Analisis faktor adopsi aplikasi mobile berdasarkan pengalaman, usia dan jenis kelamin menggunakan UTAUT2

Raden Budiarto

Abstract


Tulisan ini menganalisis faktor adopsi mobile berdasarkan kriteria pengalaman, usia dan jenis kelamin. Penelitian ini merupakan eksplorasi dan pengembangan lanjutan dari model UTAUT2 (Unified Theory of Acceptance and Use of Technology). Beberapa variabel seperti kebiasaan dan kecemasan telah ditambahkan untuk menjelaskan penerimaan teknologi pada sisi konsumen. Di samping itu variabel moderator pengalaman, usia dan jenis kelamin telah dihipotesiskan pengaruhnya. Data yang digunakan penelitian ini diperoleh hasil pengolahan kuesioner dengan sampel convenient yang melibatkan partisipasi 384 responden. Data yang terkumpul selanjutnya diolah dengan Pemodelan Persamaan Struktur (PPS) atau Structural Equation Modelling (SEM) menggunakan alat bantu aplikasi IBM SPPS 21 dan Amos 22. Hasil dari penelitian ini telah menunjukkan hasil uji empiris yang telah mendukung model teoritis yang diajukan. Dibandingkan dengan hasil penelitian terdahulu, hasil penelitian ini menunjukkan peran dominan nilai harga dan motivasi hedonis sebagai penentu pada niat perilaku. Efek nilai harga berbanding terbalik dengan niat perilaku sedangkan motivasi hedonis berbanding lurus dengan niat perilaku. Implikasi temuan dari variabel moderati yakni pengalaman, usia dan jenis kelamin juga ditemukan memiliki efek terhadap jenis adopsi aplikasi yang digunakan.

Kata kunci: aplikasi mobile, analisis pasar, adopsi teknologi, penerimaan teknologi, UTAUT.

   

   

 

 

This paper analyzes mobile adoption factors based on age, gender and experience criteria. This study is an advanced development of UTAUT2 (Unified Theory of Acceptance and Use of Technology) model, that applied in the context of adoption mobile applications. There are some variables such as habits and anxiety have been added to explain the acceptance of technology on the consumer view. In addition, moderator variable age, gender and using experience have been hypothesized. The data used in this study obtained from the questionnaire using the method of convenient sampling with involved the participation of 384 respondents. The collected data is then analyzed by the Structural Equation Modelling (SEM) using IBM SPPS version 21 and Amos version 22 program tools. The results of this study show that the results supported the proposed theoretical model. Compared with the results of previous studies, the results of this study indicate the effect of price value and hedonic motivation as a determinant of behavioral intent. The effect of the value of the price is inversely proportional to the behavioral intention while the hedonic motivation is directly proportional to the behavioral intention. Implications of findings from moderate variables i.e. experience, age and gender were also found to influence the type of adoption of the applications used.

Keywords: Mobile application, market analysis, UTAUT, technology acceptance, technology adoption.

    

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References


Ajzen, I. (2002). Perceived Behavioral Control, Self‐Efficacy, Locus of Control, and the Theory of Planned Behavior. Journal of Applied Social Psychology, 32(4), 665-683.

Ajzen, I. (2002). Residual Effects of Past on Later Behavior: Habituation and Reasoned Action Perspectives. Personality and Social Psychology Review, 6(2), 107-122.

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior (1st ed.). Englewood Cliffs: Prentice-Hall.

Ajzen, I., & Fishbein, M. (2005). The Influence of Attitudes on Behavior, in The Handbook of Attitudes. Erlbaum: Mahwah.

Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244-254.

Benbasat, I., & Barki, H. (2007). Quo vadis, TAM? Journal of the Association for Information Systems, 8(4), 211-218.

Brown, S. A., Venkatesh, V., & Goyal, S. (2014). Expectation confirmation in information systems research: A test of six competing models. MIS Quarterly, 38(3), 729-756.

Brown, S., & Venkatesh, V. (2005). A Model of Adoption of Technology in the Household: A Baseline Model Test and Extension Incorporating Household Life Cycle. MIS Quarterly, 29(3), 205-218.

Budiarto, R. (2013). Meta-analisis TAM: Analisis pengaruh norma subjektif, kategori teknologi, status respoden dan nilai budaya terhadap penggunaan teknologi. Jak-Stik.

Chau, P. Y., & Hui, K. L. (1998). Identifying early adopters of new IT products: A case of Windows 95. Information & Management, 33(5), 225-230.

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340.

Deaux, K., & Lewis, L. L. (1984). Structure of gender stereotypes: Interrelationships among components and gender label. Journal of Personality and Social Psychology, 46(5), 991-1004.

El-Qadri, Z. M., & Wijaya, T. (2013). Panduan Teknik Statistik SEM & PLS dengan SPSS AMOS (2nd ed.). Yogyakarta: Cahaya Atma Pustaka.

Gabby, M. (2011). Tingkat efektivitas sistem informasi Remote Trading menggunakan metode UTAUT pada PT Ciptadana Securities. Jakarta: Universitas Bina Nusantara.

Garson, G. D. (2015). Structural Equation Modeling. Thousand Oaks, CA: SAGE Publications.

Group, S. (2014). The Standish Group Report Chaos. London: Project Smart. Diambil kembali dari https://www.projectsmart.co.uk/white-papers/chaos-report.pdf

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th ed.). New York: Peason International.

