Technovation 31 (2011) 615–626

Contents lists available at ScienceDirect

Technovation

0166-49

doi:10.1

n Tel.:

E-m

journal homepage: www.elsevier.com/locate/technovation

How to implement innovation policies through projects successfully

Maria Kapsali n

Umea School of Business, Umea University, 901 87 Umea, Sweden

a r t i c l e i n f o

Available online 8 September 2011

Keywords:

Innovation policy

Implementation instruments

Systems thinking

Innovation projects

Flexibility

72/$ - see front matter & 2011 Elsevier Ltd. A

016/j.technovation.2011.07.006

þ46 090 786 5441.

ail addresses: kapsalis.maria@gmail.com, mar

a b s t r a c t

This paper investigates the types of policy instruments responsible for the success of policy

implementation through projects. Based on evidence from 12 comparative multiple case-studies, the

paper provides an analytical insight from real practice on how and why different types of instruments

lead to either successful or unsuccessful projects. In particular, the key finding is that in order for

projects to implement policy successfully, policy instruments have to be designed based on specific

systems thinking constructs related to flexibility. The findings provide the crucial but missing holistic

conceptual direction for the development of implementation theory, which needs to overcome

conceptual fragmentation and polarization. The findings also provide the insight as to how instruments

really function which is essential to policy makers and project managers involved in public innovation

programs.

& 2011 Elsevier Ltd. All rights reserved.

1. Introduction

Faced by rising demand and capacity constraints in nationalhealthcare systems, the EU has established policies in relation toinnovation deployment, which because of the size and complexityof healthcare systems are best implemented through multi-project, multi-country programs (Jamieson and Morris, 2007).Despite the fact that these programs are elaborately designed anduse a variety of implementation instruments, their projects fail toachieve policy goals at a high rate. In this study it is contendedthat the actual function of the implementation instruments thathave been employed to control these projects is not well under-stood and as a result, the implementation instruments used areunsuitable for ensuring successful project performance. That is,these projects often fail because theory has not yet conceptua-lized the effects of policy implementation instruments upon theirmanagement.

The purpose of this paper is to address this crucial conceptualgap in the theory of policy implementation by explaining thecause-and-effect relation between policy instruments and projectperformance. The argument in this paper is that this causality canbe investigated by analyzing real examples of how different typesof instruments affect the management of similar types of innova-tion projects. With respect to this, evidence was gathered from12 cases to answer this question: Which types of policy implementa-

tion instruments contribute to the success of projects (why and how)?

ll rights reserved.

ia.kapsali@usbe.umu.se

The argument unfolds first by providing a discussion of policyimplementation theory in Section 2, pinpointing the gap regard-ing the design and the use of instruments, and second byproviding a comparison in Section 3 between the conventionaland the systemic perspectives, identifying the need for change inpolicy design regarding the instruments they employ. The com-parative analysis of 12 cases in Sections 5–7 explains why andhow conventional and systemic implementation instrumentsaffect the management of innovation projects differently, leadingto different outcomes. The conclusion highlights a new theoreticaldirection towards the design of flexible implementation instru-ments using systems thinking constructs.

The contribution of the study is twofold. First, it explains whysystemic instruments are more effective for successful imple-mentation through projects and provides in-depth insight as tohow instruments really function. Second, the systems thinkingconstructs that are suggested to create instruments are ideal todevelop empirical studies in implementation theory which canovercome the polarization and conceptual fragmentation inextant theory and the separation of implementation from policydesign.

2. Theoretical approaches to policy implementationinstruments

The different perspectives on the implementation of policyhave not generated a generalizable theory because they sufferfrom a lack of consensus regarding the factors for achievingsuccess as well as the measures and the analysis units to beadopted (Lee, 2011; Linton, 2002). In fact, the major limitations

M. Kapsali / Technovation 31 (2011) 615–626616

within extant empirical research are associated with the endoge-nuity of public R&D support and the selection bias that isseemingly involved in the implementation of programs (Lee,2011). That means most studies analyze a specific public R&Dprogram for a specific industry or country and those dealing withmulti-project, multi-country data are almost non-existent. Thelack of generalizable theory has been the primary obstacle toachieve a clear theoretical direction for further empirical analysis;this is also the reason why policy makers designing programs findit impractical to use research findings (Lee, 2011).

In addition to the lack of generalization, implementationtheory also suffers from polarization, as research studies examineimplementation in either top-down or bottom-up approaches.Top-down approaches ignore local agency and focus on control-ling actors through coercive and normative mechanisms, whereasbottom-up models take for granted that implementation agentswill comply because of the existence of remunerative andnormative mechanisms (Sabatier, 2007; Lane, 2000; Viale andGhiglione, 1998; Matland, 1995). In general, most studies prefer atop-down approach, which provides legitimacy to policy design,is easier to use when conducting research and simplifies theprocess of designing instruments (O’Toole and Meier, 2004;Rychetnik et al., 2002).

A by-product of polarization is the fact that the policy-makingand implementation processes are treated separately and thustheir relationship is rarely addressed (Saetren, 2005), renderingimplementation still marginalized in the study of public policydesign (Robichau and Lynn, 2009; Sabatier, 2007). In fact,implementation is often perceived as an afterthought of policy(Noble, 1999), and as a fairly mechanistic control process which isrational, linear, formal and predictable (Davies et al., 2005) whichis to be controlled through top-down efficiency instruments, suchas process measures (Boyne et al., 2002).

A further consequence of this phenomenon is that the numberof process measures being investigated by researchers grows(O’Toole, 2000), thereby inhibiting generalizability further. In factthe information on indicators and measures is so complex that itis easy to understand why implementation studies have had littledirect impact on the policy community (Nauwalers and Wintjes,2008). In practice this phenomenon is rife, for even thoughElmore and McDonnell (1987) identified some time ago thatthese measures need to be classified or simplified, this has yetto materialize. As a result, there is still no clear understanding ofhow different policy measures impact upon evolutionary andnon-linear innovation processes (Etzkowitz, 2003; Lepori, 2003).

In response to this phenomenon, a number of scholars havebeen arguing for some time that there needs to be a third-generation implementation approach which would tackle thediversity and normative differences in the field (Barrett, 2004;Goggin et al., 1990). So far the latest theoretical developmentshave been various deductive synthetic and contingent approaches,which although have tried to transcend the top-down/bottom-updichotomy they still lack cohesion and they also require furthermethodological development as well as robust theoretical testing(Freitas and Tunzelmann, 2008; O’Toole and Meier, 2004). Morespecifically, the main weaknesses of these approaches appear tobe their conceptual and methodological complexity, lack of solidempirical work (Jennings and Ewalt, 1998; Stoker, 1991; Gogginet al., 1990) and overreliance on best-practice models (Lynn, 1996;Overman and Boyd, 1994).

