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What Drives Innovation in Public-Private Innovation Partnerships?

Lena Brogaard (brogaard@ruc.dk)

Institut for Samfund og Globalisering, Roskilde Universitet

Paper til Dansk Selskab for Statskundskabs Årsmøde, oktober 20151

Panel: Innovation og entreprenørskab i den offentlige sektor

Abstract What drives innovation in public-private innovation partnerships (PPI)? Based on data from a sur-

vey among 497 public and private sector respondents representing the entire known population of

PPIs in the Danish healthcare and social areas, the paper takes a first step towards addressing which

factors affect the achievement of innovation defined as the development and implementation of new

solutions in cross-sector innovation partnerships. The paper tests four hypotheses regarding the pos-

itive impact of management, innovation skills, institutional support, and trust on innovation in PPIs

derived from the literature on collaborative innovation and network governance. The findings show

that only formal innovation competencies acquired through education and courses have a significant

positive association with innovation. This suggests that a successful outcome is more likely in a PPI

where the most involved participants are familiar with and trained in innovation processes due to

the complex and uncertain nature of an innovative partnership.

Keywords: Public-private innovation partnerships, innovation, network governance, collaborative

innovation.

1 Conference paper - not to be cited

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Introduction Innovation and partnerships across the public and private sectors have become a high priority on the

research and political agenda as a way of finding solutions to the growing challenges and limited

resources facing the welfare state (Weihe et al., 2011). By involving the resources and skills of pri-

vate businesses in public service provision, public-private collaboration is considered an important

policy instrument in creating more efficient public service while maintaining or improving quality

(Steijn, Klijn, & Edelenbos, 2011: 1235). In continuation of this development, public-private inno-

vation partnerships (PPI) have been emerging as a new form of cross-sector partnership that consti-

tute an increasingly relevant and proliferating form of partnership in Scandinavia (Weihe et al.,

2011) and across European countries (see e.g. Gallouj, Rubalcaba, & Windrum, 2013). In contrast

to public-private partnerships which are often characterized as long-term, contract-based partner-

ships with a clear division of responsibilities and risk (Klijn & Teisman, 2003: 137), PPIs represent

a wide range of both formalized partnerships as well as more network-based collaborations with the

overall purpose of achieving innovation (Di Meglio, 2013). PPIs differ from the perhaps more

known concept of triple helix which entails university-industry-government relations (Fogelberg &

Thorpenberg, 2012) as universities do not necessarily participate in PPIs (Evald et al., 2014: 34).

Specifically, a PPI is an innovation-oriented partnership in which public and private entities develop

new services and technologies for use in the public sector (Olesen, 2013).

PPIs have received only limited attention in the public administration literature as the

existing research is spread across different disciplines such as entrepreneurship and business re-

search primarily with a focus on process-oriented case studies (Evald et al., 2014). So far, research

on PPIs have especially focused on the legal framework (Inden & Olesen, 2012), and on specific

aspects of the collaborative process (Fuglsang, 2013; Nissen et al., 2014). There is thus limited

knowledge on what constitutes innovation in public-private innovation partnerships as a relatively

new phenomenon as well as which specific factors contribute to or inhibit the development of inno-

vative outcomes in PPIs. Based on this, the purpose of this paper can be expressed in the following

research question: How do collaborative and institutional factors affect the achievement of innova-

tion in public-private innovation partnerships? Addressing this question will provide new insights

into the association between the partnership process, institutional context, and outcomes, and fur-

ther develop our understanding of public-private innovation.

The empirical foundation of the paper is a survey distributed among 497 key respond-

ents from public and private organizations that represent the entire known population of 260 PPIs in

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the healthcare and social areas in Denmark, where PPI is high on the political and public admin-

istration agenda. The survey was completed in early 2015 with the purpose of characterizing PPIs,

studying key drivers and barriers based on the partnership and innovation literature, and shed light

on perceived innovation and other outcomes. By using survey data this paper represents a three-fold

contribution to the growing literature on innovation partnerships which has so far been dominated

by studies of one or a few cases (Dittmer, Christiansen, & Kierkegaard, 2009; Fuglsang, 2013; Las-

sen, Bønnelycke, & Otto, 2015). First, the paper is the first known attempt to develop more general

inferences regarding PPIs based on a large number of cases across several areas. Secondly, it fur-

thers the previous and somewhat limited understanding of the innovative outcomes in PPIs, and

finally the study develops indicators for specific analyses of the factors that influence the achieve-

ment of innovation in public-private collaboration.

The paper is structured as follows. Section 2 defines innovation in PPIs as a key con-

cept in this study. In section 3, four hypotheses are derived from the partnership and innovation

literature regarding the influence of cross-organizational management, innovation skills, institution-

al support, and trust on innovation in PPIs, which is followed by a description of the survey design

and operationalization of key variables in section 4. Section 5 presents the findings from three lo-

gistic regression models of which the final model lends support to only one out of the four hypothe-

ses, thereby demonstrating the importance of formal innovation skills in a complicated innovation

process. Finally, there is a brief discussion and conclusion on the findings and the implications of

this study for future research.

Defining innovation in PPIs Innovation research has a long history which initially was anchored in the private sector but over

the past two decades has gained prominence in public sector research (Hansen & Jakobsen, 2013).

