A Paula Rodriguez Müller
email: anapaula.rodriguezmuller@kuleuven.be

Trui Steen

Behind the Scenes of Coproduction of Smart Mobility: Evidence from a Public Values' Perspective

Keywords: Coproduction, ICT, Public Values, Smart Mobility, Private Actors

The advances in information and communication technology (ICT) have extended the applicability of citizen coproduction in government service delivery and have entailed transformative changes, especially at the city level. City governments around the globe increasingly rely on the private sector to set ICT-based urban innovations, like initiatives to involve citizens in the coproduction of smart mobility. Although there are many benefits of ICT-based coproduction, there is nevertheless the potential for tension between private companies and the government with whom they are cooperating. Those tensions are built on the differences in interests and values of private and public actors, and the way of realizing them, and they can compromise the vision and duty of the government. We, therefore, aim to understand the potential impact of private companies' involvement on the expectations and perceptions of coproducing actors towards social-oriented and service-oriented public values. We conducted an exploratory in-depth case study of the smart bike-sharing system in one of the major cities in Flanders, Belgium. Data were collected through official documents and 27 semi-structured interviews with key coproducing actors. These data were then qualitatively analyzed using Nvivo software. Our exploratory case study indicated that the private actor upholds the realization of values such as efficiency, reliability, and ease of access by bringing in resources and expertise to coproduce smart mobility. However, certain social-oriented values like citizen empowerment and engagement, and (digital) inclusiveness are not part of the private partner's vision. The study highlights the potential assets and risks for the realization of public values when dealing with conflicting interests between coproducing actors, and in this way considers a different angle on private companies' involvement in the coproduction of public services.

Introduction

ICT-based coproduction of public services is alleged to improve the realization of public values in the city, as it allows citizens and non-state actors to be more actively engaged with the delivery of public services [START_REF] De Vries | Innovation in the public sector: A systematic review and future research agenda[END_REF][START_REF] Lember | The Potential Impacts of Digital Technologies on Co-Production and Co-Creation[END_REF]. As a result, this leads to a more collaborative and open government, e.g., users can have more control over the services and greater fulfillment of their needs [START_REF] William | Smart governance: Opportunities for technologically-mediated citizen co-production[END_REF]. Specifically, in the so-called 'smart city', governments need to involve private companies due to the technological and financial complexities behind smart services. This ideally encompasses a sustainable cooperation, sharing risk, and resources [START_REF] Liu | Impact of Governance Structure Characteristics of Publicprivate Partnerships on Smart City Project Success: Evidence from a Multi-case Study in China[END_REF].

Nevertheless, the role of the government runs the risk of becoming ambiguous with the increasing involvement of private companies, who can act as intermediaries between the government and its citizens. Because of their technological and financial capacity, private companies could end up assuming government's tasks and functions. The end result could be the private sector obstructing the vision and duty of the government while prioritizing profitability over a wide range of public values [START_REF] Ma | Challenges of collaborative governance in the sharing economy: The case of free-floating bike sharing in Shanghai[END_REF][START_REF] Anthopoulos | Understanding electronic government research and smart city: A framework and empirical evidence[END_REF][START_REF] Klievink | Challenges in Developing Public-private Business Models[END_REF].

In order to explore the challenges involved in the coproduction of smart mobility, we use the coproduction theory, digital government (smart cities), and public values perspective. We aim to step back from the normative perspective that highlights only the potential 'good outcomes' and promises of ICT-based collaborations and to look into the black-box [START_REF] Lember | The Potential Impacts of Digital Technologies on Co-Production and Co-Creation[END_REF][START_REF] William | Smart governance: Opportunities for technologically-mediated citizen co-production[END_REF]. Our study is guided by the following research question: to what extent does the involvement of private companies in ICT-based coproduction affect the expectations and perceptions of the coproducing actors (i.e., governmental actors, private actors, citizen-users) towards public values being realized or obstructed? To address the research question, we conducted an exploratory in-depth case study on ICT-based coproduction of smart mobility.

The next section briefly deals with the definition and context of the coproduction of smart mobility. Section 3 outlines the potential and challenges of ICT-based coproduction's ability to realize public values. Section 4 summarizes our methodological approach towards the case study. Section 5 provides a discussion of the findings and limitations. Finally, section 6 delivers our conclusions, implications, and avenues for future research.

Coproduction of Smart Mobility

The conception of coproduction fits in the New Public Governance paradigm that recognizes the provision of public services as a model based on networks and interorganizational relationships. It is understood as the collaboration between 'regular producers' and 'citizen producers' in different phases of service management. The 'regular producers' are the professional coproducers working directly (e.g., government employees) or indirectly (e.g., private actors) with the government. The 'citizen producers' are lay actors who voluntarily coproduce (individually or collectively) as citizens and/or customers [START_REF] Bovaird | From Engagement to Co-production: The Contribution of Users and Communities to Outcomes and Public Value[END_REF][START_REF] Nabatchi | Varieties of Participation in Public Services: The Who, When, and What of Coproduction[END_REF][START_REF] Bracci | Co-production of Public Services: Meaning and Motivations[END_REF]. Technological advances have led to an increased ability to perform coproduction activities [START_REF] William | Smart governance: Opportunities for technologically-mediated citizen co-production[END_REF][START_REF] Johnston | Governance infrastructures in 2020[END_REF][START_REF] Fugini | The Role of ICT in Co-Production of e-Government Public Services[END_REF][START_REF] Linders | From e-government to we-government: Defining a typology for citizen coproduction in the age of social media[END_REF][START_REF] Lember | The Increasing Role of Digital Technologies in Co-production[END_REF][START_REF] Meijer | Coproduction as a structural transformation of the public sector[END_REF], and have entailed transformative changes, especially on the city level [START_REF] Townsend | Smart cities: big data, civic hackers, and the quest for a new utopia[END_REF][START_REF] Cardullo | Smart urbanism and smart citizenship: The neoliberal logic of "citizen-focused" smart cities in Europe[END_REF]. These initiatives came with new promises. ICT is claimed to empower service users, enhance the speed and reach of communications, and promote multilateral and rich information exchange without time and space constraints [START_REF] Fugini | The Role of ICT in Co-Production of e-Government Public Services[END_REF][START_REF] Meijer | Coproduction as a structural transformation of the public sector[END_REF]. Smart mobility is an example of adopting ICTs to coproduce, as the sharing aspect implies the involvement of multiple stakeholders and the 'crowd', while the 'smartness' entails a reconfiguration of the interactions between the actors involved and their sur-rounding environment [START_REF] William | Smart governance: Opportunities for technologically-mediated citizen co-production[END_REF][START_REF] Ma | Challenges of collaborative governance in the sharing economy: The case of free-floating bike sharing in Shanghai[END_REF][START_REF] Gil-Garcia | Conceptualizing smartness in government: An integrative and multi-dimensional view[END_REF]. The main premise behind these smart systems is to offer an accessible and inclusive alternative mobility solution. Specifically, when examining city bike sharing, this solution also involves the innovative movement from private ownership of vehicles to 'usership', and a redefinition of the citizenusers role, since they become both recipient and source of the services' information, and they bring in their resources to shared platforms [START_REF] Docherty | The governance of smart mobility[END_REF].

In the context of the evolution of the public service provision, the public sector outsources most of the technological solutions to the private sector [START_REF] Lember | Public Administration[END_REF][START_REF] Alford | Rethinking Public Service Delivery. Managing with External Providers[END_REF]. This means that city governments collaborate with private companies to provide their citizens with smart solutions, like bike-sharing systems. As the digital government paradigm proposed, the role of non-state actors in the policy design and provision of public services has been spreading-out, leading to a more open and collaborative government. This collaboration between private and public actors can lead to each adopting new roles, engaging in different types of interaction, and navigating changing accountability dynamics. Based on the coproduction literature, it is assumed that the coordination of expertise, knowledge, resources, technology, and processes leads to better results than when working independently [START_REF] De Vries | Innovation in the public sector: A systematic review and future research agenda[END_REF].

