Different practices for open innovation:a context-based approach

Nicola Bellantuono, Pierpaolo Pontrandolfo and Barbara Scozzi

Abstract

Purpose – The authors aim to investigate the concept of open innovation, identify different open

innovation practices which help describe the continuum between closed and open innovation, and

propose a framework that suggests an association between innovation contexts and practices.

Design/methodology/approach – The authors first identify the variables to describe innovation

contexts and practices. Such variables are developed based on the literature and on a previous paper

by the same authors in 2011. Then, they establish an association between contexts and practices, and

test it through cases drawn from the existing literature.

Findings – The paper proposes a detailed assessment of open innovation practices and suggests the

association between each of them and diverse innovation contexts. A few case examples drawn from

the literature prove coherent with the theoretical framework underlying the proposed association.

Practical implications – The authors’ results (and specifically the framework) enhance the

organizations’ awareness of the open innovation concept and the possible practices to implement it,

as well as supporting managers to better select open innovation practices in different contexts.

Originality/value – This paper discusses the concept of open innovation practices to enhance the

comprehension of the open innovation concept. Also, to the authors’ knowledge, the proposed

association between context and practices is original in that there are no similar theoretical frameworks

that help organizations selecting innovation practices.

Keywords Open innovation, Open innovation practices, Innovation context, Knowledge supply,Innovation, Organizations

Paper type Research paper

1. Introduction

The need to support innovation by resorting to collaborations with external subjects, such as

customers or suppliers, is not new (e.g. Allen, 1977; Allen et al., 1980; Clark and Fujimoto,

1991; Eppinger, 2001; Katz and Allen, 1982; Morelli et al., 1995; Trott and Hartmann, 2009;

Tushman, 1979). What has recently changed is the attention devoted towards the so called

open innovation (Chesbrough, 2006; Gassmann, 2006; Kirschbaum, 2005; van de Vrande

et al., 2009).

Unfortunately, scholars provide numerous and broad definitions of open innovation, which

make not always clear what open innovation practices are (Dahlander and Gann, 2010;

Pisano and Verganti, 2008). Initially, the terms ‘‘open’’ and ‘‘closed’’, when referred to

innovation, were used in opposition (Chesbrough, 2006). However, recent studies have

pointed out that innovation is not simply closed (i.e. in-house developed) or open, rather it

varies in a continuum between the above extreme modes. To deal with such a continuum

some scholars have introduced the concept of openness degree (Bellantuono et al., 2011;

Knudsen and Mortensen, 2011; Laursen and Salter, 2006; Lazzarotti and Manzini, 2009).

The existence of different innovation modes determines the problem of the mode selection.

Key issues in such a problem are clarifying what open innovation practices are and

PAGE 558 j JOURNAL OF KNOWLEDGE MANAGEMENT j VOL. 17 NO. 4 2013, pp. 558-568, Q Emerald Group Publishing Limited, ISSN 1367-3270 DOI 10.1108/JKM-03-2013-0180

Nicola Bellantuono is aResearch Fellow inBusiness and ManagementEngineering at theDepartment of Mechanics,Mathematics, andManagement, Politecnico diBari, Bari, Italy.Pierpaolo Pontrandolfo is aFull Professor in Businessand ManagementEngineering at theDepartment of Mechanics,Mathematics, andManagement, Politecnico diBari, Bari, Italy.Barbara Scozzi is anAssistant Professor inBusiness and ManagementEngineering at theDepartment of Mechanics,Mathematics, andManagement, Politecnico diBari, Bari, Italy.

Received 18 March 2013Accepted: 20 March 2013

This work has been supportedby Italian Ministry of Education,Universities and Research(PON01_02499 – Decisionsupport system for maritimeenvironment emergencymanagement).

supporting organizations in the adoption of such practices. Yet, to our knowledge, no studies

address such issues.

The goal of the paper is to identify criteria to support companies in selecting the open

innovation practice(s) to be implemented in accordance with the given innovation context.

