Integration AI into an electronic supply chain (E-SCM) transforms human resources management in developing economies such as Jordan. Digital public procurement systems (DPS), AI-focused tools, and logistics platforms transform employees’ experience and organizational performance.
Objective
This study examines the impact of E-SCM-DPS components, inventory and management of workflows controlled by AI-DIWM and logistics and communication platforms (LCP).As focused on employees (ECO) and satisfaction with work) (EJS) that emphasize the role of human cooperation (HAIC).
Methods
Quantitative studies have collected data from 254 employees in Jordan’s industrial companies. The modeling of the structural equation (SEM) and the analysis of the confirmation factor (CFA) were performed using SPSS and AMOS to test hypotheses relationships and ensure the validity of measurement and reliability.
Results
DPS, AI-DIWM and LCP positively affect ECO, with HAIC significantly alleviating these relationships, increasing involvement and autonomy. The ECO fully mediates the connection between E-SCM and EJS components and emphasizes its role in improving work satisfaction.
Conclusion
E-SCM reconciliation with HR strategies supports strengthening the position of workforce. Structured training, user-friendly systems and intentional HAIC design create confidence and shared responsibility and offer managers available to integrate technology with human practices.
AbdiradMKrishnanK. Industry 4.0 in logistics and supply chain management: a systematic literature review. Eng Manag J2021; 33(3): 187–201.
2.
AndersonRESwaminathanS. Customer satisfaction and loyalty in e-markets: a PLS path modeling approach. J Market Theor Pract2011; 19(2): 221–234.
3.
AutryCWRoseWJBellJE. Reconsidering the supply chain integration-performance relationship: in search of theoretical consistency and clarity. J Bus Logist2014; 35(3): 275–276.
4.
Ben-DayaMHassiniEBahrounZ. Internet of things and supply chain management: a literature review. Int J Prod Res2019; 57(15-16): 4719–4742.
5.
ChavezRYuWJacobsMA, et al.Data-driven supply chains, manufacturing capability and customer satisfaction. Prod Plann Control2017; 28(11-12): 906–918.
6.
GarverMS. Threats to the validity of logistics and supply chain management research. J Bus Logist2019; 40(1): 30–43.
7.
HuaHCongP (2011). Analysis of E-SCM. In Communication Systems and Information Technology: Selected Papers from the 2011 International Conference on Electric and Electronics (EEIC 2011) in Nanchang, China on June 20-22, 2011, Vol. 4 (pp. 867–874). Springer Berlin Heidelberg.
8.
Le TanTThi Dai TrangD. Issues of implementing electronic supply chain management (E-SCM) in enterprise. European Business & Management2017; 3(5): 86–94.
9.
AlsheyadiABaawainAShaukatMR. E-supply chain coordination and performance impacts: an empirical investigation. Production & Manufacturing Research2024; 12(1): 2379942.
10.
Al-OmoushKSde LucasAdel ValMT. The role of e-supply chain collaboration in collaborative innovation and value-co creation. J Bus Res2023; 158: 113647.
11.
TaherdoostH. Supply chain management in e-business. In: E-business essentials: building a successful online enterprise. Springer Nature Switzerland, 2023, pp. 163–186.
12.
AdelHMYounisRAA. Interplay among blockchain technology adoption strategy, e-supply chain management diffusion, entrepreneurial orientation and human resources information system in banking. Int J Emerg Mark2023; 18(10): 3588–3615.
13.
AkyuzGARehanM. Requirements for forming an ‘e-supply chain. Int J Prod Res2009; 47(12): 3265–3287.
14.
ZamanSAAQaziHZafarA, et al.Emerging technologies and smart supply chain management: a roadmap for future success. Smart supply chain management: design, methods and impacts. Edinburgh, UK: Edinburgh Business School, Heriot-Watt University, 2025, pp. 135–156.
15.
LemessaZWWoldegiorgisBHSemegnAM. Opportunities and challenges of E-SCM in developing countries. Sustainable development research in manufacturing, process engineering, green infrastructure, and water resources: advancement of science and technology. Bahir Dar, Ethiopia: Bahir Dar Institute of Technology, Bahir Dar University, 2025, pp. 169–184.