Nevertheless, it comes with further challenges in terms of private companies assuming tasks and responsibilities traditionally performed by the government [START_REF] Ma | Challenges of collaborative governance in the sharing economy: The case of free-floating bike sharing in Shanghai[END_REF][START_REF] Anthopoulos | Understanding electronic government research and smart city: A framework and empirical evidence[END_REF][START_REF] Klievink | Challenges in Developing Public-private Business Models[END_REF]. There is a risk of 'disintermediating government', characterized by private companies providing public services directly to citizens and the government relegated as a supporter. For instance, private companies become responsible for not only the infrastructure of smart services, like bike-sharing systems, but also the operation and the interaction with citizens. Despite the dangers of unequal distribution of responsibility, information asymmetry can positively contribute to the collaboration process between the public and private sector when it exists in a complementary form. Data are one of the most valuable commodities behind smart mobility that allow governments to support the realization of public values. Yet the private sector is displacing the government as a principal source of data, becoming 'data landlords' instead of 'data tenants' [START_REF] Docherty | The governance of smart mobility[END_REF][START_REF] Johnson | Disintermediating Government: The role of Open Data and Smart Infrastructure[END_REF].

Although the private sector opens the door to innovation, "the social values inherent in public services may not be adequately addressed by the economic efficiency calculus of markets" [START_REF] Hefetz | Privatization and Its Reverse: Explaining the Dynamics of the Government Contracting Process[END_REF]. The involvement of private companies in smart services brings in a market logic, a 'corporate storytelling', while it is necessary to prioritize the social and political aspect within a value system [START_REF] Söderström | Smart cities as corporate storytelling[END_REF]. In this respect, the government not only needs to focus on the technological and managerial side of these innovative collaborations and economic growth, but also on the contributions of coproduction of smart services to realize other values, such as inclusion, equity and citizen engagement [START_REF] Johnson | Disintermediating Government: The role of Open Data and Smart Infrastructure[END_REF][START_REF] Meijer | Governing the smart city: a review of the literature on smart urban governance[END_REF].

Public Values

Public values theory is considered one of the most significant subjects in public administration and policy [START_REF] Jørgensen | Public Values[END_REF], and it has been gaining particular interest in the so-called 'smart cities' context [START_REF] Meijer | Governing the smart city: a review of the literature on smart urban governance[END_REF][START_REF] Bolívar | The Relevance of Public Value into Smart Cities[END_REF]. It refers to "the procedural ethics in […] and outcomes made possible by producing public services" [START_REF] Bryson | Towards a multi-actor theory of public value co-creation[END_REF], and it is understood as a concept used to give direction to public action or legitimize it [START_REF] Witesman | From Public Values to Public Value and Back Again[END_REF]. Bozeman [START_REF] Bozeman | Public values and public interest: counterbalancing economic individualism[END_REF] defines public values as:

(1) The rights, benefits, and prerogatives to which citizens should (and should not) be entitled;

(2) the obligations of citizens to society, the state, and one another; and (3) the principles on which governments and policies should be based1 .

Bozeman's [START_REF] Bozeman | Public values and public interest: counterbalancing economic individualism[END_REF] definition focuses purely on the citizen-side, whereas society and 'the public interest' involves further actors, such as non-profits and private companies. This distinction is particularly relevant in the context of coproduction, where public values are expected to be upheld through collaboration among diverse stakeholders.

ICT-based coproduction initiatives are expected to enhance the realization of better and more democratic public services [START_REF] De Vries | Innovation in the public sector: A systematic review and future research agenda[END_REF][START_REF] Lember | The Potential Impacts of Digital Technologies on Co-Production and Co-Creation[END_REF] through collaboration with external stakeholders, including citizens. Bearing this in mind, we clustered the expected public values in the context of ICT-based coproduction into two categories [START_REF] Jaspers | Realizing public values: enhancement or obstruction?[END_REF][START_REF] Bannister | ICT, public values and transformative government: A framework and programme for research[END_REF]. First, social-oriented values illustrate the democratic quality of the service delivered, for instance, the level of inclusiveness, equal treatment or citizen empowerment [START_REF] Jaspers | Realizing public values: enhancement or obstruction?[END_REF][START_REF] Vanleene | The professional's dynamic role in the democratic quality of co-productive community development[END_REF][START_REF] Verschuere | Democratic Co-Production: Concepts and Determinants[END_REF]. Digital democracy studies highlight that internet-based practices may improve democratic values by bringing dispersed populations closer, allowing for more citizen participation [START_REF] Schwester | Examining the Barriers to e-Government Adoption[END_REF]. ICT-based coproduction could potentially increase inclusion [START_REF] Michels | Innovations in democratic governance: how does citizen participation contribute to a better democracy?[END_REF] and equity [START_REF] Jakobsen | Can Government Initiatives Increase Citizen Coproduction? Results of a Randomized Field Experiment[END_REF] as it promises to provide the same opportunities to different actors [START_REF] Uppström | Explaining value co-creation and co-destruction in egovernment using boundary object theory[END_REF], foster local activism, unleash social innovation and reinvigorate democracy [START_REF] Linders | From e-government to we-government: Defining a typology for citizen coproduction in the age of social media[END_REF][START_REF] O'reilly | Government as a Platform[END_REF].

Second, service-oriented values refer to service quality, responsiveness, effectiveness, among others. Coproduction is expected to improve the quality as well as increase the quantity of public services [START_REF] Calabro | Coproduction: An alternative to the partial privatization processes in Italy and Norway[END_REF][START_REF] Pestoff | Citizens and co-production of welfare services[END_REF][START_REF] Vamstad | Coproduction and service quality: A new perspective for the Swedish welfare state[END_REF] through expertise and information provided by citizens/users, not available otherwise [START_REF] Loeffler | From Participation to Co-production: Widening and Deepening the Contributions of Citizens to Public Services and Outcomes[END_REF]. The advances of ICT in coproduction provide unique means for real-time, community-wide coordination, "presenting tremendous opportunities for data-driven decision-making, improved performance management, and heightened accountability" [START_REF] Linders | From e-government to we-government: Defining a typology for citizen coproduction in the age of social media[END_REF]. These initiatives can improve the efficiency of processes, speed up response times, and make them more secure/reduce human errors [START_REF] Uppström | Explaining value co-creation and co-destruction in egovernment using boundary object theory[END_REF].

In the context of New Public Management driven reforms, service-oriented or business-like values have been the primary drivers of ICT use in the public sector, while democratic values have been relegated [START_REF] Chadwick | Interaction between States and Citizens in the Age of the Internet: "e-Government" in the United States, Britain, and the European Union[END_REF][START_REF] Chun | Government 2.0: Making connections between citizens, data and government[END_REF] or even trampled [START_REF] Adams | Digitalization through the lens of law and democracy[END_REF]. As Bannister & Connolly [START_REF] Bozeman | Public values and public interest: counterbalancing economic individualism[END_REF] claim, values such as citizens' information privacy, equal access, and social inclusion have a high potential of being negatively affected by ICT. ICT is not value-neutral but instead has the potential for positive or negative impact on public values. Whereas technology can "follow its own logic", ICT's users are also responsible for the value embedded on the technologies and its applications [START_REF] Adams | Digitalization through the lens of law and democracy[END_REF].

The involvement of external coproducers, such as private companies, can account for variations in public values expectations. Since ICT-based coproduction allows the government to combine non-state actors' resources with its own, it is seen as a way to enhance government cost savings and deliver better-personalized services [START_REF] Linders | From e-government to we-government: Defining a typology for citizen coproduction in the age of social media[END_REF][START_REF] O'reilly | Government as a Platform[END_REF]. The involvement of private actors can also be considered a method to advance market values such as efficiency, innovation, and flexibility [START_REF] Nabatchi | Public Values Frames in Administration and Governance[END_REF]. Reynaers [START_REF] Reynaers | Public Values in Public-Private Partnerships[END_REF] found that service's quality expectations increase with the involvement of the private sector. Although the private and public sector may hold common core organizational values (e.g., expertise, accountability, reliability), "the extent to which an organization belongs to the public or private sector strongly determines values preferences". For instance, profitability scored high for private sector expectations [START_REF] Van Der Wal | Value Solidity in Government and Business: Results of an Empirical Study on Public and Private Sector Organizational Values[END_REF]. However, other public values such as citizen empowerment and innovation can be hampered by private companies when they hold the data and do not release it openly and make it accessible [START_REF] Jarman | Public Value and Private Organizations[END_REF], restricting evidence-based decision making [START_REF] Gil-Garcia | Conceptualizing smartness in government: An integrative and multi-dimensional view[END_REF].

