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Open innovation

A systematic literature review on the outcomes of open innovation

with different stakeholders

Faculty of Economics and Business

Amsterdam, June 29, 2015

Student: Jens Jansma Student number: 10248269

Bachelor’s Thesis Business Administration Supervisor: Dr. Carsten Gelhard

Academic year: 2014-2015 Semester 2, Block 3

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Statement of Originality

This document is written by Jens Jansma who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

This Bachelor’s thesis addresses the following research question: ‘How do the outcomes of open innovation with different stakeholders in various industries relate to each other?’ On the basis of a systematic literature review, an answer to this question is provided. The answer to this research question is not captured in a few sentences. Each type of stakeholder that the firm collaborates with, offers different contributions. The most important finding is that in selecting a specific type of value co-creation, managers should be aware of the characteristics of their industry, their firm, potential collaboration partners, and the

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Table of Contents

Statement of Originality ... 2

Abstract ... 3

1. Introduction ... 6

2. ‘Open innovation’ vs. ‘value co-creation’ ... 9

2.1 Open innovation ... 9 2.2 Value co-creation ... 10 2.3 Conclusion ... 11 3. Methodology... 12 3.1 Overall design ... 12 3.2 Protocol ... 12 3.2.1 Search terms ... 12 3.2.2 Databases ... 14

3.2.3 Filters and evaluation... 15

3.3 Synthesis ... 15

4. Results ... 17

4.1 Outcomes of customer co-creation... 21

4.2 Outcomes of lead user innovation... 26

4.3 Outcomes of community-based innovation ... 26

4.4 Outcomes of open innovation with partner firms ... 28

4.5 Outcomes of open innovation with suppliers ... 30

4.6 Outcomes of open innovation with competitors ... 31

4.7 Outcomes of nonprofit-profit collaboration ... 32

4.8 Outcomes of government-industry collaboration ... 32

4.9 Outcomes of Research institution-industry collaboration ... 33

4.10 Outcomes of collaboration networks ... 33

Manufacturing ... 34

5. Discussion ... 36

Similarities, complementarities, contradictions, and reoccurring themes ... 36

Similarities and complementarities ... 36

Differences and contradictions ... 37

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Contributions and implications ... 40

Limitations and suggestions for future research ... 40

6. Conclusion ... 42

References ... 43

Appendix ... 56

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1. Introduction

Traditionally, companies with an internal research and development (R&D) department were the main, or even sole, innovators. As market leaders they earned the majority of the profits in their specific markets. Industries consisting of a few large companies with internal R&D required potential entrants to make a considerable investment in order to be able to compete with the incumbent companies. Nowadays, however, internal R&D does not necessarily provide a firm with a competitive advantage. Cisco Systems, for example, managed to

successfully compete with, and occasionally outperform, Lucent Technologies that owned one of the most outstanding research organizations. Cisco achieved this success by acquiring technologies from sources outside their own company. Through partnerships and the

financing of startup companies, Cisco managed to compete with Lucent without investing the tremendous amount of resources in internal R&D (Chesbrough, 2003, pp. 35-36). Nowadays, many companies have found that innovating through highly controlled internal R&D is outdated. Therefore, companies now engage in innovation from a more external perspective, such as Cisco did. This shift can be described as one from ‘closed’ to ‘open innovation’. Open innovation provides a new manner to create promising innovations and enables firms to capture the value generated by those innovations in new ways. This, however, does not change the fact that firms still face the task of serving the needs of the customers with their innovations. Therefore, innovating firms should widen their scope to include knowledge, ideas and skills from ‘outsiders’ (Chesbrough, 2003, p. 41).

The view on the way in which a firm should create value for its customers has changed over the past few decades as well. Traditionally, companies would create value for their customers autonomously. Customers, however, nowadays have access to an almost unlimited amount of information on firms, products and prices from all over the world. In addition, consumers are becoming more active as they, for example, set up independent communities in which ideas are shared. Firms can hardly deny their consumers and as a result interaction between firms and their consumers is growing. The new way of creating value is by co-creating it and making the interaction a pleasant experience for the consumer (Prahalad and Ramaswamy, 2004, pp. 4-6). Vargo and Lusch contribute to these findings by arguing that in business models less emphasis is placed on tangibles and more on intangibles (2004, pp. 14-15). The authors state that there is no such thing as a pure goods-centered market anymore. Rather, there is a service side to each tangible product offered. This is their service-centered

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7 view that ‘implies that the goal is to customize offerings, to recognize that the consumer is always a co-producer, and to strive to maximize consumer involvement in the customization to better fit his or her needs’ (Vargo and Lusch, 2004, p. 12).

Value co-creation through interaction with customers basically is a form of open innovation. There are, thus, multiple possible stakeholders in open innovation. In the case of Cisco the stakeholders are partner companies or startup companies in which Cisco invested. Consumers can be a source of input in open innovation for firms as well. Other stakeholders with whom firms can choose to co-innovate or co-create value are communities, suppliers, governments, NGOs and NPOs, research institutions and universities, or even competitors (Chesbrough, 2003, p. 38-40); Lee, Olson and Trimi, 2012, p. 818; Pisano and Verganti, 2008. p. 80).

As open innovation and value co-creation are now frequently used strategies for companies and are still evolving, research in this area has also developed significantly. Researchers have addressed many topics within the area of open innovation including one or more of the different stakeholders. For value co-creation with customers, studies have focused on, for example, the relationship between customer interaction and purchase intentions (See-To & Ho, 2014), the behavior of customers in the process of value co-creation (Yi and Gong, 2013), but also on the provision of frameworks that can help managers understand and implement co-creation (Payne, Storbacka and Frow, 2008). Research on value co-creation with suppliers shows, for example, that building relationships with suppliers positively influences a firm’s lean strategy which in turn influences economic performance (Jayaram, Vickery and Droge, 2008).

It is clear that many issues have been addressed in the extant literature already.

However, there seems to be a lack of overview on the different outcomes that open innovation with the various stakeholders results in. Providing such an overview of the research up to now and a comparison of the outcomes of open innovation with the various stakeholders through different processes and in different industries could be an important contribution to theory. In addition, it would help managers that need their companies to reach certain goals to know what they can expect when engaging in co-creation practices with one or more of their

stakeholders. Therefore, the following research question will be addressed in this paper: ‘How do the outcomes of open innovation with different stakeholders in various industries relate to each other?’.

