Networking in the Asset Management Industry

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Networking in the Asset Management Industry

“Selecting partners for an innovation network at Company X”

Joyce Schellevis

March 2011

Faculty of Economics and Business

_{Kuipersstraat 162 II} 1073EV Amsterdam The Netherlands T +31 (0) 6 45284772 j.e.schellevis@student.rug.nl / jeschellevis@hotmail.com Student number: 1673041

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Networking in the Asset Management Industry

“ Selecting partners for an innovation network at Company X”

Supervisor 2nd Supervisor

dr. W. G. Biemans dr. J. D. Van der Bij

Company Supervisor _{drs. P. G. de Ree}

ABSTRACT

This research focuses on the selection of informal network innovation partners at Company X. Specifically, it aims to establish a framework which identifies parties that can make a significant innovative contribution to their Business Unit: Information Asset Management. By conducting extensive partner selection literature research and goals formulation a framework for network partner selection is presented. A case studies at six external companies, unveils multiple promising network partners and opportunities for Company X.

KEYWORDS

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1. INTRODUCTION

his research is focused on the selection of innovation network partners for Company X Information Asset Management. It shows a business unit of Company X that needs to identify partners and goals for an innovation network. Research will clarify the network goals and provides tools to select appropriate network partners for the asset management industry. In this chapter, the problem context, objective and research question.

1.1 COMPANY X

Company X is the network manager of the Railway systems in The Netherlands. The company was originally part of the Nederlandse Spoorwegen and became an independent firm in 1995 (Swier, 1995). Company X now has a three folded task. The core business of Company X consists of (1) managing the railway tracks to control the railway track quality and manage track utilization capacity. In addition, the organization (2) informs transporters and passengers and (3) assigns constructors to preserve tracks, signals and railway crossings. Company X needs to manage an extensive amount of information enabling the organization to control its quality and manage railway traffic. Company X aspires to create an external focus to enhance its tracks and provision of services in the near future (Company X annual report, 2008).

1.2 ASSET MANAGEMENT

Formerly, maintenance was seen as a costly, but necessary, craftsmanship (Swier, 1998). Technical innovations and information technology have entirely changed the importance of Asset Management, which is now considered as a valuable method to enhance a company’s performance. Assets of a company are defined as: “a physical item of property owned by a person or company, regarded as having value and available to meet debts, commitments, or legacies: growth in net assets” (Oxford dictionary). Consistently, Company X Asset Management is dedicated to control and assure the railway quality of its physical assets: the railways and railway stations in the Netherlands (BIM Report, 2010).

1.3 INFORMATION ASSET MANAGEMENT

This research focuses on Information AM, the section of Asset Management that controls and delivers all information related to a company’s physical assets (Appendix 1). Information AM consists out of 8 departments and their mutual mission is “To be the supplier of railinfra information in the Netherlands” (BIM report, 2010). Information AM manages, directs, and supplies rail information for Asset Management. Information AM consists out 4 departments: Infra Configuration Control (ICB), Infra Data Centre (IDC), Business Information Management (BIM), Rail Infra Data Services (RIGD) and four regional support offices. A small description of the activities of each department is presented in appendix 1.

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1.4 PROBLEM CONTEXT

The expected increase of traffic for Company X augments the importance of the current Asset Management Information systems. It emphasizes the need for accurate information in railway track maintenance. Information AM aims to enhance its performance by focusing on new Knowledge Management innovations. One of the focal points in the Information AM vision document 2010 is to develop an “innovation network”. The Business Unit wants to connect to external partners that can contribute to their main innovative goals. The network should not be a single event; Information AM aspires to connect to parties for long-term idea generation. Yet, no specific “Information AM goals” have been assigned and no parameters are in place to select a suitable network partner.

1.5 OBJECTIVE

Goals and criteria need to be determined to select appropriate partners for an innovation network at Information AM. This research should result in a full-perspective partner selection framework, enabling the identification of appropriate innovation network partners for Information AM. Accordingly, the objective of this research is threefold:

a. Specifying the need and goals for an innovation network at Information AM

b. Constructing a decision-making framework to optimize partner selection for an “innovation network” at Information AM.

c. Identifying “innovation network partners” by evaluating to which extent potential partners fit the criteria of the decision-making framework.

1.6 RESEARCH QUESTION

The preceding objectives resulted in the following research question:

How should Information AM manage partner selection for a long- term “innovation network” and which network partners can contribute to the goals of Information AM?

1.7 SUB QUESTIONS

In order to answer the main research question, the following sub questions have been defined: 1. What is the function of an innovation network for Information AM?

RECENT NETWORK ACTIVITIES OF INFORMATION AM

Information AM has participated in a long lasting external network project initiated by Banedanmark, a Danish railway company. Banedanmark commissioned consultancy company BSL to undertake an international “Asset Register” study. The aim was to define and compare asset management practices and systems of various European railways from Denmark, Sweden, Germany, Norway, UK, Austria, The Netherlands and Switzerland. Due to organizational issues BSL had to cease its activities in at the beginning of 2010 As a result, the Asset Register project had come to a temporarily halt. Only few “new” practices were identified between companies, creating the desire to create a network with new and different partners.

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2. Which framework and criteria enable Information AM to select partners that fit the function of their innovation network?

3. Which external parties, and companies and existing network initiatives fit the framework and criteria of Information AM?

4. How should Information AM manage network partner selection in the future?

1.8 RESEARCH MODEL

The objective, research question and sub questions result in the research model presented in figure 1. This model integrates the chapters of this research, to answer the main research question. The research starts at chapter 2, which explains the rationale behind Innovation Networks: What are innovation networks and why do companies establish them? In addition, it provides the main goals and characteristics of innovation networks. Chapter 3 presents a literature review of network partner selection criteria. Based on research over 25 studies, selection criteria for the Asset Management industry are presented.

The 4th chapter will provide an extensive methodology overview. The 1st section of this chapter justifies all process elements of this research. The 2nd section presents the partner selection framework for Information AM. This framework connects the partner selection criteria of chapter 2 to characteristics of the Company X Business Unit. Chapter 5 presents the internal and external results of this research. The internal results reflect the current innovative needs and goals of Information AM. These needs enable the selection of a sample group for network partner selection.

In the external results suitable network partners for Information AM are identified. Lastly, the conclusion will present suitable partners for Information AM. Lastly the recommendations explain how Information AM should manage network partner selection in the future.