Handayani, R. (2007). Analisis faktor-faktor yang mempengaruhi minat pemanfaatan sistem informasi dan penggunaan sistem informasi (studi empiris pada perusahaan manufaktur di Bursa Efek Jakarta). Jurnal Akuntansi dan Keuangan, 9(2), 76-88.

Henning, M., & Jardim, A. (1977). The Managerial Woman (Vol. 7). Garden City, NY: Anchor Press.

Hubona, G., & Cheney, P. H. (2004). System Effectiveness of Knowledge-base Technology. International Conference of System Science, (hal. 532-541).

Kim, S. S., Malhotra, N. K., & Narasimhan, S. (2005). Two Competing Perspectives on Automatic Use: A Theoretical and Empirical Comparison. Information Systems Research, 16(4), 418-432.

Lee, H.‐J., Cho, H. J., Xu, W., & Fairhurst, A. (2010). The influence of consumer traits and demographics on intention to use retail self‐service checkouts. Marketing Intelligence & Planning, 28(1), 46-58.

Lee, Y., Kozar, K. A., & Larsen, K. R. (2003). The Technology Acceptance Model: Past, Present, and Future. Communications of the Association for Information Systems, 12(50), 752-780.

Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705-737.

Mathieson, K. (1991). Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior. Information Systems Research, 2(3), 173 – 191.

Morris, M. G., Venkatesh, V., & Ackerman, P. L. (2005). Gender and Age Differences in Employee Decisions About New Technology: An Extension to the Theory of Planned Behavior. IEEE Transactions on Engineering Management, 52(1), 69-84.

Murray, K. B., & Häubl, G. (2007). Explaining Cognitive Lock-In: The Role of Skill-Based Habits of Use in Consumer Choice. Journal of Consumer Research, 34(1), 77-88.

Murtadho, M. A., & Wahid, F. (2016). Permasalahan Implementasi Sistem Informasi Di Perguruan Tinggi Swasta. Register: Jurnal Ilmiah Teknologi Sistem Informasi, 2(1), 17-21.

Murugesh-Warren, A., Sudbury, D., Saeed, A., Nnajiuba, U., Mashayekhi, S., Abdel-Gadir, S., . . . Cox, B. (2015). An extension of the UTAUT 2 with a focus of age in healt What do different ages want? International Journal of Integrated Care, 15, 1-3.

Mustakini, J. H. (2008). Metode Penelitian Sistem Informasi (1st ed.). Yogyakarta: Andi.

Notani, A. S. (1998). Moderators of Perceived Behavioral Control's Predictiveness in the Theory of Planned Behavior: A Meta‐Analysis. Journal of Consumer Psychology, 7(3), 247-271.

Peng, X., Zhao, Y., & Zhu, Q. (2014). Understanding post adoption switching behavior for mobile instant messaging application in China: Based on migration theory. PACIS (hal. 1-11). Chengdu, China: Association for Information Systems.

Pressman, R. S., & Maxim, B. R. (2014). Software Engineering: A Practitioner's Approach (8th ed.). New York: McGraw-Hill Higher Education.

Ramdhani, A. (2009). Analisis adopsi teknologi komputer dengan pendekatan structural equation modeling: studi empiris pada asisten dosen Universitas Indonesia. Jakarta: Fakultas Ilmu Komputer Universitas Indonesia.

Sam, H. K., Othman, A. E., & Nordin, Z. S. (2005). Computer Self-Efficacy, Computer Anxiety, and Attitudes toward the Internet: A Study among Undergraduates in Unimas. Journal of Educational Technology & Society, 8(4), 205-219.

Sedana, I. G., & Wijaya, S. W. (2010). UTAUT Model for Understanding Learning Management System. Internetworking Indpnesia Journal, 2(2), 27-32.

Slama, M. E., & Tashchian, A. (1985). Selected Socioeconomic and Demographic Characteristics Associated with Purchasing Involvement. Journal of Marketing, 49(1), 72-82.

Van Der Heijden, H. (2004). User Acceptance of Hedonic Information Systems. MIS Quarterly, 28(4), 695-704.

Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273-315.

Venkatesh, V., & Morris, M. (2000). Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior. MIS Quarterly, 115-139.

Venkatesh, V., Davis, F. D., & Morris, M. G. (2007). Dead Or Alive? The Development, Trajectory And Future Of Technology Adoption Research. Journal of the Association for Information Systems, 8(4), 267-286.

Venkatesh, V., Morris, & Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 3(27), 425-478.

Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157-178.

Widhiarso, W. (2012, Juni 18). Reliabilitas dan Validitas Konstruk dalam Pemodelan Persamaan Struktural (SEM). Yogyakarta, Yogyakarta, Indonesia: Fakultas Psikologi Universitas Gadjah Mada. Diambil kembali dari http://wahyupsy.blog.ugm.ac.id/2012/06/18/reliabilitas-dan-validitas-konstruk-dalam-pemodelan-persamaan-struktural-sem/

Widiatmika, I. M., & Sensuse, D. I. (2008). Pengembangan model penerimaan teknologi internet oleh pelajar dengan menggunakan konsep Technology Acceptance Model (TAM). Jurnal Sistem Informasi, 4(2), 81-92.




DOI: https://doi.org/10.26594/register.v3i2.830

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