The literature on innovation is in other words vast not least in the fields of diffusion (Rogers, 1995),

types of innovation (Moore & Hartley, 2008), and the role of individual entrepreneurs (Meijer,

2014) or systems of innovation (Lundvall, 2010). The differences or similarities between public and

private sector innovation (Bessant, 2005; Fuglsang & Pedersen, 2011) and innovation in collabora-

tion between citizens, public, non-profit, and private actors (Bommert, 2010) have furthermore been

topics of increasing interest.

Public-private innovation partnerships, on the other hand, is an area still characterized

by limited empirical and theoretical contributions as it constitute a specific case of innovation in the

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cross-field between public and private and is a rather new innovation model. However, the innova-

tion literature can be used to understand PPIs and lay the groundwork for the study in this paper by

defining innovation as a core concept and purpose in PPIs. More specifically, innovation is the de-

velopment and implementation of new ideas, objects, and practices (Hansen & Jakobsen, 2013)

whereby innovation is not considered achieved unless the developed solutions are put to use in

practice (Rogers, 1995: 172). The importance in this definition lies in the clarification of innovation

as more than unrealized ideas and as something different from inventions (Moore & Hartley, 2008).

This definition is used as the basis for the operationalization of the dependent variable in the meth-

ods section. The long-term purpose of a PPI – which is beyond the scope of this paper - is the ex-

pectation that achieving innovation in a PPI will lead to economic and qualitative outcome for the

public and private partner by providing more efficient means of service delivery and production for

the public sector while increasing revenue for the private partner (Groes et al., 2011), see figure 1.

Figure 1 PPI process and outcome

Source: Adapted version of (Danish Business and Construction Authority, 2009)

Besides assessing when innovation is achieved, different dimensions can be used to evaluate the

significance of the innovation. Innovation has a commercial and competitive purpose in the private

sector, whereas the idea is to generate public value in the public sector (Mulgan, 2007; Hartley,

2005). As an innovation process involving both public and private actors, PPIs imply the presence

of both purposes and hence also different types of innovations to fulfill these purposes. Drawing on

Hartley’s overview of innovation types this can be anything from product innovation - which pro-

vides a concrete solution for the private company to sell - to public-oriented service innovation,

process innovation, innovations in governance (Hartley, 2005: 28) or different combinations of in-

novation types. Innovation can also be viewed in regards to the perceived extent of change it brings

about, i.e. whether it entails incremental adjustments or radical changes in the organization and de-

livery of services (Albury, 2005), and the degree to which the innovation is perceived as new by a

proportion of the stakeholders (Hartley, 2005) which is depicted in figure 2. In this paper, the main

Idea and problem identifiation phase

Development and test phase

Implementation phase

Economic and qualitative outcome

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focus and dimension of interest is whether and how innovation defined as implementation of the

developed solutions in PPIs is achieved.

Figure 2 Dimensions of innovation space in PPI

Source: Author’s modified version of Tidd, Bessant, & Pavitt’s model (1997: 7)

Theoretical framework: Factors influencing innovation in PPI The past two decades have been characterized by an increasing focus on cross-sector collaboration

where organizations work together to address social problems (Huxham & Vangen, 2000). This

development is not least reflected in the scholarly literature on public-private partnerships (PPP) as

a specific form of cross-sector collaboration (Bryson, Crosby, & Stone, 2015: 648). The PPP litera-

ture has become extensive covering issues such as conceptual clarification (Linder, 1999), risk-

sharing (Grimsey & Lewis, 2002), institutional differences (Klijn & Teisman, 2003), outcome per-

formance (Koontz & Thomas, 2012), and public value (Reynaers, 2014).

In recent years, innovation has furthermore entered the PPP agenda looking into inno-

vation policy (Fogelberg & Thorpenberg, 2012) and the role of PPPs in enhancing innovation (Ysa,

Esteve & Longo, 2014) while other scholars explore more specifically which factors influence the

outcome in PPPs as a form of governance network (e.g. Kort & Klijn, 2011). From this perspective,

a public-private partnership is defined as a network of interdependent actors interacting within cer-

tain institutional settings to achieve a collective goal in the form of added value, innovative out-

comes, and greater efficiency (Edelenbos & Klijn, 2009; Ysa, Sierra & Esteve, 2014; Steijn, Klijn

& Edelenbos, 2011:1237-1238). Network governance entails different more specific theoretical

approaches and framework of analyses often looking into the structure (Klijn & Teisman, 2003) and

management (Ysa, Sierra, & Esteve, 2014) of partnerships.

Incremental

Radical

Copied Unique Adapted

Perceived newsworthiness

Perc

eive

d ex

tent

of c

hang

e

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The network governance perspective on outcome and partnerships is closely related to

the literature on collaborative innovation which represents a theoretical development towards ex-

plaining when and how innovation is achieved in a collaborative effort among various public, pri-

vate, and civil society actors (Bommert, 2010). The underlying assumption is that collaboration

under certain conditions contributes to achieving results (Hartley, Sørensen, & Torfing, 2013). Like

the network governance perspective, collaborative innovation looks into the institutional frame-

work, management, as well as the collaborative process (Sørensen & Torfing, 2011). A PPI is like-

wise characterized by public and private actors from different institutional contexts whom come

together as mutual development partners, dependent on each other’s respective competencies and

resources to create innovative outcomes (Weihe et al., 2011). Theories of collaborative innovation

and network governance are thus useful perspectives in understanding what influences the innova-

tive outcome in a PPI as a similar but much less studied phenomenon.