To do that, we first identify the variables to describe the open innovation practices, building

on a previous work (Bellantuono et al., 2011). Then, based on the literature review, we

characterize the innovation context. Finally, we try to establish an association between

contexts and practices, and test it through cases drawn from the existing literature.

The value of the paper is to enhance the comprehension of the concept of open innovation,

which is analysed in terms of open innovation practices. Our study helps organizations to

better select practices for open innovation.

The paper is organized as follows. A review of the literature on open innovation is reported in

Section 2. Section 3 is devoted to position the key concepts of knowledge supply, open

innovation practice, and innovation context in the extant literature. The research goal and

methodology are discussed in Section 4. Section 5 proposes the variables used to describe

open innovation practices and innovation contexts, and discusses the association between

them. Finally, in Section 6 some managerial implication are presented and a path for further

research suggested.

2. Literature review

Open innovation has been defined as ‘‘both a set of practices for profiting from innovation

and also a cognitive mode, for creating, interpreting and researching those practices’’

(Chesbrough, 2006), ‘‘the use of purposive inflows and outflows of knowledge to accelerate

internal innovation, and expand the markets for external use of innovation, respectively’’

(Chesbrough et al., 2006) and ‘‘systematically performing knowledge exploration, retention,

and exploitation inside and outside an organization’s boundaries throughout the innovation

process’’ (Lichtenthaler, 2011). Such definitions encompass several dimensions and

aspects, so leading to studies that discuss open innovation under very different

perspectives, sometimes uncorrelated among each other (Dahlander and Gann, 2010;

Pisano and Verganti, 2008).

Besides problems associated with conceptual ambiguity, some of the open innovation

principles are not new. That made some scholars discuss open innovation as ‘‘new wine in

old bottles’’ (Trott and Hartmann, 2009) and some others, provocatively, wonder if that is a

real field of study or, rather, a communication barrier to theory development (Groen and

Linton, 2010).

Despite such objections and the fact that just a minority of companies seem to resort to open

innovation (Drechsler and Natter, 2012; Lichtenthaler et al., 2011), the phenomenon has

been studied with respect to large as well as small and medium sized enterprises, and to

low-tech as well as high-tech industries, by both quantitative and qualitative studies (Mortara

and Minshall, 2011).

Open innovation is described in the literature as a way to access expertise and technology

competences not available in house, to reduce innovation costs while also sharing the risks.

Lichtenthaler (2011) found that resorting to open innovation pays off in terms of return of

investments. Nonetheless, the exist barriers to open innovation, which usually are cultural

(e.g. the Not-Invented-Here and the Not-Sold-Here syndromes), but they can also be

associated with knowledge gaps, security and copyright issues, and the existence of

competitive threats (Drechsler and Natter, 2012; Lichtenthaler et al., 2011; Mortara et al.,

2010).

Enkel et al. (2009) summarized the theoretical developments reported in the literature based

on three main open innovation processes:

1. the outside-in process, also defined as technology exploration or inbound innovation

(Dahlander and Gann, 2010; van de Vrande et al., 2009);

VOL. 17 NO. 4 2013 j JOURNAL OF KNOWLEDGE MANAGEMENTj PAGE 559

2. the inside-out process, also defined as technology exploitation or outbound innovation;

and

3. the coupled process.

The first process consists of enriching the organization’s own knowledge through the

integration of external knowledge sources. The second one refers to earning profits by

bringing knowledge to market. The last one refers to co-creation with complementary

partners, during which both ‘‘give’’ and ‘‘take’’ are crucial for success. Empirical evidence

show the outside-in as the most commonly adopted process (Knudsen and Mortensen,

2011).