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The remainder of this paper will be written in a specific structure that enables this research to provide an answer to the research question as complete as possible. The answer will be given in the form a conceptual model and a narrative that provide an overview as well as a

comparison of the different findings in the area of open innovation that can help managers make decisions on their open innovation approach and provide them with a direction for the implementation of these strategies. First of all, some of the most prominent literature on open innovation and value co-creation will be reviewed to provide a definition and a better

understanding of the research topic. Second, the methodology that will be used in order to answer the research question will be explained. Third the main findings will be addressed in the ‘results’ section and this will result in the proposition of a conceptual model. After

presenting this model, there will be a discussion of the results, as well as the limitations of the research. Also, directions for future research will be provided. Finally, the complete research will be summarized in the ‘conclusion’ section.

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2. ‘Open innovation’ vs. ‘value co-creation’

In the introduction the terms ‘open innovation’ and ‘value co-creation’ were used

interchangeably, although value co-creation does seem to be used more often in the context of customers and open innovation in the context of cooperation with other firms. A comparison of the definitions of both terms might help to determine whether they can be used

interchangeably or should both be used in different contexts.

2.1 Open innovation

When searching scientific articles for definitions of open innovation, it immediately becomes clear that there is a lot of consensus considering its interpretation. Most articles refer to the definition given by Henry Chesbrough, who is referred to as ‘the father of open innovation’ (Chesbrough, 2012, p. 20). However, there are a few authors that have introduced their own definitions. Table 1 shows some of the generally accepted definitions. What stands out is that all definitions are very much in line with each other. It is evident that open innovation is a matter of collaboration between both sources within and outside of a firm’s boundaries. One difference between the definitions is represented by the way that resources are explained. West and Gallagher (2006) argue that there is a wide range of resources that can entail interesting opportunities for innovation, whereas Chesbrough (2006) and Lichtentaler (2011) highlight knowledge as the primary source for advancing innovation.

Table 1: A selection of definitions of open innovation

Author(s) Definition

Chesbrough (2006, p. 2)

‘’Open innovation is the use of purposive inflows and outflow of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively.’’

West and Gallagher (2006, p. 320)

‘’We define open innovation as systematically encouraging and 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’’ Lichtenthaler

(2011, p. 77)

‘’Open innovation is defined as systematically performing knowledge exploration, retention, and exploitation inside and outside an organization’s boundaries throughout the innovation process’’ Sloane

(2011, p. 3)

‘’Open innovation replaces the vertical integration of innovation processes within one company with a network of collaborators working on innovation projects.’’

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The authors agree again upon the way that the advanced innovation should be exploited: broadly.

Finally, neither of the definitions explicitly mention which external sources and which external parties are involved. This could be reason to include value co-creation as one factor under the umbrella of open innovation. Support for this statement is given by research on communities in open innovation. West and Lakhani argue that ‘community-based innovation by its nature takes place outside the boundaries of the firm, which fits Chesbrough’s definition of open innovation’ (2008, p. 223). They have raised this argument to point out that most research on open innovation has focused on inter-firm cooperation and sharing resources within a specific industry. Other actors than firms, on the contrary, are hardly mentioned in the literature (West and Lakhani, 2008, p. 223). This last finding is remarkable, since a lot of research has been done on both customer- and community-firm interaction in the context of value creation. One explanation could be that the authors haven’t looked into the co-creation literature. Another possible explanation could be that value co-co-creation cannot be seen as a form of open innovation or that it is fundamentally different from open innovation. In order to find out, the term ‘co-creation’ will be examined next.

2.2 Value co-creation

Value co-creation is a term that seems quite self-explanatory at first sight. It is, however, not easy to find a proper definition of the term in the academic literature. Grönroos and Voima have addressed the issue of ‘making sense of value creation and co-creation’ (2012, p. 133). The authors state that the current literature on value creation and co-creation does not comprise of a clear definition of value. The common view on value creation, which is never literally written down, is of ‘an all-encompassing process, including activities by service providers, customer, and possibly also other actors, which lead to the conclusion that everything is value creation and everyone co-creates value’ (Grönroos and Voima, 2012, p. 144). When looking at value creation in this way, one can conclude that virtually any actor can be a co-creator of value. But the term also loses meaning for analytical use. Hence, Grönroos and Voima introduce another view of value creation in which value creation is ‘the customer’s creation of value-in-use’ and co-creation of value only may take place in a joint value sphere’ (2012, p. 146). Value-in-use is achieved through ‘an interactive relativistic preference experience’ (Holbrook, 1994, p. 27). This definition of value implies that value is

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11 obtained through an interaction in the process of consumption by the user that depends on personal attitudes, affections, and judgements (Echeverri and Skålen, 2011, p. 353). In other words, value is created by the user in the process of usage of resources and processes. Usage can take many forms: mental, physical, virtual or even the sole event of possessing something. Therefore, not the firm, but the customer is the value creator and only if the firm interacts with the customer in the process of creating value, the customer is co-creating value with the firm.

The two described perspectives on value creation and co-creation differ substantially. In this research, however, the essence is the outcome of the interaction between the firm and the stakeholder (in this case customer). Whether the firm and not the customer is the creator of value or the vice-versa is irrelevant, as for both perspectives goes that value is co-created through the interaction between them.

2.3 Conclusion

After having assessed the terms ‘open innovation’ and ‘value co-creation’, we can draw a conclusion on how co-creation relates to open innovation. Co-creation most often discusses the interaction between a firm and its customers, whereas open innovation focuses more on inter-firm interactions. However, co-creation literature does also include interactions between firms and other stakeholders and the same goes for open innovation and consumers.

According to Enkel, Gassmann and Chesbrough co-creation is a topic that is researched extensively in the open innovation management literature (2009, p. 313). Open innovation is strongly focused on peer production through communities, consumer, lead users, universities and research organizations, and partners from other industries (Enkel, et al., 2009, p. 313). This is another reason to approach value co-creation as open innovation. Although innovation is often associated with new product development (NPD) and co-creation often times also is aimed at NPD, this is not always the case. Co-creation can occur in creating new products as well as in co-design of through interaction with customer services. Baregheh, Rowley and Sambrook studied the extant literature on innovation to propose the following integrative definition: ‘innovation is the multi-stage process whereby organizations transform ideas into new/improved products, service or processes, in order to advance, compete and differentiate themselves successfully in their marketplace’ (2009, p. 1334). Since both open innovation and value co-creation strive to reach the same kind of achievements, the terms will be used

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3. Methodology

This section will explain the methods used for answering the research question: ‘How do the outcomes of open innovation with different stakeholders in various industries relate to each other?’. These methods will be explained explicitly in order to provide transparency.

Following a predetermined set of stages will reduce bias and ensure the completeness of the methodology. This enables other researchers to replicate the study, which improves the external validity (Adolphus, 2012; Zhang and Shaw, 2012, p. 9). The following sections will describe the overall research design, the protocol and the synthesis.