How management, innovation skills, institutional support, and trust affect outcome

A fundamental assumption in the governance network and collaborative innovation literature is that

obstacles might arise when actors from different institutional settings and interests have to collabo-

rate which leads to a focus on specific factors that are assumed to overcome these barriers and en-

hance network performance (Klijn & Teisman, 2003; Hartley, Sørensen & Torfing, 2013). Two or

more partners lead to greater complexity and risk of conflict which creates a need for mutual trust,

institutional support, and metagovernance to facilitate the coordination between the partners and

satisfactory outcomes (Edelenbos & Klijn, 2009: 313; Torfing, 2012), see figure 3.

Figure 3 Institutional support, collaboration, and outcomes in cross-sector partnership

Source: Author’s interpretation of (Klijn & Teisman, 2000: 92-94)

Inte

rdep

ende

nce:

Ex

chan

ge o

f kno

wle

dge

and

reso

urce

s

Collaborative process Trust, management, and innovation skills

Added va-lue/innovative

outcome

Institutional support

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The outcome in PPIs which is in focus in this study has been discussed and theorized in the previ-

ous section on innovation defined as development and implementation of new solutions. The pur-

pose of this section is to derive hypotheses based on the presented theoretical perspectives regarding

which key factors that are expected to influence innovation in PPIs. The dependent and explanatory

variables will be operationalized further in the methods section.

Management

Within network governance the concept of metagovernance has come to describe how facilitating

and managing processes of interaction in a network helps overcome collaborative and institutional

barriers in a partnership such as cultural differences or conflicts of interest (Sørensen & Torfing,

2011: 861). This entails different types of management of cross-sector partnerships and how specif-

ic styles can for instance enhance the level of trust and the perceived outcome (Ysa et al., 2014;

Klijn, Steijn & Edelenbos, 2010). Management can be one or more people and organizations in

charge of facilitating the partnership without directly participating, or it can be a form of shared

governance where a number of people and organizations direct the partnership towards specific

results through active participation (Edelenbos & Klijn, 2009; Provan & Kenis, 2008: 234). In the

literature on collaborative innovation and management of innovation, metagovernance is further-

more viewed in terms of the specific roles of an innovation leader (Torfing, 2012) and as the skill to

understand which factors facilitate and inhibit innovation (Van de Ven, 1986). What these different

perspectives on metagovernance have in common is the underlying assumption that management

increases the likelihood of a successful collaborative effort. This represents a move away from a

focus on unitary leaders of one organization to how management needs to facilitate collaboration

across the public, private, and non-profit sectors by understanding their different values and objec-

tives (Erakovich & Anderson, 2013). This is supported by previous PPI research where Nissen et

al.’s case study of knowledge-sharing in PPI suggests that strong project leadership contributes to a

more successful partnership process (Nissen, Evald, & Clarke, 2014). Hence, cross-organizational

management tasked with facilitating the collaborative process in a PPI is in this study assumed to

enhance performance as formulated in the first hypothesis.

H1management: Cross-organizational management of the collaborative process is positively related to

innovation in PPI.

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Innovation skills

PPIs constitute a very heterogeneous group of public and private representatives with different ob-

jectives which can make management of the process difficult as the literature on cross-sector col-

laboration likewise recognizes (Crosby & Bryson, 2010: 227). Participants can be anything from

innovation consultants in municipalities to hospital nurses, company CEOs, or technical project

leaders. Furthermore, PPIs are complicated by the innovative purpose as innovation processes are

uncertain and risky (Bessant, 2005). While Nissen et al. in their previously mentioned PPI study

find that project leadership can be beneficial in some cases they also conclude that it does not nec-

essarily solve all conflicts or ensure transfer of knowledge and progress (Nissen et al., 2014). The

particularly complex conditions in a PPI suggest that a successful outcome is not only dependent on

the presence of an appointed and formally authoritative project leader but on the involved partici-

pants’ skills and knowhow as they can likewise influence the partnership agenda (Huxam &

Vangen, 2000; 1167). The participating public and private partners can be considered as exercising

a form of shared governance or leadership through their activities, roles, and commitment to the

process (Provan & Kenis, 2008) which implies that the responsibility of successful completion of

the partnership lies with the most involved participants from each organization and their ability to

drive the process forward as well as with any designated project leader (Huxam & Vangen, 2000;

1167-68). Drawing on a previous survey on collaborative innovation, formal innovation competen-

cies imply an awareness of what is required to initiate and support innovative processes (Schultz

Larsen, 2014: 331). This leads to the second hypotheses positing that partnerships where the in-

volved participants possess innovation competencies acquired through education and courses are

assumed to be more likely to achieve innovation.

H2innovation skills: Formal innovation competencies in the participating partners are positively related

to innovation in PPI.