Interesting reviews of the literature on open innovation are proposed in Huizingh (2011) and

Lichtenthaler (2011). In particular, Huizingh (2011) discusses the state of the art of the

research based on three dimensions, namely the open innovation content, context and

processes. Lichtenthaler (2011) summarizes past research and present debates on open

innovation and proposes a conceptual framework for organizing open innovation within

companies. The framework identifies three main open innovation processes, namely

knowledge exploration, retention, and exploitation. Such processes can be managed

internally or externally (i.e. with external partners). For each process, the capabilities needed

at the firm level and the decisions to make at the project level are discussed. Also, the

individual attitudes that may affect the performance of the open innovation processes are

identified.

Some recent papers emphasize the existence of a continuum between open and closed

innovation (Knudsen and Mortensen, 2011; Trott and Hartmann, 2009): innovation is thus

described as a phenomenon that varies in a range from a completely closed to a completely

open model. Some studies have then characterize innovation in terms of its openness

degree (Bellantuono et al., 2011; Knudsen and Mortensen, 2011; Laursen and Salter, 2006;

Lazzarotti and Manzini, 2009). In addition, Bellantuono et al. (2011) point out that, in a certain

innovation project, an organization may adopt a different innovation model (in between open

and closed) for any of the several Knowledge Supplies (KSs) required by the project. They

defined a KS as any collaboration (or interaction) with external sources, such as other

organizations or individuals, which provide some kinds of knowledge or information.

The concept of KS, together with those of open innovation practice and innovation context, is

crucial to the scope of the paper. In the following Section, we discuss these three concepts.

3. Knowledge supply, open innovation practice, and innovation context

We describe a knowledge supply (KS) by four attributes. The knowledge recipient is the

actor (individual or organization), who makes use of the KS. The knowledge source is any

individual (e.g. a member of the innovating organization, an external consultant, etc.) or

organization (e.g. competitors, research institutions, innovation intermediaries) that provides

the recipient with knowledge. The knowledge kind, which is the type of the knowledge

provided by the knowledge source, can be described in terms of dimensions, such as

certainty, stability, usability, proficiency, applicability, originality, and onerousness

(Holsapple and Joshi, 2001). The knowledge transfer medium is the communication mean

between the knowledge source and recipient.

Chesbrough and Kardon Crowther (2006) use the expression ‘‘open innovation practice’’ to

refer to both a set of inbound or outbound activities (e.g. in-licensing and out-licensing) and

the ways such activities are adopted (e.g. ‘‘leveraging inbound open innovation to optimize

development execution’’ or ‘‘leveraging outbound open innovation to create step change

growth’’). Inbound and outbound activities are also referred to as open innovation process

(Enkel et al., 2009), open innovation approaches (Lichtenthaler et al., 2011), and open

innovation practices or initiatives (Lichtenthaler, 2011). Pisano and Verganti (2008) propose

a classification of open innovation collaboration practices based on two dimensions, i.e. the

adopted partnership (open vs closed) and the governance (hierarchical vs flat). According

to van de Vrande et al. (2009), open innovation practices can be classified as technology

PAGE 560 j JOURNAL OF KNOWLEDGE MANAGEMENTj VOL. 17 NO. 4 2013

exploitation practices (i.e. venturing, outward IP licensing, employee involvement) and

technology exploration practices (i.e. customer involvement, external networking, external

participation, outsourcing R&D inward IP licensing). Spithoven et al. (2010) focus on open

innovation practices adopted by companies resorting to collective research centres and

mention, among them, practices such as the support to external knowledge acquisition and

networking activities. Other scholars define open innovation practices in different ways. For

example[1], Fritsch and Lukas (2001) word them as cooperative relationships. Such

relationships include causal contact for information purpose, organized exchange of

information and experience, involving in planning and operation of projects, pilot use of an

innovation, joint use of equipment or laboratories, joint R&D projects, research contracts.

Sobrero and Roberts (2002) used the expression ‘‘contractual coordination mechanisms’’.

