Constructing a model to identify the determinants of successful software import substitution
Abstract
In the process of import substitution, higher educational institutions face several challenges in transitioning from the predominant use of foreign software to domestic alternatives. These challenges include a lack of user experience with domestic digital solutions, difficulty in transferring data between systems and other issues. The difficulties associated with the transition period create resistance to the digital transformation process. Research on import substitution in universities has identified three main themes: the challenges and risks associated with switching to domestic software, exploring the feasibility of a complete transition to Russian software and providing recommendations for selecting Russian solutions. This study aims to identify the factors that influence the adoption of import substitution software products in higher education. The article proposes a structural model to identify the factors that contribute to successful software import substitution. The model is based on the theories of innovation diffusion and technology adoption, and it was developed using SmartPLS software. The model is based on data collected from a survey of professors and staff at the Ural State University of Economics. The results of the study indicate that the attitude towards adopting import substitution software depends on several factors, including the personal characteristics and innovative features of the software. The most significant determinants of a positive attitude towards transitioning to domestic software include user involvement and self-efficacy. In addition, a positive perception of the need for import substitution can influence individual acceptance of transitioning to Russian software and recognizing import substitution as an economic policy of the country. The theoretical significance of the study lies in its proposal of an original model for identifying the determinants of successful software import substitution that differentiates between individual acceptance and public recognition of software import substitution. The findings of the study could be useful to university management in planning and implementing measures for an import substitution strategy.
Downloads
References
Ministry of Education and Science of Russia (2022) Methodological recommendations for the transition of educational organizations of higher education to the primary use of domestic software (messengers and video conferencing), including domestic office software. Available at: https://minobrnauki.gov.ru/importozameshcheniye/Метод_рекомендации_отеч_ПО_ВУЗы.pdf (accessed 24 May 2024) (in Russian).
Ministry of Education and Science of Russia (2022) Import substitution of IT in the field of science and higher education. Available at: https://minobrnauki.gov.ru/importozameshcheniye/ (accessed 24 May 2024) (in Russian).
Burnyashov B.A. (2022) Import substitution of the software used in the educational process in Russian universities. Informatics and Education, vol. 37, no. 1, pp. 27–36 (in Russian).
Burnyashov B.A. (2023) Russian cloud office application packages in the educational process of universities. Informatics and Education, vol. 38, no. 2, pp. 5–15 (in Russian).
Innopolis University (2022) Analytical report on determining the potential for import substitution of software (in the system of higher and secondary vocational education). Innopolis: Innopolis University (in Russian).
Pasurin D.A. (2023) Problems of software import substitution in universities. Digital models and solutions, vol. 2, no. 4, pp. 63–75 (in Russian).
Muzalevskaya A.A., Gajdamakina I.V. (2023) Prerequisites and opportunities for import substitution of software in the training of specialists in Russian universities. Scientific Notes of Orel State Universiy, no. 2(99), pp. 275–279 (in Russian).
Polonskij A.M. (2022) Import substitution of software and organization of student education using domestic or free software. Aktual’nye problemy ekonomiki i upravleniya (Actual problems of economics and management), no. 2(34), pp. 65–82 (in Russian).
Savvateeva T.P. (2019) Problems of software import substitution for teaching of bachelor students to information systems design. Modern problems of science and education, no. 5 (in Russian).
Zagvyazinskij V.I. (2001) Learning Theory: A modern interpretation. Moscow: Academia (in Russian).
Kalinichenko N.S., Velichkovskij B.B. (2022) The technology acceptance phenomenon: current state and future research. Organizational Psychology, vol. 12, no. 1, pp. 128–152 (in Russian).
Rogers E.M. (2010) Diffusion of innovations. New York: Simon and Schuster.
Rogers E.M., Agarwala-Rogers R. (1980) Communication in organizations. Moscow: Economy (in Russian).
Davis F.D. (1985) A Technology Acceptance Model for empirically testing new end-user information systems: theory and results. PhD dissertation. Cambridge: Massachusetts Institute of Technology.
Davis F.D., Bagozzi R.P., Warshaw P.R. (1989) User acceptance of computer technology: A comparison of two theoretical models. Management Science, vol. 35, no. 8, pp. 982–1003.
Moore G.C., Benbasat I. (1991) Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, vol. 2, pp. 192–222.
Parasuraman A. (2000) Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, vol. 2, no. 4, pp. 307–320.
Ajzen I. (1991) The theory of planned behavior. Organizational Behavior and Human Decision Processes, vol. 50, pp. 179–211.
Venkatesh V., Morris M., Davis G., Davis F. (2003) User acceptance of information technology: Toward a unified view. MIS Quarterly, vol. 27, no. 3, pp. 425–478.
Abraham C., Boudreau M., Junglas I., Watson R. (2013) Enriching our theoretical repertoire: The role of evolutionary psychology in technology acceptance. European Journal of Information Systems, vol. 22, no. 1, pp. 56–75.
Oh K., Kho H., Choi Y., Lee S. (2022) Determinants for successful digital transformation. Sustainability, vol. 14, no. 3, 1215.
Ram S. (1987) A model of innovation resistance. Advances in Consumer Research, vol. 14, pp. 208–212.
SmartPLS (2024) SmartPLS 4. The world´s most user-friendly statistical software. Available at: https://www.smartpls.com/ (accessed 25 May 2024).
Chu Y., Chi M., Wang W. (2019) The impact of information technology capabilities of manufacturing enterprises on innovation performance: Evidences from SEM and fsQCA. Sustainability, vol. 11, no. 21, 5946.
Miceli A., Hagen B., Riccardi M.P. (2021) Thriving, not just surviving in changing times: How sustainability, agility and digitalization intertwine with organizational resilience. Sustainability, vol. 13, no. 4, 2052.
Zhang J., Long J., von Schaewen A.M.E. (2021) How Thriving, not just surviving in changing times: How sustainability, agility and digitalization intertwine with organizational resilience? – Findings from PLS-SEM and fsQCA. Sustainability, vol. 13, no. 4, 11487.
Hair J.F., Hult G.T.M., Ringle C., Sarstedt M., Danks N., Ray S. (2021) Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer.
.jpg)
