Strategic Alliance Formation in a Dynamic Environment
A Business Ecosystem perspective applied to Strategic Alliances in the Online Media Industry
ALEXANDER FAHNEHJELM ISABEL THOMANDER
KTH ROYAL INSTITUTE OF TECHNOLOGY
SCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT
www.kth.se
Strategic Alliance Formation in a Dynamic Environment
A Business Ecosystem perspective applied to Strategic Alliances in the Online Media Industry
by
Alexander Fahnehjelm Isabel Thomander
Master of Science Thesis TRITA-ITM-EX 2020:284 KTH Industrial Engineering and Management
Industrial Management
SE-100 44 STOCKHOLM
Formandet av strategiska allianser i en dynamisk miljö
Affärs-ekosystem applicerat på strategiska allianser i digitala medieindustrin
av
Alexander Fahnehjelm Isabel Thomander
Examensarbete TRITA-ITM-EX 2020:284 KTH Industriell teknik och management
Industriell ekonomi och organisation
SE-100 44 STOCKHOLM
Master of Science Thesis TRITA-ITM-EX 2020:284
Strategic Alliance Formation in a Dynamic Environment
A Business Ecosystem perspective applied to Strategic Alliances in the Online Media Industry
Alexander Fahnehjelm Isabel Thomander
Approved
2020-05-29
Examiner
Matti Kaulio
Supervisor
Jannis Angelis
Commissioner
Confidential
Contact person
Confidential
Abstract
The online media industry has undergone changes during the last decades. Driven by technology advancements, there has been an increasing number of actors that can enhance the value of services in the media industry. The fast changing environment calls for a dynamic lens when analyzing strategic alliances forming between actors in the industry, thus this study uses a Business Ecosystem perspective to analyze how alliances should be formed to enable competitive advantage. A case study was performed on a world leading provider of broadcast and media services to analyze how the dynamic setting affects suitable strategic alliance forms, using a partner selection framework to identify possible alliances. The results showed most potential within alliance forms of lower integration, such as a Franchise, Licensing Agreement or Arms-Length Market relation. Hurdles for the higher forms of integration were identified as mostly caused by requirements of low investments and implementation times in the fast moving dynamic environment. Identified future work is presented as performing a similar study where these hurdles are nonexistent to further analyze which alliance forms are applicable in a dynamic industry.
Key-words
Strategic Alliances, Business Ecosystem, Online Media Industry, Partner Selection Framework, Dynamic Alliance forms
Examensarbete TRITA-ITM-EX 2020:284
Formandet av strategiska allianser i en dynamisk miljö
Affärsekosystem applicerat på strategiska allianser i digitala medieindustrin
Alexander Fahnehjelm Isabel Thomander
Godkänt
2020-05-29
Examinator
Matti Kaulio
Handledare
Jannis Angelis
Uppdragsgivare
Konfidentiellt
Kontaktperson
Konfidentiellt
Sammanfattning
Den digitala medieindustrin har genomgått stora förändringar under de senaste årtionden.
Teknologisk utveckling har drivit upp antalet aktörer som kan öka värdet på tjänster inom medieindustrin. Den snabbt förändrande företagsmiljön möjliggör en applicering av ett dynamiskt perspektiv när formandet av strategiska allianser mellan aktörer i ekosystemet ska analyseras. Denna studie använder sig av ett perspektiv grundat i affärsekosystem för att analysera hur allianser bör formas för att uppnå konkurrensfördelar. En fallstudie genomfördes på ett världsledande massmedieföretag för att analysera hur den dynamiska miljön påverkar lämpliga alliansformer. Ett modifierat ramverk för att välja samarbetspartner används för att identifiera möjliga partnerföretag. Resultaten visar på högst potential inom alliansformer som innefattar en lägre integrationsnivå, såsom Franchise, Licensavtal eller Marknadstransaktioner. Hinder för att uppnå alliansformer med högre nivå av integration identifieras primärt som krav på låga investeringar och korta implementeringsfaser i den snabbt förändrande miljön. Framtida studier presenteras som genomförandet av en liknande fallstudie där dessa krav är icke-existerande, för att vidare analysera hur lämpliga alliansformer påverkas av en dynamisk företagsmiljö.
Nyckelord
Strategiska allianser, Affärsekosystem, Digitala medieindustrin, Ramverk allianspartner, Dynamiska alliansformer
Acknowledgements
This research was conducted as part of the authors’ education at Industrial Engineering and Management at the Royal Institute of Technology (KTH) in Stockholm. It was the final assignment of five years of studies and was conducted for the department of Industrial Engineering and Management. The research corresponded to 30 ECTS credits and was conducted during the spring semester 2020 from January to June.
A special thank you to the supervisor of the thesis, Jannis Angelis, for all his input to our work and for always being available for discussions. We would also like to thank the supervisor at the case company who has always helped us, has allocated a significant amount of time to support us and provided us with valuable feedback on our work throughout the study. A special thanks should also be given to all participants in this study for taking their time to contribute to our research. Finally, a special thanks to family and friends for your support and encouragement through this thesis.
Stockholm, May 2020
Alexander Fahnehjelm and Isabel Thomander
Table of Contents
Abstract 2
Acknowledgements 4
Table of Contents 5
Introduction 7
Background 7
Problematization 8
Research purpose and contribution 8
Research question 8
Delimitations 9
Literature Review 10
The business ecosystem perspective 10
The media industry as a business ecosystem 11
Complexity within the Business Ecosystems alliances 12
Strategic Alliances 13
Reasons to engage in alliances 13
Forms of alliances 14
Forms of alliances - from a business ecosystem perspective 16
Co-opetition within the media industry 17
Phases of strategic alliances 19
Partner Selection 21
Partner Selection Framework 22
Step 1: Align Corporate and Strategic Alliance Objectives 22 Step 2: Develop an appropriate set of Critical Success Factors 23 Step 3: Map Current and Potential Alliances on a Value Net 23 Step 4: Analyze Targets using Dynamic Alliance Selection Analysis Tool 24
Method 25
Research design 26
Research process 27
Step 1: Aligning Corporate and Strategic Alliance Objectives 29 Step 2: Developing an appropriate set of Critical Success Factors 30
Step 3: Mapping Current and Potential Alliances 30
Current alliances 30
Potential alliances 30
Step 4: Analyzing Targets using Dynamic Alliance Selection Analysis Tool 32
Data analysis 33
Quality of research 34
Internal validity 34
Construct validity 35
External validity 35
Reliability 35
Results 35
Objective alignment and Critical Success Factors 36
Mapping Current and Potential Alliances 37
Current actors of the ecosystem 37
Potential actors - industry level 38
Potential actors - company level 39
Analyzing Targets using Dynamic Alliance Selection Analysis Tool 42
Conclusion 50
Summary 50
Discussion 51
Contribution 57
Limitations & Further work 59
References 61
Appendix 64
1. Introduction
This section aims to provide a brief background to the research area of this study.