Such mechanisms, defined in terms of type, length and specificity, include long term

contracts, strategic alliance, R&D consortia, market driven transactions (e.g. licensing),

intermediate form of governance structures (e.g. joint ventures and consortia). Lee et al.

(2010) rather define them as collaboration modes, which include funding licensing

outsourcing, R&D partnership, joint ventures and inter-firm alliance. Mortara and Minshall

(2011), who use the term practice to refer to open innovation itself, propose a classification of

the approaches to open innovation based on two criteria, i.e. the organizational change

associated with – or produced by – the introduction of open innovation and the way the

practices were coordinated. By ‘‘open innovation organizational modes’’ Bianchi et al.

(2011) refer to inbound open innovation (e.g. purchase of scientific services, in-licensing)

and outbound open innovation (e.g. collaborations, supply of scientific services,

out-licensing). According to Huizingh (2011), open innovation practices are the processes

that managers start when deciding ‘‘when, how, with whom, with what purpose, and in what

way should they cooperate with external partners’’. In the followings, we define open

innovation practices as the set of decisions made by managers for each knowledge supply

(KS). Such decisions deal with the following questions: Which knowledge source to consider

(one or more consultants vs a large community)? What incentives to use? What kind of

interaction to activate? Who should control the supply? By using what kind of coordination

form and mode?

In this paper, ‘‘innovation context’’ refers to the features that characterize the environment

wherein innovation takes place. As discussed in the literature, the innovation context

influences the choices made by organizations about their innovation practices. Pisano and

Verganti (2008) argue that the choice of the collaboration practice depends on the

knowledge and capability owned by the buyer firm, and examine two main kinds of

knowledge, namely the one necessary to define a problem and evaluate possible solutions,

and the one necessary to address that problem (i.e. determine the solution). They also

mention the collaborative architecture as relevant to the choice of the collaboration

practices. Such an architecture is defined as the ‘‘structure and organization principles’’ of

the KS buyer (above named as knowledge recipient).

Some insights regarding to the concept of innovation context can be derived from other two

streams of studies, i.e. the literature on Free/Libre Open Source Software (FLOSS) and the

literature on purchasing portfolio models. Within the former, several scholars have

investigated the success factors of FLOSS projects. To attract contributors, projects should

address a diffuse need (Crowston and Scozzi, 2002), one of the most important being

learning (Lakhani and von Hippel, 2003). User direct needs, enjoyment of the work,

enhanced reputation are other needs/motivations (Osterloh and Rota, 2007). The presence

of well-known administrators (or companies) can contribute to attract contributors. The more

the request of knowledge is able to address the mentioned needs, the more resorting to

innovation communities or crowdsourcing is convenient. Communities are able to provide

knowledge only if their participation is possible and easy.

The literature on purchasing portfolio models argues that for critical supplies strategic

integration with the supplier should be pursued. Scholars propose different criteria to assess

the criticality of supplies. Such criteria generally concern the importance of purchasing, on

the one hand, and the complexity or the risks associated with the supply market, on the other

VOL. 17 NO. 4 2013 j JOURNAL OF KNOWLEDGE MANAGEMENTj PAGE 561

hand (Kraljic, 1983; Olsen and Ellram, 1997; Gelderman and van Weele, 2005). Even though

this stream of studies is mainly concerned with operations (procurement of goods and

services), some concepts can be usefully applied to innovation (procurement of

knowledge).

4. Research goal and methodology

Given that many modes exist for an organization to be open, it makes sense to identify which

open innovation practices best fit a specific innovation project an organization is carrying

out. Based on previous works (Bellantuono et al., 2011, 2013), we think that the correct unit

of analysis to investigate such a problem is the Knowledge Supply. As a result, selecting the

practices that best fit with the project means to decide which practice to adopt for each of

the several KSs required for that project. Note that the emphasis on KSs as unit of analysis

implicitly focuses the scope of our study on inbound open innovation.