3.1 Overall design

The overall design of the research will be a systematic literature review. According to Manning Fiegen, a systematic literature review provides a structured manner to summarize and criticize the literature (2010, p. 386). This research design is particularly well-suited to provide an overview of the research on open innovation and to constructively assess how the outcomes relate to each other.

3.2 Protocol

The research protocol identifies the main steps in conducting the systematic literature review. First, the search terms will be defined. Second, the databases will be identified. Third, the criteria for filtering the results will be determined. Finally, in order to ensure that the filtering has resulted in representative articles, the process can be repeated (Adolphus, 2012).

3.2.1 Search terms

The search terms will consist of a number of keywords that will be used to search through the databases. The key words to start with are ‘open innovation’ and ‘value co-creation’.

Literature on these subjects reveal a number of other key words that are likely to yield results that will help to answer the research question. Table 2 provides an overview of these key words that relate to open innovation and co-creation. Table 3 provides an overview of the key words that are associated with the different stakeholders. Each of the key words in table 2 will be combined with the keywords of the different stakeholders, through so-called ‘Boolean’ search. In addition, some firm-stakeholder interactions require search terms that are specific for that particular stakeholder. Those search terms will be mentioned separately in table 3. In

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13 addition, during the process of reviewing the relevant articles, new key words might come to light. These key words will be added to the relevant tables and will be used to find more relevant articles. Furthermore, in order to find articles that are of interest for this study, those that indicate some outcomes of co-creation processes, words like ‘performance’, ‘outcomes’, ‘results’, etcetera, can be used either pre- or post-searching.

Table 2: Open innovation related key words

Table 3: Stakeholder related key words

Stakeholders Related key words Specific key terms

Customers  Consumers

 Users  Lead users

Communities  Virtual communities

 Brand community

 Community based

Partner firms  Organizations

 Companies  Firms  Suppliers  Competitors  Corporations  Businesses  Inter-firm  Inter-industry  Cross-firm  Cross-industry  Co-opetition  Cross-sector Main key words Related key words Related key words

Open innovation  Co-innovation

 Innovation

 Cooperation

 Co-production

 Partnership

 Joint innovation

 New product development

 Collaboration

 Customization

 Research and development

Value co-creation  Co-design

 Integration  Participation

 Boundary spanning

 Joint value creation  Interaction

 Engagement

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 Enterprises  Private sector NGOs/NPOs  Corporate-NGO Universities and Research Organizations  Academic  Educational  Institutional  University-industry  Cross-sector collaboration

Government  Public sector  Business-government interaction

 Public-private interaction  Cross-sector collaboration

3.2.2 Databases

EBSCOhost will be used as the access point to the literature that will be reviewed. EBSCOhost is one of the most commonly used platforms that provides access to a large number of research databases (https://www.ebscohost.com/). These databases offer access to a range of high quality journals. In addition, the library of the University of Amsterdam

provides access to EBSCOhost for all its students and employees. This makes this search engine a convenient and low cost option, increasing the feasibility of this research. The following relevant databases will be used:

- Business Source Premier: This business research database is the most frequently consulted one in its industry. It provides full text for over 1100 peer-reviewed

journals. According to EBSCOhost, this database is better than any other in the entire field of business (‘EBSCO databases’, n.d.).

- EconLit: This is the database of the American Economic Association, providing more than a million sources on all economic topics (‘EBSCO databases’, n.d.).

- Academic Search Premier: A database providing over 4600 journals, covering multiple disciplines from around 1975 up till now (‘EBSCO databases’, n.d.).

- Academic Search Alumni Edition: Providing full text on 3350 and abstracts for over 8000 journals, this database supplies essential information from many sources

(‘EBSCO databases’, n.d.).

- Business Source Alumni Edition: Provides full text journals and peer-reviewed

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15 management, economics and production and operations management (‘EBSCO

databases’, n.d.).

3.2.3 Filters and evaluation

In order to get a range of relevant academic articles of high quality, a number of filters will be used in the search engine. First of all, some of the earlier mentioned key words will be used to search abstracts only, rather than the full texts. This will ensure that the resulting articles are as relevant as possible for this research. In addition, a filter will be applied to only show articles that are published in high quality journals. The criterion for being selected as a high quality journal is based on the Academic Journal Quality Guide (February 2015 edition) of the Association of Business Schools (ABS). This guide ranks academic journals as indicated in table 4.

Table 4: ABS academic journal quality ranking scale (Harzing, 2015).

Rank Interpretation

4* A world elite journal

4 A top journal

3 A highly regarded journal

2 A well regarded journal

1 A recognized journal

Only peer reviewed academic articles from journals with a rank of 3 or higher will be included in this research. This is done both to ensure the quality of the sources used and to make the research more feasible, as it limits the number of results.

Finally, only articles that are online accessible will be used in the analysis.

3.3 Synthesis

Searching the database on the basis of the identified search terms with the above described filters applied will result in a list of articles. The abstracts of these articles will be examined in order to find outcomes that are relevant for this study. The remaining relevant articles will be reviewed and the results will be presented in a table that indicates:

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- The authors and the year of publication - The ABS journal rank

- The type of study

- The involved stakeholders - Environment and/or theme - The main outcomes

The citations of all relevant articles will be managed through the online research management tool RefWorks. This tool enables storing and saving the citations and will also be used to generate a reference list. In addition, a summary of the review results will be given in a specific table. This will help to reach the objective of synthesizing the results: identifying similarities, contradictions, and possibly other distinguishing features in the reviewed literature (Adolphus, 2012).

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4. Results

In this section the results of the reviewed literature will be presented. Searching according to the guidelines described in the methodology section, resulted in a large range of academic articles from high class journals. These articles were all assessed on their usability for this research, after which a total of 91 articles from 40 different journals remained for further analysis. Table 5 summarizes some statistics of the reviewed articles, table 6 shows a part of the table in which the results are listed. The entire results table can be found in the appendix. Finally, the main outcomes will be presented in a narrative form in order to prepare the results for the discussion section and simplify the process of comparing the outcomes. The results will be presented per stakeholder and distinctions will be made between different industries.

Table 5: Summary of reviewed literature

Variable Total n (%)1 Year of Publication < 2000 2000-2005 2005-2010 2010-2015 1 (1%) 14 (14%) 31 (34%) 46 (51%) Journals

 Journal of Product Innovation

Management

 Journal of the Academy of Marketing

Science

 Journal of Business Research

 Journal of Marketing  Research Policy  R&D Management  Technovation  Other Journals 10 (11%) 7 (8%) 6 (7%) 5 (6%) 4 (4%) 4 (4%) 4 (4%) 51 (56%) Study design

1 Stakeholder and study type percentages count up to more than 100% due to articles that investigate multiple stakeholders and/or use multiple methods.