Furthermore, the problematization, research purpose and contribution and the research questions are presented.
1.1. Background
Throughout the last decades the media industry has transformed significantly and rapidly.
From the innovation of broadcast television in the 1950s’, it took 50 years for the television industries to start providing cable and satellite delivery. During these years most TV production companies also owned their means of distribution and presentation to the customer, meaning that a single actor was responsible for the whole content chain ranging from production to consumption (Gomery, 2001).
With the help of advancing technology, the 21st century has offered significant changes to the industry, including the ability to view media on-demand and watching content through different devices complementary to a television set, such as computers and telephones (Gomery, 2001). Another change in the industry brought by technology advancements is the increasing number of actors that can enhance the value of services in the media industry, and the strategic alliances that are formed between actors. A strategic alliance can be defined as an agreement between two firms who engage in business together beyond normal company-to- company dealings (Wheelen and Hunger, 2008) and operate together in order to reach strategic objectives that are mutually beneficial (Brucellaria, 1997). The old structure in the media industry where a single production company owns the entire value chain is gone - allowing for the entry of new actors such as broadcast networks and content providers, advertisers, content distributors, hardware manufacturers, audience measurement and ratings firms and regulators to name a few (Ansari et al., 2016). Many actors focus on enhancing content in different ways to enrich the end-user experience, and new actors come and go quickly with the development of new technologies.
In addition to actors entering and exiting the industry fast, the actors inside the industry often engage in complex strategic alliances where the definitive line between supplier and customer becomes blurred. Different services may be exchanged both ways between two actors, and actors may be competitors in some parts of the portfolio while simultaneously cooperating in other parts (Ansari et al., 2016). Due to this dynamic nature, a business ecosystem perspective has often been applied when researching this industry (Ansari et al., 2016; Chan-Olmsted, 1998; Daidj, 2011; Wauters and Raats, 2018). While having a complex definition, the business ecosystem can be described as a network of organizations where
competitors, collaborators and complementors affect each other’s landscape (Lewin, 1999) containing companies that co-evolve capabilities around new innovation, work cooperatively to support new products and to satisfy customer needs (Moore, 1993). Originating from the biological ecosystem, it’s a dynamic perspective of interdependence between actors where the actions of one will affect the others (Korpela et al., 2013).
1.2. Problematization
In the online media ecosystem existing actors often contribute value to the industry by engaging in different forms of strategic alliances with each other, with commitment levels ranging from Mergers & Acquisitions to Arms-length market relations. However, because of the dynamic context of actors entering and exiting the ecosystem, as well as the interconnectedness of actors, partnerships between actors and the process of entering new alliances may become very complex (Cummings and Holmberg, 2009). This may imply that some forms of strategic alliances may not be of relevance under certain conditions for firms within a business ecosystem.
1.3. Research purpose and contribution
The aim of this study is to investigate whether there are specific forms of strategic alliances that are appropriate when a firm’s environment is considered as a business ecosystem.
Through a case study, it will provide potential alliances, with possible suitable alliance forms, for a Metadata Service Provider within the Online Media ecosystem.
1.4. Research question
The main research question for this study is defined as:
RQ: How should strategic alliances be formed in the Online Media ecosystem to enable competitive advantage?
In order to answer the research question, a set of sub questions were identified. As a firm enters into a strategic alliance it is engaging with other actors in its vicinity. To evaluate whether a potential alliance could generate competitive advantages for the firm at hand, a set of criteria should be identified. The first subquestion addresses criteria from the firm as well as from an ecosystem perspective:
SQ1: What criteria should the alliances fulfill to provide competitive advantage?
Secondly, by considering the Online Media industry as a business ecosystem, there may be unique aspects to take into consideration when identifying alliances forms. The second sub question addresses forms of strategic alliances in terms of the business ecosystem:
SQ2: How does the ecosystem perspective affect new alliance formations?
1.5. Delimitations
This paper is scoped to focus on actors active in the US market - although actors may be global considering that online media is globally highly digitally connected. The offering range is focused on the Sports market, including live and non-live content. Although the business ecosystem allows for complex connections and partnerships between suppliers and customers, this paper focuses on expanding the supply side for strategic alliances. Client demand will be captured through the development of criteria for evaluating partnerships.
2. Literature Review
The literature review in this paper is made in three parts. First, current Business Ecosystem literature is discussed to build the ecosystem perspective used in this paper. This is followed by a summarized review on existing Strategic Alliance theory, with greater focus on the different stages of alliance formation and partner selection. This section also contains current theory researching the effects of applying the ecosystem perspective on strategic alliances. Lastly, a partner selection framework is presented and discussed.
2.1. The business ecosystem perspective
The concept of ecosystem originates from the field of biology and was introduced by Arthur Tansley (1935). It describes how a set of organisms compete and collaborate on resources, co- evolve and adapt to external changes. This concept was later incorporated into a strategic planning concept by James Moore who developed the idea of business ecosystems in an attempt to expand the focus from the company itself to the context it operates within. Unlike in biological ecosystems, Moore (1993) argues that business communities are social systems built upon people who make choices and the pattern of the system is maintained by a complex network of choices. The business ecosystem consists of companies that co-evolve capabilities around new innovation, who work cooperatively to support new products, satisfy customer needs and when needed incorporates new innovation.
As the concept of the business ecosystem has been widely accepted, there is an increasing body of research that has derived from this topic. Upon reviewing the literature, Jacobides, Cennamo & Gawer (2018), were able to identify three main categories of papers:
“innovation ecosystem”, “platform ecosystem” and “business ecosystem”. Studies within
“business ecosystem” are focused on the individual organization and the ecosystem is thought to consist of a collection of actors that have an effect on the organization’s customers and supplies (Teece, 2007). Relevant actors may be within the same industry, or belong to an adjacent one, and their activities all affect one another within this economic community (Jacobides et al., 2018). Lewin (1999) describe the business ecosystem as a network of organizations that reside in their own landscape, where each landscape is tied to others, where e.g. competitors, collaborators and complementors reside. Eventual changes in one landscape will cause a ripple through the entire business ecosystem, beginning with those landscapes closest to it. Similarly, Korpela et al. (2013) define the business ecosystem as a dynamic structure consisting of interconnected populations of organizations, where examples of
organizations would be research institutes, public sector organizations or other actors that exert influence on the ecosystem.
