2.1.1. Digitally enabled public participation

New data-driven and digitized forms of public participation have emerged as a result of the increased availability of data and the digitalization of many government processes (Welch, Reference Welch2012; Ingrams et al., Reference Ingrams2019). This includes new methods for engaging citizens in the policy-making process (e.g., through the provision of digital platforms to solicit and respond to stakeholder feedback) (Tseng, Reference Tseng2023), data-driven approaches to service development, or the use of data to drive accountability and transparency (open government data, as an example). Many of these are discussed in more detail in future sections of this paper, further demonstrating this area of research’s interconnectedness.

In many cases, these methods for participation can be further subdivided into ‘passive’ and ‘active’ forms (Grêt-Regamey et al., Reference Gret-Regamey, Switalski, Fagerholm, Korpilo, Juhola, Kytta, Kayhko, McPhearson, Nollert, Rinne, Soininen, Toivonen, Rasanen, Willberg and Raymond2021). In the case of the latter, one would see citizens being directly involved and engaged in new data-driven initiatives, for example providing feedback to a proposed piece of legislation during an open review process. Whereas the former would see citizens only playing a more passive role, for example, by using a sensor or app on their phone to generate data for a public sector organization on, for example, air quality (e.g., citizen science projects).

In addition, research highlights that there are pressing questions around equity as studies show a clear relationship between socioeconomic status and participation (e.g., Brady et al., Reference Brady, Schlozman and Verba2012), and, more specifically, a relationship between individual characteristics, socio-economic status, and stratification theory (education, income, and occupation) thereby illustrating that a citizen’s political efficacy and participation is reflective of their personal history (Brady et al., Reference Brady, Verba and Schlozman1995; Clark, Reference Clark2017; Toots, Reference Toots2019).

Similarly, also from a political perspective, numerous approaches have been proposed to understand how citizens engage with public services. Some focus on the ‘administrative burden’ that citizens experience and highlight how “hidden politics in the policy process affect and sustain persistent inequities in policy access” (Burden et al., Reference Burden, Canon, Mayer and Moynihan2012; Moynihan et al., Reference Moynihan, Herd and Harvey2015; Nisar, Reference Nisar2018; Masood and Nisar, Reference Masood and Azfar Nisar2021, 56; Giest and Samuels, Reference Giest and Samuels2022). Other research looks more generally at the ‘administrative barriers’ that potentially exclude or burden some groups—specifically, those with lower education levels, arguing that such barriers are further linked to outright ‘administrative exclusion’ (Brodkin and Majmundar, Reference Brodkin and Majmundar2010).

2.1.2. Crowdsourcing and collective intelligence

In addition to digitally enabled public participation, crowdsourcing and collective intelligence is another area of emerging research. Crowdsourcing, as defined by Mergel and Desouza (Reference Mergel and Desouza2013), is an approach that allows “collective intelligence to be leveraged to solve complex problems when resources or expertise are otherwise lacking.” Collective intelligence is understood as a “form of universally distributed intelligence, constantly enhanced, coordinated in real-time, and resulting in the effective mobilization of skills” (Levy, Reference Levy1997).

Digital technologies have led to the creation of new collective intelligence platforms that provide a place for individuals to coordinate, collaborate, and communicate in real-time to, for example, generate and gather knowledge from the “wisdom of the crowd” (Suran et al., Reference Suran, Pattanaik and Draheim2020). There are many examples of how digital platforms can harness collective intelligence to develop value-producing platforms, such as Wikipedia or OpenStreetMaps (Budhathoki and Haythornthwaite, Reference Budhathoki and Haythornthwaite2013). Increasingly, data generated from the crowd is playing an important role in the development of a digital world, for example, in training state-of-the-art AI-based systems (Verhulst, Reference Verhulst2018; Verhulst et al., Reference Verhulst, Addo, Young, Zahuranec, Baumann and McMurren2021).

