OPEN INNOVATION CHOICES, ITS DETERMINANTS AND PERFORMANCE: THE MODERATION OF ICT TOOLS A survey in italian manufacturing companies

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RELAZIONE PER IL CONSEGUIMENTO DELLA LAUREA MAGISTRALE IN INGEGNERIA GESTIONALE

Open Innovation Choices, its Determinants and

Performance: the moderation of ICT Tools

A survey in italian manufacturing companies

RELATORI IL CANDIDATO

Prof. Luisa Pellegrini Francesco Cardini

Dipartimento di Ingegneria dell’Energia dei Sistemi, ing.francesco.cardini@gmail.com del Territorio e delle Costruzioni

Sessione di Laurea del 10/07/2019 Anno Accademico 2018/2019

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Alle persone che si amano, i migliori partner che ci possano essere nella vita

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Open Innovation Choices, its Determinants and Performance: the moderation of ICT Tools

Francesco Cardini

Sommario

L’implementazione del processo di open innovation comporta la definizione di una serie di condizioni in grado di promuoverlo: “chi”, “perché” e “come” viene coinvolto. La letteratura ha indagato le motivazioni che stanno alla base dell’apertura del processo di innovazione, i partner che potrebbero esser coinvolti, le opportunità che si possono raggiungere e i modi tramite cui questi processi possono esser implementati. L’evidenza empirica degli studi svolti ha dimostrato che non esiste ancora una convergenza. In particolar modo nell’ambito della questiona del “come”, gli strumenti di Information and Communication Technology (ICT) hanno molto da poter offrire, ma la letteratura è ancora molto carente in merito alla opportunità che questi strumenti offrono in termini di supporto alle diverse fasi del processo di innovazione. Lo scopo di questa tesi è quello di indagare le scelte di open innovation, le implicazioni che tali scelte hanno in termini di performance e di portare un contributo innovativo attraverso l’analisi del ruolo degli strumenti di ICT.

Abstract

The implementation of the process of open innovation involves the definition of a series of conditions that can promote it: "who", "why" and "how" is involved. For each variable the literature has allowed to investigate the reasons behind the openness of the innovation funnel, the partners that could be involved, the opportunities that can be obtained through this relationship and the ways in which these processes can be implemented. The empirical evidence of the studies carried out has shown that there is still no convergence on the results that link the relationships between these actors. Especially in the context of the "how" question, ICT tools have a lot to offer but the literature is still very weak on the ability of these tools to facilitate the phases of the funnel. The aim of this thesis is to investigate the relationship between the main factors and subjects involved in the phases of the open innovation funnel and to bring an innovative contribution through the study of the role of ICT tools.

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Index

1. Introduction ... 7

2. The Context and Objective of the Research ... 8

3. Methodology of Study ... 14

4. Analysis of Literature ... 17

4.1. Overview on Open Innovation... 17

4.2. The Internal Determinants ... 19

4.4. Openness to Partners and Opening Performance ... 25

4.5. The Role of ICT Tools ... 30

4.6. Summary of the Gaps and Research Questions ... 34

5. Investigation Methodology ... 38

5.1. Sample and Data Collection... 38

5.2. Constructs and Items... 41

5.3. Data Analysis ... 45

6. Data Analysis Results ... 46

6.1. Factor Analysis ... 46

6.1.1. Factor Anlysis Internal Determinants ... 46

6.1.2. Factor Analysis Openness ... 50

6.1.3. Factor Analysis Performance ... 56

6.1.4. Factor Analysis ICT ... 61

6.1.5. Factor Analysis Results ... 64

6.2. Analysis of Items and Factors ... 66

6.3. Regression Analysis ... 72

6.3.1. Regression Analysis RQ1 and HP1 ... 72

6.3.2. Regression Analysis RQ2 and HP2 ... 81

7. Discussions, Conclusions and Future Research ... 97

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1. Introduction

Over the years, open innovation has become a strategic element for many companies operating in different sectors. Therefore, open innovation research has gained a great deal of momentum over the years and scientific literature has begun to investigate and analyse this process from different points of view and perspectives, including different but heterogeneous points of view. There have been several cases, representations, theories, contexts that have emerged over time. One of the most promising perspectives proposed in the existing literature allows to differentiate open innovation into three different processes according to the way in which this process is carried out (Enkel et al. 2009; Gassman and Enkel, 2004):

• The "inbound" process that consists of accessing technical and scientific knowledge and skills from external sources and then integrating them internally.

• The "otubound" process, which involves searching for partners with a business model that is more suitable for commercialising the technology (Chiaroni et al., 2009).

• The coupled process, which consists of a balance between the two previous processes. Although analysing especiall the inbound process, the literature has pointed out that the implementation of this process implies the definition of a set of variables: "who" is involved, "why" is involved and "how" is involved.

With regard to the question of who is involved, the selection of the partners with whom the collaboration should take place is discussed (Laursen and Salter, 2006). In the section of "why" a subject is involved, the motivations and objectives underlying this collaborative process are discussed (Van de Vrande, De Jong, Vanhaverbeke, De Rochemont, 2009). The "how" issue concerns questions related to the implementation of open processes, as organizations need tools and mechanisms that allow them to make full use of the opportunities of open innovation (Slowinski and Sagal, 2010; Chiaroni et al., 2009). As far as this aspect is concerned, little attention has been paid to those tools that companies can use to support the implementation of the inbound open innovation process and to support the process that allows them to take advantage of and benefit from external sources of knowledge.

Although there are also other studies in the literature that deal with the main motivations that support openness to partners (Van de Vrande, De Jong, Vanhaverbeke, De Rochemont, 2009), the external partners that may be involved (Laursen and Salter, 2006) and the opportunities that

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may come out of this relationship (Chiaroni et al., 2009), these analyses are not always all converging towards the same result. Therefore, the relationship that binds the actors involved during the phases of this funnel in order to obtain the desired benefits at the basis of open innovation is not taken for granted and is currently still largely under investigation.

Especially in the context of the "how" question, ICT (information and communication technology) tools have a lot to offer as they allow to promote activities such as communication between different actors, cooperation, sharing and knowledge creation. These tools can play a supporting role in the implementation of the open innovation process. Although these tools are developing more and more rapidly within the business context, the literature and studies that allow to investigate the advantages, disadvantages and how these tools can facilitate the phases of the funnel, are still lacking.

