DETERMINING FACTORS OF INTEREST IN THE USE OF TECHNOLOGY READNESS BASED MULTI LANE FREE FLOW (MLFF)

Authors

  • Arshad Yahya Harnanda Master of Transportation Systems and Engineering, Gadjah Mada University, Yogyakarta, Indonesia
  • Sigit Priyanto Master of Transportation Systems and Engineering, Gadjah Mada University, Yogyakarta, Indonesia
  • Muhammad Zudhy Irawan Master of Transportation Systems and Engineering, Gadjah Mada University, Yogyakarta

DOI:

https://doi.org/10.29040/ijebar.v6i4.7565

Abstract

One of the countries with the most vehicle users in the world is Indonesia. The increasing number of vehicle users causes traffic jams, especially in big cities. Toll roads are a solution to get to your destination quickly and avoid traffic jams. One of the smoothness on the toll road is influenced by the service time at the toll gate when making transactions. However, traffic jams at toll gates cannot be avoided due to the long transaction time at toll gates. The plan to implement Multi Lane Free Flow or multi-lane non-stop toll payments is a system that allows toll road users not to need to stop or slow down their vehicles for transactions at toll gates. Socialization and belief in new technology is the current focus. Therefore it is necessary to carry out an analysis of public interest in the implementation of the electronic transaction system that will be implemented, the response of toll road users and the interest of toll users to use contactless Multi Lane Free Flow (MLFF) technology. The method in this research is descriptive analysis to analyze the characteristics of the user towards the contactless system at toll gates based on Multi Lane Free Flow (MLFF) using the Modified UTAUT Model. This study was then analyzed using Moderate Linear Regression using SEM-PLS to find out the factors that influence the interest in using contactless Multi Lane Free Flow (MLFF) with the analysis of the effect of the variables Performance Expectancy, Effort Expectancy, Social Influence, Habit on the use of the new Multi Lane Free technology Flow (MLFF) by adding Technology Readness as a moderating variable using Partial Least Square (PLS). The results of the analysis show that the characteristics of the respondents are related to the interest in using MLFF which can be shown in terms of income, occupation, gender, age, frequency of use of toll roads, segments of toll road use and reasons for using toll roads and the UTAUT Model, namely Performance Expatancy and Social Influence, have an effect on interest in using technology. MLFF except for the Effort Expatancy and Habit variables. Technology Readiness also supports the influence of UTAUT (Performance Expectancy, Effort Expectancy, Social Influence, Habit) on Behavior Intention except that the Performance Expaectancy variable does not depend on Technology Readiness and from the analysis results the use of MLFF is more efficient when used in dense cities like Jabodetabek and less efficient when used in the area is not congested because there is no delay at the toll gate. Keywords: Multi Lane Free Flow , Model UTAUT , Technology Readiness , SEM-PLS

References

Ajzen, I. (1991). The Theory of Planned Behaviour, Organisational Behaviour and Human Decision Processes, Vol. 50 No. 2, pp. 179â€211.

Ajzen, I. and Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behaviour. Englewood Cliffs, NJ: Prentice-Hall.

Al-Gahtani, S.S., Hubona, G.S. and Wang, J. (2007). Information Technology (IT) in Saudi Arabia: Culture and the Acceptance and Use of IT. Information and Management [online]. 4(8), pp. 681-691.

A.M. Sardiman. 2011. Interaksi dan Motivasi Belajar Mengajar. PT Rajagrafindo: Jakarta

Ameen, A., & Ahmad, K. (2014). Strategi sistematis untuk memanfaatkan sistem informasi keuangan dalam memerangi korupsi secara elektronik. Di dalamKonferensi Internasional Manajemen Pengetahuan (KMICE) 2014, Malaysia(hal. 12-15). 12–15 Agustus 2014. Diperoleh darihttp: //www. kmice.cms.net.my/.

Bogart, W. V. D. and Wichadee, S. (2015). Exploring Students’ Intention to Use LINE for Academic Purposes Based on Technology Acceptance Model. International Review of Research in Open and Distributed Learning. 16(3), pp.65-85.

Brown, S.A., Dennis, A.R. and Venkatesh, V. (2016). Predicting Collaboration Technology Use: Integrating Technology Adoption and Collaboration Research. Journal of Management Information Systems. 27(2), pp. 9-53.