More recently implementation studies turned to networkapproaches (Meek, 2005; Linton, 2000), which challenged thecentrality of bureaucracy in policy. In this regard, networkslooked at the relationships in agent structures in order toinvestigate patterns of behavior, to analyze interdependencies,to construct best-practice models (Calia et al., 2007) and to

examine the work of the implementer from a social perspective(Johnston and Linton, 2000). However, consensus has not beenreached on how to conceptualize network phenomena surround-ing policy action (O’Toole, 2000).

Further deductive contributions to implementation researchhave come from the realm of policy diffusion studies whichfocused into the relative speed of and spatial relations in innova-tion programs (Walker, 1969), whilst there have been a fewinductive investigations on such matters as boundary translation,the scientification of politics and the politicization of science(O’Toole and Meier, 2004; Rychetnik et al., 2002; Weingart, 1999;Gould and Fernandez, 1989). However, the outcomes of theseapproaches have neither provided clearer generalizable insightsin relation to the specific causes of successful implementation,nor have they really overcome the dichotomy between top-downand bottom-up approaches, or the separation of implementationfrom policy-making.

A different direction to implementation was initially identifiedin the realms of strategic management: the strategy implementa-

tion through projects studies (Shenhar et al., 2007; Jaafari et al.,2004; Artto et al., 2004; Shenhar, 2004), which was developedmainly from research on strategic programs in private organiza-tions, attempted to link the project management (meso) levelwith the macro level of strategy-making. These studies revealedthat the reason for the lack of achievement in terms of strategicgoals was that implementation instruments were usually notdesigned in alignment with these goals.

In further support to the above argument, there is evidence inthree respects. Firstly, because innovation producer–user rela-tions have become more reciprocal and less hierarchical within aninnovation system, policy implementation is increasingly becom-ing more dependent on market relations. As a result, innovationpolicy is slowly adopting mediator and championship roles(Caerteling et al., 2011; Etzkowitz, 2003) a fact that has shiftedattention towards the design of instruments. Secondly, the linksbetween policy goals and implementation instruments areincreasingly becoming more unclear because of the diversity inthe way actors interpret both (Sabatier, 2007). This is because anysingle instrument is context-specific in terms of both its designand its application, so it suffers from a high degree of interpretiveflexibility (being perceived differently in time, place and by actor)and it cannot be easily isolated, tested, abstracted or generalized(Flanagan et al., 2011; Rametsteiner and Weiss, 2006). Coordinat-ing actors’ interaction and collaboration however is fraught withimperfect information and bounded rationality (Arnold, 2004).Following this rationale, the design of implementation instru-ments is amenable to instrumental rationality as it involves valuejudgments into what constitutes the boundaries of policy(Flanagan et al., 2011). Thirdly, because policy implementationis multi-layered, involving macro, meso and micro levels ofimplementation, it crosses many levels of interpretation, a factthat escalates the interpretive flexibility phenomenon. Hence theeffective design of implementation instruments has to satisfy notonly policy goals but also a complex ensemble of the goals andinterpretations of diverse actors, a fact that requires both verticalcontrol and horizontal coordination (relational) instruments(Milward and Provan, 2003).

Therefore there is a need to clarify the coordination function ofimplementation instruments within the boundaries betweenmultiple actors. For this reason it is important to gain in-depth

knowledge about the effects of different types of implementationinstruments upon actors’ behavior in order to develop newinstruments or improve extant ones. As a result, contemporarypolicy practice becomes more and more commensurate withinthe logic of systems thinking, which requires the design of both

horizontal interaction and vertical control mechanisms. A systems

M. Kapsali / Technovation 31 (2011) 615–626 617

approach combines downstream with upstream perspectives todevelop more ‘holistic’ policy instruments (Luukkonen andNedeva, 2010; Guan and Chen, 2010).

To follow on this argument, Section 3 contains a discussion onthe conceptualizations of instruments as conventional and assystemic, and their link to projects.

3. Comparing the conventional and the systemic approachesto implementation instruments

3.1. The conventional implementation instruments

The vast majority of implementation literature is focused ontop-down (hereafter conventional) instruments’ effects on mar-kets and on more ‘permanent’ organizations (a project is atemporary organization). This type of research merely describesthe attributes of conventional instruments which have not, as yet,been further developed into firm theoretical concepts as dis-cussed in the previous section (Nauwalers and Wintjes, 2008;O’Toole, 2000). Conceptually, conventional instruments areclearly separated from the policy goals, process, outcomes andstyle, directing analysis to one dimension of policy: control(Nohstedt and Hansen, 2010). Furthermore, conventional instru-ments are designed according to the stages in linear policymodels which are often misinterpreted or misused as prescriptiveor normative implementation frameworks (Weiss, 2000). Becauseof their emphasis on measurement, conventional instrumentsare considered useful for controlling opportunistic behavior,for keeping performance coherent and for providing a sense ofdirection (Edwards et al., 2005) therefore they are assumedby policy-makers to be sufficient for pursuing implemen-tation. As a result, current practice regarding the managementof project portfolios is to employ as instruments mostly top-downprocess and output measures expressed in the form of opera-tional metrics (Davis, 2007; Smits and Kuhlmann, 2004; Grabher,2002).

Most conventional instruments that dominate policy imple-mentation literature are either of an authoritative, capacity,symbolic or incentive function (Schneider and Ingram, 1990)and the operational metrics specifically targeting projects areexpressed usually in terms of strict numerable measures of time,cost and scope of activities (known as the ‘‘Iron Triangle’’,Atkinson, 1999) with the focus being mainly on project processoutputs rather than outcomes in relation to policy goals(Robichau and Lynn, 2009). Conventional instruments focus oncontrolling one project at a time or on regulating project bound-ary relations (within the project and with outside actors) usingmainly mandates, inducement and capacity measures andbureaucratic top-down structures aimed at exercising controlover the project process. A supranational policy portfolio tendsto be dominated by three types of conventional instruments:financial (subsidies, tax schemes), diffusion oriented (technologytransfer, mobility of researchers) and managerial (financial sup-port of small and medium sized enterprises involved in innova-tion processes).

The problems associated with conventional instruments aresalient in technology programs at supranational levels because itbecomes hard to evaluate the effectiveness of these instruments,since project outcomes are hard to measure and it is oftenimpossible to attribute them to policy goals (Guimon, 2011). It islikely that evaluating the success of instruments in deliveringpolicy goals needs to account for a starting point of integrationbetween instruments and goals at the design stage (Luukkonenand Nedeva, 2010). The obstacle is that instruments have to fitthe prevailing political ideology; creating new intermediaries or

forcing actors to change habits usually meets with resistance (vanLente et al., 2003).

