Success factors of information technologies in the competitiveness of sugar mills: Mexico.
DOI:
https://doi.org/10.24054/face.v22i1.1478Keywords:
innovation, information technologies, AFE, factors, competitivenessAbstract
Currently, technological progress is present in most of the commercial activities, the objective was to determine the success factors that affect the acceptance of IT for the competitiveness of sugar mills located in the Huasteca Region of Mexico, by their managers. Through the quantitative method, an exploratory factor analysis was carried out by means of a questionnaire to 80 managers of sugar mills in the Huasteca region of Mexico, where the construction of the factors related to the acceptance of information technologies and business competitiveness was validated.
Downloads
References
Abubakara, A. M., Hamzah, E., Maher, A. A., y Alev, E. (2019). Knowledge management, decision-making style and organizational performance. Journal of Innovation y Knowledge, 4, 109–114.
Adamides, E., y Karacapilidis, N. (2020). Information technology for supporting the development and maintenance of open innovation capabilities. Journal of Innovation and Knowledge, 5(1), 29–38. https://doi.org/10.1016/j.jik.2018.07.001
Aguirre, R. (2018). La influencia de la adopción de tecnologías de información en la capacidad de innovación desde la perspectiva del recurso humano en las Mipymes de software en Sonora, México. Investigación Administrativa, 48(122), 1–17.
Alderete, M., y Gutiérrez, L. (2012). TIC y productividad en las industrias de servicios en Colombia. Lecturas de Economía, 77, 163–188.
Baby, A., y Kannammal, A. (2019). Network Path Analysis for developing an enhanced TAM model: A user-centric e-learning perspective. Computers in Human Behavior, 107(July), 106081. https://doi.org/10.1016/j.chb.2019.07.024
Calabretta, G., Gemser, G., y Wijnberg, N. M. (2017). The Interplay between Intuition and Rationality in Strategic Decision Making: A Paradox Perspective. Organization Studies, 38(3–4), 365–401. https://doi.org/10.1177/0170840616655483
Cano-Pita, G. E. (2018). Las TICs en las empresas: evolución de la tecnología y cambio estructural en las organizaciones. Dominio de las Ciencias, 4(1), 499. https://doi.org/10.23857/dc.v4i1.762
Davis. (1986). A technology acceptance model for empirically testing new end-user information systems: theory and results. Massachusetts Institute of Technology.
Davis. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. 13(3), 319–340.
Davis, N., y O’Halloran, D. (2018). La cuarta revolución industrial impulsa la globalización 4.0. Foro Económico Mundial. https://es.weforum.org/agenda/2018/11/la-cuarta-revolucion-industrial-impulsa-la-globalizacion-4-0/
Ferratt, T. W., Prasad, J., y Dunne, E. J. (2018). Fast and Slow Processes Underlying Theories of Information Technology Use. 19, 1–22. https://doi.org/10.17705/1jais.00477
Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage: Vol. 4ta. ed. http://www.fb4all.com/download/ebooks/statistics/%23Discovering Statistics Using SPSS 2013.pdf
Fishbein, M., y Ajzen, I. (1975). Attitude formation_ch6. In Belief, Attitude, Intention, and Behavior, An Introduction to Theory and Research (pp. 216–287). https://doi.org/10.1016/B978-0-12-375000-6.00041-0
Gao, S., Guo, Y., Chen, J., y Li, L. (2016). Factors affecting the performance of knowledge collaboration in virtual team based on capital appreciation. Information Technology and Management, 17(2), 119–131. https://doi.org/10.1007/s10799-015-0248-y
George, D., y Mallery, P. (2003). SPSS for Windows Step by Step: Answers to Selected Exercises. In A Simple Guide and Reference. https://doi.org/9780335262588
Gnambs, T., y Appel, M. (2019). Are robots becoming unpopular? Changes in attitudes towards autonomous robotic systems in Europe. Computers in Human Behavior, 93, 53–61. https://doi.org/10.1016/j.chb.2018.11.045
Griffin, J. M., Hellmich, T. R., Pasupathy, K. S., Funni, S. A., Pagel, S. M., Srinivasan, S. S., Heaton, H. A., Sir, M. Y., Nestler, D. M., Blocker, R. C., Hawthorne, H. J., Koenig, K. R., Herbst, K. M., y Hallbeck, M. S. (2020). Attitudes and Behavior of Health Care Workers Before, During, and After Implementation of Real-Time Location System Technology. Mayo Clinic Proceedings: Innovations, Quality y Outcomes, 4(1), 90–98. https://doi.org/10.1016/j.mayocpiqo.2019.10.007
Hee, J. H., Ha Kyung, L., y Ho Jung, C. (2017). Understanding usage intention in innovative mobile app service: Comparison between millennial and mature consumers. Computers in Human Behavior, 73, 353–361. https://doi.org/10.1016/j.chb.2017.03.051
Hussein, Z. (2017). Leading to Intention: The Role of Attitude in Relation to Technology Acceptance Model in E-Learning. Procedia Computer Science, 105(December 2016), 159–164. https://doi.org/10.1016/j.procs.2017.01.196
Hwang, Y., Al-Arabiat, M., Shin, D. H., y Lee, Y. (2016). Understanding information proactiveness and the content management system adoption in pre-implementation stage. Computers in Human Behavior, 64, 515–523. https://doi.org/10.1016/j.chb.2016.07.025
Jahanmir, S. F., Silva, G. M., Gomes, P. J., y Gonçalves, H. M. (2019). Determinants of users’ continuance intention toward digital innovations: Are late adopters different? Journal of Business Research, November, 1–9. https://doi.org/10.1016/j.jbusres.2019.11.010
Khan, S. S., Zhao, K., Kumar, R., y Stylianou, A. (2017). Examining Real Options Exercise Decisions in Information Technology Investments. Journal of the Association for Information Systems, 18(5), 372–402.
