Public Discourse and Digital Customer Experience in Online Motorcycle Taxi Services: A Multimethod Analysis

Ferel Rizqia Maulana; Asep Miftahuddin; Eka Surachman; Yoga Perdana; Budhi Pamungkas Gautama; Arciana Damayanti

doi:10.58905/apollo.v4i3.679

Authors

Ferel Rizqia Maulana Universitas Pendidikan Indonesia
Asep Miftahuddin Universitas Pendidikan Indonesia
Eka Surachman Universitas Pendidikan Indonesia
Yoga Perdana Universitas Pendidikan Indonesia
Budhi Pamungkas Gautama Universitas Pendidikan Indonesia
Arciana Damayanti Universitas Pendidikan Indonesia

DOI:

https://doi.org/10.58905/apollo.v4i3.679

Keywords:

Public Discourse, Digital Customer Experience, Online Motorcycle Taxi (Ojek Online), Social Network Analysis, Sentiment Analysis

Abstract

The digital technology has transformed the platform-based transportation services and now, digital customer experience is playing a pivotal role in the success of the service. But, there is a constant mismatch between what is expected from the services and what the users experience, which can be seen in the social media discourse. The goal of this study is to analyze the construction of digital customer experience, its communication and its impact on online motorcycle taxi services. The research uses a multi-method design, combining sentiment analysis, social network analysis, text network analysis, emotion classification, and trend analysis on social media discourse to get a comprehensive grasp of user-generated discourse and its complexity. The results show that the digital customer experience is multi-dimensional by nature, sometimes being characterized in a positive way and sometimes in a negative way, and the act of speaking publicly of it is a mixture of positive and negative. Furthermore, the discourse is structured, with the main actors being in the center of opinion formation and dissemination in the digital network. These findings enable the theoretical sophistication of the digital customer experience and the digital public sphere, since they show how individual experiences turn into collective perceptions, as a result of their interaction. For the practice, the study highlights the significance of businesses proactively engaging in digital conversations, enhancing their services, and effectively managing digital communities.

References

A. Chine, “Digital Transformation in Transport: Enhancing Efficiency and Economic Growth,” Eur. Econ. Lett., vol. 14, no. 4, pp. 763–773, 2024, doi: 10.52783/eel.v14i4.2198.

P. Wagh and A. Shaikh, “DIGITAL TRANSFORMATION AND RELATIONSHIP WITH CUSTOMER EXPERIENCE: A CRITICAL REVIEW OF LITERATURE FROM 1990 TO 2005 FOR PARADIGM SHIFTS IN KNOWLEDGE AND THOUGHTS IN 4-WHEELER CAR SEGMENT,” Int. J. Manag., vol. 11, no. 12, pp. 2098–2110, Jan. 2021, doi: 10.34218/IJM.11.12.2020.197.

M. Weber and C. G. Chatzopoulos, “Digital customer experience: the risk of ignoring the non-digital experience,” Int. J. Ind. Eng. Manag., vol. 10, no. 3, pp. 201–210, Sep. 2019, doi: 10.24867/IJIEM-2019-3-240.

P. Klaus, “Towards practical relevance-Delivering superior firm performance through digital customer experience strategies,” J. Direct, Data Digit. Mark. Pract., vol. 15, no. 4, pp. 306–316, 2014, doi: 10.1057/dddmp.2014.20.

R. Sun, “Digital Platforms: Conceptualisation and Practice,” the School of Management, Australian National University, 2019. [Online]. Available: https://openresearch-repository.anu.edu.au/bitstream/1885/203636/2/PhD thesis Ruonan Sun 2020.pdf

S. Satryawati et al., “Exploration of Customer Satisfaction Factors in the use of Maxim Online Transportation: An Empirical Study in the City of Samarinda,” Asian J. Environ. Res., vol. 2, no. 3, pp. 294–303, 2025, doi: 10.69930/ajer.v2i3.590.

Z. Ning and Y. Qiu, “Will Price Discrimination Affect Customer Satisfaction in the Shared Transportation Market? -A Case Study of Didi,” Adv. Econ. Manag. Polit. Sci., vol. 213, no. 1, pp. 120–130, Sep. 2025, doi: 10.54254/2754-1169/2024.26691.

T. Jameel, R. Ali, and K. A. Malik, “Social Media as an Opinion Formulator: A Study on Implications and Recent Developments,” in 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), IEEE, Jan. 2019, pp. 1–6. doi: 10.1109/ICOMET.2019.8673509.

L. Dush, “Nonprofit Collections of Digital Personal Experience Narratives: An Exploratory Study,” J. Bus. Tech. Commun., vol. 31, no. 2, pp. 188–221, 2017, doi: 10.1177/1050651916682287.

