Innovative Study

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Government Information Quarterly

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What can open innovation be used for and how does it create value? Keld Pedersen Aarhus University, Department of Management, Fuglesangs Allé 4, 8210 Aarhus, Denmark

A R T I C L E I N F O

Keywords: Open innovation Crowdsourcing Citizen sourcing Value creation

A B S T R A C T

Societies face difficult challenges which require responses that go beyond the innovation capability of most public sector organisations. Open approaches to public sector innovation that exploits digital technologies have been proposed for some years to close this gap, but our knowledge of the use and outcome of using open innovation in this context is limited. This research takes stock of the study and use of these approaches by investigating the purposes for which public sector organisations use open innovation, and how it creates value. The research question is answered through a systematic literature review and an analysis of publicly available data about the open innovation projects referred to in that literature.

The research identifies five different purposes of using open innovation. It also suggests that public sector organisations primarily use open innovation to pursue one specific purpose: innovation in society. When using open innovation for this purpose, public sector organisations attempt to create value by improving citizens' quality of life and the quality of neighbourhoods. They do this primarily by co-specialising IT and other resources in society (e.g. the transportation system) and by using the outcome of this co-specialisation process to change citizen behaviour, capabilities and experiences (e.g. encouraging citizens to use the transportation system more efficiently or making citizens feel more safe when using the transportation system).

This research indicates that open innovation is generally not used to open up public sector organisations or to give citizens more influence in public sector or democratic processes. The research also indicates that open innovation, until now, has primarily been used to solve minor problems, and not large scale wicked problems in society. The research suggests a framework for value creation from open innovation initiatives that pursues innovation in society. This framework might help public sector organisations increase value creation and solve wicked problems using open innovation, and might help researchers to focus future open innovation research on essential knowledge gaps.

1. Introduction

Public sector organisations face many challenges that require in- novative solutions. They have to reduce costs and become more effi- cient and effective (e.g. Janssen, Konopnicki, Snowdon, & Ojo, 2017). They have to improve their relationship with citizens and other stake- holders, for example by becoming more transparent (Schmidthuber & Hilgers, 2018), they have to collaborate with other public sector or- ganisations (Weerakkody & Dhillon, 2008), and they have to deal with difficult challenges in society such as climate change, ageing societies, and increases in chronic diseases (Kankanhalli, Zuiderwijk, & Tayi, 2017). Many of these challenges can be characterised as wicked pro- blems (e.g. Moon, 2018).

At the same time, the conditions for public sector innovation are difficult, both in general (e.g. Bommert, 2010) and in an e-government context (Pedersen, 2016). General challenges such as risk avoidance, conflict, lack of resources (De Vries, Bekkers, & Tummers, 2016) and

more specific e-government-related challenges such as integration problems (Van Veenstra, Klievink, & Janssen, 2011), techno-centric approaches (Weerakkody, Dhillon, Dwivedi, & Currie, 2008) and lack of e-government capabilities (Klievink & Janssen, 2009) make innovation difficult.

This combination of a pressing need for innovation and difficult conditions for innovation has led to a search for new approaches to public sector innovation, both within e-government and more broadly. A great deal of research into the various types of open innovation (e.g. Chesbrough, 2006) used in the public sector has been published in re- cent years. These approaches have been researched as different con- cepts, such as open innovation (e.g. Feller, Finnegan, & Nilsson, 2011), we-government (e.g. Linders, 2012), citizen sourcing (e.g. Hilgers & Ihl, 2010), crowdsourcing (e.g. Lampe, Zube, Lee, Park, & Johnston, 2014), co-creation (e.g. López-de-Ipiña, Emaldi, Aguilera, & Pérez-Velasco, 2016), collaborative innovation (e.g. Bommert, 2010), and open gov- ernment (e.g. Estermann, 2018). As Linders (2012) explained, the many

https://doi.org/10.1016/j.giq.2020.101459 Received 15 May 2019; Received in revised form 10 February 2020; Accepted 10 February 2020

E-mail address: [email protected].

Government Information Quarterly 37 (2020) 101459

Available online 18 February 2020 0740-624X/ © 2020 Elsevier Inc. All rights reserved.

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competing labels for this phenomenon and resulting conceptual con- fusion is problematic, because it makes it difficult to build upon the work of other researchers. In this article, only the “open innovation” concept will be used for practical reasons, even though we are including contributions using, for example, the “citizen sourcing” concept. The definition of open innovation described in Section 2 has been used as the criteria for deciding whether a specific approach can be classified as an open innovation approach. Although they differ, the essence of these approaches to innovation involves opening up public sector innovative processes and exploiting what Bommert (2010) labelled “innovative assets” that are external to public sector organisations, for example, knowledge possessed by citizens, private sector organisations, non- profit organisations, and universities.

One of the key reasons for this openness and exploitation of external innovative assets, emphasised by research, is that many of the pre- viously mentioned challenges are too difficult for a single public sector organisation, or the public sector alone, to solve (Sørensen & Torfing, 2011). There has also been political pressure regarding open innovation in some countries, such as the Obama administration's Open Govern- ment initiative in the USA (Lee, Hwang, & Choi, 2012), and a belief that open innovation might make public sector organisations “look cool” (Nam, 2012).

These approaches to innovation are especially relevant in an e- government context, because open innovation processes themselves are supported by IT (Androutsopoulou, Karacapilidis, Loukis, & Charalabidis, 2017), and in many cases, the outcome of the processes includes IT-supported solutions, such as in some of the cases described by Feller et al. (2011).

Even though open innovation clearly seems relevant, and even though significant research resources have been invested in the ap- proach, we know little about the actual use or outcome of the approach. Research into open innovation has primarily focused on how to deal with external innovative assets, for example how to motivate citizens to participate (Brabham, 2012), and how to implement a private sector approach like open innovation in public sector organisations (Gascó, 2017; Kornberger, Meyer, Brandtner, & Höllerer, 2017). Little research, such as the research of Mergel (2015), focuses on how open innovation is actually used in the context of e-government, the actual outcome, or how this outcome is achieved. Observation indicates that open in- novation processes are used by some public sector organisations without any intention of using the input they receive from participating citizens (e.g. Kornberger et al., 2017; Lodge & Wegrich, 2015; Mergel, 2015; Royo & Yetano, 2015). The research here attempts to increase our understanding of the actual use of open innovation in the context of e- government by investigating the following research question:

Why do public sector organisations use open innovation and how does it create value?

Answering this question serves two purposes. It is used to suggest a framework for value creation from open innovation initiatives that supports practitioners when designing such initiatives. Secondly, it might help focus future research into the purposes that are pursued by practitioners and the issues that matter most for value creation when using open innovation.

Our knowledge about open innovation in this context is to a large extent based on case studies (Kankanhalli et al., 2017). The research here uses the literature review approach to consolidate the findings across previous articles and the specific open innovation projects to which these articles – directly or indirectly – refer.

2. Defining the key concepts

2.1. Open innovation

Open innovation originates from the private sector where it is de- fined as a model for the management of innovation in which organi- sations open up their innovation processes and combine internally and

externally developed ideas and technologies to create value (Chesbrough, 2006). There are three different kinds of open innovation processes in the private sector perception of open innovation (Gassmann & Enkel, 2004). The outside-in process expands the orga- nisation's knowledge base through the integration of external resources from other organisations and customers into innovative processes. In a public sector context, this can be exemplified by public sector organi- sations collaborating with citizens and companies in smart city projects or by involving citizens in policy development through crowdsourcing. The inside-out process focuses on placing some of the organisation's assets outside its own walls to generate innovation in collaboration with other organisations. In a public sector context, this can be exemplified by open data projects publishing data to be used and exploited by ci- tizens and companies. The coupled process combines the outside-in and inside-out processes. Theoretically, open innovation has been perceived and researched as a way of increasing an organisation's absorptive and dynamic capabilities (e.g. Lichtenthaler & Lichtenthaler, 2009), which becomes increasingly important for responding to fast paced changes and new challenges in societies.

2.2. Value

The concept of value in an e-government context is multifaceted. Here, we will look at value from two different perspectives: value in terms of a public sector organisation's professionalism, efficiency, ser- vice and ability to engage citizens (Rose, Persson, Heeager, & Irani, 2015), and value in terms of the kind of problems, for example wicked problems (e.g. Sørensen & Torfing, 2011), that can be solved using open innovation.

According to Rose et al. (2015), “professionalism” is concerned with “providing an independent, robust and consistent administration” and fo- cuses on values such as accountability. “Efficiency” is concerned with “providing lean and efficient administration” and focuses on values such as productivity and cost reduction. “Service” is concerned with “max- imising the utility of government to civil society by providing services directed towards the public good” and focuses on values such as citizen centricity and service quality. “Engagement” is concerned with “engaging with civil society to facilitate policy development in accordance with liberal democratic principles” and focuses on values such as democracy, deliberation and participation. Open innovation provides an alternative approach to the creation of these values, for example during policy development (e.g. Janssen et al., 2017; Liu, 2017; Loukis, 2018; Malhotra, Majchrzak, & Niemiec, 2017) and service development (e.g. Tate, Bongiovanni, Kowalkiewicz, & Townson, 2018; Vicini, Bellini, & Sanna, 2012).

