Destination marketing organisations

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CHAPTER 3 THEORETICAL AND CONCEPTUAL FRAMEWORK

This chapter presents the theoretical and conceptual framework for this study. According to Imenda (2014:189), a “theoretical framework is the application of theories and consists of a set of concepts that shed more light on the research problem”. A conceptual framework is a network of interlinked concepts, which provide a comprehensive understanding of a phenomenon or phenomena (Jabareen, 2009:51).
The researcher identified and grouped theories and concepts that are relevant to this study and how they integrate to the final conceptual framework that is to solve underlying research problem.
This chapter focuses on destination image formation and processing theory, Information processing theory shows that, processed information during tourism buying process influences the type of response generated, which may be cognitive or emotional responses. The chapter examines how the decision process in consumer behaviour theory is influenced by information input and external variables. The chapter discusses the Task Technology Fit (TTF) and Technology Acceptance Model (TAM) that were used to guide the researcher in interpretation of data at evaluation process. Lastly, the chapter presents a summary of theoretical studies and their relevance in this study and concludes by discussing derived conceptual framework for this study.

Destination image theory

Tourist destination image is important to destination marketers because it relates to decision-making and sales of tourist products and services. Destination image used by the tourist is influenced by cognitive component and affective component, which results to conative component on individual reasoning and emotional interpretation that can be either positive or negative evaluation (Bosque & Martin, 2008: 557; Pena, Jamilena & Molina, 2012:265; Sarma, 2007:37).
Figure 3.1 above shows the components of destination image on attributes, functional characteristics, holistic imagery and psychological characteristics. The functional characteristics are the more tangible aspects of a destination and psychological are the intangible characteristics of a destination (Sonnleitner, 2011:21). Potential tourists access these attributes of destination image from induced and organic images.
Destination image theory is used in this study to create a mental picture using real-time images as an additional information source. The overall destination image is now developed after accessing organic, induced and real-time images from streaming mediator to reduce speculation by authenticating destination attractions before visit.
Improved TDI provide potential tourist access to real-time images that intends to create assurance of quality of expected experiences, reduce visitor search costs of destination information and offer a way for destinations to establish a unique selling proposition (Schaar, 2013:3). The next section explains TDI formation and process model.

Model of tourist destination image formation and processing

Destination images evolve through three stages namely: organic images, induced images and complex images. Organic images are formed as a result of life experience that may or may not have any relation with tourism and “induced images are formed as a result of active search” for information on various destinations (Croy & Wheeler, 2007:3).
Complex image is the result of actual visitation and experience with the destination. Organic images influences motivation to travel and active information search from available information sources. Organic image and induced image are used to create an overall image. During visit is when a more complex destination image is formed and experience with the destination will provide feedback and influence evaluation of alternative destinations on the next occasion as depicted in Figure 3.2 below (Matos, Mendes & Valle, 2012:112).
The model shows that potential tourists evaluate the destination image based overall image formed from organic and induced images, that they access before visit based on individual reasoning. TDI is then formed as a result of the knowledge the tourist acquired about the destination (cognitive component), the feelings or attachment he develops towards the destination (affective) and his intention or behaviour in the future (conative).
After that, potential tourists create an overall image comprehending functional and psychological characteristics of destination image, which creates expectations (Matos et al, 2012:111).
The strengths of this model is on influences of complex image that is developed from induced and organic images in decision-making. The main weakness is that, after tourists make decisions to travel to a selected destination. Their experience at the destination may lead to realisation or non-realisation of expectations.
The understanding of TDI formation and its effect on travel decision has high practical relevance in this study. The researcher has adopted this theory by applying organic and induced images as part of pre-visit information sources and cognitive, affective and conative component to link decision-making stage with real-time images. The overall destination image is now developed after accessing organic, induced and real-time images from streaming mediator to reduce speculation by authenticating destination attractions before visit.

