Iryna Susha
email: iryna.susha@oru.se

Maartje Flipsen

Wirawan Agahari

Mark De Reuver

Towards Generic Business Models of Intermediaries in Data Collaboratives: From Gatekeeping to Data Control

Keywords: Data Partnership, Data Collaborative, Intermediary, Business Model, Data Innovation, Data Intermediary

Data has become a core asset, as well as a "management fashion", of our time. It brings about unprecedented opportunities for data-driven decision making and innovation in various spheres of public life. This concerns data held by governments, as well as companies, academic institutions, non-profits, and citizens. In our study we investigate a novel form of cross-sector partnership called Data Collaborative, and namely the business models employed by intermediaries in data collaboratives. Based on an analysis of six cases, we derived four generic business models based on the level of openness and added value of the data: Data Gatekeeper model, One-stop-shop model, Information-as-a-service model, and Data Controls model. Our study contributes to the literature on data partnerships and on intermediation and information sharing more broadly.

Introduction

Data has become a core asset, as well as a 'management fashion' [START_REF] Abrahamson | Management Fashion[END_REF], of our time. It brings about unprecedented opportunities for data-driven decision making and innovation in various spheres of public life. This concerns data held by governments, as well as companies, academic institutions, non-profits, and citizens. Often, collaboration is needed because data from different parties have to be combined to realize opportunities. The notion of Data Collaboratives captures this collaboration imperative and stands for "cross-sector (and public-private) collaboration initiatives aimed at data collection, sharing, or processing for the purpose of addressing a societal challenge" [START_REF] Susha | Data Collaboratives as a New Frontier of Cross-Sector Partnerships in the Age of Open Data: Taxonomy Development[END_REF]. In the past five years the concept of data collaboratives, initially coined by The Gov Lab, has gained much interest (e.g. World Bank's Development Data Partnership, EU Commission's Expert Group on B2G Data Sharing).

There is a row of successful and less successful stories of data collaboratives. Data collaboratives face several rather specific challenges, such as balancing data control and ownership, governance challenges, legal constraints, privacy and ethics issues, competitive risks, technical challenges, to name a few [START_REF] Robin | Public-Private Partnerships for Statistics: Lessons Learned, Future Steps[END_REF][START_REF] Taddeo | Data philanthropy and the design of the infraethics for information societies[END_REF][START_REF] Van Den Broek | Governance of big data collaborations: How to balance regulatory compliance and disruptive innovation[END_REF]. Different types of data intermediaries have emerged that view these challenges as opportunities. There is however little knowledge on how these data intermediaries operate and what business models they employ. Providing more clarity on this can create a better understanding of the roles that government can play in such data collaboratives. Therefore, our research question is: What business models are employed by intermediaries to create value in data collaboratives?

The paper is structured as follows: in Section 2 we review relevant literature on intermediation in data sharing and collaboration processes; in Section 3 present our analytical framework for intermediary business model analysis; in Section 4 we outline our multiple case study method; in Section 5 we present a comparative analysis of the cases; and in Section 6 we formulate generic business models from the case data; and in Section 7 we summarize and reflect on our findings.

Intermediaries in Data Collaboratives: conceptualization

Data intermediaries in the context of data have characteristics that resemble wellknown notions of infomediary, partnership broker, and innovation intermediary. Intermediaries that facilitate data sharing (also known as 'infomediaries') are well described in the open data literature. There are, however, different conceptualizations of the functions of these intermediaries. Open data intermediaries can develop products and services based on open data for citizens, government, or third parties [START_REF] Magalhaes | Open government data intermediaries: a terminology framework[END_REF] and can present complex datasets in a user-friendly way [START_REF] Mercado-Lara | Open government and data intermediaries: the case of AidData[END_REF]. Meijer and Potjer [START_REF] Meijer | Citizen-generated open data: An explorative analysis of 25 cases[END_REF] broaden the concept of open data intermediary to include actors facilitating the generation of data by citizens.

Inter-organizational collaboration literature puts forward the concept of 'partnership brokers' who have specific experience and capacity to facilitate negotiation and development of partnership arrangements [START_REF] Stadtler | How broker organizations can facilitate public-private partnerships for development[END_REF]. Partnership brokers can create value by acting as matchmakers, connectors, facilitators, co-designers, conveners, mediators, or learning catalysts [START_REF] Lee | Understanding the role of the broker in business non-profit collaboration[END_REF][START_REF] Stadtler | How broker organizations can facilitate public-private partnerships for development[END_REF].

Another relevant concept is that of an 'innovation intermediary'. Overall, innovation intermediaries create value by (1) connecting actors; (2) involving, committing, and mobilising actors; (3) solving, avoiding, or mitigating potential conflicts of interests; and (4) (actively) stimulating the innovation process and innovation outcomes [START_REF] Agogué | Explicating the role of innovation intermediaries in the "unknown": a contingency approach[END_REF]. Holzmann, Sailer and Katzy [START_REF] Holzmann | Matchmaking as multi-sided market for open innovation[END_REF] discuss the role of innovation intermediaries in multisided markets, whereby innovation intermediaries are tasked with the matching process between demand and supply.

More recently, the term 'trusted data intermediary' (TDI) entered into circulation in the practitioner community [START_REF]Digital Civil Society: Trusted Data Intermediaries[END_REF][START_REF]Workshop summary: Trusted data intermediaries[END_REF][START_REF] Susha | Data Collaboratives as a New Frontier of Cross-Sector Partnerships in the Age of Open Data: Taxonomy Development[END_REF]. Recently, a research agenda was formulated by Stanford researchers who recognized this as an emerging term [START_REF]Digital Civil Society: Trusted Data Intermediaries[END_REF][START_REF]Workshop summary: Trusted data intermediaries[END_REF]. They defined TDIs as entities that have "a commitment to collect, aggregate, and make available large sets of digitized data for public purpose" [START_REF]Workshop summary: Trusted data intermediaries[END_REF]. The key distinguishing feature of TDIs is the suite of negotiations, ranging from data ownership, storage, access, analysis and security to ensuring privacy, regulations and legal conditions, and standards and practices (Ibid.). The intermediaries conduct these negotiations for different kinds of data, across sectors, and in various organizational forms (Ibid.). These intermediation concepts provide the necessary depth for conceptualizing and grounding the notion of intermediaries of data collaboratives in existing academic research. Previous research [START_REF] Susha | A Collaborative Governance Approach to Partnerships Addressing Public Problems with Private Data[END_REF] found that, compared to collaborations in general, data collaboratives face very specific collaboration challenges: the decisive role of trust between parties, data stewardship, data-related risk mitigation, and formulating value proposition to both sides. Intermediaries of data collaboratives, therefore, have a potential to create value by addressing these challenges. Our study aims to shed light on how they achieve this by analyzing emerging business models of select intermediaries in this context.

Framework for Business Model Analysis

The notion of 'business model' has been discussed in various streams of literature.