The aim of this thesis is to investigate the relationship between the main factors and subjects involved in the phases of the open innovation funnel in order to add further research to this aspect which still has non-convergent results and bring an innovative contribution thanks to the study on the role of ICT tools.

2. The Context and Objective of the Research

Companies have always aimed at exploring new fields of knowledge and new technological fields to ensure a competitive advantage over competitors. From this need derives the importance that has always covered over the years the process of innovation.

The innovation process is not limited to the improvement and optimization of existing products and technologies, but also concerns the development of new skills, products and technologies (Faems, 2005).

Although there are differences and specific characteristics, the innovation process is always characterized by three fundamental steps:

• An appropriate initial exploration study.

9 • The marketing of the idea.

During the first phase, new ideas are generated, evaluated and selected on the basis of their characteristics, development context, available company resources and knowledge. This first phase can take place in very different ways, which are changing over time and have been shaped by the development of new practices and processes, but all of them involve brainstorming activities crossed with each other in order to create a new idea.

The second step is to develop the ideas themselves so that an idea on paper is transformed into a practical application of a product or process based on business needs.

Marketing, on the other hand, includes aspects related to the discounting of activities designed to enter the global market (Shilling, 2009).

In the past, companies have always carried out an internal process of research and innovation, trying to grow and improve, exploiting their available resources as well as the technologies developed by their departments. This model, usually referred to as "closed innovation", is characterized by the fact that the process of research in order to progress and generate innovation takes place inside the organisational borders.

In order to ensure the optimization of the innovation process, closed companies acquire the most valuable human skills, with the aim of creating new ideas that can then be exploited and marketed, protecting them with intellectual property tools (IPPM) which ensure the appropriability of the innovation. At the basis of the functioning of this closed model, the innovation process must avoid any contact with the outside world in each of its phases in order to reduce the possibility of intellectual property violation and loss of strategic knowledge. Over the years, however, the limitations of the "closed innovation" model have become increasingly evident. As indicated by Lichtenthaler (2009), a "closed innovation" strategy limits the company's ability to obtain the strategic benefits that could be gained by using external resources.

In 2003 Henry Chesbrough with his book "Open Innovation" identifies a change in the innovation activities of companies, observing a growing level of attention to resources developed by external partners. The term open innovation is created in a socio-economic context characterized by a growing integration between different sectors, technologies and products, with product life-cycles always shorter and converging between them. According to

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Chesbrough, open innovation allowes the inflow and outflow of knowledge in order to accelerate internal innovation and expand markets (Chesbrough, 2003). This concept assumed that companies would use external and internal ideas to advance their technology (Chesbrough, 2003).

In this context, an increasingly important role has been played by external actors such as suppliers, customers, universities and various types of public and private institutions, together with research centres. Chesbrough (2003) in his study underlines how the search for external competences can become significant and one of the most valuable processes of the company. At the basis of the growing opening up the organizational boundariesand the progressive departure from the closed innovation model, Chesbrough (2006) identifies the increase in new technological development costs and the reduction of product life-cycles in many technological sectors, mainly in the high-tech sectors up to those with a lowertechnological content. The increase in costs in the process of developing new technologies makes the R&D activities excessively expensive, making it necessary to create a new path to reduce costs, while the reduction in product life-cycles reduces the possibility for the company to recover the investment, caused by a potential early exit of the product from the market.

The adoption of the open innovation model allows to reduce development costs thanks to the sharing of skills, responsibilities and project risks and to reduce time-to-market, by combining internal and external knowledge.

The open innovation model can go further than simply using external sources of innovation such as customers, competitors and universities because open innovation also means making technology available to the public in order to attract collaborations.

It is interesting to note that all the following definitions remain consistent with the one proposed by Chesbrough (2003) and that a common feature may emerge among the many definitions: the need to go beyond company limits and integrate innovative solutions from external partners. Although there are potential theoretical benefits from openness, companies found it difficult to implement open innovation initiatives (Huston and Sakkab, 2006 and 2012) because significant internal support resources are needed to unlock the potential of such collaboration (Chesbrough and Garman, 2009). In addition to this, it should be considered that openness towards partners can also represent a high risk of loss of intellectual property, so it will be necessary to plan an appropriate use of tools to protect the ideas developed (such as patents) not to run this risk. The

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existing risk not only concerns the loss of the new developed idea, but also the loss of the core knowledge of the company, which is why this relationship with the partners must be properly planned and protected so as not to incur these risks.

As an important resource for moderation in the context of open innovation, ICT tools providesupport and in fact they have long been shown to positively influence the adoption of this process (Verbano et al., 2013; Chiaroni et al., 2009).

Many companies use online communities to actively seek out potential external knowledge (Di Gangi and Wasko, 2009) and the virtual environment of knowledge transfer and integration is supported by innovation and communication tools. However, although these examples show how ICT tools have made this process simpler (Whelan et al., 2012), it has not yet been demonstrated which categories of ICT tools can play a more effective moderating role in supporting the relationship with partners in achieving innovation goals. One of the objectives of the study is to discuss the moderation role that the ICT tools play in the relationship between openness to partners and the performance achieved.

The following research framework (figure 1) represents the relationships that bind an open innovation project from the beginning of its conceptual phase to the achievement of the performances obtained.

12 Figure 1: research framework

OPENNESS AT THE PROJECT LEVEL • Partners • Phases PERFORMANCE • Innovative • Financial PRE-CONDITIONS • IPPMs INTERNAL DETERMINANTS • Objectives for collaborating

EXTERNAL DETERMINANTS • Business environment • Technological environment )

INTERNAL CONTEXT

• ICT tools for supporting the relationship with partners

• Assimilation of external knowledge • Routines/incentives to innovate • Organizational culture

COLLABORATION CLIMATE • Collaboration climate

Reasons for using IPPMs

GAP 3 GAP 4 GAP 1 GAP 2 GAP 5 PARTNER SEARCH

• ICT tools for partner identification CONTROL VARIABLES • Country • Industry • Size • R&D expenses

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The framework in figure 1 is composed of several constructs which represent all the stages in which the process of open innovation is generally articulated:

• In the white rectangles there are the determinants (both internal and external) and the pre-conditions that push and allow the opening towards external partners. The preliminary conditions concern the tools that companies can use in order to prevent problems related to the knowledge shared and created during the collaboration and to allow the appropriability of the results of the collaboration.