Institutional support of the PPI

Partnerships represent complex relations among different actors requiring management and certain

skills, but it also represents complex networks of different institutional settings and organizational

backgrounds of the collaborative actors with different value systems, legitimacy, and funding op-

portunities (Ysa et al., 2014: 640-41). Institutional characteristics in terms of resources and rules of

the network influence the collaborative process and hence the outcome (Klijn & Koppenjan, 2000)

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which implies that successful collaboration cannot be achieved if there is limited or no support for

the partnership. The success of the partnership is dependent on management support, access to re-

sources, and so on (Hartley et al., 2013: 827). In a PPI, this is true on several levels as the collabora-

tive process often involves both users or citizens needed to test the developed solutions, representa-

tives from the private business(es), employees, and managers in the public organization (Groes et

al., 2011) whom all need to support the common goal of the partnership to ensure progress. Moreo-

ver, the top management in the respective organizations can be the gatekeeper to the necessary

funding of the partnership and ensure a more active network management and cooperation (Ysa et

al., 2014: 640). It is thus important to take into consideration any possible institutional and organi-

zational barriers and enablers such as designs for dialogue with users and the organizations’ focus

on innovation (Sørensen & Torfing, 2011: 860). Based on this, to avoid conflict, blocking of inter-

action, formulation of common goals, and access to resources and knowledge necessary for partner-

ship (Klijn & Koppenjan, 2000: 143), commitment from the participating public and private organi-

zations as well as their management, employees, and any involved citizens is assumed to collective-

ly represent institutional support which contributes to satisfactory outcomes as expressed in the

third hypothesis of this study.

H3Institutional support: Institutional support is positively related to innovation in PPI.

Mutual trust between the partners in the PPI

Finally, trust is an important foundation for a successful outcome in a partnership as it can enhance

cooperation by reducing the perceived complexity and provide a way of handling the uncertainty of

the process (Edelenbos et al., 2007). More specifically, trust can be defined as the willingness to be

vulnerable to the actions of others due to the positive expectations that their actions will have the

benefit and interest of all partners in mind (Fuglsang, 2013: 249; Mayer et al., 1995: 712). Leaning

on the work of Mayer et al. (Mayer et al., 1995), trust is more specifically a result of the perceived

trustworthiness of the respective partners which is constituted by ability, benevolence and integrity.

Ability can be defined as the partners’ perception of the other participants’ competencies, benevo-

lence whether or not the partners’ believe the other parties only have their own self-interest in mind

(Edelenbos et al., 2007: 68; Mayer et al., 1995: 718), while integrity is understood as whether or not

the other parties can be expected to do what has been agreed (Mayer et al., 1995: 719). Finally,

presence and interaction among the partners is also believed to promote the development of trust

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(Greve & Ejersbo, 2002). Trust is important because it is conducive for the partners’ willingness to

take the necessary risks to engage in the partnership (Mayer, Davis & Schoorman, 1995). This is

especially relevant in a PPI where the end goal is often unknown at the outset thus requiring risk

willingness and continuous dialogue which is difficult if the partners are untrusting of each other.

The relation between trust and perceived outcome has proven to be correlated in previous partner-

ship studies (Edelenbos et al., 2007) and is thus likewise accounted for in the final hypothesis.

H4trust: Mutual trust between the partners is positively related to innovation in PPI.

Research design and methods The paper uses data from a survey among PPIs in the healthcare and social sectors in Denmark2. In

order to identify the total population of PPIs from which the respondents could be selected, a com-

prehensive mapping of PPIs was completed as no such list or overview existed at the time. First,

this process meant that previous reports on PPIs and websites for organizations that were expected

to list or fund PPI projects were reviewed while relevant public organizations at national, regional,

and local level were contacted for information on any ongoing or completed projects. Secondly, the

identified projects were continuously assessed by two researchers in terms of whether they could

adequately be characterized as PPIs by ensuring that each partnership has an innovative purpose and

involved both public and private organizations. Finally, 249 projects were selected for a final list

describing the title, involved partners, purpose and output, current status, social area, geographical

anchoring, and the source of project identification for each PPI (see Brogaard & Petersen, 2014).

The list of PPIs has been used to identify and contact respondents which further in-

creased the total number of known PPIs in the healthcare and social areas to 260 as some respond-

ents for instance were familiar with other PPIs. It has not been possible to identify the involved in-

dividual from all organizations on the list - which varies from 2-10 or more for each PPI - and thus

either send the survey to the full population of individuals or a random selection. Instead, from each

partnership the most involved public and private representative has been identified and invited to

participate as they are assumed to have the necessary knowledge to respond to the survey and in

order to cover both the public and private perspective. Acquiring this information entailed calling

and emailing the project leader or an organization from each partnership that could point out the

2 The survey was completed in collaboration between the Danish Institute for Local and Regional Government Re-search, Roskilde University, and the Danish Council for Public-Private Collaboration

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person most designated to, formal project leader of, responsible for, or whom spent the most time

on the project as well as trawling through websites and other public materials3. The final selection

of 497 respondents represents a diverse group of people such as hospital nurses, technical managers,

municipal project leaders, and researchers. It has not been possible to identify one public and one

private respondent for all PPIs but for the most part the strategy has been successful, see figure 4.