Here, we follow the definition by Amit and Zott [4]: a business model depicts how the content, governance, and structure of transactions create value.

With the growing importance of data as raw material for the digital economy, there is an emergence of the data-driven business model (DDBM) as one specific type of business model [START_REF] Hartmann | Capturing value from big data -a taxonomy of data-driven business models used by start-up firms[END_REF] which emphasizes data as a key resource in firms' business models, particularly to establish value proposition [START_REF] Benta | Process model for data-driven business model generation[END_REF]. The majority of scholars focused their research on identifying patterns and/or developing a framework/taxonomy for DDBM [START_REF] Hartmann | Capturing value from big data -a taxonomy of data-driven business models used by start-up firms[END_REF][START_REF] Schüritz | Capturing Value from Data: Revenue Models for Data-Driven Services[END_REF][START_REF] Hilbig | Berlin Start-ups -The Rise of Data-Driven Business Models[END_REF]. These classifications, however, apply primarily to companies in a commercial setting; they do not fully capture either the public value goals of data collaboratives or the non-profit motives of intermediaries in this context.

As for the intermediary business model, the literature in this domain is still scarce. Weill and Vitale [START_REF] Weill | Portals, Agents, Auctions, Aggregators and Other Intermediaries[END_REF] discuss the "generic business model" of electronic intermediaries. They argued that the provision of services in this business model (e.g., knowledge management, centralized management of applications, information search services) offers buyers and sellers (e.g., business, consumer, or other entities) lowered search and transaction costs. Similarly, Janssen and Zuiderwijk [START_REF] Janssen | Infomediary Business Models for Connecting Open Data Providers and Users[END_REF] explicate infomediary business models by formulating six types of business models based on the levels of data accessibility and dialogue between data users and data contributors. Most recently, intermediaries as marketplaces enabled by digital technologies were studied by Täuscher and Laudien [START_REF] Täuscher | Understanding platform business models: A mixed methods study of marketplaces[END_REF], in which they developed a taxonomy of six types of web-based platform business models.

In sum, to describe a business model, many ontologies exist. A business model ontology is an explicit, simple specification of a conceptualization of components of a business model and the relationships between them [START_REF] Heikkila | The Role of Business Models in Developing Business Networks[END_REF][START_REF] Kort | Modeling Strategic Partnerships Using the E3value Ontology[END_REF]. For our study, we needed a framework that is sufficiently broad to capture the description of kinds of value (for different customer segments), resources, governance mechanisms, and financial arrangement of intermediaries. Based on this rationale, we selected the Unified Business Model Framework (UBM Framework) by Al-Debei and Avison [START_REF] Al-Debei | Developing a unified framework of the business model concept[END_REF]. The framework is arguably one of the most comprehensive business model frameworks, as it was devel-oped through the systematization of 22 other business model frameworks. This framework has also been applied in other similar studies [START_REF] Janssen | Infomediary Business Models for Connecting Open Data Providers and Users[END_REF][START_REF] Ranerup | An analysis of business models in Public Service Platforms[END_REF] that focus on entities that act as intermediaries.

The framework's ontological structure comprises of four dimensions, each explained by specific constituent elements. We follow the operationalization of this framework as proposed by Janssen & Zuiderwijk [START_REF] Janssen | Infomediary Business Models for Connecting Open Data Providers and Users[END_REF] since they focused on open data intermediaries which is a similar context to ours. See Table 1 for an overview of the four dimensions considered in this study.

Table 1. Framework for Business Model Analysis (adapted from Al-Debei and Avison [START_REF] Al-Debei | Developing a unified framework of the business model concept[END_REF] and Janssen & Zuiderwijk [START_REF] Janssen | Infomediary Business Models for Connecting Open Data Providers and Users[END_REF])

BM Elements

Operationalization Value Proposition Business logic for creating value by offering products and services for targeted segments (data providers on one side and data users on the other) Value Architecture Architecture for the technological and organizational infrastructure used in the provisioning of products and services

Value Network

Collaboration and coordination with other organizations

Value Finance

Pricing and revenue breakdown associated with sustaining and improving the creation of value

Case study method

For our study we conducted an exploratory multiple case study [START_REF] Yin | Case study research[END_REF]. We chose to sample cases by diversity. Data collaboratives can be categorized by their expected outcome into three arenas: (a) policy intervention, (b) data science, and (c) data-driven innovation [START_REF] Susha | Data Collaboratives as a New Frontier of Cross-Sector Partnerships in the Age of Open Data: Taxonomy Development[END_REF]. In our case sampling we included two cases per each type to ensure diversity. We assumed that, based on these types, intermediaries create value for different target groups and therefore the value proposition, as well as value delivery and capture mechanisms, are likely to be different. As a result, the following cases were included in our analysis (Table 2).

Datadriven innovation

The data was collected by conducting online desk research which included analysis of the case websites, documents, and applications. The number of data sources depended on the availability of information and ranged between 2 and 8 per case. In analyzing each case, we followed the qualitative content analysis approach [START_REF] Krippendorff | Content analysis: An introduction to its methodology[END_REF] that is driven by the structure of the analytical framework, i.e. data for every case were coded and categorized into the value proposition, value architecture, value network, and value finance dimension. In cases when online research was did not provide sufficient data, we conducted interviews with key informants of the projects to obtain clarifying information (CIP) or participated in observations during meetings and presentations (HDX, AMdEX).

Findings

In this section we present our analysis of the selected cases1 through the lens of the analytical framework found in Table 1. We thus derive the business models of the intermediaries based on the four elements of the framework: Value Proposition, Value Architecture, Value Network, and Value Finance.

Our analysis shows that the intermediary model of data collaborative can be employed to address a wide range of needs and create value in different ways along the data value chain. Data intermediaries can facilitate access to previously closed data, 6 provide an infrastructure for aggregating previously fragmented data, produce visualizations and targeted apps for eased use and understanding of data, offer interactive solutions for collecting and sharing data.

In terms of Value Architecture, the majority of the cases (except for SSO) rely heavily on pooling diverse data sources together, although they create value from that via different pathways.

Regarding Value Network, our analysis of the six cases shows that several roles can be identified. The intermediaries we analyzed have diverse organizational forms and various actors can be in the lead: academic institutions, companies, inter-governmental organizations, non-profit organizations; yet, the triple helix construction (government, industry, academia) is widely leveraged.

Finally, data intermediaries can be financially supported by different actors like nonprofit foundations, industry, research institutions, government and can additionally create revenue themselves from fees for their products and services.

More nuance can be added by discussing pairs of cases according to our sampling strategy by three arenas: data science, policy intervention, and data innovation. Our analysis found that there are both similarities and differences among these types of cases.

