RESEARCH ARTICLE
Resolving the Effectiveness–Efficiency Paradox in AI-Enabled Public Services: Insights From the Resource-Based View and Public Value Theory
Novianita Rulandari,
Andri Dayarana K. Silalahi,
Novianita Rulandari
Master Program of Public Administration, Universitas Muhammadiyah Palangkaraya, Palangkaraya, Indonesia
Search for more papers by this authorCorresponding Author
Andri Dayarana K. Silalahi
Department of Marketing and Logistics Management, College of Management, Chaoyang University of Technology, Taichung, Taiwan
Correspondence:
Andri Dayarana K. Silalahi ([email protected])
Search for more papers by this authorNovianita Rulandari,
Andri Dayarana K. Silalahi,
Novianita Rulandari
Master Program of Public Administration, Universitas Muhammadiyah Palangkaraya, Palangkaraya, Indonesia
Search for more papers by this authorCorresponding Author
Andri Dayarana K. Silalahi
Department of Marketing and Logistics Management, College of Management, Chaoyang University of Technology, Taichung, Taiwan
Correspondence:
Andri Dayarana K. Silalahi ([email protected])
Search for more papers by this authorFirst published: 15 July 2025
Funding: The authors received no specific funding for this work.
ABSTRACT
The integration of AI in public services creates a paradox where efficiency can undermine effectiveness, affecting service quality, citizen trust, and stakeholder satisfaction. This study addresses the dual outcomes of citizen and employee satisfaction, highlighting the moderating role of Human-AI collaboration in balancing these dimensions. Drawing on the Resource-Based View (RBV) and Perceived Value Theory (PVT), the research examines AI's impact on citizen satisfaction (effectiveness) and employee satisfaction (efficiency). Data were collected from 805 government employees and 699 citizens across multiple Indonesian public agencies over a 6-month period in 2024 and analyzed through Structural Equation Modeling (SEM). Results show that service accuracy, transparency, and trust enhance citizen satisfaction, while processing time, accessibility, and resource utilization improve employee satisfaction. Human-AI collaboration moderates the relationship between efficiency and service quality, aligning effectiveness and efficiency to achieve dual satisfaction. By addressing theoretical gaps in public administration and AI adoption, the study underscores Human-AI collaboration as a critical mechanism for integrating technological solutions with human oversight.
Conflicts of Interest
The authors declare no conflicts of interest.
Open Research
Data Availability Statement
Data will be made available on request.
References
- Addis, S., A. Dvivedi, and B. Beshah. 2019. “Quality Management as a Tool for Job Satisfaction Improvement in Low-Level Technology Organizations: The Case of Ethiopia.” Production Planning & Control 30, no. 8: 665–681.
- Alanezi, M. A., A. K. Mahmood, and S. Basri. 2012. “E-Government Service Quality: A Qualitative Evaluation in the Case of Saudi Arabia.” Electronic Journal of Information Systems in Developing Countries 54, no. 1: 1–20.
10.1002/j.1681-4835.2012.tb00382.x Google Scholar
- Alfrink, K., I. Keller, N. Doorn, and G. Kortuem. 2023. “Tensions in Transparent Urban AI: Designing a Smart Electric Vehicle Charge Point.” AI & Society 38, no. 3: 1049–1065.
- Alkhawaldah, R. A., F. S. Alshalabi, Z. A. E. Alshawabkeh, M. N. Almarshad, M. H. Al-Tahrawi, and T. Z. A. Alshawabkeh. 2024. “The Role of E-Government in Organizational Effectiveness: The Mediating Role of Administrative Empowerment.” Human Systems Management 44: 432–447.
- Alkraiji, A. I. 2020. “Citizen Satisfaction With Mandatory E-Government Services: A Conceptual Framework and an Empirical Validation.” IEEE Access 8: 117253–117265.
- Alon-Barkat, S., and M. Busuioc. 2023. “Human–AI Interactions in Public Sector Decision Making: ‘Automation Bias’ and ‘Selective Adherence’ to Algorithmic Advice.” Journal of Public Administration Research and Theory 33, no. 1: 153–169.
- Arend, R. J., and P. Bromiley. 2009. “Assessing the Dynamic Capabilities View: Spare Change, Everyone?” Strategic Organization 7, no. 1: 75–90. https://doi.org/10.1177/1476127008100132.
