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Explaining Performance Expectancy of IoT in Chilean SMEs

  • Patricio E. Ramírez-CorreaEmail author
  • Elizabeth E. Grandón
  • Jorge Arenas-Gaitán
  • F. Javier Rondán-Cataluña
  • Alejandro Aravena
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 353)

Abstract

The purpose of this paper is to validate a research model that explains performance expectancy of IoT from psychological and cognitive variables: personal innovativeness of information technology (PIIT) and social influence respectively. Data were collected from small and medium-sized enterprises (SMEs) in Chile. A confirmatory approach using PLSc was employed to validate the hypotheses. The conclusions of the study are (a) Chilean SMEs companies do not use IoT massively, (b) goodness of fit indicators allowed to validate the proposed research model successfully, (c) both constructs, social influence and personal innovativeness of information technology, explain 61% of performance expectancy of IoT.

Keywords

IoT PIIT Performance expectancy Social influence SMEs 

References

  1. 1.
    Ibarra-Esquer, J.E., González-Navarro, F.F., Flores-Rios, B.L., Burtseva, L., Astorga-Vargas, M.A.: Tracking the evolution of the internet of things concept across different application domains. Sensors (Switzerland) 17(6), 1379 (2017)CrossRefGoogle Scholar
  2. 2.
    Parker, R., et al.: IDC FutureScape : Worldwide IT Industry 2017 PredictionsGoogle Scholar
  3. 3.
    Miazi, M.N.S., Erasmus, Z., Razzaque, M.A., Zennaro, M., Bagula, A.: Enabling the internet of things in developing countries: opportunities and challenges. In: Proceedings of the 2016 5th International Conference on Informatics, Electronics and Vision, ICIEV 2016 (2016)Google Scholar
  4. 4.
    Fundación País Digital Cómo emprender en Internet de las Cosas: Conceptos Prácticos; Gobierno de Chile. Santiago, Chile (2018)Google Scholar
  5. 5.
    Hasenauer, C.: The Internet of Things in Developing Countries. https://borgenproject.org/internet-of-things/. Accessed 5 Jan 2019
  6. 6.
    Karahanna, E., Straub, D.W.: The psychological origins of perceived usefulness and ease-of-use. Inf. Manag. 35, 237–250 (1999)CrossRefGoogle Scholar
  7. 7.
    Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13, 319–340 (1989)CrossRefGoogle Scholar
  8. 8.
    Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. 27, 425–478 (2003)CrossRefGoogle Scholar
  9. 9.
    Ramírez-Correa, P.E., Grandón, E.E., Arenas-Gaitán, J.: Assessing differences in customers’ personal disposition to e-commerce. Ind. Manage. Data Syst. (2019, In press). IMDS622482Google Scholar
  10. 10.
    Hsu, C.L., Lin, J.C.C.: An empirical examination of consumer adoption of Internet of Things services: Network externalities and concern for information privacy perspectives. Comput. Human Behav. 62, 516–527 (2016)CrossRefGoogle Scholar
  11. 11.
    Mital, M., Chang, V., Choudhary, P., Pani, A., Sun, Z.: Adoption of cloud based Internet of Things in India: a multiple theory perspective. Int. J. Inf. Manage. (2016)Google Scholar
  12. 12.
    Mital, M., Chang, V., Choudhary, P., Papa, A., Pani, A.K.: Adoption of Internet of Things in India: a test of competing models using a structured equation modeling approach. Technol. Forecast. Soc. Change 136, 339–346 (2018)CrossRefGoogle Scholar
  13. 13.
    Grandon, E.E., Aravena, A.A., Guzman, S.A., Ramirez-Correa, P., Alfaro-Perez, J.: Internet of Things: factors that influence its adoption among Chilean SMEs. In: Proceedings of the Iberian Conference on Information Systems and Technologies, CISTI (2018)Google Scholar
  14. 14.
    Agarwal, R., Prasad, J.: A conceptual and operational definition of personal innovativeness in the domain of information technology. Inf. Syst. Res. 9, 204–215 (1998)CrossRefGoogle Scholar
  15. 15.
    Jackson, J.D., Yi, M.Y., Park, J.S.: An empirical test of three mediation models for the relationship between personal innovativeness and user acceptance of technology. Inf. Manage. 50(4), 154–161 (2013)CrossRefGoogle Scholar