16.
BarngetunyDCKimutaiG. Effects of e-procurement on supply chain management performance in Elgeyo-Marakwet county. Int Academic J Pro Sup Chain Manage2015; 1(5): 99–120.
17.
BarradSValverdeR. The impact of e-supply chain management systems on procurement operations and cost reduction in the electronics manufacturing services industry. Journal of Media Management and Entrepreneurship (JMME)2020; 2(1): 1–27.
18.
KamranASyedNAAhmedO, et al.Does E-Procurement adoption help textile industry of Pakistan for recruitment. In: International Conference on Management Science and Engineering Management. Springer Nature Singapore, 2024, pp. 1202–1228.
19.
ShahSKaphantengoT. Assessment of the impact of digitalisation on improvement of downstream supply chain performance. WSEAS Trans Bus Econ2025; 22: 493–515.
20.
AlzoubiHMTanCLEl KhatibM, et al.Smart government initiatives: transforming global supply chains through digital change. Int Rev Manag Market2025; 15(3): 209–217.
21.
RawatR. A systematic review of blockchain technology use in e-supply chain in internet of medical things (IoMT). Int J CIM2022; 2(2): 119.
22.
BlessingGKieferD. Digital skills of procurement employees and their attitudes toward digital technologies. In: International Conference on Human-Centered Intelligent Systems, 2021, May. Springer Singapore, pp. 173–182.
23.
FeikemaA. Digital transformation in procurement: plan, execute and adopt a successful digital procurement programme. Kogan Page Publishers, 2025.
24.
CoxK. Digital purchasing and procurement systems: evolution and current state. In: The digital supply chain. Elsevier, 2022, pp. 181–197.
25.
ChenYBretschneiderSStritchJM, et al.E-procurement system adoption in local governments: the role of procurement complexity and organizational structure. Public Manag Rev2022; 24(6): 903–925.
26.
Daneshvar KakhkiMShrivastavaU. Data analytics management capability and strategies for interorganisational collaborations: a survey research. Journal of Business Analytics2023; 6(4): 294–314.
27.
MalikABudhwarPS. Artificial intelligence and international HRM. Challenges, opportunities and a research Agenda. SAGE Publications, 2023.
28.
IvanovD. Simulation-based ripple effect modelling in the supply chain. Int J Prod Res2017; 55(7): 2083–2101.
29.
IvanovDSokolovBDolguiA. The ripple effect in supply chains: trade-off ‘efficiency-flexibility-resilience’ in disruption management. Int J Prod Res2014; 52(7): 2154–2172.
30.
DolguiAIvanovD. Ripple effect and supply chain disruption management: new trends and research directions. Int J Prod Res2021; 59(1): 102–109.
31.
LiYChenKCollignonS, et al.Ripple effect in the supply chain network: forward and backward disruption propagation, network health and firm vulnerability. Eur J Oper Res2021; 291(3): 1117–1131.
32.
MendonçaP. Supply chains and e-supply chains: the impact on flexibilisation of work and employment. In: Work, employment and flexibility. Edward Elgar Publishing, 2024, pp. 222–241.
33.
RulandariNSilalahiADK. Human-AI collaboration for efficiency and employee job satisfaction in public administration: insights from a resource-based perspective. Transforming Gov People, Process Policy2025; 19(2): 264–287.
34.
AjzenI. The theory of planned behavior. Organ Behav Hum Decis Process1991; 50(2): 179–211.
35.
TristEEmeryF. Sociotechnical systems theory. In: Organizational behavior 2. Routledge, 2015, pp. 169–194.
36.
DavisFD. Technology acceptance model: TAM. In: Al-SuqriMNAl-AufiAS (eds) Information seeking behavior and technology adoption. University of Michigan, 1989, 205, p. 5.
37.
LuthansFStewartTI. A general contingency theory of management. Acad Manag Rev1977; 2(2): 181–195.
38.
LiJHuangJLiuJ, et al.Human-AI cooperation: modes and their effects on attitudes. Telematics Inf2022; 73: 101862.
HairJFRisherJJSarstedtM, et al.When to use and how to report the results of PLS-SEM. Eur Bus Rev2019; 31(1): 2–24.