• The grey rectangle represents the openness choice, though the collaboration with a number of partners both in width and in depth.

• The blue rectangle represents the performance achieved through the relationship with partners. Performance is measured at the innovative and financial level.

• The pink rectangle defines the control variables.

• Inside the yellow rectangles we find the variables that could play a role of moderation of the main frame of reference. There are two moderating constructs. On one hand, we have the "search for partners" which concerns the tools that the company uses to more easily identify the partners; on the other hand we find the internal context and the climate of collaboration that is established with the selected partners and the implicit exchange of knowledge that takes place through the tools.

Inside this frame of reference that defines the conditions and methods of the open innovation process, our studio wants to focus on four basic steps:

• The internal determinants underlying the openness process. • The choice of which type of partner to open up.

• Performance achieved through collaboration with partners.

• The role of moderation played by ICT tools in fostering the relationship with partners in achieving the objectives set.

The objective of this thesis is to analyze a subset of the framework represented with the aim of carrying out a preliminary analysis of the entire research study that will continue in the coming months, with the aim of going to study in advance those that are the main relationships between the elements that come in play in the process of open innovation aimed at creating a new product.

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The choice of these themes comes from what has been suggested in the literary field, since the framework created aims to cover the research gaps in the literature, which is in fact inconclusive in many issues:

• The starting point of the model is to investigate what are the internal determinants that can condition certain categories of manufacturing companies in their choices of open innovation towards different categories of partners (GAP 3).

• One of the main questions in the literature concerns the relationship between open innovation and performance (GAP 1): although the attractiveness of this collaboration is underlined in several studies, some of them are waving caution flags on the performance achieved by means of open innovation .

• Recent publications have insisted on the importance of investigating how different internal contextual factors moderate the relationship between openness and performance. Indeed, several management, technological, organisational and skills tools (such as the combination of routines, management practices, incentives, values and attitudes supporting the open innovation process) are necessary to enable openness and to get the most from it (GAP 2).

3. Methodology of Study

The method of analysis used in this thesis was the review of the literature with the aim of closing gaps regarding open innovation in its components of internal determinants, openness, performance and role of moderation of ICT. The literature review was conducted using the Scopus scientific database (http://www.scopus.com/home.uri).

The research on the extant literature was divided into three main sections of study. In general, the searches were carried out using keywords that were entered in the search fields in some cases individually, and in other cases combined with each other through the logical connective "^" (and).

For each research, a preliminary analysis of the results was carried out by reading the relevant titles and abstracts. In this way it was possible to carry out an initial screening of the research

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studies obtained. Then, the studies selected in the previous phase were analyzed in depth by reading the entire articles. Following this second analysis, the final selection of the articles used to carry out this thesis study was made.

In the first section, the existing literature on open innovation was analysed in order to frame its main characteristics. Therefore, I have analysed the closed innovation strategy and how it differs from open innovation, explaining the advantages of implementing this model and the factors that influence it . Afterwards, I completed the study on the determinants that influence open innovation relationships.

Table 1 shows the keywords and the combinations used in this section:

Individual Keywords Combinations Inbound Open

Innovation

Open Innovation Dynamic Capabilites; Openness; Performance; Conditions Internal Determinants Size; Objectives; Goals; Finality

Table 1 - Keywords and combinations used in the section

The search allowed the identification of 387 articles, which were reduced to 71 with the procedure used for the first selection and then to 24.

In the second section, the existing literature on the types of partners to which companies can open their innovation funnel was analysed. The study aimed at investigating which types of partners companies are most likely to open up to achieve their business goals.

Then I investigated which are the partners to which companies typically open and the results that companies that open up to partners generally aim to achieve. In this case I reviewed the literature in order to investigate what results are typically achieved by companies. This has been a starting point to verify what are the objectives that companies can achieve.

Table 2 shows the keywords and their combinations used in this section for the review of the literature:

16 Individual Keywords Combinations

Openness Open Innovation; Partners; Partners

Open Innovation; Know-how;

Knowledge; Knowledge Management; Knowledge Management Systems; Application

Performance Open Innovation; Finance; Innovation Process; Goals; Objectives

Table 2 - Keywords and combinations used in the section

The search allowed the identification of 442 articles, which were reduced to 133 with the procedure used for the first selection and then to 41.

In the last section I analysed the most appropriate ICT tools to moderate the relationship between openness and performance, which is a scarcely investigated field of study. The objective was to study which ICT tools were most appropriate to play this role of moderation. The search was done using the following keywords and their combinations as shown in the table 3:

Individual Keywords Combinations ICT

Tools; Support; Open Innovation; Performance; Knowledge; Knowledege Management

Table 3 - Keywords and combinations used in the section

The search allowed the identification of 57 articles, which were reduced to 11 with the procedure used for the first selection and then to 7.

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4. Analysis of Literature

4.1. Overview on Open Innovation

From several years the Open Innovation is considered as a tool to obtain a competitive advantage in many areas of business. In order to remain competitive, companies cannot only look at their own R&D, but many must necessarily create a synergistic relationship with other subjects and external partners in order to share risks and exploit mutual competences (Chesbrough and Crowther, 2006).

The literature on open innovation has extensively studied the issue of involving different partners along the phases of the innovation tunnel both in defining the number and types of partners involved (Laursen and Salter, 2006; Enkel, Gassmann and Chesbrough, 2009; Kneupp and Gassmann, 2009; Tether, 2002).

Gassmann (2006), in an attempt to analyze the applicability of the new model to define if it could be suitable for any environment and company, identifies five key aspects that facilitate the diffusion of open innovation practices:

• Globalization.

• The degree of innovation.

• The opportunity to create new ideas. • The level of high technological intensity. • The level of knowledge distribution.

