Predicting Students’ Behavioral Intention to Use Open Source Software: A Combined View of the Technology Acceptance Model and Self-Determination Theory
Source abstract
Abstract
This study focuses on students’ behavioral intention to use Open Source Software (OSS). The article examines how students, who were trained in OSS, are motivated to continue using it. A conceptual model based on Self-Determination Theory and the Technological Acceptance Model (TAM) was defined in order to test the behavioral intention to use OSS, comprising six constructs: (1) autonomy, (2) competence, (3) relatedness, (4) perceived ease of use, (5) perceived usefulness and (6) behavioral intention to use. A survey was designed for data collection. The participants were recent secondary school graduates, and all of them had received mandatory OSS training. A total of 352 valid responses were used to test the proposed structural model, which was performed using the Lisrel software. The results clearly confirmed the positive influence of the intrinsic motivations; autonomy and relatedness, to improve perceptions regarding the usefulness and ease of use of OSS, and; therefore, on behavioral intention to use OSS. In addition, the implications and limitations of this study are considered.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Technology Adoption and User Behaviour · Open Source Software Innovations · Knowledge Management and Sharing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Management and Marketing, Universidad Pablo de Olavide, 41013 Seville, Spain
References (100+)
Show source-provided references
1. Students’ ICT self-efficacy and computer and information literacy: Determinants and relationships10.1016/j.compedu.2017.11.011 ↗
2. Is it the way they use it? Teachers, ICT and student achievement10.1016/j.econedurev.2016.11.007 ↗
3. Factors that explain the use of ICT in secondary-education classrooms: The role of teacher characteristics and school infrastructure10.1016/j.chb.2016.11.057 ↗
4. Balogh, Z., and Kuchárik, M. (2019). Predicting Student Grades Based on Their Usage of LMS Moodle Using Petri Nets. Appl. Sci., 9.10.3390/app9204211 ↗
5. All-Learning: The state of the art of the models and the methodologies educational with ICT10.1016/j.tele.2017.10.004 ↗
6. A multilevel analysis of what matters in the training of pre-service teacher’s ICT competencies10.1016/j.compedu.2018.03.002 ↗
7. Multivariate characterization of university students using the ICT for learning10.1016/j.compedu.2018.03.004 ↗
8. A new educational pattern in response to new technologies and sustainable development. Enlightening ICT skills for youth employability in the European Union10.1016/j.tele.2017.09.014 ↗
9. Competitive prospects of graduate program on the integration of ICT superiority, higher education, and international aid10.1016/j.tele.2017.07.009 ↗
10. Plus Minus of ICT Usage in Higher Education Students10.1016/j.sbspro.2013.10.392 ↗
11. Ebardo, R.A. (2018, January 28–30). Visibility and Training in Open Source Software Adoption: A Case in Philippine Higher Education. Proceedings of the 8th International Workshop on Computer Science and Engineering, Bangkok, Thailand.
12. Cross-national analysis of the relation of eGovernment maturity and OSS growth10.1016/j.techfore.2015.06.024 ↗
13. Exploring the determinants of the OSS market potential: The case of the Apache web server10.1016/j.telpol.2011.11.018 ↗
14. Adopting open-source software applications in U.S. higher education: A cross-disciplinary review of the literature10.3102/0034654308325691 ↗
15. Open source software: The effects of training on acceptance10.1016/j.chb.2015.03.029 ↗
16. OSS popularity: Understanding the relationship between user-developer interaction, market potential and development stage
17. Knowledge management in OSS communities: Relationship between dense and sparse network structures10.1016/j.ijinfomgt.2017.09.004 ↗
18. Uncovering the relationship between OSS user support networks and OSS popularity10.1016/j.dss.2014.05.014 ↗
19. From closed source to open source software: Analysis of the migration process to Open Office10.1016/j.hitech.2017.10.008 ↗
20. Organizational adoption of open source software10.1016/j.jss.2011.09.037 ↗
21. Sustainability of Open Source software communities beyond a fork: How and why has the LibreOffice project evolved?10.1016/j.jss.2013.11.1077 ↗
22. How founders’ social capital affects the success of open-source projects: A resource-based view of project teams10.1016/j.elerap.2018.05.003 ↗
23. A Study on Growth Model of OSS Projects to estimate the stage of lifecycle10.1016/j.procs.2015.08.142 ↗
24. Open Source Software (OSS) Quality Assurance: A Survey Paper10.1016/j.procs.2015.07.236 ↗
25. Open source software (OSS) governance in the organization10.1016/j.clsr.2010.01.008 ↗
26. Higher education sub-cultures and open source adoption10.1016/j.compedu.2011.01.006 ↗
27. ICT for socio-economic development: A citizens’ perspective10.1016/j.im.2017.05.003 ↗
28. ICT Use in EU According to National Models of Behavior10.1016/j.sbspro.2015.11.407 ↗
29. Early adolescents’ use of information and communication technologies (ICTs) for social communication in 20 countries: Examining the roles of ICT-related behavioral and motivational characteristics10.1016/j.chb.2017.03.058 ↗
30. Malaquias, R.F., Malaquias, F.F.O., and Hwang, Y. (2018). Understanding technology acceptance features in learning through a serious game. Comput. Hum. Behav., 395–402.10.1016/j.chb.2018.06.008 ↗
31. A TAM-based approach to explore the effect of online experience on destination image: A smartphone user’s perspective
32. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology10.2307/249008 ↗
33. Fishbein, M., and Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, Addison-Wesley Reading.
34. Applying the TAM to travelers’ usage intentions of GPS devices10.1016/j.eswa.2010.11.047 ↗
35. The influence of perceived ease of use and perceived usefulness on the intention to use a suggested online advertising workflow
36. The intellectual development of the technology acceptance model: A co-citation analysis10.1016/j.ijinfomgt.2010.07.003 ↗
37. Does the technology acceptance model predict actual use? A systematic literature review10.1016/j.infsof.2009.11.005 ↗
38. Modeling Students’ Perceptions of Simulation-Based Learning Using the Technology Acceptance Model10.1016/j.ecns.2018.04.004 ↗
39. Informal tools in formal contexts: Development of a model to assess the acceptance of mobile technologies among teachers10.1016/j.chb.2015.07.002 ↗
40. Motivational factors that influence the acceptance of Moodle using TAM10.1016/j.chb.2010.06.011 ↗
41. User acceptance of information technology: Toward a unified view10.2307/30036540 ↗
42. Why do people use information technology? A critical review of the technology acceptance model10.1016/S0378-7206(01)00143-4 ↗
43. Extending the TAM for Green IT: A normative perspective10.1016/j.chb.2018.01.032 ↗
44. A review of technology acceptance and adoption models and theories10.1016/j.promfg.2018.03.137 ↗
45. Autonomy and morality: A Self-Determination Theory discussion of ethics10.1016/j.newideapsych.2017.06.001 ↗
46. Predicting the acceptance of MOOCs in a developing country: Application of task-technology fit model, social motivation, and self-determination theory10.1016/j.tele.2017.09.009 ↗
47. Examination of relationships among students’ self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs10.1016/j.compedu.2018.01.003 ↗
48. Mobile-Based Assessment: Integrating acceptance and motivational factors into a combined model of Self-Determination Theory and Technology Acceptance10.1016/j.chb.2016.11.020 ↗
49. The impact of basic human needs on the use of retailing self-service technologies: A study of self-determination theory10.1016/j.jretconser.2013.06.003 ↗
50. A theoretical extension of the technology acceptance model: Four longitudinal field studies10.1287/mnsc.46.2.186.11926 ↗
51. Technology acceptance model 3 and a research agenda on interventions10.1111/j.1540-5915.2008.00192.x ↗
52. Empirical investigation of e-learning acceptance and assimilation: A structural equation model10.1016/j.aci.2014.09.001 ↗
53. Assessing the moderating effect of gender differences and individualism-collectivism at individual-level on the adoption of mobile commerce technology: TAM3 perspective10.1016/j.jretconser.2014.09.006 ↗
54. Deci, E.L., and Ryan, R.M. (1985). Intrinsic Motivation and Self-Determination in Human Behavior, Planum.10.1007/978-1-4899-2271-7 ↗
55. Ryan, R.M., and Deci, E. (2017). Self-Determination Theory. Basic Psychological Needs in Motivation, Development, and Wellness, Guilford Press.10.1521/978.14625/28806 ↗
56. Intrinsic and extrinsic motivations: Classic definitions and new directions10.1006/ceps.1999.1020 ↗
57. Increasing collaborative, pro-environmental activism: The roles of Motivational Interviewing, self-determined motivation, and self-efficacy10.1016/j.jenvp.2018.06.004 ↗
58. Applying self-determination theory to the blood donation context: The blood donor competence, autonomy, and relatedness enhancement (Blood Donor CARE) trial10.1016/j.cct.2016.12.010 ↗
59. Creative writers’ experience of self-determination: An examination within the grounded theory framework10.1016/j.tsc.2014.06.004 ↗
60. How does performance-based financing affect health workers’ intrinsic motivation? A Self-Determination Theory-based mixed-methods study in Malawi10.1016/j.socscimed.2018.04.053 ↗
61. Exploring the working mechanisms of a web-based physical activity intervention, based on self-determination theory and motivational interviewing10.1016/j.invent.2015.11.003 ↗
62. The relationship between English language learners’ motivation and online self-regulation: A structural equation modelling approach10.1016/j.system.2018.05.003 ↗
63. Investigating the impact of Flipped Classroom on students’ learning experiences: A Self-Determination Theory approach10.1016/j.chb.2017.08.011 ↗
64. Emotional engagement in kindergarten and school children: A self-determination theory perspective10.1016/j.tine.2015.11.001 ↗
65. How perceptions of organizational politics influence self-determined motivation: The mediating role of work mood
66. A self-consistency motivation analysis of employee reactions to job insecurity: The roles of organization-based self-esteem and proactive personality10.1016/j.jbusres.2018.07.028 ↗
