A Comparative Analysis of the Diffusion of Mobile Technologies in the Visegrad Four Using an ECM Model
DOI:
https://doi.org/10.15678/krem.18618Słowa kluczowe:
diffusion of innovation, V4 countries, ECM, Gompertz functionAbstrakt
Objective: The aim of the paper is to assess the size and rate of diffusion of mobile technologies in the processing industry, and to determine the nature and strength of the impact of investment specialisation (investment attractiveness) and industry export specialisation on this phenomenon in the four Visegrad Group countries.
Research Design & Methods: The occurrence of innovation diffusion and its dynamics were examined using an econometric model of the Gompertz function. To study the impact of specialisation according to foreign direct investments (FDI) located in V4 countries and their export specialisation on the process of innovation diffusion, an error correction model (ECM) estimated for selected industrial processing sectors was used. It was based on data for 2010–2021 from Eurostat, UNCTAD and the national statistical offices of individual V4 countries.
Findings: The phase of rapid increase in innovation diffusion calculated on the basis of the Gompertz function was significantly longer in high- and medium-high technology enterprises than in low- and medium-low technology enterprises. In the short term, the determinants of mobile technology diffusion in all V4 countries in industries with low and medium-low technology are both export specialisation and investment attractiveness.
Implications / Recommendations: The results lead to the conclusion that the diffusion of mobile technologies takes place in various industries in the V4, but its pace varies depending on the individual industry’s technological development. The results indicate the need to develop industries with high technologies and sectors with high intensity of knowledge.
Contribution: A comparative analysis of the pace of diffusion of mobile technology innovations in the V4 was performed for the first time in this article. The combination of the Gompertz model with the ECM model can also be considered a pioneering solution in the analysis of innovation diffusion.
Pobrania
Bibliografia
Akçura, M., & Altınkemer, K. (2010). Digital Bundling. Information Systems and E-Business Management, 8(4), 337–335. https://doi.org/10.1007/s10257-009-0117-5 DOI: https://doi.org/10.1007/s10257-009-0117-5
Asongu, S. A. (2021). The Effects of Mobile Phone Technology, Knowledge Creation and Diffusion on Inclusive Human Development in Sub-Saharan Africa. Journal of Knowledge Economy, 12(3), 1367–1398. https://doi.org/10.2139/ssrn.3623840 DOI: https://doi.org/10.1007/s13132-020-00668-8
Balassa, B. (1965). Trade Liberalisation and “Revealed” Comparative Advantage. The Manchester School of Economic and Social Studies, 33(2), 99–123. https://doi.org/10.1111/j.1467-9957.1965.tb00050.x DOI: https://doi.org/10.1111/j.1467-9957.1965.tb00050.x
Bass, F. M. (1969). A New Product Growth Model for Consumer Durables. Management Science, 15(5), 215–227. https://doi.org/10.1287/mnsc.15.5.215 DOI: https://doi.org/10.1287/mnsc.15.5.215
Bemmaor, A. C., & Lee, J. (2002). The Impact of Heterogeneity and Ill-conditioning on Diffusion Model Parameter Estimates. Marketing Science, 21(2), 209–220. https://doi.org/10.1287/mksc.21.2.209.151 DOI: https://doi.org/10.1287/mksc.21.2.209.151
Desiraju, R., Nair, H., & Chintagunta P. (2004). Diffusion of New Pharmaceutical Drugs in Developing and Developed Nations. International Journal of Research in Marketing, 21(4), 341–357. https://doi.org/10.1016/j.ijresmar.2004.05.001 DOI: https://doi.org/10.1016/j.ijresmar.2004.05.001
Dos Santos, B. L., & Peffers, K. (1998). Competitor and Vendor Influence on the Adoption of Innovative Applications in Electronic Commerce. Information & Management, 34(3), 175–184. https://doi.org/10.1016/S0378-7206(98)00053-6 DOI: https://doi.org/10.1016/S0378-7206(98)00053-6
Firlej, K., & Żmija, D. (2014). Knowledge Transfer and Diffusion of Innovation as a Source of Competitiveness of Food Industry Enterprises in Poland. Foundation of the Cracow University of Economics.
Gwarda-Gruszczyńska, E. (2017). Dyfuzja innowacji – następstwo komercjalizacji nowych technologii. Organizacja i Kierowanie, 2, 383–396.
Klincewicz, K. (2011). Dyfuzja innowacji. Jak odnieść suckes w komercjalizacji nowych produktów i usług. Wydawnictwo Naukowe Wydziału Zarządzania Uniwersytetu Warszawskiego.
Kolarz, M. (2006). Wpływ zagranicznych inwestycji bezpośrednich na innowacyjność przedsiębiorstw w Polsce. Wydawnictwo Uniwersytetu Śląskiego w Katowicach.
