Modeling The Influence of Trust on Employee Performance and Operations in Jordanian Logistics Companies through SEM-PLS

  • Authors

    • Majd Mohammad Omoush Department of Business Administration, College of Business, Tafila Technical University, P. O. Box 179, 66110 Tafila, Jordan
    https://doi.org/10.14419/kkn74y75

    Received date: October 18, 2025

    Accepted date: October 26, 2025

    Published date: November 6, 2025

  • Goodwill Trust, Ability Trust, Logistics Synergy, Employee Performance, Jordanian Logistics
  • Abstract

    This research examines the role of dimensions of trust, such as goodwill trust and ability trust, on employees' performance with logistic synergy as a mediator. This paper uses Dynamic Capabilities Theory and Trust-Commitment theories to provide a theoretical framework for understanding the subject. It uses PLS-SEM to ensure the accuracy of results. This paper provides the results of 55 logistics companies in the Jordanian market. Results show that there is a direct influence of ability trust on logistic synergy and employee performance. It is also evident that there is no direct influence of goodwill trust on employees' performance; however, there is a mediating effect of logistic synergy. Logistic synergy is identified to have played a vital role in creating a possible outcome for employees' performance. This paper identifies that it is not emotional or goodwill skills that contribute to superior employees' performance. This paper contributes to theories related to the logic of high-performing teams. It uses the theories to develop logistic synergy theories that can add to the existing body of knowledge. This paper recommends that this subject be taught at graduate and undergraduate levels to contribute to logic theories. This paper contributes to theories related to the logic of high-performing teams. It uses theories to develop theories related to the logic of high-performing teams. This paper recommends training programs related to the logic of high-performing teams. It recommends improving online networking sites to enhance employees' performance. It recommends open communication to enhance employees' performance.