The first leads to a rapid movement of innovations thanks to the synergistic effect of advanced ICT tools currently available to many companies and the increasing reduction of communication and logistics costs. The degree of innovation is the result of different areas of technology and knowledge, determining the need to have access to these sources to stimulate technological development. The opportunity to create new ideas is the main driver that pushes companies towards the innovation process, as it is considered the first essential element for the creation of competitive advantage. The level of technological intensity is also considered by Gassman (2006) as one of the main factors, as it often becomes the motivation that leads firms

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to look for resources outside the company, considering those available insufficient to achieve the objectives set.

The level of knowledge distributionconditions accessibility and the strategic importance of know-how and the relationship with partners.

An interesting perspective on open innovation is about process analysis and how this process of innovation can be integrated with the available processes. In this perspective, West and Bogers (2013) have developed an integrated model to support the exploitation of the open innovation composed of three main phases:

• Getting innovations from external sources. • Integrating innovations.

• Market innovations.

The research model of this thesis is part of this perspective and its objective is to investigate what are the objectives that push companies to open up to certain types of partners and how processes are able to interface with each other. Above all, one of the objectives of the research becomes that of investigating how such partnership relationships can bring about an increase in company performance.

In this sense, i can define that this research study will concern the main phases of the inbound open innovation process:

• Openness. • Performance. • Moderation.

Obviously in this context of preliminary analysis i can say that Gassmann (2006) and West and Bogers (2013) were neither the first nor the only ones to define the fundamental characteristics of the process of open innovation.

Another very famous work was by Tavakoli et al. (2017). He and his colleagues outline the three fundamental characteristics of an open strategy:

• Clarity. • Inclusiveness.

19 • The support of appropriate ICT tools.

From this point of view, clarity becomes a fundamental element to define the accessibility and visibility of information, an essential element at the base of the relationship that is established with the partners of the relationship and the element of inclusiveness that allows to define a common strategy to achieve the business objectives.

Also in the model studied by Tavakoli et al. (2017), ICT tools play a fundamental moderating role that allows the facilitation of integration. In support of this statement, the authors analyse some examples of companies and also indicate which ICT tools are used to promote open innovation.

As a starting point i can argue that this process is recognized by many literature studies and practical reality as a tool which allows companies to maintain or increase their competitive advantage. As mentioned above, the objective of this study will be to investigate what are the conditions that can promote this process, especially in a first phase we will study the internal determinants that encourage openness to partners, which types of partners companies are most open, the performance achieved by this relationship and how ICT tools can play a role of moderation in achieving the desired objectives.

As will be seen in detail in the following, it has already been extensively analyzed in the literature what the advantages and disadvantages of open innovation can be. In this regard, however, it becomes interesting to go and investigate what are the factors, specifically in accordance with the literature or not, that could facilitate this process, its disadvantages and limitations.

4.2. The Internal Determinants

At the basis of this collaborative process it’s important to understand what determinants can facilitate open innovation choices. In particular, we will focus on the internal determinants and objectives of the collaboration. This phase is related to the context of identifying the necessary resources, which will be closely related to the business objectives. In order to determine the

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appropriate partners to which the partnership relationship can be focused, companies must first determine the objectives of the collaboration.

Objectives as in all business processes are the fundamental driver that move resources and guide activities.

The first phase that must then be carried out to make the partnership relationship effective and efficient is process planning:

• Establish the objectives that are at the base of the open innovation relationship. • Determine the skills (technical or human) needed to achieve the objectives. • Establish the resources needed to achieve these objectives.

• Identify company Gaps (technical resources, skills).

• Determine if these Gaps should be filled with internal or external resources. • Determine how the company can find external sources that can fill those gaps.

Some of these steps are also analyzed in the studies developed by Slowinski and Sagal in 2010 and by Laursen and Salter in 2006, underlining how companies can identify or seek external sources of innovation by collaborating with a variety of external members or by looking for specialists with specific knowledge of the sector (Tether and Tajar, 2008) with the aim of adding or integrating business knowledge (Laursen and Salter, 2006; Witzeman et al., 2006).

Companies can also look for partnerships in which innovation is "driven" by external stakeholders (Spaeth et al., 2010), but as pointed out by the studies this leads to the consideration that it is still the objectives that guide the choices of open innovation.

The literature has already identified that according to the objectives, the external sources of knowledge that can be involved can be very different and diversified among them (Li and Vanhaverbeke, 2009; Gassmann et al., 2006; Lim et al., 2010). The first phase of our research study is part of this articulated context, which aims to determine the objectives for opening up to partners, since companies in this first phase must ask themselves what methods can be used to promote the phase of obtaining knowledge (West and Bogers, 2013).

As can be deduced from the research framework, the development of ICT tools in recent years has certainly facilitated the search for external sources of innovation, as well as the development

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of technology in general, of the internet, online communities (Dahlander and Wallin, 2008), internet platforms such as blogs (Droge et al., 2010; Kohler et al., 2009). All these tools have been useful and have allowed the moderation of the search for partners. However, this study will not focus on the moderating role of these tools, even if the literature seems to be missing on this and therefore there may be room for study.

The issue of why companies use open innovation processes has already been addressed in the literature, so as to try to understand what may be the determining factors and causes behind the phenomenon.

Schroll and Mild (2012), after an in-depth critical review of the literature and empirical research on it, have studied the potential determinants of openness. The authors reduce the factors into two categories of analysis: organisational and environmental conditions. The category of greatest interest that could interface with our study seems to be the first, called "internal or specific of the company" also by other authors (eg. Lazzarotti et al., 2011; Drechsler and Natter, 2012). This includes a number of factors such as the objectives pursued through the collaborations, the drivers of the collaboration itself. Among the various objectives are the main ones such as: company innovation strategy, investments in R&D, company intellectual property strategy (IPPM).

From literature studies it seems to emerge that the objectives underlying the open innovation relationship are among the main determinants that companies evaluate as an internal determinant behind the relationship itself. It becomes interesting on the basis of this to try to understand what may be some of the most interesting objectives investigated in whole or in part by the literature that are the basis of this partnership relationship.

The literature (Hagedoorn, 1993; Calantone and Stanko, 2007) in fact seems to suggest that there are two categories of objectives that companies try to achieve by means of open innovation. On one hand, in fact, we could identify objectives that we could define as business objectives and that we could summarize in the following main ones:

• Reduce costs.

• Reduce time to market. • Reduce business risks.