As regards data intermediaries in the arena of data science, as evidenced by the cases SSO and Vivli, their core value proposition is facilitating easier access by researchers to valuable data from the private (and public sectors in case of Vivli). Industry-academia data intermediaries deliver value to researchers as data users by pre-negotiating data access agreements with data providers that otherwise cost researchers much time and effort. The rationale for the data provider differs depending on the context. In the case of SSO, data providers like Facebook may see it as a means to increase transparency and improve their reputation in the aftermath of negative data analytics publicity. In the Vivli case, which provides a one-stop-shop of clinical trials data, the value for data providers is increased discoverability of their data and enhanced capacity for data sharing and reuse, thereby breaking down silos in medical research. Data contributors are offered services for secure data hosting, tools for anonymization and mapping of data, and the service of reviewing data requests on their behalf. Data users are offered a data search engine, a form to request data with data contributors, as well as an environment and tools for data aggregation (from various sources) and analysis of this data. Both data providers and users are asked to sign a Harmonized Data User Agreement prior to data sharing. In both cases, however, the intermediary support the scientific process by providing an organizational (SSO) and/or technical (Vivli) infrastructure for data access. Furthermore, they act like a "neutral broker" and perform a function of a data steward.

Data intermediaries in the arena of policy intervention are guided by slightly different objectives. Data resources created via these data collaboratives are a public good, therefore openness is at the heart of the value proposition of these intermediaries. In the case of HDX, the value of the intermediary, besides providing a technical platform and standardized process for sharing data, is providing quality assurance services to ensure risks to privacy are minimal. HDX exists since 2014 and during this time the focus has shifted from mere data aggregation to data transformations, such as visualizations. The value that this intermediary provides to data contributors is assistance with data processing and preparing data for publication, thereby tackling the data quality challenge in the humanitarian sector. Data contributors are offered services and tools that host data, impose access controls for published data sets, create metadata, and standardize, refine, statistically analyze and visualize data. For data users, services and tools for searching, following and requesting data are offered, as well as an API infrastructure to integrate the platform into user-own developments. The HDX team verifies data contributors and evaluates contributed data sets for data quality and sensitivity levels.

For both HDX and GFW, data visualizations form one of the core elements of the value proposition. The mission of the Global Forest Watch is to bring data insights to the society, including government decision-makers, companies, journalists, researchers and the public, to drive evidence-based action in forest management and conservation domain. This platform combines and overlays best available data from various sources (government, research, crowdsourced, proprietary) to produce targeted applications, such as Forest Watch and GFW Pro. There is also an open data portal for downloading datasets as open data. Both cases, HDX and GFW, add value by centralizing large volumes of data in one portal and by transforming data into actionable visualizations and insights to drive policy action. In this sense, they can be seen as 'infomediaries' [START_REF] Janssen | Infomediary Business Models for Connecting Open Data Providers and Users[END_REF] that help users manage vast amounts of information.

In the arena of data-driven innovation, the data intermediaries we analyzed were AMdEX and Civity. These intermediaries aim to provide a secure data infrastructure and 'rules' for data sharing among diverse parties from different sectors enabling data owners to remain in control of what data they share and with whom. Both cases are connected to international initiatives potentially feeding into the larger data innovation ecosystem in Europe. The CIP platform is limited to the smart city theme, while

AMdEX has an open-ended scope potentially embracing a wide variety of data innovation use cases. Here intermediaries have to deal with issues of balancing competition and data protection with innovation and openness, therefore trust in the technical solution and in the members of the network play an important role in these cases. Both intermediaries create value to data contributors by offering a trusted data infrastructure. However, the difference is that in the case of AMdEX the business model is still a search process; it is emerging from consultations with stakeholders about their needs and challenges. Therefore, issues of standardization and interoperability are of concern, given the different demands and expectations of the wide range of stakeholders. While in the CIP case, the business model is very straightforward and determined by the company as a platform provider -'take it or leave it'.

Discussion

Overall, we find that the business models described differ based on the following discriminating variables:

• Level of openness -stands for the extent to which data access is restricted or available. A high level of openness means that anyone can use the data provided through an intermediary; a medium level of openness means that there is a process in place to approve data requests; and a low level of openness means that the data is available to members only. Thereby, we place the business models on a continuum. • Added value to the data -key activities that the intermediary performs along the data value chain to realize the value proposition.

Table 3 below shows how the six cases we analyzed are classified according to these variables. We observe that the level of openness in these six intermediary cases correlates with the three arenas based on which we selected the cases. Data science collaboratives, such as SSO and Vivli, have a medium level of openness due to the data access procedures that are put in place (call for proposals to researchers, data request forms).

Policy intervention collaboratives, such as HDX and GFW, have a high level of openness due to the public nature of the issue and the fact that the platforms they provide are considered as public good. Data innovation collaboratives, such as AMdEX and CIP, have a low level of openness as in the former case data access can be controlled by the data provider and in the latter case the platform is offered on a for-profit basis.

In terms of added value, some cases can be placed in several (more than two) categories (e.g. GFW provides data access through their open data portal, data visualizations through the Forest Watcher app, and data sharing tools for supply chain monitoring via its GFW Pro app). Nonetheless, in Table 3 below we highlight the activities that are at the very core of the value proposition of the intermediary. For some cases that are placed in two cells, namely HDX, this also shows the evolution of the business model (towards more data visualizations). Based on these variables, we distinguish the following generic business models for a data intermediary in a data collaborative setting. Since we based our analysis on six cases, we allow the possibility that other cells in this table may be filled in with other business models.

1. Data gatekeeper model (Social Science One): intermediary serves as a trusted third party that negotiates terms of access to previously closed data by users selected through a call for proposals. Value comes from the legitimacy of the process.

2. One-stop-shop model (Vivli, HDX): intermediary aggregates previously siloed data from multiple sources into a central data repository to ease discoverability, comparability, and analysis of data. Value comes from scale, therefore the intermediary is dependent on data providers contributing data. 3. Information-as-a-service model (GFW, HDX): intermediary provides data visualizations to targeted segments to ease the understandability of data for decision-makers. Value comes from ease-of-use and quality of decision support; therefore, the intermediary is dependent on users. 4. Data controls model (Civity CIP, AMdEX): intermediary offers a solution for sharing data (including sensitive data) in a secure, targeted, and controlled manner with full insight into who uses the data. Data owners are offered a menu of options what (parts of) data to share with whom and for what period. The value comes from the technical excellence of the product and the data expertise of the intermediary. Therefore, the intermediary is dependent on buy-in from key stakeholders and on standardization and interoperability efforts.