  • References

    1. Akhtar, F., Wang, Q., & Huo, B. (2023). The effect of human resource strategy on green supply chain integration: The moderating role of infor-mation systems and mutual trust. Industrial Management & Data Systems, 123(8), 2194–2215. https://doi.org/10.1108/IMDS-11-2022-0692
    2. Alavi, M., & Tavana, M. (2024). Modeling supply chain trust and performance in Industry 5.0 environments. Technological Forecasting and Social Change, 201, 122228.
    3. https://doi.org/10.1016/j.techfore.2024.122228
    4. Al-Awamleh, H.K., Omoush, M.M., Ahmed, R.T., Assaf, N., Alqudah, M.Z., & Samara, H. (2025). Less Innovation in energy management: map-ping knowledge development and technological change. International Journal of Energy Sector Management. https://doi.org/10.1108/IJESM-03-2025-0016.
    5. Alshawabkeh, R., Al-Awamleh, H., Alkhawaldeh, M., Kanaan, R., & Al-Hawary, S. (2022). The mediating role of supply chain management on the relationship between big data and supply chain performance using the SCOR model. Uncertain Supply Chain Management, 10(3), 729–736. *
    6. AL-Shboul, M. D. (2024). Artificial intelligence drivers' effect on willingness to adopt the human capital supply chain in manufacturing firms: An empirical investigation from developing countries–A mediation model. Industrial Management & Data Systems, 124(10), 2919–2938. https://doi.org/10.1108/IMDS-02-2024-0120
    7. Anderson, J. C., & Narus, J. A. (1990). A model of distributor firm and manufacturer firm working partnerships. Journal of Marketing, 54(1), 42–58. https://doi.org/10.2307/1252172
    8. Bachmann, R., & Inkpen, A. C. (2023). Trust, control, and cooperation revisited: New insights for digital organizations. Journal of Management, 49 (3), 677–699. https://doi.org/10.1177/01492063221131472
    9. Bauer, C., Mladenow, A., & Strauss, C. (2014). Fostering collaboration by location-based crowdsourcing. In Proceedings of the 11th International Conference on Cooperative Design, Visualization and Engineering (pp. 1–8). Springer. https://doi.org/10.1007/978-3-319-10831-5_1
    10. Bin, H., Wang, H. F., & Xie, G. J. (2019). Research on the influencing factors of crowdsourcing logistics under the sharing economy. Management Review, 31(8), 219–229.
    11. Bin, H., Zhao, F., Xie, G. J., et al. (2020). Crowd-sourcing a way to sustainable urban logistics: What factors influence enterprises’ willingness to implement crowd logistics. IEEE Access, 8, 149768–149781. https://doi.org/10.1109/ACCESS.2020.3016750
    12. Cao, W. J., & Yang, W. S. (2017). Coordination of agricultural product supply chain based on agricultural insurance and organizational form opti-mization. Journal of Agro-Forestry Economics and Management, 16, 34–42.
    13. Chen, Y. F., Wang, S. L., & Zheng, J. (2019). Innovation of enterprise knowledge chain under the background of green manufacturing-logistics co-evolution. Science and Technology Management Research, 39(9), 192–196.
    14. Coşkun, A. E., & Erturgut, R. (2025). Does institutionalization enhance logistics performance in international businesses? A moderated and mediat-ed model. Operations Management Research. Advance online publication. https://doi.org/10.1007/s12063-024-00475-8
    15. Dada Group. (2021). Introduction of Dada Express business. Retrieved July 29, 2025, from https://about.imdada.cn/
    16. Deutsch, M. (1960). The effect of motivational orientation upon trust and suspicion. Human Relations, 13(2), 123–139. https://doi.org/10.1177/001872676001300202
    17. Donald, J. B., & David, J. K. (1999). Logistical management: The integrated supply chain process. China Machine Press.
    18. Frank, M., Becker, T., & Gogolla, M. (2016). Interoperability of logistics artifacts: An approach for information exchange through transformation mechanisms. In Proceedings of the LDIC-International Conference on Dynamics in Logistics. Springer.
    19. Frejat, A.S., & Masa’deh, R. (2024). A systematic analysis of digital supply chain, big data and manufacturing lean time in industrial companies. Business Process Management Journal, 30(5), 1696–1715.
    20. Ganesan, S. (1994). Determinants of long-term orientation in buyer-seller relationships. Journal of Marketing, 58(2), 1–19. https://doi.org/10.2307/1252265
    21. Guo, J., & Wang, J. W. (2017). Research on the effect factors of participation behavior to the crowdsourcing logistics based on the UTAUT. Opera-tions Research and Management Science, 26(11), 1–6.