- Barney, J. 1991. “Firm Resources and Sustained Competitive Advantage.” Journal of Management 17, no. 1: 99–120.
- Baumgartner, H., B. Weijters, and R. Pieters. 2021. “The Biasing Effect of Common Method Variance: Some Clarifications.” Journal of the Academy of Marketing Science 49: 221–235.
- Benington, J., and M. Moore. 2010. Public Value: Theory and Practice. Bloomsbury Publishing.
- Bouckaert, G., and S. Van de Walle. 2003. “Comparing Measures of Citizen Trust and User Satisfaction as Indicators of ‘Good Governance’: Difficulties in Linking Trust and Satisfaction Indicators.” International Review of Administrative Sciences 69, no. 3: 329–343.
- Bracci, E. 2023. “The Loopholes of Algorithmic Public Services: An ‘Intelligent’ Accountability Research Agenda.” Accounting, Auditing & Accountability Journal 36, no. 2: 739–763.
- Bryson, J. M., B. C. Crosby, and L. Bloomberg. 2014. “Public Value Governance: Moving Beyond Traditional Public Administration and the New Public Management.” Public Administration Review 74, no. 4: 445–456. https://doi.org/10.1111/puar.12238.
- Caldwell, C., and L. A. Hayes. 2007. “Leadership, Trustworthiness, and the Mediating Lens.” Journal of Management Development 26, no. 3: 261–281.
10.1108/02621710710732155 Google Scholar
- Carter, L., and F. Bélanger. 2005. “The Utilization of E-Government Services: Citizen Trust, Innovation, and Acceptance Factors.” Information Systems Journal 15, no. 1: 5–25.
- Chan, F. K., J. Y. Thong, S. A. Brown, and V. Venkatesh. 2021. “Service Design and Citizen Satisfaction With E-Government Services: A Multidimensional Perspective.” Public Administration Review 81, no. 5: 874–894.
- Chatterjee, S., S. Khorana, and H. Kizgin. 2022. “Harnessing the Potential of Artificial Intelligence to Foster Citizens' Satisfaction: An Empirical Study on India.” Government Information Quarterly 39, no. 4: 101621.
- Chen, P., P. Sparrow, and C. Cooper. 2016. “The Relationship Between Person-Organization Fit and Job Satisfaction.” Journal of Managerial Psychology 31, no. 5: 946–959. https://doi.org/10.1108/jmp-08-2014-0236.
- Chen, T., W. Guo, X. Gao, and Z. Liang. 2021. “AI-Based Self-Service Technology in Public Service Delivery: User Experience and Influencing Factors.” Government Information Quarterly 38, no. 4: 101520.
- Chowdhury, S., P. Budhwar, P. K. Dey, S. Joel-Edgar, and A. Abadie. 2022. “AI-Employee Collaboration and Business Performance: Integrating Knowledge-Based View, Socio-Technical Systems, and Organisational Socialisation Framework.” Journal of Business Research 144: 31–49.
- Cohen, J. 2013. Statistical Power Analysis for the Behavioral Sciences. Routledge. https://doi.org/10.4324/9780203771587.
10.4324/9780203771587 Google Scholar
- Collins, B. K., and H. J. Kim. 2009. “Are Satisfied Citizens Willing to Pay More? Public Sector Consumerism as Equitable Social Exchange.” Public Money & Management 29, no. 2: 109–116.
10.1080/09540960902768004 Google Scholar
- Cranefield, J., M. Winikoff, Y. T. Chiu, Y. Li, C. Doyle, and A. Richter. 2023. “Partnering With AI: The Case of Digital Productivity Assistants.” Journal of the Royal Society of New Zealand 53, no. 1: 95–118.
- Criado, J. I., and J. R. Gil-Garcia. 2019. “Creating Public Value Through Smart Technologies and Strategies: From Digital Services to Artificial Intelligence and Beyond.” International Journal of Public Sector Management 32, no. 5: 438–450.
10.1108/IJPSM-07-2019-0178 Google Scholar
- de Fine Licht, K., and J. Fine Licht. 2020. “Artificial Intelligence, Transparency, and Public Decision-Making: Why Explanations Are Key When Trying to Produce Perceived Legitimacy.” AI & Society 35: 917–926.
