In recent years, a growing body of research has sought to unravel the complex landscape of citizens’ expectations regarding public services. This burgeoning interest reflects a fundamental shift in how public organizations engage with their constituents, emphasizing not only service delivery but also the nuanced anticipations that individuals hold before, during, and after interactions with government entities. At the heart of this inquiry lies the concept of Citizen Expectations of Public Services (CEPS), a construct that encapsulates the multifaceted perceptions and demands that citizens bring to their experiences with public institutions. Understanding CEPS is critical for the evolution of contemporary governance models, particularly as digital transformation reshapes the frontline of public service provision.
At a foundational level, CEPS encompass a broad range of expectations, often oscillating between generalized notions of performance and specific anticipations about service content and quality. Recent scholarly work categorizes CEPS into four primary types, illuminating a trajectory from broad, sometimes ambiguous perceptions toward more finely grained typologies. These include the general conceptions of CEPS and their confirmation or disconfirmation, which dominate the literature, performance and effort expectations central to the adoption of modern technology-driven services, a distinction between normative and predictive expectations that shapes citizens’ evaluation frameworks, and finally, expectations surrounding the content of services, crucial in contexts demanding rapid response and prioritization.
Analysis reveals that nearly 40% of studies focus on general CEPS or their confirmation/disconfirmation, drawing heavily on methodologies developed within citizen satisfaction and public service quality traditions. Initiatives like the American Customer Satisfaction Index (ACSI) and instruments pioneered by Parasuraman’s work between the mid-1980s and early 1990s laid the groundwork for quantifying these general expectations. Yet, these broad measures often obscure the subjective nature of citizens’ evaluations, which fluctuate based on individual benchmarks, previous experiences, and the perceived roles of public services. This ambiguity prompts debate over the validity and reliability of generalized CEPS measurements.
Addressing these methodological challenges, researchers James and colleagues have advanced the field by differentiating between normative and predictive CEPS. Normative expectations denote an ideal or “should-be” standard that citizens hold, reflecting collective societal values or personal ideals about what public services ought to provide. Predictive expectations, conversely, reflect individuals’ anticipations based on observable or past service performance, essentially forecasting what services will likely deliver. Although this dichotomy enriches the conceptual framework, these scales remain underutilized and lacking in standardization, limiting their present impact despite their potential to refine empirical insights into citizen satisfaction processes.
Emerging empirical findings underscore the critical distinctions between normative and predictive expectations. Studies suggest that citizens’ normative CEPS tend to remain stable and less susceptible to fluctuations in actual service performance, serving as enduring benchmarks against which satisfaction is gauged. Predictive CEPS, prone to adjustment based on recent experiences, exert a more transient influence on satisfaction judgments. Despite these insights, the measurement of these constructs is fraught with complexity. Existing scales frequently blur the lines between normative ideals and minimum acceptable service levels, complicating interpretations and signal a pressing need for robust, validated measurement tools within public administration research.
Complementing these classical CEPS dimensions are performance expectations (PE) and effort expectations (EE), constructs that gain prominence in the realm of technology-mediated public services. Rooted in the Unified Theory of Acceptance and Use of Technology (UTAUT), these expectations foreground citizens’ beliefs about the benefits of new digital services and the cognitive or physical effort required to use them effectively. This shift highlights an essential transformation in public service experience, where citizens are not merely passive recipients but active users navigating increasingly complex digital interfaces. Consequently, disparities in digital literacy, age, gender, and other sociodemographic factors significantly influence PE and EE, posing practical challenges for equitable service design and delivery.
The stakes of managing CEPS extend beyond day-to-day service interactions into crisis contexts, where expectations about service content and priority can profoundly affect public behavior. A small but significant subset of research investigates how clear and accurate expectations concerning service availability, prioritization, and responsiveness during emergencies—such as pandemics—can mitigate public panic, promote compliance with urgent policies, and enhance overall trust in government institutions. This domain underscores the practical necessity of aligning citizen expectations with organizational capacities in volatile environments, illustrating that public satisfaction is not merely retrospective but dynamically intertwined with anticipation management.
Measurement approaches across the diverse CEPS spectrum reveal a strong reliance on quantitative survey methods directed at ordinary citizens. These surveys frequently employ legacy scales, many of which trace their origins to consumer satisfaction research, adapted to public service contexts. Instruments like Van Ryzin’s general/(dis)confirmation scale, derived from ACSI and the Survey of Satisfaction with New York City Services (SSNYCS), are staples within this methodological toolkit. For normative and predictive CEPS, researchers often combine James’s scales with these canonical measures, though persistent measurement controversies invite further scrutiny and methodological innovation.