On this point it can be argued that institutional rigiditiesimpose hurdles for the implementation of new policy instru-ments. In order to overcome the resistance and inertia thatfollows the use of instruments, policies employ co-functionalinstruments that are meant to strengthen the effect of each other.Hou and Brewer (2010) proved that policy instruments haveinteractive effects upon each other (both complementarities andtensions) and that after the introduction of a new instrument theoverall impact increases but the effect of older instruments issubsumed or displaced by the supplements; this phenomenon isrooted in the contemporaneity of the reinforcing instruments thatcan be effective only for a certain early time span. Lascoumes andLe Gales (2007) suggest that the effects that instruments produceupon each other are usually not considered when the goals thoseinstruments serve are designed. This evolutionary trajectory ofthe interdependence between instruments has not been ade-quately explained because of the preference of extant researchand practice on conventional instruments. Without such explana-tion policy cannot overcome the rigidities that actors pose to theapplication of implementation instruments.

In particular, because conventional instruments focus on onedimension of policy: the control of actors’ activities, they areinsufficient for identifying tensions or complementarities betweeninstruments and goals that can be studied better with multi-dimensional approaches (Nohstedt and Hansen, 2010; van Lenteet al., 2003). A multidimensional design of instruments (upstream/downstream and functional/relational) can help achieve a holisticunderstanding of implementation (Morgan, 2010; Weiss, 2000).Systemic approaches are multidimensional because they combinehorizontal interaction and vertical control perspectives, withattention paid to causal interactions and relations and the timelyadjustment of management to contingencies (Shenhar et al., 2002,2007; Grundy, 1998).

3.2. The systemic implementation instruments

At the heart of the systems approach is the concept of theopen-system, according to which all of its components (actors,organizations and instruments) are open to each other’s influencebecause they interact and relate through their boundaries(Rametsteiner and Weiss, 2006). As such, systems thinkingtranscends the limitations of linear models and explains inter-dependent and interactive non-linear processes (Etzkowitz, 2003;Kaufmann and Todtling, 2001). Thereby systems thinking canexplain how instruments function within both horizontal inter-action and vertical control, and it can do so through the use ofconstructs such as equifinality, multifinality, entropy, hierarchy,feedback, self-organization and relationality (Jackson, 2003).

Authorship on systemic instruments is underdeveloped,mainly because systems approaches are conceptual frameworksrather than one formal theory (Rametsteiner and Weiss, 2006)and because systemic constructs are framed in such general termsthat it has been difficult to use them as guides and tools for actualpolicymaking (Teubal, 2002). To date, proponents of systemsthinking have not yet operationalized the above constructs intometrics that can allow for the devising of appropriate instrumentsand this is the reason why systems thinking constructs do notappear in extant policy implementation theory (which usesmainly process outputs measures).

In contrast to conventional policy design, the systemic oneincludes both control and relational instruments and createsinstitutions of both accountability and trust (Koski et al., 2004;Elmore and McDonnell, 1987). Systemic instruments orientedtowards control are minimum critical specifications based on

M. Kapsali / Technovation 31 (2011) 615–626618

outcomes and not just process outputs, whilst relational instru-ments are mechanisms to encourage, reinforce and coordinateinteraction and learning, experimentation and networking. Inorder to design instruments that are systemic, policy needs toexplore the complementarities and tensions between the actors atboth the project and the network/cluster or program boundaries(Bartzokas and Teubal, 2002; Bellamy et al., 2001). These com-plementarities and tensions will be reflected within the design ofthe instrument bundles, which aims to exalt the complementa-rities or alleviate the tensions. In systemic designs, instrumentswithin the bundles are flexibly modified in order to target thewhole system in diverse ways (not just the processes) and torespond to change. The design of combinations, complementa-rities and tensions between the control and the relational instru-ments within each bundle would differ reflecting the differentproportions of coercion or support to be exerted upon the systemactors, creating a unique type of governance (Morgan, 2010;van Lente et al., 2003).

As a general rule, the more pluralistic the array of instrumentsin a bundle, the more capable the policy is to adjusting itsimplementation instruments to local needs (Arnold, 2004). This isan important issue since instruments act as gatekeepers, incorpor-ating agency within the boundaries in between actors (Kraemer,2006), therefore the way in which the instrument bundle isdesigned has an effect on the behavior of the actors (Smits andKuhlmann, 2004). In this way, relational instruments supplementthe control ones, thereby balancing control with flexibility duringimplementation (Shenhar et al., 2007; Soderlund, 2004; Shenharet al., 2002; Smits and Kuhlmann, 2004).

4. Research design

4.1. Comparative, embedded, multiple case studies

Most implementation studies analyze a specific public R&Dprogram for a specific industry or country and those dealing withmulti-project, multi-country data are almost non-existent (Lee,2011). This study addresses this vacuum by selecting two com-

parative embedded cases incorporating multiple case studies (Yin,2003). The two programs which were chosen as embedded caseswere both multi-project and multi-country programs. Eachembedded case corresponds to a healthcare innovation deploy-ment program coordinated by an FP5 policy. These programswere also chosen because they both had healthcare innovationdeployment as the main goal, similar timeframes and policycontext, but their main difference was that they used differentimplementation instruments. The rationale behind this choicewas that the two embedded cases had a lot in common in order to

Instruments

EU EARSSProgramme

EARSS A EARSS B EARSS C

EU AR Policy

Deployment

Project Management

Fig. 1. Structure of the EARSS (left) and the eTEN (rig

minimize the variations between them, but their significantdifference allows for the comparison of the effects that differentinstruments have on the implementation process.

Each embedded case consists of several sub-case studies:the first embedded case (EARSS) has three sub-case studies andthe second (eTEN) has nine sub-case studies (Fig. 1). The firstembedded case refers to the EU public health policy on anti-microbial resistance, which coordinated the European Antimicro-bial Resistance Surveillance System (EARSS) program aimed atdeploying a pan-European electronic epidemiology surveillancenetwork in member states. The second embedded case relates tothe eHealth policy which coordinated the eTEN (electronic TransEuropean Networks) program, which required projects to eithervalidate a market or create a viable venture to deploy telemedi-cine technologies. Both embedded cases included 12 sub-casestudies overall.

The chosen comparative embedded multiple case study method isa robust treatment for discovering suitable causal evidence todevelop new testable theory (Ragin, 2007). Multiple case studieswere chosen because they permit replication and extension whenthey are compared (Eisenhardt, 1991). Replication refers to theidentification of common patterns when individual cases are usedfor the independent corroboration of specific propositions; thiscorroboration helps researchers to perceive patterns more easily,thereby allowing for the elimination of chance associations. On theother hand, extension refers to the synthesis of the identifiedpatterns into a holistic picture that can then be used to identifynew constructs to develop extant theory. Comparative case studiesare suitable for exploratory research, when investigating causalmechanisms within complex circumstances where a phenomenonis dynamic, evolutionary and calls for an applied orientationdirected at improving practice (Eisenhardt and Graebner, 2007).In this study comparison is used to elicit understanding regardingthe causal mechanisms between policy implementation instru-ments and project management practice and outcomes (Yin, 2003;Rowley, 2002; Perry, 1998; Brannick and Roche, 1997). Thedesired outcome is to identify the constructs that will be the basisfor the development of new empirical measures to direct futureresearch on implementation (Meredith, 1998). This researchdesign is particularly strong in explaining the complex phenom-enon of policy implementation and the resultant theory is novel,testable and empirically valid (Eisenhardt, 1989).