10.1007/s00146-020-00960-w Google Scholar
- Desiere, S., and L. Struyven. 2021. “Using Artificial Intelligence to Classify Jobseekers: The Accuracy-Equity Trade-Off.” Journal of Social Policy 50, no. 2: 367–385.
- Evans, J. R., and W. M. Lindsay. 2011. The Management and Control of Quality. South-Western Cengage Learning.
- Falk, R. F. 1992. A Primer for Soft Modeling. Ohio University of Akron Press.
- Fatima, S., K. C. Desouza, C. Buck, and E. Fielt. 2022. “Public AI Canvas for AI-Enabled Public Value: A Design Science Approach.” Government Information Quarterly 39, no. 4: 101722.
- Flathmann, C., B. G. Schelble, P. J. Rosopa, N. J. McNeese, R. Mallick, and K. C. Madathil. 2023. “Examining the Impact of Varying Levels of AI Teammate Influence on Human-AI Teams.” International Journal of Human-Computer Studies 177: 103061.
- Fleischer, J., and C. Wanckel. 2023. “Creativity in Policy Capacity: Organizational and Individual Determinants.” Public Administration Review 84, no. 2: 218–232. https://doi.org/10.1111/puar.13676.
- Fleischer, J., and C. Wanckel. 2024. “Job Satisfaction and the Digital Transformation of the Public Sector: The Mediating Role of Job Autonomy.” Review of Public Personnel Administration 44, no. 3: 431–452.
- Floridi, L. 2020. “Artificial Intelligence as a Public Service: Learning From Amsterdam and Helsinki.” Philosophy and Technology 33, no. 4: 541–546.
10.1007/s13347-020-00434-3 Google Scholar
- A. Florini, ed. 2007. The Right to Know: Transparency for an Open World. Columbia University Press.
10.7312/flor14158 Google Scholar
- Fukumoto, E., and B. Bozeman. 2019. “Public Values Theory: What Is Missing?” American Review of Public Administration 49, no. 6: 635–648.
- Grimmelikhuijsen, S. 2012. “Linking Transparency, Knowledge, and Citizen Trust in Government: An Experiment.” International Review of Administrative Sciences 78, no. 1: 50–73.
- Hair, J., C. L. Hollingsworth, A. B. Randolph, and A. Y. L. Chong. 2017. “An Updated and Expanded Assessment of PLS-SEM in Information Systems Research.” Industrial Management & Data Systems 117, no. 3: 442–458.
- Harter, J. K., F. L. Schmidt, and T. L. Hayes. 2002. “Business-Unit-Level Relationship Between Employee Satisfaction, Employee Engagement, and Business Outcomes: A Meta-Analysis.” Journal of Applied Psychology 87, no. 2: 268–279.
- Hasche, N., L. Höglund, and M. Mårtensson. 2021. “Intra-Organizational Trust in Public Organizations: The Study of Interpersonal Trust in Both Vertical and Horizontal Relationships From a Bidirectional Perspective.” Public Management Review 23, no. 12: 1768–1788.
- He, C., R. Teng, and J. Song. 2023. “Linking Employees' Challenge-Hindrance Appraisals Toward AI to Service Performance: The Influences of Job Crafting, Job Insecurity, and AI Knowledge.” International Journal of Contemporary Hospitality Management 36, no. 3: 975–994.
- Heald, D. 2006. Varieties of Transparency. In No. 135, 25–43. Oxford University Press for The British Academy.
- Henkel, A. P., S. Bromuri, D. Iren, and V. Urovi. 2020. “Half Human, Half Machine: Augmenting Service Employees With AI for Interpersonal Emotion Regulation.” Journal of Service Management 31, no. 2: 247–265.
- Henseler, J., C. M. Ringle, and M. Sarstedt. 2015. “A New Criterion for Assessing Discriminant Validity in Variance-Based Structural Equation Modeling.” Journal of the Academy of Marketing Science 43: 115–135.
- Hong, S. G., and D. Lee. 2023. “Development of a Citizen Participation Public Service Innovation Model Based on Smart Governance.” Service Business 17, no. 3: 669–694.