The three categories of ecosystems have slight differences in the focal point of the concept, however they show similarities in the surrounding features. No matter if the focal point is a specific innovation, platform or organization, it is acknowledged that the ecosystem consists of a collection of actors that are interdependent and where the actions of one will affect the others.
Along the lines of interconnectedness, Gobble (2015) argues that a company can belong to several ecosystems at once, and that these ecosystems may also belong to different categories. An example given to strengthen this case is that of Apple. Apple can be considered to be a part of the Silicon Valley innovation ecosystem while at the same time being a central part of its own platform ecosystem. No matter which category the ecosystem belongs to, having an awareness of the ecosystem the company resides in can lead to opportunities for growth for the company itself as well as the surrounding entities. Furthermore, Cusumano and Gawer (2014) describe how different platform ecosystems can be intertwined. A combination of several technical platforms would be the microprocessors embedded in computers or smartphones that all use the Internet where Google and Facebook exist on top of which applications function. As such, a company may reside in several ecosystems at once while also being closely tied to other ecosystems. A similar notion is present in the literature related to business ecosystems, which is for example is apparent in the definition of business ecosystem by Lewin (1999) mentioned earlier.
Furthermore, all categories mention the presence of a central node, termed ecosystem leader (Moore, 1993), platform leader (Evens, 2014a; Gawer and Cusumano, 2014), “hub”
(Gobble, 2015) or “keystone” (Iansiti and Levien, 2004). Iansiti & Levien use an analogy from the biological ecosystem to express the nature of the keystone: “Removal of biological keystones can have dramatic cascading effects through the entire ecosystem, while removal of other species, even species involved in many interactions, can have little effect beyond the loss of those connections”. It becomes quite clear that the keystone has a high importance in the business ecosystem. They argue that this player provides the ecosystem with stability.
Furthermore, they identify two other roles “dominator” and “niche player”, followed by a framework for innovation and operations strategy adapted to each role respectively.
2.1.1. The media industry as a business ecosystem
Media has been in the focus of networking or business ecosystems research. Colapinto (2010) examined how an Italian media incumbent, Mediaset Group experimented with its revenue model, the industry value chain, as well as the use of partnerships and acquisitions. Mediaset successfully adapted to the shifts in TV consumption patterns by following a networking logic
which involved finance, production, advertising and politics - with close relationships with broadcasters and content producers. Similarly, Evens (2014b) covers how TV broadcasters have implemented co-operation practices and business ecosystems in the online video market.
He argues that TV broadcasters are the keystones of the ecosystem, who cooperate with their competitors in a global online video marketplace.
While the aforementioned research focuses on incumbent TV broadcasters, Ansari et al. (2016) take the view of a disrupter entering an existing business ecosystem. The case study follows how TiVo navigated through the dilemma of gaining support from the current actors within the US television industry ecosystem. The study provides several examples of how TiVo’s alliances with its partners dynamically changes over time, both addressing new alliances that are formed but also how existing relationships change back and forth between cooperative to competitive.
The audio-visual media ecosystem stretches beyond broadcasters and distributors. It consists of companies that contribute both directly and indirectly to the creation of and investments in audio-visual and digital content services (Wauters and Raats, 2018). Examples of such companies would be public service broadcasters, distributors, content creators, print, online etc. in combination with companies within wider industries such as e-commerce, media-tech and internet services.
2.1.2. Complexity within the Business Ecosystems alliances
Within the online media industry, alliances are often diverse and complex and connections arise from different parts within the ecosystem (Ansari et al., 2016; Wauters and Raats, 2018).
Depending on the level of market disruption, alliances can also change substantially over time.
Dynamic tensions exist throughout the ecosystem, and the emergence of a disrupting actor may induce rapid changes for alliances not only between existing and new actors, but also in between incumbents (Ansari et al., 2016).
Gobble (2015) argues that although some researchers can use some of the terms of networks, cluster and ecosystems interchangeably, they have different implications. She suggests that while networks and clusters are constructed, they are not as complex as an ecosystem. Interaction and communication between parties occurs along definable lines and it is relatively clear how one action will affect conditions elsewhere. For ecosystems however, a greater complexity lies in the constantly adapting and evolving nature of a dynamic nature.
Evens (2014b) differentiates the business ecosystem from the value network by arguing that theory related to the former has a more holistic approach while the latter is focused on a network of strategic partners and allies to determine firm performance. The business ecosystem then refers not only to the close business partners, but also competitors, regulators, research institutions, etc.
Jacobides, Cennamo & Gawer (2018, p. 2264) sets the business ecosystem apart from the supply chain through their definition of an ecosystem as: “ a set of actors with varying degrees of multilateral, nongeneric complementarities that are not fully hierarchically controlled.”. In other words, the ecosystem consists of actors who offer complementary innovations, products and services and who are interdependent, although not necessarily bound by contractual agreements.
To allow for the dynamic characteristics of the ecosystem, this paper applies a Business Ecosystem perspective when analyzing the Strategic Alliances in the Online Media Ecosystem.
2.2. Strategic Alliances
Given the extensive amount of research on the topic of strategic alliances, there exists a wide array of definitions. Wheelen & Hungar (2000) provide a general definition, suggesting that a strategic alliance is an agreement between two firms who engage in business together in a way that stretches beyond normal company-to-company dealings, although not as integrated as in the case of a merger. It gives a faint idea of the nature of an alliance, however there is still much room for interpretation. Brucellaria (1997) adds a motivational aspect by describing strategic alliances as firms operating together in order to reach strategic objectives that are mutually beneficial. A definition offered by Yoshino & Rangan (1995) gives an even more detailed account; “A strategic alliance involves at least two partner firms that: (1) remain legally independent after the alliance is formed; (2) share benefits and managerial control over the performance of assigned tasks; and (3) make continuing contributions in one or more strategic areas”. These definitions accentuate different dimensions of an alliance. An alliance can involve varying numbers of partners, be formed for various reasons and may take different forms.