To establish the association between practices and context, we identified the relevant

variables to describe both these concepts, on the basis of the literature review. Then, we

analysed the possible relationship between any context variable, on the one hand, and any

practice variable, on the other hand. The authors independently analysed every possible

relationship, so defining his/her proposed list of actual relationships, expressed as ‘‘if-then’’

sentences. Their lists were then compared and all the relationships agreed by all authors

accepted. For the (few) cases of disagreement, the authors together discussed the

relationship until an agreement was reached. A similar process was adopted to characterize

the case examples, which were taken from Pisano and Verganti (2008). The authors

separately analysed the examples and came out with their evaluation of the cases in terms of

practice and context variables. They finally discussed altogether those evaluations that were

not consistent among each other, until an agreement was achieved.

5. Open innovation practices and contexts: variables and relationships

This Section presents the variables that describe open innovation practices and innovation

contexts. To do so, we build on a previous paper (Bellantuono et al., 2011), which discusses

variables related to open innovation practices. Variables related to innovation contexts are

based on the literature reviewed in Section 3.

Table I reports the variables identified to describe open innovation practices, their

description, as well as the attendant possible values.

Theoretically, more than 1,000 possible open innovation practices exist: we indeed

hypothesized that seven variables may assume two values, whereas the remaining two

variables may assume three values. This even simplifies reality, given that, for example,

coordination form (assumed to take one out of only three values) might actually take many

other values. However, not all of the theoretical practices are realistic. For example, an open

access mode is not compatible with a hierarchical coordination form (unless we imagine that

the openness only refers to the employees of the buyer company, but that would contrast our

definition of access mode).

Pisano and Verganti (2008) offer a few examples of open innovation practices:

B The innovation mall is a place wherein any company can post a problem and anyone can

propose solutions, successively selected by the company (e.g. the Innocentive.com

website).

B The innovation community is a network wherein anyone can propose problems and/or

offer solutions (e.g. the Linux open-source community).

B The elite circle is a selected group of experts chosen by the company to address a

specific problem (e.g. the Alessi case).

B The consortium is a group of organizations that jointly select problems and choose

solutions (e.g. the IBM case).

PAGE 562 j JOURNAL OF KNOWLEDGE MANAGEMENTj VOL. 17 NO. 4 2013

In Table II such examples are described in terms of the open innovation variables.

Table III reports the variables proposed to describe innovation contexts variables and the

attendant possible values.

The identified variables are five. In particular, within the scope of this paper, by collaborative

architecture we mean the knowledge recipient’s propensity to collaborate. Collaborative

Table I Open innovation practice variables and attendant values

Dimension Definition Values

Access mode The recipient’s choice to resort topre-qualification of perspective knowledgesources

Closed, if the KS is provided by ad hoc selectedsources (e.g. when consultants are hired by therecipient)Open, if any possible knowledge source canaccess to it (e.g. in the case a request is postedby the recipient on innoCentive.com)

Degree of formality The extent to which the communication betweenknowledge source and recipient is based onstandards, protocol, and procedures

High, if the KS is provided in a formalized mode(e.g. a written report)

Low, if the KS is provided in an informal mode(e.g. informal conversation)

Incentives The drivers that make the knowledge source takepart to the KS

Pecuniary, if the KS is provided thanks to apecuniary payment (e.g. in the case ofconsultants hired by the recipient)Non-pecuniary, if the KS is provided for free(e.g. in the case of open source softwaredevelopment projects)

Interaction mode The way the recipient and the knowledge sourceinteract

Static, if the KS is associated with a knowledgetransfer (e.g. in the case the knowledge source isa scientific journal)Dynamic, if the KS activates a dynamic leaningprocess in which both the source and therecipient learn (e.g. in the case of involvement ina common research project)

Information flow The direction of the information shared betweenthe recipient and the knowledge source

Mono-directional, if the knowledge source doesnot receive any information from the knowledgerecipientBi-directional, if both parties exchangeinformation