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Other objectives may relate to the performance component and we can consider this, for example:

• Extension of competences. • Extending creativity.

• Access to advanced technologies to achieve innovative developments.

At the basis of this study, in which i’m going to determine the main determinants that allow to establish the propensity to open up to certain types of partners, the literature seems to have already determined interesting correlations:

• Objectives for finding new ideas, or ways to reduce the uncertainty associated with bringing innovation to market, seem to encourage collaboration with customers (Von Hippel, 1988).

• Reducing costs or improving the quality of inputs seems to favour partnership with suppliers (Gassmann and Enekl, 2004).

• Universities and research institutes are called upon to provide advanced technologies and radical product innovations (De Backer et al., 2008; Tether, 2002; Parida et al., 2012). However, other studies state that these partners are also sought after by companies to support the efficiency of the innovation process because they allow not only the experimentation of new technologies, but also the improvement of existing technologies (Faems et al., 2005).

These results seem to be the motivation for researchers to continue investigating possible new relationships between driver types and partner types, as the literature has now amply demonstrated these are the two categories of main objectives that companies want to pursue, but what is not yet complete in the literature is the study of the combination of these two categories of objectives and all types of partners to which companies can open.

The drivers of open innovation are obviously linked to the innovation and technological strategy of a company. This strategic component must interface with that part of the strategy that deals with the growth of an organization through the development of new products, services, processes or business models (Cooper, 2000).

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• Radical: where the objective of the innovation strategy is to develop and bring to the market something that represents an innovative progress not yet present and existing at the current state of the art.

• Incremental: where instead the objective is to develop only an improvement compared to an existing condition.

Regarding the relationship between innovation strategy and open innovation, the literature suggests that when the emphasis is on radical innovation, open innovation should increase in intensity and frequency.

Companies that focus on radical innovation are rarely able to develop all their knowledge internally, and therefore have to rely heavily on complementary external sources (Colarelli O'Connor, 2006).

Many other studies have tried to link the objectives underlying the relationship of open innovation with the propensity to openness towards partners. Crema et al. (2014) have studied the influence of different types of business strategy (innovation, diversification and efficiency) on the propensity to open innovation and conclude that the innovation strategy is crucial to explain the open innovation choices. They found that companies that adopt a competitive innovation strategy (in order to gain a market advantage) are strongly motivated to open their processes towards the support of ICT tools and open innovation practices. However, these practices do not ignore internal investment in R&D, confirming what has already been pointed out by other studies such as Lazzarotti et al. (2011) who state that internal and external sources are often complementary: often companies that practice open innovation end up spending more on R&D. This higher expenditure could be justified by the complexity of the opening process (Schroll and Mild, 2012).

Many other studies have investigated what can be the drivers at the opening such as that of Verbano et al. (2015) that have identified how technological aggressiveness can be the basis of open innovationchoices.

Although there are many references and also many other aspects to consider that it is not only the objectives that are decisive for openness: there may be additional drivers that guide openness (Verbano et al., 2015), the objectives will then have to be linked to the planned innovation strategies (Bessant, 2005). Despite all the other aspects complementary to the objectives, the literature has now consolidated, however, that these are the main factors that

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push companies towards open innovation practices, as well as it has amply demonstrated that all the objectives, even if different from each other, fall either into the category of commercial objectives or into the category of performance innovation objectives. Companies that want to pursue commercial objectives typically have as their main focus the performance of the market: they want to innovate in order to increase sales, enter new market segments, defend themselves from a competitor that has launched a new product. Companies that want to pursue a performance innovation objective, on the other hand, have a focus on developing process or product innovations. These companies will be interested in acquiring or extending their knowledge, making process innovation, improving a service, improving a distribution process or improving a production process.

Considering what has been studied in the literature, the study will focus on these two types of objectives, and then go on to investigate whether companies that want to achieve a certain type of objective towards which category of partners are more likely to open up, because if it is true that the literature has now found that these two are the main categories of objectives that companies want to try to achieve there are no comprehensive studies that link these two objectives to all types of partners.

4.3. Size

I decided to go and investigate not only whether these objectives could guide the company towards opening up to partners, but the next step was to ask what other important determinants could play a key role.

The most interesting variable that might be able to influence this relationship is probably the size of the companies, considering that this is another factor specific to the company that has been studied by different authors but with results that are still controversial.

On one hand, in fact, it is stated that the opening is mainly driven by large companies. This is due to the greater availability of resources that large companies have compared to small and medium enterprises (SMEs). In addition, larger firms have a more systematic approach of processes that allows them a better use of resources (De Backer et al., 2008; Drechsler and Natter, 2012).

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On the other hand, other contributions point out that especially small businesses, which often do not have the resources and skills to innovate on their own, would benefit greatly from the exploitation of the open innovation model. This is why, despite a more limited availability of resources, today are increasingly small and medium enterprises that are using the practices of open innovation (van de Vrande et al., 2009; Spithoven et al., 2013), although the more limited availability of resources certainly exposes them to the risk of losing their innovations, having less willingness to invest in tools to protect ideas.

In the end, there were other authors such as Schroll and Mild, 2011, who found no correlation between size and openness.

This is why, given what has been suggested in the literature, even in this case it seems that there is no obvious correlation in what is the relationship between the company size and openness. It therefore seems interesting to investigate the relationship between the size of the company and the openness to partners, and try to verify whether the increase in the size of the company can be seen in an increase in openness to partners.

4.4. Openness to Partners and Opening Performance

The next phase of our study aims at investigating which are the subjects towards which the company should value the opening, as they will be those who will carry out that process of sharing their technical and human skills for the achievement of business objectives.

In that case, it will be analyzed:

• The way the opening process takes place.

• What are the subjects towards which companies should open up.

Also in this case the literature is full of useful references. The most common way to study the degree of openness is proposed by Laursen and Salter (2006), in which the concept is defined by:

26 • Depth.

The two parameters allowed the study to identify the number of optimal sources to be used in the opening process and the intensity of collaboration with each source. It is not obvious that all sources should bring the same degree of technical and human knowledge into the partnership process. Laursen and Salter (2006) also provide a list of the main partners, taken as a reference in almost all of the subsequent studies:

• University. • Research centres. • Customers. • Suppliers. • Competitors.