Looking at the success of these distributed collective intelligence platforms, governments have begun to experiment with similar initiatives and initial research does seem to suggest that when new services engage with citizens, it may generate better public services (Dutil, Reference Dutil2015; Liu, Reference Liu2017). While there appear to be some benefits to crowdsourcing and collective intelligence, and the development of new digital technologies is improving the accessibility of these techniques, it is also clear that the applicability and usefulness of crowdsourcing are still limited (e.g., van den Berg et al., Reference van den Berg, Giest, Groeneveld and Kraaij2020). Potential weaknesses include a lack of support from internal stakeholders (Mergel and Desouza, Reference Mergel and Desouza2013), questions around data quality (Leibovici et al., Reference Leibovici, Rosser, Hodges, Evans, Jackson and Higgins2017; Jacobs, Reference Jacobs2016), and in the case of the public sector, a lack of interest from citizens (Gelman et al., Reference Gelman and Wu2011; Liu, Reference Liu2017).

Due to these weaknesses, some scholars warn that the cost of engaging citizens drains resources from core administrative work (Liu, Reference Liu2017) and may cater specifically to a rather idiosyncratic group of highly motivated civic influencers and/or groups that have been uniquely galvanized around an issue that affects their economic, political, or social interests (Cunningham, Reference Cunningham1972; Fiorina, Reference Fiorina, Skocpol and Fiorina1999; Cleaver, Reference Cleaver2005; Lodge and Wegrich, Reference Lodge and Wegrich2015).

2.2.1. Co-creation

A core area of research within this domain is co-creation, particularly in the context of new public services (Osborne et al., Reference Osborne, Radnor and Strokosch2016). Defined as “the involvement of outside, non-typical, stakeholders in the initiation, design, implementation, and evaluation of a new public service” (Toots et al., Reference Toots, McBride, Kalvet and Krimmer2017), co-creation holds the potential to enhance service accessibility, personalization, and generate higher public value for administrators and users (Casiano Flores et al., Reference Casiano Flores, Rodriguez Müller, Albrecht, Crompvoets, Steen and Tambouris2021; Jarke, Reference Jarke2021). The extant literature explores how co-creation processes unfold, particularly in the context of new digital systems. Lember et al. (Reference Lember, Brandsen and Tõnurist2019) present technologies that could diversify co-creation opportunities, while cautioning against a potential future where decision-making relies on complex algorithms and collective data.

Studies on digitally enabled co-creation, such as those by Khayyat and Bannister (Reference Khayyat and Bannister2017), McBride et al. (Reference McBride, Aavik, Toots, Kalvet and Krimmer2019, Reference McBride, Nikiforova and Lnenicka2023), Nikiforova (Reference Nikiforova2022), demonstrate how open government data (OGD) fosters innovation ecosystems supporting co-creation. This has been further demonstrated during the COVID-19 pandemic, where co-creation and OGD-based ecosystems emerged as strategic crisis management tools (McBride et al., Reference McBride, Nikiforova and Lnenicka2023) and opportunities to promote innovation through, for example, hackathons (Kangro and Lepik, Reference Kangro and K-L2022; Nikiforova, Reference Nikiforova2022).

Though initial evidence suggests clear benefits for data and digitally-enabled forms of co-creation, there is limited evidence regarding the tangible and sustainable outcomes of co-creation initiatives (Cingolani, Reference Cingolani2021). Further research is needed to understand how co-creation unfolds in public service development and delivery, including its process, and its effects on stakeholder relations, especially regarding power dynamics, information asymmetry, and trust. In this context, Castells’ work (Reference Castells and Castells2013, Reference Castells2022) on power relations offers a critical lens through which to examine the role of technology in reshaping interactions between governments and citizens. His insights into the network society and the shifting nature of power in the digital age can illuminate the complexities of co-production, particularly how technology can both empower and marginalize different stakeholders. Understanding these dynamics is crucial for assessing the true impact of co-creation initiatives on public service development and delivery, and in ensuring that such efforts genuinely enhance democratic engagement and equity.

