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Key factors of information management for crowdfunding investor satisfaction

Author

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  • Ribeiro-Navarrete, Samuel
  • Palacios-Marqués, Daniel
  • Lassala, Carlos
  • Ulrich, Klaus

Abstract

Crowdlending platforms are becoming increasingly important as a collective financing mechanism for entrepreneurs and small and medium-sized enterprises (SMEs), especially those at an early stage. This study, which is based on a survey of investors on a Spanish crowdlending platform, uses fuzzy-set qualitative comparative analysis (fsQCA) to examine investor satisfaction with crowdlending platforms. Specifically, the study examines communication policies and the quality of the investor experience based on the information provided by these platforms. The value of this article lies in its examination of the antecedents of crowdlending investor satisfaction. The analysis shows that the actions of ensuring that it is easy to browse the platform, frequently updating project details, offering a mobile application, publishing a blog with details of new developments and frequently sending investors emails with information to support their investment decisions increase investors’ satisfaction with crowdlending platforms.

Suggested Citation

  • Ribeiro-Navarrete, Samuel & Palacios-Marqués, Daniel & Lassala, Carlos & Ulrich, Klaus, 2021. "Key factors of information management for crowdfunding investor satisfaction," International Journal of Information Management, Elsevier, vol. 59(C).
    • Handle: RePEc:eee:ininma:v:59:y:2021:i:c:s0268401221000475
    DOI: 10.1016/j.ijinfomgt.2021.102354
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    Citations

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    Cited by:

    1. Skare, Marinko & Gavurova, Beata & Polishchuk, Volodymyr, 2023. "A decision-making support model for financing start-up projects by venture capital funds on a crowdfunding platform," Journal of Business Research, Elsevier, vol. 158(C).
    2. Kumar, Satish & Sahoo, Saumyaranjan & Lim, Weng Marc & Kraus, Sascha & Bamel, Umesh, 2022. "Fuzzy-set qualitative comparative analysis (fsQCA) in business and management research: A contemporary overview," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    3. Wu, Chih-Wen & Botella-Carrubi, Dolores & Blanco-González-Tejero, Cristina, 2024. "The empirical study of digital marketing strategy and performance in small and medium-sized enterprises (SMEs)," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    4. Vazirani, Ashish & Sarkar, Subhro & Bhattacharjee, Titas & Dwivedi, Yogesh K & Jack, Sarah, 2023. "Information signals and bias in investment decisions: A meta-analytic comparison of prediction and actual performance of new ventures," Journal of Business Research, Elsevier, vol. 155(PB).
    5. Grijalvo, Mercedes & Segura, Alejandro & Núñez, Yilsy, 2022. "Computer-based business games in higher education: A proposal of a gamified learning framework," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    6. Seddik, Ahmed & Maleh, Yassine & El Banby, Ghada M. & Khalaf, Ashraf A.M. & Abd El-Samie, Fathi E. & Gupta, Brij B & Psannis, Konstantinos & Abd El-Latif, Ahmed A., 2022. "AI-enabled digital forgery analysis and crucial interactions monitoring in smart communities," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    7. Ferrer, José María & Ulrich, Klaus & Blanco-González-Tejero, Cristina & Caño-Marín, Enrique, 2023. "Investors’ confidence in the crowdlending platform and the impact of Covid-19," Journal of Business Research, Elsevier, vol. 155(PA).
    8. Youssef Riahi & Karim Garrouch, 2024. "A model explaining perceived investment value and switching intentions toward FinTech: the case of crowdlending," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(2), pages 553-567, June.

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