How to Support the Inbound Open Innovation Process: Conceptual Design of an Integrated ICT IOI Platform

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DIPARTIMENTO DI INGEGNERIA DELL’ENERGIA DEI SISTEMI,

DEL TERRITORIO E DELLE COSTRUZIONI

RELAZIONE PER IL CONSEGUIMENTO DELLA

LAUREA MAGISTRALE IN INGEGNERIA GESTIONALE

How to support the Inbound Open Innovation

Process: Conceptual Design of an Integrated ICT

IOI Platform

RELATORI IL CANDIDATO

Prof.ssa Luisa Pellegrini

Dipartimento di Ingegneria dell'Energia, dei Sistemi, del Territorio e delle Costruzioni

Andrea Pennacchi

andrea.pennacchi@outlook.it

Prof. Ing.Davide Aloini

Dipartimento di Ingegneria dell'Energia, dei Sistemi, del Territorio e delle Costruzioni

Ing. Giulia Farina

Dipartimento di Ingegneria dell'Energia,

dei Sistemi, del Territorio e delle Costruzioni

Sessione di Laurea del 04/10/2017 Anno Accademico 2016/2017

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Index

Introduction ...

4

1-

Literature review ...

7

1.1-

State of the art on Open Innovation

...

7

1.1.1- Open Innovation ... 9

1.1.2- Inbound Open Innovation ... 14

1.1.2.1- Technology scouting ...

19

1.1.2.2- External knowledge sourcing ...

23

1.1.2.3- Collaboration establishment ...

29

1.1.3- ICT and Open Innovation ... 34

1.1.4- Overview of existing Open Innovation platforms ... 43

1.2- Literature review on Conceptual Design for ICT

Platforms ...

54

1.2.1- Conceptual design ... 54

1.2.2- Conceptual design in Information Systems ... 56

1.2.3- Conceptual design of ICT platforms for the OI

process ... 61

1.2.3.1- Functions conceptualization ...

61

1.2.3.2- Preliminary design ...

65

1.2.3.3- System/software architecture conceptual design ...

67

2-

Methodology and adopted modeling language

71

2.1- Project methodology ...

71

2.1.1- Platform functions conceptualization ... 72

2.1.2- Platform preliminary design ... 74

2.1.3- System data architectural model conceptual

design ... 75

2.2- Adopted modeling language: UML (Unified

Modeling Language) ...

76

3

2.2.2- UML class diagrams ... 83

3- Results and analysis ... 85

3.1- Results and analysis of the platform functions

conceptualization ...

86

3.1.1- Framework supporting the Inbound Open

Innovation process exploitation ... 86

3.1.2- Company use cases analysis ... 91

3.2- Results and analysis of the platform preliminary

design ...

122

3.2.1- Platform functional groups determination ... 122

3.2.2- Platform functional groups description ... 123

3.3- Results and analysis of the system data

architectural model construction ...

149

3.3.1- Data classes identification and description ... 149

3.3.2- Platform data architectural model UML class

diagram ... 169

3.3.3- System data architectural model exploitation:

classes set and classes associations analysis ... 170

4- Conclusions: Platform final conceptual design

output ...

180

4.1- Representation and description of the platform final

conceptual design output ...

180

4.2- Final conclusions ...

182

Bibliography ...

184

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INTRODUCTION

Since Open Innovation is increasingly becoming a key factor in the competitive business success, this thesis has been carried out with the aim of creating, at a conceptual level, a system able to assist a company throughout the Open Innovation process. The intention is therefore to establish a platform capable not only of supporting certain specific functions linked to innovation activities of the company, but also that of bringing together all the functions that might be necessary for the enterprise in this field, thus constituting a solid basis and a reference to the Open Innovation process of the company itself, specifically for the Inbound Open Innovation process.

This thesis is part of a research project originated because of the need of the Technological Developments business unit, that is a business unit within the Engineering area of a company operating in the military field, to include even the civilian market by means of dual-purpose technologies (i.e. technologies for both the military and civilian markets) and make the Inbound Open Innovation process possible, in particular, to establish partnerships and non-equity agreements. This firm is interesting because it perceives the compelling necessity to facilitate its openness to external partners notwithstanding its military nature – and hence the necessity to strictly protect the intellectual property and the difficulty in sharing and transferring knowledge- plays a role as factor which holds back from making firm’s boundaries porous. This objective has another implication: it can contribute to research by showing how ICT can support firms in their OI processes, supporting firms in the creation of a positive environment that encourages people at leveraging existing technological capabilities outside the boundaries of the organization [Hung and Chou, 2013].

The considered design phase is the conceptual design. Conceptual design is an umbrella term given to all forms of non-aesthetic design management disciplines. It is an early phase of the design process, in which the broad outlines of function and form of something are articulated. It includes the design of interactions, experiences, processes and strategies. It involves an understanding of people’s needs and how to meet them with products, services, and processes. In our case, it

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is a conceptual design of a platform supporting the Inbound OI process; therefore, the output obtained comprises: (i) the definition of the platform’s functions; (ii) the definition of the relations among the functions identified and the Inbound OI sub-processes; (iii) the data architectural model that regards the definition of the connections among the defined functions of the platform and the external or internal databases.

In order to achieve this goal, the thesis begins with a first part in which we retrace and analyse the main works that the literature provides on this subject. Particularly, it starts with the concept of innovation to come to consider the origins of the Open model and the contrast that this new model manifests with respect to the traditional model called closed innovation. It then focuses on that part of Open Innovation defined as "Inbound Open Innovation", which refers to the practice of exploring and integrating the exogenous knowledge for the development and exploitation of technologies. This choice is due to the fact that the platform in question is born with the goal of supporting this specific type of Open Innovation process, omitting the innovation part of the so-called "Outbound Open Innovation". The paragraph about Inbound Open Innovation is then subdivided into three paragraphs, containing important elements for the three key sub-processes that have been identified as the hubs of Inbound Open Innovation and that, for this reason, are the beneficiaries of the support provided by the platform. These sub-processes are: (a) technology scouting, (b) external knowledge sourcing, (c) collaborations' establishment. The first chapter continues with the introduction of the ICT world and some considerations about how this world combines with that of Open Innovation and about which role it may have in relation to the Open Innovation itself. Subsequently there is a short overview of some existing Open Innovation platforms to provide some examples and see how such platforms are currently working. The second part of the literature review continues with an introduction to the conceptual design, focusing on what doing conceptual design means and on the contributions that literature provides in relation to this design phase. The conceptual design is first discussed at a generic level and is subsequently considered more specifically in the case of information systems.