2.2.2. Digital transformation of public services

Against this backdrop there are two sets of factors relevant for the citizen-government relationship in the context of digital public service delivery: first, the design and usability of the system matters. Second, personal experience and characteristics that affect comprehension and navigation abilities when confronted with the digital system. These include experience with (similar) systems (administrative capital), as well as individual, demographic characteristics.

From the public servant perspective, bureaucrats, and especially those at the front-line or so-called ‘street-level bureaucrats’, which have traditionally been directly involved in the experiences that citizens have with a public service are seeing their roles and relationships with citizens transform (Olabe, Reference Olabe2017). This change is driven by today’s digital world where screens might replace personal engagement on both sides of the citizen-state interaction. For bureaucrats in particular, studies show that digitalization has come with managerial demands for efficiency coupled with performance metrics (Jewell, Reference Jewell2007; Brodkin, Reference Brodkin2011, Reference Brodkin2012). This has effects on their responsiveness to citizen-clients, their discretionary space in the decision-making process as well as their position as mediators between citizens and managers as well as policymakers (Gofen and Lotta, Reference Gofen and Lotta2021).

Some foresee the emergence of new bureaucratic roles aligned with digital processes. Bovens and Zouridis (Reference Bovens and Zouridis2002) delineate three employee groups: “(1) those actively involved in data processing, including system designers, legislative specialists, legal policy staff, and system managers; (2) managerial roles overseeing production processes; and (3) the ‘interfaces’ engaging citizens with information systems, encompassing public information officers, help desk members, and legal staff handling complaints and objections on behalf of the organization” (Ibid, 180).

This suggests that, as per Bovens and Zouridis (Reference Bovens and Zouridis2002), system designers, legal policy staff, and IT experts assume roles akin to modern-day street-level bureaucrats. Recent research, however, emphasizes that even as face-to-face interactions diminish in public service delivery—hallmarks of street-level bureaucrats (Lipsky, Reference Lipsky1980)—individual bureaucrats retain influence over policy implementation and decisions concerning citizen-clients, given that many applicants do not neatly fit eligibility criteria (Keiser, Reference Keiser2010). Studies on street-level bureaucracy and digital office technologies support this, asserting that digital applications aren’t just managerial tools impacting these bureaucrats but an infrastructure shaped by frontline workers (Hoybye-Mortensen, Reference Høybye-Mortensen and Hupe2019).

2.3.1. Emergence of open government

The openness paradigm outlines a future for government that is open, responsive, and transparent, where government data is freely available for any to use and create value from, and where technological innovations and developments funded by the public sector are able to be freely reused by any who are interested. From a technological standpoint, “openness” is primarily associated with the open-source software movement originating in the late 1980s and early 90s which placed a strong emphasis on “opening up” software so that it was free, reusable, and non-discriminatory, amongst other things (Kelty, Reference Kelty2001; Stallman, Reference Stallman and Gay2002; Tozzi, Reference Tozzi2017). Viewing the open-source software movement as a success, many were interested in how this belief system could be applied in other areas of society.

One sector with perhaps the strongest interest was the public sector and the idea of an “open government” began to emerge together with the associated topic of “open government data”—data collected, produced, or paid for by the public bodies and made freely available for re-use for any purposeFootnote ¹ compliant with principlesFootnote ² of (1) completeness; (2) primariness; (3) timeliness; (4) availability; (5) machine-readability; (6) non-discriminatory; (7) non-proprieteness; (8) license-free (Bauer et al., Reference Bauer, Ebner-Priemer, Eid, Goritz, Lange, Maaz, Nagel, Raum, Richter and Trappmann2020). In line with this transformation, there is a large amount of literature that helps untangle the complexities associated with openness in the public sector.