One enduring challenge resides in the conceptual ambiguity of CEPS as psychological constructs. Some scholars argue that expectations may not correspond to concrete or measurable service levels but instead function as fluid cognitive frameworks that shape satisfaction in less quantifiable ways. This epistemological ambiguity is compounded by public services’ distinctive characteristics—often intangible, heterogeneous, and administered within complex bureaucratic systems—compared to private-sector services. As such, debates continue regarding the conceptual clarity and operationalization of CEPS, especially pertaining to normative dimensions that inherently engage value judgments and societal norms.
Technological adoption within public services intensifies the importance of PE and EE as predictive measures. Empirical research increasingly documents these constructs as pivotal factors shaping user intentions and experiences in e-government, mobile government, and emerging AI-powered services. Scales developed by Venkatesh and other technology acceptance theorists have thus been widely incorporated into public administration research, particularly to capture pre-usage expectations and post-hoc evaluations of digital service encounters. These technological dimensions invite cross-disciplinary collaboration, linking public administration with information systems research in pursuit of enhanced citizen-centric service models.
Despite the array of measurement tools available, researchers emphasize the necessity of tailoring scales to fit specific research objectives and contexts. Whether focusing on broad citizen satisfaction, differentiating normative versus predictive expectations, or addressing the unique challenges posed by digital and crisis-oriented services, researchers must navigate tradeoffs regarding scale comprehensiveness, contextual relevance, and methodological rigor. This balancing act informs future research trajectories, encouraging iterative refinements and the development of standardized yet flexible frameworks that can accommodate evolving public service landscapes.
Moreover, the multidimensionality of CEPS calls for a conceptual synthesis that integrates disparate expectation types into cohesive theoretical models. By recognizing the interplay between normative ideals, predictive forecasts, functional benefits, and content-specific anticipations, scholars can construct richer explanatory frameworks that better reflect the lived experiences of citizens engaging with public services. Such models hold promise not only for academic understanding but also for practical applications in public management, policy design, and service innovation.
Importantly, citizen heterogeneity emerges as a critical consideration throughout this research domain. Factors such as socioeconomic status, cultural background, digital literacy, and prior service encounters shape how individuals form and adjust their CEPS. Appreciating this diversity is vital for designing inclusive public services that cater effectively to different segments of the population, ensuring fairness and enhancing legitimacy. Future research methodologies need to incorporate stratified sampling, mixed methods, and longitudinal designs to capture this complexity comprehensively.
From a practical standpoint, public administrators and policymakers benefit from these conceptual advances by gaining clearer insights into how citizen expectations shape satisfaction, trust, and engagement. Tailoring communication strategies, service delivery models, and feedback mechanisms to align more closely with citizens’ normative and predictive expectations can enhance perceived service quality. Additionally, integrating performance and effort considerations into technology adoption initiatives can improve user acceptance and reduce disparities in service utilization.
As governments worldwide grapple with increasing demands for transparency, accountability, and responsiveness, refined understanding and measurement of CEPS become indispensable. The systematic review of existing research lays a foundation for this endeavor, highlighting both promising avenues and persistent challenges. The ongoing evolution of public services amid digital transformation, demographic shifts, and complex societal challenges positions CEPS research at the forefront of governance innovation, with the potential to redefine citizen-government relationships in the decades ahead.
In conclusion, the study of citizens’ expectations about public services reveals a rich, intricate tapestry of perceptions that significantly influence satisfaction and engagement. By dissecting CEPS into definable types—general, normative, predictive, performance, effort, and service content expectations—researchers and practitioners can approach public service delivery with greater precision. The development and standardization of robust measurement instruments remain critical tasks, demanding interdisciplinary cooperation and empirical rigor. Ultimately, embracing the multidimensionality of CEPS fosters more responsive, effective, and equitable public services that resonate with citizens’ evolving needs and aspirations in an increasingly complex sociopolitical landscape.
Subject of Research: Citizens’ expectations about public services
Article Title: Citizens’ expectations about public services: a systematic literature review
Article References:
Qin, Z., Liu, B., Cao, Y. et al. Citizens’ expectations about public services: a systematic literature review.
Humanit Soc Sci Commun 12, 1123 (2025). https://doi.org/10.1057/s41599-025-05357-y
Image Credits: AI Generated