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The second section discusses project objectives, methodology and modelling language adopted to carry out the conceptual design of the platform. First of all we start from the definition of the main purpose, namely the design of an integrated ICT platform that supports the IOI (Inbound Open Innovation) process, as wanted by the military company for which the all project originates. This subject is contextualized and the originating causes are introduced and explained. The second part of this section only deals with the integrated ICT platform, focusing on the methodology employed to get the results of the conceptual design, introducing the three phases in which the conceptual design activities have been divided: functions conceptualization, preliminary design and system/SW data architectural model conceptual design.

The third section of this thesis concerns the results and the conducted analysis. It starts with the definition of a model created for the Inbound Open Innovation process, in order to have a clear reference structure to take into account in determining the platform configuration and functions. This is because the ICT platform will have to support the inbound Open Innovation process shown by this framework. After determining the framework supporting the inbound Open Innovation process exploitation we will move to consider and analyse the results of the platform's functions conceptualization phase. To get these results we identify different use cases, analysing different needs which may occur within the Inbound OI process and in particular within the identified sub-processes of technology scouting, external knowledge sourcing and collaborations' establishment. Once all the possible use cases have been identified, a synthesis with the aim to describe these use cases and the associated scenarios is created, thus having both a clear vision of the set of needs to be met and a useful breakdown to then focus on the specific functions. These use cases are then reported through a graphic representation, using the UML (Unified Modelling Language), and specifically the use case diagrams, in order to ensure a greater immediacy and clarity to the reader. A single representation for each use case is reported and also an overall map to give an overview and to illustrate how a user can move within the platform and its functions, as conceived in the process of conceptual design. Once the use cases analysis has been completed we move on

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with the preliminary design phase, analysing the use cases until reaching the their aggregation and combination into functional groups (modules), arriving at the determination of a conceptual model for the integrated ICT OI platform. These functional groups are then considered one by one and addressed by giving a description of the characteristics and objectives of each one of them, also reporting references to the literature about how these functions have been previously treated. The last part of the third section refers to the construction of the system data architectural model, starting with the data classes identification and description, until providing the UML Class Diagram capable of describing the architectural model of the obtained data and then explain the set of data classes and their associations.

The fourth section reports the platform conceptual design final output, graphically shown to illustrate the embedded functions, the data classes and their relationships. After explaining what emerges from the figure, the work ends with the drawing of the conclusions, both general and practical implications for the company.

1. LITERATURE REVIEW

1.1- State of the art on Open Innovation

In order to address the issue of Open Innovation, focusing specifically on Open Innovation platforms, this thesis starts from the identification of the main findings of research in the literature by various authors. The literature review has been conducted using some databases available to the University Library System of the University of Pisa and, together with the scientific search engines, the Google Scholar search engine has been flanked to obtain the various search results. The two reference scientific database for conducting the literature review have been Scopus (https://www.scopus.com/home.uri) and Web of Science (http://apps.webofknowledge.com/ WOS_GeneralSearch_input).

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The keywords used to define the object of the research are divided into several sub-groups in relation to the respective paragraph. These keywords sometimes have been included in the search fields individually, while in other cases a combined search has been made by linking two or more keywords through logical connectives. The following keywords (Tab.1) are the ones mostly used for the literature review in the different paragraphs.

Paragraph

Keywords

1

.1

S

ta

te

o

f

th

e

ar

t

o

n

O

p

en

I

n

n

o

v

at

io

n

1.1.1 Open Innovation Open Innovation, Open Innovation process, innovation, innovation changes, innovation phases, innovation model, innovation types, closed innovation, closed model, closed strategy, open strategy, innovation activities, Open Innovation model, openness, open tools, integration 1.1.2 Inbound Open

Innovation

Open Innovation, Inbound, Inbound Open Innovation, process, Inbound Open Innovation process, Inbound Open Innovation model, Inbound Open Innovation practices,Inbound Open Innovation phases, Outside-in, external knowledge exploitation, external sources 1.1.2.1 Technology

Scouting

Technology, Technology Scouting, Technology scouting process,Technology Scouting methods, Technology Scouting approach, new technologies, Technology Scouting tools

1.1.2.2 External Knowledge Sourcing

External knowledge, External Knowledge Sourcing, external sources, process, approach, knowledge management,

knowledge management practices, external knowledge sourcing tools, external

involvement 1.1.2.3 Collaborations'

Establishment

Collaborations, Collaborations'

establishment, technological partnering, technological collaboration, joint R&D, licensing, consortium, alliance, research funding, Collaborations' establishment process, collaboration types

9 1.1.3 ICT and Open

Innovation

ICT, Open Innovation, ICT tools, openness, ICT benefits, ICT potential, ICT support, ICT adoption cases, open strategy, ICT strategy, ICT tools, integration, interaction mechanisms, ICT and Open approach, ICT and Open Innovation relationship

1.1.4 Overview of existing ICT Open Innovation platforms

Open Innovation, platform, Open Innovation platform, ICT, ICT platform

1

.2

L

it

er

at

u

re

r

ev

ie

w

o

n

C

o

n

ce

p

tu

al

D

es

ig

n

f

o

r

IC

T

P

la

tf

o

rm

s

in Information Systems

Conceptual design in Information Systems, conceptual design, Information systems model, conceptual Information Systems model,Information Systems languages, conceptual modelling, conceptual modelling for Information Systems 1.2.3.1 Functions

conceptualization

Functions, conceptualization, functions conceptualization, ICT platform functions, OI platform functions, IOI platform functions, OI platform conceptualization, OI platform practices, functions

conceptualization examples 1.2.3.2 Preliminary

design

Preliminary design, ICT platform preliminary design, IOI platform preliminary design, system preliminary design