- Hou, K., T. Hou, and L. Cai. 2023. “Exploring Trust in Human–AI Collaboration in the Context of Multiplayer Online Games.” System 11, no. 5: 217.
10.3390/systems11050217 Google Scholar
- Javed, M. U., N. Javaid, A. Aldegheishem, N. Alrajeh, M. Tahir, and M. Ramzan. 2020. “Scheduling Charging of Electric Vehicles in a Secured Manner by Emphasizing Cost Minimization Using Blockchain Technology and IPFS.” Sustainability 12, no. 12: 5151.
- Jiang, N., X. Liu, H. Liu, E. T. K. Lim, C. W. Tan, and J. Gu. 2023. “Beyond AI-Powered Context-Aware Services: The Role of Human–AI Collaboration.” Industrial Management & Data Systems 123, no. 11: 2771–2802.
- Kalambokidis, L. 2014. “Creating Public Value With Tax and Spending Policies: The View From Public Economics.” Public Administration Review 74, no. 4: 519–526.
- Kim, Y., S. Myeong, and M. J. Ahn. 2023. “Living Labs for AI-Enabled Public Services: Functional Determinants, User Satisfaction, and Continued Use.” Sustainability 15, no. 11: 8672.
- Kinowska, H., and Ł. J. Sienkiewicz. 2023. “Influence of Algorithmic Management Practices on Workplace Well-Being: Evidence From European Organisations.” Information Technology & People 36, no. 8: 21–42.
10.1108/ITP-02-2022-0079 Google Scholar
- Kleizen, B., W. Van Dooren, K. Verhoest, and E. Tan. 2023. “Do Citizens Trust Trustworthy Artificial Intelligence? Experimental Evidence on the Limits of Ethical AI Measures in Government.” Government Information Quarterly 40, no. 4: 101834.
10.1016/j.giq.2023.101834 Google Scholar
- Koskimies, E., and T. Kinder. 2022. “Mutuality in AI-Enabled New Public Service Solutions.” Public Management Review 26, no. 1: 219–244. https://doi.org/10.1080/14719037.2022.2078501.
- Koskimies, E., J. Stenvall, T. Kinder, J. Leikas, and M. Nieminen. 2022. “ Artificial Intelligence and Public Innovations.” In Public Innovation and Digital Transformation, vol. 68. Routledge, Taylor and Francis.
10.4324/9781003230854-5 Google Scholar
- Kulal, A., H. U. Rahiman, H. Suvarna, N. Abhishek, and S. Dinesh. 2024. “Enhancing Public Service Delivery Efficiency: Exploring the Impact of AI.” Journal of Open Innovation: Technology, Market, and Complexity 10, no. 3: 100329.
10.1016/j.joitmc.2024.100329 Google Scholar
- Kumar, R., R. Kumar, A. Sachan, and P. Gupta. 2021. “An Examination of the E-Government Service Value Chain.” Information Technology & People 34, no. 3: 889–911.
- Kurti, S., and K. Kina. 2024. “Citizen Satisfaction's Determinants With the Integrated Public Services Quality Provided by One-Stop-Shop: A Case From a Western Balkan Country.” Public Policy and Administration 23, no. 3: 369–381.
10.5755/j01.ppaa.23.3.31953 Google Scholar
- Lai, K. K., T. H. Liu, and F. C. Kao. 2009. “Why Is Quality Improving Continuously? An Integrated Perspective of Institution Theory and the Resource-Based View of the Firm.” Total Quality Management 20, no. 10: 1111–1122.
10.1080/14783360903247098 Google Scholar
- Latan, H., C. J. Chiappetta Jabbour, A. B. de Lopes Sousa Jabbour, M. Ali, and V. Pereira. 2022. “Career Satisfaction in the Public Sector: Implications for a More Sustainable and Socially Responsible Human Resource Management.” Human Resource Management Journal 32, no. 4: 844–863.
- Le, K. B. Q., L. Sajtos, and K. V. Fernandez. 2023. “Employee-(Ro)bot Collaboration in Service: An Interdependence Perspective.” Journal of Service Management 34, no. 2: 176–207.
- Li, Y., and H. Shang. 2020. “Service Quality, Perceived Value, and Citizens' Continuous-Use Intention Regarding E-Government: Empirical Evidence From China.” Information & Management 57, no. 3: 103197.