Kim, J., y Gambino, A. (2016). Do we trust the crowd or information system? Effects of personalization and bandwagon cues on users’ attitudes and behavioral intentions toward a restaurant recommendation website. Computers in Human Behavior, 65, 369–379. https://doi.org/10.1016/j.chb.2016.08.038
Macedo, I. M. (2017). Predicting the acceptance and use of information and communication technology by older adults: An empirical examination of the revised UTAUT2. Computers in Human Behavior, 75, 935–948. https://doi.org/10.1016/j.chb.2017.06.013
Manis, K. T., y Choi, D. (2019). The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware. Journal of Business Research, 100(October 2018), 503–513. https://doi.org/10.1016/j.jbusres.2018.10.021
Mikalef, P., y Pateli, A. (2017). Information technology-enabled dynamic capabilities and their indirect effect on competitive performance: Findings from PLS-SEM and fsQCA. Journal of Business Research, 70, 1–16. https://doi.org/10.1016/j.jbusres.2016.09.004
Orantes, S. (2011). Viabilidad del “Modelo de Aceptación de la Tecnología” en las empresas mexicanas. Una aproximación a las actitudes y percepciones de los usuarios de las tecnologías de la información. Revista Digital Universitaria, 12, 1–15.
Prasanna, R., y Huggins, T. J. (2016). Factors affecting the acceptance of information systems supporting emergency operations centres. Computers in Human Behavior, 57, 168–181. https://doi.org/10.1016/j.chb.2015.12.013
Ratten, V. (2016). Continuance use intention of cloud computing: Innovativeness and creativity perspectives. Journal of Business Research, 69(5), 1737–1740. https://doi.org/10.1016/j.jbusres.2015.10.047
Razavi, S. M. H. R., Nargesi, G. R., Hajihoseini, H., y Akbari, M. (2016). The impact of technological innovation capabilities on competitive performance of Iranian ICT firms. Iranian Journal of Management Studies, 9(4), 855–882. https://doi.org/10.1108/17585521011059893
Rezvani, A., Khosravi, P., y Dong, L. (2017). Motivating users toward continued usage of information systems: Self-determination theory perspective. Computers in Human Behavior, 76, 263–275. https://doi.org/10.1016/j.chb.2017.07.032
Ringle, C. M., Sarstedt, M., Mitchell, R., y Gudergan, S. P. (2018). Partial least squares structural equation modeling in HRM research. The International Journal of Human Resource Management, 31(12), 1617–1643. https://doi.org/10.1080/09585192.2017.1416655
Ryan, R. M., y Deci, E. L. (2000). Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions. Contemporary Educational Psychology, 25, 54–67. https://doi.org/10.1006/ceps.1999.1020
Sari, E. F., Nasution, R. A., y Kosala, R. (2019). The effect of the use of the online transportation application on public transport and private vehicle ownership: The case of the Jakarta metropolitan area. Transportation Research Interdisciplinary Perspectives, 1, 100018. https://doi.org/10.1016/j.trip.2019.100018
Sepasgozar, S. M. E., Hawken, S., Sargolzaei, S., y Foroozanfa, M. (2019). Implementing citizen-centric technology in developing smart cities: A model for predicting the acceptance of urban technologies. Technological Forecasting y Social Change, 142, 105–116. https://doi.org/10.1016/j.techfore.2018.09.012
Shiau, W., y Chau, P. Y. K. (2016). Understanding behavioral intention to use a cloud computing classroom: A multiple model comparison approach. Information y Management, 53(3), 355–365. https://doi.org/10.1016/j.im.2015.10.004
Tornatzky, L. G., y Fleischer, M. (1990). The Processes of Technological Innovation. Lexington Books, Lexington, MA.
Ullah, F., Raza, S. A., y Azeem, M. (2020). Social media and unemployment: Evidence from Pakistan. Social Indicators Research, 151(3), 951–967. https://doi.org/10.1007/s11205-020-02391-6
Venkatesh, V., Morris, M. G., Davis, G. B., y Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Downloads
Published
Versions
- 2022-05-29 (5)
- 2022-05-29 (4)
- 2022-05-29 (3)
- 2023-03-22 (2)
- 2022-09-29 (1)
How to Cite
Issue
Section
License
Copyright (c) 2022 FACE: Revista de la Facultad de Ciencias Económicas y Empresariales
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.