1.2.3.3 System data architectural model conceptual design

Architectural model, system architecture, software architecture, data architectural model, data model conceptual design, OI platform data architectural model, software architecture conceptual design

Tab.1 - Literature review paragraph and keywords

1.1.1 Open Innovation

To get to deal with Open Innovation, we start with a few considerations on the term innovation, on its meaning and its nature, both as a concept and as a process. Hauschildt and Salomo [2007] identify some concepts belonging to all the

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proposed definitions for the term innovation. In particular, Hauschildt and Salomo [2007] state that "an invention must be commercially exploited in order to qualify under the term innovation" and that an innovation consists in "new products or processes from a qualitative point of view that differ sharply from the previous state". Therefore, an innovation must at least be introduced into the market as a new product or be used as a new process in production. In other words, the common element lies in the novelty, in the improvement compared to the previous situation.

To analyse and manage the novelty and change that innovation involves, Abernathy and Clark [1985] have developed the "matrix of change" which allows to outline the impact that innovation can have on the individual business skills. The matrix is structured in two dimensions, the first of which concerns the impact on technological skills, while the second concerns the impact on market knowledge. This matrix identifies four different innovative configurations: (a) Architectural innovation, in the case in which the technological progress lead to the development of a new market. This innovation is marked by the inadequacy of the current competencies of an enterprise for the purpose of product development, as well as by insufficient market knowledge in view of the satisfaction of the new demand generated by the new product architecture.

(b) Niche innovation, in the case in which the progress opens new market opportunities without changing the technological skills required for managing it. In this case the change involves the conditions of the demand.

(c) Regular innovation, in the case in which this produces slight changes both as regards the product technology and as regards the relationship with the market. This category corresponds to an incremental innovation.

(d) Radical innovation (revolutionary), in which substantial changes with respect to the architecture of the product are introduced, without, however, altering the relations with the market. This form of innovation requires new technological resources and skills.

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Fig. 1: Matrix of change (source: Abernathy, Clark (1985) “Innovation: mapping the winds of creative distruction”)

Considering innovation as a process, Shilling [2009] identifies three general characteristic phases, that can be recognized as valid for every innovation process represented by exploratory studies, experimental research and commercialisation. The first phase consists in the generation, selection and evaluation of new ideas, both from the technological point of view and from the market insertion point of view. The second phase concerns the construction and development of selected ideas, while commercialisation includes aspects related to the implementation of activities aiming to the insertion in the global market.

In the world of innovation we may encounter different types of innovation, sometimes even opposites. For example there are radical or incremental innovations, continuous or discontinuous, disruptive or sustainable, well-defined innovation processes or flexibility in the opening to innovation. In fact, innovation must not aim only to the improvement and optimisation of existing products and technologies, but also address the development of new technologies and skills [Faems et. al, 2005]. This is due to the fact that companies must also strive to explore new fields of knowledge and technologies for the future.

Traditionally, companies developed to do this internally, trying to grow and progress by exploiting the resources and technologies developed inside the enterprise boundaries. This model is called "closed innovation" and it is distinguished by the fact that the innovative activities are conducted internally through the research and development system and equally internally the company proceeds with the subsequent development up to the production and commercialization of finished product. The companies’ objective for innovation

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was therefore to acquire the work of the most valuable human resources available in the field, to get ideas to exploit and commercialise, also resorting to intellectual property tools to protect the results and ensure the exclusivity of the innovation. According to the closed model the innovation process must therefore avoid any form of contact with the outside world and this must be valid for every stage included by this process. Referring to the steps indicated by Gottardi [2006] for an innovation process, it should not be considered any interaction with the outside neither in the early stages of basic research (targeted to extend the understanding of a given scientific field) and applied research (concerns the definition of a manufacturing process to the knowledge emerged from the previous step) nor on subsequent design and development phase, intended to demonstrate the technical feasibility, industrial manufacturability and economic advantages arising from the generated ideas.

Over the years the limitations of the "closed innovation" model have become more evident. They have been summarized in three points by Quarantino and Serio [2009]. First, the increasing mobility of highly skilled people makes it more difficult the control of ideas from companies and brought a considerable amount of knowledge available outside of research laboratories of large companies. Second, the capital market has funded business ideas and promising technologies so that they can be further developed outside the company. Finally, another limit of the closed model is due to the growing importance that other companies hold in the innovation process, by providing an ever increasing amount of resources. Furthermore, Lichtenthaler [2009] also states that a "closed" strategy limits the ability of the company to achieve the strategic benefits that could get instead using outside resources.

Henry Chesbrough, with his book "Open Innovation" [Chesbrough, 2003] is the author

who first identifies a change in the enterprises innovation activities, observing an increasing level of attention to the resources developed by external partners. The term Open Innovation has been created in a socio-economic environment characterized by increasing integration between different sectors, different technologies and different products, also marked by increasingly shorter product

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life cycles. Innovation thus becomes a competitive necessity for market participants and the classic innovation form needs for a strong change in the approach and for distinctive features compared to traditional innovation models adopted in the past and commonly grouped together under the definition of closed innovation. The new type of innovation, called “Open Innovation”, owes its origin to Henry Chesbrough who coins the term stating that "Open innovation is the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively. [This paradigm] assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as the firms look to advance their technology " [Chesbrough, 2003]. The model of Open Innovation, conceived and theorized by Chesbrough [2003], appears to be a consequence of the evolution of the market, more and more complex, marked by intense rhythms, by the need to combine the potential of different forms of knowledge and by the difficulty on the part of companies to exclusively benefit of their human and technological resources. In such a context it has become increasingly important the interaction with external subjects such as suppliers, customers, universities and various kinds of institutes, so focusing on approaches based on openness, collaboration and information exchange. Chesbrough [2003] also points out that the ability to enhance expertise and competencies that are outside the company become the company's advantage factor, and the Research and Development from external sources can generate significant value. There is in fact no need to internally develop research to generate value, so it's crucial to be able to enhance research produced from the outside and transfer it into the business model because building a better business model is more important than arriving first in the market. At the base of the increasing openness of corporate boundaries Chesbrough [2006] identifies the rise of new technology development costs and the shortening of product life cycle. The increase in development costs of new technologies makes it overly expensive to the R & D activities conducted internally, while the reduction of life cycle reduces the possibility for the company to recover the investment due to an early exit of the product from the market. Through the adoption of the open innovation model it is possible to reduce development costs

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and time to market by combining internal and external knowledge and also to sell to third parties internally developed technologies.