The potential impact on public values shows the relevance of disentangling the promises and assumptions behind ICT-based coproduction, and of identifying the actual possibilities and limitations behind the different expectations and interests of the coproducing actors. timize the service. Although the mobile application and the website are the means to do the reporting, citizens can also help by turning the saddle 180 degrees, which is a signal for the technicians that something is wrong with that bike. The citizen-users have the right to choose how active they want to be, as the reporting-service is not specified in the rules.

Data Collection and Analysis

Our qualitative data collection included two sources: documents and semi-structured in-depth interviews [n=27], which took place from October 2017 to February 2018. First, we conducted two face-to-face pilot interviews with two public servants involved in the project from its beginning, as well as with the Smart-Bike's operational manager. They provided us with official documents, including promotion materials, policy documents, the contract, and KPIs' and research reports. We also consulted relevant online texts like the official website, the city's open data platform, and news articles to acquire a complete overview of the project and its context. For our second step, following a snowball approach, the interviewees recommended other potential respondents from both the city and the private partner who are/were actively involved. We interviewed all the key actors, such as senior managers, operational managers, coordinators, and IT analysts/experts from the private company and the city Department of Urban Development. In this way, we were able to gather feedback from a wide range of perspectives. The contact with the citizen-users was made through a public call sent by Fietsersbond2 , which is an independent association with more than 23,000 members and 500 volunteers that advocates for all cyclists from Flanders and Brussels. The final selection resulted in 8 interviews with public servants and 5 with private actors [n=13], followed by 14 interviews with citizen-users 3 . The interview questions were tailored to the roles of individuals. On the regular producers' interviews, the first questions were on the role of the respondents in their organization and the project. Then respondents were inquired about the project in general, relevance and their motivations and expected outcomes. Specific questions were asked about the collaboration with other stakeholders and the challenges and advantages; and finally, about the overall impact of technology on (coproducing) public services. Citizenusers were asked about their experience with the service and the reporting system, their expected and perceived outcomes and their motivations for using the service. The interview ended with questions about their experience with the service's technology (e.g., mobile application). The interviews lasted between 45 and 70 minutes and were recorded, transcribed, and kept confidential. The representatives of the city were identified by the letter "A", the representatives of the private partner by the letter "B", and the citizen-users by the letter "C", all followed by an identification number.

From the official documents, we were able to gather insights on the expected public values expressed in the mission, vision, and goals of Smart-Bike's project. We also identified the main stakeholders involved and their responsibilities. The information deployed in the open data platform allowed us to get data on the service, e.g., location of the stations. Users' information and details on the reporting system were provided by the private partner. All these documents allowed us to gain a holistic understanding of the project and its context, as well as to delimit the interview protocol.

The resulting data from the interviews were analyzed with the support of qualitative analysis software NVivo 12. In the first round of coding, the interviews were divided into segments wherein different variables are discussed and labeled following the theoretical framework on coproduction, public values, and digital government. Next, sub-codes for every variable were added through open coding (e.g., public values sub-coded as 'realized' vs. 'obstructed'). Second, a round of axial coding was executed to identify relationships connecting the open codes. Detailed findings from our analysis of the smart bike-sharing system are presented below.

Findings

The Involvement of Private Actors

Public servants highlighted the importance of having an external partner to coproduce smart mobility because of their lack of technological and personnel capacity, and due to the high operational costs. The private partner provides the city with more flexibility to start new projects as they share the risks. The company's operations manager claimed that their risk-sharing partnership is strongly defined by the contract and its rules: "you have a contract, and you have to follow the contract that they give you. So, it is a relationship based on the contract" (B9). Still, public actors experienced issues relating to accountability. Although the private sector's actors claimed it is a relationship based on the contract, that contract did not always seem to be strictly followed. The city is challenged not only by a lack of capacity to analyze data about users and service performance, but also by a lack of accessibility. Public servants point out that requesting data is an arduous process since it takes time to get it, and sometimes they need to move the request to higher levels (i.e., political level).

Even though the collaboration between the private and public parties is characterized by the contract-based dynamics, three other factors were identified as affecting the collaboration, and thereby the potential realization of public values. These factors are communication, trust, and shared understanding.

All respondents mentioned that communication is the key in Smart-Bike's partnership: it is essential to speak the same language as a way to achieve their goals. Despite sharing this belief, communication issues still arise. For instance, the public servants find it difficult to translate the issues to the private actors, whereas the private partner perceives the demands from the city as unrealistic. Although there is room for communication improvement, much has been accomplished based on mutual trust. Trust between the parties allows for a more flexible, open, and innovative interaction. This kind of open dynamic avoids the need to hold meetings every month. A respondent explained that "if you do not have to discuss every little detail, every comma… that reflects we can trust each other, and that is very important" (A3). The private actors perceive the city's trust as a benefit and advantage, "if there is no trust between the municipality and the private partner, we would not be here anymore" (B7). They pointed out that trustworthy cooperation was essential to overcome operational issues. According to the public sector's professionals, they have to let go of control because there is no room for distrust as there are "no open books" (A5). Another challenge was to align the diverse expectations of politicians, administration, company, and citizen-users. Private actors accentuated the need of having a common vision, "we need to be aware and informed about where the city is going so that we can adapt, prioritize correctly or adjust our operations and strategy so that we are aligned with theirs" (B7, also B8).

Co-producers' Public Values Expectations and Perceptions

In order to pinpoint the challenges that might arise due to private actors' involvement, we discuss perceptions of public values realization or obstruction following the two sub-clusters outlined in section 3: service-oriented values (i.e., service quality and business-like values) and socially oriented values (i.e., democratic quality of the service delivered).

Service-oriented Values

Service Quality. The 'waiting list' refers to the periods when no additional citizens were allowed to subscribe to the service. The quality and effectiveness were put above the inclusiveness of the service. "It's not so nice for the political level either to say we have a bike sharing system for everybody but 'oh, by the way, sorry, there is a waiting list and we don't know when this waiting list will be cleared.' We didn't have another choice" (B7). Citizen-users expected to have better quality bikes. Users that have had a subscription from the beginning stated that, when the service started, the quality of the bikes was inferior, but by now it has improved. Nevertheless, they agreed that due to the low price of the service, they do not expect to get the best bikes.

Ease of Access. The company expects to deliver an accessible service: "ease of access is vital for us. So, no need to fill out 10 forms and write 20 emails before you can use the system" (B7). The dense network of stations and the 24/7 availability allow a high rate of accessibility to the service. Therefore, they monitor the service continuously. This also relates to the digital side of the service. The mobile application is the bridge between the location of the stations and the citizen-user, completing the experience of the user. As the city's coordinator states, "everybody who has a smartphone wants to know everything right now and make it possible to order something right now" (A3). However, challenges emerge when citizen-users do not have a smartphone or digital literacy, which are both necessary in order to use the mobile app or website. For them, the perceived valueaccessibilityis the opposite as they are not able to look for that information in advance.

Responsiveness. The city has no direct interaction with the citizen-users. All communication happens via the private partner, who receives the data from the users and takes the information they believe to be pertinent to the meetings with the city. The private actor claimed that it is essential to consider user's feedback for decisionmaking, "it has to do with raising awareness about what is bike-sharing so that the users know what is expected from them and what they can expect from us" (B7). The user-friendliness of the mobile app is important for the private actor so that users can reach them easily, to report broken bikes or technical issues. Yet the company's intentions are mainly about their image: "If there is a complaint or suggestion, you have to do something with it. You cannot ignore it. If you ignore it, you will get bad publicity" (B9). This reflected in the users' perceptions; they agreed that the efforts of getting citizen-users feedback and use it are far from reality. As some users described: "once I filled in a long question list with more than 100 questions, and for example, there were only one or two questions about the technical condition of the bikes" (C24); "they are always friendly, but they do nothing about the problem" (C23).

Innovation. For the managerial level of the city's department, innovation is crucial: "you must have an open mind, an eye for innovation in different aspects of society and be aware of innovations, having a broad network with people in the sector" (A5).