In the realization of these business models the intermediaries are dependent on interactions with other actors in the data ecosystem. In the Data Gatekeeper model, the data intermediary is dependent on the acceptance and trust of the wider (scientific) community. The role of government, at least based on the SSO case, is supporting, providing guidance and/or setting norms. In the One-stop-shop model, where more value comes from scale, the intermediary is dependent on data providers contributing data to build a comprehensive repository. In both Vivli and HDX government organizations can be data providers or users, as well as partners of the initiative. In the Information-as-aservice model, the intermediary is dependent on the users from different target groups. Governments can play multiple roles here by providing data, supporting the initiative, and consuming the data analysis products themselves. And in the Data Controls model, where value comes from buy-in from key stakeholders, government can be a facilitator, a data provider/client, data user, and funder. Overall, our study confirms and provides illustrations of the roles of government in data collaborations described in previous research [START_REF] Kort | Modeling Strategic Partnerships Using the E3value Ontology[END_REF][START_REF] Schwabe | The role of public agencies in blockchain consortia: Learning from the Cardossier[END_REF]: namely, government as a data provider, data user, facilitator of collaboration, supporter or funder, an active partner in the consortium, a guarantor of data quality, source of trust, public interest promoter. Our research however shows that it is rarely just one role that government organizations assume but a combination of roles. When compared to the existing literature [START_REF] Janssen | Infomediary Business Models for Connecting Open Data Providers and Users[END_REF], there are some similarities and differences. For instance, the One-stop-shop model is an extension of three different business models, as this model aggregates siloed data from multiple sources (i.e. information aggregators) and stores those data centrally (i.e. open data repository) to make the data easier to search, compare and analyze (i.e. service platforms). Similarly, in the Information-as-a-service model, data intermediaries will act as service platforms that offer data processing and analysis services that can help decision-makers in making better policies. However, there are notable differences in a way that we also emphasize technical resources and the enabling environment to promote data transparency and sovereignty, as can be seen in the Data gatekeeper and Data control models. In this way, we allow the possibility to open up the data that are traditionally challenging to be open, especially data possessed by private entities.

Conclusion

Our study investigated how intermediaries create value and what business models they use to facilitate data exchange and collaboration in the context of data collaboratives.

For our analysis we selected six cases representing three different arenas of data collaboratives: data science, policy intervention, and data-driven innovation. Based on the case analysis, we derived four generic business models that can be employed by intermediaries in data collaboratives. These generic business models are distinguished by two variables -level of openness and added value to the data. We labeled these business models as follows: Data Gatekeeper model, One-stop-shop model, Information-as-aservice model, and Data Controls model.

Our study shows that the intermediary model of data collaboratives can have different configurations and can follow various pathways for value creation. As evidenced by our cases, in their offerings intermediaries aim to tackle diverse challenges that data collaboratives face, such as balancing collaborative data sharing with control over data, overcoming fragmentation and creating data pools, brokering access to controversial data, matching data supply and demand though market rules, and more. The four business models further differ based on what the value comes from and who or what the intermediary is dependent on to realize the value proposition. We further discussed the implications of these findings for governments explicating the different roles in which they can step in these initiatives.

Our research contributed empirically derived knowledge about data intermediaries through the lens of data collaboratives. This adds to our understanding of emerging data ecosystems leveraging diverse data sources for creating public value through crosssector collaboration. The limitations of our work are that our study is exploratory and was based on a limited number of cases. Future research can test and elaborate our findings in other empirical settings. Furthermore, much literature discusses trust as an important element of intermediaries (e.g. [START_REF] Bailey | An Exploratory Study of the Emerging Role of Electronic Intermediaries[END_REF][START_REF]Digital Civil Society: Trusted Data Intermediaries[END_REF][START_REF]Workshop summary: Trusted data intermediaries[END_REF][START_REF] Froomkin | The Essential Role of Trusted Third Parties in Electronic Commerce[END_REF][START_REF] Skevington | Trusted Third Parties in Electronic Commerce[END_REF][START_REF] Stadtler | How broker organizations can facilitate public-private partnerships for development[END_REF][START_REF] Van Schalkwyk | Viscous Open Data: The Roles of Intermediaries in an Open Data Ecosystem[END_REF][START_REF] Womack | Information intermediaries and optimal information distribution[END_REF]). In our study we did not explicitly interrogate whether and to what extent the conceptualizations of trust can be different across the various intermediary business models. We propose this research question for future investigations.

Table 2 .

 2 Selected cases with descriptions

	Case	Since Summary	Purpose
	Social	2018 SSO is an initiative that enables social scientists around	Data sci-
	Science One	the world to analyze and use the increasingly rich troves	ence
	(SSO)	of information amassed by companies to address societal
		issues. SSO is incubated at Harvard University (USA).
	Vivli	2018 Vivli is an independent non-profit organization that pro-	Data sci-
		vides a global data sharing and analytics platform for	ence
		clinical research data.

Table 3 .

 3 Variables for deriving generic business models from cases

	Added Value	Level of Openness
		Low	Medium High
	Data Access		SSO
	Data Aggregation		Vivli	HDX
	Data Visualization		GFW, HDX
	Data Exchange	AMdEX, CIP

The complete analysis of the cases per each element of the framework is uploaded as an open dataset to 4TU.Centre for Research Data repository and can be found using the following DOI: 10.4121/uuid:951848c4-6447-4fce-9f33-b1223b0c18e1

Acknowledgements

This research received funding from the Swedish Research Council under the grant agreement 2015-06563 "Data collaboratives as a new form of innovation for addressing societal challenges in the age of data". This paper is in part based on the work done by the second author in a scientific thesis. All copyrights on the prior work rest with the second author of the paper. Any views expressed by the second author in this paper are those of the author and do not necessarily reflect the views of her employer.


Göran Goldkuhl
email: goran.goldkuhl@liu.se

Between overexploitation and underexploitation of digital opportunities -a case study with focus on affordances and constraints

Keywords: E-government, affordance, constraint, policy, digital opportunity

Several policies for e-government, both on national and supranational levels, express visions and claims for more advanced exploitation of digital opportunities. The paper contributes through a problematization of the idea of utilizing digital opportunities and a conceptualization of this into the polarity of overexploitation vs. underexploitation of digital opportunities. It is based on a qualitative and diagnostic case study on the digitalization of medical certificates and theoretically informed by affordance theory and activity theory. Digital arrangements in the case study are investigated and different types of digital affordances and constraints are revealed. There are examples of surplus of affordances (i.e. overexploitation), lack of affordances and affordances with embedded constraints (i.e. underexploitation), and useful affordances (i.e. adequate exploitation). The application of the affordance and constraint concepts is, in the paper, done through a two-step staging: 1) General characteristics of digital technology give affordances for design. 2) The resulting digital artifacts will have different properties and these properties give affordances but also constraints for use. The resulting conceptualizations are discussed in relation to normative, regulative and other institutional aspects concerning digitalization in the public sector. This is conceptualized in a graphical model describing policy and other pre-conditions, designed digital artifacts, and workpractice effects.