After the introduction of the term Open Innovation by Henry Chesbrough, numerous definitions have proliferated, adding nuances to the original definition and helping to deepen the concept focusing on different aspects. Among them we find for example West and Gallagher [2006] claiming that "[...] exploring a wide range of internal and external sources for innovation opportunities, consciously integrating that exploration with firm capabilities and resources, and broadly exploiting those opportunities through multiple channels. Therefore, the Open Innovation paradigm goes beyond just utilizing external sources of innovation such as customers, rivals, and universities and it is much a change in the use, management, and employment of IP as it is in the technical and research driven generation of IP. Henkel [2006] indicates as "the openness of innovation processes can lead far beyond the exchange mediated by the market, where technology is treated as a marketable good, to buy and sell on the market in appropriate circumstances. Companies can make their own technology available to the public, to attract collaboration." It is useful to emphasize that all subsequent definitions remain consistent with that proposed by Chesbrough [2003] and how a common feature emerges between the multiple definitions: the need for organizations to overcome business boundaries and integrate innovative solutions from external partners.

1.1.2 Inbound Open Innovation

One of the first distinctions that arise within the vast world of Open Innovation is the one between “Outbound Open Innovation” and “Inbound Open Innovation”. While the term “Outbound Open Innovation” identifies the practice of exploiting the technological capabilities, using internal and external marketing channels, the term “Inbound Open Innovation” refers instead to the practice to explore and integrate the exogenous knowledge for the development and exploitation of

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technologies [Chesbrough and Crowther, 2006]. Nowadays Inbound Open Innovation (IOI) is a source of competitive advantage, in fact enterprises can’t increasingly rely exclusively on their own R&D (Chesbrough and Crowther, 2006). Through Inbound Open Innovation processes companies seek to integrate external technologies to those already developed in-house, in order to support innovation, also managing to reduce development time, risks and costs associated with such activities. Companies look for fast and flexible collaborative relationships that could help to support the process of innovation and launch new products into the market in the short term. In addition, a continuous replacement of the actors involved always guarantees new and fresh ideas, innovations and technologies. The Inbound Open Innovation process can be routed to any form of innovation, both to support incremental innovations than to support kinds of radical innovations, so oriented also to help the organization to expand into new markets. It thus recognizes a flow of knowledge from the outside world beyond the firm borders to find refuge in the enterprise; for this reason the phenomenon takes also the name of "outside-in process" and it is defined as the activity with which it is possible "Enriching the firm's own knowledge base through the integration of suppliers, customers, and external knowledge sourcing " [Enkel, Gassmann and Chesbrough, 2009].

The use of external sources of knowledge increases not only in high-tech sectors but also in a growing number of companies in other sectors. Chesbrough and Crowther [2006] demonstrate this aspect through a study conducted on a sample of twelve companies operating in other sectors than those specified in hi-tech. Their study reveals that an increasing number of organizations would use open tools to access knowledge developed by others, thus witnessing the further spread of the Inbound Open Innovation phenomenon.

Gassmann [2006], in the attempt to analyse the applicability of the new Open model to define whether it is suitable for any environment and company, identifies five key aspects that facilitate the spread of Inbound Open Innovation practices, but he also focuses on difficulties and obstacles which may occur along the way. These five factors indicated by Gassmann [2006] are:

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movable capital, advanced ICT tools and reduced communication costs and logistics;

- the degree to which innovation is the result of different knowledge and technology areas, thus determining the need for access to these different sources; - the opportunity to create new business;

- the level of high technological intensity, which often makes insufficient the internally owned resources;

- the level of knowledge distribution, also due to the mobility of workers and thus of the knowledge itself.

In contrast to these elements in favour of Inbound Open Innovation, the difficulties and barriers reported by Gassmann [2006] mainly concern the fear of externally spread knowledge and key resources for the company, the difficulty in finding resources for Open Innovation processes and some psycho-cultural issues such as the Not Invented Here syndrome (NIH).

Significant precursors of the change that have led from the closed innovation model to the new Open model (especially for the IOI), can be identified in the field of the technology management process. These larger models focused on the entire technology management process give rise to kinds of patterns that could be an important base for innovation. One of the first models has been that by Gregory [1995] who states that the technology management process consists of five main stages: (1) identification of technologies which are (or may be) of importance to the business; (2) selection of technologies that should be supported by the organization; (3) acquisition and assimilation of selected technologies; (4) Exploitation of technologies to generate profit, or other benefits; (5) Protection of knowledge and expertise embedded in products and manufacturing systems. Similar patterns but with different contents are then proposed by Summanth and Summanth [1996], whose identified steps are awareness, acquisition, adaptation, advancement and abandonment and by Jolly [1997]: imagining, incubating, demonstrating, promoting and sustaining. Phaal et al. [2001] resume the model by Gregory [1995] and, relying on that model, they show the structure of a technology evaluation process with the application to a specific case study.