Figure 1: Research Model for Network Partner Selection

Conclusion & Recommendations Chapter 3

Chapter 2 Chapter 4

Innovation Network Criteria Partner Selection Framework_{Methodology & Framework}

Network characteristics

Network partners Information AM

Methodological requirements

Goals Information AM Literature Review

Industry Characteristics

Partner selection conditions

Chapter 5 Input network partners

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2. INNOVATION NETWORKS

2.1 TAPPING INTO EXTERNAL RESOURCES

ccording to Dyer et al. (2006) knowledge is increasingly acknowledged by firms as “the most important source of lasting competitive advantage.” The relevance of knowledge is emphasized by the European Union which has formulated and accepted the Lisbon strategy in 2000 (Raspe et al., 2006). By adopting this strategy, Europe is aiming to become “the most competitive and dynamic knowledge-based economy in the world”. In this case knowledge industry should enhance the economical growth of the European Union. In order to reach this objective, European firms should continuously generate new knowledge as input for enhancements. Traditionally, firms relied on their own R&D for innovations and market dominance (Pyka et al., 2002). Nevertheless, an increasing amount of firms claim there is “not enough time to develop all knowledge internally” (Augier et al., 1999). As problems become more complex companies are also struggling to innovate alone (Pyka et al., 2002).

Consequently, many firms have switched their attitudes towards external innovation. Companies now tap into external resources to acquire assets that would not have been obtainable otherwise (Chesbrough, 2003). Moreover, firms embrace the thought that external knowledge can add substantial value to their corporation. Coalescing these internal and external resources can lead to competitive advantage over other firms (Dyer et al., 2000).

2.1.1 DEFINING INNOVATION NETWORKS

Nowadays, an increasing amount of companies collect external knowledge via “innovation networks.” The interest for innovation networks is also visible in European literature (Kusiak, 2009). The existence of innovation networks can potentially provide the insights that are needed in the current knowledge based economy. Gulati (1999) states that firms effectively participating in innovation networks are expected to have advantages over firms that do not have access to network knowledge resources. Accordingly, companies may establish an innovation network to enhance their

innovative performance. Table 1 presents multiple definitions of an innovation network. The

definitions of innovation networks show similarities. These definitions clarify that innovation networks consist out of parties that are: (1) autonomous, (2) connected to other parties, (3) conducted in order to acquire and (4) use knowledge in order to boost innovation. In this research, innovation networks will be defined as: Multiple autonomous parties assembled in order to accumulate and use knowledge primarily by means of knowledge creation and transfer processes, for the purpose of enhancing products or processes (Dyer et al., 2006; Gilbert et al., 2001; Dhanaraj, 2006; Rycroft, 2002).

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Table 1: Definitions of an innovation network

AUTHOR DEFINITION

Rycroft (2002) The complex webs of relationships among firms, universities, government agencies, and other organizations for generating and sharing knowledge relevant to technological innovation.

Lipparini et al. (1994) Loosely coupled coalitions, where loose coupling is a situation in which elements are responsive, but retain evidence of separateness and identity.

Dhanaraj (2006) Voluntarily formed, low-density innovation networks contain elements that are linked and preserve some degree of determinacy

Gilbert et al. (2001) Innovation networks are evolving from the dynamic and contingent linkage of heterogeneous units each possessing different bundles of knowledge and skill.

Dyer et al. (2006) Parties who are assembled in order to accumulate and use knowledgeprimarily by means of knowledge creationand transfer processes, for the purpose of enhancing innovation.

2.2 PHASES OF INNOVATION NETWORKS

According to Powell et al. (2005) an innovation network can be viewed as a collection of alliances and collaborations. Accordingly, academic scholars have embedded alliance and collaboration literature in network research (Beckman et al., 2004). This literature provides insights about the main phases of

innovation networks. Kale et al. (2009) created a model

which depicts the most

dominantly applied alliance phases in literature, as: (1) Alliance Partner selection, (2)

Alliance Governance and

Design and (3) Post formation Alliance Management (figure

2). Identical phases are

distinguished in collaboration

and innovation network literature (Van Aken et al., 2000; Beckman et al., 2004; Sami et al., 2002). This research focuses on the first phase of innovation networks: the selection of “innovation network” partners. Figure 2 shows that the partner selection phase is linked to the achievements of objectives and success drivers. These factors are supported by Nambisan (2009) who defines partner selection,

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goals setting and success selection criteria as the main ingredients for collaboration. This research will extensively explore goal setting and selection criteria to select network partners.

2.3 INNOVATION NETWORK GOALS

Innovation networks can have different purposes. Accordingly, companies find their own way of tapping into “The global brain” (Nambrisan et al., 2007). Companies such as, IBM, Proctor & Gamble and Toyota have different incentives to establish innovation networks. For instance, Toyota has established a supplier network to gain access to productivity enhancing knowledge (Dyer, 1994). On the other hand, Proctor & Gamble is taking networking to a new level by launching their “Connect and Develop” program to get access to new technologies (Huston et al., 2006). In the 1st_{section of this} paragraph, the main goals of innovation network goals will be presented. The 2nd_{section of this} paragraph focuses on the innovative needs regarding innovation networks.

2.3.1 INNOVATION NETWORK MOTIVES

The selection of network partners influences the outcome of collaboration initiatives (Ozman et al., 2008). Prospective network partners have different characteristics that may, or may not, fit the purpose of an innovation network. Table 2 presents the main reasons to establish an innovation network. These main functions are defined as: (1) risk-driven, (2) business opportunity and (3) reputation.

1. RISK-DRIVEN

It is difficult to estimate the success of an innovation in the early development phase (Love et al., 1999). When a product or service is in fact successful, shrinking product-life-cycles may force companies to innovate faster. Firms are lowering such risks by tapping into external resources in order to accelerate innovation activities (Chesbrough, 2006). R&D departments frequently modify an Table 2: Firm Collaboration Motives

Function Motive to collaborate

Risk-driven Reducing risks of failure in high costs of R&D (Pyka, 1999 Milis, 2008) Time – to - market (Chesbrough, 2006 Love et al., 1999 Bresnen et al., 2000)

Product Differentiation (Austin, 2008) Market Expansion (Austin, 2008)

Exploring new markets and market niches (Pyka, 1999) Quick pre-emption strategies on a world scale ( Pyka, 1999) Monitoring technologies and opportunities (Pyka, 1999) Process enhancements (Dyer, 2000)

Business opportunity

Reputation

Enhancing the innovative Reputation (Moen et al.,2005) Enhancing Reputation (Dhanaraj et al.,2006; Austin, 2008)

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“existing external idea.” Thus, their R&D departments do not need to invent a new technology; they simply adjust an existing technology to save time. This has two potential advantages: it reduces costs and decreases time-to-market. High-tech parties such as bio-industry firms are known to value these advantages. As stated by Pyka (2000): “Although the lead times between the discovery of new knowledge and its final embodiment in new products may be very long, the time between the creation of new knowledge and the funding of industrial research aimed at its applications is in general very short.” As a result, minimization of time and cost related risks is an appealing strategy for high-tech firms. Nevertheless, Chesbrough (2006) states that external knowledge is not only beneficial for high- tech companies: External knowledge is potentially advantageous for every innovating company.

