Research Model and Hypotheses

A theoretical framework is used for establishing relationships between variables, providing a systematic framework to test hypotheses, and making inferences from samples to populations (Creswell 2009). Vanderstoep and Johnston (2008, p.4) defined theoretical models as ‘sets of organizing principles that help researchers describe and predict events’. The literature review in Chapter 3 presented the theoretical framework for this study incorporating models of technology adoption that have been advanced by theorists in the field of marketing and technology adoption research See table 4.1.

81 Table 4.1: Comparison of Different Technology Adoption Theories

Theory by Factors

Innovation Diffusion Theory

Rogers 1962 Variables: Relative advantage, compatibility complexity, Trialability and Observability

Theory of Reasoned Action

Fishbein and Ajzen 1975

Variables: Attitude Toward Behavior (A) and Subjective Norm (SN)

Theory of Planned Behaviour

Ajzen 1985 Variables: Attitude Toward Behavior (A), Subjective Norm (SN) and Perceived Behavioral Control (PBC)

Controllers: Attitudinal Beliefs, Normative Beliefs and Control Beliefs

Technology Adoption Model

Davis 1989 Variables: Perceived Usefulness and Perceived Ease of Use

Technology Adoption Model 2

Venkatesh & Davis (2000)

Variables: Perceived Usefulness, Perceived Ease of Use Subjective Norm, Image, Job Relevance, Output Quality and Result Demonstrability

Moderators: Experience & Voluntariness.

Unified Theory of Acceptance and Use of Technology Venkatesh et al. 2003

Variables: Performance expectancy, Effort Expectancy, Social Influence and Facilitating Conditions,

Moderators: Experience & Voluntariness, Gender And Age

However, the theoretical framework for this study is predominantly based on the Unified Theory of Acceptance and Use of Technology (UTAUT) in combination with constructs from eight technology acceptance and diffusion models to formulate a unified model. This theory was selected for many reasons. There has been criticism of Technology Acceptance Model (TAM) for being too simplistic, and this motivated the researcher to combine it with UTAUT, which has been accepted as a more sophisticated model and extensively adopted in current studies. Although TAM and its extended versions, Theory of Reasoned Action (TRA) and Theory of Planned Behaviour (TPB), are the most popular models for explaining technology acceptance, these models are criticised for their relatively low explanatory power (30-40 per cent only) in terms of behavioural intentions, while the approach adopted by Venkatesh et al. (2003) reports an explanatory power of 70 per cent. Two empirical studies with six different organisations validated the UTAUT and proved its high explanatory ability (Venkatesh et al. 2003). Further, other researchers have successfully tested the unified model of UTUAT as well (Anderson & Schwager 2004, Wang & Yang 2005, Marchewka, Liu & Kostiwa 2007, Wills, El-Gayar & Bennett 2008, Shaobo & Gang 2008).

82 As this research targets organisational attitude to e-commerce adoption in terms of the behavioural attitudes of the decision makers in the orgainsations, the research model based on the technology adoption theories of UTUAT was modified by adding constructs from two other theories of organisational culture, namely, the Competing Value Framework (CVF) and the Perceived E-Readiness Model (PERM). The use of these further models is discussed in the following sections with their proposed hypotheses. The revised model with relevant constructs from the different theories is presented below in Figure 4.2. The hypotheses were designed from the research model using statements that reflect the nature and interrelationships of the independent, dependent and moderator variables.

Figure 4.2: Revised UTAUT model

4.1.1.Elements of UTAUT Theory and PERM Model

The Unified Theory of Acceptance and Use of Technology (UTAUT) was developed by Venkatesh et al. (2003) and has been used extensively in national studies over the ensuing decade, generally with data collection at the level of the individual’s response, and notably in the context of e-government and on-line shopping in Saudi Arabia (Alsharif et al. 2013, Alzahrani & Goodwin 2012, Marchewka et al. 2007, Qingfei et al. 2008, Wills et al. 2008). With its deductive reasoning, quantitative data collection, statistical analysis, and flexibility in classifications allowing choice in variables, the unified theory was selected for this study to understand the factors influencing Saudi tourism organisations’ adoption of technology.

83 Following Molla and Licker’s (2005) argument regarding organisational e- readiness, concepts of perceived organisational e-readiness (OER) and perceived external e-readiness (EER) were also adopted. The OER construct measures the firm’s adoption or the decision-maker’s attitude to e-commerce, whilst External E-Readiness refers to the state of the ICT industry in facilitating e-commerce adoption. Thus, organisational and external e-readiness replace the UTAUT’s facilitating condition

category. The first set of hypotheses relates to perceived organisational e-readiness on adoption of e-commerce by the firm and state that:

H1Perceived organisational e-readiness has a positive influence on e-commerce adoption in tourism services.

H2 Perceived external e-readiness has a positive influence on e-commerce adoption in tourism services.

The perceived ease of use (PEU) concept derived from the TAM theory advanced by Davis (1989) will be used to measure the extent to which the complexity in mastering the required skills and ease of using a technology can determine the decision to adopt e- commerce. Although this concept is over two decades old, its essential point about the importance of ease of use of a particular device or technology still remains valid, especially given the large number of applications (apps) available for mobile technology. The next variable for hypotheses testing was PEU:

H3 Perceived ease of use has a positive influence on intention to adopt e- commerce in tourism services.

Customer influence (CI) measures the firm’s perception that their customers are adopting e-commerce and thus there are market pressures for the firm to follow. The following hypothesis addresses the impact of Customer Influence on e-commerce adoption:

H4Customer influence has a positive influence on intention to adopt e-commerce in tourism services.

Perceived Relative Advantage (RA) similarly measures managers’ expectation that adoption of e-commerce would give the firm a market advantage, particularly, if other firms in the industry were slow to adopt such technology. Thus, customer influence and relative advantage are treated as proxies for rational in the original UTUAT model.

84 H5 Perceived relative advantage has a positive influence on behavioural

intentions to adopt e-commerce in tourism services. 4.1.2.Elements of CVF Model

As organisations are the focus of this research, the Competing Values Framework (Quinn & Rohrbaugh 1981) described in Chapter 3, was used to conceptualise relevant aspects of organisational culture. This framework has recently been used in a study on the Saudi banking sector by Aldhuwaihi et al. (2012) and the Iran Oil Company by Karimi and Kadir (2012). The framework includes four organisational cultural dimensions: developmental (entrepreneurial), rational, hierarchical, and group (team), which may act as moderators for the other variables within the unified theory for this study. In addition, the moderating variable of Organisational Culture Dimensions (OCD) is supported by the competing values framework. As this study focuses on the adoption of e-commerce on an organisational level, the moderating construct of voluntariness in UTAUT was removed (Al-Gahtani et al. 2007). Figure 4.2 presents the UTAUT (unified theory) model revised by use of the Competing Values Framework. The last hypotheses relating to the moderating variable of organisational culture are:

H6aOrganisation’s cultural dimensions positively moderate customer influence on intention to adopt e-commerce in tourism services

H6b Organisation’s cultural dimensions positively moderate the influence of perceived organisational e-readiness on e-commerce adoption in tourism services

H6c Organisation’s cultural dimensions positively moderate the influence of perceived external e-readiness on e-commerce adoption in tourism services H6d Organisation’s cultural dimensions positively moderate the influence of

perceived relative advantage on behavioural intentions to adopt e- commerce in tourism services

H6e Organisation’s culture dimensions positively moderate the influence of perceived ease of use on behavioural intentions to adopt e-commerce in tourism services