    22. Hou, L., Yao, B., Hu, Y., Yu, K., & Yuan, K. (2025). How trust affects hazardous chemicals logistics enterprises’ sustainable safety behavior: The moderating role of government governance. Sustainability, 17(8), 3577. https://doi.org/10.3390/su17083577
    23. Huang, L., Xie, G., Blenkinsopp, J., Huang, R., & Bin, H. (2020). Crowdsourcing for sustainable urban logistics: Exploring the factors influencing crowd workers’ participative behavior. Sustainability, 12(8), 3091. https://doi.org/10.3390/su12083091
    24. Hulland, J. (2015). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195–204. https://doi.org/10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7
    25. Huo, B., & Zhao, X. (2023). Trust and coordination in supply chain management: Revisiting the dynamic capability perspective. Supply Chain Management: An International Journal, 28(5), 755–770. https://doi.org/10.1108/SCM-09-2022-0355
    26. Inkpen, A. C., & Tsang, E. W. K. (2005). Social capital, networks, and knowledge transfer. Academy of Management Review, 30(1), 146–165. https://doi.org/10.5465/amr.2005.15281445
    27. Jain, S., Gupta, A., & Kumar, P. (2024). The mediating role of operational synergy between trust and firm performance: Evidence from logistics SMEs. International Journal of Productivity and Performance Management, 73 (2), 412–428. https://doi.org/10.1108/IJPPM-09-2023-0521
    28. Joseph, F., Patrick, F., Jeremy, H., & Philip, O. R. (2012). ‘Orchestrating’ sustainable crowdsourcing: A characterisation of solver brokerages. The Journal of Strategic Information Systems, 21(3), 216–232. https://doi.org/10.1016/j.jsis.2012.03.002
    29. Kamalahmadi, M., & Parast, M. M. (2024). Building resilience through trust and agility in logistics operations. Transportation Research Part E: Lo-gistics and Transportation Review, 188, 103328.. https://doi.org/10.1016/j.tre.2024.103328
    30. Kim, S. (2025). Impact of trust on workforce agility and logistics performance: Korean manufacturing industry. Supply Chain Forum: An Interna-tional Journal. Advance online publication. https://doi.org/10.1080/16258312.2025.2301234
    31. Knorringa, P., & Meyer-Stamer, J. (1998). New dimensions in local enterprise cooperation and development: From clusters to industrial districts. Stamer, 9, 231–235.
    32. Kottala, S. Y., & Herbert, K. (2019). An empirical investigation of supply chain operations reference model practices and supply chain performance: Evidence from manufacturing sector. International Journal of Productivity and Performance Management, 69(9), 1925–1954. https://doi.org/10.1108/IJPPM-09-2018-0339
    33. Lai, F., Chu, Z., Wang, Q., & Fan, C. (2013). Managing dependence in logistics outsourcing relationships: Evidence from China. International Journal of Production Research, 51(10), 3037–3054. https://doi.org/10.1080/00207543.2012.746796
    34. Layaoen, H. D., Abareshi, A., Abdulrahman, M. D., & Abbasi, B. (2023). Sustainability of transport and logistics companies: An empirical evi-dence from a developing country. International Journal of Operations & Production Management, 43(7), 1040–1067. https://doi.org/10.1108/IJOPM-08-2022-0508
    35. Lee, C., & Ha, B. C. (2024). Relationship between trust, the investment model and logistics performance in supply chain management. Business Process Management Journal, 30(2), 485–504. https://doi.org/10.1108/BPMJ-05-2023-0387
    36. Liang, X. P., Huang, L. X., & Jiang, J. (2017). Research on antecedent factors of solvers’ continuous participation in crowdsourcing logistics. Jour-nal of Business Economics, 7, 5–15.
    37. Lin, C. C., & Lu, C. S. (2023). Cultural differences and job performance in container shipping: A social exchange theory perspective. Maritime Pol-icy & Management, 50(2), 157–181. https://doi.org/10.1080/03088839.2021.1970172
    38. Lin, J., Zhou, W., & Du, L. (2017). Is on-demand same day package delivery service green? Transportation Research Part D: Transport and Envi-ronment, 61, 118–139. https://doi.org/10.1016/j.trd.2017.10.016
    39. Lin, Y., & Yu, C. (2024). Trust and collaboration mechanisms in digital logistics networks: Evidence from emerging economies. International Jour-nal of Production Economics, 272, 109015.https: //doi.org/10.1016/j.ijpe.2024.109015
    40. Liu, W. F., & Ai, S. Z. (2014). An empirical resaerch on the factors influencing firm performance in IT outsourcing. Chinese Journal of Manage-ment Science, 22(2), 142–148.
