Mix method analysis for analyzing user behavior on logistic company mobile pocket software

  • Satria Fadil Persada Bina Nusantara University https://orcid.org/0000-0002-8141-1957
  • Farid Afandi Institut Teknologi Sepuluh Nopember https://orcid.org/0009-0006-6543-2738
  • Anak Agung Ngurah Perwira Redi Sampoerna University
  • Reny Nadlifatin Institut Teknologi Sepuluh Nopember
  • Yogi Tri Prasetyo Yuan Ze University
  • Adji Candra Kurniawan Universitas Pertamina
Abstract views: 292 , PDF downloads: 437
Keywords: Mix method, PLS-SEM, Customer journey, Logistic company


The present study emphasizes mixed-method analysis, integrating the partial least square structural equation model (PLS-SEM) and customer journey for mobile pocket office improvement in logistic XYZ company. The extension of the unified theory of acceptance and use of technology (UTAUT 2) model by incorporating perceived risk (PR), personal innovativeness (PI), and trust (TR) variables are used. The sample for this study consisted of 243 res­pondents. Based on the results of the PLS-SEM analysis, two of the eleven tested hypotheses were determined to be rejected. In application usage, the proposed model effectively explained 85.7 per cent of the influence on beha­vioral intention (BI) and 72.1 per cent on use behavior (UB). The customer journey mapping (CJM) investigation's findings show that fluctuations in the use of mobile pocket office technology in the field are generally brought on by a lot of data entry, sluggish internet connections, and overworked field operations. The XYZ company may acquire sugges­tions and knowledge for developing further applications due to this inquiry.


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R. Padilla-Vega, C. Sénquiz-Díaz, and A. Ojeda, ‘Toward a conceptual framework of technology adoption: Factors impacting the acceptance of the mobile technology in the international business growth’, Int. J. Sci. Technol. Res., vol. 6, no. 1, pp. 81–86, 2017, [Online]. Available: https://www.ijstr.org/final-print/jan2017/Toward-A-Conceptual-Framework-Of-Technology-Adoption-Factors-Impacting-The-Acceptance-Of-The-Mobile-Technology-In-The-International-Business-Growth.pdf.

H. Chin, D. P. Marasini, and D. Lee, ‘Digital transformation trends in service industries’, Serv. Bus., vol. 17, no. 1, pp. 11–36, 2023, doi: https://doi.org/10.1007/s11628-022-00516-6.

V. Venkatesh, J. Y. L. Thong, and X. Xu, ‘Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology’, MIS Q., vol. 36, no. 1, pp. 157–178, 2012, [Online]. Available: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2002388.

C.-S. Yu, ‘Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT model’, J. Electron. Commer. Res., vol. 13, no. 2, pp. 104–121, 2012, [Online]. Available: http://www.jecr.org/sites/default/files/13_3_p01_0.pdf.

C. Carlsson, J. Carlsson, K. Hyvonen, J. Puhakainen, and P. Walden, ‘Adoption of Mobile Devices/Services - Searching for Answers with the UTAUT’, in Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS’06), 2006, vol. 6, p. 132a–132a, doi: https://doi.org/10.1109/HICSS.2006.38.

L. Al-Azizi, A. H. Al-Badi, and T. Al-Zrafi, ‘Exploring the Factors Influencing Employees’ Willingness to Use Mobile Applications in Oman: Using UTAUT Model’, J. e-Government Stud. Best Pract., vol. 2018, pp. 1–27, Feb. 2018, doi: https://doi.org/10.5171/2018.553293.

Y. Fukuoka, T. Lindgren, and S. Jong, ‘Qualitative Exploration of the Acceptability of a Mobile Phone and Pedometer-Based Physical Activity Program in a Diverse Sample of Sedentary Women’, Public Health Nurs., vol. 29, no. 3, pp. 232–240, 2012, doi: https://doi.org/10.1111/j.1525-1446.2011.00997.x.

K. Anderson, O. Burford, and L. Emmerton, ‘Mobile Health Apps to Facilitate Self-Care: A Qualitative Study of User Experiences’, PLoS One, vol. 11, no. 5, p. e0156164, May 2016, doi: https://doi.org/10.1371/journal.pone.0156164.

N. Mallat, ‘Exploring consumer adoption of mobile payments – A qualitative study’, J. Strateg. Inf. Syst., vol. 16, no. 4, pp. 413–432, 2007, doi: https://doi.org/10.1016/j.jsis.2007.08.001.

S. F. Persada, B. A. Miraja, and R. Nadlifatin, ‘Understanding the Generation Z Behavior on D-Learning: A Unified Theory of Acceptance and Use of Technology (UTAUT) Approach.’, Int. J. Emerg. Technol. Learn., vol. 14, no. 5, pp. 20–33, 2019, [Online]. Available: https://www.learntechlib.org/p/208414/.

Y. T. Prasetyo et al., ‘Determining Factors Affecting the Acceptance of Medical Education eLearning Platforms during the COVID-19 Pandemic in the Philippines: UTAUT2 Approach’, Healthcare, vol. 9, no. 7. 2021, doi: https://doi.org/10.3390/healthcare9070780.