2.2.1. Reasons to engage in alliances
Upon entering into an alliance, the firms in question are acting with a strategic intent with the final objective to improve future circumstances for the parties involved. The underlying reasons for the individual firm to initiate a partnership may be to seek new markets, gaining access to technology, obtaining economies of scale, achieving vertical integration, diversifying into new businesses, cost sharing, product development, achieving competitive advantage, complementarity of goods and services to markets, pre-emptying competition, to name a few (Todeva and Knoke, 2005) . Elmuti & Kathawala (2001) identified five main reasons for why firms form strategic alliances:
1) Growth strategies and entering new markets. Due to the increasing globalization and fast-paced technological advancements, new markets are constantly presenting
themselves to the firm. However, there may be several constraints in place, such as time or resources, that hinder the firm from entering these markets. A possible solution would therefore be to form an alliance with an existing firm in the desired market.
2) Obtain new technology and/or best quality or cheapest cost. Being able to offer top of the line technology requires financial resources, technical know-how and skilled labour. By partnering with a company that has access to these resources, the firm will be able to compete effectively in their markets.
3) Outsource business functions. By successfully outsourcing business functions such as marketing, production, accounting, or sales, the firm can focus on its core competencies while at the same time enjoying better and cheaper operations.
4) Reduce financial risk and share costs of research and development. In the case that the development of a new product, or changes in manufacturing methods, are deemed too risky for one firm to manage, entering into an alliance is a method of mitigating the risk.
5) Achieve or ensure competitive advantage. For smaller firms, especially, alliances provide an ability to gain competitive advantage by tapping into an increased pool of resources.
Research has shown that alliance arrangements change over time in relation to the industry life cycle (Rice and Galvin, 2006). From the early phases of the industry life cycle to the latter, firms tend to move from alliances aimed at facilitating technological innovations toward those aimed at creating diversified product offerings (Hagedoorn, 1993). Furthermore, during the early phases firms are interested in mitigating risk through risk sharing and knowledge acquisition (Rice and Galvin, 2006). As the industry consolidates, alliances focus less on mitigating risks and more on operational efficiency and competence leveraging. During the later phases, products and technologies mature and alliances work to facilitate technological innovations by sharing information and innovation in regards to new products.
2.2.2. Forms of alliances
The term strategic alliance refers to different types of collaborations and covers a range of arrangements with a varying degree of integration. They can be grouped together based on business functions: joint marketing/promotion, joint selling or distribution, production, design collaboration, technology licensing, research and development contracts and other outsourcing purposes (Elmuti and Kathawala, 2001). An alliance may be a crossover of one or more of these types, and may take different forms. Based on a review of research on strategic alliances, Todeva and Knoke (2005), identified thirteen forms of relationships between firms presented in Table 1.
Form Description
JOINT HIERARCHICAL
RELATIONS Through acquisition or merger, one firm takes full control of another’s assets and coordinates actions by the ownership rights mechanism VENTURES Two or more firms create a jointly owned legal organization that serves
a limited purpose for its parents, such as R&D or marketing
EQUITY INVESTMENTS A majority or minority equity holding by one firm through a direct stock purchase of shares in another firm
COOPERATIVES A coalition of small enterprises that combine, coordinate, and manage their collective resources
R&D CONSORTIA Inter-firm agreements for research and development collaboration, typically formed in fast-changing technological fields
STRATEGIC COOPERATIVE
AGREEMENTS Contractual business networks based on joint multi-party strategic control, with the partners collaborating over key strategic decisions and sharing responsibilities for performance outcomes
CARTELS Large corporations collude to constrain competition by cooperatively controlling production and/or prices within a specific industry FRANCHISING A franchiser grants a franchisee the use of a brand-name identity
within a geographic area, but retains control over pricing, marketing, and standardized service norms
LICENSING One company grants another the right to use patented technologies or production processes in return for royalties and fees
SUBCONTRACTOR NETWORKS Inter-linked firms where a subcontractor negotiates its suppliers’ long- term prices, production runs, and delivery schedules
INDUSTRY STANDARDS GROUPS Committees that seek the member organizations’ agreements on the adoption of technical standards for manufacturing and trade
ACTION SETS Short-lived organizational coalitions whose members coordinate their lobbying efforts to influence public policy making
MARKET RELATIONS Arm’s-length transactions between organizations coordinated only through the price mechanism
Table 1. The table displays different forms of strategic alliances along with a description for every form.
The forms are organized in such a way that the level of integration as well as formalization in governance increases from bottom up. Governance in this case refers to the
“combinations of legal and social control mechanisms for coordinating and safeguarding the alliance partners’ resource contributions, administrative responsibilities, and division of rewards from their joint activities” (Todeva and Knoke, 2005, p. 2). The forms that reside in the lower end of the table require lower levels of integration, and interaction between the partnering firms. These are so-called nonstructural alliances in the forms of marketing agreements, licensing, joint ventures, and partial equity. These types were often seen in major global telecommunication in the end of the 90’s and contributed to the shaping of competition
in the market (Chan-Olmsted and Jamison, 2001). There can be little cooperation, coordination or collaboration in these cases. This in contrast to the forms that are depicted in the top of Table 1, where the highest level of integration is displayed by one firm fully taking over the other and as a result assimilating that firm’s assets. Such structural alliances include mergers, acquisitions and the friendlier version consolidation - a type of cooperative deal (Chan-Olmsted and Jamison, 2001). However, these are the two extreme points of the scale and there are many forms in between, so called “hybrids” (Todeva and Knoke, 2005).
The form a company decides upon may be shaped by both internal factors, limited to the individual company, and external factors. For instance, firms are more willing to enter alliances regarding peripheral activities as opposed to core functions (Lorange and Roos, 1993). Through joint ownership, large firms have been able to restructure poorly performing business segments by letting the dominant firm in the partnership alter peripheral activities.
According to Todeva and Knoke (2005) the form is affected by general economic conditions as well as the institutional frameworks such as legal requirements, macro-economic policies, methods of contract enforcements etc, which are unique to the respective country. The government can also affect the firm’s freedom to form coalitions and joint ventures.
During the 20th century the media industry was heavily regulated by the government.
However, by the end of the 20th century, the market became increasingly deregulated. In the US, the 1996 deregulation led to a convergence between broadcasting, cable television, and telephone companies (Chan-Olmsted, 1998). In such an early stage of convergence, there was a need to quickly integrate different communications segments, attain a developed customer base, and accelerate the implementation of new technologies. Strategic alliances through M&A’s became an effective tool under these circumstances, where time is of the essence.
2.2.3. Forms of alliances - from a business ecosystem perspective
Psyka (2002) argues that there are three factors that affect firms in such a way that drives them toward network aggregation, which can be seen as a precursor to formalized knowledge alliances. These factors are technological uncertainty, technological opportunity and spill-over appropriability. The linkage between alliance formation and technological emergence makes it highly relevant to study an industry marked by changing and emerging technology such as the media industry (Rice and Galvin, 2006). Furthermore, it strengthens the case of investigating the network natured business ecosystem in combination with alliances.