They have concerns about the innovative capacity of their private partner, and not about financial means: "my perception is that [the private partner] is not a very market player, an innovative player. Our system is 7, 8 years old", states the director of the urban development department (A5). This clarifies the private actor's perceptions of innovation: "one of the most difficult things is managing expectations of the city versus the budget you have to do things. Sometimes it is hard to find the funding to be able to innovate" (B10

Social-oriented Values

Citizen Empowerment. Empowerment does not seem to be a relevant value for the project, based on the interviewees' responses. A private actor stated that "the more you give them the ability to do things on their own, the more they can do things on their own. But of course, there are always people that might not be able to, and that's why we always have a front-office where you can go and get help if needed" (B10). The citizens' voice is taken as a part of the service, but sometimes it is merely a formality, as the suggestions need to be "good and right" to get discussed (A2). The citizen-users of this sample believe that they do not have a genuine voice in the process, although they expect to have it. "I made a suggestion to [Smart-Bike], and they accepted it: 'Oh, that's a nice thing, we will take it'. But they don't do anything with it" (C1). In general, citizen-users claimed that individual efforts are worthless; rather, they need to act as a group or through non-profit organizations to get their voices heard.

Inclusiveness. For private actors, efficiency is more valued than inclusiveness. For example: "you might say that there is no waiting list, but then you get under-capacity, and you risk failing completely, then the system is not adopted anymore by the users because it does not offer a solution anymore" (B7). They are aware of the difficulties of aligning different visions, "sometimes, the decisions are hard to take for the city; even more when different organizations have something to say in the story" (B8). The low level of inclusiveness is reflected in the digitalization of the services. A citizenuser argued: "they skip a group of people who are not digital. They can't use it because they can't get an account or they don't know how to use the app or the screen. We are a forgotten group, and they should take care of us" (C1, also C2, [START_REF] William | Smart governance: Opportunities for technologically-mediated citizen co-production[END_REF][START_REF] Ma | Challenges of collaborative governance in the sharing economy: The case of free-floating bike sharing in Shanghai[END_REF][START_REF] Anthopoulos | Understanding electronic government research and smart city: A framework and empirical evidence[END_REF][START_REF] Bracci | Co-production of Public Services: Meaning and Motivations[END_REF][START_REF] Fugini | The Role of ICT in Co-Production of e-Government Public Services[END_REF]. This is seen again in the numbers behind the mobile application's reports from 2016 to 2018. Whereas 47% of the users are younger than 35 years old, more than 70% of the reports via the mobile app came from this group. Moreover, both private and public actors accept that the 'offline' experience is not the same as the 'digital' one. As a user stated: "you can use the system without a mobile phone, but for me, it feels like half a system" (C6). The city claims to not have enough data to understand who is included and who might be left behind, digitally and in terms of language and cultural aspects. The company is aware of this problem, yet inclusiveness is not prioritized: "you also have people who get angry because they can't give us a paper, but it's too expensive to have offices and people everywhere" (B8).

Privacy & Security. Private actors showed more concern in terms of privacy and security policies and regulations than the city. With new regulations like GDPR, the company needs to change procedures: "we had to change what we ask. We also had to implement a procedure if people want to delete their personal data" (B8). It was striking thatdespite the involvement of private companiesthe users interviewed did not have any concern about privacy and security regarding their data since they understood that the city is behind the service and believed that their personal information would not be compromised. As some users claimed: "Because the city is backing up the project, it feels more reliable" (C3); "if they are more commercial the risk that they will spread the data around is bigger. And if it's more government-oriented or social profit, I don't believe they misuse it" (C6). On the other hand, a MaaS expert (Mobility as a Service) of the city (A6) pointed out that no privacy and security policy on smart services has yet been defined in their regulations. The expert highlighted that the interest of the city is now put on opening the data and creating projects interesting enough for MaaS providers, as a "political game".

Discussion

The private sector has been insourcing most of the technological solutions in the public sector, playing a pivotal role in initiatives such as ICT-based coproduction of smartsharing -services. Still, private actors' expectations regarding the service tend to diverge from the public actors. Although this might not be striking, the significant aspect lies in the public nature of the coproduced service, and therefore, the importance of public values being realized through the coproduction process. This paper aimed to unveil the impact that the involvement of private actors has in the delivery and coproduction of smart mobility on the realization of service-oriented and social-oriented public values. The findings advance our understanding of the public values expected or aimed for, in how far these values are actually being realized, and which factors enhance the realization of public values.

In the context of Smart-Bike, the city's shortage of specific expertise, skills, staff, financial resources, and technology required to set up the smart mobility project made it necessary to involve a private company. This involvement is determined by a contract-based collaboration between the parties. All the actors, both public and private, agree that the project's primary motivation is its effectiveness as a real solution and an alternative for improving mobility in the city. However, from that point on, the actors tend to differ in what they value most.

The private actors prioritize the realization of public values such as efficiency, reliability, and ease of access, whereas social-oriented values like citizen engagement and (digital) inclusiveness are not part of their core vision. They do highlight values like responsiveness or empowerment but in a 'defensive way'; the main concern is to protect the company's image. As citizen-users manifest, there are no genuine opportunities to give feedback and be heard. Moreover, the company sustains that the service is inclusive, although the digital limitations of certain groups of the society are not taken into consideration. The users need digital skills and resources to fully enjoy the smart service fully, which might hamper not only equal access (a fundamental value of public service) but also the effectiveness of the service.

Concerning innovation, it is expected that the private partner fosters and facilitates venues to develop new smart solutions. Nevertheless, our case study reveals that the private partner points to the budget and contract-based dynamics as an obstruction to innovate, while the public actors believe that the issue is related to the company not being up to date on the market's innovations. In contrast, the private actors show a higher concern about values such as privacy and the security of citizen-users' data. However, while Smart-Bike is presented as a city's service, the users may hold mistaken perceptions of their privacy and security of the data they share.

In the case studied, four specific factors of the coproduction's collaborative process play a role in the realization (or obstruction) of public values: contract-based dynamics, communication between the stakeholders, building trust, and shared understanding of the interests, goals, and vision of the different involved parties. The evidence suggests that contract-based collaboration might foster efficiency, while innovation, citizen empowerment, and privacy and security aspects are hindered due to the restricted access of the city to the service's data and system. Communication has been a problem between the private and public actors, mainly because of the disparities in the perceptions of the role that each party has in the decision-making process and in their various ways of achieving goals. Furthermore, the private partner being solely responsible for the interaction with citizen-users entails barriers to advance socialoriented values. However, mutual trust helps to balance those issues by providing more flexibility and openness within the collaboration. At the same time, trust is fundamental in terms of efficiency (e.g., time and flexibility), and accountability. Although the city has no direct and open access to all the facts and data from the service, trust has been playing a crucial role in the sustainability of the project. Another influential factor is the shared understanding in working together that facilitates the alignment of different motivations and priorities, even if they do not share all their expectations. For instance, the private actors aim to line up their plans with the city's priorities (e.g., political level), while public professionals also include the citizens' visions as part of the bigger picture. Shared understanding also facilitates the pooling of key resources and common values. To sum up, the evidence suggests public actors need to correctly align the resources, expertise, legal frameworks, and goals to balance public values priorities when involving external partners in the coproduction of smart public services.

Concluding Remarks

This paper provides evidence consistent with existing research on ICT-based coproduction, smart services, and conflicting interests between private and public actors. Additionally, it highlights how important it is to understand private actors' involvement in coproduction through a public values' lens. This study offers a new angle on the conflicting interests among different coproducing actors and the long-standing tension between social-oriented and service-oriented values. It also pinpoints some factors of the coproduction process that may help to detect possible venues to handle the differences in public values' priorities. Overall, the identified factors reveal that the collaborative process may be more relevant than the actual coproducing actors' resources and expertise when it comes to upholding public values.

An early thinking on the potential downside and risks behind future ICT-based coproduction projects will broaden the possibilities of developing innovative and efficient solutions in the field of smart mobility while safeguarding the social aspect of public services. Our study offers some suggestions for such collaborative projects. First, attention should be given to the contract and the legal framework behind the initiative. The potential power asymmetry between the cities and private companies at the time of coproducing smart services underpins the relevance of a well-defined legal framework. In Smart-Bike, the lack of regulations in terms of data access has become an obstacle to improving the service, evaluating the level of inclusiveness, fostering innovation, and assessing the general performance of the private partner. In particular, our analysis points at the need for clear approaches in terms of data and information sharing that protect and uphold the realization of public values. It also stresses the importance of clearly defining the tasks and responsibilities between the parties to manage expectations. Second, transparency can be a significant factor in the collaborative process, mainly towards citizen-users who need to be aware of the parties involved in the service, e.g., who is handling their data and how. Finally, future research on ICT-enabled coproduction and realization of public values should incorporate insights from public-private partnership literature and public-private innovation networks. For example, it would be useful to look into power asymmetries between principal and agent, the government's ability to adequately prepare the contract, and the competencies needed for purchase and procurement. In contrast to the first factor (i.e., the contract), the other three identified factors (i.e., communication, trust, shared understanding) link more with insights from collaborative governance theory and the more 'soft' side of inter-organizational collaboration.