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Empirical  Experimental  Case study  Netnographic  Survey  Interview

 Quantitative data analysis  Literature review 86 (95%) 13 (14%) 13 (14%) 6 (14%) 34 (37%) 12 (13%) 17 (19%) 5 (5%) Stakeholder Customer Community Firm  Supplier  Competitor  NGO/NPO Research Institution Government 46 (51%) 13 (14%) 34 (37%) 12 (13%) 7 (8%) 5 (5%) 10 (11%) 3 (3%) Environment Services Technological Manufacturing Retail Industrial Multiple Other 19 (21%) 12 (13%) 12 (13%) 9 (10%) 6 (7%) 6 (7%) 27 (29%)

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19 Table 6: Partial results table

Author (year) Journal (ABS Rank)

Type of Study Stakeholder Environment/ Theme Outcome Nishikawa, Schreier and Ogawa, (2013). International Journal of Research in Marketing (4) Empirical Case study Customer Consumer goods Co-design

User-generated products outperform their designer-generated counterparts. The products contain more novelty and score better on the main market performance metrics. Most importantly the sales revenues were higher and product lifetime was longer Schreier, Fuchs, and Dahl, (2012). Journal of Marketing (4*) Empirical Experimental

Community User design Common design by users occurs through the firm’s user

community for creating new product designs for the consumer market. User design increases the customer’s perception of a firm’s innovative abilities. The ‘innovation effect of user design’ positively affects purchase intentions, willingness to pay and the willingness to make recommendations about the firm to others. Familiarity with user innovation (+) and product complexity (-) have a moderating effect.

De Propris, (2002). Entrepreneurship and Regional Development (3) Empirical Survey design Firm Multiple sectors SMEs

Product, process, incremental, and radical innovation all benefit from cooperating with other firms in the innovation process in addition or instead of investing in internal research and

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Marano and Tashman, (2012). International Business Review (3) Conceptual Case study NGO/NPO MNEs NGOs

NGO partnerships can help MNEs to achieve conforming to social legitimacy demands of their stakeholders, as well as shape those demands. Global legitimacy enhancing partnerships could help MNEs to satisfy both local and global stakeholders at the same time. Potoski and Prakash, (2004). Public Administration Review (4)

Conceptual Government Environmental

regulations

Cooperative regulatory enforcement (firms self-police their environmental operations, government provide regulatory relief for voluntarily disclosed violations) yields optimal win-win outcomes. Effective cooperation reduces bureaucratic outputs (inspections, notices of violation, regulatory sanctions) and also reduces pollution.

Kyoung-Joo Lee, (2011).

R&D

Management (3)

Case study Research

institutions

University-Industry

University-industry collaboration enables both parties to perform more explorative research, to organize interdisciplinary research projects and to establish larger R&D projects.

Nieto and Santamaría, (2007). Technovation (3) Empirical Longitudinal sample Firm Customer Research institutions Competitor Network Manufacturing Collaborative networks

Technological collaborative networks are crucial for increasing the novelty in product innovation. Suppliers, clients and research organizations (in this sequence) have a positive influence on the degree of novelty. Collaboration with competitors has a negative impact. The strongest positive influence stems from a

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4.1 Outcomes of customer co-creation Services

Value co-creation practices with customers do not necessarily create value. Flaws in the process actually cause customers to be more dissatisfied than under conditions without co-creation. Co-creation increases the volatility of customer satisfaction quite strongly, causing satisfaction to be higher when outcomes are perceived positively, and lower when outcomes are perceived negatively. This has major implications, as customer satisfaction is narrowly tied to customer retention and the firms profitability (Heidenreich, Wittkowski, Handrich and Falk, 2015). The best way to restore damaged customer satisfaction is by co-creating the recovery solution (Heidenreich et al., 2015). In addition, it is a low-cost strategy for the firm to implement when consumers are faced with a setback, such as delays in service delivery. Moreover, besides restoring satisfaction, co-creating such solutions increase the customer’s satisfaction of the initial service and the recovery, increase repurchase intentions, provide role clarity, increase value perceptions of future creation, and increases the likelihood of co-creating again in the future (Dong, Evans and Zou, 2008; Roggeveen, Tsiros and Grewal, 2012). Not meeting the requests of the consumer in the recovery stage will, again, damage the evaluation. Exceeding these requests, however, does not improve the evaluation compared to just meeting the requests (Roggeveen, et al., 2012).

Chan, Yim and Lam, and Gallan, Jarvis, Brown and Bitner report that higher levels of positivism and participation increase both the perceived quality of the service provider and customer satisfaction with the creation experience (2010; 2013). In addition to this, co-creation capability and participation increase trust and commitment, strengthening the

relationship between the customer and the firm and its employees. This in turn, drives market and financial performance, as it is argued that maintaining customers increases profitability (Chan, et al., 2010; Karpen, Bove, Lukas and Zyphur, 2015; Revilla-Camacho, Vega-Vázquez and Cossío-Silva, 2015). Bolton and Saxena-Lyer confirm and complement these findings, as they find that customer participation directly influences service quality, service usage, repeat purchasing, word-of-mouth, firm efficiency, revenues and profits (2009). Chan et al.,

however, report that value creation through customer participation depends on the cultural values of the employees and customers. A closer match between them, results in the facilitation of value creation (2010).

New service development (NSD) also benefits from customer involvement. In the design and development stages of NSD, it can help a firm to identify market opportunities, to generate and evaluate new service ideas, determine the desired benefits of the potential new

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service, and to be provided with feedback. Customer involvement in NSD indirectly affects the sales performance and process efficiency (Melton and Hartline, 2010). Service innovation is an area that is affected by customer collaboration as well. This positively affects the volume of innovation, however not the radicalness. Customer orientation and knowledge integration do affect radicalness. Collaboration with contact employees, that interact directly with

customers, influences both forms of innovation. Both volume and radicalness directly increase revenue growth, radicalness (directly) and volume (indirectly) also increase profit growth (Ordanini and Parasuraman, 2011). Wagner and Sutter, contribute to these findings, stating that customer integration in innovation projects further intensifies the relationship between customer and firm, and improves performance through enhanced innovation (2012).

Employees are important actors in the process of customer interaction. Customer-employee interaction is often regulated through the use of a service script, that is established to make employees behave according to a set standard in order to increase the likelihood of receiving supportive feedback from the customer and to increase customer retention. Employees with a low customer orientation, however, still perform worse than employees with high customer orientation (Nguyen, Groth, Walsh and Hennig-Thurau, 2014).