Chen, C., Fan, Y., & Farn, C. (2007). Predicting electronic toll collection service adoption : An integration of the technology acceptance model and the theory of planned behavior, 15, 300–311. https://doi.org/10.1016/j.trc.2007.04.004

Choi, H., Kim, Y.C. and Kim, J.W. (2011). Driving Factors of Post Adoption Behavior in Mobile Data Services. Journal of Business Research . 64(11), pp. 1212-1217.

Chong, A.Y.L. (2013). Predicting M-Commerce Adoption Determinants: A Neural Network Approach. Expert Systems with Applications 40(2), pp. 523-530.

Chong, A.Y.L., Chan, F.T.S. and Ooi, K.B. (2012). Predicting Consumer Decisions to Adopt Mobile Commerce: Cross Country Empirical Examination Between China and Malaysia. Decision Support Systems . 53(1), pp. 34-43

Chu, C., Zhu, C., Wang, C., & Zhang, M. (2013). ScienceDirect Electronic Toll Collection System Engineering Quality Inspection Evaluation and Control Method, 96(Cictp), 1420–1425. https://doi.org/10.1016/j.sbspro.2013.08.161

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008

Departemen Teknik Sipil dan Lingkungan., 2019, Pedoman Penulisan Tugas Akhir, Tesis, dan Disertasi, Universitas Gadjah Mada

Evaluation of Single Lane Free Flow ( SLFF ) for Electronic Toll Collection Evaluation of Single Lane Free Flow ( SLFF ) for Electronic Toll Collection System. (2021), (May 2019).

Hawkins, D. I. (n.d.). Building Marketing Strategy Consumer Behavior.

Holguín-veras, J., & Preziosi, M. (2011). Behavioral investigation on the factors that determine adoption of an electronic toll collection system : Passenger car users, 19, 498–509. https://doi.org/10.1016/j.trc.2010.07.005

Ghozali, I. (t.thn.). Structural Equation Modeling Metode Alternatif Dengan Partial Least Square. Semarang: Badan Penerbit Undip

Joewono, T. B., Effendi, B. A., Gultom, H. S. A., & Rajagukguk, R. P. (2017). ScienceDirect ScienceDirect ScienceDirect Influence of Personal Banking Behaviour on the Usage of the Electronic Influence of Personal Banking Behaviour on the Usage of the Electronic Card for Toll Road Payment Card for Toll Road Payment. Transportation Research Procedia, 25, 4454–4471. https://doi.org/10.1016/j.trpro.2017.05.355

Ghozali, I., dan Fuad. (2005) Structural Equation Modelling: Teori, Konsep dan Aplikasi. Semarang: Badan Penerbit Universitas Diponegoro

Groß, M. (2015). Mobile Shopping: A Classification Framework and Literature Review. International. Journal of Retail and Distribution Management. 43(3) pp.221 – 241.

Gruzd, A., Staves, K. and Wilk, A. (2012). Connected Scholars: Examining The Role of Social Media in Research Practices of Faculty Using The UTAUT Model. Computers in Human Behavior. 28(6), pp. 2340-2350.

Kotler, Philip dan Kevin Lane Keller (2012). Manajemen Pemasaran, Edisi 14, Jilid 1.Jakarta : PT . Indeks.

Kotler, Philip dan Keller. (2012). Manajemen Pemasaran, Edisi 13, Jilid 1. Jakarta: Erlangga

Kotler, P., dan Keller, K.L., (2009). Manajemen Pemasaran, PT. Indeks, Jakarta.

Kusuma, V. (2015). Pengembangan dan Analisis Kualitas Sistem Informasi Ekstrakulikuler Berbasis WEB dia SMANegeri 1 Purbalingga. Yogyakarta: UNY.

Marheni Eka Saputri, Trisha Gilang Saraswati, Farah Oktafani (2022). The Effect of Performance Expectation, Effort Expectancy, Social Influence, Perceived Risk, and Perceived Cost on The Intention of Using Mobile payment in Indonesia, Jurnal Sosioteknologi, Volume 21, No. 1.

Martin, H.S. and Herrero, A. (2012). Influence of The User’s Psychological Factors on The Online Purchase Intention in Rural Tourism: Integrating Innovativeness to the UTAUT Framework. Tourism Management [online]. 33(2), pp. 341-350.