4.2. Data collection and sources

The procedure undertaken involved first, the inspection of policyand project documentation such as official publications (legaldocuments, etc.), ex-ante and ex-post-evaluation reports andofficial websites, which were used to construct the background in

Instruments

eTENProgramme

AIDMANEURODONOREVITALIREMMAMEDASHIPMEDICATEMED-CONTINENTNIVEMESTELE-REMEDY

EU eHealth Policy

Project Management

Deployment

ht) embedded multiple case studies (the author).

M. Kapsali / Technovation 31 (2011) 615–626 619

each of the 12 sub-case studies. Armed with this knowledge,second, 31 semi-structured interviews in total were carried out,13 of which were with the EARSS project managers and laboratoriesheads for the first 3 sub-case studies and 18 interviews were withproject managers and participants in the eTEN projects for theremaining 9 sub-case studies.

4.3. Analysis process

Analysis was conducted according to the techniques suggested byMiles and Huberman (2002) regarding a process of first within-caseand second across-case comparisons. To begin with, after thedetailed descriptions of the 12 sub-case studies were constructed,the first categorization of data from interviewee responses wasconstructed using content analysis with NVivo. The data on projectmanagement tasks have been categorized as planning, communicat-ing and task control/coordination (Tables 1 and 2), implementationinstruments have been classified into two categories (conventionaland systemic), performance was categorized into outcomes andoutputs (Table 3) and the project success was categorized into the

Table 2Corroborating patterns in eTEN project management tasks (based on empirical data).

Project manager tasks Method Explanation

Planning Prescriptive, top-downplans

The project ma

plans—project

partners—chan

Communication Infocracy (standardizedcommunicationprocedures)

Focus on exter

– diverse partn

participation r

Task control and

coordination

Loose task control processoriented

Low at operati

project teams

Table 3Comparing the findings from both embedded cases (based on empirical data).

Policy

Strategic goals Implementation instruments

EARSS Stimulate

innovation

deployment

through

collaborative

projects

Systemic—provision of resources,

organize collaboration through

interaction and monitoring of results,

flexibility to manage, learn,

communicate, experiment and network

eTEN Traditional – financial and managerial

instruments – monitoring of the

managerial process through participation

rules and operational criteria

a Ceremonial deployment refers to the ritualistic–symbolic fashion in which proje

evaluations, but these outputs did not really represent the actual large scale of marke

Table 1Corroborating patterns in EARSS project manager tasks (based on empirical data).

Project manager tasks Method Explanation

Planning Plan as they go The project ma

process output

on the course

Communication Boundary management Main project m

manager comm

network, collea

Task control and

coordination

Loose task control outputoriented

Low at the ope

standardization

actual deployment of technology and the management of contin-gencies (Table 4). Subsequently, the categorized data were trans-ferred into comparative matrices and through data reductiontechniques the common categories within the embedded cases wereidentified. The next stage involved looking for corroborating patternsfirst within the categories in each embedded case (amongst the sub-case studies), and then by corroborating these patterns across thetwo embedded cases (Patton, 1997). The final set of patterns wastransferred into chains of causality to discover cause-and-effectfactors between instruments and project outcomes. Summaries ofthe resultant causal factors are registered in Tables 1–4.

5. Case study 1: the antimicrobial resistance policyand the EARSS projects

Section 5.1 provides background information on the policy andthen Section 5.2 contains a discussion on the instrumentsemployed. Finally, in Section 5.3 the management and outcomesof the EARSS projects are evaluated.

nager satisfies contract requirements/compromises tasks to fit WBS

managers have limited negotiation power with both EU and consortium

ge aversion

nal communication with the clients – limited communication with other projects

er objectives – distance between participants/dictated by contract and

ules. Other project interfaces (e.g. users) are marginalized

onal level because the project managers did not have the leverage to control the

– fulfill the contract – diverse partner objectives inhibit task control

Project management Outputs Outcomes

Systemic—focus on

mediating between

different stakeholder

boundaries to achieve

the project goals

Compromise goals

and efficiency

Average

deployment

(differing according

to project)

Normative—focus on

managing the boundary

with the sponsor to pass

evaluation

Compromise goals

and effectiveness

Ceremoniala

deployment

ct outputs (as in the satisfying of project performance criteria) were presented in

t deployment (outcomes) in reality.

nager gives output reports with aggregated data on the project outcomes not

s. Plans are flexible with certain focal goals and then there is flexibility to decide

of action

anager tasks throughout the project. Both formal and informal. The project

unicates through the boundaries with the (national and EU) government, the

gues and promotes the network to laboratories (3 interfaces)

rational level because the project managers did not have the leverage to enforce

of data management on laboratories or control over resourcing

Table 4Comparison of the successful completion of the projects between the two programs, success being defined in terms of achieving deployment of technology in the market

and the nature and management of change (based on empirical data).

Outcome is it deployed Nature of changes in the plans and activities Dealing with change

Case EARSS

1 Yes mostly Plans are emergent—specific for the situation Adapting—seeking assistance from other

professionals

2 Yes low Plans are emergent—specific for the situation Cost and diversity of professional practice

3 No—very low Plans are emergent – but more formal – not frequent

boundary management with laboratories

Cost, diversity of professional practice and

diverse strategic plans

Case eTEN

1 No Incremental development—no major contingencies Not utilizing change

2 No Trivial—technical ‘‘Inefficient’’ management (that led to

problems with task and technical completion)

as in the lack of contingency planning and

effective change management

3 No 3 Months extension for deliverables

4 No 6 Months delay—had to change PM in the first nine

months

5 No Bad planning of WP and loss of technical objective

6 No 6 Months extension the technical component did not

work

Communication procedures and with the

sponsor procedures not flexible enough

7 No Bad planning—unrealistic expectations

8 Yes A lot of delays—friction with administration in

hospital

9 Yes partially Plan generally successful—minor changes Market changes did not allow full deployment

but product is commercially released

M. Kapsali / Technovation 31 (2011) 615–626620

5.1. The antimicrobial resistance policy

Prior to the FP5, EU public health policy was conducted by anuncoordinated ensemble of dispersed institutional structures andwas rather restricted by the principle of subsidiarity (member

states still have their autonomy in relation to several key policies).As a consequence, although there were a number of initiativesand programs, they could not amount to a comprehensive EUpublic health policy. Moreover, the design of these programs hadseveral inherent weaknesses, such as a lack of coherent goalsand detailed implementation objectives, vague disseminationtechniques and a selection process for projects, which lackedthe rigor of peer review and was concentrated in the hands of theCommission.