A. A. Alalwan, Y. K. Dwivedi, N. P. Rana, and R. Algharabat, ‘Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk’, J. Retail. Consum. Serv., vol. 40, pp. 125–138, 2018, doi: https://doi.org/10.1016/j.jretconser.2017.08.026.

D. Dajani and A. S. Abu Hegleh, ‘Behavior intention of animation usage among university students’, Heliyon, vol. 5, no. 10, p. e02536, Oct. 2019, doi: https://doi.org/10.1016/j.heliyon.2019.e02536.

M. S. Farooq et al., ‘Acceptance and use of lecture capture system (LCS) in executive business studies’, Interact. Technol. Smart Educ., vol. 14, no. 4, pp. 329–348, Jan. 2017, doi: https://doi.org/10.1108/ITSE-06-2016-0015.

M. Merhi, K. Hone, and A. Tarhini, ‘A cross-cultural study of the intention to use mobile banking between Lebanese and British consumers: Extending UTAUT2 with security, privacy and trust’, Technol. Soc., vol. 59, p. 101151, 2019, doi: https://doi.org/10.1016/j.techsoc.2019.101151.

K. N. Lemon and P. C. Verhoef, ‘Understanding Customer Experience Throughout the Customer Journey’, J. Mark., vol. 80, no. 6, pp. 69–96, Nov. 2016, doi: https://doi.org/10.1509/jm.15.0420.

C. Kuehnl, D. Jozic, and C. Homburg, ‘Effective customer journey design: consumers’ conception, measurement, and consequences’, J. Acad. Mark. Sci., vol. 47, no. 3, pp. 551–568, 2019, doi: https://doi.org/10.1007/s11747-018-00625-7.

A. Crosier and A. Handford, ‘Customer Journey Mapping as an Advocacy Tool for Disabled People: A Case Study’, Soc. Mar. Q., vol. 18, no. 1, pp. 67–76, Mar. 2012, doi: https://doi.org/10.1177/1524500411435483.

J. F. Hair, B. J. Babin, R. E. Anderson, and W. C. Black, Multivariate Data Analysis. Cengage Learning, 2022, [Online]. Available: https://books.google.co.id/books?id=PONXEAAAQBAJ.

M. S. Featherman and P. A. Pavlou, ‘Predicting e-services adoption: a perceived risk facets perspective’, Int. J. Hum. Comput. Stud., vol. 59, no. 4, pp. 451–474, 2003, doi: https://doi.org/10.1016/S1071-5819(03)00111-3.

A. K. S. Ong et al., ‘Determining factors affecting the perceived usability of air pollution detection mobile application “AirVisual” in Thailand: A structural equation model forest classifier approach’, Heliyon, vol. 8, no. 12, p. e12538, 2022, doi: https://doi.org/10.1016/j.heliyon.2022.e12538.

M. J. J. Gumasing, Y. T. Prasetyo, A. K. S. Ong, S. F. Persada, and R. Nadlifatin, ‘Factors influencing the perceived usability of wearable chair exoskeleton with market segmentation: A structural equation modeling and K-Means Clustering approach’, Int. J. Ind. Ergon., vol. 93, p. 103401, 2023, doi: https://doi.org/10.1016/j.ergon.2022.103401.

M. M. L. Cahigas, Y. T. Prasetyo, S. F. Persada, and R. Nadlifatin, ‘Filipinos’ intention to participate in 2022 leyte landslide response volunteer opportunities: The role of understanding the 2022 leyte landslide, social capital, altruistic concern, and theory of planned behavior’, Int. J. Disaster Risk Reduct., vol. 84, p. 103485, 2023, doi: https://doi.org/10.1016/j.ijdrr.2022.103485.

Y.-T. Jou, C. S. Saflor, K. A. Mariñas, M. N. Young, Y. T. Prasetyo, and S. F. Persada, ‘Assessing Service Quality and Customer Satisfaction of Electric Utility Provider’s Online Payment System during the COVID-19 Pandemic: A Structural Modeling Approach’, Electronics, vol. 11, no. 22. 2022, doi: https://doi.org/10.3390/electronics11223646.

B. Ardiansyahmiraja, R. Nadlifatin, S. F. Persada, Y. T. Prasetyo, and A. A. N. P. Redi, ‘Learning from a distance during a pandemic outbreak: Factors affecting students’ acceptance of distance learning during school closures due to COVID-19’, J. e-Learning Knowl. Soc., vol. 17, no. 2, pp. 21–31, 2021, doi: https://doi.org/10.20368/1971-8829/1135412.

S. F. Persada, B. A. Miraja, R. Nadlifatin, P. F. Belgiawan, A. A. N. Perwira Redi, and S.-C. Lin, ‘Determinants of Students’ Intention to Continue Using Online Private Tutoring: An Expectation-Confirmation Model (ECM) Approach’, Technol. Knowl. Learn., vol. 27, no. 4, pp. 1081–1094, 2022, doi: https://doi.org/10.1007/s10758-021-09548-9.