• Companies operating in other sectors.

Other authors, such as Lazzarotti et al. (2011), have identified different types of collaborators depending on the number of phases and types of partners with which the companies can collaborate, taking inspiration from what was studied by Laursen and Salter, 2006. Other studies have instead considered reducing the types of partners into two or more categories based on the distinctive characteristics of the partners (Du et al., 2014; Bengtsson et al., 2015). In particular, there are two categories that are mostly taken as reference:

• One with a more academic and scientific extraction. • One with a market or business extraction.

In the first we can find subjects such as: • University.

• Research centres.

• Innovation intermediaries.

The second instead presents subjects with extraction closer to the market value chain as: • Customers.

• Competitors. • Suppliers.

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Clearly, categorisation has the disadvantage of causing a loss of detail, but this simplifies the analysis allowing us to focus on the main distinguishing features (Thompson, 2004).

Despite the empirical evidence on the types of partners suitable for the degree of openness, this remains a very interesting construct to be investigated (Schroll and Mild, 2012; Greco et al., 2015). We can therefore argue that there are many possibilities and many possible combinations, all theoretically acceptable and supported but to be verified with empirical checks. The key step to verify is that this relationship is closely linked to a collaborative behavior between a focal company and different types of partners in order to achieve the objectives of the relationship.

After Laursen and Salter (2006) there have been other studies on the subject all converging on the fact that the degree of openness reflected how deeply intense a company activates an external relationship to share knowledge and support innovation (Drechesler and Natter, 2012; Garcia et al., 2014). The depth of collaboration with external partners is limited to two types of partners (Du et al., 2014; Bengtsson et al., 2015): the intensity of collaboration with scientific partners (universities, research centres, etc.) and with business partners (suppliers, customers, etc.). The literature has outlined the need to study these two types of partners separately because of their differences.

While the commercial partners share the cultural values, competences and market objectives of the enterprises, the scientific partners seem to show different characteristics, so that the relationship with this type of partner seems to be more complex, as it depends on the objectives (Pertuzè et al., 2010). The main differences in this field concern cultural differences, the way in which research is carried out, and mainly the remuneration aspect of research. Typically, literature has pointed out that researchers in universities are slower in carrying out their activities than researchers in the R&D functions of private companies. This is also an area where private companies have difficulty in influencing, as research subjects generally enjoy greater autonomy and freedom.

On the other hand, however, it should be pointed out that this approach to research allows more space for improvisation, allowing and facilitating the channelling and development of ideas (Aghion et al., 2008). In a scientific environment often the reputation of researchers is considered by these subjects as more important than the monetary benefits, so researchers are less concerned about the industrial spin-offs, work more freely on the development of ideas and this often favors the best creative processes.

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By contrast, although business partners are often more similar to companies in terms of the characteristics mentioned, they are often characterised by a specific set of technical skills and more developed resources than their business partners (Croom, 2001).

Commercial partners often have different characteristics from those of a scientific nature, the skills in general can be very specific and sectoral, this could certainly promote efficiency in the individual research process but sometimes you may feel the lack of a more extensive portfolio of skills. Another limit that seems to be suggested by the literature is related to the efficiency that is required to business partners. The need to conclude several research projects on time for business efficiency reasons, given the numerous projects with different partners, could affect the effectiveness of the partnership itself.

The literature therefore seems to confirm what was suggested at the preliminary stage by the ideas underlying this study. Although there are many references to the types of partners towards which companies can open up, and given the considerable differences, it seems that the two subjects of greatest interest continue to be partners of a scientific nature and partners of a commercial nature. These will therefore be the partners involved in the research study.

As regards the performance that can be achieved through openness to partners, there is still no consensus on the effects of openness on the innovation performance of enterprises. In fact, several advantages can be obtained through openness that positively affect the innovation performance of companies, also in this case as in the argument of the factors of openness we mention the main benefits obtainable as sublitled by Drechsler and Natter (2012) and Tidd (2014):

• Access to new skills and know-how. • Sharing costs.

• Sharing the risks of innovation. • Reduction of time to market. • Increased creativity.

• Expansion of the product range. • Capturing market opportunities. • Monitoring of technological changes.

However, there are also several potential disadvantages that could be caused by openness that could negatively affect innovation performance. In the followings we report the main risks as

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underlined by the studies of Trott and Hartmann (2009), Praest Knudsen and Bøtker Mortensen (2011) and Rafols et al. (2014):

• Uncontrolled falls and loss of control over internal know-how. • "Not invented here" effect.

• Increased organisational management complexity. • Increased operating costs.

• General increase in time and costs.

Despite the presence of potential advantages and risks, several empirical studies have already shown that the positive effects overcome the negative ones, revealing a positive relationship between openness and performance (e.g. Bengtsson et al., 2015). In addition, the models of open innovation that can be adopted by companies are different, each corresponding to a different degree and mode of openness.

This is why the assumption of different ways of relating openness and performance seem to justify the study we are about to carry out in which we want to investigate how openness to partners of a scientific or commercial nature favours the achievement of certain objectives. It is possible to deepen this survey by studying contexts characterized by different levels of openness: depending on the objectives that drive companies to collaborate, the scope and depth of the partnership will be different, for each company may vary the number of external sources with which companies collaborate in innovation activities. However, what all companies have in common at this stage of the study will be the achievement of the objectives of the collaboration.

The nature of my study is further driven by the fact that i want to investigate whether opening up to different subjects can more easily lead to the achievement of different performances. Although we have understood that the literature has established that there is no unanimous relationship between openness and performance, it is clear that the results that can be obtained could fall under different categories. It seems natural, as in the case of openness, to be able to think that some performances may concern mainly commercial or market aspects, such as increasing sales or entering new markets, while others objectives may concern process performance, such as extending their knowledge, making process innovation, improving a service, improving a distribution process or improving a production process. It is quite logical that the performance i’m going to study is in line with the objectives that have conditioned the

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opening and the partners chosen. It would make no sense to have investigated as objectives underlying the opening to partners market and process objectives and then go to check the achievement of different performance from these. It seems therefore interesting to consider separately these two performance aspects, both important but different from each other, in order to investigate how much the openness towards a certain category of partners has facilitated the achievement of commercial or business objectives with respect to process innovation objectives.

