Logistics HR Capabilities, Iot Integration, and Service Quality on Operational Performance: Mediating Delivery Timeliness

Authors

  • Neneng Kristanti Universitas Logistik dan Bisnis Internasional
  • Agus Purnomo Universitas Logistik dan Bisnis Internasional
  • Melia Eka Lestiani Universitas Logistik dan Bisnis Internasional

DOI:

https://doi.org/10.59261/bustechno.v7i4.824

Keywords:

Delivery Timeliness, Operational Performance, IoT Integration, Service Quality, Logistics Human Resource Capability, Digital Logistics

Abstract

Background: The development of digital logistics demands companies to improve the speed, accuracy, transparency, and quality of operations. This study seeks to examine how logistics human resource capabilities, Internet of Things (IoT) integration, and service quality influence the company's operational performance, both directly and via delivery timeliness acting as a mediating variable within the digital logistics services of PT Pos Indonesia (Persero).

Method: This research applies a quantitative approach using the Partial Least Squares–Structural Equation Modeling (SEM-PLS) method operated through SmartPLS. Data were collected from 145 internal respondents who were familiar with digital logistics services, Service Level Agreements, tracking systems, service quality, logistics HR capabilities, and operational performance. The analysis includes testing measurement models, structural models, hypotheses, and mediating effects. This research emphasizes the importance of employee capabilities, technology integration, and service quality in improving delivery timeliness and operational performance.

Results: The findings reinforce scholarship on digital operations and logistics management and offer recommendations for firms to enhance performance by developing logistics human resource capabilities, leveraging IoT, raising service quality, and managing delivery times.

Conclusion: This study concludes that Logistics HR Capabilities, Internet of Things (IoT) Integration, and Service Quality exert a positive and significant effect on Delivery Timeliness and on Company Operational Performance. Delivery Timeliness is likewise shown to have a positive and significant effect on the Company's Operational Performance and to function as a partial mediator linking Logistics HR Capabilities, IoT Integration, and Service Quality to Operational Performance.

References

Chen, J., Lan, Y.-C., & Chang, Y.-W. (2023). Consumer behaviour in cross-border e-commerce: Systematic literature review and future research agenda. International Journal of Consumer Studies, 47(6), 2609–2669. https://doi.org/10.1111/ijcs.12969

Deu, I., Masnita, Y., Yusran, H. L., & Laulita, N. B. (2025). Optimizing logistics capability: Integrating human resources, technology, and cooperative efforts. International Journal of Scientific Research and Management, 13(5), 8945–8954. https://doi.org/10.18535/ijsrm/v13i05.em04

Dwita, F., & Sadana, S. M. S. (2021). Human resource and supply chain strategy to improve company performance through organizational capability in PT Pos Indonesia. Airlangga Journal of Innovation Management, 2(2), 154–166. https://doi.org/10.20473/ajim.v2i2.29903

Evangelista, P., Kianto, A., Hussinki, H., Vanhala, M., & Nisula, A.-M. (2023). Knowledge-based human resource management, logistics capability, and organizational performance in small Finnish logistics service providers. Logistics, 7(1), 12. https://doi.org/10.3390/logistics7010012

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

Ghozali, I. (2021). Partial least squares: Konsep, teknik, dan aplikasi menggunakan program SmartPLS 3.2.9 untuk penelitian empiris. Badan Penerbit Universitas Diponegoro.

Gupta, A., Singh, R. K., & Gupta, S. (2022). Developing human resource for the digitization of logistics operations: Readiness index framework. International Journal of Manpower, 43(2), 355–379. https://doi.org/10.1108/IJM-03-2021-0175

Hair, J. F., & Alamer, A. (2022). Partial least squares structural equation modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 100027. https://doi.org/10.1016/j.rmal.2022.100027

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE.

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer. https://doi.org/10.1007/978-3-030-80519-7

Indonesia, P. T. P. (2025). Data Performance SLA, OverSLA, dan Customer Contact Handling (CCH) periode 2025. PT Pos Indonesia.

Jena, S. K., & Ghadge, A. (2021). An integrated supply chain–human resource management approach for improved supply chain performance. The International Journal of Logistics Management, 32(3), 918–941. https://doi.org/10.1108/IJLM-03-2020-0151

Jhantasana, C. (2023). Should A Rule of Thumb be used to Calculate PLS-SEM Sample Size. Asia Social Issues, 16(5). https://doi.org/10.48048/asi.2023.254658

Katinienė, A., Jezerskė, Ž., & Vaičiūtė, K. (2021). Research on competencies of logistics specialists in transport organisations. Journal of Business Economics and Management, 22(5), 1308–1322. https://doi.org/10.3846/jbem.2021.15299

Kim, J., & Song, Y. (2026). Structural Model of Medication Errors in Clinical Nursing: A Structural Equation Model Based on the Ecological Systems Theory. Journal of Nursing Management, 2026(1). https://doi.org/10.1155/jonm/1245208

Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227–261. https://doi.org/10.1111/isj.12131

Koh, L. Y., & Yuen, K. F. (2022). Emerging competencies for logistics professionals in the digital era: A literature review. Frontiers in Psychology, 13, 965748. https://doi.org/10.3389/fpsyg.2022.965748

Nong, N.-M. T., Nguyen, Q. P., & Ha, D.-S. (2024). The effect of employee competence and competence–job fit on business performance through moderating role of social exchange: A study in logistics firms. The Asian Journal of Shipping and Logistics, 40(4), 187–197. https://doi.org/10.1016/j.ajsl.2024.10.001

Panzeri, A., Castelnuovo, G., & Spoto, A. (2024). Assessing Discriminant Validity through Structural Equation Modeling: The Case of Eating Compulsivity. Nutrients, 16(4). https://doi.org/10.3390/nu16040550

Populix. (2023). Indonesia outlook on the logistic delivery services. Populix. https://info.populix.co/id/reports/2023-07-logistic-delivery-services

Roemer, E., Schuberth, F., & Henseler, J. (2021). HTMT2—An improved criterion for assessing discriminant validity in structural equation modeling. Industrial Management & Data Systems, 121(12), 2637–2650. https://doi.org/10.1108/IMDS-02-2021-0082

Syafrianita, S., Purnomo, A., & Nasrudin, M. F. (2025). Investigasi hubungan antara advanced technology, logistics service cost, dan logistics performance di Shopee Express Bandung Raya. LAND Journal, 6(1), 253–265. https://doi.org/10.47491/landjournal.v6i1.4038

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Published

2026-10-14