2.3. Value creation

While research within information systems has provided several business value models (e.g. Dedrick, Gurbaxani, & Kraemer, 2003; Dehning & Richardson, 2002; Melville, Kraemer, & Gurbaxani, 2004; Schryen, 2013) that focus on value creation based on the use of IT in private sector organisations, we do not have similar models within e- government. There are major differences regarding values and value creation between public and private sector organisations. Schryen (2013) focuses on the values market and accounting performance, while Rose et al. (2015), as described above, emphasise quite different values. Value creation differs; for example, private sector organisations are concerned with how to create value that can be protected in order to create a sustainable competitive advantage (e.g. Piccoli & Ives, 2005), which is less relevant for public sector organisations. Value creation is in this article, however, based on Schryen (2013), perceived as a process through which IT investments, such as the development of a new app, and non-IT investments, such as organisational change, are combined in a co-specialisation process (e.g. Teece, 2007) to change one or more objects, such as an organisational process or citizen be- haviour. The purpose of the change is to affect the previously described

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public values, and to solve problems that are important for society. In open innovation, the key element for value creation is that solutions rely not only on internal knowledge, but also on knowledge from ex- ternal innovative assets. The literature emphasises three kinds of ex- ternal knowledge: expert knowledge, for example knowledge about a new technology (Liu, 2017), situated knowledge, for example knowl- edge about specific citizen needs in a specific neighbourhood (Liu, 2017), and “the wisdom of the crowd” in terms of the new creative in- sights, ideas and solutions that might emerge when different kinds of knowledge are combined (e.g. Brabham, 2009). Contextual factors, such as some of the conditions for innovation described in the in- troduction, and lag effects, have an impact on value creation, making value creation more or less difficult and taking more or less time. Our understanding is incomplete (Schryen, 2013), but Pedersen (2018) provides an overview of some of the major contextual factors related to e-government. Lag effects in terms of delayed value creation might be caused, for example, by implementation problems and learning and adjustments taking considerable time when introducing new technol- ogies (Schryen, 2013). Lag effects during open innovation are especially important to investigate, because one of the reasons for using open innovation is the previously mentioned need to enable public sector organisations to innovate faster and address fast changing challenges in society.

3. Research method

The research question is answered via a systematic literature review (Webster & Watson, 2002) of the public sector open innovation litera- ture and on document analysis (Bowen, 2009) of publicly available descriptions of the specific open innovation projects directly or in- directly mentioned in the articles identified in the literature review. The research question could be investigated using just one of the two data sources, but using both sources has some advantages. Combining the two sources increases the validity of the findings and leads to ob- servations about differences between the uses of open innovation as described in the literature and how it seems to be used in practice.

3.1. Identifying the open innovation literature

The literature review is based on Webster and Watson's (2002) methodology for systematic literature reviews. Research articles were identified through four different searches: a pilot search, a primary search, a forward search and a backward search.

The pilot search was primarily used to define the search criteria to be used in the primary search, and to determine where to search for research articles. This search was repeated many times using different search criteria and sources until a reliable search strategy emerged. The starting point was the “open innovation” concept, and the starting source was EGRL core journals and conferences. It quickly became obvious that the “open innovation” concept had to be supplemented with many different concepts used in the same or similar approaches to innovation (we-government, citizen sourcing, crowdsourcing, co-crea- tion, collaborative innovation and open government) due to the many competing concepts (Linders, 2012). A few examples can illustrate the complexity. The article by Mergel and Desouza (2013) uses the concept “open innovation”, and studies crowdsourcing initiatives, but perceives (as most research does) crowdsourcing as a specific approach to out- side-in open innovation. The initiative that Mergel and Desouza study is described as being a part of the US government's open government program. Other articles use the concept “citizen sourcing” as a specific variant of crowdsourcing (e.g. Hilgers & Ihl, 2010).

The pilot search also demonstrated that the source had to be much broader, and Web of Science was subsequently used to identify articles, because public sector open innovation articles are published outside the traditional e-government literature, for example in the public admin- istration literature and the innovation literature. The open innovation

related concepts were combined with public sector concepts (e-gov- ernment, public administration, public sector) to delimit the articles to the public sector use of open innovation.

The primary search contains research articles to the end of 2018. The search and filtering process took place from April 2018 to January 2019. The primary search using the previously described concepts in Web of Science resulted in 211 research articles. The search string used in Web of Science was TS = (“e-government” OR “egovernment” OR “public administration” OR “public sector”) AND TS = (“citizen sour- cing” OR “citizen-sourcing” OR “open government” OR “open innova- tion” OR “crowdsourcing” OR “collaborative innovation” OR “co- creation” OR “we-government”). Only English language articles were included. The research articles were subsequently filtered using a manual process based on title and abstract. The criteria below were used during this manual process. The articles should:

• Focus on open innovation using one of the concepts from the search string such as crowdsourcing. • Focus on the use of IT as a part of the innovative solution, for ex- ample a new innovative app that supports specific citizen activities or as a tool that supports the innovation process, for example a new web solution that supports citizens in providing new innovative ideas that could improve public sector services. • Focus on the use of open innovation in a public sector context. • Focus on issues relevant to the research question – the purpose of open innovation and value creation.

Articles with a strong technical focus or articles that only focused on open data but not the innovation process were excluded.

This manual filtering process resulted in 73 relevant research arti- cles. A backward search based on the references in these articles re- sulted in 21 relevant articles, and a forward search (based on Google Scholar) resulted in an additional 17 relevant articles. The forward and backward search minimised the risk of ignoring major contributions due to the previously mentioned conceptual confusion and resulting lack of relevant concepts in the original search string. Significant con- tributions would most likely be referenced from the 73 articles or re- ference the 73 articles.

3.2. Identifying open innovation projects

Identifying and analysing the projects took place from May 2018 to August 2019. The projects were identified directly or indirectly through the identified articles, and further information was included by col- lecting data from websites describing the projects if possible. Some open innovation projects are described directly in the research articles. For example, Feller et al. (2011) briefly describe eight open innovation projects taking place in Sweden. One of these projects is concerned with creating a web portal for elderly citizens. Using Google identified fur- ther information about this project. In other cases, open innovation projects were identified indirectly through the articles. For example, the research article by Schmidthuber and Hilgers (2018) mentions “Digital Agenda Vienna” from the “Smart city Wien” initiative, which led to information about open innovation projects in Vienna based on the website describing the projects. In the same way, Mergel's research (e.g. 2018) based on Challenge.gov led to the identification of US projects from the Challenge.gov website. In this case, only projects from 2017 were included, based on an assumption that these projects are re- presentative of the projects on Challenge.gov. This process resulted in 289 projects. The data was then evaluated, and several projects were excluded because too little data was available, resulting in a dataset of 261 projects.

3.3. Analysing open innovation literature and projects

The same coding scheme (see Table 1) was used to analyse the open

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innovation literature and data about open innovation projects. There was no expectation that we would find data about all concepts in both datasets; for example, it was unlikely that we would find data about the impact of contextual factors or lag effects in the descriptions of the open innovation projects. However, to the extent that data about the same phenomenon existed in both datasets, the data should be coded using the same concepts.

The initial codes were based on the research question and the concepts defined in Section 2. The two most general codes, “purpose” and “value creation”, reflect the two parts of the research question. “Purpose” was used to code data that describes why public sector or- ganisations use open innovation, and “value creation” was used to code data that describes how value is created from these projects.

“Purpose” was specified in more detail using the two codes “object of change” and “value” as defined in Section 2 and summarised in Table 1. In this way, purpose is perceived as an intention to change some types of objects; for example, an organisational process or service, to create some kind of value related to the four categories of values described in Section 2 and solve some kind of problem. In a similar way, “value creation” was specified and coded in more detail using the second level codes “IT investments” etc. also described in Section 2 and summarised in Table 1.

The research articles were coded and analysed through an iterative process guided by the coding scheme described in Table 1. In the subsequent iterations, additional and more detailed codes emerged (see Table 3, Section 4).

The open innovation projects were analysed by copying data about the projects into a spreadsheet, and then coding the data by placing it in the right columns, matching the coding scheme described in Table 1 and the codes that emerged during the analysis of the research articles (see Table 3, Section 4).

The analysis of the projects was also an iterative process, and more codes emerged during the process (see Tables 5, 6, 8 and 9, Section 5). As more detailed codes were identified during the analysis, for example codes describing the “object of change” in more detail, data was placed into specific columns for the purpose in the spreadsheet.

The descriptions of these projects generally suffer from the same problem as the majority of research articles: with few exceptions, they do not describe the actual outcome in terms of value created. By ana- lysing data about the projects, we can get indications of the purpose of the projects, and how the practitioners behind the projects describe how the projects are supposed to create value. The obvious weaknesses with this data is that we do not know if the project descriptions reflect the real purpose, for example public sector organisations might initiate projects to “look cool” as described by Nam (2012) but be reluctant to use the outcome (e.g. Lodge & Wegrich, 2015), and we do not know the degree to which the identified projects are representative. Most im- portantly, we do not know the degree to which value actually was created. However, we do use data from the same sample of projects that, directly or indirectly, are referred to by the research articles.

Table 2 summarises key data about the identified projects. As can be seen in Table 2, most of the projects in the sample are

from the USA, and most projects are initiated at a local government level.

4. Results: the open innovation literature

4.1. The purpose of open innovation

To answer the first part of the research question – why do public sector organisations use open innovation – we will start with an analysis of the different kinds of purposes as presented by the literature. The identified articles were coded initially using the concepts “purpose”, “object of change” and “value”, leading to the five different purposes listed in Table 3. These purposes were subsequently added to the coding scheme in Table 1 and used during the analysis of the open innovation projects. Values were categorised using the categories defined by Rose et al. (2015) as described in Section 3. The perceptions of the kinds of problems that open innovation might be used to solve are presented at the end of this section.