Introduction

There is a strong claim, among both practitioners and scholars, for increased exploitation of digital opportunities in public administration. In policy planning for egovernment development, there exist visions and claims for better utilization of opportunities that digital technology offers. This can be seen in policy documents both on national and supranational levels. There exist several EU policy documents that argue for more advanced exploitation of digital opportunities such as the Tallinn Declaration that states "we are yet to seize the full potential of the digital transformation in our administrations as well as at the EU level" [START_REF]EU: Tallinn Declaration on eGovernment[END_REF]. Another policy document argues for "embracing creative disruption from technology … packaged in new digital gov-ernment offerings" [START_REF]EC: Powering European public sector innovation: Towards a new architecture[END_REF] as an important design principle for overcoming barriers of innovation in public administration. One policy example on the national level is the national agenda for digitalization in the public sector of Sweden. There is an enounced objective to reach e-government of world-class: "Sweden should be best in the world at using the opportunities of digitalization." [START_REF]Swedish Government: It i människans tjänst -en digital agenda för Sverige[END_REF]. This objective, originally formulated in 2011, has recurrently been expressed in several policy reports; e.g. [START_REF]För digitalisering i tiden. Slutbetänkande av Digitaliseringskommissionen[END_REF].

There is a clear competitive reasoning behind this vision; to be one of the best. The recurring benchmarks of e-government maturity [START_REF] Berntzen | Benchmarking e-government. A comparative review of three international benchmarking studies[END_REF] seem to be a driver for this kind of thinking. There exist international benchmarks such as the United Nation's e-Government Development Index [39] and the European Commission's eGovernment Benchmark [START_REF]EC: eGovernment Benchmark 2018[END_REF].

In the scholarly literature, there exist several proposals for stage models [e.g. [START_REF] Kim | E-government maturity model using the capability maturity model integration[END_REF][START_REF] Layne | Developing Fully Functional E-government: A four-stage model[END_REF][START_REF] Lee | 10 year retrospect on stage models of e-Government: A qualitative meta-synthesis[END_REF] of egov evolution. These models describe stages of different maturity layers, where more advanced layers are presumed to be better. However, as noted [START_REF] Cordella | E-government success: how to account for ICT, administrative rationalization, and institutional change[END_REF], "these stages … do in fact mainly assume that the level of technological sophistication can be an indicator of success". This paper addresses this issue of exploitation of digital opportunities in egovernment. The main inquiry question is: In what ways are digital opportunities utilized? This is based on a knowledge interest in relationships between digital policies and digital realizations. This is an area that is considered as under-researched [START_REF] Cordella | E-government success: how to account for ICT, administrative rationalization, and institutional change[END_REF][START_REF] Jaeger | The history of the future: Changes in Danish e-government strategies 1994-2010[END_REF]. The paper contributes to this discourse through a problematization of the idea of utilizing digital opportunities and a conceptualization of this into the polarity of overexploitation vs. underexploitation of digital opportunities. It does so, empirically informed by a qualitative and diagnostic case study on the digitalization of medical certificates and theoretically informed by affordance theory [START_REF] Gibson | The ecological approach to visual perception[END_REF] and activity theory [START_REF] Kuutti | Activity theory as a potential framework for human-computer interaction research[END_REF][START_REF] Wertsch | Mind as action[END_REF].

Research approach

This presented research is a "slice" of a larger research endeavor on the governance of multi-organizational digital artifacts in public administration. A research team has studied the relations between different policies and the realization and use of digital artifacts. Several qualitative case studies have been conducted. In the first stage of the research, eight case studies were conducted in parallel. In a later stage of research, another case study was performed based on results from the previous empirical studies. The case studies were based on a general research interest in relations and possible tensions between a policy level and the actual artifact level [START_REF] Goldkuhl | From policy to design and effects: A framework for e-government research[END_REF]. The focus was on complex multi-organizational digital artifacts in the public sector [START_REF] Goldkuhl | Governance of shared digital artifacts in the public sector: A multi-dimensional approach[END_REF]. The presented research is based on the last case study. Several purposes guided this specific case study on the digitalization of medical certificates. It aimed at 1) an evaluation of the digitalization of medical certificates (primary target group: those responsible for these digital artifacts), 2) an application and assessment of a multidimensional evaluation approach with digital medical certificates as the evaluation object (target groups: scholars and practitioners interested in methods for evaluation of digital artifacts), and 3) abstracted (case study-based) knowledge on complex multi-organizational digital artifacts in the public sector (target groups: scholars and practitioners interested in policies and the realization of digital artifacts in the public sector). The sliced research presented in this paper is part of the third purpose.

The case study research was conducted through a continual alternation between 1) an empirical and diagnostic inquiry of digital medical certificates and 2) theorizing with qualitative data analysis, reflection, and abstraction [START_REF] Goldkuhl | The research practice of practice research: theorizing and situational inquiry[END_REF][START_REF] Vanwynsberghe | Redefining case study[END_REF]. In the empirical part, we mainly used the following methods for collection/generation of data: Interviewing and workshops with knowledgeable practitioners, document studies, and inspections and explorations of the focused digital artifacts [START_REF] Goldkuhl | The generation of qualitative data in information systems research: the diversity of empirical research methods[END_REF][START_REF] Nielsen | Usability engineering[END_REF]. In these studies of digital artifacts, we acted as potential users and collected empirical data concerning digital functionality, interactivity, and information. Screenshots were generated and also annotated with comments on critical concerns. We used a multi-dimensional evaluation approach that guided an alternating focus on dimensions such as stakeholders, digital work processes, digital functionality, digitalized information, digital interaction, interoperability in digital landscapes, goals and values, and laws and regulations [START_REF] Goldkuhl | Governance of shared digital artifacts in the public sector: A multi-dimensional approach[END_REF]. The generation and analysis of data were initially performed in an inductive manner close to the ideals of grounded theory [START_REF] Corbin | Basics of qualitative research. Techniques and procedures for developing Grounded Theory[END_REF]. We aimed at discovery of new knowledge rather than driven by certain hypotheses. This quest for discovery and novel knowledge comprised an open-minded approach in data generation (in order to see new things) and data analysis (in order to create a new understanding) through interpretation and abstraction leading to new categories [START_REF] Goldkuhl | Grounded theory in information systems research -from themes in IS discourse to possible developments[END_REF].

However, the generation and analysis data were not conducted by the researchers as "blank slates". The evaluation approach with its different dimensions and concepts guided the generation and analysis of data. This means that this type of preunderstanding had an influence on the knowledge development process [START_REF] Goldkuhl | Grounded theory in information systems research -from themes in IS discourse to possible developments[END_REF]. Later in the data analysis and abstraction process, new categories and conjectures emerged. For this presented slice of research, the inquiry question was formulated: In what ways are digital opportunities utilized? The formulation of this inquiry question was based on 1) findings and insights from the case study and 2) our general knowledge interest on the potential influence from policies with an aim to "maximize" the utilization of digital opportunities (see discussion in Section 1). The formulation of this inquiry question was guided by an identified problematic situation in the empirical practice and not by spotting gaps in the literature [START_REF] Corbin | Basics of qualitative research. Techniques and procedures for developing Grounded Theory[END_REF][START_REF] Dewey | Logic: The theory of inquiry[END_REF][START_REF] Van Maanen | The interplay between theory and method[END_REF]. Based on these emergent insights and the formulated inquiry question, the analysis turned from an inductive to an abductive manner [START_REF] Goldkuhl | Adding theoretical grounding to grounded theory -Towards Multi-grounded theory[END_REF][START_REF] Thornberg | Informed grounded theory[END_REF][START_REF] Van Maanen | The interplay between theory and method[END_REF]. Appropriate theoretical assistance was sought for. Through previous acquaintance with affordance theory [START_REF] Goldkuhl | Actability theory meets affordance theory: Clarifying HCI in IT usage situations[END_REF], this theory was found suitable as a theoretical lens for further analysis. Further theorizing was conducted partially as a problematization of the dictum of maximizing the utilization of digital opportunities. "The more -the better" can be challenged. Affordance theory was found useful for this further theorizing. Through a conceptual analysis of affordance theory, a need was found to complement this through the addition of views from activity theory.