41.
HairFJrSarstedtMHopkinsL, et al.Partial least squares structural equation modeling (PLS-SEM) an emerging tool in business research. Eur Bus Rev2014; 26(2): 106–121.
42.
DeviMKDharMMUnnamalaiK, et al.A human-centered approach to artificial intelligence in the supply chain. In: Data-driven technologies and artificial intelligence in supply chain. CRC Press, 2023, pp. 1–30.
43.
HairJFSarstedtMRingleCM. Rethinking some of the rethinking of partial least squares. Eur J Market2019; 53(4): 566–584.
44.
KumandangCRuslainiRSantosoS, et al.Optimizing organizational performance: exploring the integration of AI and HR practices. In The International Conference on Education, Social Sciences and Technology (ICESST) (Vol. 1, No. 2, pp. 269–277), 2022, December.
45.
XuCChoSE. Factors Affecting Human–AI Collaboration Performances in Financial Sector: Sustainable Service Development Perspective. Sustainability2025; 17(10): 4335.
46.
StrittoGDSchiraldiMM. A strategy oriented framework for food and beverage e-supply chain management. Int J Eng Bus Manag2013; 5: 50.
47.
DuTLiXJiangN, et al.Adaptive AI as collaborator: examining the impact of an AI’s adaptability and social role on individual professional efficacy and credit attribution in Human–AI collaboration. Int J Hum Comput Interact2025; Publised online: 1–12.
48.
WirokoEPMurtyAI. How does business owner’s employee-centric leadership affect SME Employees’ Work Engagement: the Mediating Role of “Diuwongke”. In: Indigenous entrepreneurship in Southeast Asia: theoretical and practical implications. Springer International Publishing, 2024, pp. 251–262.
49.
KocollariUCavicchioliMDemariaF. The 5 E (lements) of employee-centric corporate social responsibility and their stimulus on happiness at work: an empirical investigation. Corp Soc Responsib Environ Manag2024; 31(3): 1959–1976.
50.
HoogervorstJ. The imperative for employee-centric organizing and its significance for enterprise engineering. Organ Des Enterp Eng2017; 1: 43–58.
51.
EvansL. Reconceptualizing effective professional development for teachers: shifting from causal chains and generativity to complexity and employee-centrism. Int J Leader Educ2025; Publised online: 1–23.
52.
RulandariNSilalahiADK. Achieving effectiveness of public service in AI-enabled service from public value theory: does human–AI collaboration matters?Transforming Gov People, Process Policy2025; 19(2): 428–452.
53.
SrimongkolkulPBorirajJWongsansukcharoenJ. Effects of authentic leadership, employee resilience, job satisfaction, and innovative work behavior on employee work performance in transport and logistics of Thailand. Cogent Business & Management2025; 12(1): 2511282.
54.
VaithilingamSOngCSMoisescuOI, et al.Robustness checks in PLS-SEM: a review of recent practices and recommendations for future applications in business research. J Bus Res2024; 173: 114465.
55.
MuhammadiyahO. The effect of job empowerment on the creative behavior of workers at the Jordan tourism board. Jordan J Bus Adm2016; 10(2): 220–239.
56.
WilkinsonKVlachopoulosDKlentrouP, et al.Soft tissues, areal bone mineral density and hip geometry estimates in active young boys: the PRO-BONE study. Eur J Appl Physiol2017; 117: 833–842.
57.
ChuanCLPenyelidikanJ. Sample size estimation using Krejcie and Morgan and Cohen statistical power analysis: a comparison. Jurnal Penyelidikan IPBL2006; 7(1): 78–86.
58.
KulalARahimanHUSuvarnaH, et al.Enhancing public service delivery efficiency: exploring the impact of AI. J Open Innov Technol Mark Complex2024; 10(3): 100329.
59.
WuH. The impact of employee satisfaction on firm profitability: a focus on employee performance and customer satisfaction. J Appl Eco Policy Stud2024; 10: 62–72.
60.
RondaLValorCAbrilC. Are they willing to work for you? An employee-centric view to employer brand attractiveness. J Prod Brand Manag2018; 27(5): 573–596.
