Effect of the Rise in Online Motorcycle Taxi Services on the Number of Motorcycles using the Interrupted Time Series Method

Authors

  • Yovita Fabriska Laras Anindityas Parahyangan Catholic University
  • M. Rizki Institut Teknologi Nasional Bandung
  • T.B. Joewono Parahyangan Catholic University

DOI:

https://doi.org/10.9744/ced.23.2.123-130

Keywords:

number of motorcycles, government policy, online motorcycle taxis, interrupted time series method

Abstract

The substantial growth of motorcycle users in Indonesia is hypothesized to be influenced by a government policy on motorcycle purchase waivers and the massive growth of online motorcycle taxis. This study aims to analyse the relationship between the emergence of online motorcycle taxis and government policy changes towards the number of motorcycles and compare the estimation model seen from the consumer and sales sides. The data were collected from the Indonesian Bureau of Statistics, Motorcycle Industry Association, and World Bank. Several estimation models were built using the interrupted time series method. The results showed that changes in government policy and income per capita significantly increased the number of motorcycles. However, the emergence of online motorcycle taxis negatively affected the increasing number of motorcycles. The results also showed that models with data representing motorcycle usage behavior provided better results than the model with motorcycle sales.

References

Zukhruf, F., Frazila, R.B., and Wibowo, S.S., Efektivitas Jalur Sepeda Motor Pada Jalan Perkotaan Menggunakan Model Simulasi-Mikro, Jurnal Transportasi, 10(1), 2010, pp. 23–32.

Gómez-Gélvez, J.A. and Ubando, C., Joint Disaggregate Modeling of Car and Motorcycle Ownership: Case study of Bogotá, Colombia, Transportation Research Record, 2451, 2014, pp. 149–156.

Nishitateno, S. and Burke, P.J., The Motorcycle Kuznets Curve, 2014/04, 2014.

Chamon, M., Mauro, P., and Okawa, Y., Mass Car Ownership in the Emerging Market Giants, Economic Policy, 23(54), 2008, pp. 243–296.

Wang, Y., Teter, J., and Sperling, D., China’s Soaring Vehicle Population: Even Greater than Forecasted?, Energy Policy, 39(6), 2011, pp. 3296–3306.

OtoDetik, Kecelakaan Tak Pernah Turun, Penga-mat: Setop Produksi Motor 80 cc ke atas, 2020. https://oto.detik.com/motor/d-4920769/kecelakaan-tak-pernah-turun-pengamat-setop-pro-duksi-motor-80-cc-ke-atas/1 (accessed Aug. 13, 2020).

IBS, Perkembangan Jumlah Kendaraan Bermotor menurut Jenis, Indonesian Bureau of Sta-tistics, 2019. https://www.bps.go.id/linkTable Dinamis/view/id/1133 (accessed Aug. 08, 2020).

Wadud, Z., The Effects of E-Ridehailing on Motorcycle Ownership in an Emerging-Country Megacity, Transportation Research Part A: Policy and Practice, 137(March), 2020, pp. 301–312.

Shaheen, S., Chan, N., Bansal, A., and Cohen, A., Shared Mobility. Definitions, Industry Develop-ments, and Early Understanding, 2015, p. 30.

Aziah, A. and Adawia, P.R., Analisis Perkembangan Industri Transportasi Online di Era Inovasi Disruptif (Studi Kasus PT Gojek Indone-sia), Cakrawala, 18(2), 2018, pp. 149–156.

DetikInet, Awal Mula Transportasi Online Menjamur di Indonesia, Detik inet, 2017. https://inet.detik.com/cyberlife/d-3609781/awal-mula-transportasi-online-menjamur-di-indonesia? utm_source=copy_url&utm_campaign=detikcomsocmed&utm_medium=btn&utm_content=inet (accessed Aug. 13, 2020).

Irawan M.Z., Belgiawan, Tarigan, A.K.M., and Wijanarko, F., To Compete or Not Compete: Exploring the Relationships between Motorcycle-Based Ride-Sourcing, Motorcycle Taxis, and Public Transport in The Jakarta Metropolitan Area, Transportation, 47(5), 2020, pp. 2367–2389.

Azzuhri, A.A., Syarafina, A., Yoga, F.T., and Amalia, R., A Creative, Innovative, and Solutive Transportation for Indonesia with Its Setbacks and How to Tackle Them: A Case Study of the Phenomenal GOJEK, Review of Integrative Business and Economics Research, 7(1), 2018, pp. 59–67.

Mawar, G.P., Otu, M.N., and Suprayatna, N., Analisis Pengaruh Kualitas Layanan dan Harga Transportasi Online terhadap Kepuasan Mahasiswa Pengguna Ubermotor di Provinsi Banten, 2(3), 2020.

Annisa, F.M., Hubungan Preferensi Pengguna terhadap Intensitas Penggunaan Transportasi Online di Kota Bandung, Universitas Katolik Parahyangan, 2019.

Riandiatmi, O., Persepsi Masyarakat Kota Bandung dan Kota Bangkok terhadap Transportasi Online, Universitas Katolik Parahyangan, 2019.