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from what has been developed by Chesbrough [2003], some attempts to give a structure to the Open Innovation process have arisen in the literature. To efficiently design from the early stages an Open Innovation system aiming to concrete results and to continuous improvements, Slowinski and Sagal [2010] come to the drafting of twelve good practices that are considered as fundamental inputs for an efficient Open Innovation system. The twelve good practices are based on a model that can be a useful reference for the design of any Open Innovation system. This model, called "Want, Find, Get, Manage" model follows the entire cycle of the innovation process dividing it in four phases within which are grouped the twelve good identified practices. The Want phase involves practices like “Incorporate external thinking into the strategic planning process, convert planning outcomes into a set of prioritized want briefs, utilize a structured process for the Make/Buy/Partner decision”. The Find phase is composed of “Look inside first, treat the Find effort as a bilateral process and use information gathered in Find to refine the Want Briefs”. In the Get phase we can find “Establish and maintain internal alignment, use a structured process for internal planning and negotiate with a focus on "Win-Win-Lose-Lose-Lose". Finally the three practices belonging to the Manage phase are “Hold a kick-off session to enable integration of management systems, use the kick-off session to ensure that both firms have the same understanding of the operating principles established in the agreement and train managers in both firms in the principles of conflict resolution”. From this outline of good practices for structuring an Open Innovation system it emerges then some key issues, such as the importance of identifying immediately the right assets for which the company needs, the centrality of locate possible external sources, but also the compulsory presence of internal alignment and the ability to manage the system once started. In the picture below it is reported a diagram which represents a synthesis of this model (Fig. 2).

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Fig. 2: Want Find Get Manage Model (source: Slowinski and Sagal, Good Practices in Open Innovation, 2010).

Another successful model in this context is that by West and Bogers [2014], who report a supporting model of the Open Innovation process that identifies four general stages:

1- obtaining innovations from external sources (searching, sourcing, enabling, incentivizing, contracting);

2- integrating innovations, taking into account both the factors that make it possible and those who impede integration and the changes that occur in the organization's activities;

3- Commercializing innovations;

4- Interaction mechanism, which may be related to each of the four phases. The figure below (Fig. 3) summarizes the model just described.

Fig. 3: Open Innovation process model by West and Bogers (source: West and Bogers, “Leveraging External Sources of Innovation: A Review of Research on Open Innovation”, 2013).

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This project focuses on the typical stages of Inbound Open Innovation process i.e. those indicated by Slowinski and Sagal [2010] in the WFGM model, or with ref-erence to the model proposed by West and Bogers [2014], on the obtaining and in-tegrating phase, with the relative interaction mechanisms, since these mechanisms are transverse in all stages. In light of this, we have identified across the literature, three key sub-processes that characterize these phases of the Inbound Open Inno-vation process and we have continued the literature analysis focusing on them: (i) Technology Scouting, (ii) External Knowledge Sourcing and (iii) Collaborations' Establishment. Specifically, the obtaining phase is composed by two of these sub-processes, i.e. (i) technology scouting and (ii) external knowledge sourcing, while the integrating phase regards the collaboration establishment, which includes the assessment and selection of external knowledge sources.

1.1.2.1 Technology Scouting

Technology has been recognized as one of the major sources of competitive advantage (Kocaoglu, Anderson and Milosevic, 2001; Edler, Meyer-Krahmer and Reger, 2002; Liao, 2005; Phaal, Farrukh and Probert, 2006). For any technology-based company, two questions arise: (1) How can it sustain its technological leadership and thus its competitiveness? (2) How can it develop promising new technologies and use them to move into new business fields (Rohrbeck, 2010)? Research on technological disruptions has also shown that discontinuous technological changes threaten the competitive position of incumbent companies, because they are slower to react than smaller rivals (Christensen, 1997; Arnold, 2003; Danneels, 2004). It also has been shown that being aware of discontinuous technological change does not ensure that the company will be able to produce adequate reactions (Paap and Katz, 2004; Lucas and Goh, 2009). Companies are faced with two challenges (Levinthal, 1992):

- identifying, anticipating, and assessing discontinuous change;

- effectively using this information to plan and execute appropriate reactions. Technology scouting is a systematic approach by companies whereby they assign

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part of their staff or employ external consultants to gather information in the field of science and technology and through which they facilitate or execute technology sourcing. Thus it enters into play the role of technology scouts, who may be either internal or external and must unite in themselves certain qualities and attitudes, which Wolff [1992] identifies as: "be lateral thinker, knowledgeable in science and technology, respected inside the company, cross-disciplinary orientated, and imaginative".

Although in the literature the concept of technology scouting is sometimes used in a similar manner to that of technology foresight, Rohrbeck [2010] marks the border between these two concepts, however indicating the existence of a common area related to the contribution that the technology scouting can provide to technology foresight. In fact, while the technology foresight only regards the identification, assessment and management of technological information, the concept of technology scouting focuses on creating a network of experts who could provide competitive advantage in the technology field and on the consequent actions performed by the network. And it is precisely the set of technologies identification and evaluation activities, conducted by these scouts, which happens to be the shared area between two highly related concepts but well distinct from each other.

The technology scouting can answer various recurring needs within companies: to analyse the full situation of a technology and make comparisons across multiple technologies, through documents of interest research and study; to analyse the patents of a given technology area and patents of various competitors who act in that area, even leaning to the use of text mining tools to retrace vast arrays of documents from multiple sources; to identify the technology industry trends in order to recognize the most promising technologies, their applicability also in related fields and possible future developments; to get answers to specific issue, through the attempt to address a well-defined technological problem, thanks to support tools and technical methodologies. In light of these identified needs, the technology scouting approach should aim to four major goals: (1) early identification of technologies and technological trends; (2) raising awareness of the threats and opportunities of technological development; (3) stimulation of

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innovation by combining the technology reports with business potential assessment; (4) facilitation of the sourcing of external technologies by allowing for a direct channel through the network of technology scouts to their sources of information (Rohrbeck, 2010). In a broader sense, the goal of technology scouting is to gain a competitive advantage by identifying opportunities and threats arising from technological

developments at an early stage and to provide the technological capabilities needed to face these challenges. Knowing in detail the technological trends in a certain field can be an important step to improve these capabilities to get new ideas and to obtain competitive advantage. With this regard, Spitzberg et al. [2013] build a structured process aimed at technological awareness, to be spread and then manage within the organization. This structure is based on technology scouting and technology landscape maps, trying to exploit the identification of technology drivers, technology attributes, related and emerging technologies in a certain domain, also considering the commercial readiness level and the opportunity space.