Applying the Business Ecosystem perspective to the literature of Strategic Alliances yields some similarities and contrasts. The network structure of a business ecosystem allows for actors to compete and collaborate simultaneously; i.e. engaging in ‘co-opetition’ which is often considered as an extension of cooperation between companies in Strategic Alliance theory (Daidj, 2011). Brought into the theory of ecosystems, the term co-opetition can be
described as firms working co-operatively and competitively to develop innovative technology, launch new products and satisfy customer needs (Moore, 1993). Bengtsson and Kock (2000) describe co-opetition as ‘the dyadic and paradoxical relationship that emerges when two firms cooperate in some activities, such as in a strategic alliance, and at the same time compete with each other in other activities’. Several positive effects have been noted in the research of these alliances, pointing to positive effect on general industry profit levels when engaging in horizontal joint ventures (Tong and Reuer, 2010), reduced financial and operational risks, reduced time to market and decreased cost of collaborated product development (Fjeldstad et al., 2012), and greater access to new markets and technologies (Horvath, 2001). Even though research to date has yet to investigate co-opetition profitability specifically within the media industry, “co-opetition seems one of the dominant strategies to build and sustain competitive advantage in the online video ecosystem these days” (Evens, 2014b).
Aligning with the biological origin of the term business ecosystems, the theory of alliances within business ecosystems has also inherited some of the biological terminology. In their Narrative Literature Review of the business ecosystem literature, Hakala et al. provide an extensive summary of types of relationships that have been noted throughout the literature (2019). Symbiotic relationships are regarded as mutually beneficial relationships (++). The results of these relationships is a win–win situation for all parties concerned (Bititci et al., 2004). Agonistic relationships are also broadly recognized by the business ecosystem literature, where one party benefits and the other party suffers from the relationship. These win-lose relationships can be further divided into predatory and parasitic relationships, where the predator-prey metaphor is the most commonly used in business ecosystems to describe co-evolving relationships (Moore, 1993). Hakala et al. do differentiate business agonistic relationships (+-) from biological competitive relationships (--) “in which both parties suffer due to competition over the same resources” (2019). Within entrepreneurial ecosystems, Hakala et al. describes the idea of commensalistic (+0) relationships, in which one firm benefits without harming the other. They suggest linking to theory on industrial clusters, defined as “geographically proximate groups of interconnected companies and associated institutions in a particular field, linked by commonalities and complementarities” (Porter, 2000). Smaller firms in the cluster can often be seen benefiting from existing in the same cluster as leading firms, without the leading firms being affected by the smaller firms.
2.2.3.1. Co-opetition within the media industry
The nature of co-opetition makes it highly suitable in industries which possess short product cycles, a high level of technical convergence and high R&D costs - which makes the ICT ecosystem a suitable setting (Basole et al., 2014). Applied to the Media Industry, Ansari et al.
use an extensive case study on the DVR (Digital Video Recorder) provider TiVo and its
disruption of the US Media market during the early 2000’s (2016). From the study, three different types of co-opetition are theorized: dyadic, intertemporal and multilateral.
Dyadic co-opetition is described as the basic form of co-opetition, where the competitive firms are cooperating without any other stakeholders involved in the relationship.
Ansari et al. exemplify this type of relationship by a data gathering collaboration between TiVo and Nielsen (a US information, data and analytics firm). Nielsen had good coverage of viewer data from live broadcasting, but partnered with TiVo to be able to measure data from recorded viewing as well.
Intertemporal co-opetition mostly applies to discrepancies in the market.
Intertemporal co-opetition may arise when a new actor in the ecosystem brings an innovative technology to the ecosystem, initially disrupting the ecosystem and not benefiting incumbent actors until at a later stage. TiVo experienced this as their emerging technology was mainly perceived as a disrupting threat, whereas the benefits were uncertain and would be realized only in the future.
Multilateral co-opetition is defined as setting up alliances within a cluster of several actors, allowing cooperation to span across multiple dyads or ecosystem sides. In 2004, TiVo and Netflix engaged in a joint development of a TiVo service, the ability for TiVo-users to download Netflix-available movies from the internet. This collaboration also engaged the content-provider side of the ecosystem who were concerned about inadequate mechanisms in place to prevent piracy of their content. Ultimately this resulted in the content-providers refusing to license their content for this service for four years until better mechanisms were in place (Ansari et al., 2016).
The ICT ecosystem (consisting of the segments: media, hardware component, hardware equipment, software and telecommunications) has seen a tremendous transformation since the turn of the millenium, with coopetition becoming more prevalent.
Apart from the Telecommunications act in 1996 mentioned previously, there have been fast technological advancements and changes in consumer behaviours along with changes in economic conditions. As a result, the ICT ecosystem is a highly dynamic and competitive business environment (Basole et al., 2014). In the beginning the ecosystem was characterized by convergence, however the segment convergence is now decreasing which suggests that the ecosystem is reaching higher levels of maturity. Instead, co-opetition is becoming increasingly prevalent. The most occuring alliance forms have also changed in accordance with the ecosystem lifecycle. During the early phases R&D, marketing and joint-venture alliances were dominant, while the later phases exhibit a growth in technology-transfer and non-equity relationships with a shift towards more informal interfirm relationships (ibid). Basole et al (ibid) argue that this indicates a shift from value exploration to value capturing, that firms are focusing on knowledge exchange rather than sharing resources and reducing risks.
2.2.4. Phases of strategic alliances
The process of entering and maintaining a strategic alliance has been discussed thoroughly in literature. While the different stages of the process varies somewhat in the discussions, it is defined as a consistent process. Kinderis and Jucevičius (2013) provide a review of five methods based on Lewis (1990), Keen and Mac Donald (2000), Kuglin (2002), Mitsuhashi (2002), and Whipple and Frankel (1998). Kinderis and Jucevičius combine these five methods and conclude that the four most important and most frequently mentioned stages of the process is the Formation of the alliance (the selection of partners and estimation of the future benefit), the Design of the alliance, Management (rules and trust) and the Management of the formed alliance. These stages are also mentioned as the alliance life-cycle phases, further detailed into a three stage framework presented in Table 2 (Prashant and Harbir, 2009;
Sambasivan and Nget Yen, 2010).