Our research is not without limitations. The reporting conclusions are based on a small-scale single case study of a smart mobility public service in one of the major cities in Flanders, Belgium. The resulting conclusions are case-specific and cannot be generalized to other cases. Yet the insights derived from our case study might be relevant to other cities coproducing smart services in related conditions or with similar characteristics. Future research could examine initiatives from different policy fields (e.g., health care, social care) which may shed light on other public values being upheld or obstructed due to collaboration with private actors. As the involvement of private actors will remain necessary for ICT-based coproduction initiatives, more research is needed to further reflect on the potential trade-offs between delivering a better service and fostering democratic quality. We also need studies to show how to successfully deal with the tensions that arise due to different public values being prioritized in a context of power asymmetry, where the private sector seems to orchestrate the changes behind the government ICT-based projects.

Scholars such as Alford[START_REF] Alford | Co-Production, Interdependence and Publicness: Extending public servicedominant logic[END_REF] and Osborne et al.[START_REF] Osborne | Co-Production and the Co-Creation of Value in Public Services: A suitable case for treatment?[END_REF] discuss the co-creation of 'public value' (singular), which Moore[START_REF] Moore | Creating public value: strategic management in government[END_REF], representative of this line of thought, refers to as an appraisal "on behalf of the public" of the outcome of public service delivery. Nevertheless, this study will provide insights from the Bozeman[START_REF] Bozeman | Public values and public interest: counterbalancing economic individualism[END_REF] strand of thought, as "these public values can serve as reasons or reference points for valuing the 'public value' created"[START_REF] Vandenabeele | Public value creation and strategic human resource management: Public service motivation as a linking mechanism[END_REF].

Research Approach4.1 The case: Smart Bike-sharing SystemThe presented research is based on a qualitative in-depth case study of a dock-based smart bike-sharing service coproduced in one of the major cities in Flanders, Belgium, hereafter referred to as Smart-Bike. A case study allows us to deeply understand a real-life phenomenon while considering the contextual conditions, even with a limited number of observation units. In this way, we can gain insights into complex social phenomena[START_REF] Yin | Case study research: design and methods[END_REF], such as smart mobility systems. These can be defined in the frame of technological transition as a "set of connected changes, which reinforce each other but take place in several different areas, such as technology, the economy, institutions, behavior, culture, ecology and belief systems"[START_REF] Rotmans | More evolution than revolution: transition management in public policy Article information[END_REF].The Smart-Bike public service was launched in 2011, led by the city's Department of Urban Development. The primary provider is a private company which offers this service internationally, although Smart-Bike responds to both the city and the private partner. The service is part of the city's efforts to introduce smart solutions and innovations in different public services, specifically in mobility.The smart bicycle system aims to offer an alternative mobility service that is available 24/7 and provides a solution to the 'first/last mile problem'. It is one of the most successful public smart bike-sharing systems in Belgium in terms of the growing number of active users, with 172% more active users than in 2012. It offers a mobile application which allows users to report service-related issues (e.g., bikes malfunctioning, empty stations, software problems), helping the provider to improve and op-

https://www.fietsersbond.be/

Detailed information on the respondents and interview protocol can be provided upon request.

Acknowledgments. This project has received funding from the European Commission (H2020) under grant number: 726755, project CITADEL, and KU Leuven C1 research fund under the grant number: C14/15/011, project "For the public, by the public."


Dian Balta
email: balta@fortiss.org

Peter Kuhn

Daniel Kulus

Claudius Lieven

Helmut Krcmar

How to Streamline AI Application in Government? A Case Study on Citizen Participation in Germany

Keywords: natural language processing, standardization, government

Artificial intelligence (AI) technologies are on the rise in almost every aspect of society, business and government. Especially in government, it is of interest how the application of AI can be streamlined: at least, in a controlled environment, in order to be able to evaluate potential (positive and negative) impact. Unfortunately, reuse in development of AI applications and their evaluation results lack interoperability and transferability. One potential remedy to this challenge would be to apply standardized artefacts: not only on a technical level, but also on an organization or semantic level. This paper presents findings from a qualitative explorative case study on online citizen participation in Germany that reveal insights on the current standardization level of AI applications. In order to provide an in-depth analysis, the research involves evaluation of two particular AI approaches to natural language processing. Our findings suggest that standardization artefacts for streamlining AI application exist predominantly on a technical level and are still limited.

Introduction

AI represents a concept that incorporates various characteristics of intelligent systems that follow particular goals, including a formal representation of (incomplete) knowledge and an automated logical interference based on that knowledge [START_REF] Russell | Artificial intelligence: a modern approach[END_REF]. Application domains have been discussed as far as the 1960s (e.g. [START_REF] Minsky | Steps toward artificial intelligence[END_REF]), followed by principles for design and application in the 1980s (e.g. [START_REF] Nilsson | [END_REF]). Currently, if designed in an ethical and a trustworthy manner, AI is expected to represent a huge leap from data analysis to high quality and efficiency predictions, and increases the value of informed judgements decisions by humans [START_REF] Agrawal | Prediction Machines: The simple economics of artificial intelligence[END_REF]. Still, being in the trends spotlight for more than 10 years (e.g. [START_REF] Chen | AI, E-government, and Politics 2.0[END_REF]), AI applications prove challenging in government practice (cf. e.g. [START_REF] Sun | Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare[END_REF]). While application examples continuously provided indications of AI's potential (cf. e.g. [START_REF] Androutsopoulou | Transforming the communication between citizens and government through AI-guided chatbots[END_REF][START_REF] Tambouris | Using Chatbots and Semantics to Exploit Public Sector Information[END_REF]), they have yet to deliver sustainable and reproducible results in the government domain. In particular, online citizen participation has been in the focus of research and practice in the last decades regarding natural language processing (e.g. text mining), that would provide a more efficient and effective service to citizens and government (cf. e.g. [START_REF] Teufl | Automated analysis of e-participation data by utilizing associative networks, spreading activation and unsupervised learning[END_REF][START_REF] Maragoudakis | A review of opinion mining methods for analyzing citizens' contributions in public policy debate[END_REF][START_REF] Rao | Decision support for e-governance: a text mining approach[END_REF]).

This paper states the argument that standardized artefacts (e.g. business processes, models, shared terminologies, software tools etc.) are required in order to streamline AI application in government. To support this argument, we present findings from a case study in Germany and discuss their implications.

The rest of the paper is structured as follows. First, we introduce the required theoretical background. Next, we present details and background information on the case study and describe our research approach. After this, we present our findings and discuss implication for AI application in government.

2

Theoretical Background

Standardization

We apply the definition of a standard as "a uniform set of measures, agreements, conditions, or specifications between parties" [START_REF] Gregor | The nature of theory in information systems[END_REF], and standardization represents the process of reaching a standard encompasses stabilizing and solidifying its definition and boundaries [START_REF] Balta | Effective Management of Standardizing in E-Government[END_REF][START_REF] Goldkuhl | Pragmatism vs interpretivism in qualitative information systems research[END_REF]. Hence, standardization can be described in detail as "the activity of establishing and recording a limited set of solutions to actual or potential matching problems directed at benefits for the party or parties involved balancing their needs and intending and expecting that these solutions will be repeatedly or continuously used during a certain period by a substantial number of the parties for whom they are meant" [START_REF] Wilde | Forschungsmethoden der Wirtschaftsinformatik[END_REF].

In order to analyze IT standardization artefacts in government, the following framework that consist of two dimension can be applied [START_REF] Balta | Effective Management of Standardizing in E-Government[END_REF][START_REF] Balta | Managing Standardization in eGovernment: A Coordination Theory based Analysis Framework[END_REF]. The first dimension includes three levels of interoperability and the second dimension includes five functional views (cf. table 1, with exemplary artefacts). The interoperability dimension is structured along three layers. First, the interoperability of business processes applied in delivering public service is found on the organizational layer. Second, interoperability regarding exchange of information and data as well as to their meaning between parties involved is found on the semantic layer. Third, interoperability regarding data structure and format, sending and receiving data based on communication protocols, electronic mechanisms to store data as well as software and hardware is situated on the technical/ syntactic layer.