Consumer psychology in web advertisements

Advertisers seek greater communication effectiveness when marketing destination products to create a cognitive and affective response. Greater information processability, which is the ease with which consumers can interpret information, can produce a positive affective response that is transferred to the product being evaluated. When information is presented in incomplete and incompatible format, it may interfere with potential tourist ability to carry out imagery and analytical information processing (Thompson & Hamilton 2006:531; Ruiz & Sicilia, 2004:657).
The model of attitude toward the web in Figure 3.3 above indicates that the uses and gratifications antecedents “(informativeness, entertainment, and irritation) affect the attitude toward the web application which later determines web usage and user satisfaction “(Luo, 2002:35). Online advertisements provide important functional characteristics that are used to create mental imagery of the destination. Thompson, Hsio and Kosslyn (2011:256), explain that mental imagery involves creation of a mental image, interpreting and transforming visual internal representation.
It is therefore necessary when marketing destination using the online media to ensure that the content is ‘complete’ for users to easily access and understand the message being communicated by advertisers. The researcher used this theory to ensure that the prototype provide a complete functional requirement.
Figure 3.4 below depicts decision process factoring in cognitive and affective components. The affective and cognitive triggers need to search for alternatives from other advertisers before the choice of purchase is made.
This model is used to improve current destination selection by having real-time images as additional information sources that intends to tap into consumer emotions when they are making travel decisions. The next sub section gives an overview of consumer behaviour theory on how it affects consumer decision-making process.

Consumer behaviour theory

The Engel-Kollat-Blackwell model described in Figure 3.5 below shows the consumer decision process model. The model consists of the need recognition stage, which is followed by alternative evaluation and involves obtaining information from internal and external sources. The other stages are information processing, decision process and variables influencing precision process (Sahney, 2008:9).
Decision-process stage is influenced by information input and external variables. When the outcomes are not satisfactory during post purchase evaluations, customers tend to go back to search for other alternatives (Suelin, 2010:2910).
The models have generalised the decision-making process for any consumer product. This view implies a biased approach to the consumer decision-making process and discuss that the more important a product, the more complex the decision-making process (Mohammadi & Mohamed, 2011:156).
The models also show that potential tourists collect and analyse information from available information sources, and gradually reduced range of alternative destination and eventually select the best possible choice. Potential tourists’ final choice is based on evaluation of the advantages and disadvantages of each possible outcome from developed TDI. This theory is applicable in this study in five stages: need recognition stage, information search, information evaluation, purchase and post purchase.
The need recognition stage is the anticipatory phase where travel need or desire that leads to information collection during pre-visit. The next stage is information search about identified possible destinations and gathering knowledge about destination. Information search behaviour influences trip outcomes and the greater the match between the pre-purchase and after-purchase destination image the more likely that the tourist has favourable perceptions toward that destination (Luo et al, 2016:17).
Information evaluation of destination information is the decision making stage during pre-visit that involves emotional interpretations resulting from cognitive and affective component. Purchase stage is adopted at online reservation component and lastly post-visit which is the post purchase stage.

Theory of constraints and continuous process improvement

Theory of Constraints (TOC) helps to improve processes to performance. Theory of constraints is used in business process improvement and focuses on the right problem and the right solution at the right time (Pacheco, 2014:332). Business Process Improvement (BPI) involves discovering weaknesses in a business process and addressing them in subsequent passes (Aalst, Netjes & Reijers, 2007:92).
According to Jacob and McClelland (2001:3), TOC focuses on three important questions ‘what to change’ in the old process, ‘to what to change to’ and ‘how to cause the change’ in the new process. During ‘what to change’ stage the core problems in the old process are identified and analysed, the next step is to find the solutions to the problems. How to cause the change: If ‘to what to change to’ is identified, but it is not possible to cause that expected change, then the solution is not of much of use.
Theory of Constraints is categorised in Figure 3.6 above consist of five steps:
1. Identify the system’s constraints.
2. Decide how to exploit the system’s constraints.
3. Subordinate everything else to the above decision.
4. Elevate the system’s constraints.
5. If in the previous steps a constraint has been broken, go back to the first step.
TOC was applied in this study to identify constraints in current customer journey framework that involves activities that potential customers perform during pre-visit, during the visit and post-visit (Croy & Wheeler, 2007:3). Customer journey framework starts from potential visitor first thinking about a vacation to planning, booking, experiencing and recalling the experience. TOC was used to exploit the constraint in customer journey framework and determine what to change to and how to cause change using streaming technology to reach primary goal of improving the effectiveness of destination selection.
The theory was as well used to develop a research process in a diagrammatic presentation of the three phases that the researcher followed to accomplish research objectives.