Figure 4 Sample strategy

The strategic sample means that the survey has been distributed among the entire known population

of PPIs. As the respondents represent the most involved public and private participants from the

PPIs they were assumed to be inclined to respond as seen in similar surveys (Klijn, Koppenjan &

Boer, 2014). To further activate the respondents reminder emails were sent out twice after the initial

distribution and phone calls were made to those whom after two reminders still had not completed

the survey. By the third and final week of the survey, a response rate of 60 % (see table 1) was

achieved which is higher than comparable surveys on PPPs that range from 12 % (Li, Akintoye,

Edwards, & Hardcastle, 2005) to 35 % (Ysa et al., 2014) and 46 % (Klijn, Koppenjan, & Boer,

2014) and 205 out of the 260 PPIs are represented by at least one respondent.

Table 1 Sample and responses

N Percentage

Total number of respondents 497 100 %

Completed responses (I) 217 43,7 %

Partial responses (P) 82 16 %

Refusal and break-off (R) 13 2,6 %

Non-contact (NC) 185 37,2 %

Response rate (I+P)/(I+P+R+NC) 299 60,2 % Note: Based on APPORs calculation and reporting of response rates 1 (The American Association for Public Opinion Research, 2008). See response, cooperation, refusal, and contact rates in table 5 in appendix. 3 The author acknowledges the indispensable help from Mia M. Jørgensen, Kiki Jørgensen, and Anna W. Westergaard in identifying respondents and thanks Cecilie Bræmer Müller and Leander Isaksen for sharing their list of PPIs.

Sample strategy

• 260 PPIs • 520 respondents • 260 public • 260 private

Sample process

• 260 PPIs • 14 PPIs only public

respondents (for one of these it is 2 public)

• 11 PPIs only private respondents

Survey distribution

• 260 PPIs • 497 respondents • 246 private • 251 public

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It is important to emphasize that the strategic selection of the most involved respondents implies a

non-probability which means that there are empirical limitations preventing inferences to the full

population of organizations and individuals involved in PPIs (Thomsen, 2012: 330) (see table 6 in

appendix). The 497 respondents were all asked to answer the same questions but specifically for the

named partnerships in which they had been involved on behalf of their organization which means

that the attitudes and answers from the survey are not general reflections but pertain to specific ex-

periences. The key variables from the survey are operationalized in the next sections and summa-

rized in table 3.

Dependent variable: Innovation

Predicting a nebulous concept such as innovation based on correlations between dependent and ex-

planatory variables from the same source of self-reported data survey can lead to inflated correla-

tions due to perception-based measurements and ill-defined criteria (common source bias, see An-

dersen, Heinesen, & Pedersen, 2015). This issue necessitates careful operationalization of survey

items and well-defined criteria where it is for instance avoided posing questions where the respond-

ents clearly have to assess their own performance thus potentially leading to a positive bias. In the

survey used for this study, the respondents were therefore not asked to assess achievement of inno-

vation in the partnership. Instead, those whom had previously stated in the survey that a product,

process, or a different solution had been developed in the PPI were asked the following question: Is

the developed solution being used today by the public partner in the PPI or by a different public

organization? This is a concrete and rather unique way of measuring innovation as it fulfills the

applied definition of innovation as development and implementation while reducing the respond-

ents’ subjective perception and self-evaluation. The respondents had the option of answering either

‘Yes’, ‘No’, ‘No but it is expected to soon’, or ‘Don’t know’ with the latter being coded as missing.

The variable is dichotomous with innovation achieved (= 1) in reference to cases in which innova-

tion is not achieved which include both negative response categories.

Explanatory variables: Management, innovation skills, trust, and institutional support

The operationalization of the independent variables from the survey is to some extent based on ex-

isting survey studies on the relationship between trust, management, support, and outcome in pub-

lic-private partnerships and networks. However, some of these studies have asked the respondents

to assess for instance the level of trust (Ysa, Sierra, & Esteve, 2014: appendix A) or the link be-

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tween trust and outcome (Edelenbos & Klijn, 2007: 33) thereby increasing possible common source

bias, cf. discussion above. Hence, a different approach has been taken in this study by operationali-

zating the concepts into more concrete and factual items. Based on the perspectives on metagovern-

ance presented earlier, management has been measured by asking the respondents the following

question: Was/is there an overall project leadership consisting of one or more persons to facilitate

the collaborative process and/or manage the PPI across the participating organizations? This rep-

resents a shared governance perspective as the respondents were selected because they were the

most involved and had the primary responsibility for their respective organizations’ participation in

the PPI. The variable is dichotomous for the presence (= 1) or absence (reference group) of cross-

organizational management. The explanatory variable of innovation competencies is based on the

following survey question: Have you participated in courses/education on innovation? The variable

is likewise dichotomous where the respondents whom selected one or more out of four different

options of courses or diplomas in innovation have all been coded as 1 for cases with formal skills in

reference to those whom selected the option of not having participated in any courses or diplomas.

Trust and institutional support are indexes constructed from factor analyses of survey items opera-

tionalizing the theoretical perspectives presented earlier in this paper, leaning especially on the op-

erationalization of trust developed by Mayer et al. (1995) and Edelenbos, Klijn, & Steijn (2007),

while for institutional support the respondents have been asked about relevant sources of support

within the organizations and partnership necessary for among other things access to resources and

exchange of knowledge, see table 2.

Table 2 Survey items constituting trust and institutional support

Items constituting the trust index Items constituting the institutional support index

The other organization only act according to their own and not the common interests of the partnership*. Your organization can expect that the other parties will do what has been agreed in the PPI. The other organizations in the PPI have the necessary professional/technical skills. There is frequent interaction (dialogue, meetings, pres-ence) among the public and private organizations in the PPI.