The second dimension includes five functional views [START_REF] Balta | Effective Management of Standardizing in E-Government[END_REF]. The administration view includes predominantly non-technical standards. They affect personnel and process aspects as well as communication within or between public administrations. For instance, a standardized business process definition or standardized shared terminology to describe public services or a standardized business reporting standard represent particular artefacts in this view. Second, the modeling view includes reference models and architectures, as well as modelling languages for each corresponding interoperability level.

For instance, an ontology can be applied to model a semantic standard towards the creation of a shared terminology and its sustainable use. Third, standards that focus the computation of data are included in the processing view. Exemplary artefacts in this view include a specific software application such as an information search service or a tax accounting software application. Fourth, corresponding standards for data and information exchange between different public administrations is handled in the communication and interaction view. For instance, a common metadata definition (i.e. data describing other data) is applied in a shared methodology in order to allow for an effective information search service. Fifth, the security and privacy view contains standards that aim at addressing issues such as definition of access management policies, application of cryptography methods or requesting a minimum of personal data and respecting privacy. An analysis of standards for e-government based on the described framework would include assigning them to one or several cells along the two dimensions. An assignment to multiple cells is possible, since a standardized solution might address different interoperability layers and functional views at the same time. Consequently, we apply the framework to analyze challenges (e.g. organizational and managerial, data as well as technological challenges [START_REF] Sun | Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare[END_REF]) of AI application in government and, in particular, in online citizen participation.

Online Citizen Participation

Online citizen participation can be described as a form of participation that is based on the usage of information and communication technology in societal democratic and consultative processes focused on citizens [START_REF] Saebø | The shape of eParticipation: Characterizing an emerging research area[END_REF][START_REF] Susha | eParticipation research: Systematizing the field[END_REF]. Given the fact that different levels of online citizen participation and models to describe them exist [START_REF] Al-Dalou | E-participation levels and technologies[END_REF], the participation referred to in our research can be described as collaboration between citizens and government. In particular, government employees and/ or politician are still the ultimate decision makes, but a two-way communication between government and citizens takes place and the latter play an active role in proposing and shaping policy and decisions [START_REF] Wimmer | Ontology for an e-participation virtual resource centre[END_REF]. Implementation of online citizen participation is a challenging task [START_REF] Islam | Towards a sustainable e-Participation implementation model[END_REF] that includes the application of various techniques and technologies [START_REF] Tambouris | A framework for scoping eParticipation[END_REF][START_REF] Tambouris | A framework for assessing eParticipation projects and tools[END_REF]. With regard to existing models and frameworks of online citizen participation [START_REF]Youthpolicy: Participation Models: Citizens, Youth, Online. A chase through the maze[END_REF][START_REF] Scherer | E-participation and enterprise architecture frameworks: An analysis[END_REF][START_REF] Porwol | An ontology for next generation e-Participation initiatives[END_REF], the online citizen participation that lays the ground for our analysis can be described as follows. First, the participation process is steered top-down and is government led [START_REF] Porwol | An ontology for next generation e-Participation initiatives[END_REF], where a public administration invites users to provide feedback by providing a set of topics and applies a set of participation techniques over a particular platform [START_REF] Tambouris | A framework for scoping eParticipation[END_REF].

Fig. 1. Four generic steps of a citizen participation process

Second, the participation process can be described based on four generic steps from a government's perspective (cf. figure 1). In the first step, public administration representatives design and kick-off citizen participation by setting objectives and by adjusting the focus to the participation goals. In a second step, citizens are invited to participate and provide feedback. In this step, ideation techniques are applied, and public administration employees aim at facilitating the process. In the third step, public administration employees or instructed service providers analyse and evaluate the generated citizens' feedback. This includes classifying ideas based on a predefined set of topics and objectives as well as clustering all ideas into new feasible subsets in order to develop a summary report that includes a prioritization of citizens' ideas. This step can require substantial effort from the involved employees, given the potentially large amount of citizen input to be analysed and evaluated. Finally, based on predefined policy processes, the implementation of the ideas is triggered (e.g. by providing the summarized report to action-taking parties such as architects' offices).

Applied AI

According to the Association for Computing Machinery (ACM) Computing Classification System (CCS), AI is a broad research field with various application areas. In particular, AI employs machine learning methods that are based on algorithms that can learn from data without relying on rules-based programming. These methods emerged in the 1990s, making use of steady advances in digitization and cheap computing power, and enabling to efficiently train computers to develop models for analysis and prediction. Recent developments in machine learning include novel models for knowledge representation based on neural networks, and logical interference is based on deep learning [START_REF] Nielsen | Neural networks and deep learning[END_REF]. Neural networks represent a biologically-inspired programming paradigm which enables a computer to learn from observational data, while deep learning represents a powerful set of techniques for learning in neural networks [START_REF] Nielsen | Neural networks and deep learning[END_REF]. An application of AI with a particular relevance for online citizen participation is a methodology named natural language processing (NLP). With NLP, tasks such as information extraction and summarization or discourse and dialogue or even machine translation can be automated to a certain degree. Consequently, goals of applying NLP in online citizen participation include designing a more efficient participation process through supporting the ideation (e.g. suggesting keywords or related contributions during ideation) as well as the analysis and evaluation (e.g. clustering and classifying user contributions). NLP has been already applied in government practice (e.g. [START_REF] Androutsopoulou | Transforming the communication between citizens and government through AI-guided chatbots[END_REF][START_REF] Tambouris | Using Chatbots and Semantics to Exploit Public Sector Information[END_REF]) as well as in online citizen participation (e.g. [START_REF] Teufl | Automated analysis of e-participation data by utilizing associative networks, spreading activation and unsupervised learning[END_REF][START_REF] Maragoudakis | A review of opinion mining methods for analyzing citizens' contributions in public policy debate[END_REF][START_REF] Rao | Decision support for e-governance: a text mining approach[END_REF]). While various tools and automated programmable interfaces (APIs) exist (cf. e.g. [START_REF] Hagen | Introducing textual analysis tools for policy informatics: a case study of e-petitions[END_REF] for an overview), recent analysis shows that open source tools, that allow for a better control of data privacy and on premise operation of NLP, perform well in comparison with established API providers over closed source logical interference software and knowledge models [START_REF] Braun | Evaluating natural language understanding services for conversational question answering systems[END_REF].

Given the great number of applications, methodologies and tools, there are also numerous challenges to be addressed [START_REF] Sun | Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare[END_REF]. Hence, it would be of interest to analyse standardized artefacts potentially suitable for application in the government and, in particular, in the online citizen participation domain in order to effectively manage and streamline AI.

Online Citizen Participation in the Free and Hanseatic City of Hamburg and the Project Civitas Digitalis

Hamburg is a vivid city in northern Germany, with over 1.8 million citizens that has a strong economic development and a steady growth in terms of urban development and infrastructure projects. Since this growth affects a large number of citizens, citizen participation obtains an important role. In order to intensify information and participation in urban development projects and environmental protection issues and to develop a new planning culture in Hamburg, the 'Stadtwerkstatt' (city workshop) was set up as an organizational entity in the state-ministry of urban development and housing in 2012. Consequently, the Hamburg follows the concepts of top-down participation [START_REF] Porwol | An ontology for next generation e-Participation initiatives[END_REF] by providing an own platform for participation and thus steering the democratic participation process (cf. chapter 2.2). Since 2016, the city workshop unit offers a tool for online participation as part of its participation platform. The open source tool was developed in cooperation with the city's Agency for Geoinformation and Surveying (LGV) and since then has been used in more than 30 participation processes, with a total of over 10,000 contributions created by users. This geodata-based web application allows citizens to gather information about urban development projects and to submit contributions, including ideas, questions and criticism (cf. figure 2, accessible online https://geoportal-hamburg.de/be-teiligung_grasbrook/mapview-beitraege).

Fig. 2. An exemplary application of the online participation tool

The online participation tool is a basic online service that allows citizens to participate at any time and from any location. For the city administration and those officials responsible for project planning, the focus is particularly on greater reach and inclusion of social groups that are not able to participate at in-person meetings and workshops. For citizens who would like to participate, the tool provides an overview over the discussed topics, a thematic filter function and a city map visualization.