2. BUSINESS OPPORTUNITY

Values and risks are not the only incentive to contact companies. As stated by von Hippel et al. (1999): “Developers simply don’t know how to achieve breakthroughs, because there is no effective system in place to guide them and support their efforts.” Thus, companies may also be in search of new knowledge combinations that they can not capture individually. For instance, companies may be in search of new products (Austin, 2008) or process enhancements (Dyer, 2000). A large part of the innovation networks are focused on these “business opportunities”. In fact, this is the most frequently selected purposes for an innovation networks. The enhancement of products, services, strategies and processes are considered as the main reason to establish an innovation network (Pyka, 1999).

3. REPUTATION

Companies also connect to innovation networks to enhance their reputation. Small firms tend to show interest in large multinationals to boost their familiarity (Dhanaraj et al., 2006). On the other hand, large companies are frequently aiming for an “innovative reputation”. (Moen et al., 2005). In collaborations reputation enhancement is often considered to be “a positive side effect” of networking. (Austin, 2008). Thus, the majority of firms to not consider reputation to be the main incentive to establish an innovation network.

2.4 GOAL ASSESSMENT

In order to select suitable partners for an innovation network, a thorough goal assessment is needed (Brouthers et al., 1995). Goal setting is the first step towards partner selection; it is necessary to properly determine the desired capabilities of a company (Chesbrough et al., 2007). This assessment should match the strategy of a company (Kale et al., 2009; Gilbert et al., 2005). Stanek (2004) also emphasized the importance of network goals by stating that “by determining the goals and objectives, firms can ensure that each others’ desired outcomes can be met”

Companies tend to focus on their own network goals, actions and resources. Håkansson (1997) claims that the strategic task is to formulate”a scope of action that includes both current and potential relationships”. This is supported by Gilbert et al. (2005) who emphasize that network

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12 Figure 3: Internal and external newness strategy should include interests and the innovative orientation of current company network activities.

2.5 INNOVATIVE ORIENTATION

Innovation network goals are usually connected to the innovative orientation of a firm (Rijnders ,2002). A network can focus on

radical operational processes such as New Product Development and production as well as incremental innovation such as continuous improvement.

Freel et al. (2009) distinguish four types of innovative “needs” for innovation networks as: (1) Market Developing, (2) Radical, (3) Incremental and (4) Competence

Developing (figure 3). the innovation

networks needs of a company are determined by the degree of internal and external

newness. Different orientations result in different network partners. External newness refers to the need to improve existing skills and competences. For instance, Information AM could have an IT system which requires minor adjustments. The Business Unit might decide that their existing skills are adequate for system improvement. Additionally, newness to the market is distinguished. When a desired technology or knowledge is new to the market, firms should seek network partners outside their own market (Pyka, 1999) if skills are only new to the firm, companies may tap into resources from parties in their own market. Also, incremental and market developing requirements are mostly developed internally, since improvement is based on existing skills. For Competence Developing and radical goals, companies should reach out for new network partners.

2.6 INNOVATION NETWORKS: FORMAL AND INFORMAL CONSTRUCTS

Literature shows a variety of innovation networks types. Networks do not solely differ in purpose; they also differ in formality (Ritter, 2003). Table 3 displays the differences of formal and informal information networks. Van Aken et al. (2000) characterize formal networks as “an organization network, based on an explicit collaboration agreement”. The majority of scholars focus on formal constructs such as: Strategic Alliances, R&D Consortia and Joint Ventures. Nevertheless, an increasing amount of academic scholars confirm the existence of informal networks (Van Aken et al., 2000). Informal networks are based on trust instead of legally binding contracts. Informal networks are preferable for idea generation; at the start of the innovation funnel (Ritter, 2003). Wheelright et al. (1992) concur by stating “Collaboration in informal networks is not aimed at actual information, but at learning and testing of ideas for innovation.”

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Table 3: Characteristics of formal and informal networks

Source: Ritter, 2003 Formality in innovation networks should be labeled as a continuum (Van Aken et al., 2000). There are many levels of formalization in networks. In time, the formalization of innovation networks can change. For instance, when suitable ideas arise in an informal innovation network, firms may decide to enter formal agreements. The potential network of information AM is clearly focused on learning and idea generation. Therefore, this research is dedicated to the selection of informal innovation network partners.

2.7 SHARING KNOWLEDGE IN NETWORKS

Sharing knowledge with external parties can be challenging. Willingness to share information

depends on the knowledge topics and a company’s interests (Sarvary, 1999; Van Koetsveld et al., 1992). Companies are especially hesitant to share information that affects their core business. When members compete against one another for resources and markets, suspicion may replace trust in relationships. Therefore, firms need to make a knowledge screen to define which resources a company needs and wants to share (Sarvary, 1999; Dyer & Singh, 1998). Network partners may want to imitate or copy the distinctive competencies of one another firm. A successful imitation would lead to the loss of competitive advantage of that particular network partner. Thus, risk may be enhanced when working with a competitive network partner. Literature shows that collaborations with competitors may be successful (Hamel et al,, 1989). Due to a lack of trust formal contracts need to be established and specific objectives need to be determined. Thus, working with competitors is less suitable for informal innovation networks.

2.8 DYADIC AND NETWORK PERSPECTIVES

Network partner selection literature defines two main perspectives: a dyadic perspective and a network perspective (Anderson, 2004). Håkansson (1994) presents the differences between dyadic and network perspectives (table 4). In a dyadic relationship a partner is selected on an individual level. This is advocated in literature since mixed-motives, in which the partners have private and common interests, are best captured for two individual partners. Yet, others claim that the complexity of networking is best captured in a network perspective (Anderson, 2004). In a network perspective partners are matched to the portfolio of existing network partners. This perspective focuses on the dynamics and interests of all partners to leverage maximum results (Gulati et al., 1994).

