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CHAPTER 1. INTRODUCTION
Image building serves as a significant positioning strategy in the tourism industry. The research conducted for this dissertation uses computing metaphor to lay emphasis on developing a systematic approach for forming alliances in order to build attractive and unique images. This chapter introduces the core topics addressed in this dissertation:
alliance partner selection, image building and computing metaphors. It offers an overview of interrelationships between these concepts and elucidates research background, motivations, questions, method and contributions.
1.1 Research Background
In tourism industry, Small- and Medium-sized enterprises (SMEs) are those actors who account for a significant proportion of tourism service providers. For example, 99% of tourism achievements in Austria are constituted by SMEs (OECD 2008).
Tourism SMEs usually have poor resources for human resource development, limited budget for marketing and lack of knowledge in recognizing their important roles in tourism development. Due to these facts, researchers and governments still keep asking “what can we do for them to make them be more sustainable?”
In an effort to answer this question, the research suggests that SMEs in tourism to join a co-operative scheme in order to increase their performance and profitability.
Tourists usually expect to attain a holistic experience from a destination, but such an experience often cannot be satisfied by a single small business service provider (OECD 2008). Therefore, there have been numerous studies in the literature about the prominence of cooperation and partnerships in the tourism sector (OECD 2008;
Smeral 1998; Reid 2008). The report from Organization for Economic Co-operation and Development (OECD) indicates the success of an individual business often
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depends on the success of a destination which can be derived from greater cooperation between tourism SMEs in the specific context of local networks and clusters (OECD 2008). Through cooperating with others, SMEs are capable to diversify tourism product portfolios to attract tourists and, in turn, improve their sustainability and profitability by making it possible for tourists to stay longer and consume more.
In addition, it has been widely recognized that it is important to build unique and attractive destination images for tourism development (e.g., Mackay & Fesenmaier 1997; Vanolo 2004). Destination image might be thought of as “an impression of a destination (Echtner& Ritchie 2003).” The more attractive a destination image is built, the more chances tourists select the destination. Thus, positive, appealing and charming image-building of a destination can serve as a policy and strategic tool in order to attract tourists, economic actors and investments (Vanolo 2004).
However, a gap has been identified between proposed destination images and supplied tourism products (Camprub ı´ 2008) because destination images are too extensive to be built or provided by only one single SME business. In order to reduce this gap, cooperation between businesses is needed. In the context of all of the above, the key means to further ongoing tourism development in a regional area will be to form highly integrated destinations with flexible operating network alliance. In alliance formation process, partner selection is undoubtedly an important task for future success (Medcof .1997).
1.2 Research Motivations and Questions
A number of literatures have investigated how to select appropriate partners in order to form a prosperous alliance. Brouthers proposed a framework for analyzing the likely success of strategic alliances, called ‘the 4 Cs’, which involves complementary
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skills, cooperative cultures, compatible goals, commensurate levels of risk (Brouthers et al. 1995). Several studies (e.g., Pesa¨maa et al. 2007; Shah et al. 2008) have also identified a series of criteria (e.g., trust, loyalty, complementarity, financial payoff) for selecting partners.
While considerable attention has been paid in the past to research issues related to develop the partner selection criteria for the intentions of resource complement (Lin et al. 2009; Shah et al. 2008), cost reductions (Geringer 1991; Lin et al. 2009; Medcof 1997) and knowledge sharing (Brouthers et al. 1995; Dacin et al. 1997), there is no work on establishing a systematic approach to identify partner portfolios with the attractive and unique features (e.g., image building in tourism).
In fact, partner selection is inherently time-consuming process. When practitioners deal with this kind of potential partnership discovering process, it’s burdensome for them to identify every possibility of partner compositions.
Nevertheless, very few studies attempt to develop an information system to facilitate this process in an automatic way.
For image building, it is inherently a value co-creation process as indicated in the service-dominant logic (Vargo & Lusch 2008). It involves pre-visit and post-visit stages. When a tourist visits a tourism destination, he/she would have intensive interactions with the destination. The image of a destination is then co-created both by tourists and service providers within the destination.
However, past research in image building often reflects a goods-dominant orientation of value creation (Kotler et al. 1999; Yu¨ ksel & Akgu¨ l 2007; Mackay &
Fesenmaier 1997). They viewed the customers as operand resources and focus on making use of different marketing approaches to influence and change how the customers perceive the image of a destination in their image building processes. This
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perspective somewhat limits the value co-creation opportunities. Therefore, we would like to develop an approach in the form of an information system enacts as an operant resource which can be leveraged by the SME owners co-creating the value with tourists (i.e., the other operant in destination tourism) in order to identify appropriate partners so as to integrate resources more effectively and propose the compelling value propositions (i.e., destination images).