  16. 16.
    Prasetya, W.Y.S., Shihab, M.R., Sandhyaduhita, P.I.: Exploring the roles of personality factors on knowledge management system acceptance. In: Proceedings of the 2015 3rd International Conference on Information and Communication Technology, ICoICT 2015 (2015)Google Scholar
  17. 17.
    Hwang, Y.: User experience and personal innovativeness: an empirical study on the enterprise resource planning systems. Comput. Human Behav. 34, 227–234 (2014)CrossRefGoogle Scholar
  18. 18.
    Wang, W., Li, X., Hsieh, J.P.A.: The contingent effect of personal IT innovativeness and IT self-efficacy on innovative use of complex IT. Behav. Inf. Technol. 32(11), 1105–1124 (2013)CrossRefGoogle Scholar
  19. 19.
    Zhong, B., Hardin, M., Sun, T.: Less effortful thinking leads to more social networking? the associations between the use of social network sites and personality traits. Comput. Human Behav. 27(3), 1265–1271 (2011)CrossRefGoogle Scholar
  20. 20.
    Wong, C.H., Tan, G.W.H., Tan, B.I., Ooi, K.B.: Mobile advertising: the changing landscape of the advertising industry. Telemat. Inform. 32(4), 720–734 (2015)CrossRefGoogle Scholar
  21. 21.
    Liu, Y., Li, H., Carlsson, C.: Factors driving the adoption of m-learning: an empirical study. Comput. Educ. 55(3), 1211–1219 (2010)CrossRefGoogle Scholar
  22. 22.
    Nasco, S.A., Grandón, E., Mykytyn Jr., P.P.: Predicting electronic commerce adoption in Chilean SMEs. J. Bus. Res. 61, 697–705 (2008)CrossRefGoogle Scholar
  23. 23.
    Grandon, E.E., Nasco, S.A., Mykytyn Jr., P.P.: Comparing theories to explain e-commerce adoption. J. Bus. Res. 64, 292–298 (2011)CrossRefGoogle Scholar
  24. 24.
    Grandón, E., Ramirez-Correa, P.E.: Managers/Owners’ innovativeness and electronic commerce acceptance in Chilean SMEs: a multi-group analysis based on a structural equation model. J. Theor. Appl. Electron. Commer. Res. 13, 1–16 (2018)CrossRefGoogle Scholar
  25. 25.
    Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50, 179–211 (1991)CrossRefGoogle Scholar
  26. 26.
    Lu, J.: Are personal innovativeness and social influence critical to continue with mobile commerce? Internet Res. 24(2), 134–159 (2014)CrossRefGoogle Scholar
  27. 27.
    Koivisto, K., Makkonen, M., Frank, L., Riekkinen, J.: Extending the technology acceptance model with personal innovativeness and technology readiness: a comparison of three models. In: BLED 2016 Proceedings 29th Bled eConference Digit. Econ. (2016). ISBN 978-961-232-287-8Google Scholar
  28. 28.
    Lewis, W., Agarwal, R., Sambamurthy, V.: Sources of influence on beliefs about information technology use: an empirical study of knowledge workers. MIS Q. (2003)Google Scholar
  29. 29.
    Mącik, R.: The adoption of the internet of things by young consumers – an empirical investigation. Econ. Environ. Stud. 17(42), 363–388 (2017)CrossRefGoogle Scholar
  30. 30.
    MINECOM Antecedents for the revision of the classification criteria of the SME Statute; Santiago, Chile (2014)Google Scholar
  31. 31.
    Dijkstra, T.K., Henseler, J.: Consistent partial least squares path modeling. MIS Q. 39, 297–316 (2017)CrossRefGoogle Scholar
  32. 32.
    Parasuraman, A., Colby, C.: Techno-ready marketing: how and why your customers adopt technology. J. Consum. Mark. (2002)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Patricio E. Ramírez-Correa
    • 1
    Email author
  • Elizabeth E. Grandón
    • 2
  • Jorge Arenas-Gaitán
    • 3
  • F. Javier Rondán-Cataluña
    • 3
  • Alejandro Aravena
    • 4
  1. 1.Escuela de IngenieríaUniversidad Católica del NorteCoquimboChile
  2. 2.Departamento de Sistemas de InformaciónUniversidad del Bío-BíoConcepciónChile
  3. 3.Departamento de Administración de Empresas y MarketingUniversidad de SevillaSevilleSpain
  4. 4.Bioforest S.ACoronelChile

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