Characteristics Formal Innovation Networks Informal Innovation networks

Goal Setting Narrow goal setting Broad goal setting

Innovation phase: Executive Idea generation,

Main company interests Financial output Learning; collecting knowledge Partner selection Few selected partners Broad variety of partners

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Table 4 : Dyadic and network perspectives

According to Baum et al. (2010) “relationships are not regarded as dyads and their relationships are always related to each other.” As a result, companies might favor a network perspective to gain a holistic view of networking. Nevertheless, in order to select companies on their dependence, companies need an existing network of partners.

DYADIC PERSPECTIVE NETWORK PERSPECTIVE

• Strategic choice based on:

- Autonomy, The interest of individual partners, - The firm’s function in the market

• Strategic choice based on: - Dependence

- The firm’s interest in its network - The firm’s function in the network • Alliances are managed as dyads

- Partner selection based on individual fit - Bilateral knowledge exchange

- Manage alliances as separate contracts

• Alliances are managed as a portfolio - Partner selection based on network fit - Knowledge leverage across partners - Manage alliances as a set of competences • Top management initiates and evaluates • Top management moderates and prioritizes

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3. CRITERIA FOR NETWORK PARTNER SELECTION

n innovation network consists out of multiple individuals, parties and organizations that share information to enhance their innovation activities. Tailored selection criteria facilitate a more selective and purposive partner selection process (Che-Mat et al., 2009). Consequently, this chapter focuses on indentifying criteria suitable for the Asset Management industry. An extensive literature review will determine how network partners should be selected.

3.1 PARTNER SELECTION CRITERIA

According to Pyka et al. (2002): “Any partner who can contribute to your organization is a potential network partner.” Nevertheless, from this broad perspective almost any company should be evaluated for an innovation network. Since company resources are exhaustive and time is limited a company can only approach a select sample of companies for their network. Therefore, specific partner selection criteria need to be evaluated in order to determine whether a prospective partner can contribute to a company’s innovation network objectives. Frequently, companies spend little time on network partner selection (Brouthers, 1995). Solely focusing on desired resources will provide limited insights into the future contribution of a network partner (Gulati, 1999). Consequently, a broad set of criteria including research skills, technologies and markets should be evaluated.

The preference for partner selection criteria varies per industry, geographical location and even per company (Geringer, 1991). This research focuses on Asset Management companies in search of suitable informal network partners. Hence, the main criteria are supported by literature linked to the Asset Management Industry in order to help companies and organization from this sector to select suitable network partners. Appendix 2 presents evaluation of the partner selection criteria for informal partners in the Asset Management Industry. This assessment results in the partner selection criteria presented in table 5.

The broad set of literature has been divided in criteria in 5 main selection topics to make the process of partner selection manageable. The final categorization is provided in appendix 2 and now consists of: (1) Complementarity (2) Strategic Motives, (3) Company Culture, (4) Company relatedness, (5) Connectivity. These aspects will be explained individually in the next paragraphs.

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Table 5: Network partner selection criteria

PARTNER CRITERIA CATEGORIZATION DEFINITION

Complementarity

Gains

Fit

Market knowledge access (Dacin et al,, 1997) Tangible assets (Dacin et al,, 1997)

Complementary resources (Solesvik., 2010) New practices and technologies (Powell et al., 1996)

Technical capability (Bailey et al., 1998) Technical Alignment (Cantalone et al,, 2006) Higher or equal technical skills (Zahra et al,, 2000) Intangible Assets (Milis, 2008; Dacin et al,, 1997) Complementary skills (Brouthers et al,, 1995) Complementary partners (Pena, 2002) Unique competencies (Hitt et al,, 2002) Partner Complementarity (Kale et al, 2009)

Complementary skills (Das et al. 2000 ;Shah et al., 2008)

Strategic Motives

Fit

Similar goals (Marwell et al., 1993) Comparative goals (Brouthers et al., 1995) Compatible goals (Dat et al., 2006)

Strategic inter-dependance (Zaheer et al., 2000) Matching aims (Bailey et al., 1998)

Strategic positioning (Bailey et al,., 1998) Strategic motives (Pena., 2002)

Partner Compatibility (Kale et al., 2009) Strategic Alignment (Cantalone et al., 2006) Strategic fit (Solesvik, 2010)

Company Culture

Fit

Similar company culture (Renforth, 1974) Cultural fit (Littler et al,, 1995)

Cooperative cultures (Brouthers et al., 1995) Cultural compatibility (Bailey et al., 1998) Similar corporate culture (Chung et al., 2000) Relational Alignment (Cantalone et al., 2006) Connectivity

Connections

Bridge to other companies (Nelson, 1993) Network function (Anderson et al, ,1994) Links with major suppliers (Solesvik, 2010) Links with major customers (Solesvik, 2010) Links to major buyers”(Nielsen, 2003a) Network Redundancy (Baum et al,, 2000)

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3.2 COMPLEMENTARITY

The need to assess the complementarity of a network partner is acknowledged throughout literature (Brouthers et al., 1995; Dacin et al., 1997; Hitt et al.,2002; Dat et al.,2006; Pena, 2002;). The Oxford Dictionary defines complementary as: “Combining in such a way to enhance or emphasize the qualities of each other.” It represents something the company knows it needs. Buono (1997) claims that complementarity also implies dissimilarity enabling “two partners to compensate for their individual inadequacies.” This may be the case if “one company has excellent marketing but mediocre production technology, whereas the other company does not know how to sell its products very well but has excellent production technology” (Van Oudenhoven, 1996).

3.2.1 GAINS

Complementarity reflects various company gains. The literature overview (Table 5) discerns tangible and intangible gains. Innovation networks frequently focus on intangible gains such as skills, knowledge and technologies (Mowery et al., 1998; Peña, 2002; Kale et al., 2009). For instance, Mazda collaborated with Ford in order to gain global marketing advantages (Cunningham et al., 1995). Tangible assets of innovation networks consist of goods, revenue and related transactions (Solesvik, 2010; Milis, 2008). Connecting for tangible resources supports the resource-based view, which entails that firms are in search for partners with unique resources (Hitt et al., 2001). The preference for resources, competency or technology approach is determined by the motives to establish an innovation network. Thus, the need for either process enhancements or product differentiation can result in different complementarity gains. Stanek (2004) states that network goals and connected gains determine partner complementarity requirements. Consequently, the gains of an innovation network largely influence the criteria of complementarity.