In 1998, with the introduction of FP5, the structure of EU publichealth policy changed from being disease-based to priority-based inorder to establish more comprehensive goals for their projectportfolios. As a part of the new policy, the EU legislated onantimicrobial resistance (hereafter AR) mainly through the Commu-nity Strategy against antimicrobial resistance (COM(2001)333).AR was declared to be the number one public health threat andconsequently it was decided that participation in a designated ARsurveillance network was mandatory for all member states. To createa system of close cooperation and effective coordination of routineand emergency surveillance between member states, a decisionwas taken (Decisions 2119/98/EC and 2000/96/EC) to create 17surveillance networks of specific communicable diseases to cut acrossnational networks; the designated AR one is called the EuropeanAntimicrobial Resistance Surveillance System (EARSS). Initially,specific coordinators were chosen to supervise each national network,but because of the complexity that emerged, which in particularresulted in unmanaged interdependence amongst the national net-works, the EU Council of Ministers agreed in 2005 to create a newEuropean Centre for Disease Prevention and Control (ECDC) tocoordinate all of them.

5.2. The EARSS program (policy goals and implementation

instruments)

The EARSS program goals were set up by the specialistprofessionals that formed the program management team (here-after EARSS MT) at the ECDC. Subsequently, in order to design the

program goals and instruments the EARSS MT consulted with thepublic health experts who were managing national AR epidemiol-ogy networks. Microbiologists and epidemiologists alreadyworking on AR were invited to join in as advisors as well, withthe overall aim of involving as many public health expertsacross the community as possible. The managers of the nationalEARSS projects were responsible for realizing the goals of theprogram which were mainly: (a) the recruitment of laboratories(expansion of participation and use of protocols), (b) the operationof the network (data collection and analysis) and (c) the deploy-ment of the electronic network (encouraging electronic datasubmission). The managers were also responsible for the promo-tion of AR policies to the political echelons of member states.

The national projects were the responsibility of the projectmanagers to setup and run, with their right of participation in theprogram depending on the completion of certain thresholds, suchas achieving 25% coverage of total national laboratory population,4 aggregate reports a year, etc. These thresholds were acting asminimum critical specifications and had the form of flexible outputtargets. Project time and cost were constraining factors, but theywere not the criteria used to evaluate and monitor the projects,whilst these were the scope, quality and reliability of data collectedby the national networks. The EARSS MT also focused on support-ing the newly formed community of expert project managers byproviding them with technical tools, expertise, some funding andopportunities for collaboration. Regarding the foremost, technicaland electronic tools for deployment of the network were provided,such as software and protocols for laboratory standardization, buttheir use by the laboratory operatives was voluntary.

The implementation rationale behind EARSS was to workthrough existing epidemiology networks with minimum interven-

tion in the national surveillance infrastructures thereby causing aminimum level of disruption in the participating laboratories.Further, the EARSS MT measured performance on the minimumcritical specifications and did not concern itself with the manage-rial process. The reasons for this non-invasive implementationapproach were first, because there was great diversity of labora-tory practices and of operational capacity in member states’electronic surveillance infrastructures, and second because theEU lacked the capability of enforcing public health legislation onthe member states; both reasons made it impossible to coordinateimplementation centrally.

M. Kapsali / Technovation 31 (2011) 615–626 621

The success of the EARSS pilot (1998–1999) encouraged severalcountries to establish or to update their national AR surveillancesystems and consequently the expansion of the network went fromstrength to strength in terms of both laboratory and countrymemberships. However, some national EARSS networks sufferedmore than others from lower electronic deployment, which overallranged from only 15% to 16% by the end of the pilot and this figureremained fairly stagnant after that. This is because the implemen-tation of new practice depended on the voluntary adoption at thelaboratory level. In addition, national public health systems werenot obliged to set up electronic surveillance systems althoughthey were obliged to participate in the EARSS network. In realitymember states displayed varying levels of commitment and useddifferent mechanisms to implement the EU AR policy and as a resultthe national networks achieved diverse levels of deployment, asituation that is elucidated further through the within-case com-parison of the three sub-case studies analyzed in Section 5.3: EARSSA, B and C.

5.3. The EARSS projects and their management (within case

comparison)

Regarding EARSS A, there was no official national AR policy tosupport the EARSS project and implementation depended uponthe project manager’s lobbying of politicians for the setup andongoing support of a new national AR center. Implementation alsodepended upon the project manager personally motivating labora-tory heads to participate in the electronic network. This approachworked well, with participation reaching quite impressive levels;however, there was some inconsistency in data collection becauseof poor lab resourcing. In this regard, the laboratories were poorlyresourced in electronic resources by the government and theregional health authorities and they had to request the nationalAR center to provide support for their overstretched operations.Therefore regarding its outputs EARSS A succeeded in deliveringall its goals and in particular goal—(a) network expansions werevery successful whilst it had to make some compromise betweengoals, (b) operation and (c) electronic deployment.

By contrast, regarding EARSS B, a national AR policy wasalready in place which did not endorse fully the objectives ofthe EU policy and which did not have a comprehensive imple-mentation plan, this being delegated to the national public healthagency. In addition, the regional health authorities who wereresponsible for resourcing laboratories were not involved inimplementation and moreover, they were beyond the control ofthe national agency. In addition to the problem of overstretchedcapacity, laboratories used different standardization protocolsand electronic networks, others than those supported by theEARSS MT. Subsequently, given that AR was not considered apriority by the government at the time, a hands-off approachregarding implementation emerged. In sum, the project managerscould not approach all the laboratory heads informally or providethem with resources and as a consequence the networks grewslowly, although satisfied the minimum specifications in the threeprogram goals.

Finally, during EARSS C the government set up a national ARstrategy which endorsed the EU’s AR goals in two ways: first,laboratory participation in the EARSS network was deemedmandatory and second, there was a plan made to standardizeoperational protocols across the laboratories according to EUspecifications. In addition to this political endorsement, theproject manager used regular formal and informal boundaryactivities to bring the laboratory professionals together in con-ferences, training sessions and meetings so as to educate themin using the network and to provide follow-up support. Thisapproach had the best results of the three cases in terms of goals

(a) network expansion and (b) operation, but electronic deploy-ment (goal c) although successful was still lower than anticipatedowing to the fact that laboratory capacity was still stretched.

The project managers’ role in all three cases was found to bethat of a mediator who negotiated between the policy and thelaboratory boundaries, and made adjustments to implementationactivities making compromises between the practical needs of thenetwork stakeholders and the program goals. In effect, the projectmanagers worked in a systemic fashion, managing and adjustingboth activities and relationships (Table 1). Their style of manage-ment though differed because of two factors. Firstly, the projectmanagers had to avoid being over obtrusive when working withthe laboratories, in order to encourage willing participants. Thismeant that the project managers had to settle for the laboratoriesparticipating in the data collection by any means they could,given the limited resources they had. Therefore making compro-mises amongst the program goals was linked to the behavior ofthe laboratories; for example if the laboratories were pushed intotaking up extra electronic activities, they might report lowerquality data just to get the job done (which they sometimes did).Secondly, the managers had to make different compromisesbecause of the differences in the infrastructures: standardizationand operational methodologies protocols and electronic equip-ment between laboratories in national systems.