Various industries

R&D departments of small- and medium-sized enterprises (SMEs) can increase their influence within the company by increasing customer connection and innovativeness. More influential R&D departments are seen to positively affect the performance of the company, especially for cost-leadership firms (Engelen and Brettel, 2012). Customer connections can be managed by making use of personal media, ‘individualized, important communication tools for communication between persons, including telephone, chat, text messaging and social media through a mobile device’ (Bacile, Ye and Swilley, 2014, p. 118). Through these media, customers can be enabled to co-produce the characteristics of the communication that the firm provides them with. Co-production provides the firm with first-hand customer information, feedback and preferences. This may increase consumer purchase intentions, attitude toward the communication, response rate (i.e. purchases), word-of-mouth (WOM) recommendations, consumer satisfaction, as well as a decrease in the consumer’s perceived risk, and opt-out rate. In addition, the customer gets a clearer image of what the brand means (Bacile, et al., 2014).

Zhang and Chen (2008) contribute to these findings by presenting that customer value creation improves customerization capabilities, that are generated during the process of co-creation with the customer. This capability helps the firm to serve customers according to

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23 their exact wishes and enables targeting specific groups of consumers. In addition, service capability (the ability to offer customized service during co-creation) is positively influenced, which indirectly also improves customerization capability (Zhang and Chen, (2008).

For both services and goods goes that customer satisfaction differs depending on whether the customer participates in production. This is due to the theory of self-serving bias, that recognizes that customers feel that a positive outcome of co-production is due to their own effort, while a negative outcome is ascribed to the firm. Providing customers with the choice of participating or not, reduces the self-serving bias effect when the outcome is below expectations (Bendapudi and Leone, 2003).

Customer can also be involved in advertising. Ad involvement prior to advertising, influences customer attitudes and intentions towards the ads in corporate advertising. The same, but less significant, is found for product advertising. Especially corporate advertising should include advertising involvement, as it can increase purchase intentions, even for ads that don’t involve a focus on a particular product (Kim, Haley and Koo, 2009).

Finally, firms can also stimulate customers to help each other. Product reviews are an important factor in the decision-making process of consumers, when it comes to purchasing. Customer-written reviews, particularly concrete ones, are helpful for potential customers (Li, Huang, Tan and Wei, 2013).

Retailing and consumer goods

Co-design is an effective way of improving sales revenues and extending product lifetime. User-generated products turn out to outperform their designer-generated counterparts, measured on the basis of novelty and market performance (Nishikawa, Schreier and Ogawa, 2013; Sunley, Pinch, Reimer and Macmillen, 2008). In addition, consumers value their self-designed products better, if they enjoyed the process of creating it. Toolkits therefore should evoke affective reactions (Franke and Schreier, 2010). Self-production, being actively involved in the production of an end product, is somewhat alike this. Consumers give higher ratings to products, when the opportunity for self-production is offered. This is a tool for building a stronger bond between consumers and products. This is, however, not relevant to consumers for whom self-production is not part of their goal pursuit (Troye and Supphellen, 2012). Another way to create a stronger demand for a product in which the consumer’s psychological processes play an important role is by empowering them to select the products to be marketed. Customers show a stronger demand for these selected products, even if these are not distinctive in terms of quality. Due to a sense of psychological ownership, this

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‘empowerment-product demand’ effect is created. It is crucial to reflect the customer’s preferences in the empowerment process, as the effect otherwise diminishes (Fuchs, Prandelli and Schreier, (2010).

Particular useful platforms for interaction are represented by social media. Brand performance is likely to increases, as well as retailer performance and the loyalty of the customer to the retailer, (Rapp, Beitelspacher, Grewal and Hughes, 2013). Loyalty and repeat business are also positively enhanced by continuously satisfying the consumer through an online customer experience that is created through consumer interaction with the e-retailer. Accumulated satisfaction will ultimately result in trust, again securing repeat business (Rose, Clark, Samouel and Hair, (2012).

Interaction between customers is another angle from which repeat purchasing intentions and perceptions of quality can be enhanced. Therefore, customer co-production interfaces should be designed into self-service settings (Li, Choi, Rabinovich, and Crawford, (2013).

Technology

Value co-creation strongly influences the firm’s innovativeness (di Tollo, Tanev, Davide, Ma, 2012). Partnerships with customers extend the technological development capabilities of the firm (Angel, 2002). Any stage of the new product development (NPD) process benefits from customer indirection, as it is found to directly affect the technical quality and the speed of innovation, which on their turn affect competitiveness and sales performance (Carbonell, Rodríguez-Escudero and Pujari, 2009). Magnusson findings are somewhat less explicit (2009). Considering NPD/NSD in the mobile telephony industry, the author finds that firms should not expect ordinary users to provide ideas that are directly ready for NPD. They rather inspire the firm with knowledge of their needs (Different from lead user).

Industry

Customer co-design is seen to improve quality and delivery improvements. Virtual and affinity proximity have a positive relationship with co-design, and co-design is a mediator in the relationship between proximity and performance (da Silveira, 2011). Customer integration in the product development process, which is more about gaining access to knowledge,

information, or other resources, does not affect the occurrence of glitches or the performance of handling last-minute engineering changes. Customer integration directly affects market success, most likely due to a sense of ownership (alike psychological ownership in retail) and

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25 satisfaction (Koufteros, Rawski and Rupak, 2010).

According to Hirst and Mann (2004), team R&D activities are aimed at transferring new knowledge into a commercially valuable outcome. It is important to provide the consumers, that are involved in these teams, with communication safety. This factor is the strongest predictor of customer performance ratings. Furthermore, the boundary spanning role should be fulfilled by the project leader (as opposed to sales teams) in order to yield optimal effectivity.

Manufacturing

Zeng, Xie and Tam found a positive influence of cooperation with customers in the innovation process (2010). More specifically, high consumer involvement increases the perceived innovativeness of the firm, which leads to customer excitement and loyalty. The overall corporate image also improves and consumers express a higher level of tolerance for occasional product failure. No evidence for a propensity to pay premiums was found (Henard and Dacin, 2010). In collaborative networks, which are crucial for increasing novelty in product innovation, client collaboration is seen to positively influence the degree of novelty (Nieto and Santamaría, 2007). Customer collaboration also results in enhanced productivity and satisfaction (Allred, Fawcett, Wallin and Magnan, 2011)

Surprisingly, research on R&D collaboration with customers did not significantly alter product and process innovation (Un, Cuervo-Cazurra and Asakawa, 2010; Un and Asakawa, 2015).