3.2.2 FIT

Firms should also consider compatibility of a potential network partner (Das, 1998; Geringer, 1988). Compatibility refers to the ability to implement the potential technologies or practices in an

PARTNER CRITERIA CATEGORIZATION DEFINITION

Company characteristics Size Business Relatedness Reputation

Similar company size (Daniels, 1971 ; Al-Khalifa et al., 1999; Chung et al., 2000)

Sufficient size (Solesvik, 2010)

Industry relatedness (Dacin et al., 1997)

Relatedness of Business (Li et al., 2002 ; Moen et al.,2005) Company Relatedness (Gulati,2003)

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organization. If a network partner is exceptionally complementary, its assets may also be very different (Parise et al., 2003). This creates new opportunities: since different network partners may offer numerous radical and unexplored insights. A high degree of complementarity is especially valued in radical innovations (Powell et al., 2006). For instance, 3M is continually in search of radically “different” partners that are able to provide breakthrough technologies (Von Hippel, 1999).

Yet, when a network partner is extremely complementary, a large amount of adaption and improvement is needed for the implementation of practices and technologies (Parise et al., 2003). Hence, complementarity should also reflect the innovative orientation of firm.

3.3 STRATEGIC MOTIVES

Academic scholars conclude that complementarity is a qualifier and not a sufficient indicator for successful partnerships (Mindruta, 2008). According to Huggins (2001) and Kale et al. (2009) networks should consist out of firms that are pursuing similar objectives or problems. In the model of Cantalone et al. (2006) this is defined as goal correspondence. Goal correspondence refers to partners that have non-competing goals. High goal correspondence enhances “the consistency of expectations and mutual gains.” Parties in the network are seeking for partners with information that fit their network purposes (Cantalone et al., 2006). Thus, this criterion reflects the evaluation of companies’ individual goals and the external partner’s needs and goals.

Network partner goals are not necessarily identical; it merely assures that one goal should not exclude the other one. Exclusion of each other’s goals is the most visible between competitors (Brouthers et al., 2000). Interests are so similar they conflict heavily, which lowers trust and the ability to share knowledge and resources. Accordingly, competitors are reluctant to collaborate and participate in informal networks (Ritter, 2003). A stakeholder analysis can provide insights about the competitive interests between companies (Schmeer, 1999).

3.4 COMPANY CULTURE

Arthur (1995) and Brouthers et al., (2005) emphasize the importance of in-depth knowledge about the cultural contexts and socio-economic relations of actors within networks. Relational alignment enlightens an additional aspect of partner selections for inter-firm collaborations. Relational alignment defines the financial and legal feasibility of collaborations (Cantalone et al,, 2006). Furthermore, a company should be able to adapt when changes occur in an organization. Company culture is especially important in formal innovation networks (Littler et al., 1995). In constructs such as strategic alliances, partners frequently work closely together (Chung et al. 2000). Even in less formal initiatives companies should select companies which culture is compatible. Hence, a minimum amount of congruity should exist between company norms (Inkpen, 1998). This enables partners to create a shared communication platform enabling them to speak the same company language.

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A company’s network normally consists out of multiple interrelated parties. This also implies that external contacts may have access to other valuable firms and organizations. The connectivity of a network is frequently labeled as the secondary function of a network (Anderson et al., 1994). It reflects the indirect positive and negative effects from the connection to other relationships. For some companies connectivity is the main reason to connect to other firms. It helps firms to attract new indirect contacts that can contribute the most to the enhancement of their organization. High connectivity makes a company “sought after” network partner (Burt, 1992: Nelson, 1993). As a result, it is relevant to determine if potential network partners have a special connectivity rate, that attracts new and appealing partners.

3.6 COMPANY CHARACTERISTICS

The company characteristics are a combined set of sub-categories in literature that can be evaluated with publicly available company information. The characteristics labeled as company Characteristics are: (1) Business Relatedness, (2) Company size and (3) Reputation will be discussed.

1. RELATEDNESS OF BUSINESS

Companies often selected business partners based on their business relatedness (Li, 2002). Firms are in search of companies with similar businesses in order to create synergies (Buzzell et al., 2000). In this case the relatedness of business does not mean that the network companies need to be exactly similar. On the contrary, if firms are particularly similar, the learning expectancy of firms is known to decrease (Harrisson, 2002). Thus, the relatedness of business should have enough overlap in order to be able to implement new ideas that fit the needs of the company.

2. COMPANY SIZE

The size of a company is considered to be a relevant network characteristic for inter-organizational networks (Brouthers et al., 1995). Partner size is known to create symmetry between partner firms, measuring a partners experience and knowledge (Kraatz, 1998). The similarity of size also leads to an enhancement of cultural compatibility between alliance partners. Lastly, company size also affects the organizational learning capacity of a company (Hokisson et al.,1994). Small companies frequently lack the expertise and resources for intensive tacit knowledge sharing (Khanna et al.,1998). This means that small companies do not have specific frameworks and base their decision-making on intuitive ideas. Thus, they have a less clear structure which makes it more difficult for large partner firms to compare activities with smaller firms.

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3. REPUTATION

In chapter 2, enhancing one’s reputation is defined as one of the reasons to establish an innovation network. Also, the reputation of external companies influences the selection of a network partner selection. According to Moen (2005) “Engaging in collaboration activities with firms that have a well-known name and reputation in the market would lead to increased legitimacy”. As a result, managers often prefer research partners that are “well-known” and “respected” throughout their own company.

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4. METHODOLOGY

his chapter presents the methodology of the innovation network research. It justifies the selection of all data sets, interviews and conducted methods. Section 1 will validate the type of research and defines the research process. Section 2 will present the partner selection framework for Information AM. This framework is the main evaluation tool of this research, enabling Information AM to select network partners.

4.1 RESEARCH CHARACTERIZATION

Van Aken et al. (2007) explain that qualitative research is preferable when determining the behavior of people, groups and organizations. Moreover, it provides a deeper level of understanding about research topics (Cooper et al., 2006). This research determines the internal and external altitudes of managers in different organizations. Since this research is explorative, qualitative research is preferable.

De Pelsmacker et al. (2006) distinguish two qualitative research methods: (1) in-depth interviews and (2) case-study research. This research will use both methods to select innovation network partners. In-depth interviews will provide the information that is necessary for the research. Additionally, a case- study will be conducted in order to test which network partner is the most suitable for Information AM. Furthermore, De Leeuw (1996) states that case studies consist of a comparison of multiple company cases, with the objective to be able to make assumptions and conclusions. Yin (2004) states that case studies are often used to conduct explorative research, which makes this method appropriate for this research. In this research, cases consist out of the six companies that are evaluated for the external interviews.