The project managers had to prioritize amongst the level ofnetwork participation, the quality of data reported, the reliabilityof reports and the deployment of software-protocols. For instance,although in EARSS A there were strenuous efforts to encouragemaximum adoption of the software in the laboratories, thisadoption was compromised by the lack of resource. By contrast,in EARSS C the laboratory heads were actively supported but alsoforced by mandatory policy, whereas EARSS B managers were notenthusiastic about EU software and protocols and instead theydecided to develop their own in order to help laboratories.

Therefore, ongoing prioritizing and compromises had to bemade by the project managers because there were tensionsbetween the goals in the policy handed down to them, a situationthat is certainly not uncommon in innovative project settings.Despite these stretches, diversity and the gaps in national policiesand infrastructures, the EARSS network has been expandingenough to produce workable aggregate surveillance results from1998 up to the present day and this can be attributed to theflexibility the project managers were awarded by the way theimplementation instruments were designed into the policy.

6. Case study 2: the eHealth policy and eTEN projects

Section 6.1 provides background information on the policyand then Section 6.2 contains a discussion on the instrumentsemployed. Finally, Section 6.3 looks at the management of theeTEN projects.

6.1. The eHealth policy

The EU innovation strategy during the FP5 aimed to support theemergence and integration of competitive national markets. Therationale was that by supporting collaborative innovation projects,demand would be identified and enterprises would emerge fromthe extant fragmented systems that would create networks andclusters eventually forging new markets. Nevertheless, it wasrecognized that there were substantial obstacles in achieving thisgoal, for although EU institutions have increasingly taken a post-national character (converging decision-making power at the supra-

national level, Caracostas and Soete, 1997), at the same time thepower of implementation of EU institutions was limited by the rule

M. Kapsali / Technovation 31 (2011) 615–626622

of subsidiarity (member states still have their autonomy in relation to

several key policies). As a consequence, although the EU Commis-sion could centrally run the program as a whole, they were unableto control implementation at the local settings (Borras, 2003). As aresult no significant infrastructure convergence took place butinstead a multi-level system emerged which included on the onehand the substitution of weak national policies in countries with-out strong infrastructures and on the other the emergence ofmarkets which were fed by EU funding (Banchoff, 2002; Moussis,2005; Banda, 2002).

In this regard, in some national innovation systems the EUpolicy was used to cover for the lack of an official nationalinnovation policy. Under these circumstances, implementationwas usually on a small, local scale owing to the lack of empow-ered regional authorities, clear information provision and coher-ent infrastructures. In other cases, the national innovation policiesfocused on the needs of their internal markets and thus the EUpolicy was seen as providing an opportunity for transnationalcooperation, in particular in relation to specialized technologiesor the development of foreign markets.

Although it was clearly stated in EU Commission documents(e.g. COM(2003)226, OM(2003)112) that there was a need for a‘‘broad and systemic’’ approach to innovation, one incorporatingindustrial, enterprise and research policies, the implementationrationale was based on Framework Programs (FPs) that were top-down, rule-based conventional instruments, which embodied therationale of managing the largest possible number of projectsat the lowest cost. In this regard, the Commission standardizedand bureaucratized the monitoring and evaluation processes(infocracy) of FPs since 1982, under which projects were underperiodic and standardized controls from evaluators, as it wasconsidered that this method lowered the costs and risks ofprogram coordination (Wigzell, 2002; Levy, 2000).

The FP5 had four thematic priorities, one of which was tocreate a user friendly information society through funding differ-ent types of technology programs (research–development–deployment), one of which aiming at the improvement of health-care services (eHealth). The eHealth policy stream of FP5 wascoordinated by the Health Unit of the ‘Systems and Services forthe Citizen’ Directorate. The focus was to coordinate co-operativeclusters of healthcare technology projects to help healthcareproviders and administrations deliver the best possible eHealthpackages to Europe’s citizens. The objective of eHealth was tosupport people doing R&D involving IT and health (such asinteractive and ubiquitous IST services, remote telemedicine andtelecare technologies), or interested in applying the results of such

research (deployment). Part of the bundle of programs run undereHealth was the eTEN program.

6.2. The eTEN program (policy goals and implementation

instruments)

The eTEN (electronic Trans European Networks) programincluded 26 projects. The goal of eTEN was to support thedeployment of mature electronic healthcare technologies by EUmarkets, through the funding of either the validation or themarketization phases of start-ups. Therefore, the eTEN programaimed at projects moving on from a business case (a good serviceidea) to a business plan (to put the idea into practice-market-ization), based on existing or recently identified demand for thesehealthcare technologies (validation). Furthermore, the eTEN did

not provide funding for new scientific research and in fact, theexplicit conditions stated that there should be a very small pro-portion of researchers participating as well as that any technicaltrials should be strictly geared towards the customization of

technology. The main purpose was to support projects that wouldend up setting up a venture to market these technologies.

The implementation instruments of the eTEN were controloriented, as dictated by the Commission: the starting point beinga clear business plan, and an accompanying investment plan,along with the deployment of monitoring-evaluation proceduresbased on PMBOK (a Guide to the Project Management Body of

Knowledge, an internationally recognized set of standards pub-lished by the Project Management Institute), which includescommunication protocols that impose both participation rulesupon consortiums and pre-specified performance targets of theproject processes. The projects had to go through periodic reviewswhilst the procedure for any changes in the planned activities wasadmittedly long. In addition there were no opportunities fornetworking amongst the projects.

6.3. The eTEN projects and their management (within case

comparison)

Despite the successful conclusion of the majority of eTENprojects, only a fraction of them finished with an actual venturethat marketed the technology; most of them produced some kindof market validation and a business plan. The first reason for thiswas the fact that the eTEN program provided a choice betweentwo goals (either validation of the existence of a market for aproduct or real deployment) which allowed most projects (95% inthe specific population from which the sample originates) to optfor achieving the easier goal (validation) in preference to a realventure. The second reason was that because the focus ofevaluation was on measuring project efficiency according toplans, project managers were restricted in two ways: firstly, theproject managers could not cross the boundary with the programmanagement and get involved in the design of the goals andinstruments and secondly, the project managers did not manageto exert the power to form a group identity, thereby being unableto coordinate the tasks of the participants more effectively. Inaddition, the procedures restricted the levels of flexibility to makechanges that project managers should avail themselves in orderto deal effectively with the contingencies. Consequently, eTENmanagers frequently focused on form filling exercises and any-thing that deviated from the plans was avoided or ignored. Inother words the managers focused on exhibiting that the projectwas carried out efficiently and that the evaluation objectives werebeing met (Table 2). In some cases it was reported that themanagers were marginalized by their own team and in twoprojects they were specifically selected to handle administrationtasks and not to ‘interfere’ with the running of the work packages.