The purposes listed in Table 3 only reflect the public sector purposes as described by the literature. External innovative assets might be in- volved in open innovation for other purposes. For example, private sector companies might use open innovation projects as a testbed for future technologies (Ferraris, Santoro, & Papa, 2018), and citizens might use open innovation projects as a way of advancing their careers (Brabham, 2012).

When analysing the literature, two quite different types of changes to the “objects of change” emerged based on two different uses of ex- ternal innovative assets. These types can be categorised using the business model concept as introduced in this context by Feller et al. (2011). At the one extreme, external innovative assets, typically citizens or experts, are used temporarily, for example to develop a new service or IT system. When the innovation has taken place, it is difficult to differentiate the service or IT system from other services or IT systems developed using methods that are more traditional. This is innovation of “objects of change”, that optimise within the current business model: a public sector organisation becomes, for example, more efficient or transparent, but is not fundamentally changed. The other extreme is innovation of “objects of change” that radically changes the current business model. The typical business model change is that external assets are not used only temporarily for the innovation of, for example, services, but also on a more permanent basis as resources during the actual production of service.

The five different purposes of using open innovation are described in detail in the remaining part of this section.

Open innovation can be used to improve democracy as we know it today by increasing transparency (Liu, 2017; Mergel, 2015; Mergel & Desouza, 2013; Schmidthuber & Hilgers, 2018; Baka, 2017; Martins., de Souza B., & de Souza W., 2015; Janssen et al., 2017; Brabham, 2012),

Table 1 Coding scheme.

First level codes Second level codes

Purpose: Used initially to code data related to the first part of the research – why public sector organisations use open innovation.

Objects of change: The objects that are to be changed by the use of open innovation. Value: The kind of value that should be obtained by changing the objects and the kind of problems that can be solved by using open innovation.

Value creation: Used initially to code data related to the second part of the research question – how open innovation creates value.

IT investments: The type of IT systems, which, in combination with the non-IT investments, are used to achieve the desired change and create value. Non-IT investments: The investments in organisational and other kinds of change, such as changes in citizen behaviour that are combined with the IT investments. External innovative assets: The kind of innovative assets used as part of open innovation (e.g. citizens). Contextual factors: Factors that impact value creation during open innovation. Lag effects: Factors that have an impact on the duration of the period from when an investment in open innovation takes place and value is created.

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increasing accountability (Brabham, 2012; Janssen et al., 2017; Janssen, Charalabidis, & Zuiderwijk, 2012;Liu, 2017 ; Schmidthuber & Hilgers, 2018), and by decreasing corruption (Schmidthuber & Hilgers, 2018). Open innovation can also be used for more comprehensive changes of democracy by improving the political decision-making process (Hilgers & Ihl, 2010), including citizens in policy innovation (Janssen et al., 2017; Liu, 2017; Loukis, 2018; Malhotra et al., 2017), including citizens in regulatory reviews (Mergel, Bretschneider, Louis, Smith et al., 2014), and ultimately citizens might vote for new reg- ulations using a crowd sourcing process (Mergel et al., 2014).

The innovation of public sector organisations involves changes to the organisational output in terms of services and products (e.g. Linders, 2012; Mergel & Desouza, 2013; Tate et al., 2018; Vicini et al., 2012), the processes used to produce and deliver the outcome (e.g. Schmidthuber & Hilgers, 2018; You, Motta, Liu, & Ma, 2016), the technology that supports the processes (e.g. Fosltad, 2008; Mergel et al., 2014), employee capabilities (e.g. Davis, Richard, & Keeton, 2015; Feller et al., 2011), and organisational culture and structure (e.g. Davis et al., 2015; Feller et al., 2011; Linders, 2012). These subcategories are all related, and in many cases, technological innovation is a significant component that enables other kinds of innovation. The innovative purposes are concerned with overcoming economic challenges (Linders, 2012; Schmidthuber & Hilgers, 2018; Thapa, Niehaves, Seidel, & Plattfaut, 2015), improving operational performance (Janssen et al., 2017), decision-making (Hilgers & Ihl, 2010; Liu, 2017), and innovative performance (Gascó, 2017; Thapa et al., 2015), improving sensing capabilities (Liu, 2017), and increasing the knowledge about citizens' perception of service quality (Linders, 2012; Mergel & Desouza, 2013). This could ultimately improve the conditions and capacity for the de- livery of public benefits that meet the growing demands of citizens, as emphasised in some research (Moon, 2018; Tate et al., 2018; Thapa et al., 2015), and in general make public sector organisations more responsive (Liu, 2017; Schmidthuber & Hilgers, 2018), user-centric, proactive, and automated (Liu, 2017). While the changes mentioned

above might largely be accomplished within current business models, some articles (e.g. Feller et al., 2011; Linders, 2012) describe how the use of open innovation might transform entire organisations, including their business models. In a similar way, Moon (2018) suggests that “traditional government-dominated public-service system is no longer effec- tive and needs to be replaced with a new alternative design”.

Innovation of the relationship between public sector organisations is only modestly dealt with by the reviewed open innovation literature. Feller et al. (2011) have described some cases where public sector or- ganisations innovate together and create shared resources and services. Bartlett (2017) mentions the same phenomenon. Dias and Escoval (2012) have researched open innovation and collaboration between hospitals. Compared to the obvious possibilities for public sector or- ganisations to learn and innovate together, however, and the attention this issue has been given in the e- and t-government literature, for ex- ample to implement one-stop-shopping, there are surprisingly few re- search articles about the use of open innovation for this purpose.

Innovation of the relationship between public sector organisations, citizens and other stakeholders focuses on the way that external sta- keholders and public sector organisations collaborate, the way they understand and perceive each other, and the way power and work is distributed between them. Many articles are concerned with how to increase the level of public participation and engagement (Brabham, 2012; Hilgers & Ihl, 2010; Lampe et al., 2014; Mergel, 2015; Tate et al., 2018, Linders, 2012). Some articles explain that open innovation is used for branding purposes, in the sense that it, for example, makes government look more open and “cool” (Nam, 2012; Ojasalo & Kauppinen, 2016; Schmidthuber & Hilgers, 2018), and in some cases the process therefore matters more than innovative outcomes (Gascó, 2017). Other articles present open innovation as a way of increasing citizen trust in government (e.g. Janssen et al., 2017; Kankanhalli et al., 2017; Schmidthuber & Hilgers, 2018), citizen perceptions of govern- ment legitimacy (Liu, 2017; Schmidthuber & Hilgers, 2018), and citizen perceptions of governmental fairness (Schmidthuber & Hilgers, 2018).

Table 2 Overview of the projects.

The projects

Project nationality USA 57%, Austria 15%, Spain 8%, Finland 5%, UK 4%, Australia 2%, Sweden 2%, Italy 2%, international projects 1%, and less than 1% from these countries: Canada, China, Denmark, France, Germany, the Netherlands, New Zeeland, Singapore, South Africa, and South Korea.

Project initiated by Local government organisations (cities or municipalities) 65%, national government organisations 34%, other organisations 1%.

Table 3 Purposes – the literature.

Purpose Object of change and values

Innovation of democracy Objects of change: The political decision-making processes and democracy in general. Values: The identified values belong to the “engagement” and “professionalism” categories. For example, citizen engagement, transparency, and accountability.

Innovation of public sector organisations Objects of change: The organisational output in terms of services and products, the processes used to produce and deliver the outcome, the technology that supports the processes, employee capabilities, and organisational culture and structure. Values: The identified values belong to the “efficiency” and “service” categories. For example, operational performance and responsiveness.

Innovation of the relationship between public sector organisations Objects of change: The relationship between public sector organisations. Values: No solid findings due to the limited number of articles.

Innovation of the relationship between public sector organisations, citizens and other stakeholders

Objects of change: The way that external stakeholders and public sector organisations collaborate, the way they understand and perceive each other, and the way power and work is distributed between them. Values: The values are predominantly related to “engagement”, but also to “service” and “efficiency” in the way that some articles advocate for new relationships between government and citizens where citizens provide some of the services previously delivered by government.

Innovation in society Objects of change: Citizens, neighbourhoods and regions. Values: The values are difficult to categorise using Rose et al. (2015). They are, for example, related to citizen health, the quality of life in specific neighbourhoods or the innovation capabilities in a region. The values could be perceived as indirectly linked to “service” and “efficiency”. For example, trying to improve citizen behaviour regarding health could be perceived as a service that might have an impact on “efficiency” by lowering future healthcare costs.

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This kind of innovation is also used to educate the public about public sector problems (Mergel & Desouza, 2013) and to create recognition of the contribution from services provided by communities, individuals, and public organisations themselves (Mergel & Desouza, 2013). Finally, some articles emphasise citizen empowerment (Liu, 2017) and the importance of giving citizens more “customer voice” (Hilgers & Ihl, 2010). In this way, many articles generally emphasise how open in- novation might strengthen the relationship between public sector or- ganisations and the public (e.g. Sandoval-Almazan, Gil-Garcia, & Valle- Cruz, 2017; Schmidthuber & Hilgers, 2018). Some research describes more radical changes to the relationship. Feller et al. (2011) describes business models based on new and different relationships between public sector organisations and citizens, and other external stake- holders. Linders (2012) describes the emergence of “a new kind of social contract (Long, 2002) in which society places greater trust in – and em- powers – the public to play a far more active role in the functioning of their government. In this new arrangement, government will continue to provide the rules, platforms, and access while citizens and communities take on more responsibility in exchange for a greater say”.

