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As noted, MOPTUM is based on a synthesis of models describing technology adoption. The difference between MOPTUM and the major contributing models, notably TAM, the model for mobile phone technology adoption and UTAUT, will now be discussed.

The differences and similarities between MOPTUM and the TAM are discussed in section 8.4.1, in section 8.4.2 MOPTUM is compared to the mobile phone technology adoption and use model by Kwon and Chidambaram, section 8.4.3 deals with MOPTUM in relation to UTAUT and section 8.4.4 considers how MOPTUM is related to usage space models.

8.4.1 MOPTUM and TAM

The noteworthy differences between MOPTUM, as illustrated in Figure 8.2 and TAM, are the following:

• TAM models technology adoption while MOPTUM models mobile phone use. Use is dependent

A model for representing the motivational and cultural factors that influence mobile phone usage variety 175 • The external variables component in TAM is differentiated into demographic, socio-economic and

personal factors in MOPTUM.

• TAM was developed for organisations, which means that infrastructure was provided by the organisation. The cost of using a technology, as perceived by the users, was therefore not considered a relevant variable [Malhotra and Galletta, 1999; Pedersen, 2003; Kleijnen et al., 2004]. In the mobile phone scenario, infrastructure and cost are important to the individual user and therefore this component of facilitating factors has been added.

• Social influence (or subjective norm) was not included in the TAM, though the TRA, on which it is based, did include the component. The inclusion has been advocated by Malhotra and Galletta [1999]. Venkatesh and Davis [2000] found that social influence influenced both perceived usefulness (PU) and use behaviour, but noted that social influence diminished over a three-month period as the participants became more familiar with the technology. Pedersen [2005] found weak support for including social influence in mobile phone adoption and attributed this partly to their selection of innovative participants.

• TAM did not model cultural influence but the inclusion of culture in explaining mobile Internet adoption is advocated by Urbaczewski et al. [2002]. Social influence encompasses cultural influences, and therefore cultural influence as exerted by peer culture, organisational and ethnic culture on the issue of ’what will the other person(s) think of my decision’ is represented as part of the social influence component.

8.4.2 MOPTUM and THE KWON AND CHIDAMBARAM MODEL

The application of TAM to mobile phone adoption and usage focused on extrinsic and intrinsic motivations, and found that user’s perceptions were significantly associated with their motivation to use mobile phones [Kwon and Chidambaram, 2000]. For example, perceived ease of use was found to significantly influence user’s extrinsic and intrinsic motivation to use mobile phones. The following differences between the mobile phone technology adoption and use model by Kwon and Chidambaram [2000] and MOPTUM are noted:

• Both consider demographic variables, including age, gender and nationality, for their influence on ease of use but MOPTUM also includes technological development and technological orientation. This makes these models more specific than TAM, which refers to external variables without stating the specific variables.

• According to the Kwon and Chidambaram model, the respondent’s individual characteristics of gender, income and occupation have no significant effect on their perceptions of mobile phones or the social pressure to use them. According to MOPTUM personal factors do influence mobile phone usage perceptions. The effect of nationality was not reported in either of the studies.

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• The Kwon and Chidambaram model and MOPTUM both include the influence of social pressure

on technology usage. The Kwon and Chidambaram model notes apprehensiveness as a factor influencing intrinsic motivations, while MOPTUM identified uncertainty avoidance.

• The mobile phone technology adoption and use model by Kwon and Chidambaram considers

usage by looking at number of calls (similar to usage intensity) and length of calls, and differentiates between personal use and work-related use (differentiating into usage variety). MOPTUM also distinguished UI but does not distinguish between personal and work related use. However, the basic usage spaces remain applicable to both work and personal use and the allocation will be based on individual preference and requirements.

• The Kwon and Chidambaram model and MOPTUM explain some of the variance in mobile phone

user’s perceptions, motivations and usage, but both models acknowledge that much of the variance remains unexplained.

8.4.3 MOPTUM and UTAUT

The noteworthy differences between MOPTUM and UTAUT are the following:

• UTAUT models general technology adoption and use, while MOPTUM focuses on mobile phone

adoption and usage.

• UTAUT refers to performance expectancy and effort expectancy, which are not included in the MOPTUM, though effort expectancy seems related to ease of use.

• Gender, age and experience as referred to by UTAUT are included under demographic factors in the MOPTUM, while personal factors and socio-economic factors are added as mediating factors.

• MOPTUM considers only personal use and therefore volitional use, as identified in UTAUT, is not relevant in MOPTUM.

8.4.4 MOPTUM and usage space models

Marcus and Chen’s usage space model [Marcus and Chen, 2002a; Marcus, 2005b] is the basis for the MOPTUM model’s refinement of usage spaces. Marcus and Chen’s model [2005b] proposed six usage spaces, namely relationships, information, commerce, entertainment, self-enhancement and the identity space that lie at the core of the intersection of the other spaces as described in Chapter 4, section 4.6.