In the case of extended product responsibility (ERP), there is a trade-off to be made. Higher customer integration in ERP leads to better market performance, through an

environmentally responsible corporate image and increased opportunities of accessing international markets. Lower customer integration, however, increases the financial benefits of these practices. Implementation should be improved to reduce costs and managers should align their performance goals according to these findings (Lai, Wong and Venus Lun, 2014).

Sales

Boundary spanning is behaving with the intention to gain knowledge from external sources through founding relationships, in order to support a team in reaching their goals. When this is performed by the customer, customer satisfaction increases. However, this requires the

organization to alter its coordination. Therefore, combined firm and customer boundary spanning results in the highest level of performance (Sleep, Bharadwaj and Lam, 2015).

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4.2 Outcomes of lead user innovation

Lead users are distinctive from ordinary users, as they ‘present strong needs that will become general in a marketplace months or years in the future’ (Von Hippel, 1986, p. 791). They can serve for need-forecasting in marketing research and provide new product concepts, as they try to fill their unserved needs (Von Hippel, 1986).

Various industries

Leading companies rely on collaborations with lead users. These collaborations have proven to benefit innovation and increase the chances of product performance. Lead users have the ability to identify new needs ahead of the market, improve novelty of information, leading to higher expected turnover (Lüthje and Herstatt, 2004).

Technology

Active participation of lead users is the key to successful implementation and maintenance of ideas competitions, supporting the development of innovative ideas (Leimeister, Huber, Bretschneider and Krcmar, 2009).

Lead users possess more technological knowledge, which leads to the provision of contributions important to the success of innovative products and services (Magnusson, 2009).

4.3 Outcomes of community-based innovation

Communities can be either customer-initiated or firm-sponsored. Both types of communities are suited for the extraction of value by a firm. Firm-sponsored communities, however, include effort of the sponsor, which is stronger than information that is generated by members. Also, sponsor effort increases the building of trust between customer and firm. Therefore, more value can be captured from a firm-sponsored type of community (Porter, Devaraj and Daewon, (2013).

One way of creating value in communities is through the practice of common design. This is design that occurs through the firm’s user community for new product design for the consumer market. User design increases the perceived innovativeness of the firm. This ‘innovation effect of user design’ positively impact purchase intentions, willingness to pay, willingness to make recommendations to other consumers about the firm. Familiarity with

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27 user innovation positively moderates the effect, whereas product complexity negatively

moderates is (Schreier, Fuchs and Dahl, 2012).

Brand communities are aimed at facilitating customer engagement and creating strong relationships with customers through firm-customer interaction and interaction between customers. This leads to more loyalty, satisfaction, empowerment, emotionally bonded, trusting, and committed customers that also show higher levels of brand identification (Brodie, Ilic, Juric and Hollebeek, 2013; Stokburger-Sauer, 2010). Also, innovation

management and customer relationship management tools are provided by brand communities (Zaglia, 2013). Community marketing is the key to achieve this, especially when

complemented with offline activities (e.g. events), that have a greater impact than online activities (Stokburger-Sauer, 2010). Social networks represent a cost efficient, high speed, and easy in use platform for creating a brand community. Groups are well-suited for customer-to-customer (C2C) information exchange and learning. Fan pages, on the other hand, offer great communicational means and access to a very large audience (Zaglia, 2013).

Some firm-established communities are primarily focused on C2C interaction. These C2C communities are especially well-suited for problem solving, reducing the amount of resources needed by the firm. Furthermore, when toolkits for user innovation are provided, innovation outcomes can potentially be improved (Jeppesen, 2005). Franke, Keinz and Schreier (2008) found that such peer support in communities of web-based toolkits for mass customization benefits inexperienced customers, stimulates the use of existing solutions in problem solving and provide external feedback. This in turn positively affects the design process to better fit to the customer’s preferences. Moreover, purchase intentions and

willingness to pay are increased. Back up for these findings is provided by Wang, Yu and Wei (2012) who found that consumer socialization through peer communication directly affects purchase decisions, through peer conformity, and indirectly through reinforcing product involvement.

Communities also are a promising source of innovation. User innovations can be leveraged by firms through establishing communities. Synergy effects are found in all entrepreneurial phases. During the identification of novel business opportunities, the user innovation system enables ongoing design capacity for the firm. Risk is reduced for both the firm and the lead users during opportunity evaluation and development. During the

exploitation of business opportunities, the overall system creates buzz (Hienerth, Lettl and Keinz, (2014). Lead user cooperation in communities for innovation is particularly beneficial for solving problems and developing new functionalities, on the basis of technical expertise

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(Mahr and Lievens, 2012)

Joint-innovation with online consumers comprises interactions between ‘professional’ community members and less-experienced ones. Sharing opinions, proposing improvements, and asking critical questions will result in a new product superior to one that is produces by a single user. In addition, the overall innovation experience is valuable for the user in itself (Füller, Jawecki and Mühlbacher, 2007). In addition, communities of practice, composed of members that share knowledge, tools, and other resources on a specific professional topic, are particularly well-suited for the innovation phase in which the initial product concepts are formed. Management support, investment in collaboration competence and creating a climate characterized by openness, risk taking, trust, and interaction stimulates innovation (Bertels, Kleinschmidt and Koen, (2011).

A remarkable finding is that supportive customer networks hosted by service firms can result in health benefits for customers, including a sense of perceived cohesion, and improved subjective sense of well-being. Simultaneously, the firm benefits from improved customer satisfaction, positive intentional behaviors, and the ability to set higher prices (Rosenbaum, 2008).

4.4 Outcomes of open innovation with partner firms Service

Collaboration with business partners positively affects innovation radicalness, which is seen to directly affect revenue and profit growth (Ordanini and Parasuraman, 2011). Business growth and competitiveness also improves through collaboration within the (virtual) value chain. Joint product innovation cycle time is seen to reduce with the aid of IT (Chatfield and Bjorn-Andersen, 1997). In NSD, knowledge sharing provides projects with a higher degree of novelty. Open approaches improve variety and quality of the outcomes, whereas development time is shorter for more closed NSD. However, the quality and intensity of relationships with both the external and internal resources is more important than the distinction between them (Hsieh and Tidd, 2012).

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Various industries

Cross-functional, cross-firm teams are found to increase the profitability of relationships with key customers and suppliers (Enz and Lambert, 2012).

For SMEs, partnerships with supply chain members facilitate more rapid and sustained growth (Wynarczyk and Watson, 2005). The effect of partnerships on corporate

entrepreneurship, through combining and accumulating resources, depends on partner fit, which is optimal when firms have dissimilar capabilities and similar organizational cultures (Thogren and Winsent, 2012). Product, process, incremental, and radical innovation all benefit from cooperation in the innovation process, in addition or instead of investing in internal R&D (De Propris, 2002). Moreover, cooperation activities of SMEs are correlated to commercial success in innovation (Fukugawa, 2006).