Task-technology fit theory

Task-Technology Fit (TTF) is the degree to which technology assists users to perform certain tasks (Goodhue & Thompson, 1995:216). The theory suggests that system users can perceive task-technology fit and the perceived fitness can further affect their usage and the performance of using the technology.
Task is the action carried out by the system users and technologies are the tools used by the users to perform tasks. They consist of products, required acts, and information cues (Goodhue &Thompson, 1995:216). Technology-as-tool provides the physical interface for manipulating the technology as representation (Davern, 2007:51). Figure 3.7 below shows that the TTF influences the performance and utilisation of that technology.
The implication of this model in this study is that, increased utilisation of the prototype might lead to positive performance impacts. Secondly, the TTF model indicates that performance may be increased when a technology provides features and support that fit the requirements of the task that is being improved (Irick, 2008:216). The TTF model was also as a conceptual basis for assessing the performance impacts of proposed tool.

Technology acceptance model

Davis, Bagozzi and Warshaw (1989) first developed the Technology Acceptance Model (TAM). The model was centred on the theory of reasoned action in psychology research (Maslom, 2007:2). Figure 3.8 below shows an improved TAM by (Chen, Li &Yi-Li, 2011:125), and theorised that an individual’s behaviour and intention to adopt a particular piece of technology is determined by the person’s attitude toward the use of the technology. Attitude in turn, is determined by perceived usefulness and perceived ease of use (Kulviwat, Bruner, Kumar & Clark, 2007:1060).
The perceived usefulness and perceived ease of use influence user behaviour and attitude towards the task technology fit (Surendran, 2012:175). Perceived usefulness is the extent to which persons believe that technology will enhance their productivity or job performance. Perceived ease of use is the extent to which a person believes that using a technology will be simple (Bagozzi, & Warshaw, 1989:987).
Consumers are more likely to adopt innovations that have perceived advantages than they are to buying products that have little or no additional benefits over the alternatives. Technology users may adopt technological products not only to obtain useful benefits but also to enjoy the experience provided by technological products (Kulviwat et al, 2007:1065).
A major challenge in development of information system evaluation is to develop frameworks that are universally applicable to a wide range of applications (Stockdale & Standing, 2005:1091). The main strength of TAM is that intentions to use a technology influence usage behaviour, and perceived usefulness and perceived ease of use determine intentions to use and actual use. This model has proven to be a useful theoretical model in helping the researcher to understand and explain use behaviour, perceived usefulness and ease of use during prototype implementation and evaluation. The model guide researchers during design of prototype user interface to achieve a high user usage of the prototype.

Realisation of research objective one

The main objective of this phase was to identify current destination selection frameworks and information sources. The researcher identified information sources gaps in existing tour destination selection. Tables 3.1 above on theoretical studies summarise important aspects from the theoretical overview.
The summaries outline the gaps, tool to support destination selection, application of theories and concepts in this study and conclusions of each area of study. The concepts used to develop the conceptual framework are information processing, tourist destination image, pre-visit information sources, use of streaming technology aimed at influencing decision-making process. Technology Acceptance Model was used to measure the effectiveness of the tool during evaluation.
Empirical studies summarise important aspects from literature review and outlines the gaps and the relevance of identified theories in this study. Destination image theory was used in this study to improve TDI using real-time images in addition to organic and induced images. Potential tourists collect and analyse information from available information sources, and gradually reduced range of alternative destination and eventually select the best possible choice. Potential tourists’ final choice is based on evaluation of the advantages and disadvantages of each possible outcome from developed TDI, which may be positive, or negative evaluation based on individual reasoning and emotional interpretation.

Conceptual framework for this research

Concepts are used to express abstract idea and can be found from previous theories or empirical research. After modelling a new conceptual framework, it must relate back to previous concepts (Jabareen, 2009:50).
The researcher improved the relationship between the components as research progressed. The initial conceptual framework was used in Phase 1 to get practitioners’ inputs is depicted in in Figure 3.9 below. The final conceptual framework emerged after framework building and validation in Chapter 5. The improved tour destination selection conceptual framework using Real-Time Data Streaming Technique (RTDST) as the technology mediator contains three phases, starting from pre-visit, during visit and post–visit. The old process shows the current destination selection process and information sources based on literature review and theoretical and conceptual frameworks. The new process is an improvement that aims at addressing the gaps using a technology mediator tool in form of RTDST.