Technology scouting can be carried out through two different perspectives: (i) the internal perspective, searching information inside the company’s boundaries; (ii) the external perspective, searching information outside the company’s boundaries. Furthermore, the research target can be known, when the enterprise searches a specific technology/application or solution, or it can be unknown, when the enterprise searches technologies that could be interesting/useful in the future, and for this reason they should be monitored. Technology scouting can rely on formal and informal information sources, including the personal networks of the scouts. The most widely used technology foresight and scouting methods are using automated search mechanisms to find information in databases. Such methods include publication and patent analysis (Porter, 2005; Daim et al., 2006) as well as trend curves, such as technology lifecycles (Jones, Lanctot and Teegen, 2001), and the S-curve analysis (Sood and Tellis, 2005; Modis, 2007; Phillips, 2007). Using such methods in combination with intelligent data-mining tools (Porter and Cunningham, 2005) makes possible to retrieve useful information and can give appropriate answers in a timely manner.

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The technology scouting benefits in the field of Inbound Open Innovation are addressed in more studies. For example technology scouting has been shown to dramatically improve on organizations' success at finding and capturing critical technologies that fuel business growth [Miller, 2015] and recites an important part in improving firms' performance through the horizontal and vertical collaboration in technology acquisitions [Wang et al., 2015]. Wang et al. [2015] argue that technology scouting is positively related to horizontal technology collaborations and reliance on horizontal technology collaborations with competitors allows firms to tap into advanced technology, thereby providing a preemptive advantage that accelerates firms' innovation capabilities. And technology scouting is also positively related to vertical technology collaboration, which refers to a collaborative relationship with customers, that allows firms to capture technologies and knowledge of market development trends in a timely manner. In turn horizontal and vertical technology collaborations are positively correlated with the performance of the company and they act as mediators between the technology scouting and such performance. So the link between technology scouting and firms' performance, through the mediation mechanisms exercised by horizontal and vertical technology collaborations, provides superior performance and gains competitive advantage through the ability to exploit abundant external knowledge and technology, facilitating in this way the improve of internal innovation capabilities and efforts. The diagram in figure 4 graphically shows the relationship between technology scouting and firms' performance through horizontal technology collaborations and vertical technology collaborations as represented by Wang et al. [2015].

Fig. 4: relationship between technology scouting and firms' performance through horizontal technology collaborations and vertical technology collaborations (source: Wang et al., 2015)

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1.1.2.2 External Knowledge Sourcing

In the on-going quest for competitive advantage, organizations have increasingly focused on knowledge as a strategic resource (Alavi, 2000), which has led them to adopt a range of knowledge management practices that are intended to help them to compete more effectively (Wang, Gray and Meister, 2014). In this context, the external sourcing of knowledge is taking a more central role in companies. To access external sources of knowledge, firms can choose from different sourcing modes, such as cooperation, buying licences, and so on. Companies can choose between these external knowledge sourcing modes to react in a flexible way to new technological developments and changing market conditions (Vrande, Vanhaverbeke and Duysters, 2009). Analysing the effects of the external knowledge sourcing Kang and Kang [2009] focus on the relationship between external knowledge sourcing and performance of technology innovation, recognizing three main types of external knowledge sourcing which can cause different effects in terms of performance of technology innovation. These three main identified methods of external knowledge sourcing are: information transfer from informal network, R&D collaboration and technology acquisition. Results from this study show that information transfer from informal networks and technology acquisition have a positive correlation with the technology innovation performance, while R&D collaboration makes register a different relationship with technology innovation performance, graphically represented by an inverted-U-shape graph.

The same trend borne out by this last method of external knowledge sourcing is also presented by another relationship that involves the external knowledge sourcing in general: that between external knowledge sourcing and creativity and success of the products to be derived from this external knowledge. Salge et al. [2013] show that the expressed relationship can be represented in a graph by an inverted-U-shape, thus demonstrating that, both a too small search openness and an excessive search openness in the phase of external knowledge sourcing entail a negative influence on resulting products from that knowledge, in terms of creativity and success. Moreover, the same authors indicate how the search

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openness in external knowledge sourcing depends on three aspects that vary from time to time: project type, project leader and project environment. In fact explorative projects have more to gain from search openness at the ideation stages than exploitative projects; a project leader with substantial prior management and innovation experience results in greater search openness; a work environment actively supporting creative efforts stimulates greater search openness in external knowledge sourcing. Evidence of such inverted-U-shape relationship between external knowledge sourcing and innovation performance is also given by Ardito and Messeni Petruzzelli [2016], who also show how certain human resources practices act on this relationship, in particular the implementation of heterogeneous work groups and brainstorming sessions. When heterogeneous work groups and brainstorming sessions are implemented to conduct product innovation activities, the threshold levels after which the negative returns of external search breadth set in, shift to right as we can see in the figures below (Fig. 5-6).

Fig. 5: Effects of the heterogeneous work-groups on the relationship between innovation performance and breadth of external knowledge sourcing (source: Ardito and Messeni Petruzzelli, Breadth of external knowledge sourcing and product innovation: The moderating role of strategic human resource practices, 2017

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Fig. 6: Effects of the brainstorming on the relationship between innovation performance and breadth of external knowledge sourcing (source: Ardito and Messeni Petruzzelli, Breadth of external knowledge sourcing and product innovation: The moderating role of strategic human resource practices, 2017)

Confirming the relationship described above, Williams and Vossen [2014] find strong support for an inverted U-shaped relationship between openness to external knowledge sourcing and value appropriation in multinational corporations (MNCs) engaging in Open Innovation.

Laursen and Stalter [2006] discuss the research strategy of external knowledge sources by a firm, creating two components: the breadth ("the number of external sources or channels that search firms rely upon in innovating their activities") and the depth ("the extent to which firms draw deeply from the different external sources”).

Furthermore, in creating Open Innovation systems, firms should be very careful about the types of sources from which to draw on external knowledge. [Frey et al., 2011] identifies two different types of contributions obtained in this context: the substantial and non-substantial contributions, where a substantial contribution is an innovative and pertinent contribution. Through the collection of data and the formulation of hypotheses, they argue that while extrinsic desire for monetary rewards tends to be positively related to the making of non-substantial

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contributions, intrinsic enjoyment tends to breed substantial postings. A second factor that is discussed is the diversity of knowledge, considered a feature which could lead to useful contributions for the innovation projects. The interactions between motivations that drive an individual to make a contribution and the diversity of his knowledge are finally analysed: it emerges that the most valuable contributions are obtained in cases where there is the combination of a strong intrinsic motivation and a wide and varied base of different knowledge. In the study by Frey et al. [2011] this analysis is referred to individuals, but may in some aspects be valid not only for individuals but also for companies, indicating statistically proven attractive features, that could be considered in the searching of external knowledge sources through an Open Innovation system.