67. Sheldon, K.M., Turban, D.B., Brown, K.G., Barrick, M.R., and Judge, T.A. (2003). Applying Self-Determination Theory to Organizational Research. Research in Personnel and Human Resources Management (Research in Personnel and Human Resources Management, 22), Emerald Group Publishing Limited.10.1016/S0742-7301(03)22008-9 ↗
68. Motivational processes in the coach-athlete relationship: A multi-cultural self-determination approach10.1016/j.psychsport.2017.06.004 ↗
69. Bakker, A.B. (2013). Self-Determination Theory’s Contribution to Positive Organizational Psychology. Advances in Positive Organizational Psychology (Advances in Positive Organizational Psychology, 1), Emerald Group Publishing Limited.10.1108/S2046-410X(2013)1 ↗
70. Self-determination and persistence in a real-life setting: Toward a motivational model of high school dropout10.1037/0022-3514.72.5.1161 ↗
71. Motivation profiles at work: A self-determination theory approach10.1016/j.jvb.2016.07.004 ↗
72. A profile approach to self-determination theory motivations at work10.1016/j.jvb.2012.09.002 ↗
73. A test of hypotheses derived from self-determination theory among public sector employees10.1108/01425450910916814 ↗
74. Online brand community: Through the eyes of Self Determination Theory10.1108/IntR-01-2015-0017 ↗
75. Self-Regulation and the Problem of Human Autonomy: Does Psychology Need Choice, Self-Determination, and Will?10.1111/j.1467-6494.2006.00420.x ↗
76. Self-determination theory and the facilitation of intrinsic motivation, social development and well-being10.1037/0003-066X.55.1.68 ↗
77. Self-determination theory and the role of political interest in adolescents’ sociopolitical development10.1016/j.appdev.2017.03.008 ↗
78. Facilitating optimal motivation and psychological well-being across life’s domains10.1037/0708-5591.49.1.14 ↗
79. Autonomy as the guiding aim of entrepreneurship education10.1108/00400911011089006 ↗
80. Igniting students’ inner determination: The role of a need supportive climate10.1108/JEA-04-2017-0036 ↗
81. A self-determination theory perspective on customer participation in service development10.1108/JSM-01-2015-0053 ↗
82. Fun environmentalism!: Potential contributions of autonomy supportive psychology to sustainable lifestyles10.1108/14777831011025508 ↗
83. Principals’ leadership and teachers’ motivation: Self-determination theory analysis10.1108/09578231111129055 ↗
84. Motivating users toward continued usage of information systems: Self-determination theory perspective10.1016/j.chb.2017.07.032 ↗
85. Understanding e-learning continuance intention in the workplace: A self-determination theory perspective10.1016/j.chb.2007.06.001 ↗
86. Aesaert, K., van Braak, J., van Nijlen, D., and Vanderlinde, R. (2015). Primary school pupils’ ICT competences: Extensive model and scale development. Comput. Educ., 326–344.10.1016/j.compedu.2014.10.021 ↗
87. The effect of a mobile-application tool on biology students’ motivation and achievement in species identification: A Self-Determination Theory perspective10.1016/j.compedu.2016.12.011 ↗
88. Autonomy, competence, and relatedness in the classroom. Applying self-determination theory to educational practice10.1177/1477878509104318 ↗
89. Modeling and measuring attributes influencing DevOps implementation in an enterprise using structural equation modelling10.1016/j.infsof.2017.07.010 ↗
90. Relating motivation to information and communication technology acceptance: Self-determination theory perspective10.1016/j.chb.2015.05.021 ↗
91. The role of self-determination theory in explaining teachers’ motivation to continue to use e-learning technology10.1016/j.compedu.2009.06.001 ↗
92. An analysis of the dynamics of activity and travel needs in response to social network evolution and life-cycle events: A structural equation model10.1016/j.tra.2013.11.006 ↗
93. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error10.1177/002224378101800104 ↗
94. A Practical Guide to Factorial Validity Using Pls-Graph: Tutorial and Annotated Example
95. Understanding Information Systems Continuance: The Case of Internet-Based Learning Technologies10.1016/j.im.2008.02.005 ↗
96. Hair, J.F., Black, W.C., Babin, B.J., and Anderson, R.E. (2010). Multivariate Data Analysis, Prentice Hall. [7th ed.].
97. Jöreskog, K.G., and Sörbom, D. (2006). Lisrel 8.80 for Windows (Computer Software), Scientific Software International, Inc.
98. Structural equation modeling with Lisrel: Application in tourism10.1016/S0261-5177(98)00104-6 ↗
99. Evaluating estimation methods for ordinal data in structural equation modeling10.1007/s11135-007-9133-z ↗
100. Skrondal, A., and Rabe-Hesketh, S. (2004). Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models, Chapman & Hall/CRC.10.1201/9780203489437 ↗