1. Alliance Planning, Selection of Partners and Negotiation
Partners’ complementarities Compatibility of partners Obligation of partners
2. Alliance formation and management of relations
Property Capital sharing Contractual provisions Management of relations
3. Management of formed alliance and assessment
Coordination mechanism, evaluation of relations
Development of trust relations Dealing with conflicts and escalation
Table 2. A combined three-stage framework for entering in a new alliance (Kinderis and Jucevičius, 2013).
Another combination of methods has been made by Das and Tang (2002) who analyze methods provided by Brouthers et al. (1997), Das and Teng (1997), D’Aunno and Zuckman (1987), Kanter (1984), Ring and Van der Ven (1994) and Spekman et al. (1996). From these methods, three major stages of the process are derived, which closely tangents the conclusion made by Kinderis and Jucevičius:
1. Formation - An alliance strategy is formulated, partners identified, deals are negotiated and the alliance is set up
2. Operation - Partners start to operate the alliance and implement the agreement 3. Outcome - Results are obtained and evaluated and the alliance either stabilizes or continues to change and reform
These stages and which steps the analyzed methods use in each stage is presented in Table 3.
Models in the literature Model Summary
1. Formation 2. Operation 3. Outcome
Brouthers et al. (1997) ● Selecting mode of operation
● Locating partners
● Negotiation
● Setting up the alliance
● Managing the
alliance ● Evaluating performance
Das and Teng (1997) ● Choosing an alliance strategy
● Selecting partners
● Negotiation
● Setting up the alliance
● Operation ● Evaluation
● Modification
D’ Aunno and
Zuckman (1987) ● Emergence of a coalition ● Transition to a
coalition ● Maturity
● Crossroads Kanter (1994) ● Selection and courtship
● Getting engaged
● Setting up housekeeping
● Learning to
collaborate ● Changing within
Ring and Van de Ven
(1994) ● Negotiation
● Commitment ● Execution ● Assessment
Spekman et al. (1996) ● Anticipation
● Engagement
● Valuation
● Coordination
● Investment ● Stabilization
● Decision
Table 3. A review of partner selection models in the strategic alliance literature made by Das and Tang (2002). The three derived stages, Formation, Operation and Outcome are presented as headers in the categorical columns.
Das and Tang also highlight some overlapping characteristics of the stages, such as that an alliance may start to operate before formal agreements are fully developed (2002). They do, however, underline the life-cycle perspective that an alliance goes through noticeable stages throughout its operational life.
This paper researches the question of how new partnerships should be formed. Thus, the first Formation stage (and especially the Partner Selection part/step/process), is applicable to analyze deeper. The latter two, the operational and evaluational stages, will be excluded from this paper.
2.2.5. Partner Selection
Partnership selection is one of the most important steps in creating a successful alliance, and can likely be one of the most intensive steps (Elmuti and Kathawala, 2001). The individual partner selection and the setting of the “rules” of the specific alliance. However, when done extensively they help to ensure a higher quality on the alliance and promotes a longer lasting relationship (Elmuti and Kathawala, 2001).
During the partner selection process, Kinderis and Jucevičius (2013) identify three main factors that influence the alliance formation positively: partners’ complementarities, compatibility and suitability of partners.
● Partners’ complementarities are defined as the ability to combine exclusive resources and create value. The stronger the partners’ complementarities, the higher chance for success.
● Partners’ compatibility is expressed as the harmony of working styles, similarities in culture and work ethic as well as support to partners. A greater compatibility aids profitability and helps to achieve the long-term goals of the alliance.
● Partners’ obligations are explained as the commitment level of both parties. This includes sufficient resource allocation in accordance with the agreement and clear communication channels to aid the success of the alliance.
Kinderis and Jucevičius (2013) highlight that while all mentioned factors are important for alliance success, partner’s complementarities are distinguished as the most important one.
They are very efficient when one of the parties is younger and has less experience than the other. However, future expectations from the alliance may be hard to define.
Complementarities often mean a higher level of interdependence between partners which helps to manage the alliance efficiently (Kinderis and Jucevičius, 2013).
A partner selection sets the foundation to the strategic alliance. The initial agreement should be structured so that similar goals can be reflected between the two parties, opening the possibility of success for the alliance. An example where similar goals were not clearly structured and things went wrong is highlighted by Bierly and Gallagher (2007), who describes the rash alliance entering between Toys R Us and Amazon in 2000. The time to form the alliance was limited due to Christmas peak demand coming up. The two companies were a great strategic fit, but had different visions of what it meant to be the ‘best’ toy store. “Amazon envisioned leading the industry by having as many products as possible available, ie ‘a selection competitive advantage’; while Toys R Us envisioned always having the most popular toys available and in stock for customers, ie ‘an availability competitive advantage.”
(Bierly and Gallagher, 2007). This divergence of visions, however, was not noted since the two companies had a great deal of trust to each other and “never once needed to refer to the contract”.
2.3. Partner Selection Framework
An extensive framework for the final candidate selection process is defined by Cummings and Holmberg who developed a framework including dynamic partner considerations (2009).
Prior research regarding alliance partner selection focuses predominantly on static alliance partner selection analysis. Their framework adds a dynamic perspective to alliance partner selection to hedge for success factors changing over time, which is the case for many alliances (Cummings and Holmberg, 2012). In their weighted decision matrix, by adding weights not only to CSF’s but also to a Time Importance, they allow for incorporation of the many dynamic changes likely to affect any partnership over time. Cummings and Holmberg also highlight that the specific criteria to be assessed by a focal firm will change in importance and relevance depending on the firm’s own dynamic context, but that their analytical methodology can be applied flexibly across a range of situations. This dynamic consideration would thus make the framework applicable to apply with the complex business ecosystem perspective. The four- step process is defined as:
Step 1: Align Corporate and Strategic Alliance Objectives Step 2: Develop an appropriate set of Critical Success Factors Step 3: Map Current and Potential Alliances on a Value Net
Step 4: Analyze Targets using Dynamic Alliance Selection Analysis Tool
A snapshot of their framework is presented in Figure 1 and the steps are further detailed below.
Step 1: Align Corporate and Strategic Alliance Objectives
Cummings and Holmberg (2009) agree with points previously made by Elmuti & Kathawala (2001) and Bierly & Gallagher (2007) that alignment of objectives is an important and often overlooked step in the process of forming alliances. They also highlight that ‘firms facing dynamic external and/or internal environments have an even greater need to align their corporate and strategic alliance objectives systematically’. Leaving these strategic alignments unconsidered until after the formation of the alliance ‘increases the risk of alliance issues becoming intertwined with individual managers' personal career implications and internal political agendas, rather than following the broader objectives of the firm’. As is mentioned in 2.2.1 Motivational objectives, there are numerous reasons why firms enter into an alliance, with strategies ranging from new market entry or accessing technology to outsourcing business functions.