Many studies treat about benefits from the activities of searching for external knowledge sources and it is therefore useful to consider how the functions related to the enabling of external knowledge sources could be conceptualized. For example Jeppesen and Lakhani [2010] highlight the importance of opening up to external knowledge sources by firms through the demonstration of the positive relationship between the winning solution and a growing gap between the solver technological field and the problem technological field. Thus it seems important trying to break down obstacles and barriers and consider functions supporting this search because external knowledge sources able to be winners solution makers could come from anyone and from any area.

In order to bring within the firm's boundaries external knowledge sources and innovation there is the necessity to define and analyse functions related to the acquiring of these sources. In this sense, Ceccagnoli et al. [2010], jointly analysing transaction costs and the ability of internal R&D, shows that firms with more complementary assets and higher R&D capabilities have a lower propensity for searching and acquiring external knowledge sources. It might therefore be useful to examine the levels of these variables in the specific case of the company, in order to understand if and how much could be immediate and feasible to identify these functions as part of the Open Innovation system.

As regards the strategic forms of external knowledge sourcing in the field of small and medium sized enterprises, the following types of external knowledge sourcing

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can be identified: minimal, supply chain, technology-oriented, application-oriented, and full-scope sourcing [Brunswicker and Vanhaverbeke, 2015]. They suggest this classification based on the different relationships created with the external and the different internal practices that these forms of external knowledge sourcing fee.

Mol and Birkinshaw [2014] propose a further subdivision in the manner with which to conduct the external knowledge sourcing process. They identify three generic methods that can encompass all possible cases of external involvement: "direct input from external change agents; prior external experience of internal change agents; and the use of external knowledge sources by internal change agents". In analyzing the complementarity of such forms of external involvement, they show that the three types appear to be largely substitute each other rather than complementary. Another issue related to these three forms of external knowledge sourcing concerns the degree of influence which they exercise on the type of innovation. In fact Mol and Birkinshaw [2014] ask whether and how much these three modes of external involvement affect the innovation radicality/incrementality and the fact that it is systemic or not. From their studies it can be seen as a direct input from external change agents usually lead to systemic and incremental innovations and how the lack of prior external experience of internal change agents causes systemic and radical innovations. The use of external knowledge sources by internal change agents does not seem to have clear and unambiguous consequences on the type of follow-on innovation. The table below (Tab. 2) shows all the key features of the three categories of external knowledge sourcing identified by Mol and Birkinshaw [2014].

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Tab. 2: key characteristics of the three forms of external involvement (source: Mol M. J. And Birkinshaw J., The Role of External Involvement in the Creation of Management Innovations, 2014)

Focusing on external sources of knowledge that can be reached, we can identify four different groups of sources: science-based partners; horizontal connections; value chain partners, and technology service providers [Chen et al., 2016]. All these external knowledge sources have different relationships with the internal R&D activities: it is shown that the combination of the positive effects of higher internal R&D capabilities and external sourcing from value chain partners and horizontal connections lead to improvements in the firms' innovative performance; it seems to be no complementarity relationship in the joint action of internal R&D and external knowledge sourcing from science-based partners and technology-service providers.

A crucial concept for companies to be able to conduct efficiently and to exploit the external knowledge sourcing process, is the absortive capacity defined as "a firm's ability to recognize the value of new information, assimilate it, and apply it to commercial ends" [Cohen and Levinthal, 1990]. In fact to be able to tap into external sources of knowledge for innovative purposes a company need a certain ability to identify, create and carry on cooperation with external parties for the

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acquisition of external knowledge, and an appropriate subsequent absorptive capacity. Internal R&D, training and an educated workforce, as core aspects of firms' absorptive capacity, are positively associated with innovation cooperation [Clausen, 2013]. This shows how external knowledge sourcing requires costs and targeted investments to join the company and give the desired results in the field of Open Innovation. Without investing in internal R&D, training and recruiting workers with good educational qualifications, companies cannot assimilate relevant external knowledge; in this way they may not be able to enter the path of Open Innovation and to obtain satisfactory outcomes.

1.1.2.3 Collaborations' Establishment

A promising challenge in the OI paradigm [Chesbrough, 2003] is building cross-enterprise processes [Deck and Strom, 2002] to leverage the internal strengths with partners’ competencies and knowledge to provide new/superior products/services [Mohr and Spekman, 1994], to reduce risk and possibly to open new market segments. Researchers and practitioners have recently paid great attention to technological partnering. For the purposes of integration and collaboration the characteristics of those figures who perform tasks related to Open Innovation within the firm are crucial. Du Chatenier et al. [2010] determine through interviews and focus groups the competencies of a professional profile who works in an Open Innovation team, defining the skills and indicating how he could help to create new useful knowledge for the attainment of the Open Innovation objectives. In this light, it is also essential to emphasized the typical and new aspects of the Open Innovation approach. Herzog and Leker [2009] analyse this approach comparing it to that related to a closed approach. To draw the conclusions they treat typical themes that take particular connotations in the field of Open Innovation, such as management support and risk taking, also focusing on typical characteristics and phenomena as the syndrome of "not invented here" (NIH). The need for technological collaboration is increasing and benefits can be gained from participating in networks. In networks, firms can