4.1.1 INTERNAL INTERVIEWS

According to Huggins (1999), the in-depth face-to-face interview is a reliable method to collect information about a respondents‘ motivation and attitudes. In order to collect information about the goals of prospective innovation networks, individual interviews were conducted with all the managers of Information AM.

4.1.1.1 SAMPLE SIZE

Qualitative research involves non-probability sampling (Cooper et al., 2006). This means that, little attempts generally result in a representative sample group. Within non-probability sampling, purposive sampling was applied. Participants are selected based on their characteristics and experiences. The sample group consists out of all managers at Information AM, since they are able to provide the necessary tactical and strategic view of the “needs” of Information AM. The managers have provided information about the current and future strategy during in-depth interviews with duration of approximately one hour each.

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22 4.1.1.2 INTERVIEW CONTENTS

Data collection of explorative research is discerned in (1) explorative and (2) verification activities (Johnson, 2002). The individual internal interviews explored the individual knowledge themes of the managers at Information AM (Appendix 3). In the interviews, all the former MT members were interviewed, since they had the expertise necessary to make decisions (Table 6), Afterwards, the management meeting was conducted in order to verify, define and prioritize these goals. Verification of in-depth interviews is also preferred by Johnson (2000), who states that “members can fruitfully use in-depth interviews to check, stimulate or inspire their own self reflection and to see in their understandings are the same as those shared by others who are also members or participants.”

In the management meeting, all themes were presented and definitions were formulated to enhance the consistency of goals and visions. At the management meeting the newly established MT individually selected the knowledge themes most beneficial for Information AM (Table 6). Lastly, managers were confronted with all prioritization results. This is also defined as “mirroring” and is a suitable method to combine individual preferences and stimulate decision-making (van Berge et al., 1999).

Table 6: Interview & network session participants: Managers of Information AM

Function II* MM**

Manager Information AM Central X X

Manager Infra Data Centre X X

Manager Infra Configuration Control X X

Manager Business Information Manager (BIM) X X

Program Manager, Alliance Manager Rail Infra GD X X

HR Advisor Infra Information X

Regional Manager “Randstad Zuid” X

Regional Manager “Zuid” X

Regional Manager “Noord- Oost”, “Randstad Noord” X X

4.1.2 MEASUREMENTS FROM THE MANAGEMENT MEETING

In the second management meeting the decision-making criteria were prioritized and accepted by the management team. Schindler et al. (2006) define four types of evaluation scales as: rating, ranking, categorization and sorting. When selecting the knowledge themes for Information AM, a direct comparison had to be made between various knowledge topics. Consequently, ranking was the most appropriate selection method to determine the most suitable knowledge topics in the network meeting.

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4.1.3 EXTERNAL INTERVIEWS

The external interviews were conducted to indicate which partners are potentially suitable for information AM. The conducted interviews were semi- structured and focused on answering the requirements of the managers of Information AM. Participants of the interviews were mostly new to Company X and the meeting was presented as an opportunity to meet and potentially help each other in the future. To ensure the best input for the framework, the external companies were not told that they were “scored” as a potential network partner. As a consequence, the managers of Information AM completed the evaluation of all potential network partners. One manager was present at all external interviews. After discussing his individual rankings with the management team, scores were submitted for the research,

4.1.4 VALIDITY AND RELIABILITY

When conducting research, reliability and validity need to be considered. Firstly, the internal validity needs to be addressed. The results of a study are internally valid when conclusions about relationships are justified and complete. (Van Aken et al., 2007). To establish this, one has to make sure that there are no plausible competing explanations. Internal validity is high when many of the actual causes of the problem are found. To support internal validity a construct was built based on the multiple information sources: literature, desk research, internal and external interviews. Additionally, all characteristics were gathered and supported by extensive theoretical literature. According to van Aken et al. (2007) external validity reflects the extent that a research result can be generalized to other companies. From this point of view the general partner selection criteria could be applicable for the Asset Management Industry. Construct validity as described by van Aken et al. (2007) will be dependent on the questions that will be conducted for the research. To ensure sufficient construct validity for the internal and external face-to-face interviews, questions were asked to measure the challenges of Information AM, the innovation network best practices at Company X and the suitability of external companies.

The reliability of a research is high when the outcomes of a research will be consistent when it is conducted by another researcher (van Aken et al., 2007). Reliability can be enhanced by using multiple research methods. In this research, a combination of documents and multiple types of face to face interviews were used to accomplish “triangulation.”

4.1.5 CREATING A STRUCTURE FOR NETWORK PARTNER SELECTION

Brouthers et al. (1995) claim that the main focus of companies in an innovation network should be individual company goals. Moreover, firms should only be in an innovation network if it contributes to company goals (Ritter, 2003; Kale et al., 2009). Chapter 2 defined boundary condition for knowledge sharing. This section will combine all literature to create a structure for network partner selection at Information AM. Figure 4 shows how knowledge themes are selected for Information AM. Networking starts with a strategy.

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Figure 4: Selecting Network themes for Information AM

Not every topic may be suitable for knowledge sharing with external parties. As a result not every strategic goal of Information AM might be realizable through innovation

networks. Thus, boundary conditions

influence the selection of knowledge themes. After considering these conditions knowledge themes can be selected for Information AM.

When sharing knowledge in external

companies (1) new opportunities might arise (Van Aken et al., 2000) and (2) new boundary conditions might be discovered (Cravens et al., 2000). These learning affects can lead to new strategies that call for a refinement of the process. Thus, strategies may affect new boundary conditions, knowledge themes and network partners in the future.

4.2 FRAMEWORK FOR NETWORK PARTNER SELECTION

Chapter 3 defined a list of selection categories suitable for network partner selection. But how should literature criteria be fitted into a framework for Information AM? When is a partner relevant for Information AM? And which perspective should be selected? Information AM has not yet established a network it is not possible to determine if partners are compatible with other partners and fit within a portfolio. Therefore, this research uses a dyadic approach to determine if single companies possess the competencies that are required by Information AM. Subsequently, the data of the previous chapters is integrated in figure 5 which presents: “The dyadic partner selection framework for Information AM”. The framework shows how the main network criteria: (1) complementarity, (2) connectivity, (3) strategic alignment and (4) cultural alignment are measured for network partner selection.