Innovation in society focuses on solving issues that are beyond the control of public sector organisations (Lee et al. 2012). The objects of change are citizens, neighbourhoods, and regions. At the level of in- dividual citizens, there are attempts to improve citizen capabilities (e.g. promoting excellence in technology) (Liu, 2017; Mergel, 2015), at- tempts to change citizen behaviour (e.g. towards more healthy beha- viours) (Mergel & Desouza, 2013) and attempts to raise awareness, mobilise and create commitment among citizens about critical issues in society (Martins, de Souza Bermejo, & de Souza, 2015; Mergel & Desouza, 2013). At the next level, public sector organisations might attempt to change neighbourhoods and improve the quality of life in various ways (Gascó, 2017; Juujärvi & Lund, 2016; Konsti-Laakso, 2017), for example by involving citizens in urban planning (Haltofova, 2018; Pánek, 2018). Some articles emphasise making cities more in- clusive (Aguilera, Peña, Belmonte, & López-de-Ipiña, 2017) and solve problems in municipalities (Royo & Yetano, 2015). At the highest level, the attempts might focus on improving regions by developing compe- titive regional ecosystems (Liu, 2017; Mergel, 2015), on creating a fa- vourable innovative climate (Lee et al., 2012) and strengthening the regional economy and innovativeness (Bakici, Almirall, & Wareham, 2013), or on dealing with societal and environmental challenges (Martins et al., 2015; Schuurman & Tõnurist, 2016; Thapa et al., 2015). While citizens might experience some of these innovations as radical, they do not necessarily imply radical changes to public sector business models.

There are two extreme expectations regarding the kind of problems that can be solved with open innovation: solving wicked problems or solving minor problems.

Many research articles emphasise that open innovation is necessary for solving wicked problems (e.g. Bommert, 2010; Gascó, 2017; Juujärvi & Lund, 2016; Liu, 2017; Malhotra et al., 2017; Sandoval- Almazan et al., 2017; Thapa et al., 2015; Wass & Vimarlund, 2016). The primary argument is that these problems are so complicated that they cannot be solved by isolated public sector organisations, and that they

require collaboration from citizens, private sector organisations and other stakeholders. It has, however, not been possible to identify re- search articles that have studied how large-scale wicked problems (e.g. ageing society, chronic deceases or climate change) have actually been solved using these new forms of innovation as part of this review.

Fewer research articles, such as those by Mergel et al. (e.g. 2014) studying the use of Challenge.gov in USA, have more modest expecta- tions about the outcome of these kinds of open innovation. The primary argument is that “the potential role for government organizations and non- elected public managers to produce innovative goods and services is sig- nificantly constrained by the role of political actors and processes in a de- mocracy” (Mergel, 2015). Mergel (2015) explains that radical innova- tions are unlikely to emerge due to the nature of public sector organisations, and that innovations will most likely occur at the mar- gins, for example in terms of improving public sector service delivery. Liu (2017) questions (based on other sources) the use of crowdsourcing as a way of fostering innovation, because crowdsourcing participants spend little time and have short attention spans, even though the evo- lution of innovative ideas takes time. The interaction and collaboration between participants is often limited, which also limits innovation. It has only been possible to find a few studies of the actual implementa- tion of innovations and the resulting outcome in terms of value, and they indicate that there is a gap between the high hopes and the actual results. Lodge and Wegrich (2015), for example, studied the “red tape challenge” that was supposed to reduce red tape in the British govern- ment, and found the results disappointing. The findings presented by Kornberger et al. (2017) also indicate a modest outcome from open innovation. One of the public servants interviewed by Kornberger et al. (2017) characterised open innovation as “calling into the woods and awaiting what butterflies come back”, implying that the approach could only be used “where quality standards are low or services are only playful supplements to a basic offer provided by the city”. Other case studies (e.g. Baka, 2017; Konsti-Laakso, 2017; Sandoval-Almazan et al., 2017; Zhang, Zhao, Zhang, Meng, & Tan, 2017) provide examples of value creation for citizens within smaller communities, but not value creation in terms of solving large wicked problems.

4.2. Value creation from open innovation

Now we will look at the second part of the research question – how these projects create value. The first step in the analysis was to code the articles using the concept “value creation” to identify findings from the articles that were related to value creation. In the next step, the second level codes described in Table 1 were used. The findings are sum- marised in Table 4.

The IT systems dealt with in the literature are predominantly sys- tems that support the open innovation process and not IT systems (such as the open platform studied by Baka (2017)) as the outcome of open innovation processes. Technological development makes it easier to exploit external knowledge by expanding the search for knowledge from being entirely internal or local, to include distant innovative assets (Prpić, Taeihagh, & Melton, 2015), and this is examined by many ar- ticles that focus on how to include primarily citizens in innovative

Table 4 Value creation – the literature.

Concept Finding

IT investments The research predominantly focuses on systems that support open innovation processes, not on systems that result from using open innovation processes. Non-IT investments The research predominantly focuses on the non-IT investments needed to implement and use open innovation in public sector organisations, not on non-IT

investments needed to implement and create value from IT systems that are the outcome of open innovation projects. Innovative assets The e-government and public administration literature focuses primarily on local citizens as the innovative assets, while the smart city and more general

innovation literature also focuses on companies, universities etc. as external innovative assets. Contextual factors There are three categories: factors related to the external innovative assets, factors related to the objects of change, and factors related to the conditions for

innovation. Lag effects There is no research into lag effects when using open innovation.

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processes using IT. Research focuses on, for example, IT systems that enable citizens to take part in the IT development of new services, ty- pically new apps based on open data (e.g. López-de-Ipiña et al., 2016; Veeckman & van der Graaf, 2015). Many articles focus on the use of social media (e.g. Díaz-Díaz & Pérez-González, 2016; Konsti-Laakso, 2017; Loukis, Charalabidis, & Androutsopoulou, 2017; Picazo-Vela, Fernandez-Haddad, & Luna-Reyes, 2016; Spiliotopoulou, Charalabidis, Loukis, & Diamantopoulou, 2014; Wirtz, Daiser, & Binkowska, 2018; Zhang et al., 2017) to support open innovation. More specialised IT systems that support the inclusion of citizens in innovation of policies and plans (e.g. Gagliardi et al., 2017; Haltofova, 2018; Liu, 2017; Malhotra et al., 2017; Minner, Holleran, Roberts, & Conrad, 2015; Panagiotopoulos, Bowen, & Brooker, 2017) have also received much attention. Further, there is research into open innovation platforms such as Challenge.gov (Mergel, 2015), and how to support the inter- action between citizens when engaging in debates in forums (Lampe et al., 2014). Little research about platforms includes private sector organisations, such as the research by Klievink, Bharosa, Tan et al. (2016). Androutsopoulou et al. (2017) provide an overview of the IT systems that can be applied during the various phases in an open in- novation project.

The non-IT investments emphasised by the literature are primarily investments related to implementing and using open innovation in public sector organisations, not the investments needed to implement IT systems resulting from open innovation processes. The investments needed to implement open innovation seem substantial. For example, Feller et al. (2011) describe fundamental changes to public sector business models, capabilities, organisational structures, and processes as a part of implementing open innovation, and Mergel (2018) has described the changes needed and the challenges that had to be over- come in order to implement and use Challenge.gov. Other sources emphasise the need for new types of organisational units to facilitate open innovation processes such as living labs (e.g. Gascó, 2017) and public open innovation intermediaries (e.g. Bakici et al., 2013).

The literature can be roughly divided into two categories regarding the exploitation of external innovative assets; the public administration and e-government literature (e.g. Liu, 2017) that focuses on citizens as the primary external innovative asset (often through the use of crowdsourcing) and the smart city innovation literature (e.g. Aguilera et al., 2017) that also focuses on the collaboration with private sector companies and other organisations.

When trying to identify the contextual factors in the reviewed lit- erature that probably affect value creation in open innovation projects, three categories emerge:

• Factors related to the external innovative assets. • Factors related to the objects of change. • Factors related to the conditions for innovation. Factors related to the external innovative assets involve, for ex-

ample, defining the problems that should be solved (e.g. Mergel, 2015), attracting (e.g. Loukis, 2018; Royo & Yetano, 2015; Thapa et al., 2015; You et al., 2016) and managing (e.g. Almirall, Lee, & Majchrzak, 2014) the crowd that takes part in the innovative process, how to establish collaboration between private and public organisations (Ferraris et al., 2018), and how to evaluate initiatives (Paskaleva & Cooper, 2018). Key issues include how to ensure both representativeness (Liu, 2017; Seltzer & Mahmoudi, 2013; Veeckman & van der Graaf, 2015) and diversity (Royo & Yetano, 2015; Tate et al., 2018) in the crowd, and how to filter, integrate, and validate knowledge from the crowd (e.g. Schmidthuber & Hilgers, 2018). These factors demonstrate that a key concern in value creation through open innovation must be to attract the relevant ex- ternal innovative assets for the problem to be solved, being able to facilitate collaboration (e.g. overcoming cognitive distance and dif- ferent interests) and creativity among participants, and to create new knowledge that might solve the problems. An example of using a crowd

wrongly is the situation described by Moon (2018), where the use of ordinary citizens as programmers often leads to low quality programs that are of little value to other citizens.