Conceptual definitions

Destination selection involves activities that potential customers perform during pre-visit, during actual visitation and during post-visit (Croy & Wheeler, 2007:3). Customer journey starts from a potential visitor first thinking about a vacation, to planning, booking, experiencing and recalling the experience. Information sources used in destination selection are a force which influences the formation of perceptions or cognitive evaluations but not the affective component of destination image (Baloglu & Mccleary, 1999:874).
Information sources during pre-visit that enable potential tourist to make travel decision are in the form of organic and induced images. According to Dominique (2011:331), image influences the attitude that tourists develop towards destinations, which influences the buying decision process.
Induced images are formed as a result of active search for information on various destinations while organic images are formed as a result of life experience that may or may not have any relation with tour destination. Real images are those images that are formed during visit of the destination and it is during this period that the image of tour destination is changed, clarified and expanded (Croy& Wheeler, 2007: Dominique, 2011:310).
Mediation in the tourism setting refers to an individual’s active attempt to interpret the tourism experience to another individual. Mediator in the tourism setting is the tour guide, while technology mediators are technological tools used to influence consumer buying behaviour (Tussyadiah & Fesenmaier, 2009:37).
The framework starts from the anticipatory phase and ends at post-visit. During pre-visit potential tourists are in a position to make travel decisions from organic images, induced images and real time images from technology mediator.
Tourists access real-time images using technology mediator to authenticate tourist destination attractions. With the knowledge derived from organic, induced and real time images about selected and alternative destinations, they are in a better position to make informed travel decisions. During visit, tourists compare destination image and experience with pre-visit information sources, which leads to either realisation or non-realisation of expectations. The last component is post-visit where they recall the experience. Any difference between expectations and experience affects destination reputation and overall customer satisfactions.

Table of contents
Abstract
Acknowledgements
Dedication
List of Tables
List of Figures
Author’s declaration
CHAPTER 1 INTRODUCTION
1.1 Background to the research problem
1.2 Statement of the research problem
1.3 Research questions
1.4 Research aim and objectives
1.5 Rationale
1.6 Conceptual and theoretical framework
1.7 Research paradigm
1.8 Research design and methodology
1.9 Research scope
1.10 Research contribution
1.11 Ethical considerations
1.12 Thesis outline
CHAPTER 2 LITERATURE REVIEW
2.1 ICT and tourism
2.2 Destination marketing organisations
2.3 Destination selection
2.4 Consumer buying behaviour
2.5 Information source and formation process
2.6 Information search behaviour
2.7 Consumer psychology
2.8 Destination Marketing Systems
2.9 Technology-based mediators
2.10 Data streaming
2.10 Chapter summary
CHAPTER 3 THEORETICAL AND CONCEPTUAL FRAMEWORK
3.1 Destination image theory
3.2 Model of tourist destination image formation and processing
3.3 Consumer psychology in web advertisements
3.4 Consumer behaviour theory
3.5 Theory of constraints and continuous process improvement
3.6 Task-technology fit theory
3.7 Technology acceptance model
3.8 Realisation of research objective one
3.9 Conceptual framework for this research
3.10 Conceptual definitions
3.11 Chapter summary
CHAPTER 4 RESEARCH DESIGN AND METHODOLOGY
4.1 Research philosophy
4.2 Research approach: Design-Science Research
4.3 Research methodology
4.4 Ethical considerations
4.5 Chapter summary
CHAPTER 5 FRAMEWORK BUILDING AND VALIDATION (PHASE 1)
5.1 Phase 1 research instrument
5.2 Data analysis and results
5.3 Conceptual definitions
5.4 Realisation of research objective two: improved conceptual framework
5.5 Chapter summary
CHAPTER 6 PROTOTYPE DESIGN AND IMPLEMENTATION (PHASE 2)
6.1 Unified modeling language
6.2 Conceptual graphs
6.3 Framework implementation option
6.4 Software and hardware platform
6.5 Prototype functionality
6.6 Performance testing
6.7 Realisation of research objective three
6.8 Chapter summary
CHAPTER 7 FRAMEWORK EVALUATION (PHASE 3)
7.1 Evaluation criteria
7.2 Phase 3 research instruments
7.3 Practitioners’ evaluation process
7.4 Web analysis using Google analytics
7.5 Web analytics results
7.6 Expert evaluation analysis and results
7.7 Inferential statistics
7.8 Coefficient of determination
7.9 Realisation of research objective four
7.10 Chapter summary
CHAPTER 8 CONCLUSION AND FUTURE WORK
8.1 Research contribution
8.2 Limitations and directions for future work
8.3 Final remarks
List of references
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