4.2.1 THE ORDER OF SELECTION CRITERIA

Cantalone et al. (2006) and Pena (2000) created different phases for partner selection. This main focus is based on complementarity; the individual needs of the company. Complementarity is the main reason to collaborate with a partner (Cantalone et al., 2006). Only after this stage, two main characteristics determine if the complementary partner can and will collaborate. Accordingly, the first question is: are partners complementary for Information AM? Nevertheless, in fruitful partnership needs of both partners are fulfilled. The next phase determines if the needs of a partner are strategically aligned and a win-win situation can potentially be created. However, this is not sufficient for partner selection. Can the potential partners actually work together with Information AM? This is measured in the third question that leads to a suitable network partner.

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4.2.2 PRE SELECTION OF PARTNERS: COMPANY CHARACTERISTICS

The first step included the selection of the sample group. Since firms have limited time for networking, Information AM made a selection of potentially interesting network partners. The first selection was fully based on publicly available information and preferences of the managers of Information AM. The sample group was based on the partner selection criteria “Company Characteristics” defined in paragraph 3.6. As mentioned previously, these are aspects that can be determined in advance. This sample selection determined which companies should be approached for the external interviews.

Thus, this is merely a pre selection based on publicly available information. The managers of Information AM determined how to measure the company characteristics sub categories: (1) business relatedness, (2) company size and (3) reputation. The full lists of measurements is shown in appendix 4.

1. BUSINESS RELATEDNESS

In order to test business relatedness, managers were asked to define characteristics that determine the business relatedness of Company X. These characteristics consisted out of aspects such as: relatedness to Asset management and a governmental company link.

2. COMPANY SIZE

The managers are interested in companies with at least 500 FTE and a maximum of 10.000 FTE. Consistent with the literature managers estimated that companies with at least 500FTE and a maximum of 10.000FTE have more knowledge access and are more similar to information AM than companies that do not meet these characteristics.

3. REPUTATION

The managers determined if companies are known as “high class companies” and could enhance the reputation of Company X. In the 2010 vision document of Company X companies defined as leading also received a positive mark.

Parise et al. (2003) claim that company become more “similar” once they start to exchange knowledge. They benefit from each others’ insights and implement best practices. Approaching new and more unexpected parties can help a company to gain new innovative ideas. To avoid repetition and to aim for new insights, the railway companies of the Asset register (Discussed in chapter 1) will not be included in this research. Nevertheless, the selection of strategy, goals and knowledge topics of this research may be used as input for further activities of the Asset Register Network.

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Figure 5: The partner selection framework

COMPANY CHARACTERISTICS REQUIREMENTS

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27 4.2.3 STEP ONE: MEASURING COMPLEMENTARITY

Chapter 3 explained the importance of partner complementarity. But when exactly can an external firm contribute to these themes? The management of Information AM has defined the following six requirements for complementarity:

Current project that has the potential to be successful Agree Disagree

1. The firm has created a vision/model/process 1 2 3 4 5 2. The initiative is either promising or successful 1 2 3 4 5

3. The initiative has been implemented 1 2 3 4 5

4. The initiative is maintained and implemented by the company 1 2 3 4 5 5. The initiative is implementable within Information AM 1 2 3 4 5

In the framework, a 5-point-scale is selected to evaluate all questions. Schindler et al. (2006) state that the scale “ has to make sense” and depends on the complexity of the questions. As a result the managers selected a 5-point-scale because the amount of criteria is limited and nuance is needed to answer the questions.

In order to pass the criteria, companies need to score above the average (average above 3).. To exclude extremes, only one score below three is permitted to pass the complementarity test. Only when a partner passes the complementarity stage, the strategic alignment of a company should be evaluated. Otherwise, the only thing left to do is to evaluate the connectivity of the network partner.

4.2.4 STEP 2: MEASURING STRATEGIC ALIGNMENT

The management team of Information AM wants to create a win-win situation for its network partners. Strategic alignment will identify if Information AM can meet the needs of a network partner. Accordingly, the following requirements for strategic alignment were set:

Agree Disagree

1. The company is willing to share its knowledge 1 2 3 4 5

2. Information AM is able to fulfill knowledge needs of the external partner? 1 2 3 4 5 3. The knowledge needs of both company is balanced 1 2 3 4 5 4. Sharing information does not result in significant risks 1 2 3 4 5

5. The goals of both parties are synergetic 1 2 3 4 5

Consistent with the measurements of complementarity, scores should be above average and only one scores below 3 is allowed. If the scores for Strategic Alignment do not suffice, Information AM could still evaluate if the company can provide a “one shot of knowledge”. In this scenario, it is likely that a company is not a long-term innovation network partner and only the connectivity of the external company can be examined.

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28 4.2.5 STEP 3: MEASURING CULTURAL ALIGNMENT

Finally, the cultural alignment for an innovation network will be examined. Partners need to be able to”understand each other” and work together in order to participate in an innovation network. Additionally, the management team decided to focus on competence development (paragraph 2.5): which means that common grounds between partners are preferred. For now, the management team of Information AM has determined that only three cultural aspects could be formulated. As a result, the requirement for cultural alignment is formulated as:

Agree Disagree

1. Companies can potentially create a communication platform 1 2 3 4 5 2. Structures and working methods of companies are similar 1 2 3 4 5 3. Working together does not cause cultural issues 1 2 3 4 5

When passing the last criteria (2 scores above 5, average below 5), companies are labeled as potentially interesting network partners for long-term collaboration. Thus, it is worthwhile for Information AM to explore and invest in the partner and either implement its best practices or evaluate new initiatives and technologies.

4.2.6 MEASURING CONNECTIVITY

From a dyadic perspective of Anderson (1994) Information AM may consider to keep in touch with the network partner because they have access to potential relevant partners. This evaluation is solely based on the interests of Information AM. Thus, interest of potential partners will not yet be compared Accordingly, the measurements for connectivity are presented:

Agree Disagree

1. Contact has access to new contacts that contribute to the knowledge themes? 1 2 3 4 5 2. We need to “keep in touch” to obtain the new contacts? 1 2 3 4 5 If a company meets all requirements (no scores below 3) it is worth-wile to invest additional time in the network partner. Thus, firms need to pass all stages to be an attractive network partner for Information AM . If partners are not suitable for collaboration, they might still have or attract potential interesting contacts. In this case a firm meets the connectivity requirements. Information AM can decide to “stay in touch” in order to reach for new promising contacts. When connectivity requirements are met, a company is defined as a “Connector.”