M. Waqas, Z. L. Hamzah, and N. A. M. Salleh, “A typology of customer experience with social media branded content: a netnographic study,” Int. J. Internet Mark. Advert., vol. 14, no. 2, p. 184, 2020, doi: 10.1504/ijima.2020.10029779.

S. J. Mohammed, “Digital Marketing and its Role in Customer Engagement,” Am. J. Econ., vol. 7, no. 8, pp. 414–422, 2024.

Yessi Claudia Sianipar, Syafrizal Helmi Situmorang, and Rulianda Purnomo Wibowo, “ANALYSIS OF THE EFFECT OF DIGITAL CUSTOMER EXPERIENCE ON CUSTOMER LOYALTY THROUGH EMOTIONAL MARKETING AND CUSTOMER SATISFACTION FOR INDIHOME CUSTOMERS,” Int. J. Econ. Business, Accounting, Agric. Manag. Sharia Adm., vol. 3, no. 4, pp. 1235–1247, Jul. 2023, doi: 10.54443/ijebas.v3i4.1023.

B. Adisu Fanta and B. Ayman, “Social Media as Effective Tool for Understanding Customer Experience: A Systematized Review,” Mark. Menedzsment, vol. 55, no. 4, pp. 15–25, Feb. 2022, doi: 10.15170/MM.2021.55.04.02.

L. Muradkhanli and Z. Karimov, “Customer Behavior Analysis Using Big Data Analytics and Machine Learning,” Probl. Inf. Soc., vol. 14, no. 2, pp. 61–67, 2023, doi: 10.25045/jpis.v14.i2.08.

A. Scalcău, “"Research Methods in Discourse Analysis: Quantitative, Qualitative and Mixed-Methods Approaches ",” Prof. Commun. Transl. Stud., vol. 14, pp. 114–122, 2023, doi: 10.59168/krla6949.

A. Bruns, “Big Social Data Approaches in Internet Studies: The Case of Twitter,” in Second International Handbook of Internet Research, 2019, pp. 1–17. doi: 10.1007/978-94-024-1555-1_3.

D. Cogburn, M. Hine, N. Peladeau, and V. Yoon, “Introduction to the Minitrack on Text Analytics,” in Hawaii International Conference on System Sciences, 2022, pp. 755–757. doi: 10.24251/HICSS.2022.094.

A. T. S. Wicaksono and S. Sudarmiatin, “Social Media Sentiment Analysis: Customer Perception of Digital Marketing,” Asian J. Appl. Bus. Manag., vol. 4, no. 2, pp. 437–450, May 2025, doi: 10.55927/ajabm.v4i2.187.

M. S. Schäfer, “Digital Public Sphere,” Int. Encycl. Polit. Commun., pp. 1–7, 2016, doi: 10.1002/9781118541555.wbiepc087.

K. Modi and V. B. Patel, “The Role of Social Media in Shaping Public Opinion: A Comprehensive Literature Review,” Int. J. LATEST Technol. Eng. Manag. Appl. Sci., vol. 14, no. 10, 2025, doi: 10.70183/lijdlr.2025.v03.133.

N. G. Alimin, “THE ROLE OF SOCIAL MEDIA IN FORMING PUBLIC OPINION: A CONTEMPORARY SOCIOLOGICAL PERSPECTIVE,” 2024, doi: 10.31235/osf.io/d7g89.

P. A. Carter, “UNDERSTANDING THE RELATIONSHIP BETWEEN DIGITAL TOUCHPOINTS AND CUSTOMER LOYALTY: THE MEDIATING EFFECTS OF ENGAGEMENT AND SATISFACTION,” Int. J. Manag. Bus. Dev., vol. 2, no. 3, pp. 1–6, Mar. 2025, doi: 10.55640/ijmbd-v02i03-01.

W. Xu et al., “An analysis of ridesharing trip time using advanced text mining techniques,” Digit. Transp. Saf., vol. 2, no. 4, pp. 308–319, 2023, doi: 10.48130/DTS-2023-0026.

P. JÜRGENS and A. JUNGHERR, “A TUTORIAL FOR USING TWITTER DATA IN THE SOCIAL SCIENCES : DATA COLLECTION, PREPARATION, AND ANALYSIS,” SSRN Electron. J., 2016.

S. M. Emaduddin, R. Ullah, I. Mazahir, and M. Z. Uddin, “Enhancing Information Preservation in Social Media Text Analytics Using Advanced and Robust Pre-processing Techniques,” Int. J. Media Inf. Lit., vol. 7, no. 1, pp. 60–70, Jun. 2022, doi: 10.13187/ijmil.2022.1.60.