Cummings and Holmberg underline the undeniably important fact that aligning corporate and alliance strategic objectives is not easy (2009). However, the early attending of these matters may lead to a better alliance formation outcome.
Step 2: Develop an appropriate set of Critical Success Factors
In the subsequent step, the firm should derive a list of critical success factors (CSFs) from the strategic alliance objectives identified by the firm. These CSFs are certain activities that the firm must perform well to gain competitive advantage. As a result, the firm strategy, project needs along with industry and technology environments are included in the decision process - all of which are essential to the alliance analysis (Cummings and Holmberg, 2009).
Cummings and Holmberg give the example of a firm wanting to enter a new foreign market. There are numerous challenges a firm will face upon market entry, which may be refuted with the correct measures. Successful measure in this case could entail building a local brand, distribution channel sophistication, developing customer knowledge, to name a few. If the firm cannot achieve this alone, it may search for potential partners and evaluate them against these CSFs. This step of the framework corresponds well with the first sub-research question of this study, “SQ1: What criteria should the alliances fulfill to provide competitive advantage?”.
Step 3: Map Current and Potential Alliances on a Value Net
Once the strategic objectives along with the derived CSFs have been identified, Cummings and Holmberg (2009) argue that firms tend to have a narrow focus in terms of potential partners.
In the process they often overlook the plethora of possible players active in the same or similar industries. As such, firms are encouraged to conduct an analysis on the “macro level and include industry groups and segments most closely connected to the firm’s broader goals and objectives”. The authors apply the ‘value net’ framework proposed by Brandenburger and Nalebuff (2011), where the participants are classified into suppliers, customers, competitors and complementors - including current att potential alliance partners. The framework helps firms identify which value creation strategies are linked to which participant of the value net.
For example, if a firm has a strategy focused on reducing input costs it is likely that it would have close collaboration with suppliers.
The value net captures certain nuances of the firm’s environment. It allows for inclusion of not only the current, but also the future players that could create value for the firm. Furthermore, it allows participants to occupy one or more roles in the net value. A participant could be both a customer and a competitor for the focal firm. Lastly, potential alliances are included to illustrate the constellations of alliances across industry groups.
Research has shown that some industries contain alliances with one firm at the strategic
centre, catering for various functions in the net (Lorenzoni and Baden-Fuller, 1997). In such cases it is important to identify the participants in the respective segments.
One of the main reasons for utilizing the value net in this step is to better understand the firm’s environment, the occupants within it as well as the relationship among the occupants. For the same reason, a business ecosystem perspective would facilitate this step of the process. Both perspectives show a broad range in terms of inclusion criteria as both the obvious, current actors should be included as well as the more unexpected firms in the periphery. Furthermore, both recognize the concept of one firm acting as a central node in the environment, carrying great importance for other actors. Similarly to the value net, the ecosystem captures the ability for an occupant to have one or more roles. In the value net the actors are categorized into roles that describe them in relation to the focal firm. In the business ecosystem the actors are described as species, and they are grouped together based on their characteristics. However, the latter perspective extends the notion of different roles by adding a new layer of complexity. A specific firm may participate in one or more ecosystems at once, and may serve different roles in the different ecosystems. As such, the ecosystem perspective captures the dynamic nature of the firm environment. Which is important to consider in an industry centered around technology, with inherent fast-paced development. In contrast, the value net has greater emphasis on alliances to determine firm performance (Evens, 2014a).
Given that the similarities outweigh the differences and with the main purpose of the two perspectives overlapping, mapping the actors from a the business ecosystem perspective may be a beneficial substitute to a value net in a dynamic context. . After the industry groups and the most attractive segments within them have been identified, it is time to conduct evaluation at a firm-level.
Step 4: Analyze Targets using Dynamic Alliance Selection Analysis Tool
The purpose of the fourth and final step is to evaluate the potential of various targets using a dynamic partner selection analysis tool. To identify potential new alliance opportunities, an evaluation must be performed to assess how well a partner might help or hinder the focal firm in achieving its strategic objectives. For this evaluation to be made accurately, the CSF’s defined in Step 2 should be weighted with relative importance across two time factors (Current and Future importance). The calculated weighted average scores of the individual potential new partners can then be measured against each other to provide basis of which potential partner has the overall best fit for the formation of a new alliance, both in short-term and long- term perspectives with the help of the time factor.
Each CSF is answered by assigning a rating of 1-10 depending on how well the CSF fulfilled the criteria for each potential partner. This rating process is described by Cummings and Holmberg as part of developing an understanding of how well a partner might support the
focal firm's CSFs, which they state is not an easy process (Cummings and Holmberg, 2009).
They state that the better results are achieved by not solely focusing on the precise numbers entered, but by using this matrix as an indication to drive discussions that expose underlying assumptions and firm-specific experiences.
Figure 1. Example of conducting a Dynamic Partner Selection Analysis (Cummings and Holmberg, 2009). *Weighted average of current weights × ratings. **Weighted average of future weights x ratings. ***Current time weight × current overall fit rating + future time weight × future overall fit rating for each segment.
This concludes the literature review, and the framework provided by Cummings and Holmberg is brought into section 3. Method of this research for further usage in this study.
3. Method
This section presents the research design of this case study, together with the research process, the 4-step framework used and how the quality of research is maintained in this study.
3.1. Research design
The thesis aims to investigate appropriate strategic alliance forms in a business ecosystem. To increase the obtainability of data and to enable deeper research within one part of the ecosystem, a case study approach was used to answer the research question (Harrison et al., 2017). The case study methodology is suitable when exploring a single phenomenon in a natural setting (Collis and Hussey, 2013). This approach is used when the topic of interest has many more variables than data points, there are multiple sources of evidence and which benefits from prior theoretical advancements for guidance in data collection and analysis (Yin, 2009). Furthermore, it is useful when the researchers have a low level of control of the context, and when the main research question begins with “how” or “why” (Yin, 2014). As such, an explorative approach is taken.