Rizki, M., Joewono, T.B., and Belgiawan, P.F., Travel Experience and Multitasking of Toll Road Users in Jakarta Metropolitan Area, Indonesia: An Investigation for Passenger of Private Car, Taxi, and Ridesourcing, Journal of the Eastern Asia Society for Transportation Studies, 13, 2019, pp. 523–541, doi: 10.11175/easts.13.523.

MIA, Statistic Distribution, Motorcycle Industry Association, 2020. https://www.aisi.or.id/statistic/ (accessed Nov. 23, 2020).

Syah, A., Ekonomi untuk SMA dan MA kelas X. ESIS, 2006.

Fahrina, A.R., Pengaruh Pendapatan Daerah dan Populasi Penduduk terhadap Kondisi Keuangan Pemerintah Daerah (Studi pada Pemerintah Daerah Provinsi/Kabupaten/Kota di Wilayah Jawa Barat Tahun Anggaran 2016-2018), 2020.

Sitio, B.S., Pengaruh Variabel Ekonomi terhadap Jumlah Sepeda Motor di Indonesia, Universitas Negeri Semarang, 2015.

Astutik, Y., 21,7 Juta Masyarakat Indonesia pakai Transportasi Online, CNBC Indonesia, 2020. https://www.cnbcindonesia.com/tech/20200 317150135-37-145529/217-juta-masyarakat-indonesia-pakai-transportasi-online (accessed Dec. 20, 2020).

Andriani, D., Jumlah Pengguna Aktif Gojek di Indonesia Setara dengan Aplikasi Ride-Sharing Terbesar Dunia, Bisnis.com, 2019. https://eko-nomi.bisnis.com/read/20190829/98/1141953/jumlah-pengguna-aktif-gojek-di-indonesia-setara-dengan-aplikasi-ride-sharing-terbesar-dunia (accessed Dec. 20, 2020).

Gojek, Kini Gojek Hadir di 167 Kota dan Kabupaten Indonesia, 2018. https://www.gojek.com/ blog/gojek/go-jek-dimana-mana/ (accessed Dec. 21, 2020).

Azka, R.M., Berapa Sih Jumlah Pengemudi Ojek Online? Simak Penelusuran Bisnis.com!, Bisnis. com, 2019. https://ekonomi.bisnis.com/read/ 20191112/98/1169620/berapa-sih-jumlah-penge- mudi-ojek-online-simak-penelusuran-bisnis.com (accessed Dec. 21, 2020).

Irawan, M.Z., Belgiawan, P.F., Joewono, T.B., and Simanjuntak, N.I.M., Do Motorcycle-Based Ride-Hailing Apps Threaten Bus Ridership? A Hybrid Choice Modeling Approach with Latent Variables, Public Transport, 12(1), 2019, pp. 207–231.

Rizki, M., Joewono, T.B., Belgiawan, P.F., and Irawan, M.Z., The Travel Behaviour of Ride-Sourcing Users, and Their Perception of the Usefulness of Ride-Sourcing Based On the Users’ Previous Modes of Transport: A Case Study in Bandung City, Indonesia, IATSS Research, 2020.

Tirachini, A., Ride-Hailing, Travel Behaviour and Sustainable Mobility: an International Review, Transportation, 47(4), 2020, pp. 2011–2047, doi: 10.1007/s11116-019-10070-2.

Rizki, M., Joewono, T., Belgiawan, P., and Prasetyanto, D., Exploring the Ride-Hailing Drivers’ Characteristics and Their Order Rejection Behavior in Bandung City, In: Mohammed B.S., Shafiq N., Rahman M. Kutty S., Mohamad H., Balogun AL. (eds) ICCOEE 2020. ICCOEE 2021. Lecture Notes in Civil Engineering, vol 132. Springer, Singapore. https://doi.org/10.1007/978-981-33-6311-3_98.

Bernal, J.L., Cummins, S., and Gasparrini, A., Interrupted Time Series Regression for the Evaluation of Public Health Interventions: a Tutorial, International Journal of Epidemiology, 46(1), 2017, pp. 348–355.

Fox, J. and Weisberg, S., An R Companion to Applied Regression, 3rd ed. SAGE Publications, Inc., 2019.

Breusch, T.S., Testing for Autocorrelation in Dynamic Linear Models, Australian Economic Paper, 17(31), 1978, pp. 334–355.

Box, G.E.P., Jenkins, G.M., and Reinsel, G.C., Time Series Analysis: Forecasting and Controls, Fourth, Canada: John Wiley & Sons, Inc, 2008.

Bartlett, M.S., On The Theoretical Specification and Sampling Properties of Autocorrelated Time-Series, Journal of the Royal Statistical Society, 8(1), 1946, pp. 27–41.

Zaenudin, A., Motor Pribadi Versus Naik Ojek Online, Mana Lebih Irit?, tirto.id, 2018. https://tirto. id/motor-pribadi-versus-naik-ojek-online-mana-lebih-irit-cLLz (accessed Jan. 04, 2020).

Downloads

Published

2021-10-05

How to Cite

Anindityas, Y. F. L., Rizki, M., & Joewono, T. (2021). Effect of the Rise in Online Motorcycle Taxi Services on the Number of Motorcycles using the Interrupted Time Series Method. Civil Engineering Dimension, 23(2), 123-130. https://doi.org/10.9744/ced.23.2.123-130