A. R. Lubis and M. K. M. Nasution, “Twitter Data Analysis and Text Normalization in Collecting Standard Word,” J. Appl. Eng. Technol. Sci., vol. 4, no. 2, pp. 855–863, 2023, doi: 10.37385/jaets.v4i2.1991.

V. S. Tomashevskaya and D. A. Yakovlev, “Research of unstructured data interpretation problems,” Russ. Technol. J., 2021.

M. Taboada, “Sentiment Analysis: An Overview from Linguistics,” Annu. Rev. Linguist., vol. 2, pp. 325–347, 2016, doi: 10.1146/annurev-linguistics-011415-040518.

M. A. A. Saputra, A. Alamsyah, D. P. Ramadhani, T. S. Siadari, and H. Fakhrurroja, “IndoBERT-Sentiment: Context-Conditioned Sentiment Classification for Indonesian Text,” pp. 1–8, 2026, [Online]. Available: http://arxiv.org/abs/2604.07057

S. Cahyawijaya et al., “IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding,” EMNLP 2021 - 2021 Conf. Empir. Methods Nat. Lang. Process. Proc., pp. 8875–8898, 2021, doi: 10.18653/v1/2021.emnlp-main.699.

S. Winarno et al., “Comparative Performance of Fine-Tuned IndoBERT BASE and LARGE Variants for Emotion Detection in Indonesian Tweets,” J. Online Inform., vol. 11, no. 1, pp. 14–26, 2026, doi: 10.15575/join.v11i1.1704.

V. A. and S. S. Sonawane, “Sentiment Analysis of Twitter Data: A Survey of Techniques,” Int. J. Comput. Appl., vol. 139, no. 11, pp. 5–15, Apr. 2016, doi: 10.5120/ijca2016908625.

J. Ziegler and M. Gertz, “Who Is behind a Trend? Temporal Analysis of Interactions among Trend Participants on Twitter,” in Proceedings of the International AAAI Conference on Web and Social Media, Jun. 2023, pp. 960–969. doi: 10.1609/icwsm.v17i1.22203.

J. Jussila, M. Boedeker, H. Jalonen, and N. Helander, “Social Media Analytics Empowering Customer Experience Insight,” in Springer Proceedings in Business and Economics, 2017, pp. 25–30. doi: 10.1007/978-3-319-56288-9_4.

A. Serna, J. K. Gerrikagoitia, and U. Bernabe, “Discovery and Classification of the Underlying Emotions in the User Generated Content (UGC),” in ENTER2016. eTourism: Empowering Places. IFITT and ENTER Conferences Connect the global eTourism Community, 2016. doi: 10.1007/978-3-319-28231-2.

W. Yen-Jou, N. Yen, and J. C. Hung, “Design of a Multi-Dimensional Model for UGC-Based Emotion Analysis,” in 2019 International Conference on Computational Science and Computational Intelligence (CSCI), IEEE, Dec. 2019, pp. 1383–1387. doi: 10.1109/CSCI49370.2019.00258.

B. Huseynli, “Digital transformation for improving customer experience,” in Handbook of Research on Interdisciplinary Reflections of Contemporary Experiential Marketing Practices, 2022. doi: 10.4018/978-1-6684-4380-4.ch005.

E. Çela, “Social Media as a New Form of Public Sphere,” Eur. J. Soc. Sci. Educ. Res., vol. 4, no. 1, p. 195, Aug. 2015, doi: 10.26417/ejser.v4i1.p195-200.

K.-M. Tramvalidou and V. G. Vrana, “Customer Experience in Public Organizations: A Multidimensional Analysis,” in 1st International Conference on Public Administration 2024, 2025, p. 9. doi: 10.3390/proceedings2024111009.

M. R. Alam, A. M. Sadri, and X. Jin, “Identifying Public Perceptions toward Emerging Transportation Trends through Social Media-Based Interactions,” Futur. Transp., vol. 1, no. 3, pp. 794–813, 2021, doi: 10.3390/futuretransp1030044.

R. Song, W. Shi, W. Qin, X. Xue, and H. Jin, “Exploring Passengers’ Emotions and Satisfaction: A Comparative Analysis of Airport and Railway Station through Online Reviews,” Sustain. , vol. 16, no. 5, 2024, doi: 10.3390/su16052108.

B. Liu, F. Meng, C. Luo, and H. Jiang, “User Interactions in Online Travel Communities: A Social Network Perspective,” J. Hosp. Tour. Res., vol. 48, no. 7, pp. 1149–1163, 2024, doi: 10.1177/10963480221141616.