- Li, Y., Y. Fan, and L. Nie. 2023. “Making Governance Agile: Exploring the Role of Artificial Intelligence in China's Local Governance.” Public Policy and Administration 40, no. 2: 276–301.
- Liu, B., T. Chen, P. Jia, and L. Wang. 2020. “Effective Public Service Delivery Supported by Time-Decayed Bayesian Personalized Ranking.” Knowledge-Based Systems 206: 106376.
- Loske, D., and M. Klumpp. 2021. “Intelligent and Efficient? An Empirical Analysis of Human–AI Collaboration for Truck Drivers in Retail Logistics.” International Journal of Logistics Management 32, no. 4: 1356–1383.
10.1108/IJLM-03-2020-0149 Google Scholar
- Loureiro, S. M. C., R. G. Bilro, and D. Neto. 2023. “Working With AI: Can Stress Bring Happiness?” Service Business 17, no. 1: 233–255.
10.1007/s11628-022-00514-8 Google Scholar
- Mahoney, J. T., and J. R. Pandian. 1992. “The Resource-Based View Within the Conversation of Strategic Management.” Strategic Management Journal 13, no. 5: 363–380. https://doi.org/10.1002/smj.4250130505.
- Mansoor, M. 2021. “Citizens' Trust in Government as a Function of Good Governance and Government Agency's Provision of Quality Information on Social Media During COVID-19.” Government Information Quarterly 38, no. 4: 101597.
- Marikyan, D., S. Papagiannidis, O. F. Rana, R. Ranjan, and G. Morgan. 2022. ““Alexa, Let's Talk About My Productivity”: The Impact of Digital Assistants on Work Productivity.” Journal of Business Research 142: 572–584. https://doi.org/10.1016/j.jbusres.2022.01.015.
- Mikhaylov, S. J., M. Esteve, and A. Campion. 2018. “Artificial Intelligence for the Public Sector: Opportunities and Challenges of Cross-Sector Collaboration.” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 376, no. 2128: 20170357.
- Mishra, L., and S. Varma. 2020. “Performance Evaluation of Real-Time Stream Processing Systems for Internet of Things Applications.” Future Generation Computer Systems 113: 207–217.
- Moore, M. H. 1995. Creating Public Value: Strategic Management in Government. Harvard University Press.
- Mukherjee, P. K. 2022. “ Artificial Intelligence-Based Smart Government Enterprise Architecture (AI-SGEA) Framework.” In International Symposium on Artificial Intelligence, 325–333. Springer Nature Switzerland.
10.1007/978-3-031-22485-0_30 Google Scholar
- Noor, N., S. Rao Hill, and I. Troshani. 2022. “Recasting Service Quality for AI-Based Service.” Australasian Marketing Journal 30, no. 4: 297–312.
10.1177/18393349211005056 Google Scholar
- O’Flynn, J. 2007. “From New Public Management to Public Value: Paradigmatic Change and Managerial Implications.” Australian Journal of Public Administration 66, no. 3: 353–366. https://doi.org/10.1111/j.1467-8500.2007.00545.x.
- Olan, F., E. O. Arakpogun, J. Suklan, F. Nakpodia, N. Damij, and U. Jayawickrama. 2022. “Artificial Intelligence and Knowledge Sharing: Contributing Factors to Organizational Performance.” Journal of Business Research 145: 605–615.
- Osei-Kojo, A. 2017. “E-Government and Public Service Quality in Ghana.” Journal of Public Affairs 17, no. 3: e1620.
- Pandey, J. K. 2024. “Evaluating Public Service Value Within Collaborative E-Governance: A Study in the Indian Context.” Digital Transformation and Society 3, no. 2: 197–213.
10.1108/DTS-08-2023-0065 Google Scholar
- Pereira, G. V., M. A. Macadar, E. M. Luciano, and M. G. Testa. 2016. “Delivering Public Value Through Open Government Data Initiatives in a Smart City Context.” Information Systems Frontiers 19, no. 2: 213–229. https://doi.org/10.1007/s10796-016-9673-7.
10.1007/s10796-016-9673-7 Google Scholar
- Prebble, M. 2018. “Is ‘We’ Singular? The Nature of Public Value.” American Review of Public Administration 48, no. 2: 103–118.