Since 2016, the city workshop offers a tool for digital participation as part of its participation platform. The open source online participation tool was developed in cooperation with the city's Agency Geoinformation and Surveying (LGV) and since then has been used in more than 30 participation processes, with a total of over 10,000 contributions created by users. This geodata-based web application allows citizens to gather information about urban development projects submit contributions, including ideas, questions and criticism (cf. figure 2, accessible online https://geoportal-hamburg.de/beteiligung_grasbrook/mapview-beitraege).

The online participation is a basic online service that allows citizens to participate at any time and from any location. For the city administration and those responsible for project planning, the focus is particularly on greater reach and inclusion of social groups not able to participate at in-person meetings and workshops. For citizens who would like to participate, the tool provides an overview of which topics are discussed, a thematic filter function and a city map visualization.

A greater reach provides a higher number of citizens' ideas and, in consequence, a significantly bigger effort for the evaluation and analysis of the ideas by the public administration employees is required. Currently, contributions from digital and analog participation need to be merged in one digital file and are evaluated manually. The entire process is quite time-consuming. In several work steps, the contribution data are viewed, checked with regard to content and topic and, if necessary, differentiated into further categories or subcategories. At the end, the results are summarized, and potential courses of action are formulated.

In this context, the research project Civitas Digitalis (https://civitas-digitalis.informatik.uni-hamburg.de/en/about-the-project/) was initiated with Stadtwerkstatt as partner from practice. A project goal is to develop and evaluate a toolset for supporting a more efficient and effective online citizen participation.

Research Approach

We follow a qualitative analysis approach to explorative research. We aim at developing descriptive artefacts that can be categorized as a theory for analyzing [START_REF] Gregor | The nature of theory in information systems[END_REF]. Our research approach is rooted in the paradigm of pragmatism [START_REF] Goldkuhl | Pragmatism vs interpretivism in qualitative information systems research[END_REF]. We studied the findings through an argumentative-deductive analysis [START_REF] Wilde | Forschungsmethoden der Wirtschaftsinformatik[END_REF].

Data Collection

For the analysis of this paper multiple types of data have been collected from three different sources. The first source of data are online citizen participation projects realized by the city of Hamburg in the last couple of years. We collected the ideas in German language from citizens in nine participation projects, cleaned the data by removing double entries or insufficient details entries. The total number of ideas was 3,859. The number of ideas per project vary from 95 to 1,689 ideas. The ideas, in turn, differ significantly in length, with the longest counting 1,079 words and the shortest 1 word. The median of words per idea is 15. Furthermore, the ideas have different properties. While most ideas consist of both the title and the description, some have only one of them. For instance, 1,018 ideas have no title. For every project, the ideas have been assigned by the citizen to a given category and after an idea has been submitted, the assignment has been analyzed, evaluated and potentially corrected by public administration employees. For the nine projects there is a total of 50 used categories-from now on called subcategories-that for the purpose of the analysis have been combined into eight groups -from now on called categories. The second source of data are interviews conducted in the course of this research that lasted between 35 and 60 minutes. One interview was undertaken with a citizen participation expert from a service provider that operates participation processes for municipalities. The second interview partner was an expert from the Stadtwerkstatt Hamburg which supports offices of the city with participation processes. Both interviews were conducted via telephone and based on a semi-structured questionnaires. The third interview has been conducted with an AI expert in order to evaluate the feasibility of the planned applications.

A workshop with 11 officials from the city of Hamburg and experts from service providers was the third source of data. In this workshop, the participants were asked to categorize 25 ideas from a recent citizen participation process (which is not part of the previously mentioned nine processes) into five predefined categories. The exercise was concluded by three groups of 3-5 experts in parallel, resulting in three classifications. Participatory observations as well as the allocation of ideas by the participants have been documented in writing.

Data Analysis

The analysis of the collected data included manually conducted reviews of the summarized interview reports, workshop results and reports as well as an automated NLP. The manual analysis was conducted by one researcher in our research group and was reviewed by a second researcher to assure consistency and to correct potential errors. With respect to methodological development and practical tool availability of NLP (cf. e.g., [START_REF] Maragoudakis | A review of opinion mining methods for analyzing citizens' contributions in public policy debate[END_REF][START_REF] Rao | Decision support for e-governance: a text mining approach[END_REF][START_REF] Stumme | Semantic web mining: State of the art and future directions[END_REF][START_REF] Berry | Survey of text mining[END_REF][START_REF] Tan | Text mining: The state of the art and the challenges[END_REF][START_REF] Mirończuk | A recent overview of the state-of-the-art elements of text classification[END_REF]), we decided to analyze data based on a traditional machine learning approach as well as on a neural network and deep learning approach (cf. our open source implementation https://civitasdigitalis.fortiss.org/ with data sets available upon request). Prior to applying each NLP approach, stratified sampling has been applied to the collected data set, splitting it into a training (80% -3,087 ideas) and an evaluation (20% -772 ideas) set, i.e. the resulting training and evaluation sets have the same distribution over the classes of ideas.

The first approach was based on the tool LingPipe [START_REF] Carpenter | Text analysis with LingPipe 4[END_REF] given its suitability for the analysis tasks (cf. e.g. [START_REF] Carpenter | LingPipe for 99.99% recall of gene mentions[END_REF][START_REF] Carpenter | Phrasal queries with LingPipe and Lucene: ad hoc genomics text retrieval[END_REF]). We implemented a character-level language-model based classifier. The classifier trains a model based on the occurrence count of characters and their combinations as well as the probability of both. The classifier predicts the assignment to a class based on the multivariate distribution of characters and their combinations to that class.

With regard to recent developments in neuronal network and deep learning approaches to NLP (cf. e.g. [START_REF] Alberti | A BERT Baseline for the Natural Questions[END_REF][START_REF] Gao | Neural approaches to conversational AI[END_REF][START_REF] Hu | An Introductory Survey on Attention Mechanisms in NLP Problems[END_REF]), the second approach applied in our data analysis is a classifier based on BERT [START_REF] Devlin | Bert: Pre-training of deep bidirectional transformers for language understanding[END_REF]. BERT implements a model architecture that includes a multi-layer bidirectional transformer encoder that can be configured to apply up to 1,024 hidden layers as well as 340 million parameters. Consequently, we decided to use the largest available BERT transformer that is pre-trained in a multilingual text setup and recommended for German language. We experimented with different characters sequence length, batch sizes, learning rates and number of epochs during the customization of the model, in order to evaluate accuracy.

Findings

Level of Standardization of AI Application in Online Citizen Participation

Based on the analysis of documents, interviews and workshop results, we apply the framework for standardization analysis as follows (cf. table 2) and note "NA" in each table cell, if the analyzed data did not allow to present a finding. On the organizational level, there have been only general standardization artefacts regarding security and privacy. In particular, the EU General Data Protection Regulation (GDPR) has been considered as a guide for conducting any type of data analysis. For instance, there have been concerns regarding any application using an API or 3rd party software that was not hosted on computers in Germany or in our research group. These concerns have also been linked to still missing standards for communication and interaction, since vendor or tool lock-in could result. In terms of particular business processes or models, there have been only initial considerations such as at which step of the participation process AI would be suitable and of use.

NA

At the semantic level, there has been a shared terminology regarding the classification of citizen ideas (e.g. "transportation" or "public space"). Still, this terminology has emerged and has not been a product of particular coordination effort. From a modeling functional perspective, there have been some implicit initial considerations (e.g. particular sentiment in an idea), but these have not been further detailed.

The technical and syntactic level included some initial considerations on how to integrate NLP techniques in existing tools (e.g. host an own analysis services, integration with front-end of the participation tool). Since the initial task of the researchers involved in the project was to apply NLP techniques, we were able to analyze a set of tools that can be applied and reused as standardized artefacts (e.g. LingPipe and BERT). Further, we were able to analyze standardization of communication and interaction between different tools. Based on the particular technology and technique applied, there are particular data exchange formats (e.g. a vector based representation of text for feature extraction). Still, there is no standard available and interoperability between tools and techniques have to be fitted to context.

AI Based Analysis

In order to compare both NLP approaches and their practical applicability, we conducted a number of tests with the data available (cf. table 3). Consequently, we applied a statistical confusion matrix that summarizes true positives (TP), false negatives (FN), false positives (FP), and true negatives (TN) as well as the F1 score to measure the accuracy of the prediction. For each category (listed in German), we had a different number of ideas split into training data and prediction test data.

