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What antecedent attitudes motivate actors to commit to the ecosystem of digital social innovation?

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  • Rodrigo, L.
  • Palacios, M.

Abstract

The purpose of this article is to identify those antecedent factors affecting the commitment among professionals and managers of projects and initiatives that are part of the ecosystem of Digital Social Innovation (DSI) in Spain. These factors are related to the commitment experienced towards their job, as well as to their commitment to the cause or social goal pursued by the project or organization. The study of the literature allows the development of an iterative theoretical framework that measures the most relevant variables that affect the attitude of these actors. Finally, a qualitative comparative analysis (QCA) is carried out to test a new model looking for those antecedent attitudes that become core conditions to the success of organizational commitment. What emerges from the research is that the presence of antecedent factors that belong to the cognitive dimension leads to a high level of commitment, while the absence of some factors from the affective dimension, together with high levels of anxiety, lead to a lack of commitment.

Suggested Citation

  • Rodrigo, L. & Palacios, M., 2021. "What antecedent attitudes motivate actors to commit to the ecosystem of digital social innovation?," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    • Handle: RePEc:eee:tefoso:v:162:y:2021:i:c:s0040162520312208
    DOI: 10.1016/j.techfore.2020.120394
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    References listed on IDEAS

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    1. Cajaiba-Santana, Giovany, 2014. "Social innovation: Moving the field forward. A conceptual framework," Technological Forecasting and Social Change, Elsevier, vol. 82(C), pages 42-51.
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    4. Cédric Gossart & Müge Özman Gossart, 2018. "Digital social innovation: exploring an emerging ecosystem," Post-Print hal-01991087, HAL.
    5. Beynon, Malcolm J. & Jones, Paul & Pickernell, David, 2020. "Country-level entrepreneurial attitudes and activity through the years: A panel data analysis using fsQCA," Journal of Business Research, Elsevier, vol. 115(C), pages 443-455.
    6. Söderholm, Patrik & Hellsmark, Hans & Frishammar, Johan & Hansson, Julia & Mossberg, Johanna & Sandström, Annica, 2019. "Technological development for sustainability: The role of network management in the innovation policy mix," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 309-323.
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    Cited by:

    1. Kabengele, Christian & Hahn, Rüdiger, 2021. "Institutional and firm-level factors for mobile money adoption in emerging markets–A configurational analysis," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    2. Rodrigo, L & Pérez-Arechaederra, D & Palacios, M & Romero, J, 2022. "Organisational commitment in the digital social innovation context: does qualitative comparative analysis add information to linear regression?," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    3. Yu, Tiffany Hui-Kuang & Huarng, Kun-Huang & Lai, Yun Ting, 2021. "Configural analysis of innovation for exploring economic growth," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    4. Piotr Tomasz Makowski & Yuya Kajikawa, 2021. "Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle," Papers 2103.02395, arXiv.org.
    5. Joti kumari & Jai Kumar, 2023. "Influence of motivation on teachers’ job performance," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    6. Makowski, Piotr Tomasz & Kajikawa, Yuya, 2021. "Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle," Technological Forecasting and Social Change, Elsevier, vol. 168(C).

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