The above had several consequences for group dynamicswhich were observed right from the inception of many of theseprojects (Table 2). For instance, because the planning method wasbased on work breakdown structures, the work packages werecarried out almost independently of each other’s input and as aresult a pattern emerged of diverse/distant teams that rarelycommunicated. Related to this, the participation rules placingrestrictions on who should be invited to participate, although intheory aimed at supporting collaboration within project net-works, in practice they were hindering the effective rolling outof close interdisciplinary work. More specifically, there was thecondition that at least two members came from a differentcountry and this meant that sometimes a more suitable domesticcandidate was passed over so as to fulfill the specification. Theresult was the creation of research ‘islands’ which were notoptimally effective. Moreover, in many cases project ‘rule breach-

ing’ emerged, because the consortiums consisted of a greaternumber of researchers than that dictated in the program rules,which shifted the focus of project activities from the

M. Kapsali / Technovation 31 (2011) 615–626 623

customization of technologies to user needs to the continuoustesting and modification of the technologies for their sake of theirown development, or for exhibiting that the technologies worked.

Therefore the projects failed to market the technologiesbecause first the managers were unable to manage changes andsecond because the managers could not control the direction ofthe project and the participants followed their own researchinterests. This situation resulted in the project outcomes beinginconsistent with the program goals and ironically with theprojects not completely complying with the rules despite, orbecause of, the inflexible monitoring through standardized con-trol instruments.

In essence the implementation instruments of the eTENprogram did not allow the project managers to manage: this lackof flexibility in managerial activities resulted in weak leadershipand in-group/task coordination problems and loss of focus. Givenmanagers focused heavily on fulfilling the process specifications,they were unable to work through boundaries and in particularworking with their markets and making changes in activities. Lastbut not the least, because the goals were optional perhapsunderstandably most project groups chose the easiest, renderingimplementation instruments ineffective.

7. Discussion of findings—comparative analysis acrossembedded cases

This study aimed at identifying the effects of policy imple-mentation instruments upon project performance. The researchquestion was: Which types of policy implementation instruments

contribute to more successful projects (why and how)? To answerthis question two EU multi-project and multi-country programswere chosen as embedded cases, each corresponding to a health-care innovation deployment FP5 policy. These programs hadhealthcare innovation deployment as the main goal, similartimeframes and policy context, but their main difference wasthat they used different implementation instruments.

In Sections 5.1 and 6.1 there was a brief discussion on each ofthe policies’ goals and structures, where it emerged that bothpolicies had similar goals: to stimulate change and deployment ofhealthcare innovation by users. Moreover, both policies hadsimilar structural issues: they were bound by subsidiarity andboth addressed fragmented, diverse or underdeveloped nationalinfrastructures with stretched capacities. It was found that bothpolicies had goals that were either optional or partially in-tension.On the one hand the eTEN project managers were given an optionbetween validation or deployment, with the former goal being byfar the easier option, whereas on the other hand, EARSS projectmanagers had to implement three goals: expansion of the net-works, data collection and the deployment of an electronic grid.

Subsequently Sections 5.2 and 6.2 discussed the policies’ instru-ments. In relation to these, the EARSS program used systemicinstruments, including both performance control (minimum criticalspecifications) and relational instruments. Consequently, there wereopportunities for collaboration plus sufficient room to managethrough the boundaries of the project with the users and withinthe project team, as well as having the flexibility to deal with changein plans. By contrast, the eTEN program used conventional instru-ments embedded in standardized evaluation procedures and hencethe system was rigid, with little or no evidence of boundarymanagement and effective provisions for change management.

In Sections 5.3 and 6.3 the management of the projects wasdescribed (see Tables 1 and 2 and also the results of theircomparison in Table 3). The EARSS projects were successful inachieving all the goals, with the caveat of having to make someprioritization and compromise in relation to some of them. The

EARSS subjects explained how they participated in the establish-ment of the program goals with the EARSS MT and how theymanaged their individual projects in ways that suited their localsystems and users; thereby each of the EARSS projects hadvarying levels of resources and yet, within an acceptable varia-tion, they managed to fulfill their goals. It would have been evenmore beneficial for the projects if policy used more controlinstruments not aimed at managing the projects as such, but fordealing with resource support or standardization of laboratorypractices in the infrastructure.

The eTEN projects were at the other end of the spectrum, whereconventional instruments were being used to monitor and controltheir process (Table 3). Consequently, in the majority of cases therole of the project managers ended up being one where they had toexhibit compliance to the monitoring requirements and to do sothey prioritized administrative tasks at the expense of pursuingmarketization. Management focused at controlling change so theprojects did not deviate from the plan and as a consequence theproject managers were unable to influence the behavior withinthe projects and adjust to the market needs, individual interestsprevailed and project coordination became weak.

How can these marked differences in project outcomes beexplained? When the findings from all 12 projects were comparedit was very clearly revealed that there was a positive relationbetween the employment of systemic instruments with success-ful project outcomes and in most cases of failure a loss ofmanagerial control over the projects related to conventionalinstruments. The managers who used a more flexible systemicapproach (the EARSS) were the most successful ones in achievingproject goals. By contrast, the eTEN projects had higher levels offailure which can be attributed to the lack of flexibility inhandling operational change and boundary management activ-ities with users, stakeholders and project members. Therefore thelink between project performance and instruments depended onthe levels of flexibility to manage change and boundary relations(Table 4).

In sum, project flexibility emerges as being the crucial factorfor the successful implementation of policy. Evidence from all 12case studies proves that flexibility has to be embedded into policydesign by the form of systemic instruments in order to achievepolicy goals successfully through projects.

8. Conclusion and future research direction

The purpose of this paper was to address the gap in thetheories of policy implementation by explaining the causalitybetween policy instruments and project performance. The argu-ment in this paper is that this causality can be investigated byanalyzing real examples of how different types of instrumentsaffect the management of similar types of innovation projects,with the premise being that effective project management willlead to successful policy implementation. With respect to this,evidence was gathered from 12 multiple cases to answer thisresearch question: Which types of policy implementation instru-

ments contribute to the success of projects (why and how)?