Identified factors related to the objects of change are, for example, related to organisational change (e.g. Dias & Escoval, 2012; Wass & Vimarlund, 2016), public sector reluctance about the relevance of the outcome of open innovation (e.g. Kornberger et al., 2017; Thapa et al., 2015) and low or no use of the outcome (e.g. Gascó, 2017; Mergel, 2015).

Factors related to the conditions of innovation include, for example, the availability of resources (Gascó, 2017; Seltzer & Mahmoudi, 2013), the availability of open data (Kankanhalli et al., 2017) and data pro- tection issues (Wass & Vimarlund, 2016), organisational and institu- tional barriers (e.g. Mergel, 2018; Sandoval-Almazan et al., 2017), and constraints or support from the political actors and processes in a de- mocracy (e.g. Mergel, 2018; Mergel & Desouza, 2013; Tate et al., 2018).

There is significantly more research about factors related to the external innovative assets than the two other categories.

The analysis of the literature did not identify any research focusing on lag effects. Having some indication of whether open innovation makes public sector organisations more responsive and dynamic due to faster innovation processes compared to the use of traditional closed innovation could be beneficial.

5. Results: the open innovation projects

5.1. The purpose of open innovation

In this section, we will continue our attempts to answer the research question, but now we will do so by studying public sector open in- novation projects. We will start by looking at the first part of the re- search question – why do public sector organisations use open innovation – using the five categories of innovation described in Section 4 (see Table 3) to code and categorise the projects by both purpose and the distinction between optimising within and radically changing the cur- rent business model. Except for the examples mentioned by Feller et al. (2011), we have found no projects that radically change public sector business models.

Few projects (6% in the dataset) explicitly focus on the innovation of democracy. There are projects that provide forums for political dis- cussions, projects that provide opportunities for monitoring democratic elections (e.g. a project that develops software for reporting and in- forming citizens about voting incidents in Philadelphia), and projects that facilitate community talks. Compared to the attention this use of open innovation receives in the scientific literature, the number of identified projects seems low, however, other projects might have an impact on citizens' perception of democracy as a side effect. It has not been possible to identify the use of sophisticated tools for policy de- velopment such as policy modelling and simulation, social media monitoring or opinion mining as described by Androutsopoulou et al. (2017); what was identified was mostly collaboration support and so- cial media tools such as forums and Facebook. Possible reasons for this could be that using open innovation to innovate democracy is ex- tremely difficult because it requires substantial political commitment, and changes to legislation and the processes through which political decisions are made. Using crowdsourcing, for example, to make poli- tical decisions conflicts with the basic ideas of representative democ- racy and creates uncertainty and unpredictability. For example, Pre- sident Obama implemented an online “Citizen's Briefing Book” where citizens could submit ideas to him during the transition period. Ap- proximately 44,000 proposals and 1.4 million votes were received, however, the most popular ideas included legalizing marijuana and online poker, which were of little use to the President (Birkinshaw, Bouquet, & Barsoux, 2011).

The use of open innovation to innovate public sector organisations internally is also limited (8% in the dataset). Projects typically provide

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front ends for processes that, for example, allow citizens to register problems (e.g. SeeClickFix) that are subsequently dealt with by a pro- cess in a public sector organisation, or support public sector technical experts in solving a specialised technical task. We have found very few open innovation projects that focus on innovating a process within a public sector organisation, such as the US Peer-to-Patent project, however, we have found no examples of using open innovation to de- scribe a current public sector process with all the weaknesses and strengths it might have and exploit external innovative assets to in- novate the process. We have found several projects on Challenge.gov that focus on product innovation in terms of developing new software that typically supports public employees in solving a technical task (e.g. the “build the best algorithm that predicts how the chemical spectrum of a substance changes in different molecular environments” challenge from Challenge.gov). These projects are all characterised by being limited to the development of software. Based on the identified projects, it is hard to find any support for the hopes of using open innovation to increase the service capacity of public sector organisations, or making them more responsive, user-centric and proactive. One possible explanation for the low number of projects could be that public sector processes and services are to a large extent controlled by political actors, legislation, and processes in a democracy, leaving little room and mandate for ra- dical innovation based on open innovation (Mergel et al., 2014).

It is difficult to find any open innovation projects that explicitly target the relationship and collaboration between public sector orga- nisations (below 1% in the dataset). They are rare cases, but they might be under-represented in the dataset, because they can be accomplished without publicly reporting on the projects due to the lack of involve- ment from citizens.

There might be more impact from the open innovation projects, regarding the innovation of the relationship between public sector or- ganisations, citizens and other stakeholders, even though the number of projects that explicitly target the relationship is low (2% in the dataset). We have found very few projects that explicitly describe their purposes as trying to change citizen perceptions of government fairness or le- gitimacy, or increase the level of trust, or have the sole purpose of branding, but such goals may play a more implicit role for public sector organisations when engaging in projects. A single project in the sample from Challenge.gov encouraged participating citizens to “tell the best story about the impact of technologies developed by the Federal government” might be perceived as branding, however, the great majority of projects across all categories are based on citizen participation, engagement and collaboration and that must have some impact on the relationship be- tween citizens and government.

The overwhelming majority of the identified projects explicitly focus on innovation in society (83% of the projects in the dataset). These projects might have an impact on public sector organisations, the relationship between public sector organisations, citizens and other external stakeholders, and the relationship between public sector or- ganisations, but these impacts are side effects, not the main goals. Given the large number of these projects, the purpose of these projects in terms of objects of change and the values pursued is analysed in more detail.

If the projects were traditional information systems projects taking place within a public or private organisation, they would typically at- tempt to create value by changing internal objects of change such as an organisational process that produce services for citizens. The projects in this category are different in the sense that they primarily attempt to change citizen behaviour, capabilities and experiences. The specific objects of change and values described in Tables 5 and 6 emerged during the analysis and were added to the coding scheme in Table 1.

In the open innovation projects studied here, the major part of projects targets two different kinds of value through changing, for ex- ample, citizen behaviour: the quality of citizen life and the quality of neighbourhoods.

These two kinds of values are of course closely related. A change in

individual citizen behaviour, capability or experiences might not only affect the quality of life of individuals but also the neighbourhood in general. These values could also have an impact on other public values such as those in the “efficiency” category. For example, more healthy behaviours might reduce public sector healthcare costs.

The projects focus on solving minor, not wicked, problems. The most innovative projects are generally the smart city projects. Some projects seem to attempt to make small contributions to solving wicked problems (e.g. experimenting with electric cars) in the context of a single city, such as climate change or transportation problems, but there are no examples of projects attempting to provide complete solutions to wicked problems on a larger scale. Most projects seem to solve minor problems – for example supporting users in planning how to use public transportation.

5.2. Value creation from open innovation

The findings regarding value creation from the projects are sum- marized in Table 7. Using dynamic capability concepts (Teece, 2007), the IT investments are concerned with co-specialising resources in so- ciety with IT systems. Public sector organisations place resources, and regulate and protect resources in society, and the IT systems seem to support these activities and to provide public value by optimising the value of new or existing resources. The analysis and coding of the projects identified a range of both tangible and intangible resources within several domains, as described in Table 8.

Analysing the projects from a resource perspective meant that dif- ferent categories of projects that deliver different kinds of IT systems emerged, as illustrated in Table 9.

IT systems can technically be categorised into apps, websites, ad- vanced algorithms (such as algorithms for face recognition), and the more complex systems typically delivered by R&D smart city projects (such as mobility-as-a-service projects). The majority of IT systems target citizens as the primary users. IT solutions support citizens in exploring resources before using them, planning the use of resources, locating resources, using resources, protecting resources, sharing and re-using resources, paying for the use of resources, optimising value creation from resources, using resources in a sustainable way and be- coming a resource for other citizens and the neighbourhood, for ex- ample by helping other citizens or helping to maintain or improve re- sources in the neighbourhood. Some of the projects found on Challenge. gov support public sector technical experts in doing their job.

Data is not available regarding the non-IS investments. The de- scriptions of the projects are generally very techno-centric, focusing on technical solutions and not, for example, on how to help citizens to use the IT systems and change behaviour.

The projects all exploit some kind of innovative asset outside public sector organisations, such as knowledge or products from private sector organisations, scientific knowledge from universities or citizen knowl- edge, and they predominantly seem to rely on a local search for situated knowledge (e.g. local citizens) and expert knowledge (local companies), not a distant search. The major exception is the Challenge.gov projects, which seem to reach participants from other countries that have the expert knowledge required to solve a complicated technical task. Surprisingly, knowledge from other similar public sector organisations is not exploited, except in a few cases. Generally, the smart city projects include the broadest group of innovative assets. In terms of project descriptions the data does not contain information about lag effects or contextual factors. Table 10 summarises key data about the identified projects.

6. Results: suggesting a framework for IT-enabled value creation using open innovation

We will now use the findings from the previous analysis of the open innovation articles and the projects, including the perception of value

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creation presented in Section 2, to suggest a framework for IT-enabled value creation in society when using open innovation (see Fig. 1). The framework serves two purposes: 1) it supports practitioners when de- signing open innovation projects with a strong focus on value creation in this particular context, and 2) it supports future research in open innovation by highlighting critical areas where more research is needed to better support value creation when designing such projects. The framework also clearly illustrates the complexity of open innovation in this context.