10.1177/0275074016671427 Google Scholar
- Prokop, C., and M. Tepe. 2021. “Talk or Type? The Effect of Digital Interfaces on Citizens’ Satisfaction With Standardized Public Services.” Public Administration 100, no. 2: 427–443. https://doi.org/10.1111/padm.12739.
10.1111/padm.12739 Google Scholar
- Prysmakova, P. 2020. “Contact With Citizens and Job Satisfaction: Expanding Person-Environment Models of Public Service Motivation.” Public Management Review 23, no. 9: 1339–1358. https://doi.org/10.1080/14719037.2020.1751252.
- Robins, J., and M. F. Wiersema. 1995. “A Resource-Based Approach to the Multibusiness Firm: Empirical Analysis of Portfolio Interrelationships and Corporate Financial Performance.” Strategic Management Journal 16, no. 4: 277–299.
- Robles, P., and D. J. Mallinson. 2023. “Artificial Intelligence Technology, Public Trust, and Effective Governance.” Review of Policy Research 00: 1–18.
- Ryzin, G. G. V. 2004. “The Measurement of Overall Citizen Satisfaction.” Public Performance & Management Review 27, no. 3: 9–28.
- Santa, R., J. B. MacDonald, and M. Ferrer. 2019. “The Role of Trust in E-Government Effectiveness, Operational Effectiveness, and User Satisfaction: Lessons From Saudi Arabia in E-G2B.” Government Information Quarterly 36, no. 1: 39–50.
- Scutella, M., C. Plewa, and C. Reaiche. 2024. “Virtual Agents in the Public Service: Examining Citizens' Value-In-Use.” Public Management Review 26, no. 1: 73–88.
- Snyder, H. 2019. “Literature Review as a Research Methodology: An Overview and Guidelines.” Journal of Business Research 104: 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039.
- Talbot, C. 2009. “Public Value—The Next “Big Thing” in Public Management?” International Journal of Public Administration 32, no. 3–4: 167–170. https://doi.org/10.1080/01900690902772059.
10.1080/01900690902772059 Google Scholar
- Tan, S. C., W. Chen, and B. L. Chua. 2023. “Leveraging Generative Artificial Intelligence Based on Large Language Models for Collaborative Learning.” Learning: Research and Practice 9, no. 2: 125–134.
10.1080/23735082.2023.2258895 Google Scholar
- Tenenhaus, M., V. E. Vinzi, Y. M. Chatelin, and C. Lauro. 2005. “PLS Path Modeling.” Computational Statistics & Data Analysis 48, no. 1: 159–205.
- Tranfield, D., D. Denyer, and P. Smart. 2003. “Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review.” British Journal of Management 14, no. 3: 207–222. https://doi.org/10.1111/1467-8551.00375.
- Valle-Cruz, D., and R. García-Contreras. 2023. “Towards AI-Driven Transformation and Smart Data Management: Emerging Technological Change in the Public Sector Value Chain.” Public Policy and Administration 40, no. 2: 254–275.
- van der Voet, J., and P. van den Bekerom. 2024. “Performance Information, Expectations, and Satisfaction With Public Service Delivery in the Context of co-Production Initiatives.” Public Management Review 27, no. 4: 1157–1178.
- Vassilakopoulou, P., A. Haug, L. M. Salvesen, and I. O. Pappas. 2023. “Developing Human/AI Interactions for Chat-Based Customer Services: Lessons Learned From the Norwegian Government.” European Journal of Information Systems 32, no. 1: 10–22.
- Véronneau, S., and Y. Cimon. 2007. “Maintaining Robust Decision Capabilities: An Integrative Human–Systems Approach.” Decision Support Systems 43, no. 1: 127–140.
- Vigoda, E. 2000. “Are You Being Served? The Responsiveness of Public Administration to Citizens' Demands: An Empirical Examination in Israel.” Public Administration 78, no. 1: 165–191.
- Wagenheim, G. D., and J. H. Reurink. 1991. “Customer Service in Public Administration.” Public Administration Review 51: 263–270.
- Walmsley, J. 2021. “Artificial Intelligence and the Value of Transparency.” AI & Society 36, no. 2: 585–595.