4.5. The Role of ICT Tools

As i said, open innovation is defined as the targeted use of inflows and outflows of knowledge by companies in order to accelerate internal innovation (Chesbrough et al., 2006). Therefore, open innovation is based on the combination of internal and external knowledge of companies in order to create successful innovation to create value. With these assumptions, the implementation of open innovation requires the use of systems to manage the diffusion, sharing and transfer of knowledge within the company and with the external environment (Chiaroni et al., 2010; Santoro et al., 2017). More importantly, for this purpose, companies could use their IT skills to establish knowledge management systems, to connect with external actors and then effectively use internal and external knowledge.

However, ICT tools can offer opportunities to improve the performance of open innovation. In this context, there’s to understand how useful ICT tools are in the relationship between openness and performance. I can assume that the effectiveness of ICT tools is proportional to their ability to achieve the objectives described in the literature (Chiaroni et al., 2010 and Santoro et al., 2017), to acquire, assimilate, transform and exploit resources and know-how in the relationship with partners.

Based on the above, one of the objectives of our study is to examine the ability of ICT tools to play a role in the relationship between openness and performance, supporting that they play a significant role on the performance of open innovation by supporting the relationship with partners.

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ICT tools allow to move and configure resources related to information technology, their fundamental role will therefore be the management of data and their processing with the aim of creating information that can be used to support processes. The objective of this preliminary analysis of ICT tools is to identify those tools that could most play a role in support of the main process between openness to partners and performance. One idea could be to make a difference between ICT tools that play different roles; i could consider tools that are able to support activities inside the organizational boundaries to help companies build reliable products and services and minimize overhead costs, or tools that can support resources and capabilities in activities with other companies or individuals outside the organization. Since research aims at investigating how much ICT tools are able to influence the relationship between the company and its partners (external subjects), it seems more logical in this context to investigate external tools.

As previously analysed, internal knowledge resources are often limited, so companies increasingly tend to look for external sources of knowledge to conduct open innovation (Chesbrough et al., 2006). On the basis of what analysed, it’s possible to argue that external IT capacity plays a very important role in the performance of open innovation. First of all, such ICT tools allow companies to get information from such external actors, reducing communication costs, but also increasing communication distances. As a result, companies with high external IT tools can contact more external actors such as customers (current or potential), suppliers, universities and even competitors and seek from them a diversity of knowledge that contributes to companies' performance in open innovation. On the other hand, in the open innovation process when companies contact partners in search of more external knowledge, their relationships require communication and considerable coordination to be maintained. In particular, companies need to communicate with partners to organise and coordinate their operations, address any problems that may arise during the communication process and make the necessary changes to ensure that the objectives are achieved (Lioukas et al., 2016). In this context, ICT tools can help companies to seek more knowledge from partners in a timely way or to reduce the time taken to process knowledge, thereby improving the performance of open innovation. Second, ICT tools can promote social interaction between companies and partners to deeply look for external knowledge in the open innovation process. On one hand, social interaction plays an important role in shaping a common set of objectives and values between different organisations. These will promote more knowledge or opportunities for free exchange of information between different companies, including tacit knowledge, improving the

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performance of open innovation (Lin and Wu, 2010; Roldán Bravo et al., 2017). On the other hand, with a greater social interaction with the partners, their relationship of trust will become more concrete and the actors will have more chances to perceive each other as reliable (Tsai and Ghoshal, 1998). When partners trust each other, they will be more willing to exchange their knowledge and ideas, without worrying about being exploited by other parties (Tsai and Ghoshal, 1998).

Therefore, one of the advantages of ICT tools lies in the depth of research, which is positive for the performance of open innovation.

It is clear that there are not only advantages as a proper use of ICT tools requires a significant initial financial payment justified not only by the purchase of all hardware but also by the training process that needs to be done on staff and all stakeholders. Often the introduction of such systems does not simply become a software installation project but an introduction project that could involve entire departments or even the entire company. Clearly the greatest impact will be seen towards those companies that introduce for the first time ICT tools in their business context because the investments in this case would be very large as well as the time of introduction and implementation. The costs to be considered would not only concern the installation butalso the phases of operation and maintenance. Often, for large projects, the help and support of external consultants may be necessary, which could lead to the loss of technological control, with the risk of becoming dependent on these subjects over time. Another aspect to consider in such a context is the rigidity that is transmitted to processes through the use of such ICT systems. Processes become standardised on the basis of what is contained in the programmes and this can lead to greater rigidity of use on the part of the subjects involved. In this context, one of the most important roles played by ICT tools is absorptive capacity, as this allows to acquire, assimilate, transform and exploit the knowledge that is transmitted in the partnership relationship. This capacity can allow the company to configure its resource base and adapt to changing environmental conditions to obtain a competitive advantage. However, the absorption capacity must be diversified into a potential absorption capacity and realised absorption capacity. The first includes the potenzial acquisition of knowledge and assimilation of information, while the second includes the transformation and exploitation of knowledge (Zahra and George, 2002). The difference in absorption capacity generated by different ICT tools becomes fundamental as this emphasizes the process through which a company acquires and assimilates external knowledge (Zahra and George, 2002).

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We can in fact distinguish ICT tools on the basis of their ability to optimize the capacity of potential absorption or realized, distinguishing them on the basis of their potential to acquire knowledge and information different from external partners. In particular, i will look for systems that allow to emphasize the advantages analyzed and minimize the risks and benefits of ICT tools, because this context of study concerns the use of tools to support only the process of open innovation and not the introduction of management systems such as ERP systems that instead have much more important impacts and payments.

Product ICT Management System systems can promote product development information related to innovation and production. These seem to be tools able to maximize the realized absorption capacity as they are very specific and sectoral allowing companies to have information already filtered and ready for a specific purpose.

Other external resources related to IT aspects such as online communities, blogs or discussion forms can increase the potential opportunity to acquire additional external knowledge and reduce the costs of the knowledge acquisition process (West and Bogers, 2014). These, on the contrary, seem to be the right tools to maximize the potential absorption capacity as they allow the acquisition of a large amount of information which, however, will have to be filtered before it can be used.

