • Conceptualization
      Arfah Piliang
    • Data curation
      Arfah Piliang, Meutia
    • Investigation
      Arfah Piliang, Elvin Bastian
    • Methodology
      Arfah Piliang
    • Writing – original draft
      Arfah Piliang
    • Formal Analysis
      Meutia
    • Project administration
      Meutia, Munawar Muchlish
    • Writing – review & editing
      Meutia, Elvin Bastian, Munawar Muchlish
    • Resources
      Elvin Bastian, Munawar Muchlish
    • Validation
      Elvin Bastian
    • Visualization
      Munawar Muchlish