Liu, A. X., Wang, Y., Chen, X., & Jiang, X. (2014). Understanding the Diffusion of Mobile Digital Content: A Growth Curve Modelling Approach. Information Systems and E-Business Management, 12(2), 239–258. https://doi.org/10.1007/s10257-013-0224-1 DOI: https://doi.org/10.1007/s10257-013-0224-1
Liu, X., Wu, F.-S., & Chu W.-L. (2009). Innovation Diffusion: Mobile Telephony Adoption in China. International Journal of Innovation Management, 13(2), 245–271. https://doi.org/10.1142/S1363919609002285 DOI: https://doi.org/10.1142/S1363919609002285
Mahajan, V., Muller, E., & Bass, F. M. (1990). New Product Diffusion Models in Marketing: A Review and Directions for Research. Journal of Marketing, 54(1), 1–26. https://doi.org/10.2307/1252170 DOI: https://doi.org/10.1177/002224299005400101
Meade, N., & Islam, T. (1995). Forecasting with Growth Curves: An Empirical Comparison. International Journal of Forecasting, 11(2), 199–215. https://doi.org/10.1016/0169-2070(94)00556-R DOI: https://doi.org/10.1016/0169-2070(94)00556-R
Meade, N., & Islam, T. (2006). Modelling and Forecasting the Diffusion of Innovation – a 25-year Review. International Journal of Forecasting, 22(3), 519–545. https://doi.org/10.1016/j.ijforecast.2006.01.005 DOI: https://doi.org/10.1016/j.ijforecast.2006.01.005
Morrill, R. L., & Manninen, D. (1975). Critical Parameters of Spatial Diffusion Processes. Economic Geography, 51(3), 269–277. https://doi.org/10.2307/143121 DOI: https://doi.org/10.2307/143121
OECD/Eurostat. (2005). Oslo Manual. Guidelines for Collecting and Interpreting Innovation Data (3rd ed.). OECD Publishing. https://doi.org/10.1787/9789264013100-en DOI: https://doi.org/10.1787/9789264013100-en
Peres, R., Muller, E., & Mahajan, V. (2010). Innovation Diffusion and New Product Growth Models: A Critical Review and Research Directions. International Journal of Research in Marketing, 27(2), 91–106. https://doi.org/10.1016/j.ijresmar.2009.12.012 DOI: https://doi.org/10.1016/j.ijresmar.2009.12.012
Ramkumar, S., Mueller, M., Pyka, A., & Squazzoni, F. (2022). Diffusion of Eco-innovation through Inter-firm Network Targeting: An Agent-based Model. Journal of Cleaner Production, 335, 130298. https://doi.org/10.1016/j.jclepro.2021.130298 DOI: https://doi.org/10.1016/j.jclepro.2021.130298
Rogers, E. M. (1962). Diffusion of Innovations. The Free Press.
Roy, A., Dutta, G., & Das, P. K. (2019). Exploring the Determinants of Mobile-based Services Diffusion: Past Determinants, Emergent Pattern and a Proposed Framework. International Journal of Business Innovation and Research, 18(4), 429–452. https://doi.org/10.1504/IJBIR.2019.098759 DOI: https://doi.org/10.1504/IJBIR.2019.098759
Salamaga, M. (2020). Econometric Analysis of the Relationship between Innovation and Foreign Trade Distance in Central and Eastern Europe Countries. Folia Oeconomica Stetinensia, 20(1), 360–372. https://doi.org/10.2478/foli-2020-0021 DOI: https://doi.org/10.2478/foli-2020-0021
Sharif, M. N., & Kabir, C. (1976). System Dynamics Modelling for Forecasting Multilevel Technological Substitution. Technological Forecasting and Social Change, 9(1–2), 89–112. https://doi.org/10.1016/0040-1625(76)90046-9 DOI: https://doi.org/10.1016/0040-1625(76)90046-9
Singh, S. K. (2008). The Diffusion of Mobile Phones in India. Telecommunications Policy, 32(9–10), 642–651. https://doi.org/10.1016/j.telpol.2008.07.005 DOI: https://doi.org/10.1016/j.telpol.2008.07.005
Skiti, T. (2020). Institutional Entry Barriers and Spatial Technology Diffusion: Evidence from the Broadband Industry. Strategic Management Journal, 41(7), 1336–1361. https://doi.org/10.1002/smj.3146 DOI: https://doi.org/10.1002/smj.3146
Tarde, G. (1895). Les lois de l’imitation. G. Baillière & C.
Teng, T. C., Grover, V., & Guttler, W. (2002). Information Technology Innovations: General Diffusion Patterns and Its Relationships to Innovation Characteristics. IEEE Transactions on Engineering Management, 49(1), 13–27. https://doi.org/10.1109/17.985744 DOI: https://doi.org/10.1109/17.985744
Van den Bulte, C., & Stremersch, S. (2004). Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-analytic Test. Marketing Science, 23(4), 530–544. https://doi.org/10.1287/mksc.1040.0054 DOI: https://doi.org/10.1287/mksc.1040.0054
Wiśniewska, J. (2004). Ekonomiczne determinanty dyfuzji innowacji produktowych i technologicznych w banku komercyjnym. Wydawnictwo Naukowe Uniwersytetu Szczecińskiego.
Pobrania
Opublikowane
Numer
Dział
Licencja
Prawa autorskie (c) 2024 Uniwersytet Ekonomiczny w Krakowie
Utwór dostępny jest na licencji Creative Commons Uznanie autorstwa 4.0 Międzynarodowe.