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create linkages between each other in order to obtain common or complementary objectives of innovation [Chesbrough and Teece, 1996; Davidow and Malone, 1992; Rothwell, 1994; Upton and McAfee, 1996]. Once the firm decides that a certain technology is to be acquired externally, it needs to identify the most appropriate mode for such an acquisition. A lot of variety of organizational modes can be adopted to access external sources of technology [see, for example, Roberts and Berry, 1985; Brockhoff, 1991; Chatterji, 1996; Millson et al., 1996]: (i) acquisition; (ii) educational acquisition; (iii) merger; (iv) licensing; (v) minority equity; (vi) joint venture; (vii) joint R&D; (viii) R&D contract; (ix) research funding; (x) alliance; (xi) consortium; (xii) networking; (xiii) outsourcing [Chiesa and Manzini, 1998]. From a financial point of view there is a distinction between equity and non-equity modes of collaboration; the latter ones don’t need an equity involvement. Our focus is on non-equity modes of collaboration, which can be:

licensing, when a company acquires a license for a specific technology. Often especially in the early development stages, many enterprises acquire advanced technologies from multinational corporations, thus being able to combine their own knowledge with externally acquired technology and accumulating in the meantime the necessary technological skills gradually [Chen and Chen, 2014] .

joint R&D, when a company agrees with others to jointly carry out research and development on a definite technology (or technological discipline), with no equity involvement. This form of joint R&D does not exclude the continuation of the usual internal R&D activities. Choi et al. [2012] show how there could exist complementarity between internal R&D and joint R&D and indicate as contextual variables the firm's cumulative patent stocks and the scientific information inflows from public research institutes and universities, driving the decision to combine in-house and joint R&D.

R&D contract, when a company agrees to fund cost of R&D at a research institute or university or small innovative firm, for a definite technology. In this regard Tubig and Abetti [1990] propose four variables

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identified as the most influential on performance arising from the R&D contracts: type of R&D, type of solicitation, type of contract, and size of business of the contractor.

research funding, when a company funds exploratory research at a research institute or university or small innovative firm to pursue opportunities and idea for innovation;

alliance, when a company shares technological resources with other companies in order to achieve a common objective of technological innovation (without equity involvement). For this form of collaboration Han et al. [2012] confirms some hypotheses about the effects that establishing an Open Innovation alliance may entail. They indicate positive returns, further increased every time a leader in its market join the alliance, however determining at the same time also positive abnormal returns for the rival firms that competes with the firms participating in the Open Innovation alliance due to knowledge spillover. Another important aspect that is underlined is that companies that build alliances with heterogeneous partners get higher returns than those who create an alliance composed of more homogeneous partners and, companies that base the alliance on radical innovations achieved greater returns than those that focus on incremental innovations. Finally, another key aspect is that those companies participating in the alliance with full access and decision authority can reap returns much greater than those who have limitations in terms of authority and decision-making power.

Consortium, several companies and public institutions join their efforts to achieve a common objective of technological innovation (without equity involvement).

Networking, when a company establishes a network of relationships, to keep the pace in a technological discipline and to capture technological opportunities and evolutionary trends. The main reasons that can push networking are: accelerating innovation process, proving effect of innovation at an early stage to save time and money, expanding product range, sharing risks and gaining knowledge optimizing innovation

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processes [Maurer and Valkenburg, 2011]. In following these motivations it is also possible to detect various types of challenges that a company faces in the structuring of its network path. Maurer and Valkenburg [2011] divided these challenges based on three levels: organizational level (as the high degree of regulation within industries in certain sectors, differences in legislation and routines, different size of companies, trusts, finding partners), project level (such as the lack of established methods, formalization of agreements and partnership management) and actor level (sharing knowledge, relationships within teams, management expectations of team members).

Outsourcing, when a company externalizes technological activities and, then, simply acquires the relative output. R&D outsourcing of core-related activities facilitates the access of fresh knowledge and new technology. This helps to benefit from complementary capabilities. Though, so this could happen it requires a sufficient capacity of appropriation and assimilation of the results of the outsourced R&D. Furthermore, the probability that the company recourse to outsourcing decreases with increasing technology radicality and with the increasing size of R&D internal department [Davidson and McFetridge, 1985]. Moreover, in general, outsourcing is more frequent the mores codifiable and less complex the technology is. The internal capacity to manage and apply the findings arising from the outsourcing activities is indispensable especially if the company intends to take possession only of the results and not of the accumulated person-embodied skills [Veugelers, 1997]. Teirlinck and Spithoven [2013] indicate that the propensity for a firm to engage in R&D outsourcing should be seen in relation to the internal R&D personnel potential to assimilate and manage external ideas and it is linked to the size of the firm. Particularly, a lower internal availability of research managers and R&D experts in the firm should be related to an environment that stimulates knowledge external relations by means of R&D outsourcing.

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An aspect to consider in the collaborations' establishment process concerns the relationship between the acquisition of external knowledge for innovation and the ability to take ownership of these innovations and related benefits, through patenting. This relationship is important because it strongly affects the type of collaboration to be established with the various partners. This issue leads to the "paradox of openness", namely the fact that opening up to outside sources of knowledge to innovate may weaken the firm's power to capture rents from that knowledge [Laursen and Salter, 2014]. About this paradox there are two different schools of thought: the spillover prevention view and the organizational openness view. The spillover prevention view argues that firms that advance collaboration with external partners need to resort to patents to reduce the spillover of valuable knowledge. This is because they want to protect their innovation obtained through collaboration and the background knowledge implicit in the innovation and moreover they want to communicate messages about their value as innovation partners. Instead, the organizational openness view is based on the fact that companies which have recourse to external sources of knowledge should limit as much as possible the use of patents to make money from collaborations undertaken and to avoid to appear a less attractive partner for future more collaborations with the same partner or with other partners. In reference to this Arora et al. [2016] show that the relationship between the acquisition of external knowledge and patenting is very tied to the company's position, in the sense that leading companies are more prone to unintended knowledge spillovers than the follower companies. It follows that, with the increasing degree of openness, the patenting activity is more widespread in the leader companies rather than in the follower ones. And this has a significant influence on the types of collaboration selected by the companies for the process of acquisition of technology and knowledge. In confirmation of this concept, Miozzo et al. [2016] investigate the relationship between the importance of innovation collaboration and the importance of formal appropriability mechanisms, focusing in this case on the knowledge-intensive business services firms, which naturally undergo regular conflict over ownership of the jointly-developed knowledge assets. The paradox is also manifest in this case. In fact, the formal appropriability mechanisms can