The context of the study was two innovation deploymentpolicies funded by EU FP5, both of which comprised highlycomplex and powerful contexts (healthcare) that involved supra-national and national policy systems and as such presentedserious challenges to project management. Subsequent analysisrevealed that the two policies had used polar opposite instru-ments (conventional vs. systemic), which had a marked differenceon their effects upon the management of their projects. That is theprojects subjected to the systemic instruments in the EARSSprogram by far out-performed the eTEN projects that were

M. Kapsali / Technovation 31 (2011) 615–626624

subjected to conventional ones. On further investigation itemerged that systemic instruments allowed for greater flexibilityin relation to the management of change and boundary activities.In other words project managers were able to cross boundariesand manage relations with users and collaborators, makingchanges to their plans and activities as and when they saw fitthe local reality and prioritizing goals to achieve better results. Bycontrast, the eTEN managers were restricted by the conventionalinstruments, with no room for maneuver, causing group coordi-nation problems and alienation from the user groups and even-tually not achieving the program goal. Therefore, the conclusion isthat when flexibility is afforded through systemic instrumentsthen there is a higher probability of successful policy implemen-tation because projects achieve policy goals.

8.1. A new conceptual direction in policy implementation research

Extant policy implementation theory suffers from a crucialconceptual gap. First, previous studies provide a fragmented imageof policy implementation since they analyze different levels of thesystem separately, restrain their analyses on one-country/industrysamples, and use diverse measures in their analyses, in which theybecome so immersed that they still lack the holistic-macro, ‘‘heli-copter’’ view needed to investigate this issue as has been identifiedby Mazmanian and Sabatier some time ago (Mazmanian andSabatier, 1980). The result of this fragmentation is the lack ofgeneralization and the polarization of theory in top-down/bottom-up approaches. A consequence of this polarization comes down tothe separation of policy-making from implementation which usuallyresults in the design of instruments that are not suitable either fortheir context they are applied to, or to the policy goals. Theseweaknesses in extant study render theory unable to have an impacton policy design. Second, most studies analyze a specific public R&Dprogram for a specific industry or country and those dealing withmulti-project, multi-country data are almost non-existent. Various

Projectefficiency:control ofactivities

Projecteffectiveness

Achievingthe goals

Leadershipthroughproject

boundaries

Flexibility

Policy-programme goals Implementationinstruments

Fig. 2. The central role of flexibility, which is the critical ingredient in the

interdependence between the policy’s goals and implementation instruments

and the project’s outputs, outcomes and project leadership (the author).

Policy implementation:control and relational

instruments

Systems thFlexibility t

the equificonstr

Fig. 3. Use of systemic flexibility that links policy and project ma

approaches have not solved these issues and the development ofpolicy implementation theory seems to be repeating the samepatterns.

In order to address this gap and develop implementationtheory further, studies ought to provide a new direction from aholistic perspective (Robichau and Lynn, 2009; Sabatier, 2007).The difference between this study and previous ones is that itprovides this direction as it uses the systems thinking perspectiveto overcome the theoretical polarization and fragmentation thatare prominent in the field. This study reveals the interdependen-cies between policy goals, implementation instruments and themanagement of projects and suggests this essential direction tobase further development of instruments upon systems thinkingconstructs; to that extent this study offers an original contribu-tion to the field of policy implementation. And it does so byanalyzing multi-country, multi-project policies, addressing thismethodological gap in other studies.

Therefore, this study directs towards the use of systems thinkingconstructs related to flexibility which offers the opportunity of aholistic design of implementation. More specifically, flexibility isimportant for the development of policy implementation theorybecause it allows for the combatable design of the interdependencebetween policy goals, instruments and the inner workings of theproject, which the evidence from the case studies has shown isnecessary for successful policy implementation (Fig. 2).

8.1.1. Proposed construct for flexible instruments

Flexibility is a concept that has been conceptualized oroperationalized in manufacturing and service systems designbut not in projects and policy design. Systems thinking providesa variety of concepts at multiple levels of abstraction such asequifinality, multifinality, entropy, hierarchy, feedback and self-organization. Flexibility in achieving a goal is better serviced bythe concept of equifinality. Equifinality is the systemic property ofhaving the choice of alternative paths of action in order to achievea goal; otherwise, effectively reaching the same goal throughdifferent ways–trajectories–paths because ‘‘systems can achieve a

final state independently of their initial conditions, by a high variety

of different paths and through multiple structures’’ (Gresov andDrazin, 1997, pp. 403–404). Equifinality is essential to manageeffectively in non-linear unpredictable environments, and itneeds to be built into the instruments of innovation policy (Fig. 3).

In order to build equifinal policy implementation instruments,first further research is needed to understand the complementaritiesand tensions within policy design: that is amongst instruments,between instruments and goals and between instruments and theagents of change (i.e. projects). Based on these complementaritiesand tensions, studies can determine the range of change in projectplans and activities and the range of effective options for managersthat can be afforded by policy. Second, the outcomes from the aboveresearch need to feedback into the design phase of the policy toascertain how equifinal implementation instruments are designedby the policy-makers and how their design is effectively integratedinto policy goals. By doing so, the elements of implementationcan be pieced together into a holistic picture explaining the

inking:hroughnalityuct

Project management:leadership, boundaryrelations, efficiencyand effectiveness of

activities

nagement through the construct of equifinality (the author).

M. Kapsali / Technovation 31 (2011) 615–626 625

interdependence between ‘policy goals–implementation instruments–

project’, thereby gaining insight into how implementation reallyworks through the whole policy process, from design to finaloutcome.

8.2. Implications for practice

This study suggests that both policy and project practitionerswould perform more effectively if they could exercise variousdegrees of discretion when engaging in implementation. Since theevidence has indicated that the most successful projects are theones that involve managers who can handle change and relations,the proposition of this paper is that flexibility should be embeddedas an element of control mechanisms and relations with therelevant stakeholders and especially project owners, somethingthat hitherto has been lacking and explains the common failure ofprojects.

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Maria Kapsali graduated from ManchesterBusiness School with a Ph.D. in BusinessAdministration, specialising in Operations,Technology and Innovation Management. HerPh.D. won funding from UMIST, ManchesterSchool of Management. Her thesis, entitled‘‘European Policy and Operational Change’’explored the effects of European Innovationpolicies on the management of innovationprojects in Framework Programs. Previousqualifications include an M.Sc. in OperationsManagement (UMIST) and a B.A. Hons in

Business (DeMontfort University).

Maria has been a Research Associate in the Innovation and Entrepre-neurship Group at Imperial College Business School from 2009 to 2011,where she worked in two projects: firstly, the one funded by the EPSRC‘‘Designing Out Medical Error’’ (DOME) project and secondly, in theInnovation Studies Centre awarded ‘‘Simulation Modelling in HealthcarePlanning’’ project. Maria is now Browaldh post doc fellow at Umea Schoolof Business in Sweden, working in Innovation systems, networks andprojects.

Maria has 8 years of experience conducting research as an associate,assistant and doctoral/visiting researcher in the areas of: Project Manage-ment, Innovation Systems, Innovation Policy and Healthcare operations.

Maria is interested in research projects in innovation policy, imple-mentation instruments and the operations in innovation firms andinnovation projects. This includes the application of Systems Thinkingmethodologies in R&D and deployment projects.