3

Theoretical lens: Affordance theory and activity theory

Affordance theory was originally formulated by Gibson [START_REF] Gibson | The ecological approach to visual perception[END_REF]. It is considered as an ecological theory of perception. The main idea is that the environment of humans (and other species) is perceived in terms of what it affords for action. This means that affordances are properties of the environment in relation to actors. They are not just physical properties of things. The difference between affordances and pure physical properties is described by Gibson [11,p 127]. A floor is stand-on-able, walk-on-able and run-over-able when recognizing what it affords. These affordances are of course based on certain physical properties (e.g. the floor being horizontal, flat, extended and rigid). However, affordances should not be seen as subjective or mental constructs as Gibson emphasizes. The affordances are in the external objects -but these properties are relational properties, i.e. they exist in relation to an observer/actor. "These positive and negative affordances are properties of things taken with reference to an observer but not properties of the experiences of the observer" [11, p 137].

Affordance theory has attracted interest in information systems research. This comprises both issues of human-computer interaction [e.g. [START_REF] Goldkuhl | Actability theory meets affordance theory: Clarifying HCI in IT usage situations[END_REF][START_REF] Hartson | Cognitive, physical, sensory, and functional affordances in interaction design[END_REF][START_REF] Hutchby | Conversation and technology. From the Telephone to the Internet[END_REF][START_REF] Mcgrenere | Affordances: Clarifying and evolving a concept[END_REF][START_REF] Norman | The psychology of everyday things[END_REF] and broader IS issues [e.g. [START_REF] Hutchby | Conversation and technology. From the Telephone to the Internet[END_REF][START_REF] Kim | E-government maturity model using the capability maturity model integration[END_REF][START_REF] Leonardi | When flexible routines meet flexible technologies: affordance, constraint, and the imbrication of human and material agencies[END_REF][START_REF] Scott | Institutions and organizations[END_REF]. The general view of affordances in digital technology is that digitalized artifacts have properties that are relational to their users and that these properties provide (=afford) action possibilities to the user. Affordances need to be both informative (visible and understandable) and operational (accessible and executable) to the user; see [START_REF] Goldkuhl | Actability theory meets affordance theory: Clarifying HCI in IT usage situations[END_REF][START_REF] Hartson | Cognitive, physical, sensory, and functional affordances in interaction design[END_REF]. This paper leans more to the HCI tradition [START_REF] Goldkuhl | Actability theory meets affordance theory: Clarifying HCI in IT usage situations[END_REF][START_REF] Hartson | Cognitive, physical, sensory, and functional affordances in interaction design[END_REF][START_REF] Mcgrenere | Affordances: Clarifying and evolving a concept[END_REF] of employment of the affordance notion than the broader IS orientation. This follows from the close empirical investigation of the digital artifacts' functionality and interactivity as mentioned in section 2 above [START_REF] Goldkuhl | The generation of qualitative data in information systems research: the diversity of empirical research methods[END_REF][START_REF] Nielsen | Usability engineering[END_REF].

According to Gibson [START_REF] Gibson | The ecological approach to visual perception[END_REF], there exist also negative affordances. These are properties in the environment that can be seen as aggravating or preventing actions. To consider an affordance as negative can, however, be seen as confusing. This terminological problem has been discussed by [START_REF] Volkoff | Affordance theory and how to use it in IS research[END_REF][START_REF] Zammuto | Information technology and the changing fabric of organization[END_REF]. Volkoff & Strong [42] express this conceptual and terminological issue in the following way: "A different question relates to whether affordances can be both enabling and constraining, or whether affordances are only enabling, and constraints are different." Zammuto et al. [45 p 752] argue for an inclusive notion of affordance covering both positive and constraining functions: "An affordance perspective recognizes how the materiality of an object favors, shapes, or invites, and at the same time constrains, a set of specific uses." A way to dig deeper into this conceptual/terminological controversy is to turn to etymology. The etymological meaning of the word "afford", coming from the Middle English word "aforth", is "to put forth, contribute; further, advance" (Online Etymology). A lexical definition of "further" is "to help the progress of something so that it is more likely to be successful" (MacMillan Dictionary). Based on these etymological and lexical definitions, a "negative affordance" seems to be close to a self-contradiction. Conceptually, there is thus a need for a theoretical complement to affordance theory.

Activity theory can contribute to such distinctions through its concept of mediated action [START_REF] Wertsch | Mind as action[END_REF]. Within this theoretical tradition, Kuutti [START_REF] Kuutti | Activity theory as a potential framework for human-computer interaction research[END_REF] emphasizes that "the tool is at the same time both enabling and limiting". This means that tools (like digital artifacts) have properties that afford/enable actions but also properties that constrain and sometimes prevent actions. All such artifact properties have the function of mediating/directing actions in certain ways. The key theoretical concept of affordance is thus here complemented with the concepts of constraint and prevention. These different concepts are used, and thus illustrated, in the theoretical reasoning on findings from the performed case study (section 5 below).

Case study description: digitalization of medical certificates

The case study covers digital artifacts related to doctors' issuing of medical certificates and the transfer of those certificates to patients, their employers and the Social Insurance Agency (SIA), that manages sickness benefit cases. A medical certificate, issued by a doctor, is needed by citizens/employees to prove a legitimate sickness leave to the employer and to SIA. There exist several related digital artifacts in this digital landscape of medical certificates and sickness management. DigCert is a healthcare system containing digital support for issuing, storage and transfer of certificates. MyCert is a module in the national health portal where each citizen/patient can manage his/her medical certificates. One possibility is to print the certificate for delivery to the employer. There exist several digital artifacts at SIA; one e-service for patients' submission of sickness benefit applications and an internal case handling system for sickness benefits. Before the digitalization, the medical certificates were issued using paper forms. This form was provided by the Social Insurance Agency to healthcare organizations. The doctor handed over the issued medical certificate to the patient who was responsible to distribute it (or copies) to the employer and to SIA. There are still some doctors that use this old form and procedure.

