Advertisement

E-Commerce Decision-Making Factors in Peruvian Organizations of the Retail Sector

  • Enrique Saravia
Conference paper
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 180)

Abstract

The purpose of this research is to identify, by an exploratory approach, the main factors of decision-making on adopting e-commerce technologies in Peruvian organizations of the retail sector. The study was based on the application of 80 on-line surveys and 8 interviews with experts. The main findings of the quantitative analysis, based on a structural model with a high reliability and validity index, indicate the main factors that influence decision-making on adopting e-commerce technologies, is the awareness that high investments in technologies generate profit in the long-term (motivating factor) and risks of innovation (inhibiting factors), in addition to other factors that influence at a lower level as the organizational culture, the attitudes of innovation and optimism to the use of technologies of decision-makers, people’s skills, and process flexibility to adapt them to e-commerce activities, among others. The qualitative analysis allows further the study and identify specific details which can make a significant contribution to knowledge generation and practical application in the organizations, which gives us an extensive list of aspects that have to be managed appropriately, and can thus lead the investments and mitigate the risks.

References

  1. COTEC: Innovación Tecnológica. Ideas Básicas (2001). https://www.innova.uned.es/webpages/innovaciontecnologica/mod1_tema1/InnovacionTecIdeasBasicas.pdf. Accessed Febrero de 2016
  2. Davis, F.: A technology acceptance model for empirically testing new end-user information systems: theory and results. Doctoral dissertation, MIT Sloan School of Management, Cambridge (1986)Google Scholar
  3. Davis, F.D.: Perceived usefulness, perceived easy of use, and user acceptance of information technnology. MIS Q. 13(3), 319–340 (1989)CrossRefGoogle Scholar
  4. Cuadernos delebcenter, e-business Center: Pricewaterhouse Coopers & IESE. Cuadernos de ebcenter (2008). www.iese.edu/en/files/Criterios%20de%20adopción%20de%20las%TIC_tcm4_23387.pdf. Accessed 20 de febrero de 2016
  5. Fishbein, M., Ajzen, I.: Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Addison-Wiley Publishing Company, Reading (1975)Google Scholar
  6. Guerrero Cuellar, R., Rivas Tovar, L.A.: Comercio Electrónico en México: Propuesta de un modelo conceptual aplicado a las PyMEs. In: SOCIOTAM XV, vol. 1, pp. 79–116 (2005) Google Scholar
  7. Guisado, M.: La relación entre diferentes tipos de innovación en el Sector Servicios. Un análisis desde el enfoque de Complementariedad. In: XXX AEDEM Annual Meeting. Las Palmas de Gran Canaria (2016)Google Scholar
  8. Hair Jr., J., Sarstedt, M., Hopkins, L., Kuppelwieser, V.: Partial least squares structural equation modeling (PLS-SEM). An emerging tool in business research. Eur. Bus. Rev. 26(2), 106–121 (2014)CrossRefGoogle Scholar
  9. Kline, S., Rosenberg, N.: An overview of innovation. In: The Positive Sum Strategy: Hearnessing Technology for Economic Growth, 14, 640. National Academy of Sciences, Washington (1986) Google Scholar
  10. Kurnia, S., Karnali, R., Rahim, M.M.: A quality study of business-to-business electronic commerce adoption within the Indonesian grocery industry: a multi-theory perspective. Inf. Manag. 52, 518–536 (2015)CrossRefGoogle Scholar
  11. Mick, D.G., Fournier, S.: Paradoxes of technology: consumer cognizance, emotions, and coping strategies. J. Consum. Res. 25, 123–143 (1998)CrossRefGoogle Scholar
  12. OECD: Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data, 3rd edn. OECD/EC/Eurostat, OECD Publishing, Paris (2005)Google Scholar
  13. Oliveira, T., Martins, M.F.: Literature review of information technology adoption models at firm level. Electron. J. Inf. Syst. Eval. 14(1), 110–212 (2011)Google Scholar
  14. Parasuraman, A.: Technology readiness index (TRI). A multiple-item scale to measure readiness to embrace new technologies. J. Serv. Res. 2(4), 307–320 (2000)CrossRefGoogle Scholar
  15. Parasuraman, A., Colby, C.A.: An updated and streamlined technology readiness index: TRI 2.0. J. Serv. Res. 18(1), 59–74 (2015)CrossRefGoogle Scholar
  16. Rao, J., Weintraub, J.: How innovative is your company’s culture? MIT Sloan Manag. Rev. 54(3), 28–39 (2013)Google Scholar
  17. Vankatesh, V., Davis, F.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46(2), 186–204 (2000)CrossRefGoogle Scholar
  18. VISA: Informe sobre e-Readiness en Latinoamérica 2014 (2014). http://promociones.visa.com/lac/ecommerce/es/index.html. Accessed Marzo de 2016
  19. Wigand, R.T.: Electronic commerce: definition, theory, and context. Inf. Soc. 13, 1–16 (1997)CrossRefGoogle Scholar
  20. Wong, K.: Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Mark. Bull. 24(1), 1–32 (2013)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Universidad del PacíficoLimaPeru

Personalised recommendations