CHAPTER 2. LITERATURE REVIEW
2.1 Alliance Partner Selection
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CHAPTER 2. LITERATURE REVIEW
Chapter 2 reviews relevant research from alliance partner selection, destination image and metaphors. First, justification for a growing need of a systematic approach in partner recommendation is offered by examining current research on alliance partner selection. The literature regarding this issue is discussed to provide (1) a review of partner selection criteria and (2) a primary justification for establishing a creative method to excavate innovative partner composition. Following this discussion, a review of the destination image literature is provided to justify the importance of image building in tourism sector and amplify the interrelationship between image building and alliance formation. Finally, the introduction of metaphors is given to justify the application of computing metaphor as a sound tool to facilitate the innovative partner selection process.
Chapter 2 has three objectives and it serves as the theoretical foundation specified in research framework in Figure 1.1. The first is to review common approaches used for alliance partner selection. The second is to provide theoretical justification for sustainability improvements by the aid of image building and cooperation. The third is to provide the evidence that metaphors have great potential for tackling partner recommendation problem with the purpose of attractive and unique image building.
2.1 Alliance Partner Selection
Alliance can provide firms with new source of competitive advantages (Bierly and Gallagher, 2007). A number of studies have sought to identify the underlying
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motivations for the alliance formation. These motivations majorly include resource complement (Lin et al. 2009; Shah et al. 2008), transaction cost reductions (Geringer 1991; Lin et al. 2009; Medcof 1997) and knowledge sharing (Brouthers et al. 1995;
Dacin et al. 1997). In the resource complement perspective, it is innately superior to have partners with different resources that can provide absent ingredients or capabilities so as to leverage and integrate them to create synergies (Lin et al. 2009;
Shah et al. 2008). On the other hand, transaction cost can be an important concern (Geringer 1991; Lin et al. 2009; Medcof 1997). Organizations tend to seek the partners who can reduce their business transactions in order to do more with less efforts and money. Meanwhile, knowledge sharing can be another consideration.
Learning through cooperation could be one of the efficient and effective ways to gather additional expertise and skills of specific areas (Brouthers et al. 1995; Dacin et al. 1997). However, despite the growing numbers and increasing significance of alliances, considerable proportions of alliances performed ineffectively (Inkpen &
Ross, J 2001).
The reasons behind the ineffectiveness of alliance are complex. Two common causes are inappropriate partner selection and poor alliance management (Holmberg
& Cummings 2009). In this study, we focus on partner selection. The rich body of literature thus have explored and developed the partner selection approaches, checklists and criteria for partner selection (Brouthers et al. 1995; Dacin et al. 1997;
Geringer 1991; Lin et al. 2009; Medcof 1997;Shah et al. 2008; Wu et. al. 2009). The paper in Wu (2009) provided a review of the partner selection criteria developed by numerous studies (see Table 2.1). The common criteria include characteristics of the partner, marketing knowledge capability, intangible assets, complimentary
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capabilities and degree of fitness. These criteria can be further subdivided into minor aspects for evaluating the fitness of partners.
Table 2.1 Criteria and sub-criteria for the partner selection (source: Wu et. al. 2009)
Criteria Sub-criteria
Characteristics of the partner
Unique competencies, compatible management styles, compatible strategic objectives, higher or equal level of technical capabilities between manufacturers and distributors
Marketing knowledge capability
Increased market share, better export opportunities, and knowledge of local business practices
Intangible assets Trademarks, patents, licenses, or other proprietary knowledge, reputation, previous alliance experiences, technically skilled employees among partners
Complimentary capabilities
Partners owned managerial capabilities, wider market coverage, diverse customer, the quality of distribution system to those of the strategic partners
Degree of fitness Compatible organization cultures, willingness to share expertise, equivalent of control
Such criteria contributes to the research works for developing systematic methods in partner selection. Above-listed criteria are often integrated into the development of partner selection methods. Table 2.2 presents the methods for partner
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selection and their criteria used. In fact, most methods are concentrating functional aspects (i.e., cost, quality, performance, etc) of partner selection, especially those used in developing production network or supply chain management (Amid et. al.
2006;Chang 2006; Feng et. al. 2010; Fischer et. al. 2004; Hacklin et. al. 2006; Jung 2010; Yeh
& Chuang 2010). These methods also demonstrate product-centric perspectives, which regard products as the starting point of planning process and focus on performance, efficiency and utility (Sheth et. al. 2000).
However, we argue that customer-centric perspective should be bought into partner selection issue, particularly for service industry like tourism, which inherently involves cross-industries relationships resulting in alliances because tourists need various kinds of service (i.e., transportation, accommodation, entertainment and so on) during a journey. To best practice the customer-centric perspective, the intrinsic value (i.e., psychological or emotional value) should not be ignored. As observed in Table 2.2, these psychological and emotional aspects are also neglected in current methods for partner selection. The problem regarding how to select partners in order to create superior service experiences remains unanswered.
Table 2.2 Methods for partner selection
Authors Methods Criteria used Target
(Jung
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technological level, quality of local personnel, knowledge of local business practice, location of joint venture facilitiesexperience, capability to access new market ), collaborative utility
cost, time, trust, risk, quality Virtual enterprise
cost, quality. service, capacity Supply Chain (Fischer
number of offer, date of delivery, price, social competence
Production Network
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system strategy, culture, structure Production Network
(Ding&Li
ang 2005) Fuzzy
complementary capabilities, deeper contents and forms of collaboration, similarities match with partners,
On the other hand, the research indicates that partner selection is time-consuming process and the decisions of alliance formations are often made in the limited time and information (Holmberg & Cummings 2009; Bierly and Gallagher, 2007). For tourism SMEs, the business owners rely on the knowledge of their social network to form the alliances. The search base of the list often is limited to those companies they have known, and the opportunities for innovation consequently are constrained. Such calls provide motivation for us to develop an information rich platform with a set of semi-automatic and manageable mechanisms that can enlarge the potential partner base and facilitate the process.
Therefore, for recent study, researchers have produced conceptual partner selection framework, checklists criteria and methods for partner selection, but little is known how to select partners in order to bring emotional value to their customers. To further facilitate partner selection process, our study intends to develop an alternative approach characterized by the ability to search in a wider candidate base automatically and the ability to evaluate partner portfolios while considering emotional value brought to customers.
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