When investigating the digital solution, we found that were three different ways to transfer the digital medical certificate from healthcare to SIA for their case handling. 1) Since there exist restrictive privacy regulations in Sweden, it was not permitted for healthcare to just distribute the medical certificate to SIA. An explicit consent from the patient was needed. If this was given and then recorded by the doctor in DigCert, the issued medical certificate could be transferred digitally to SIA. 2) Another way to transfer the certificate digitally was by the patient through the use of MyCert. After selecting a specific certificate in the web application, the patient can initiate a digital transfer to SIA. 3) The first two weeks of sick leave are paid by the employer. After this period, the patient/employee needs to apply to SIA for sickness benefits. This can be done digitally by the patient through SIA:s e-service. In this application process, the medical certificate can be digitally retrieved from DigCert and attached to the application.

The case handling process of sickness benefits at SIA is substantially facilitated by receiving the medical certificate in a digital format. This was a strong motivating force in the design of digital solutions. Therefore, these three alternative ways of digital transfer were designed and implemented. However, these digital solutions have given dysfunctional effects. These three digital transfer solutions are built on different communication logics. The first two are based on a push-logic. In these situations, the medical certificates are digitally pushed from the healthcare organization to SIA before any sickness benefits application is submitted. If the patient/employee gets well during the first two weeks, there is no need to submit any benefits application to SIA. In these situations, SIA receives medical certificates that have no function for their case handling. However, they cannot just throw them away. According to regulations, SIA must open a case and try to reach the health insured/patient and ask for a sickness benefits application. This is a totally unnecessary administration that costs time and money. The third situation builds on a pull-logic. The digital medical certificate is submitted together with a sickness benefits application.

One important element in the digitalization of medical certificates was the introduction of a decision support in the DigCert's digital service for doctors issuing of certificates. This is a health-insurance decision support containing a repository of medical diagnoses and recommended periods of sick leave for each diagnosis. These standards guide the doctor to select an appropriate sickness leave period. If the doctor issues a period that deviates from the standard period, the doctor is prompted by the digital service to motivate such a deviation.

5

Findings and discussion

Overexploitation vs. underexploitation of digital opportunities

In the analysis of this case, it was discovered that some parts of the digital artifacts could be characterized as overexploitation of digital opportunities, while others could be seen as underexploitation of such opportunities. These categories were generated through a cross-data analysis, which is an analysis tactic of grounded theory [START_REF] Corbin | Basics of qualitative research. Techniques and procedures for developing Grounded Theory[END_REF]. Through a "constant comparison" of different data items and generated categories looking for similarities and differences, new categories can emerge. What is here called overexploited and underexploited digital opportunities are ascribed features of digital artifacts. They are characterized as such in relation to (policy) expectations on digital artifacts. The artifact features were thus seen in relation to pre-conditional policy formulations, such as visions for "world-class" utilization of digital opportunities as expressed in national digital agendas [START_REF]Swedish Government: It i människans tjänst -en digital agenda för Sverige[END_REF][START_REF]För digitalisering i tiden. Slutbetänkande av Digitaliseringskommissionen[END_REF]. However, these characterizations were also made through an assessment of the effects of the artifact features. The identification of dysfunctional effects influenced the way these features were conceived of and thus that they were characterized as a deviation from an appropriate exploitation of digital opportunities. A contextual analysis was thus necessary to formulate these categories of overexploited and underexploited digital opportunities, i.e. looking "backward" to policy pre-conditions and "forward" to effects in the digitalized workpractice.

Overexploitation means that a quest to exploit digital opportunities can sometimes be pushed too far. One such example is the design of three variants of digital transfer processes of the medical certificate from healthcare to the Social Insurance Agency. This means identifying opportunities with digital technologies and then exaggerating the use of such opportunities. Three alternative ways of transfer were designed to ensure that SIA receives the medical certificate in a digital format. As described above (in the case study description, Section 4), these alternative transfer ways had dysfunctional effects.

The case shows several examples of the contrary, i.e. what is here called digital underexploitation. A retained form thinking is one such example. The earlier paper form for medical certificates has heavily influenced the interaction design of a digital certificate form. This has meant a lack of communicative renewal. The digital form for issuing a medical certificate is lacking in precision and clarity (e.g. insufficient explanations, contradictions, unnecessary linguistic variation, work-language imperfections). Another example of such a digital underexploitation is that digital communication has been optimized to one stakeholder/recipient (SIA). There is a lack of adaptation of communication to other recipients (the patient and the employer). This comprises 1) information content not adapted (through information deficiencies and information surpluses) to different recipients and 2) a lack of seamless digital transfer to employers.

The case shows also examples of adequate exploitation of digital opportunities. One such example is the introduction of the health-insurance decision support with standardized sickness leave periods. The designers have here utilized the possibility to embed a digital repository into the issuing service of medical certificates. This decision support/repository can be continually updated with changed health-insurance considerations and it is well integrated into the certificate service with a digital retrieval function that is easy for the doctors to manage.

Affordances, constraints and other pre-conditions for design and use

Digital technology affords generally different opportunities, such as programmability and digitization of information with efficient capture, storage, processing, transfer and presentation of such information [START_REF] Yoo | The new organizing logic of digital innovation: An Agenda for information systems research[END_REF]. These features give affordances for design. However, the design of digital artifacts in workpractices (such as handling of medical certificates) is influenced by many other circumstances. There are digital policies with appeals to more fully exploit digital opportunities. There are also specific needs and different circumstances in the actual workpractice that influence the design (issues concerning healthcare, employment, and health-insurance). The workpractice situation of medical certificates management frames the design of digital artifacts. The main requirements for the digital design are obtained from conceptions of objectives, problems, and work-processes in these workpractices. The substance for the digital design (as values, stakeholder roles, work-language, procedures) emanates from the related practices of healthcare and health-insurance. One important concern in this case (as in most other egov areas) is the regulative background of extant legislation [START_REF] Contini | Assembling law and technology in the public sector: the case of e-justice reforms[END_REF][START_REF] Knackstedt | The relationship of IS and law -the perspective of and implications for IS research[END_REF]. It is said that there exist more than Swedish 70 laws/statutes that have relevance for medical certificates. Digital design is thus a choice of what kind of digital opportunities to utilize [START_REF] Fountain | Building the virtual state. Information technology and institutional change[END_REF].