When using open innovation, value creation is based on the ex- ploitation of both internal and external innovative assets. The con- tributions from these innovative assets are used to co-specialise IT sys- tems (see for example Table 9) with resources in society (see for example Table 8). Resources in society can be owned by the public sector, by private sector organisations, or by citizens. These are co- specialised with, and intended to change, one or more “objects of change”, and it is these changes that potentially create value. For ex- ample, changing citizen behaviour in a specific way might make citi- zens healthier. Even though the purpose is “innovation in society”, such innovations will also have implications for, and rely upon, objects of change in the other categories, except for “objects of change” related to “innovation of democracy”. In the previous example, changes in citizen health-related behaviours might have implications for internal pro- cesses and capabilities in, and services provided by, healthcare orga- nisations.

The change processes (the non-IT investments) used to create these changes have been divided into three different categories. Two of these categories were identified in Section 4: the optimisation of the current business model and changing the current business model of a public sector organisation. The last change process category represents an obvious knowledge gap in the reviewed literature: how to implement the changes in society, for example how to encourage citizens to change their behaviour as an outcome of open innovation initiatives.

The last column in Fig. 1 is concerned with capturing the different kinds of value. Many open innovation initiatives include a push towards involving citizens (see Tables 9 and 10) more in the actual value creation (values created in society in Fig. 1). These values are closely related to the traditional values emphasised and created by public sector organisations. For example, a core question is how to secure professionalism and equality in healthcare, if healthcare services are provided by, for example, having chronically ill or elderly citizens monitoring their own health using IT systems. We know from in- formation systems research, as described in Section 2, that such pro- cesses of IT-enabled value creation are affected by contextual factors and lag effects. These lag effects have not been researched in this spe- cific context and represent a knowledge gap.

In the remaining part of this section, we will briefly explain how practitioners might use the framework to design open innovation pro- jects that pursue “innovation in society”. Practitioners could start from the right and consider which values to create, whether the creation of these values can take place within the current business model or require changes to the existing business model, and what objects need to be changed, and how to create value. To obtain these changes, there must be consideration of how the changes can be supported by IT systems that are designed to, for example, increase the exploitation of, or im- prove, resources in society, including the citizens themselves. There must also be consideration of which innovative assets are needed, and in which way they are needed. For example, in the majority of projects studied here, it seems that citizens and other external innovative assets are primarily used as programmers to solve technical tasks, and not the most challenging tasks, such as changing the objects of change. By considering lag effects and contextual factors, ways of improving the conditions for using open innovation might be identified.

7. Discussion

In this section, we will look into the existing open innovation re- search reviewed here, as well as the open innovation projects, in order to identify possibilities for future research.

The analysis of the research literature and the identified projects indicate that research and practice are misaligned. Some of the pur- poses of using open innovation emphasised in the research literature are apparently not matched by a similar interest in practice, which primarily seems to focus on innovation in society. Some possible ex- planations regarding the unexpectedly low number of projects in some of the categories are presented in Section 5.2. Another possible ex- planation could be the way the literature review has been conducted, for example including less or more open government articles has an impact on the number of projects in the “Innovation of democracy” category since open government explicitly focuses on values such as, for example, transparency. However, the projects have been identified through articles that also describe the various purposes. The apparent lack of alignment between research and practice could be perceived as problematic because it creates a risk of producing research that is less relevant to practice, however, the lack of alignment might also be considered a strength in the sense that open innovation research in this context is relatively new, and therefore naturally explores the use of the approach for many different purposes.

There also seems to be a difference between the scale of innovation in research and practice. While many research articles describe how open innovation can be used to solve wicked problems, it has not been possible to identify research that reports solving such problems or

Table 5 The object of change – innovation in society.

Object of change Examples

Citizen behaviour Enabling citizens to become more efficient by using less time on transportation, encourage the citizens to share both public and private resources (e.g. shared bicycles, e-cars, library of things), enabling citizens as resources to help other citizens (e.g. a mentor for new businesses in the community), helping elderly citizens live longer in their own homes, helping citizens to be more careful drivers, or enabling them to live in a more sustainable way.

Citizen capability Enabling citizens to exploit opportunities in the neighbourhood, helping them understand the relationship between the environment and health, or increase their capabilities to take part in digital innovation.

Citizen experience Helping citizens feel more safe or included in society, reducing the level of noise from streets, making public places more pleasant (e.g. by reducing wind and heat), providing cultural experiences through public art installations, and social experiences through social events that bring people together in a specific neighbourhood.

Table 6 Values – innovation in society.

Value Examples

The quality of citizen life The previous examples relating to citizen behaviour, capability and experience all illustrate this kind of value. The quality of neighbour-hoods Examples of quality are making the neighbourhood more sustainable, more resilient, inclusive, safer or more innovative.

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practical projects that aim to do so in a wider context. Some knowledge gaps need to be addressed by open innovation research in order to use open innovation to solve large scale wicked problems in society. The existing research predominantly focuses on the external innovative assets: how to get knowledge of external innovative assets, primarily citizens, the IT systems needed for getting this knowledge, and how to implement the process of getting this knowledge. The actual exploita- tion and creation of value based on this knowledge is largely ignored. Pursuing the following issues might improve this situation:

• How to increase the quality of the input received from external

innovative assets. Reports from both public sector cases (e.g. Birkinshaw et al., 2011) and cases based on collaboration between private and public sector organisations (e.g. Garcia, Wigger, & Hermann, 2019) show us that this is not trivial at all. We have seen no examples of cases where “the wisdom of the crowd” (e.g. Brabham, 2009) has clearly emerged. • How to increase the acceptance and the use of this input among internal innovative assets. Public sector open innovation literature (e.g. Davis et al., 2015; Kornberger et al., 2017; Lodge & Wegrich, 2015; Mergel, 2015; Royo & Yetano, 2015) indicates a reluctance regarding the use of input from external innovative assets. Private

Table 7 The findings – open innovation projects.

Concept Finding

IT investments The IT investments are concerned with co-specialising resources in society with IT systems. Few open innovation projects focus on developing IT systems that support the open innovation process.

Non-IT investments The project descriptions are generally very techno-centric, containing no information about, for example, how to implement the IT systems and getting citizens to use the developed IT systems.

Innovative assets The smart city projects include the broadest group of innovative assets, while most other projects only rely on contributions from citizens. Contextual factors No data available in project descriptions. Lag effects No data available in project descriptions.

Table 8 Domains and resources.

Tangible resources

Domain Example resources

Transportation Streets, electric cars, autonomous vehicles, bicycles, street light, parking opportunities, charging stations, buses, trains, school buses, street name signs, traffic control cameras, bicycle lanes.

Infrastructure Public space furniture, public spaces, IoT networks, public Wi-Fi, public charge stations for smart phones, trees, supply of electricity and water. Culture Libraries, public art installations, locations used in classic films, local artists (e.g. famous writers), memorials. Private home Smart lights to be used by elderly people, fibre optics in homes, library of things that provides resources that are shared among citizens. Education Schools, kindergartens, school buses, school meals, savings for educational purposes. Recreation Tennis courts, playgrounds, public parks, restaurants. Social Communities for elderly people, social services, opportunities for citizens with special needs (e.g. immigrants) to improve their lives, support networks. Health Typically technological resources in private homes to be used by elderly or chronically ill people. Environment Rivers, air, noise, climate. Innovation support Open data, innovation labs, innovative public-private ecosystems, intermediaries, citizen mentors that support start-up businesses, public funding for

innovative projects. Intangible resources Close collaboration between schools and parents, parent involvement in schools, citizens' feeling of security, citizen capabilities and experience (e.g. their ability to understand, use and

contribute to the development of digital tools), citizens' feeling of being included in the neighbourhood, well-functioning neighbourhoods, resilient communities, citizen engagement in neighbourhoods, traffic safety in the community, the ability to live a sustainable life, low level of crime, public health, innovation.

Table 9 Project categories.

Category Description

Planning resources Projects that include the citizens in open innovation process planning, for example future infrastructure in a city. For example, The Future Melbourne project.

Exploit resources Projects that attempt to make it easier for citizens to exploit resources in society, for example by helping citizens use the transportation systems in the most efficient way.

Protect resources There are projects such as the Citizen Corps (www.citizencorps.gov) projects in the US that engage citizens in helping their communities to prepare for the threats of terrorism, crime, public health issues and disasters, and projects that have an environmental focus.

Maintain resources The typical project in this category develops apps that support citizens in reporting and tracking issues (such as a damaged road). For example, SeeClickFix, which is a widely used tool that allows citizens to report non-emergency neighbourhood issues, for example potholes to local government bodies.

Improve resources For example, projects that improve neighbourhoods, projects that collect information from patients to improve healthcare, or the project from Citilab Barcelona, Spain, that improves digital competencies in a specific neighbourhood.

Table 10 Overview of the projects.

The projects

Project purposes Innovation of democracy, regulations and policies 6%, innovation of public sector organisations 8%, innovation of the relationship between public sector organisations 0,4%, innovation of the relationship between public sector organisations citizens and other stakeholders 2%, innovation in society 83%.

Project categories Improve resources 51%, exploit resources 32%, maintain resources 8%, protect resources 5%, planning resources 4%.