There is support among the top management in your or-ganization. There is support for the PPI with the nearest management in your organization. There is support among the other organizations in the PPI. There is support for the PPI among the participating em-ployees in your organization. There is support for the PPI among the participating us-ers/citizens.

*The scale for this item was reversed to match the other items before constructing the index

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Factor analyses confirmed that the items in both cases have strong associations with one underlying

component interpreted as trust and institutional support respectively (see table 8 and 9 in appendix).

Reliability analyses confirmed the robustness of the indexes with a Cronbach’s Alpha of 0,633 for

trust and 0,767 for institutional support - a high alpha (0,8) especially with only few items (Ho,

2013: 288). The items were all based on the same five-point Likert-scale ranging from ‘Strongly

agree’ to ‘Strongly disagree’ with a neutral middle option making it possible to add and divide them

by number to create a scale from 1-5 where high values indicate a high degree of trust or support.

Control variables

Based on previous research on partnerships and outcome, project phase as well as the respondents’

organizational background and role in the PPI are included as control variables (Klijn, Steijn, &

Edelenbos, 2010: 1082; Kort & Klijn, 2011: 623; Ysa et al., 2014: 644). A completed PPI might be

more likely to have achieved innovation and is included as a dummy variable for project phase

comparing the respondents whom characterized the PPI as completed compared to PPIs in progress

(reference group). Organizational background and role are each coded as dummy variables distin-

guishing public from private sector organizations (reference group), and project leaders from other

roles (reference group) in the PPIs as reported by the respondents4.

Table 3 Descriptive statistics for all variables

Type Variable N Min. Max. Mean Dependent variable Innovation (implementation of developed solutions) 187 0 1 0.51

Key explanatory

variables

Project management 240 0 1 0.89

Institutional support 171 1 5 4.44

Trust 188 1 5 3.94

Innovation competencies 221 0 1 0.65

Control variables Public organizations 299 0 1 0.59

Project leader in the PPI 221 0 1 0.46

PPI completed 249 0 1 0.46

4 The size of the organizations might also have an effect on the organization’s innovation abilities (Damanpour, 1992). A dummy variable comparing large organizations of 250 employees or more in reference to small and medium sized organizations (reference group) has been tested in the multivariate model but as it does not significantly contribute to the model or markedly change the effect of the explanatory variables, it is not included in the final analysis in order to increase the number of cases per variable.

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Logistic regression models

As the dependent variable is dichotomous a logistic regression model is applied with the purpose of

predicting the odds of achieving innovation compared to not achieving innovation for each case

(Peng, Lee, & Ingersoll, 2002). For a more intuitive interpretation in probabilities, the calculated

average marginal effect in percentage points is reported as well. The regression analyses are com-

pleted in three models in STATA. The first model is bivariate with the purpose of exploring each

explanatory variable as predictor of innovation without controlling for differences in other varia-

bles. The second model tests each independent variable holding the control variables constant to

check sensitivity towards changes in variables. The third model is a multivariate regression analysis

used for hypotheses testing which includes all variables with innovation as the predicted variable.

The independent variables have been checked for multicollinearity which shows tolerance values

well above 0.1 indicating no significant overlaps (see table 7 in appendix) (French, Moon, & Stan-

ley, 2004: 363), and an insignificant Hosmer and Lemeshow chi-square test of the difference be-

tween predicted and observed values indicates a good model fit (Peng, Lee, & Ingersoll, 2002: 6)

Findings

Table 4 displays the results of the three regression models with innovation as the predicted variable.

Models 1 and 2 are interpreted with caution as the influence of the other predictors is not controlled

for and they are therefore used for explorative purposes. In model 1, the bivariate analyses show

that innovation competencies are insignificant, but trust and institutional support have a significant

positive association with innovation. On average across cases, an increase in trust and institutional

support means that the likelihood of achieving innovation increases by approx. 10 and 13 percent-

age points respectively when the other variables are not controlled for. The presence of cross-

organizational management, on the other hand, has a negative association with innovation. The

probability of achieving innovation is reduced with 23 percentage points when cross-organizational

management is present compared to a PPI with no management. The positive association between

trust and outcome as well as institutional support and outcome are found in similar studies which

show that support from top-level management and trust between the partners increase the positive

perception of partnership outcome (Ysa et al., 2014). The negative impact of cross-organizational

management is, on the other hand, somewhat surprising although previous studies on PPPs recog-

nize that managing partnerships is difficult and some management strategies are not correlated with

outcomes (Edelenbos & Klijn, 2010).

16

Table 4 Logistic regression analysis with innovation as predicted variable Model 1a Model 1b Model 1c Model 1d Model 2a Model 2b Model 2c Model 2d Model 3

Odds ratio

(S.E.) Odds ratio

(S.E.) Odds ratio

(S.E.) Odds ratio

(S.E.) Odds ratio

(S.E.) Odds ratio

(S.E.) Odds ratio

(S.E.) Odds ratio

(S.E.) Odds ratio

(S.E.)