SMEs serving local markets do not see their productivity increase directly through co-innovation. An indirect effect is found for firms that initiate international expansion (Díaz-Chao, Sainz-González and Torrent-Sellens, 2015).

Retailing and consumer goods

Knowledge on managing a firm’s distributors enables continuous learning from them. Learning to collaborate is vital, since it stimulates knowledge acquisition and both

exploitation- and exploration-based (improving existing products and processes’ vs. creating new technologies, products, or services that could replace existing ones’) innovation.

Learning from distributors makes firms less likely to rely on one type of innovation only. The effect of knowledge in inter-firm relationships on firm performance is mediated by innovation (Hernández-Espallardo, Sánchez-Pérez and Segovia-López, 2011).

Technology

Direct and indirect ties with other firms positively affect the innovation output of a firm. The effect of indirect ties is moderated by the number of direct ties. In an inter-firm collaboration network, an increasing number of disconnections between partners negatively influences innovation (Ahuja, 2000). Strength of ties (length and multitude) affect regular (as opposed to high quality) innovation performance, as knowledge flows, creation, and sharing, as well as joint learning are stimulated. Interestingly, R&D network ties with a higher degree of cooperation and similarity of network ties affect innovation performance when weaker (Bertrand-Cloodt, Hagedoorn and van Kranenburg, 2011).

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innovation success. Successful external collaboration leads to faster product development and commercialization, better product performance and more radical innovation (Hartung and Mac Pherson, 2000). Parida, Westerberg and Frishammer (2012) found that for SMEs both incremental and radical innovation can be increased by open innovation, through technology scanning and sourcing and respectively. Vertical collaboration affect radical innovation performance, whereas horizontal collaboration influences incremental innovation. This is probably due to customers in high tech environments being large firms (e.g., IBM and Siemens) that are more informed about future requirements.

Manufacturing

In international networks, inter-firm knowledge transfer has a particular strong influence on innovation performance and the wider the reach of these networks, the higher are innovative sales. In collaborative agreements, it is unlikely that such an effect on performance will occur. This can possibly be explained through the shared organizational culture of transnational corporations in international networks (Frenz and Letto-Gillies, 2009). Other research, however finds that collaboration with external partners does positively contribute to

innovation, market and financial performance, (Wang, Dou, Zhu and Zhou, 2015; Zeng, Xie and Tam, 2010).

4.5 Outcomes of open innovation with suppliers Retailing and consumer goods

When supplier make use of social media, this use encourages retailers to make use of it to, which on its turn encourages consumer social media usage. Suppliers and retailers that combine their efforts can enhance performance for both parties, through better information provision and up-to-date communication. Brand reputation moderates this relationship (Rapp, et al., 2013).

Technology

Partnership with suppliers (and customers) is the most important type of partnership in the innovation strategy of a firm, as it is particularly well-suited for knowledge sourcing, and enable the firm to extend technology development capability, all leading to increased innovation. In addition, most inter-firm partnerships are with non-local firms, in order to extend market access and supplier networks (Angel, 2002; Huggins and Johnston, 2010).

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Industry

Supplier product integration does not significantly alter the occurrence of glitches in product development. In combination with supplier process innovation, however, fruitful indirect effects were found. Supplier process innovation also directly led to less glitches and better processing of last-minute engineering changes. This is possibly due to the relative long existence of supplier process integration in the US. Lower incidences of glitches improves market success, through higher quality, faster product introduction, lower costs, and improved customer satisfaction (Koufteros et al., 2010). Supplier involvement in NPD increases

performance for both the supplier and the buyer, with suppliers experiencing the greatest performance returns (Yeniyurt, Henke and Yalcinkaya, 2014).

Manufacturing

Relationships between buyers and suppliers that involve high levels of joint decision making and lower levels of joint sense meaning (operational knowledge integration) are seen to have high levels of efficiency, but limited innovation improvement. Higher levels of operational knowledge and lower levels of joint decision making exhibit the exact opposite. Therefore, the two strategies should be balanced to an equilibrium between efficiency and innovation. This does, however, not imply that both can be performed at their maximum levels (Revilla and Villena, 2012). Collaboration with suppliers was found to positively affect innovation performance of SMEs (Zeng et al., 2010) and manufacturers R&D (Calabrese, 2002).

4.6 Outcomes of open innovation with competitors Various industries

Competitors nowadays collaborate more often, sharing activities like technology

development, product design, and distribution. This often leads to lower costs, lower prices, and thus a higher consumer surplus. In addition the distinctiveness between the cooperation competitors decreases, but increases in comparison to non-collaborators. These effects put pressure on the prices of competing non-collaborators (Ghosh and Morita, 2012).

Technology

Horizontal collaboration improves the likelihood of launching a new product in comparison to launching it alone. Also, facing technological challenges together, creates benefits for both firms and advances innovation. This is especially the case when resource requirements are greater, resource availability is more limited, and the firm has stronger competence in

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inter-organizational concerns (Garette, Castañer and Dussauge, 2009; Gnyawali and Park, 2011). In the case of large competing firms, collaboration is challenging but rewarding. When executed effectively, a larger part of the benefits can be gained.

4.7 Outcomes of nonprofit-profit collaboration Various industries

When multinational enterprises (MNEs) expand into developing countries, they need to adapt to the local market’s cultural, economic, institutional, and geographic characteristics.

Collaborating with NGOs can help MNEs to reduce the difficulty of this challenge by providing resources and knowledge. Producing products of services together, by each

contributing capabilities can be beneficial for both parties and create and deliver social as well as economic value (Marano and Tashman, 2012). Another form of collaboration with NGOs in developing countries for for-profit firms is by sending teams of employees to work with an NGO in a cross-sector partnership. As a result these employees were provided with learning in several areas that was proven to be effective on the long term for developing and improving crucial competences for responsible global leadership (Pless, Maak and Stahl, 2011).

Business-nonprofit partnerships most frequently result in direct impact on the issue, for which collaboration was initiated. Businesses mostly aim to improve business accountability and gaining competitive advantage. The results are improved reputation, public awareness, or social capital. Another outcome is learning (interpersonal and administrative skills, technical skills in the area of the issue, reflective skills, and social learning that can lead to innovations) (Selsky and Parker, 2005).

4.8 Outcomes of government-industry collaboration

Government business partnerships are problematic. They may decrease short term costs, but they do not exhibit superior performance in terms of equity, access, or democracy per se. In addition, no regulation reduction is guaranteed, as government must protect the public good (Selsky and Parker, 2005).

