Analyzing the determinants of e-commerce in small and medium-sized enterprises: a cognition-driven framework
Abstract
The increasing use of information technology in enterprises’ daily operations has led to multiple innovative ways to run a business, including electronic commerce (hereafter, e-commerce). However, firms with fewer resources, such as small and medium-sized enterprises (SMEs), are more reluctant to use electronic channels during transactions. This aversion to contemporary business models is a result of these companies’ lack of knowledge and capabilities regarding e-commerce. To improve their businesses, SMEs’ managers and decision makers could benefit from a methodological framework that fosters a deeper understanding of the determinants of e-commerce. This study sought to explore the use of fuzzy cognitive mapping to address this need. The results are grounded in the knowledge and experience of a panel of experts in e-commerce. The fuzzy cognitive map (FCM) developed shows that entrepreneur profile, market, operational management, marketing and promotions, website and digital platform, and products present the highest centrality indices as determinants of SME e-commerce. The findings offer a better understanding of the cause-and-effect relationships between these determinants. The advantages, limitations, and shortcomings of our constructivist proposal are also discussed.
First published online 10 April 2019
Keyword : small and medium-sized enterprises (SMEs), e-commerce, decision support systems, fuzzy cognitive map (FCM)
How to Cite
Barroso, R. M. R., Ferreira, F. A. F., Meidutė-Kavaliauskienė, I., Banaitienė, N., Falcão, P. F., & Rosa, Álvaro A. (2019). Analyzing the determinants of e-commerce in small and medium-sized enterprises: a cognition-driven framework. Technological and Economic Development of Economy, 25(3), 496-518. https://doi.org/10.3846/tede.2019.9386
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Ferreira, F. (2016). Are you pleased with your neighborhood? A fuzzy cognitive mapping-based approach for measuring residential neighborhood satisfaction in urban communities. International Journal of Strategic Property Management, 20(2), 130-141. https://doi.org/10.3846/1648715X.2015.1121169
Ferreira, F., & Jalali, M. (2015). Identifying key determinants of housing sales and time-on-the-market (TOM) using fuzzy cognitive mapping. International Journal of Strategic Property Management, 19(3), 235-244. https://doi.org/10.3846/1648715X.2015.1052587
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Ferreira, F., Ferreira, J., Fernandes, C., Meidutė-Kavaliauskienė, I., & Jalali, M. (2017). Enhancing knowledge and strategic planning of bank customer loyalty using fuzzy cognitive maps. Technological and Economic Development of Economy, 23(6), 860-876. https://doi.org/10.3846/20294913.2016.1213200
Ferreira, F., Jalali, M., & Ferreira, J. (2016). Integrating qualitative comparative analysis (QCA) and fuzzy cognitive maps (FCM) to enhance the selection of independent variables. Journal of Business Research, 69(4), 1471-1478. https://doi.org/10.1016/j.jbusres.2015.10.127
Ferreira, F., Jalali, M., Ferreira, J., Stankevičienė, J., & Marques, C. (2016). Understanding the dynamics behind bank branch service quality in Portugal: pursuing a holistic view using fuzzy cognitive mapping. Service Business, 10(3), 469-487. https://doi.org/10.1007/s11628-015-0278-x
Fonseca, M., Ferreira, F., Fang, W., & Jalali, M. (2018). Classification and selection of tenants in residential real estate: a constructivist approach. International Journal of Strategic Property Management, 22(1), 1-11. https://doi.org/10.3846/ijspm.2018.317
Glykas, M. (2013). Fuzzy cognitive strategic maps in business process performance measurement. Expert Systems with Applications, 40(1), 1-14. https://doi.org/10.1016/j.eswa.2012.01.078
Grandón, E., Nasco, S., & Mykytyn, P. (2011). Comparing theories to explain e-commerce adoption. Journal of Business Research, 64(3), 292-298. https://doi.org/10.1016/j.jbusres.2009.11.015
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Grillo, C., Ferreira, F., Marques, C., & Ferreira, J. (2018). A knowledge-based innovation assessment system for small- and medium-sized enterprises: adding value with cognitive mapping and MCDA. Journal of Knowledge Management, 22(3), 696-718. https://doi.org/10.1108/JKM-08-2017-0332
Hester, P. (2015). Analyzing stakeholders using fuzzy cognitive mapping. Procedia Computer Science, 61, 92-97. https://doi.org/10.1016/j.procs.2015.09.159
Kang, B., Deng, Y., Sadiq, R., & Mahadevan, S. (2012). Evidential cognitive maps. Knowledge-Based Systems, 35, 77-86. https://doi.org/10.1016/j.knosys.2012.04.007
Kim, H., & Lee, K. (1998). Fuzzy implications of fuzzy cognitive map with emphasis on fuzzy causal relationship and fuzzy partially causal relationship. Fuzzy Sets and Systems, 97(3), 303-313. https://doi.org/10.1016/S0165-0114(96)00349-1
Kok, K. (2009). The potential of fuzzy cognitive maps for semi-quantitative scenario development, with an example from Brazil. Global Environmental Change, 19(1), 122-133. https://doi.org/10.1016/j.gloenvcha.2008.08.003
Kosko, B. (1986). Fuzzy cognitive maps. International Journal of Man-Machine Studies, 24(1), 65-75. https://doi.org/10.1016/S0020-7373(86)80040-2
Koulouriotis, D. (2004). Investment analysis & decision making in markets using adaptive fuzzy causal relationships. Operational Research: An International Journal, 4(2), 213-233. https://doi.org/10.1007/BF02943610
Lip-Sam, T., & Hock-Eam, L. (2011). Estimating the determinants of B2B e-commerce adoption among small & medium enterprises. International Journal of Business and Society, 12(1), 15-30.
MacGregor, R., & Vrazalic, L. (2006). The effect of small business clusters in prioritising barriers to e-commerce adoption in regional SMEs. Journal of New Business Ideas and Trends, 4(1), 24-44.
Mackenzie, A., Pidd, M., Rooksby, J., Sommerville, I., Warren, I., & Westcombe, M. (2006). Decision aiding: wisdom, decision support and paradigms of decision making. European Journal of Operational Research, 170(1), 156-171. https://doi.org/10.1016/j.ejor.2004.07.041
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