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5. RESULTS: NETWORK PARTNER SELECTION

his chapter presents the internal and external results of the network partner selection research. The internal results reflect the innovative needs and the sample group that can potentially fulfill these needs. In the external results sample group parties are evaluated based on the dyadic partner selection framework that was presented in chapter 4. The outcome unveils new and interesting network opportunities for topics of Information AM.

5.1 INTERNAL RESULTS

5.1.1 INNOVATIVE NEEDS: BUSINESS OPPORTUNITIES FOR INFORMATION AM

Chapter 4 presented a framework for partner selection. Yet, it does not unveil the business opportunities that are of interest to Information AM. It only refers to “initiatives” that should meet criteria set by the managers of Information AM. Consequently, this paragraph lists the five innovative knowledge themes, enabling the managers of Information AM to identify if partners are currently complementary to their Business Unit.

In individual interviews the managers struggled to define the main business opportunities for Information AM. They found it difficult to define the future interests for the whole business unit. Instead, managers focused on their own interests, resulting in an extensive list of different knowledge themes (Appendix 5). The only clear agreement was the need to focus on tactical process improvements of the whole business unit. Therefore, a management meeting with seven managers was organized to individually select five topics, reflecting the most significant network benefits for Information AM (Appendix 6). In this meeting managers were also asked to consider the knowledge conditions of paragraph 1.5. The managers had to evaluate if (1) the knowledge for this opportunity is available at firms and (2) companies would be willing to share this knowledge. The final rank was made collectively: The management team evaluated the number of managers that selected a topic and the average priority that was assigned to each score (Appendix 7). Table 7 shows the five selected business opportunities: (1) Data quality, (2) Configuration Management, (3) Geo Information Systems, (4) 3D - Digitalization and (5) Information Management/Information Technology.

Table 7: Themes for knowledge sharing

T

Selected topics Rank* Average Priority score** S Selected by… managers Total priority score

Data quality 1 1,5 6/7 9

Configuration Management 2 1,33 3/7 4

Geo Information Systems 3 2 4/7 8

3D Digitalization 4 2,75 4/7 11

IM / IT 5 3 4/7 12

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The definition and main considerations of these topics are discussed in the following sub sections.

1. DATA QUALITY

Information AM manages a large variety of data and data systems in various departments. The managers of Information AM have little insights about data quality. More specifically, the management of Information AM aims to find a model that is appropriate to manage their data quality. This topic is tactical; it has impact on the business unit of Information AM. Research on data quality could also affect the strategy of Information AM. It aims to determine which level of enhancement is needed for the data quality of its system. Information AM desires to gain new data quality competences: New skills are needed to evaluate data quality of the current information systems.

Considerations

Many different companies could have access to data quality models. For instance, banks have necessity to control their data quality. Events are already organized for companies that focus on data quality. This implies that different companies might be willing to either share or develop a data quality model. Therefore, managers mentioned that “data quality” should be one of the main topics of a network meeting

2. CONFIGURATION MANAGEMENT

Configuration management refers to the configuration systems of Information AM. The configuration management systems contain information about al attributes at and around the railway tracks. The Management team is interested in the methods of configuration management implemented by other companies. In other words, the Management Team of Information AM prefers to benchmark the systems of external companies to search for tactical improvements.

Considerations

Companies that might fit the boundary conditions are likely to be in the Asset Management sector. As a result, other organizations such as consultancy companies are less relevant, This topic does not address “the creation of something new, which is often characteristic of innovation networks (Drejer, 2004). Nevertheless, exploration and idea generation of CM issues in the informal network might result in more specific innovation network topics that can be addressed in long-term meetings.

3. GEO INFORMATION SYSTEMS (GIS)

GIS enables the visualization of geo information on maps which facilitates by asset management employees. GIS includes the advice, execution, support and development of geographical information systems. Centrally, Information AM desires to increase the usage of GIS Information within their organization. This knowledge theme does not refer to technical specifications, but to the way people have embedded GIS in their organization and culture.

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Considerations

Companies that use Geo Information stages or implement GIS systems on a daily basis are most likely to contribute to this problem area. In the past, companies such as Staatsbosbeheer and Company H showed a lot of interest in sharing information about GIS and were also willing to share their information in the single meetings. This indicates that it is a potentially attractive topic for Information AM.

4. 3D- IMAGING

The last case includes 3D-Imaging. The Management team needs insights about implementing 3-D Imaging for Asset Management purposes. Recently, the Management Team of Information AM has proposed to implement 3D-Imaging to enhance maintenance information for railway stations. Yet, little knowledge is available about the applicability of this technology. The management team is in search for a process and technology that enhances the operational excellence of Company X.

Considerations

3-D Imaging is a relatively new concept for Asset Management. For now it is known to register visible (above-the-ground) assets on railway stations. Therefore, only companies with physical assets may contribute to this topic. Also, technology providing companies and universities may have access to this information. For Information AM this is an explorative topic; the usability of 3-D networking can be discussed in the informal network and its usability may be explored with other network partners.

5. INFORMATION MANAGEMENT / INFORMATION TECHNOLOGY ( IM/IT)

This topic reviews the dynamics between Information Management and Information Technology. It entails defining how other companies cope with the linkage between Information Management and Information Technology and how do they connect Information Management to their business. The issue is to de-bureaucratize the process of Information Management and IT.

Considerations

This topic may be applicable to a larger variety of companies. According to the management team, many companies should be willing to share this information with Information AM.

5.1.2 CRAFTING NETWORK GOALS FOR INFORMATION AM

The incentives for the innovation network at Information AM were determined in the network meeting. As a result the objective of the innovation network is: To learn from external companies in order to enhance the processes of Information AM contributing to life cycle costs and operational excellence of Company X. To enhance focus, complementarity will be determined by selecting network partners that are willing to contribute to the five most relevant knowledge topics of Information AM. At this moment, five knowledge themes have been identified, these are: (1) Data quality, (2) configuration management (3) GIS, (4) 3D-Imaging and (5) IM/IT. These

Networking in the Asset Management Industry

Networking in the Asset Management Industry

“Selecting partners for an innovation network at Company X”

Joyce Schellevis

Networking in the Asset Management Industry

“ Selecting partners for an innovation network at Company X”

TABLE OF CONTENTS

1. INTRODUCTION

2. INNOVATION NETWORKS

3. CRITERIA FOR NETWORK PARTNER SELECTION

4. METHODOLOGY

5. RESULTS: NETWORK PARTNER SELECTION

T