The design outcome will be an amalgamation of these different affordances, constraints and other pre-conditions (Figure 1). The designed digital artifacts (as a net-worked digital arrangement) with different properties give affordances for use in workpractice contexts. Some of the characteristics of the designed digital artifacts do, however, not provide any desired action possibilities. In this actual case there exist:

1. A surplus of affordances, as three ways of digital transfer of certificates that give dysfunctional effects such as unnecessary excess work. 2. Affordances with embedded constraints, as unclear instructions in the certificate form that entail risks for incomplete or deficient medical certificates. 3. A lack of affordances, as no adaptation to employers that may generate extra work for patients and also intrude patient/employee privacy. 4. Useful affordances, as the use of the health-insurance decision support for guidance to set adequate sick leave periods. A main formulated category, based on this case study, is degree of digital exploitation. This is an attributive construct as being a property class of digital arrangements. The degree of digital exploitation, as described above, varies between overexploited digital opportunity (1), adequately exploited digital opportunity (4), and underexploited digital opportunity [START_REF] Contini | Assembling law and technology in the public sector: the case of e-justice reforms[END_REF][START_REF] Corbin | Basics of qualitative research. Techniques and procedures for developing Grounded Theory[END_REF]. What has been clear through this case study is the necessity to analyze these kinds of phenomena relationally; i.e. both to antecedents and to consequences. The digital arrangement with its properties (affordances, constraints, and lack of affordances) are pre-conditions for digital use in workpractices. They are also "post-conditions"; in this case, results of design practices. Obviously, there are important differences between the separate design practices leading to the different kinds of digital properties. In (1) and ( 4), an exploitive strategy has been applied implying a design where digital opportunities were utilized to create something novel in the practices of medical certificate management. In [START_REF] Berntzen | Benchmarking e-government. A comparative review of three international benchmarking studies[END_REF], the design has given full priority to the objective to have medical certificates in digital format while neglecting other consequences. Three different ways were designed in order to ensure medical The application of the affordance concept is, in this analysis, done through a twostep staging: 1) General characteristics of digital technology give affordances for design. Different digital options of a general character can be utilized in designing and such digital opportunities can be utilized in different ways and degrees. The implemented egov artifacts for use are results of diverse design practices where digital opportunities have been exploited differently. 2) The resulting digital artifacts will have different properties and these properties give affordances but also constraints for use. Digital properties will not only enable actions but they also direct, constrain and prevent different actions following the synthesized view of affordance theory and activity theory (Section 3). Such digital affordances and constraints will thus influence the actions of different users/stakeholders.

The model in Figure 1 is influenced by the policy/design/effect (PDE) model [START_REF] Goldkuhl | From policy to design and effects: A framework for e-government research[END_REF]. The PDE model describes efficacy linkages from policy expectations (P) to the designing activities leading to designed artifacts (D) and further to the use of these artifacts and subsequent effects (E). In the new model (figure 1), an expansion has been made to include other aspects than only a policy influence as in the original model. Policy was already, in the PDE model [START_REF] Goldkuhl | From policy to design and effects: A framework for e-government research[END_REF], given a broad interpretation covering policy statements, values and regulations (as legally codified values). However, in this new and enhanced model other aspects are included as influencing design processes: General properties of digital technology that give affordances for design and the specific subject matter of addressed workpractices that frames the design process. This enhanced model could still be called PDE model, but with another elucidation: "Pre-conditions/Design/Effects".

Related thinking about egov evolution can be found in the Technology Enactment Model [START_REF] Fountain | Building the virtual state. Information technology and institutional change[END_REF] and variants/modifications of this [START_REF] Cordella | Information systems in the public sector: The e-Government enactment framework[END_REF][START_REF] Luna-Reyez | Digital government transformation and internet portals: The co-evolution of technology, organizations, and institutions[END_REF]. The institutional character of 1) governmental activities and 2) the use of egov artifacts is emphasized in these models. This applies also to the enhanced PDE model. There are, however, some important differences that need to be noted. In Technology Enactment Model, there is a differentiation between objective technology and enacted technology. Enacted technology is considered as the, by its users, appropriated digital artifact; i.e. what it is actually used for, following the theoretical views from [START_REF] Orlikowski | The duality of technology: Rethinking the concept of technology in organizations[END_REF]. Objective technology has, unfortunately, fluid meanings in the Technology Enactment Model. In some places, it seems to mean general characteristics of information technology and sometimes an implemented digital artifact as such. In the PDE model, there is an important difference between 1) digital technology with general characteristics giving affordances for digital design and 2) specific digital artifacts. "Technology" is never used to mean specific digital artifacts as can be the case in [START_REF] Fountain | Building the virtual state. Information technology and institutional change[END_REF][START_REF] Orlikowski | The duality of technology: Rethinking the concept of technology in organizations[END_REF]. An implemented digital artifact gives affordances and constraints for use. How these affordances and constraints are utilized, followed and appropriated by a user corresponds to "enacted technology" in the Technology Enactment Model. In the PDE model, institutional elements are not put in one "box". There are different institutional elements in the listed preconditions. "Egov policy" contains normative expectations from policymakers. "Regulations" cover all kinds of laws and statutes that pertain to the addressed workprac-tices. These are two pivotal parts of institutions following [START_REF] Scott | Institutions and organizations[END_REF]. "Workpractice circumstances" include other institutional elements that govern the kinds of workpractices addressed. There will be relational elements (such as stakeholder roles), linguistic elements (concepts and vocabulary), performative elements (established processes and procedures), and also normative elements (specific workpractice values). Such institutional elements may, through design processes, be inscribed in the digital artifacts and thus substantially affect its use and give practice impacts. The digital artifacts will be mediators of the institutional pre-conditions through its use.

Conclusion

This paper has contributed a conceptualization of the utilization of digital opportunities in e-government through the polarity of overexploitation vs. underexploitation. The conceptual development was based on a theoretical lens of affordances and constraints. This has been further theorized through the enhancement of a conceptual model (PDE) of Pre-conditions for design, Designed digital artifacts, and Effects that arise from their uses. Besides these obvious conceptual contributions that could influence further empirical and theoretical studies, the conducted inquiry demonstrates a way to research e-government with the following traits: a qualitative case study with a combination of inductive investigation aiming for discovery, evaluation of findings and use of a synthesized theoretical lens for conceptual development. This proposed case study approach involves also an alternation between three different foci in empirical inquiry, data analysis, and conceptualization: 1) different features of designed and used digital arrangements (i.e. connected digital artifacts), 2) a "backward" analysis revealing the rationale for design and other kinds of pre-conditions for design, and 3) a forward analysis clarifying both functional and dysfunctional effects from the use of digital arrangements. See Figure 1 for illustration; start with the center (1) and move backward to pre-conditions for design (2) and forward to effects from use [START_REF] Corbin | Basics of qualitative research. Techniques and procedures for developing Grounded Theory[END_REF].

Based on this inquiry the following advice can be given to practice: A challenge in this context is to achieve a balanced digital exploitation where you do not overexploit or underexploit the digital opportunities. The dictum should be: Exploit digital opportunities in a balanced way to reach real improvements in workpractices. An evaluation of how digital opportunities are utilized should not stop until an assessment of effects on workpractices and stakeholders is completed.

Fig. 1 .

 1 Fig. 1. Pre-conditions for digital design and digital arrangements as pre-conditions for workpractice use and effects.

Acknowledgments

The empirical and theoretical work presented in this paper has benefited from close cooperation with my research colleague Annie Röstlinger. I am also grateful to informants from the public agencies for providing good empirical access. Parts of this research work has been financially supported by the Swedish Governmental Agency for Innovation Systems (VINNOVA).