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sector research studying similar challenges points towards causes such as the not-invented-here syndrome (e.g. Salter, Criscuolo, & Ter Wal, 2014) and lack of absorptive capacity (Di Gangi & Wasko, 2009). • How to co-specialise IT systems, resources in society and the objects of change. The great majority of all the identified open innovation projects seem very concerned with the technological solution and seem to neglect the users and the complementary investments that are needed to exploit the investments in IT solutions. The living lab literature (e.g. Gascó, 2017) has some of the answers, but we need a more holistic understanding that also includes the redesign of public sector organisations. • How to implement changes to objects of change in society, for ex- ample how to use IT to change citizen behaviour. Here, the beha- viour change support systems literature (e.g. Oinas-Kukkonen, 2013) and persuasive design literature (Halko & Kientz, 2010) might inspire and provide some of the answers. • How to secure traditional values, such as equal access to healthcare, when the production of, for example, healthcare services, takes place outside public sector healthcare organisations. Addressing such questions becomes important when considering business model changes, as proposed by, for example Feller et al. (2011) and Linders (2012). • How to improve the conditions for using open innovation and un- derstanding lag effects. Studies have emphasised the difficulties of implementing open innovation in a public sector context (e.g. Mergel & Desouza, 2013), and lag effects are not researched at all.

Kankanhalli et al. (2017) described the lack of exploitation of es- tablished theories in open innovation research. The research here in- dicates that he resource-based view, absorptive capacity theory, and theory about how to change citizen behaviour, for example through nudging or behavioural change support systems, might be relevant.

8. Conclusion

The framework in Fig. 1 illustrates the answer to the initial research question: Why do public sector organisations use open innovation and how does it create value? It seems like public sector organisations primarily

use open innovation for innovation in society. They attempt to create value in terms of citizens' quality of life and neighbourhood quality, and they do that primarily by co-specialising IT and other resources in so- ciety, and by using the outcome of this co-specialisation process to change citizen behaviour, capabilities, and experiences.

Based on data about the open innovation projects, the research here indicates that open innovation is generally not used to open up public sector organisations in order to give citizens more influence in public sector processes or democratic processes. It instead seems that open innovation is primarily used by public sector organisations to reach out, trying to control issues in society and change the way citizens behave, and the capabilities and experiences that citizens have.

The practical and research implications have been discussed in the previous section. The research here has several limitations, as pre- viously emphasised in the research method section. The primary lim- itations are that the identified open innovation projects might not be representative, and that we do not know anything about the realised outcome of these projects. We can only see how the projects intend to create value.

Author statement

Keld Pedersen is the corresponding author and sole responsible for the article.

References

Aguilera, U., Peña, O., Belmonte, O., & López-de-Ipiña, D. (2017). Citizen-centric data services for smarter cities. Future Generation Computer Systems, 76, 234–247.

Almirall, E., Lee, M., & Majchrzak, A. (2014). Open innovation requires integrated competition-community ecosystems: Lessons learned from civic open innovation. Business Horizons, 57(3), 391–400.

Androutsopoulou, A., Karacapilidis, N., Loukis, E., & Charalabidis, Y. (2017, December). Towards an integrated and inclusive platform for open innovation in the public sector. International Conference on e-Democracy (pp. 228–243). Cham: Springer.

Baka, V. (2017). Co-creating an open platform at the local governance level: How openness is enacted in Zambia. Government Information Quarterly, 34(1), 140–152.

Bakici, T., Almirall, E., & Wareham, J. (2013). The role of public open innovation in- termediaries in local government and the public sector. Technology Analysis & Strategic Management, 25(3), 311–327.

Bartlett, D. (2017). Champions of local authority innovation revisited. Local Government Studies, 43(2), 142–149.

Fig. 1. Framework for value creation. OC = objects of change.

K. Pedersen Government Information Quarterly 37 (2020) 101459

11

Birkinshaw, J., Bouquet, C., & Barsoux, J. L. (2011). The 5 myths of innovation.MIT Sloan Management Review, 52(2), 1–10.

Bommert, B. (2010). Collaborative innovation in the public sector. International Public Management Review, 11(1), 15–33.

Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40.

Brabham, D. C. (2009). Crowdsourcing the public participation process for planning projects. Planning Theory, 8(3), 242–262.

Brabham, D. C. (2012). Motivations for participation in a crowdsourcing application to improve public engagement in transit planning. Journal of Applied Communication Research, 40(3), 307–328.

Chesbrough, H. W. (2006). Open innovation: The new imperative for creating and profiting from technology. Boston, MA: Harvard Business School Press.

Davis, J. R., Richard, E. E., & Keeton, K. E. (2015). Open innovation at NASA: A new business model for advancing human health and performance innovations. Research- Technology Management, 58(3), 52–58.

De Vries, H., Bekkers, V., & Tummers, L. (2016). Innovation in the public sector: A sys- tematic review and future research agenda. Public Administration, 94(1), 146–166.

Dedrick, J., Gurbaxani, V., & Kraemer, K. L. (2003). Information technology and eco- nomic performance: A critical review of the empirical evidence. ACM Computing Surveys, 35(1), 1–28.

Dehning, B., & Richardson, V. J. (2002). Returns on investments in information tech- nology: A research synthesis. Journal of Information Systems, 16(1), 7–30.

Di Gangi, P. M., & Wasko, M. (2009). Open innovation through online communities. In W. R. King (Ed.). Knowledge management and organizational learning (pp. 199–213). Boston, MA: Springer.

Dias, C., & Escoval, A. (2012). The open nature of innovation in the hospital sector: The role of external collaboration networks. Health Policy and Technology, 1(4), 181–186.

Díaz-Díaz, R., & Pérez-González, D. (2016). Implementation of social media concepts for e-government: Case study of a social media tool for value co-creation and citizen participation. Journal of Organizational and End User Computing, 28(3), 104–121.

Estermann, B. (2018). Development paths towards open government–an empirical ana- lysis among heritage institutions. Government Information Quarterly, 35(4), 599–612.

Feller, J., Finnegan, P., & Nilsson, O. (2011). Open innovation and public administration: Transformational typologies and business model impacts. European Journal of Information Systems, 20(3), 358–374.

Ferraris, A., Santoro, G., & Papa, A. (2018). The cities of the future: Hybrid alliances for open innovation projects. Futures, 103, 51–60.

Fosltad, A. (2008). Living labs for innovation and development of information and communication technology: A literature review. The Electronic Journal for Virtual Organizations and Networks, 10, 99–131 (special issue on living labs).

Gagliardi, D., Schina, L., Sarcinella, M. L., Mangialardi, G., Niglia, F., & Corallo, A. (2017). Information and communication technologies and public participation: Interactive maps and value added for citizens. Government Information Quarterly, 34(1), 153–166.

Garcia, R., Wigger, K., & Hermann, R. R. (2019). Challenges of creating and capturing value in open eco-innovation: Evidence from the maritime industry in Denmark. Journal of Cleaner Production, 220, 642–654.

Gascó, M. (2017). Living labs: Implementing open innovation in the public sector. Government Information Quarterly, 34(1), 90–98.

Gassmann, O., & Enkel, E. (2004). Towards a theory of open innovation: Three core process archetypes. Proceedings of The R&D Management Conference, Lisbon, Portugal, July 6–9.

Halko, S., & Kientz, J. A. (2010, June). Personality and persuasive technology: An ex- ploratory study on health-promoting mobile applications. International Conference on Persuasive Technology (pp. 150–161). Berlin, Heidelberg: Springer.

Haltofova, B. (2018). Using crowdsourcing to support civic engagement in strategic urban development planning: A case study of Ostrava, Czech Republic. Journal of Competitiveness, 10(2), 85–103.

Hilgers, D., & Ihl, C. (2010). Citizensourcing: Applying the concept of open innovation to the public sector. The International Journal of Public Participation, 4(1), 67–88.

Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, adoption barriers and myths of open data and open government. Information Systems Management, 29(4), 258–268.

Janssen, M., Konopnicki, D., Snowdon, J. L., & Ojo, A. (2017). Driving public sector in- novation using big and open linked data (BOLD). Information Systems Frontiers, 19(2), 189–195.

Juujärvi, S., & Lund, V. (2016). Enhancing early innovation in an urban living lab: Lessons from Espoo, Finland. Technology Innovation Management Review, 6(1), 17–26.

Kankanhalli, A., Zuiderwijk, A., & Tayi, G. K. (2017). Open innovation in the public sector: A research agenda. Government Information Quarterly, 34(1), 84–89.

Klievink, B., Bharosa, N., & Tan, Y. H. (2016). The collaborative realization of public values and business goals: Governance and infrastructure of public–private in- formation platforms. Government Information Quarterly, 33(1), 67–79.

Klievink, B., & Janssen, M. (2009). Realizing joined-up government—Dynamic cap- abilities and stage models for transformation. Government Information Quarterly, 26(2), 275–284.

Konsti-Laakso, S. (2017). Stolen snow shovels and good ideas: The search for and gen- eration of local knowledge in the social media community. Government Information Quarterly, 34(1), 134–139.

Kornberger, M., Meyer, R. E., Brandtner, C., & Höllerer, M. A. (2017). When bureaucracy meets the crowd: Studying “open government” in the Vienna City Administration. Organization Studies, 38(2), 179–200.

Lampe, C., Zube, P., Lee, J., Park, C. H., & Johnston, E. (2014). Crowdsourcing civility: A natural experiment examining the effects of distributed moderation in online forums. Government Information Quarterly, 31(2), 317–326.

Lee, S. M., Hwang, T., & Choi, D. (2012). Open innovation in the public sector of leading countries. Management Decision, 50(1), 147–162.