Government cooperation however can be beneficial in the case of cooperative

regulatory enforcement. This entails that firms self-police their environmental operations and government provides regulatory relief for voluntarily disclosed violations, yielding optimal win-win outcomes. Effective cooperation reduces bureaucratic outputs (inspections, notices of violation, regulatory sanctions) and also reduces pollution (Potoski and Prakash, 2004).

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4.9 Outcomes of Research institution-industry collaboration Various industries

Universities can be a source of new technological knowledge. In this case, US universities can, whereas Japanese universities mostly cannot. Domestic firms profit more from this than foreign firms (Spencer, 2001). Collaboration between university and industry enables both to perform more explorative research, organize interdisciplinary research projects, and establish larger R&D projects (Lee, 2011). In addition, university-industry collaborations can stimulate innovative and economic performance of the local economy, through superior transfer of academic knowledge to the industry. Cooperation works best when both actors share one or more of the following: geographical area, technological knowhow, characteristics and adequate R&D competence, common values and norms, background, and experience (Slavtchev, 2013).

Technology

University-industry collaborations are crucial for innovation in science-based industries (Bstieler, Hemmert and Barczak, 2015). Partnerships with research institution can enable a firm to grow to become a profitable and competitive company through engaging in license agreements, getting access to materials at minimum costs to compensate this with royalty payments later (Marks, 2009).

Manufacturing

R&D collaborations between firms and research institutions have a significant positive influence the innovation performance of both product and process innovation and the degree of novelty (Nieto and Santamaría, 2007; Un et al., 2010; Zeng et al., 2010).

4.10 Outcomes of collaboration networks Technology

Describes the case of Centocor, biotechnological company. Achieved to grow to a profitable competitive company on the basis of partnerships with research institutions (license

agreements, provision of materials at minimum costs, royalties) and partner companies (filling product pipeline and faster market entry). Later the firm faced bankruptcy as it let go of its

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collaboration strategy, only to be saved by returning to its old strategy (Marks, 2009). Inward technology licensing does not significantly alter innovative performance. Internal R&D investment negatively moderates R&D outsourcing effect (more internal R&D and less external R&D drives performance). Collaborating with different types of partners yield higher innovation returns for firms with more internal R&D investment (Tsai and Wang, 2009).

Technological collaborative networks are crucial for increasing the novelty in product innovation. Suppliers, clients and research organizations (in this sequence) have a positive influence on the degree of novelty. Collaboration with competitors has a negative impact. The strongest positive influence stems from a collaborative network with multiple partners of different types (Nieto and Santamaría, 2007).

Manufacturing

Inter-firm cooperation, cooperation with intermediary institutions and cooperation with research institutions has significant positive influence on innovation performance of SMEs. Inter-firm cooperation shows to have the strongest impact. Vertical and horizontal

cooperation with customers, suppliers and partner firms are found to play a more important role in the innovation process of SMEs in comparison to horizontal collaboration with research institutions, universities, and government agencies. In fact cooperating with government agencies does not result in a significant positive influence on innovation performance (check for more) (Zeng et al., 2010).

R&D collaborations with suppliers have the strongest positive influence on product innovation, followed by university collaborations. Customer collaboration does not seem to affect product innovation, whereas collaborating with competitors even harms it. The positives are sustained over longer time, whereas the negative impact disappears after some time. Therefore, ease of knowledge access, above breadth, appears to be the driver of success. Before collaborating, facilities for knowledge transferring should be installed, also it is better to seek partners with a relatively narrow knowledge base. (Un, Cuervo-Cazurra and Asakawa, 2010). Collaborations with suppliers and universities have the most positive influence on process innovation. Customer collaboration does not have a significant impact, whereas collaborations with competitors influence process innovation in a negative way. Partners close in contextual knowledge distance are less suitable for process innovation. Upstream

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35 Even moderate levels of collaboration result in superior productivity and satisfaction. Collaboration capability makes firms aware and appreciate strong functional orientations and stimulates developing them to be essential parts of core competency. In addition, less

counterproductive decisions are made, by bridging the divide between up- and downstream business sides (Allred, Fawcett, Wallin and Magnan, 2011).

Tri-sector collaboration

Cross-sector social partnerships (CSSPs) can produce benefits at individual, organizational, sectoral and societal levels. Industry certification standards are set through tri-sector

partnerships. Four outcomes for competitive advantage of businesses: community building to resolve future local disputes, community recognition as a company of choice, reduced risk from negative publicity, and increased attractiveness to prospective employees.

However, complicated goals in tri-sector partnerships may lead to counterproductive outcomes as power of resolving public policy issues is shifted towards corporate interest (Selsky and Parker, 2005).

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5. Discussion

This section addresses the synthesizing of the results. Since the outcomes are already

discussed per stakeholder and a distinction in industries has been made, conditions for making the comparison easier have been facilitated. First of all, general outcomes for collaboration with the distinct stakeholders will be discussed. Second, some specific, remarkable results will be presented. Third, the contribution to the extant literature will evaluated, and

implications and recommendations for managers will be presented. Finally, the limitations of this research will be acknowledged and suggestions for future research will be provided.

Similarities, complementarities, contradictions, and reoccurring themes

The results of the literature review show that there are many ways in which a firm can achieve one of the many potential benefits of open innovation. Research agrees upon quite some outcomes, but there also appear some remarkable differences. In order to provide managers with a sense of direction, and to reveal interesting areas for future research, an effort will be made to identify important similarities and distinctions between different outcomes, as well as reoccurring themes that firms should be aware of.

Similarities and complementarities

A range of potential outcomes can be found throughout the reviewed literature. Most articles about co-creation with a certain stakeholder or in a specific industry back each other up on these outcomes. These outcomes will be presented as ‘general outcomes’ later. Therefore, these similarities will not all be listed. Rather, outcomes from collaboration with different stakeholders of industries that is complementary will be discussed here. The contradictory evidence that was found, will be discussed in the ‘contradictions’ section.

Multiple articles on customer-firm and buyer-supplier interaction in retailing, brand communities and co-producing communication found that social media represent a very valuable tool for brand management. Moreover, this is not only valid for collaboration between a firm and one stakeholder, a combined effort of all three stakeholders seems to be even more beneficial (Bacile et al., 2014; Rapp et al., 2013; Stokburger-Sauer, 2010; Zaglia, 2013).

Other complementarities consist of psychological processes that reoccurred in

different contexts throughout the reviewed literature, but result in the same effects. These are important for managers to consider when planning to implement a co-creation strategy.

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