More importantly, ICT tools with partners can increase shared understanding between companies, allowing them to be more efficient and will help them to communicate effectively and coordinate with others to gain additional external knowledge (Gòmez et al., 2017).

In addition, ICT tools help companies to acquire the amount of external knowledge available from valuable partners, and to assimilate that knowledge. These can help companies increase the redundancy and diversity of their knowledge base. In this way, the diversity of business knowledge can increase the prospect that new external knowledge will combine with existing knowledge, allowing the acquisition and assimilation of new additional knowledge (Jansen et al., 2005).

The potential and realised absorption capacities are very different from each other, also playing a different role within the enterprises. Potential absorption capacity plays mainly a role in knowledge acquisition and exploration. Instead, the absorption capacity generated by ICT tools can allow to exploit the knowledge acquired (Lichtenthaler, 2009). When businesses acquire more external knowledge, the absorption capacity generated by ICT tools could make it possible

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to transform and exploit external knowledge more effectively, as businesses are only able to transform and exploit external knowledge once they have acquired and assimilated the most relevant ones. In this way, companies rely on knowledge acquisition and use their capacity to transform and exploit this knowledge. Existing research already seems to underline that there is an important relationship between the absorption capacity generated by ICT tools and the increase in performance generated by the opening process, as companies cannot exploit knowledge without first acquiring and absorbing it (Zahra and George, 2002).

After studying the literature, it seems interesting to investigate how the use of external ICT tools characterized by a different nature can contribute to moderate the relationship between openness and performance. The two most interesting categories of tools seem to be, in fact, on the one hand those tools of a strictly social nature, such as blogs, forms or social platforms, which allow to maximize the transmission of information from external subjects in order to increase the development of new ideas, on the other hand we could investigate instead a much more specific category of tools of Product ICT Management System to support product development information during the life cycle of the product, which seem to be the tools most able to allow the transformation of data into knowledge.

In the light of what has been analysed in the literature, it seems that the ICT tools identified can play a role of moderation between openness and performance. This will therefore be the objective of the investigation of the empirical research of this study

4.6. Summary of the Gaps and Research Questions

From the analysis of the literature i have been able to verify how the process of open innovation can follow different dynamics and develop in different ways depending on the circumstances and the context of reference.

As we anticipated in the definition phase of the research objectives, the following study is intended to be a preliminary analysis of the entire framework of reference that will take place in the coming months. In particular, to give a logical meaning to this study i investigated the relationship between the elements and the main actors that carry out the process of open innovation in the processes of development of new products, studying the internal determinants

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of openness, the openness and performance. To these i have added one of the aspects that we found most missing in the literature, that is the ability of ICT tools to play a role of moderation in the relationship between openness and performance.

I started by determining the categories of objectives also considered by literature as the most significant that represented in my model of reference the internal determinants underlying the relationship of open innovation. After analysis, i came to the conclusion that i wanted to investigate two different categories of objectives:

• Business or market targets.

• Product or process performance targets.

I have added an additional analysis, trying to understand if the size of the companies could also be a determining factor in the process of openness.

I have analyzed the main partners already recognized in many literature studies, which I have grouped into two categories so as to represent the differences with their advantages and disadvantages:

• Business or commercial partners. • Scientific research partners.

About the performance analyzed, these were the natural consequence of the objectives underlying the openness. After analyzing what were the potential benefits and limitations that had already been examined in the literature about the performance of open innovation, i took two categories of performance that were the nature of the targets set:

• Achievement of business or market targets.

• Achievement of process or product innovation targets.

The last step was to try to investigate if ICT tools could play a role of moderation in the in the relationship betweenopen innovation and performance. Specifically, I identified two specific categories of such tools that presented different aspects. Once the potential advantages and risks in the use of ICT tools were exposed, i identified two tools that could imfluence the potential absorptive capacity and one the realized absorption capacity.

36 I then identified:

• Product ICT management systems.

• Social ICT systems (discussion social ICT).

On the basis of what has been studied in the literature and of the existing gaps, i want to ask the following questions to which i want to try to answer with the support of a survey among Italian manufacturing companies:

• RQ 1: Are companies that want to achieve business and market targets and companies that want to achieve product performance targets more likely to open up to commercial partners or scientific research partners?

• RQ 2: Are companies that have opened up to commercial partners or scientific research partners able to achieve more business and market targets or process and product innovation targets?

To these two questions that represent the main research, the literature has allowed me to highlight two other hypotheses that I will try to investigate through the use of data generated by the survey:

• Hp 1: The size is positively related to openness to commercial partners or scientific research partners.

• Hp 2: The tools of discussion social ICT or product ICT management systems moderate the relationship between the openness of companies to partners and the performance achieved.

37 Moderation Effect INTERNAL DETERMINATS RQ 1 OPENNESS PERFORMANCE OPENESS

Figure 2: empirical investigation framework Business or Market Targets Product or Process Performance Targets Scientific Research Partners Business or Commercial Business or Market Targets Process or Product Innovation Targets Discussion Social ICT Product ICT Management Systems RQ 1 Size HP 1 RQ 2 HP 2

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5. Investigation Methodology

5.1. Sample and Data Collection

I developed a survey based on a study by the research team called OIS 2.0 (Open Innovation Survey), following the innovation survey already developed in 2012 in four countries (Finlandia, Italy, Sweden and the United Kingdom). The objective of the OIS was to collect data in the manufacturing sector regarding the choices of open innovation, the drivers of these choices and the resulting performance. In particular, the OIS 2.0 was conceived as a second step of longitudinal research developed during 2018 with a delay of six years compared to the previous survey.

The OIS 2.0 study was based on a consortium composed of Austria, Brazil, Denmark, France, Germany, Italy, Spain, Sweden and Ukraine.

About the sampling method, the survey was based on three aspects: • Target population of the sample.

• Sample drawing. • Sample size.

NACE Rev. 2 codes were used for the selection of the target population of the sample and therefore for the selection of the enterprises to be included in the sample. Moreover, given the objective of a survey based on a well-developed set of knowledge, the survey was carried out by focusing the analysis on manufacturing industry (although open innovation also takes place in other sectors), which is recognised as a well-established field of open innovation. The following NACE Rev. 2 codes were therefore used:

• 10-17. • 1811. • 1812. • 1813.