Locus of control The actor who makes decisions regarding the KS In the hands of the knowledge recipient, if thelatter controls any aspect of the supplyIn the hands of the knowledge source, if he/she isin charge of any decisionsShared, if both the recipient and the sourcetogether control the KS

Coordination mode The way the interdependences betweenknowledge recipient and source are managed

Programming, if the knowledge source’ tasks, thedeliverables and the time schedule are detailedin advanceFeedback, if tasks, deliverables, and timeschedule are continuously adjusted based uponideas and discoveries that emerge during theKS

Output The existence of limitations to have access on,and adopt, results of the KS

Closed, if results of KS are private or protectedby a copyright or licenseOpen, if they are accessible or usable by anyone(e.g. a research project financed by the State)

Coordination form The kind of (inter-firm) relationships betweenknowledge source and recipient

Pure market relationships (e.g. by consultancycontracts)Partnership relationships (e.g. by theinvolvement in the same research project)Hierarchical relationships (e.g. by equityinvestments)

VOL. 17 NO. 4 2013 j JOURNAL OF KNOWLEDGE MANAGEMENTj PAGE 563

architecture is low if such a propensity is low (e.g. because of a diffuse presence of the Not

Invented Here Syndrome), and high otherwise.

The context variables identify a multidimensional matrix, which represents the space

wherein the different innovation practices can be positioned, once the association between

practices and contexts has been established. In the following, the analysis focuses on three

of the five context variables, namely KA, KDE, and IEP.

It is noteworthy that certain combinations of values for the context variables are not feasible,

and certain others are associated with innovation that should be in-house developed.

Specifically, the combinations ‘‘high KA, low KDE, and high/low IEP’’ are not feasible

because an organization cannot know how to address the problem without knowing how to

define it and evaluate the solutions. Furthermore, open innovation should not be advisable if

both KA and KDE are high, regardless the value for IEP. The above considerations are

reflected in Table IV, wherein, besides these not relevant combinations, we label the four

remaining feasible combinations as A to D. Figure 1 displays the information given by

Table IV in a graphical form.

Table II Examples of open innovation practices

Example of innovation practiceInnovation practice variable Elite circle Innovation mall Innovation community Consortium

Access mode Closed Open Open ClosedDegree of formality High High High HighIncentives Pecuniary Pecuniary Non-pecuniary PecuniaryInteraction mode Static Static Dynamic DynamicInformation flow Bi-directional Mono-directional Bi-directional Bi-directionalLocus of control Recipient Recipient Both BothCoordination mode Programming Programming Feedback ProgrammingOutput Closed Closed Open ClosedCoordination form Hierarchy Market Market Partnership

Table III Context variables

Independent variable Values

Knowledge owned by the recipient to addressthe innovation problem (KA)

High vs low

Knowledge owned by the recipient to define theinnovation problem and Evaluate solutions (KDE)

High vs low

Knowledge source’s Interest and Easiness ofParticipation to innovation project (IEP)

High vs low

Recipient’s collaborative architecture (CA) High vs lowCriticality of the knowledge supply (CKS) High vs low

Table IV Analysis of the combinations for context variables

KA KDE IEP Combination

Low Low Low ALow Low High BLow High Low CLow High High DHigh Low Low Not feasibleHigh Low High Not feasibleHigh High Low Closed innovationHigh High High Closed innovation

PAGE 564 j JOURNAL OF KNOWLEDGE MANAGEMENTj VOL. 17 NO. 4 2013

We have then considered the possible relationships between context variables and

innovation practice variables with respect to the above A to D combinations. Table V

summarizes such relationships in terms of ‘‘if-then’’ rules.

Table VI displays the ‘‘if-then’’ rules reported in Table V in the form of the values that are

assumed by every innovation practice variable for innovation contexts A to D.