In sum, we recognized the importance of cooperation between SMEs in tourism industry and briefly reviewed partner selection criteria. We also noticed that image building play a critical role in tourism success and its interdependency with business cooperation. However, we finally discovered that there is a valuable research question still remains unanswered. That is, how do we help SMEs identify their alliance partners in order to build attractive and unique images? Is there any mechanism that can be designed to aid SME owners to choose partners for image building? To what extent is the proposed mechanism leveraged to establish market niche for the SME owners? These questions then lead to the following research objectives.
1.3 Research Objectives
The overall goal of this research is to develop a creative and automatic approach that can facilitate partner selection process in order to build attractive and unique images.
Through erecting differential images and forming novel partnerships, new niche markets and new tourism products could be explored and developed. To achieve this goal, the following list of more specific objectives is established.
(1) To identify a way for innovative partner composition discovery.
(2) To develop a system architecture and a series of algorithms that forms a basis for facilitating this alliance partner recommendation service.
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(3) To implement a prototype system to demonstrate the feasibility and practicability of the proposed method.
By successfully forming a unique and attractive image, SMEs can seek to build promising alliances together, and thus improve their sustainability and profitability.
1.4 Research Method
In this study, the proposed approach employs metaphor as a starting point. Metaphor is a structure of our cognitive system (Lakoff 1987) and affects the way we perceive the world, categorize experiences, and organize our thoughts (Casakin 2007).For example, the metaphor “my lawyer is a shark” entails that the lawyer is aggressive or terrifying. A metaphor usually highlights certain aspects of the concept (i.e. aggressive) and downplays others (i.e. a creature). One of the utilities of metaphors is to help people to define abstract concepts into a more concrete level (Hill 1995). Metaphors are thus a great form to represent abstract concepts like images.
Metaphors have been used to foster creative and innovative thinking in different domains. For example, metaphors were applied to product design and architectural design (Casakin 2007; Wang 2009). In product design, metaphors are used to explore the possibilities of product design solutions, and the product designers make their design to reflect the characteristics of metaphors to products on visual level, action level and image level (Wang & Liao 2009). Additionally, researcher and practitioners often make analogy between business environments and ecosystem so as to develop a series of strategies (Iansiti & Levien 2004). We have seen evidences of the usefulness of metaphors to reinforce innovative thinking. Therefore, we believe it can be applied to solve our research questions.
Furthermore, computing metaphor is one of interesting topics in natural language
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processing domain. Fruitful researches have produced lots of techniques to excavate the meanings behind metaphors (Abe & Nakagawa 2006; Baumer et. al. 2009;
D'Harris 2002;Jones 1992; Mason 2004; Martin 1990; Slack 1980; Veale & Hao 2007;
Weiner 1984; Zhou et al. 2007). These researches provide a solid basis for us to be able to develop a metaphor-based partner recommendation system.
In general, the main reasons why we employ computing metaphors as the kernel of our approach are as follows.
(1) Metaphors are great meaning carriers which help us to define abstract concepts like images.
(2) Metaphors have been widely recognized that its ability to foster unconventional solutions discovering.
(3) Computing metaphor theory provides us a solid basis to analyze metaphors automatically.
In the scenario of using metaphor-based partner recommendation system, the users will be asked to provide a metaphorical statement which signifies the images they want to build. Then the system starts to analyze the metaphor and finally generate a series of partner candidates. Through integrating computing metaphors, we are able to develop a generative of discovering alliance partners for building the unique and attractive destination images.
1.5 Research Contributions
This dissertation presents the following key contributions:
(1) From the theoretical perspective, we attempt to adopt computing metaphor to propose a new frame of problem-solving.
(2) From the practical perspective, we provide SME owners with a useful approach
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for managing partner selection and attractive and unique image building.
(3) From service science perspective, we develop a systematic approach to facilitate value network development and service integration.
1.6 Content Organization
The research framework of this study is presented in Figure 1.1. In this chapter, the environment where the problem space resides is briefly described in terms of people, organizations and technology. SME owners and tourists are two kinds of people who play active roles in this research. Businesses usually have scarce resources and limited capabilities. Such calls provide motivations for SMEs into how to leverage information technology to improve their sustainability and profitability. In order to finely investigate and design innovative artifacts to tackle this challenging problem, related literatures addressing alliance partner selection, destination image and metaphors will be provided in chapter two. The chapter serves as the fundamental knowledge for us to further extend the human and organizational capabilities by creating new artifacts. Chapter 3 then delineates the whole picture of our research work and demonstrates the role of the proposed mechanism in the application context.
Next, Chapter 4 elaborates our metaphor-based alliance partner recommendation approach including the conceptual framework that guides the system design and the technical detail of system architecture. For the purpose of validating the effectiveness and quality of the new artifact, Chapter 5 provides a detailed scenario and Chapter 6 offers a set of experiments to manifest its utility and performance. Finally, the research findings, implications and future research are addressed in Chapter 7 for researchers and practitioners to extend and implement.
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Figure 1.1 Research framework (Source: Hevner et al, 2004)
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