    41. Liu, Y., Xue, J. Q., & Liu, T. (2007). An empirical research of the impacts of attitudinal commitment and satisfaction on knowledge transfer. Fore-casting, 6, 7–13.
    42. Mayer, R. C., Davis, J. H., & Schoorman, F. D. (2007). An integrative model of organizational trust. Academy of Management Review, 32(2), 344–354. https://doi.org/10.5465/amr.1995.9503271996
    43. McAllister, D. J. (1995). Affect and cognition-based trust as foundations for interpersonal cooperation in organizations. Academy of Management Journal, 38(1), 24–59. https://doi.org/10.5465/256727
    44. Meng, T., & He, C. (2020). An investigation on the trust mechanism in the sharing economy in the perspective of role. Journal of Guizhou Universi-ty of Finance and Economics, 4, 40–49.
    45. Michalski, M., & Montes-Botella, J. L. (2022). Logistics service quality in an emergent market in Latin America. The International Journal of Logis-tics Management, 33(1), 79–101. https://doi.org/10.1108/IJLM-02-2021-0080
    46. Mladenow, A., Bauer, C., & Strauss, C. (2015). Crowdsourcing in logistics: Concepts and applications using the social crowd. In Proceedings of the 17th International Conference on Information Integration and Web-based Applications & Services (pp. 244–251). ACM. https://doi.org/10.1145/2837185.2837192
    47. Mladenow, A., Bauer, C., & Strauss, C. (2016). “Crowd logistics”: The contribution of social crowds in logistics activities. International Journal of Web Information Systems, 12(3), 379–396. https://doi.org/10.1108/IJWIS-04-2016-0020
    48. Nguyen, C. T., Nguyen, T. T., Cai, L., Yuen, K. F., & Wang, X. (2025). A perception-based investigation on logistics robot adoption: From an inte-grated perspective of trust formation and technology acceptance. The International Journal of Logistics Management, 36(4), 1094–1118. https://doi.org/10.1108/IJLM-05-2023-0190
    49. Nguyen, L. T., Nguyen, D. T., Ngoc, K. N., & Duc, D. T. (2023). Blockchain adoption in logistics companies in Ho Chi Minh City, Vietnam. Co-gent Business & Management, 10(2), 2216436. https://doi.org/10.1080/23311975.2023.2216436
    50. Nong, N. M., Phuong, N. Q., & Duc-Son, H. (2024). The effect of employee competence and competence–job–fit on business performance through moderating role of social exchange: A research in logistics firms. The Asian Journal of Shipping and Logistics, 40(4), 187–197. https://doi.org/10.1016/j.ajsl.2024.09.002
    51. Norat, J. (2015). Crowdsourcing with all-pay auctions: A field experiment on Taskcn. Management Science, 60(8), 2020–2037. https://doi.org/10.1287/mnsc.2014.1949
    52. Omoush, M. (2021). The Impact of Green Productivity Strategy on Environmental Sustainability through Measurement of the Management Support: A Field Study in the Industry Sector in Jordan. Management Science Letters, 11(3), 737–746. https://doi.org/10.5267/j.msl.2020.10.033
    53. Omoush, M. (2025). The Impact of Supply Chain Integration via Mediator—Supply Chain Resilience on Improvement in the Performance of Man-ufacturing Sectors. International Review of Management and Marketing, 15(2), 157–170. *
    54. Omoush, M.M. (2022). The impact of the practices of logistic management on operational performance: A field study of road transport companies. Journal of Governance & Regulation, 11(4), 237–245. *
    55. Omoush, M.M. (2025a). Harnessing of Logistics in the ERA of Generative Artificial Intelligence. In A. Al-Marzouqi et al. (Eds.), Generative AI in Creative Industries (Vol. 1208). Springer, Cham. https://doi.org/10.1007/978-3-031-89175-5_39.
    56. Omoush, M.M. (2025b). Human–AI collaboration in HRM and employee-centric outcomes: Evidence from E-supply chain management. Human Systems Management. https://doi.org/10.1177/01672533251365119
    57. Pang, Q., Wang, M., Yao, J., & Fang, M. (2025). Employees’ perceived respect and performance in Logistics 4.0: A dyadic perspective of the con-gruence between employee voice and supervisor listening. International Journal of Physical Distribution & Logistics Management. Advance online publication. https://doi.org/10.1108/IJPDLM-06-2023-0208
    58. Park, S., & Lee, H. (2023). The impact of organizational trust on logistics performance under digital transformation. Journal of Business Logistics, 44(2), 89–105.
    59. https://doi.org/10.1111/jbl.12345