Mufarrikoh, Z., 2019, Statistika Pendidikan (Konsep Sampling dan Uji Hipotesis), https://books.google.co.id/books?hl=en&lr=&id=hknWDwAAQBAJ&oi=fnd&pg=PR1&dq=macam+teknik+sampling+adalah&ots=g-2Nfcq43q&sig=CdoIYGYIVYcAZY2bV2fMe1LPZqs&redir_esc=y#v=onepage&q&f=false

Nassar, A. A. M., Othman, K., Nizah, M. A. B. M. (2019). The Impact of the Social Influence on ICT Adoption: Behavioral Intention as Mediator and Age as Moderator. International Journal of Academic Research in Business and Social Sciences, 9(11), 963–978.

Parasuraman, A., & Colby, C. L. (2014). Journal of Service Research, (June), 0–16. https://doi.org/10.1177/1094670514539730

Park, E. and Ohm, J. (2014). Factors Influencing Users’ Employment of Mobile Map Services. Telematics and Informatics . 31(2), pp. 253-265.

Pei Ying Chua, Sajad Rezaei, Man-Li Gu, YokeMoi Oh, Manimekalai Jambulingam (2018). Elucidating Social Networking Apps Decisions: Performance Expectancy, Effort Expectancy and Social Influence", Nankai Business Review International Quarterly, M. I. S. (2012). No Title, 36(1), 157–178.

Pertiwi, Ni Wayan Yogi, dan Dodik Ariyanto. (2017). Penerapan Model Utaut2 Untuk Menjelaskan Minat Dan Perilaku Penggunaan Mobile Banking di Kota Denpasar. E-Jurnal Akuntansi Universitas Udayana 18(2): 1369- 1397

Rizal, R S. (2018): Re-Evaluasi Penerapan Sistem Pengumpulan Tol Elektronis Di Indonesia, Tesis Program Studi Magister, Institut Teknologi Bandung.

Shrafat Ali Sair (2018). Effect of Performance Expectancy and Effort Expectancy on the Mobile Commerce Adoption Intention through Personal Innovativeness among Pakistani Consumers , Journal of Commerce and Social Sciences, Vol. 12 (2), 501-520

Sulieman, M., Sawsan, A. and Al-Majali, M. (2015). Electronic Library Services Acceptance and Use. The Electronic Library . 33(6), pp. 1100 – 1120.

Suseno. (2009). Analisis Faktor-Faktor Penerimaan Karyawan PT KAI (persero) terhadap Sistem E-Ticket di Semarang : Pendekatan TAM. Jurnal Jurusan Akuntansi Fakultas Ekonomi Universitas Diponegoro.

Taylor, D.G. and Strutton, D. (2010). Has E-Marketing Come of Age? Modelling Historical Influences on Postadoption Era Internet Consumer Behaviors. Journal of Business Research. 63(9), pp. 950-956.

Taylor, S. and Todd, P.A. (1995). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research. 6(2), pp. 144-176.

Venkatesh, V. (2000). Determinants of Perceived Ease of Use : Integrating Control , Intrinsic Motivation , and Emotion into the Technology Acceptance Model, 1997, 342–365.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478. https://doi.org/10.2307/30036540

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 Quaterly, vol. 36, no. 1, pp. 157-178.

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 Quaterly, vol. 36, no. 1, pp. 157-178.

Valaei, N., Rezaei, S., Ismail, W. K. W. and Oh, Y. M. (2016). The Effect of Culture on Attitude Towards Online Advertising and Online Brands: Applying Hofstede's Cultural Factors to Internet Marketing, International Journal of Internet Marketing and Advertising, Vol. 10 (4), pp. 270-301.

Venkatesh, V., Michael, G., Morris, G. B., Davis, F. D. D. (2003). User Acceptance of Information Technology : Toward a Unified View. MIS Quarterly, 27(3), 425–478.

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

Wei, T.T., Marthandan, G., Chong, A.Y.L., Ooi, K.B. and Arumugam, S. (2009). What Drives Malaysian Mcommerce Adoption? An Empirical Analysis. Industrial Management and Data System. 109(3) pp. 370-388.

Wong, C.H., Tan, G.W.H., Loke, S.P. and Ooi, K.B. (2015). Adoption of Mobile Social Networking Sites For Learning. Online Information Review . 39(6), pp.762 – 778.

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Published

2022-12-29

How to Cite

Harnanda, A. Y., Priyanto, S., & Irawan, M. Z. (2022). DETERMINING FACTORS OF INTEREST IN THE USE OF TECHNOLOGY READNESS BASED MULTI LANE FREE FLOW (MLFF). International Journal of Economics, Business and Accounting Research (IJEBAR), 6(4). https://doi.org/10.29040/ijebar.v6i4.7565

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