- Wan, X., A. K. Jha, N. Kazantsev, and W. F. Boh. 2023. “Online-To-Offline Platforms: Examining the Effects of Demand-Side Usage on Supply-Side Decisions.” Information & Management 60, no. 2: 103757.
- Wang, C., T. S. Teo, and M. Janssen. 2021. “Public and Private Value Creation Using Artificial Intelligence: An Empirical Study of AI Voice Robot Users in the Chinese Public Sector.” International Journal of Information Management 61: 102401.
10.1016/j.ijinfomgt.2021.102401 Google Scholar
- Wang, D., and X. Zhao. 2024. “Effect of Resource Integration on Organizational Resilience of Megaprojects: Role of Dynamic Capability and Resource Availability.” Journal of Asian Architecture and Building Engineering 24: 1–1593.
- Wang, Y.-F., Y.-C. Chen, and S.-Y. Chien. 2023. “Citizens' Intention to Follow Recommendations From a Government-Supported AI-Enabled System.” Public Policy and Administration 40, no. 2: 372–400.
- Wernerfelt, B. 1984. “A Resource-Based View of the Firm.” Strategic Management Journal 5, no. 2: 171–180.
- Wetzels, M., G. Odekerken-Schröder, and C. Van Oppen. 2009. “Using PLS Path Modeling for Assessing Hierarchical Construct Models: Guidelines and Empirical Illustration.” MIS Quarterly 33, no. 1: 177–195.
- Willems, J., M. J. Schmid, D. Vanderelst, D. Vogel, and F. Ebinger. 2023. “AI-Driven Public Services and the Privacy Paradox: Do Citizens Really Care About Their Privacy?” Public Management Review 25, no. 11: 2116–2134.
10.1080/14719037.2022.2063934 Google Scholar
- Williams, I., and H. Shearer. 2011. “Appraising Public Value: Past, Present, and Futures.” Public Administration 89, no. 4: 1367–1384.
- Wixom, B. H., and P. A. Todd. 2005. “A Theoretical Integration of User Satisfaction and Technology Acceptance.” Information Systems Research 16, no. 1: 85–102.
- Yang, Y. 2018. “Is Transparency a Double-Edged Sword in Citizen Satisfaction With Public Service? Evidence From China's Public Healthcare.” Journal of Service Theory and Practice 28, no. 4: 484–506.
10.1108/JSTP-06-2017-0102 Google Scholar
- Yap, C. S., R. Ahmad, F. T. Newaz, and C. Mason. 2021. “Continuous Use and Extended Use of E-Government Portals in Malaysia.” International Journal of Public Administration 44, no. 15: 1329–1340.
- Yigitcanlar, T., R. Y. M. Li, P. B. Beeramoole, and A. Paz. 2023. “Artificial Intelligence in Local Government Services: Public Perceptions From Australia and Hong Kong.” Government Information Quarterly 40, no. 3: 101833.
- Yin, Y., Q. Di, J. Wan, and T. Liang. 2023. “Time-Aware Smart City Services Based on QoS Prediction: A Contrastive Learning Approach.” IEEE Internet of Things Journal 10, no. 21: 18745–18753.
- Young, M. M., J. B. Bullock, and J. D. Lecy. 2019. “Artificial Discretion as a Tool of Governance: A Framework for Understanding the Impact of Artificial Intelligence on Public Administration.” Perspectives on Public Management and Governance 2, no. 4: 301–313.
- Yue, B., and H. Li. 2023. “The Impact of Human-AI Collaboration Types on Consumer Evaluation and Usage Intention: A Perspective of Responsibility Attribution.” Frontiers in Psychology 14: 1277861.
- Zhang, J., G. Puron-Cid, and J. R. Gil-Garcia. 2015. “Creating Public Value Through Open Government: Perspectives, Experiences and Applications.” Information Polity 20, no. 2–3: 97–101. https://doi.org/10.3233/ip-150364.
10.3233/IP-150364 Google Scholar
- Zhang, X., P. Yu, L. Ma, and Y. Liang. 2024. “How the Human-Like Characteristics of AI Assistants Affect Employee Creativity: A Social Network Ties Perspective.” International Journal of Human-Computer Interaction 41, no. 10: 6431–6649.