    60. Pavlov, A., Mura, M., Franco-Santos, M., & Bourne, M. (2017). Modelling the impact of performance management practices on firm performance: Interaction with human resource management practices. Production Planning & Control, 28(5), 431–443. https://doi.org/10.1080/09537287.2017.1302614
    61. Peng, X. (2019). Resaerch on the legal management of crowdsourcing logistics in China. China Business and Market, 33(4), 113–120.
    62. Persaud, A. (2005). Enhancing synergistic innovative capability in multinational corporations: An empirical investigation. Journal of Product Inno-vation Management, 22(5), 412–429. https://doi.org/10.1111/j.1540-5885.2005.00139.x
    63. Pervez, A., Shah, A. A., Sheikh, M., & Prodhan, F. A. (2019). Fuzzy-Likert scale based assessment of marketing risk faced by the hybrid rice growers of Bangladesh. Agricultural Economics, 60(1), 9–22. https://doi.org/10.17221/107/2018-AGRICECON
    64. Qiu, H. Q. (2018). Research on the influencing factors of public participation behaviors in crowdsourcing logistics based on TAM model. China Business and Market, 32(4), 110–119.
    65. Qureshi, M. A., Ahmed, K., & Li, X. (2025). Inter-firm trust and supply chain synergy: A PLS-SEM approach. International Journal of Logistics Management, 36(1), 120–138.
    66. https://doi.org/10.1108/IJLM-01-2025-0043
    67. Ramirez, M. J., Roman, I. E., Ramos, E., & Patrucco, A. S. (2021). The value of supply chain integration in the Latin American agri-food industry: Trust, commitment and performance outcomes. The International Journal of Logistics Management, 32(1), 281–301. https://doi.org/10.1108/IJLM-02-2020-0096
    68. Restuputri, D. P., Indriani, T. R., & Masudin, I. (2021). The effect of logistic service quality on customer satisfaction and loyalty using Kansei en-gineering during the COVID-19 pandemic. Cogent Business & Management, 8(1), 1906492. https://doi.org/10.1080/23311975.2021.1906492
    69. Shang, K. C., Kuo, S. Y., Hsu, S. W., Lai, P. L., & Ye, K. D. (2024). Leader-member exchange, team-member exchange, employee satisfaction, and service-oriented organizational citizenship behavior in the international logistics industry: The moderating effect of the service climate. Re-search in Transportation Business & Management, 52, 101072. https://doi.org/10.1016/j.rtbm.2023.101072
    70. Sinkovics, R. R., & Roath, A. S. (2004). Strategic orientation, capabilities and performance in manufacturer-3PL relationships. Journal of Business Logistics, 25(2), 43–64. https://doi.org/10.1002/j.2158-1592.2004.tb00181.x
    71. Story, V. M., Raddats, C., Burton, J., Zolkiewski, J., & Baines, T. (2017). Capabilities for advanced services: A multi-actor perspective. Industrial Marketing Management, 60, 54–68. https://doi.org/10.1016/j.indmarman.2016.04.015
    72. Sun, A., & He, M. K. (2017). Identification and analysis of crowdsourcing logistics risk based on structural equation model. Modernization Man-agement, 37(6), 111–115.
    73. Teoman, S., & Ulengin, F. (2018). The impact of management leadership on quality performance throughout a supply chain: An empirical study. Total Quality Management & Business Excellence, 29(11-12), 1427–1451. https://doi.org/10.1080/14783363.2017.1379470
    74. Tetteh, F. K., Mensah, J., & Owusu Kwateng, K. (2025). Understanding what, how and when green logistics practices influence carbon-neutral supply chain performance. International Journal of Productivity and Performance Management, 74(6), 2211–2244. https://doi.org/10.1108/IJPPM-05-2023-0230
    75. Tu, S. L. (2015). Research on China’s tourism logistics network construction based on crowdsourcing. Journal of Jiangxi University of Finance and Economics, 4, 42–48.
    76. Wahab, S. N., Hamzah, M. I., & Sohal, A. (2025). Leveraging top management support for blockchain-driven innovations in logistics and supply chain. Asia-Pacific Journal of Business Administration. Advance online publication. https://doi.org/10.1108/APJBA-10-2023-0512
    77. Wang, M., Kumar, M., & Tsolakis, N. (2025). Exploring the role of job satisfaction in enhancing logistics performance in the era of Industry 5.0. International Journal of Logistics Research and Applications. Advance online publication. https://doi.org/10.1080/13675567.2025.2333877
    78. Wang, Q. S., Wang, Y. G., & Chen, C. M. (2009). The experimental analysis of the roles of third party trust service on online purchase intentions. Business Management Journal, 31(7), 102–109.