MOPTUM provides quantitative support for the existence of the relationships space. However, based on the interviews and qualitative observations of mobile phone usage, all Marcus and Chen’s dimensions can be supported, i.e. people use mobile phones for all these spaces.

An important difference between MOPTUM and Marcus and Chen’s model is that MOPTUM has the goal of linking mobile phone features to usage spaces. This means that the spaces are distinguished as

A model for representing the motivational and cultural factors that influence mobile phone usage variety 177 separate entities even though they may overlap, as the same feature may be used in two or more spaces. For example, SMS may be used for relationship building as well as organisation.

Looking at the findings regarding features, the analysis of the survey data as discussed in section 7.7 provides evidence that features cluster around user-specific uses. While some of these uses correspond to the usage spaces proposed by Marcus and Chen [2005b], i.e. relationships, information, m-commerce and self-enhancement, others like security, micro and hyper-organisation correspond to the usage spaces proposed by Ling and Yttri [2002].

The dimensions which emerged from the feature frequency also show similarities with the basic human needs levels proposed by Maslow [1954] and the Institute of Management Excellence [2006]. The fact that some features were used by almost all users while other features were only used by some users, suggests the existence of a set of core usage spaces and additional usage spaces which may not be used by all people.

Herzberg’s distinction between hygiene and motivational needs supports the idea of a set of core needs [Herzberg, 1968]. Kano’s model [Kano, 1984; Parker, 2006] identifies levels of importance attributed to product features, as discussed in section 4.4.3, and supports the idea of feature grouping according to user needs. Kano’s model distinguishes between basic needs, performance needs and excitement needs. The basic needs are the features that customers generally expect of a product or service, while at the other side of the spectrum, the excitement needs refer to the features that will excite or delight the customers. The categories in Kano’s model range progressively from the minimum requirements which will cause dissatisfaction if not met - the 'must be' factors, the 'more is better' - to the 'surprise and delight' factors which distinguish the product [Kano, 1996].

MOPTUM identifies only two groups and therefore the core group includes the dissatisfiers and the

must haves while the additional group includes the more is better and the surprise and delight factors.

Given the demographic profile of the participants in the survey, i.e. university students in South Africa under the age of 30, the core uses were safety and security, relationships, organisation and personal information. The distinction between core usage spaces and the rest will have to be adapted according to the demographic, socio-economic and personal factors of the user. For example, a teenager in Sweden may have relationships, entertainment and personal history as core groups.

8.5 SUMMARY

In this chapter the findings of the research have been considered in relation to the research questions presented in Chapter 5. Regarding the research questions, the following has been found:

• The usage spaces identified show similarities with models of basic motivational needs and lead to the notion that mobile usage spaces may be influenced by motivational human needs, i.e. there seems to be a link between motivational human needs and mobile phone usage variety

• The cultural factors of uncertainty avoidance and individualism/collectivism influence mobile phone usage. Technological advancement was also found to influence mobile phone usage but will

A model for representing the motivational and cultural factors that influence mobile phone usage variety 178 be regarded as a demographic factor for the rest of the research. Independence to explore, independence from assistance and efforts to maximise time and technology were identified as constructs that should be investigated further to find whether they are new dimensions or manifestations of existing dimensions.

• Mobile phone usage does not always conform to the cultural context of the user.

• Usage spaces can be used to represent usage variety but the usefulness of this idea can only be determined by the evaluation of the MOPTUM.

• One of Marcus and Chen’s usage spaces have been verified qualitatively by the findings of this research, which leads to the conclusion that Marcus and Chen’s usage spaces can be verified empirically.

The findings are then integrated to propose a mobile phone technology usage model (MOPTUM), which is based on the TAM, the mobile phone technology adoption and use model by Kwon and Chidambaram, UTAUT and usage space models. The newly proposed mobile phone usage model was described and the inclusion of each component was motivated.

The components of the MOPTUM are structured into determinant factors and mediating factors. This structure has been used in UTAUT, but the selecting of determinants and mediating factors and their composition is new. MOPTUM combines the demographic, socio-economic and infrastructural components from these different models to form the group of mediating factors. Mediating factors influence the relationships between determinants. The determinants consist of the social influence, perceived ease of use, perceived usefulness and behavioural intention components.

As noted, MOPTUM integrates and synthesises concepts from three technology adoption models, but the main contribution of MOPTUM is to extend and refine the actual use component to include usage frequency, usage breadth and usage variety, and then to extend usage variety further into usage spaces.

In order to be useful, the MOPTUM model will have to balance being generic and sufficiently advanced to survive the fast-paced and volatile nature of mobile telephony, with being specific enough to provide useful guidance. If this can be achieved, the model for understanding the factors that influence mobile phone use will be useful to mobile users, marketers and the designers of mobile phones. The evaluation of the model is described in Chapter 9.

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