The context is essential for a case study, and it can be studied from the point of a business, a group of workers, an event etc (Collis and Hussey, 2013). In an opportunist case study, an opportunity can arise as the researcher gains access to a particular business or person (ibid). In such studies, the basis can consist of a single case. As such, this study was an opportunist case study, performed on a world leading provider of broadcast and media services, hereinafter referred to as the Company. This case study was performed within a specific part of the portfolio, hereinafter referred to as BA1 (Business Area 1), which focuses on surrounding metadata to enrich online media content and allow for significant enhancements of the end user experience.
A case study explores social phenomena and in this type of method the researcher is interacting with the context which he or she is investigating. This method falls under the interpretivist paradigm and during such circumstances qualitative approaches are appropriate (Collis and Hussey, 2013). Qualitative data is understood within a distinct context which implies that an understanding of the context is required before data collection begins, i.e.
contextualization (ibid). Therefore, this study began with contextualization measures. The study used a natural sampling method for the interviews conducted with representatives from the Company, meaning only particular employees involved in the phenomenon being researched was included (ibid). A screening sampling method was employed during the identification of potential partnering companies. Such sampling methods are appropriate for
studies conducted under the interpretivist paradigm, when the results are not to be generalized across a population meaning random sampling is not required (ibid). Data collection was conducted through qualitative methods such as a literature review and unstructured or semi-structured interviews. In the early stages the interviews were unstructured in order to explore the issues and subject fields (Blomkvist and Hallin, 2015).
Later in the study, when the purpose was established together with the final research questions, the interviews mostly had a semi-structured layout in order to gather more specific information. It is important to note that the results of this thesis are influenced by the collection of qualitative data.
3.2. Research process
In this section, the overall process and timeline of the research is presented.
During the study, several interviews were held with different interviewees from the case study company as well as from potential partner companies, displayed in Table 4. The interviews were conducted between January 2020 and May 2020. During the problematization phase the interviews were conducted face-to-face. During the remaining part of the study the interviews were conducted via different video conferencing technologies as a result of geographical and health-related limitations of the COVID-19 situation during this time period.
3.2.1. Contextualizing phase
The first phase of the research was dedicated to understanding the industry, the underlying problem for the case company and to formulate the research questions. The contextualizing data is found in the literature as well as from initial interviews. The first weeks of the study were used to define the problem and to get an understanding of the company, its various portfolios and industry positions. To gain this insight, several unstructured interviews were conducted with employees and managers in different parts of the organization. Internal documentation was consulted to attain an understanding of the current situation and context prior to commencing the study of identifying potential partnerships.
3.2.2. Partner Selection
The partner selection phase of this study was conducted using Cummings and Holmberg’s four-step framework as a baseline as it provides an additional dynamic perspective discussed in the literature review, applicable in the business ecosystem. The different data collection methods used are described for each step as the data required differed for each step. The first step was to define strategic goals and objectives for the Company to understand why the alliance is needed and what it should achieve (2009). Secondly the CSFs against which the
Phase? Interviewee Purpose of interview Structure Channel
Contextua lizing phase
Head of BA1 Define potential research areas Unstructured Telephone Head of BA1 Introduction to the company 1/2 Unstructured Office Head of BA1 Introduction to the company 2/2 Unstructured Office Product Mgr.
BA1
Introduction BA1 product portfolio Unstructured Video Conference
Sales Rep. BA1 Introduction BA1 US product portfolio Unstructured Video Conference
Step 1
Head of BA1 Identify Corporate Strategic Objectives Unstructured Video Conference Head of BA1 Clarify Corporate Strategic Objectives Semi- Structured Video Conference Step 2 Head of BA1 Identify Strategic Alliance Objectives Semi- Structured Video Conference
Step 3
Head of BA1 Map Current Alliances Semi- Structured Video Conference Product Mgr
BA1
Iterate map of Current Alliances Semi- Structured Video Conference
Sales Rep. BA1 Iterate map of Current Alliances Semi- Structured Video Conference Head of BA1 Finalize survey template Unstructured Video Conference Head of BA1 Discuss survey results: Services Semi- Structured Video Conference Head of BA2 Discuss survey results: Services Semi- Structured Video Conference Head of Sales
BA1
Discuss survey results: Services Semi- Structured Video Conference
Head of DevBA2 Discuss survey results: Services Semi- Structured Video Conference Head of BA1 Identify potential partners Unstructured Video Conference Sales Rep. BA1 Identify potential partners Unstructured Video Conference Product Mgr.
BA1
Identify potential partners Unstructured Video Conference
Sales Rep. BA1 Filtering of potential partners Semi-structured Video Conference
Step 4
Head of BA1 Assign weights to CSFs Structured Video Conference Partner D Potential partner D external data
collection
Semi-Structured Video Conference
Partner L Potential partner L external data collection
Semi-Structured Video Conference
Head of Sales BA1
Potential partner D internal data collection
Semi-Structured Video Conference
Head of Sales BA1
Potential partner L internal data collection
Semi-Structured Video Conference
Head of Dev.
BA1
Potential partner D internal data collection
Semi-Structured Video Conference
Head of Dev.
BA1
Potential partner L internal data collection
Semi-Structured Video Conference Table 4. This table gives a chronological account of the conducted interviews. It includes the research stage, a title description for the representatives from the Company or the name of the potential partnering company, the purpose of the interview as well as the interview format and its setting.
potential alliances would be evaluated were formed. After developing the applicable CSF’s, the current and potential actors of the ecosystem were mapped out to define which business segments and potential partners would be applicable for analysis. At this stage, the ‘value net’
framework originally used by Cummings and Holmberg was replaced by an ecosystem framework. Lastly, the new potential partners were evaluated using a modified version of Cummings and Holmberg’s dynamic partner selection analysis tool to evaluate the potential of various partners. The entire process is presented in Figure 2 below.
Figure 2. Modified version of Cummings and Holmberg’s (2009) framework which was used in the research.
3.2.3. Step 1: Aligning Corporate and Strategic Alliance Objectives
To ensure that high-level corporate and strategic objectives were stated properly, internal interviews with the Head of Business Area 1 (BA1) were conducted. An initial, unstructured interview for 20 minutes was conducted, where the Head of BA1 was asked about the corporate strategic objectives of the Company for the current fiscal year. Using Holmberg and Cummings common corporate strategic objectives the objectives were grouped and clarified. The interviewee was then instructed to identify strategic alliance objectives before a subsequent interview. Once the Head of BA1 had identified and presented the strategic alliance objectives, a semi-structured interview of 45 minutes was conducted with the same interviewee in order to clarify the objectives. At this point, some of the objectives were discarded while some were divided into subparts. The corporate strategic objectives were compared and matched against the objectives presented by Holmberg and Cummings (2009).