Scholars have explored how openness and open government data can drive (open) innovation and economic value creation (Jetzek et al., Reference Jetzek, Avital and Bjorn-Andersen2014; Susha et al., Reference Susha, Grönlund and Janssen2015; Ahmadi Zeleti et al., Reference Ahmadi Zeleti, Ojo and Curry2016; Ruijer and Meijer, Reference Ruijer and Meijer2020), promote accountability and transparency in the public sector (Mayernik, Reference Mayernik2017; Matheus and Janssen, Reference Matheus and Janssen2020; Lnenicka and Nikiforova, Reference Lnenicka and Nikiforova2021), be used to assist in crowdsourcing and collective intelligence applications (Handler and Ferrer Conill, Reference Handler and Ferrer Conill2016; Hemmings et al., Reference Hemmings, Gupta, Mysore, Bontempi and Jacobberger-Jellison2019; Colovic et al., Reference Colovic, Caloffi and Rossi2022; Nikiforova, Reference Nikiforova2022; McBride et al., Reference McBride, Nikiforova and Lnenicka2023) within open data ecosystems (Dawes et al., Reference Dawes, Vidiasova and Parkhimovich2016; Najafabadi and Luna-Reyes, Reference Najafabadi and Luna-Reyes2017; Linåker and Runeson, Reference Linåker and Runeson2021; Lnenicka et al., Reference Lnenicka, Nikiforova, Luterek, Milic, Rudmark, Neumaier, Santoro, Flores, Janssen and Bolívar2024a, Reference Lnenicka, Nikiforova, Clarinval, Luterek, Rudmark, Neumaier, Kević and Bolívar2024b), and lead to the creation of new digital services or create new public service co-creation ecosystems (Turki et al., Reference Turki, Martin and Renault2017; Lember et al., Reference Lember, Brandsen and Tõnurist2019; McBride et al., Reference McBride, Aavik, Toots, Kalvet and Krimmer2019; Miasayedava et al., Reference Miasayedava, McBride and Tuhtan2022).

Research has similarly highlighted that along with these benefits, there are also risks, with some scholars highlighting the potential “dark side” of openness (Zuiderwijk and Janssen, Reference Zuiderwijk and Janssen2014; Charalabidis et al., Reference Charalabidis, Zuiderwijk, Alexopoulos, Janssen, Lampoltshammer, Ferro, Charalabidis, Zuiderwijk, Alexopoulos, Janssen, Lampoltshammer and Ferro2018; Schnell, Reference Schnell2020). According to Schnell (Reference Schnell2020), this includes the idea of “autocratic openness,” where open government initiatives hide more authoritarian norms behind the scenes. To Zuiderwijk and Janssen (Reference Zuiderwijk and Janssen2014), the “dark side” includes potential risks to privacy, wasted resources, or poor decision making, amongst others, which are even increasing in the current age of Generative AI.

2.3.2. Creating value from open government data

One potential way to create value from OGD is through the support and development of innovation infrastructures, also called public data ecosystems open data ecosystems, data spaces, and innovation platforms. Yet, there is a clear need for these innovation infrastructures, data ecosystems, and data exchange platforms (Bharosa et al., Reference Bharosa, Lips and Draheim2020; McBride et al., Reference McBride, Kamalanathan, Valdma, Toomere and Feudenthal2022). One key component of these ecosystems is individual data ownership and consent management. With increased interest in the opening up of data, there has been a drive to develop and implement the means for citizens to “own” their data, being able to use it as they wish and share it only as needed (Lehtiniemi and Haapoja, Reference Lehtiniemi and Haapoja2020).

While research does exist on new forms of data ownership and management, especially in the smart city literature where ideas such as data collaboratives or data banks are often discussed (Paskaleva et al., Reference Paskaleva, Evans, Martin, Linjordet, Yang and Karvonen2017; Susha et al., Reference Susha, Janssen and Verhulst2017; Klievink et al., Reference Klievink, van der Voort and Veeneman2018; Artyushina, Reference Artyushina2020; Bozkurt et al., Reference Bozkurt, Rossmann and Pervez2022), there is still a lack of research that explores and conceptualizes the personal ownership of data.