For the NLP approach implemented with LingPipe, an average of 66.84% accuracy was observed. The accuracy varied significantly between categories. Although no correlation was analyzed in detail, our initial findings suggest that categories with higher numbers of ideas have better accuracy results. The NLP approach implemented with BERT achieved an improvement of 1.56% and resulted in a total of 68.4% accuracy. In summary, both approaches showed promising results, the data available is of reasonable quality and there is a large enough data set. For instance, the best results were generated for the category "Verkehr & Mobilität" (transportation & mobility). This category contains 1.689 ideas in the data set and, arguably, the data quality is consistent among all ideas. On the contrary, the category "Sonstiges" (miscellaneous) contains 456 ideas in the data set that appear to be of varying quality, i.e. ideas were put in this category only if not matching any other. Apparently, there were no further semantic or any other classification rules applied.

Comparing AI and Human based Analysis

The collected human-based classification obtained in the workshop and the above described analysis allow for a comparison of human-based and AI-based categorization of participation ideas. The baseline for this comparison is the original category assignment of the contributor which we will consider as the correct category.

The groups of experts in the workshop categorized 14, 15 and 16 out of 25 categories correctly. This corresponds with a success rate of 60% in average. While some categories seemed to be easier to categorize for the experts, others appear to be less so -potentially, due to semantic heterogeneity. This was also reflected in the discussions among the workshop participants.

For the AI-based categorization, we applied both NLP approaches and selected the results with highest accuracy. Moreover, we developed an analysis improvement that delivered not only the first best fitting category, but also the second best fitting category. Considering, with the first best guesses considered, 8 out of 25 categories have been classified correctly which corresponds with a 32% success rate. Including also the second-best guesses, 13 out 25 ideas have been assigned to their correct category, resulting in a success rate of 52%. As for the human-based results, the success rate by category varied also for the AI-based assignment. In comparison, the AI-based categorization is not as effective as the human-based one (cf. table 4). Considering the average of the workshop groups and the more favorable AI-based counting (including the second-best guess), there still remains a difference of two ideas less assigned correctly.

Discussion and Conclusion

The objective of this paper was to address the question of how to streamline AI application in government and, in particular, in the online citizen participation. We presented theoretical background on standardization, online citizen participation processes and application of AI and developed and argument that a standardization of AI artefacts at different levels and from different functional perspectives is required towards streamlining AI application. Based case study in Germany, we presented findings on levels of standardization, results from applying two different AI techniques for natural language processing as well as a comparison between human and AI performance.

Our findings show the following implications regarding AI application in government and, in particular, in online citizen participation. First, there are already NLP tools and pre-trained models available that can provide efficient support along the steps of the participation process. Quality, amount and availability of data seem to be of high importance for sufficient prediction, though. Second, human based analysis still has a number of advantages. As the results of our workshop show, humans are capable-in the course of intensive discussion and collaboration-to outperform AI and NLP. Additionally, the arguments provided by the workshop participant explained why a particular idea was assigned to a particular category. In the case with the implemented NLP techniques and tools, we were not capable of providing these insights. What is a reference model or an architecture, based on e.g. [START_REF] Scherer | E-participation and enterprise architecture frameworks: An analysis[END_REF][START_REF] Santana | Software platforms for smart cities: Concepts, requirements, challenges, and a unified reference architecture[END_REF] How to integrate AI in existing tools for the design of online participation?

How to assure a technology shift?

How can GDPR conformity be evaluated and assured?

Semantic

What are shared contextspecific concepts that can be integrated using AI?

What is a suitable ontology, e.g. based on [START_REF] Wimmer | Ontology for an e-participation virtual resource centre[END_REF][START_REF] Porwol | An ontology for next generation e-Participation initiatives[END_REF] What are available AI services that fit requirements of online citizen participation?

How to share language specific AI results?

Technical / Syntactic How to monitor and manage AI applications?

How to integrate AI applications in existing IT infrastructures?

How to improve data quality and customize models? Which competencies are required for the application of AI?

Are the any certified tools available?

Third, our findings suggest that a standardization of AI application in government and, in particular, in online citizen participation is still in its infancy. There were only a few standardized artefacts available, predominantly on the technical/ syntactic level. Due to this current status, available data in suitable quality for efficient and effective AI application is even more challenging. This research presents a first glimpse of the potential of and barriers to standardized artefacts for streamlining AI application in government. Given the contextual limitations-a case study on online citizen participation in Germany, data set size and quality, available tools and techniques etc.-we would like to encourage researchers to dig deeper in the sketched challenges and derive potential remedies. Therefore, we have summarized a number of questions that emerged during our research and could be addressed in future (cf. table 5). Additionally, future research could focus on interactions between the different standardization levels and their implications to adoption of AI in government. Given the number of human languages available and the expected potential of AI in government, we hope that future research would allow for a more efficient development and sustainability of AI application.

Table 1 .

 1 Analysis framework and exemplary standardization artefacts in e-government

			Administra-tion	Modeling	Processing	Communi-cation & Inter-action	Security & Privacy
	Organi-	zational	Business Process	Reference Process	Business Process Mod-eling Tool	Process Model Ex-change Format	Information Access Policy
	Seman-	tic	Shared Ter-minology	Ontology	Information Search Service	Common Metadata Defi-nition
	Technical	/ Syntactic	Business Reporting	Application Architecture	Tax Accounting Application Software	Data For-mat	Encryption Algorithm

Table 2 .

 2 Analysis of standardization level of AI application in the case study

				Administra-tion	Modeling	Processing	Communi-cation & Inter-action	Security & Privacy
	Organ-	izational		initial con-siderations	initial con-siderations	NA	vendor or concerns tool lock-in	GDPR
	Seman-	tic	shared ter-minology in similar partici-	initial con-siderations	NA	NA
			pation projects
	Tech-	nical / Syn-	tactic	initial con-siderations	NA	tools based on machine learn-ing	model or technique spe-cific

Table 3 .

 3 Comparison of the applied NLP approaches

		LingPipe tool			BERT tool
	Category TP FN FP TN	Recall	Precision	F1	TP FN FP TN	Recall	Precision	F1	Test Data	Training	Data
	Verkehr &
	Mobilität	326 12 120 314 96,45% 73,09% 83,16% 302 36 66 368 89,35% 82,07% 85,55% 185 1504
	Wohnen &
	Arbeiten	24 24 21 703 50,00% 53,33% 51,61% 24 24 19 705 50,00% 55,81% 52,75% 15 225
	Grün &
	Erholung	20 38 8 706 34,48% 71,43% 46,51% 32 26 28 686 55,17% 53,33% 54,24% 24 265
	Sport &
	Freizeit	74 21 30 647 77,89% 71,15% 74,37% 76 19 32 645 80,00% 70,37% 74,88% 50 426
	Klima &
	Umweltschutz 1 18 1 752 5,26% 50,00% 9,52% 7 12 8 745 36,84% 46,67% 41,18% 10 85
	Städtebau &
	Stadtraum	20 50 10 692 28,57% 66,67% 40,00% 23 47 36 666 32,86% 38,98% 35,66% 33 317
	Soziales &
	Kultur	25 28 11 708 47,17% 69,44% 56,18% 34 19 20 699 64,15% 62,96% 63,55% 25 239
	Sonstiges	26 65 55 626 28,57% 32,10% 30,23% 27 64 38 643 29,67% 41,54% 34,62% 44 412

Table 4 .

 4 Human and AI based analysis

Human based AI based Group 1 Group 2 Group 3 average first- best guess first and sec- ond-best guess Correctly assigned ideas

		14	16	15	15	8	13
	Success	56%	64%	60%	60%	32%	52%
	Rate

Table 5 .

 5 Future research on streamlining AI application in online citizen participation

		Administra-tion	Modeling	Processing	Communi-cation & Inter-action	Security & Privacy
	Organizational	How does an online par-ticipation pro-cess with AI
		look like?

Acknowledgements

This research was partially funded by the German Federal Ministry of Education and Research (BMBF) with the project lead partner PTKA (Projektträger Karlsruhe am Karlsruher Institut für Technologie/KIT) in the context of the project Civitas Digitalis (funding code '02K15A050').

We thank our reviewers for their careful reading and their constructive remarks.