    79. Wang, X. (2011). The relationship resaerch on network organization relationship interaction and network organizational efficiency [Doctoral disser-tation, Tianjin University].
    80. Wang, X. Y., Zhang, Y. J., & Ran, L. Z. (2018). Scale development of logistical synergistic capability of enterprises and its effect on market orien-tation and performance relationship. Journal of Management Science, 31(5), 56–73.
    81. Weir, J. P. (2005). Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. Journal of Strength and Conditioning Research, 19(1), 231–240. https://doi.org/10.1519/00124278-200502000-00038
    82. Wikipedia. (2021). Control variable. Retrieved July 29, 2025, from https://en.wikipedia.org/wiki/Control_variable
    83. Wu, Y. J., & Hou, J. L. (2010). An employee performance estimation model for the logistics industry. Decision Support Systems, 48(4), 568–581. https://doi.org/10.1016/j.dss.2009.11.008
    84. Yang, C. S., & Lin, M. S. (2024). The impact of digitalization and digital logistics platform adoption on organizational performance in maritime lo-gistics of Taiwan. Maritime Policy & Management, 51(8), 1884–1901. https://doi.org/10.1080/03088839.2023.2299343
    85. Yang, X. Q. (2016). Crowd logistics rules are the soul of management. Sino Foreign Management, 3, 48–49.
    86. Yang, Y., Obrenovic, B., Kamotho, D. W., Godinic, D., & Ostic, D. (2024). Enhancing job performance: The critical roles of well-being, satisfac-tion, and trust in supervisor. Behavioral Sciences, 14(8), 688. https://doi.org/10.3390/bs14080688
    87. Yao, P. J. (2019). The moderating effects of information sharing on supply chain performance: Research on fruit farmers’ feeling of relationship quality to wholesaler [Doctoral dissertation, Yunnan University of Finance and Economics].
    88. Yao, S. J., & Fan, Z. L. (2019). Customer participation, resource synergy and enterprise innovation performance: An empirical resaerch based on crowdsourcing platform. Journal of Nanjing Tech University (Social Science Edition), 18(1), 99–110.
    89. Ye, H., & Kankanhalli, A. (2017). Solvers’ participation in crowdsourcing platforms: Examining the impacts of trust, and benefit and cost factors. The Journal of Strategic Information Systems, 26(2), 101–117. https://doi.org/10.1016/j.jsis.2017.02.001
    90. Zhang, C., Zhang, G. S., & Wang, Y. L. (2020). Co-evolution and policy optimization of rural e-commerce and rural logistics under government poverty alleviation. Journal of Beijing Jiaotong University, 19(1), 98–105.
    91. Zhang, X. H. (2020). Research on collaboration of cross-border e-commerce and cross-border logistics under the Belt and Road Initiative. Contem-porary Economics and Management, 42(4), 27–32.
    92. Zhang, X. M., & Chen, W. (2011). Trust, relationship commitment and cooperative performance in supply chain – An empirical resaerch based on the perspective of knowledge trading. Studies in Science of Science, 29(12), 1865–1874.
    93. Zhang, X. R., & Yu, D. (2018). A resaerch on the development of sharing economy in China. Journal of Xinjiang Normal University (Edition of Philosophy and Social Sciences), 39(2), 132–146.
    94. Zhang, X. Y., Sun, Z. Z., & Hu, J. (2019). The constraints and their function mechanism of horizontal logistics collaboration in western logistics cluster based on grounded theory - Case resaerch of five provinces and municipalities. Journal of Business Economics, 9, 5–18.
    95. Zhao, X., Huo, B., Flynn, B., & Yeung, J. H. Y. (2008). The impact of power and relationship commitment on the integration between manufactur-ers and customers in a supply chain. Journal of Operations Management, 26(3), 368–388. https://doi.org/10.1016/j.jom.2007.08.002
    96. Zhou, H. (2017). Research on evaluation of operational capability of agricultural products logistics enterprises based on synergetic theory [Doctoral dissertation, Southwest Jiaotong University].
    97. Zhu, T. (2019). Research on users’ relationships’ development, maintenance, deepening based on the evolvement of social media [Doctoral disserta-tion, Huazhong University of Science and Technology]
  • Downloads

  • How to Cite

    Omoush, M. M. . (2025). Modeling The Influence of Trust on Employee Performance and Operations in Jordanian Logistics Companies through SEM-PLS. International Journal of Accounting and Economics Studies, 12(7), 219-230. https://doi.org/10.14419/kkn74y75