H1: Project management .376** (.191)

.471

(.251)

.629 (.426)

H2: Innovation competencies 1.253 (.411)

1.385 (.482)

2.251* (.972)

H3: Institutional support 1.679* (.502)

1.663 (.525)

1.682 (.608)

H4: Trust 1.502** (.320)

1.319 (.298)

1.317 (.325)

Control variables

Public sector .694

(.231) .634

(.208) .819

(.296) .569

(.201) .899

(.358)

Project completed 2.102** (.686)

2.172** (.710)

1.998** (.2969)

2.309*** (.795)

2.350** (.902)

PPI Project leader 1.872** (.607)

1.903** (.608)

1.922* (.675)

2.080** (.722)

1.860 (.722)

Model summary and statistics

N 182 173 146 156 168 171 142 154 132

Hosmer and Lemeshow χ2 4.69 3.94 16.43** 4.03 7.85

Model χ2 p-value .044** .492 .071* .052** .011*** .016** .028** .004*** .019**

Correctly predicted 53.8 % 53.2 % 60.3 % 56.4 % 61.9 % 60.8 % 66.2 % 63.6 % 68.2 %

Pseudo R2 .016 .002 .016 .032 .055 .051 .055 .071 .092

Note: *p<.10; **p<.05; p<.01*** Odds ratio indicate a negative relation when Exp (B) < 1,0.

17

Table 4 furthermore shows the results of testing the effect of the four predictors individually while

holding the control variables constant (model 2). In this case, none of the explanatory variables are

significant predictors of innovation, although institutional support is close to being significant at

p<0.1, and the direction of each variable is unchanged i.e. project management is negative. The

control variables of project completed and project leader are both significant and positive. The like-

lihood of achieving innovation increases with 17.5 percentage points when a PPI changes from be-

ing in progress to completed, while the likelihood of innovation increases by 15 percentage points

when assessed by a project leader in the PPI compared to other participants. Model 2 overall sug-

gests that there might be an interaction between the independent variables which is not accounted

for at this stage of the analysis while also showing the model’s sensitivity.

Finally, the multivariate results are displayed in table 4. The model suggests that only

innovation competencies constitute a significant (close to p<.05) and positive predictor of innova-

tion when controlling for the influence of trust, institutional support, cross-organizational manage-

ment as well as respondent and partnership characteristics. In fact, the odds of participants with

formal innovation skills achieving innovation in a PPI are 2,159 times greater than for participants

with no formal innovation competencies. In probabilities this means that the likelihood of achieving

innovation increases by 18 percentage points if the participants change from having no formal inno-

vation competencies to having innovation skills. Among the control variables, project phase has a

significant and positive association with innovation as in model 2.

The multivariate model confirms H2innovation skills, while hypotheses H1management,

H3institutional support, and H4trust should be rejected. Trust, institutional support, and project manage-

ment, which were insignificant in model 2, remain as such when the influence of all four predictors

and the control variables are held constant. However, institutional support is once again close to

being significant at p<0.1. A possible interpretation is that a very heterogeneous group of people in

a complex partnership calls for something more concrete and fundamental in the individual partici-

pants than trust and overall leadership which are factors relevant at the partnership level. Partici-

pants familiar with and trained in innovation processes might in effect be exercising a form of

shared governance driving the PPI forward through their commitment and knowhow in what it takes

to innovate no matter the presence of a designated cross-organizational leader. This is also support-

ed by the nearly significant effect of institutional support in all three models suggesting that com-

mitment from individuals in certain positions increases the likelihood of innovation possibly be-

18

cause they provide access to resources or professional knowledge. The implications of the results

are discussed in the next section.

Discussion and conclusion The paper set out to explore what drives innovation in PPIs based on data from a survey distributed

among the entire known population of 260 PPIs in the Danish social and healthcare sectors. Derived

from the literature on governance networks and collaborative innovation, four hypotheses have been

tested assuming a positive relationship between management, innovation skills, institutional sup-

port, and trust as the respective explanatory variables and innovation in PPIs as the dependent vari-

able. Exploratory bivariate regression models showed, first, that trust and organizational support

have a significant positive relationship with innovation, when the influence of other variables is not

controlled for, while management has a significant negative effect. Secondly, when each predictor

was tested again, this time holding all control variables constant, none of the explanatory variables

were significant which might suggest that there is an interaction between the independent variables

not accounted for in this model and that the model is sensitive to changes and thus should be inter-

preted with caution. Finally, when controlling for differences in the other explanatory variables as

well as in respondents’ background, role, and project phase in the multivariate regression analysis,

trust, management, and institutional support remain insignificant predictors of innovation while

formal innovation competencies significantly increases the likelihood of innovation by 18 percent-

age points, thus lending support to one out of four hypotheses.

The results of the regression analyses are somewhat surprising not least in the light of

previous PPI research where case studies have so far led to the conclusion that management, institu-

tional support, and trust enhance team performance, knowledge-sharing, and direct the partnership

towards innovative outcomes (Brogaard, 2015; Fuglsang, 2013; Nissen, Evald, & Clarke, 2014).