Note that the case examples presented in Table II may be considered as specific instances

of the analysed combinations. In particular, the consortium is associated with A, the

innovation community with B, and the elite circle as well as the innovation mall with

C. Another interesting instance is represented by the innovation competition, which can be

started by a famous company that, differently from the case of elite circle, solicits an open

access competition without any pecuniary incentives. Such a case is associated with

combination D.

6. Conclusions

The present paper has in-depth analysed the concept of open innovation, identified several

different practices to implement it, and associated the latter with different possible

innovation contexts.

Figure 1 Innovation context and practices

Table V Relationships between context and innovation practice variables

Value of the context variable(s) Value of the innovation practice variable(s)

If IEP is high Then Open access modeNon-pecuniary incentives

If IEP is low Then Any access modePecuniary incentives

If IEP is high and KA is low Then Any coordination form but hierarchyIf KA is low Then High degree of formalityIf KA is low and KDE is high Then Static interaction mode

Bi-directional information flowLocus of control in the hands of the recipientProgramming-based coordination mode

If KA is low and KDE is low Then Any interaction modesAny information flowsAny locus of control but in the hands of recipientAny coordination form but hierarchy

If KA is low and KDE is high and IEP is low Then Any information flows

VOL. 17 NO. 4 2013 j JOURNAL OF KNOWLEDGE MANAGEMENTj PAGE 565

In particular, we have proposed the concept of knowledge supply as units of analysis to

characterize innovation. Building on the literature and on a previous paper by the same

authors (Bellantuono et al., 2011), we have identified the variables to characterize the

contexts, on the one hand, and the practices, on the other hand. An association between

different contexts and different practices has been developed, which helps clarify the

concept of open innovation as well as explore the several different modes to implement it. In

particular the detailed description of such modes sheds light on what the literature has

defined as a continuum between closed and open innovation.

The theoretical contribution given by this paper puts the basis for deriving some managerial

implications. The framework underlying the hypothesized relationships between innovation

contexts and open innovation practices represents a decision support for managers

involved in innovation projects. Organizations can utilize the framework to enhance the

awareness of their innovation context, understand the possible available innovation

practices, and properly select among them.

The proposed research is exploratory. Although the methodology adopted is quite common

in qualitative research, it does not preserve from possible authors’ biases. Another limit of

our research is the need for empirical validation of the suggested relationships. In particular,

some of the relationships we suggest are confirmed by all the examined cases, which were

drawn by the literature. However, other examples or cases are needed to generalize our

hypotheses. Further research should then include a survey to validate the variables as well

test the hypothesized relationships.

Note

1. The first two citations mentioned as examples refer to paper written before the expression ‘‘open

innovation’’ was coined.

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About the authors

Nicola Bellantuono is Post-Doc Research Fellow in Business and Management Engineeringat Politecnico di Bari (Italy). He holds a Laurea Degree in Management Engineering (2004)and a PhD in Environmental Engineering (2008). His main research interests include supplychains coordination by contracts, logistics services procurement, open innovation, andcorporate social responsibility.

Pierpaolo Pontrandolfo holds a PhD in Engineering of Advanced Manufacturing Systemsand is Full Professor in Business and Management Engineering at the Politecnico di Bari(Italy), where he has been Head of the Department of Environmental Engineering andSustainable Development (2006 to 2009). In 1995 and 1997, he was visiting scholar at theUniversity of South Florida (Tampa, USA). He is or has been responsible for several researchprojects granted by both public institutions and companies. He is author of many paperspublished in international books or journals in the fields of supply chain management,corporate social responsibility, and green product development.

Barbara Scozzi is Assistant Professor in Business and Management Engineering at thePolitecnico di Bari (Italy). She holds a PhD in Business and Management Engineering(2001). Since 1999, Barbara Scozzi has been involved in many research projects, carriedout both at national and international level. Her main research interests deal with businessprocess management, knowledge management, innovation in small and medium-sizedenterprises and corporate social responsibility. Barbara Scozzi is the corresponding authorand can be contacted at: bscozzi@poliba.it

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