Y. B. Kurata et al., ‘Predicting factors influencing intention to donate for super Typhoon Odette victims: A structural equation model forest classifier approach’, Int. J. Disaster Risk Reduct., vol. 81, p. 103287, 2022, doi: https://doi.org/10.1016/j.ijdrr.2022.103287.

P. Kusonwattana et al., ‘Determining Factors Affecting Behavioral Intention to Organize an Online Event during the COVID-19 Pandemic’, Sustainability, vol. 14, no. 20. 2022, doi: https://doi.org/10.3390/su142012964.

A. A. Abella et al., ‘The effect of positive reinforcement of behavioral-based safety on safety participation in Philippine coal-fired power plant workers: a partial least squares structural equation modeling approach’, Int. J. Occup. Saf. Ergon., vol. 29, no. 3, pp. 951–962, Jul. 2023, doi: https://doi.org/10.1080/10803548.2022.2089474.

N. Yuduang et al., ‘Utilizing Structural Equation Modeling–Artificial Neural Network Hybrid Approach in Determining Factors Affecting Perceived Usability of Mobile Mental Health Application in the Philippines’, International Journal of Environmental Research and Public Health, vol. 19, no. 11. 2022, doi: https://doi.org/10.3390/ijerph19116732.

J. P. Alegre Perez et al., ‘Determinant factors for consumers’ intention in choosing a shopping center: An extended Theory of Planned Behavior approach’, in 2022 The 3rd International Conference on Industrial Engineering and Industrial Management, Jan. 2022, pp. 108–114, doi: https://doi.org/10.1145/3524338.3524382.

R. T. Kishimoto, Y. T. Prasetyo, S. F. Persada, and A. A. Redi, ‘Filipino generation z on mobile legends during COVID-19: A determination of playtime and satisfaction’, Int. J. Inf. Educ. Technol., vol. 11, no. 8, pp. 381–386, 2021, [Online]. Available: http://www.ijiet.org/vol11/1538-AT021.pdf.

T. Chuenyindee, R. B. Torres, Y. T. Prasetyo, R. Nadlifatin, and S. F. Persada, ‘Determining Factors Affecting Perceived Quality among Shoe Manufacturing Workers towards Shoe Quality: A Structural Equation Modeling Approach’, Journal of Open Innovation: Technology, Market, and Complexity, vol. 8, no. 2. 2022, doi: https://doi.org/10.3390/joitmc8020082.

J. D. German et al., ‘Choosing a package carrier during COVID-19 pandemic: An integration of pro-environmental planned behavior (PEPB) theory and service quality (SERVQUAL)’, J. Clean. Prod., vol. 346, p. 131123, 2022, doi: https://doi.org/10.1016/j.jclepro.2022.131123.

A. A. Santosa et al., ‘How the COVID-19 Pandemic Affected the Sustainable Adoption of Digital Signature: An Integrated Factors Analysis Model’, Sustainability, vol. 14, no. 7. 2022, doi: https://doi.org/10.3390/su14074281.

R. Nadlifatin et al., ‘Understanding factors influencing traveler’s adoption of travel influencer advertising: an Information Adoption Model approach’, Bus. Theory Pract., vol. 23, no. 1, pp. 131–140, 2022, [Online]. Available: https://www.ceeol.com/search/article-detail?id=1057299.

D. B. Bekti et al., ‘Determining Factors Affecting Customer Intention to Use Rooftop Solar Photovoltaics in Indonesia’, Sustainability, vol. 14, no. 1. 2022, doi: https://doi.org/10.3390/su14010280.

J. R. Balinado, Y. T. Prasetyo, M. N. Young, S. F. Persada, B. A. Miraja, and A. A. N. Perwira Redi, ‘The Effect of Service Quality on Customer Satisfaction in an Automotive After-Sales Service’, J. Open Innov. Technol. Mark. Complex., vol. 7, no. 2, p. 116, 2021, doi: https://doi.org/10.3390/joitmc7020116.

B. A. Miraja, S. F. Persada, Y. T. Prasetyo, P. F. Belgiawan, and A. A. . P. Redi, ‘Applying Protection Motivation Theory To Understand Generation Z Students Intention To Comply With Educational Software Anti Piracy Law’, Int. J. Emerg. Technol. Learn., vol. 14, no. 18, pp. 39–52, Sep. 2019, doi: https://doi.org/10.3991/ijet.v14i18.10973.

M. R. Ab Hamid, W. Sami, and M. H. Mohmad Sidek, ‘Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion’, J. Phys. Conf. Ser., vol. 890, no. 1, p. 12163, 2017, doi: https://doi.org/10.1088/1742-6596/890/1/012163.

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S. F. Persada, F. Afandi, A. A. N. P. Redi, R. Nadlifatin, Y. T. Prasetyo, and A. C. Kurniawan, “Mix method analysis for analyzing user behavior on logistic company mobile pocket software”, j. sist. manaj. ind., vol. 7, no. 1, pp. 69-81, Jun. 2023.
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