The findings should be interpreted with caution as the regression models show sensitivity to chang-

es in variables and is based on a relatively small number of cases. However, the final model can be

seen as support for the explanation that innovation partnerships imply uncertain and complex pro-

cesses which require specific skills in those responsible for and most involved in the innovation

process to increase the odds of successful outcome. Although the bivariate models cannot be used

for testing hypotheses and theoretical development, the results from the first two models likewise

offer perspectives for future PPI research. Explanations for the negative influence of project man-

agement may be found in the innovation and network governance perspective where research has

19

shown that traditional project management is not necessarily correlated with outcome due to the

complex and uncertain nature of a partnership (Edelenbos & Klijn, 2009). Moreover, the literature

on collaborative innovation suggests different roles for a leader of an innovation partnership in or-

der for the leadership to be effective (Torfing, 2012). These perspectives point to the potential in

exploring the influence of different management styles in PPI which has been beyond the scope of

this study.

Overall, the findings have empirical limitations due the non-probability sample but

nonetheless provide important new insights in regards to a large part of the known population of

PPIs in the Danish healthcare and social areas as well as the literature on partnerships and cross-

sector collaboration. First, previous survey-based research on outcomes in cross-sector networks

and partnerships has so far primarily looked into the impact of factors such as network complexity,

trust, and management either individually or together (Edelenbos & Klijn, 2007; Klijn, Steijn, &

Edelenbos, 2010; Ysa et al., 2014). The four hypotheses in this study contribute to the literature by

adding and developing key indicators for institutional support and innovation skills, thereby show-

ing that the influence of management and trust might be preceded by participant characteristics.

Moreover, compared to some of the previous survey-based studies, this paper has attempted to re-

duce common source bias by introducing new items and ways of operationalizing nebulous con-

cepts in a survey. Finally, the findings support the theoretical expectation that shared governance

exercised by the most involved and skilled individuals can have a positive impact similar to what

Edelenbos & Klijn (2009) conclude in regards to their concept of process management.

In part, the findings challenge fundamental assumptions in the partnership and net-

work literature when it comes to trust and management which have previously been found to be

significant and positive factors in a successful partnership. At the same time, this paper does not

attempt to deny the importance of these factors but instead provides a more comprehensive picture

of what is required in an innovation partnership. Based on the findings and theoretical arguments

put forward in this paper, there are grounds for further development of hypotheses in regards to the

alternative relations and interaction that might be in play between the different institutional and col-

laborative factors as well as the specific forms of management in PPIs which has been beyond the

scope of this paper.

20

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APPENDIX Calculation of response rate

Table 5 displays in detail the number of completed and partial responses as well as those respond-

ents whom have broken off while completing the survey and refused to participate or complete.

Finally, the number of non-contact is shown which represent the respondents invited to participate

in the survey but who have not responded or opened the survey. Based on these numbers, different

rates are calculated. The cooperation and contact rate is the percentage of respondents who have

been contacted and in some way have responded.

Table 5 Sample and responses

N Percentage Total number of respondents 497 100 %

Completed responses (I) 217 43,7 %

Partial responses (P) 82 16 %

Refusal and break-off (R) 13 2,6 %

Non-contact (NC) 185 37,2 %

Response rate (I+P/I+P+R+NC) 299 60,2 %

Cooperation rate (I/I+P+R) 312 69,6 %

Refusal rate (R/(I+P+NC+R) 13 2,6 %

Contact rate I+P+R/I+P+R+NC 312 62,8 %

Note: Based on APPORs recommended calculation and reporting of response, cooperation, refusal, and contact rates 1

(The American Association for Public Opinion Research, 2008).

Representativeness

Table 6 shows that there is a significant difference between the proportion of public respondents in

the sample and in the responses (although the practical difference in percentage is not striking) indi-

cating the empirical generalizable limitations in data.

Table 6 Binomial test of public and private respondents in sample and responses

Sector Sample Responses Exact Sig. (1-tailed) N Percentage N Percentage Public 251 50,5 % 175 58,5 % ,003* Private 246 49,5 % 124 41,5 % Total 497 100 % 299 100 % *p<.05

26

Multicollinearity

Table 7 documents the VIF and Tolerance values for all the independent variables using OLS re-

gression which shows that there is not significant overlap.

Table 7 Test statistics for multicollinearity using OLS regression Variable VIF 1/VIF (tolerance)

Project_management 1.11 0.897480

Innovation_competencies 1.09 0.919799

Trust 1.12 0.889682

Institutional support 1.10 0.905494

Public_organization 1.11 0.900034

PPI_Project leader 1.11 0.899478

Project_completed 1.03 0.973634

Dependent Variable: Has the developed solution been put to use in the public sector today? Note: Mean VIF 1.10; VIF < 5; 1/VIF < .1

Factor analyses

Table 8 and 9 show the factor loadings from the principal component analyses used to reduce data

and construct two of the main independent variables, trust and institutional support.

Table 8 Factor loadings for trust

Extraction Method: Principal Component Analysis. a. 1 components extracted.

Table 9 Factor loadings for institutional support

Extraction Method: Principal Component Analysis. a. 1 components extracted.

Component 1

The other organization only act according to their own and not the common interests of the partnership.

,615

Your organization can expect that the other parties will do what has been agreed in the PPI ,756 The other organizations in the PPI have the necessary professional/technical skills. ,724 There is frequent interaction (dialogue, meetings, presence) among the public and private organizations in the PPI.

,682

Component 1

There is support among the top management in your organization. ,727 There is support for the PPI with the nearest management in your organisation. ,782 There is support among the other organizations in the PPI. ,756 There is support for the PPI among the participating employees in your organization ,710 There is support for the PPI among the participating citizens/users ,624