Lichtenthaler, U., & Lichtenthaler, E. (2009). A capability-based framework for open innovation: Complementing absorptive capacity. Journal of Management Studies, 46(8), 1315–1338.

Linders, D. (2012). From e-government to we-government: Defining a typology for citizen coproduction in the age of social media. Government Information Quarterly, 29(4), 446–454.

Liu, H. K. (2017). Crowdsourcing government: Lessons from multiple disciplines. Public Administration Review, 77(5), 656–667.

Lodge, M., & Wegrich, K. (2015). Crowdsourcing and regulatory reviews: A new way of challenging red tape in British government? Regulation & Governance, 9(1), 30–46.

Long, M. (2002). Beyond traditional boundaries: Government in the information age. Australian Journal of Public Administration, 61(1), 3–12.

López-de-Ipiña, D., Emaldi, M., Aguilera, U., & Pérez-Velasco, J. (2016). Towards citizen co-created public service apps. Ubiquitous Computing and Ambient Intelligence (pp. 469–481). Cham: Springer.

Loukis, E. (2018). Citizen-sourcing for public policy making: Theoretical foundations, methods and evaluation. Policy Analytics, Modelling, and Informatics (pp. 179–203). Cham: Springer.

Loukis, E., Charalabidis, Y., & Androutsopoulou, A. (2017). Promoting open innovation in the public sector through social media monitoring. Government Information Quarterly, 34(1), 99–109.

Malhotra, A., Majchrzak, A., & Niemiec, R. M. (2017). Using public crowds for open strategy formulation: Mitigating the risks of knowledge gaps. Long Range Planning, 50(3), 397–410.

Martins, T. C. M., de Souza Bermejo, P. H., & de Souza, W. V. B. (2015). Open innovation for citizen coproduction. International Conference on Electronic Government and the Information Systems Perspective (pp. 177–188). Cham: Springer.

Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Information technology and organi- zational performance: An integrative model of IT business value. MIS Quarterly, 28(2), 283–322.

Mergel, I. (2015). Opening government: Designing open innovation processes to colla- borate with external problem solvers. Social Science Computer Review, 33(5), 599–612.

Mergel, I. (2018). Open innovation in the public sector: Drivers and barriers for the adoption of Challenge.gov. Public Management Review, 20(5), 726–745.

Mergel, I., & Desouza, K. C. (2013). Implementing open innovation in the public sector: The case of Challenge.gov. Public Administration Review, 73(6), 882–890.

Mergel, I., Bretschneider, S. I., Louis, C., & Smith, J. (2014, January). The challenges of Challenge. gov: Adopting private sector business innovations in the Federal Government. 2014 47th Hawaii International Conference on System Sciences (pp. 2073– 2082). IEEE.

Minner, J., Holleran, M., Roberts, A., & Conrad, J. (2015). Capturing volunteered his- torical information: Lessons from development of a local government crowdsourcing tool. International Journal of E-Planning Research, 4(1), 19–41.

Moon, M. J. (2018). Evolution of co-production in the information age: Crowdsourcing as a model of web-based co-production in Korea. Policy and Society, 37(3), 294–309.

Nam, T. (2012). Suggesting frameworks of citizen-sourcing via government 2.0. Government Information Quarterly, 29(1), 12–20.

Oinas-Kukkonen, H. (2013). A foundation for the study of behavior change support sys- tems. Personal and Ubiquitous Computing, 17(6), 1223–1235.

Ojasalo, J., & Kauppinen, H. (2016). Collaborative innovation with external actors: An empirical study on open innovation platforms in smart cities. Technology Innovation Management Review, 6(12), 49–60.

Panagiotopoulos, P., Bowen, F., & Brooker, P. (2017). The value of social media data: Integrating crowd capabilities in evidence-based policy. Government Information Quarterly, 34(4), 601–612.

Pánek, J. (2018). Participatory mapping in community participation–case study of Jeseník, Czech Republic. Quaestiones Geographicae, 37(3), 151–162.

Paskaleva, K., & Cooper, I. (2018). Open innovation and the evaluation of internet-en- abled public services in smart cities. Technovation, 78, 4–14.

Pedersen, K. (2016). E-government in local government: Challenges and capabilities. Electronic Journal of E-Government, 14(1), 99–116.

Pedersen, K. (2018). E-government transformations: Challenges and strategies. Transforming Government: People, Process and Policy, 12(1), 84–109.

Picazo-Vela, S., Fernandez-Haddad, M., & Luna-Reyes, L. F. (2016). Opening the black box: Developing strategies to use social media in government. Government Information Quarterly, 33(4), 693–704.

Piccoli, G., & Ives, B. (2005). IT-dependent strategic initiatives and sustained competitive advantage: A review and synthesis of the literature. MIS Quarterly, 29(4), 747–776.

Prpić, J., Taeihagh, A., & Melton, J. (2015). The fundamentals of policy crowdsourcing. Policy & Internet, 7(3), 340–361.

Rose, J., Persson, J. S., Heeager, L. T., & Irani, Z. (2015). Managing e-government: Value positions and relationships. Information Systems Journal, 25(5), 531–571.

Royo, S., & Yetano, A. (2015). “Crowdsourcing” as a tool for e-participation: Two ex- periences regarding CO2 emissions at municipal level. Electronic Commerce Research, 15(3), 323–348.

Salter, A., Criscuolo, P., & Ter Wal, A. L. (2014). Coping with open innovation: Responding to the challenges of external engagement in R&D. California Management Review, 56(2), 77–94.

Sandoval-Almazan, R., Gil-Garcia, J. R., & Valle-Cruz, D. (2017). Going beyond bureau- cracy through gamification: Innovation labs and citizen engagement in the case of “Mapaton” in Mexico City. Beyond Bureaucracy (pp. 133–149). Cham: Springer.

Schmidthuber, L., & Hilgers, D. (2018). Unleashing innovation beyond organizational boundaries: Exploring citizensourcing projects. International Journal of Public Administration, 41(4), 268–283.

K. Pedersen Government Information Quarterly 37 (2020) 101459

12

Schryen, G. (2013). Revisiting IS business value research: What we already know, what we still need to know, and how we can get there. European Journal of Information Systems, 22(2), 139–169.

Schuurman, D., & Tõnurist, P. (2016). Innovation in the public sector: Exploring the characteristics and potential of living labs and innovation labs. OpenLivingLab Days 2016 (pp. 78–90). .

Seltzer, E., & Mahmoudi, D. (2013). Citizen participation, open innovation, and crowd- sourcing: Challenges and opportunities for planning. Journal of Planning Literature, 28(1), 3–18.

Sørensen, E., & Torfing, J. (2011). Enhancing collaborative innovation in the public sector. Administration and Society, 43(8), 842–868.

Spiliotopoulou, L., Charalabidis, Y., Loukis, E. N., & Diamantopoulou, V. (2014). A fra- mework for advanced social media exploitation in government for crowdsourcing. Transforming Government: People, Process and Policy, 8(4), 545–568.

Tate, M., Bongiovanni, I., Kowalkiewicz, M., & Townson, P. (2018). Managing the “fuzzy front end” of open digital service innovation in the public sector: A methodology. International Journal of Information Management, 39, 186–198.

Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350.

Thapa, B. E., Niehaves, B., Seidel, C. E., & Plattfaut, R. (2015). Citizen involvement in public sector innovation: Government and citizen perspectives. Information Polity, 20(1), 3–17.

Van Veenstra, A. F., Klievink, B., & Janssen, M. (2011). Barriers and impediments to transformational government: Insights from literature and practice. Electronic Government, An International Journal, 8(2/3), 226–241.

Veeckman, C., & van der Graaf, S. (2015). The city as living laboratory: Empowering citizens with the citadel toolkit. Technology Innovation Management Review, 5(3),

6–17. Vicini, S., Bellini, S., & Sanna, A. (2012). The city of the future living lab. International

Journal of Automation and Smart Technology, 2(3), 201–208. Wass, S., & Vimarlund, V. (2016). Healthcare in the age of open innovation – A literature

review. Health Information Management Journal, 45(3), 121–133. Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing

a literature review. MIS Quarterly, 26(2), xiii–xxiii. Weerakkody, V., & Dhillon, G. (2008). Moving from e-government to t-government: A

study of process reengineering challenges in a UK local authority context. International Journal of Electronic Government Research, 4(4), 1–16.

Weerakkody, V., Dhillon, G., Dwivedi, Y., & Currie, W. (2008). Realising transformational stage egovernment: Challenges, issues and complexities. Proceedings of the Fourteenth Americas Conference on Information Systems, Toronto, ON, August 14th–17th.

Wirtz, B. W., Daiser, P., & Binkowska, B. (2018). E-participation: A strategic framework. International Journal of Public Administration, 41(1), 1–12.

You, L., Motta, G., Liu, K., & Ma, T. (2016). City feed: A pilot system of citizen-sourcing for city issue management. ACM Transactions on Intelligent Systems and Technology, 7(4), 1–25.

Zhang, N., Zhao, X., Zhang, Z., Meng, Q., & Tan, H. (2017). What factors drive open innovation in China's public sector? A case study of official document exchange via microblogging (ODEM) in Haining. Government Information Quarterly, 34(1), 126–133.

Keld Pedersen has conducted research within several research areas such as manage- ment of systems development and value creation using information systems. During the last years, Keld Pedersen has focused on public sector digitalization, and on how IT can be used to facilitate open innovation and on how IT can be used to solve problems in society.

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