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Development Of An Attitude Measurement Framework For Information Technology:A Study To Curb The Digital Divide In Mauritius

Posted on:2016-12-15Degree:DoctorType:Dissertation
Country:ChinaCandidate:Shibchurn JoshanaFull Text:PDF
GTID:1109330503969923Subject:Management Science and Engineering
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This doctoral dissertation is concerned with studying individuals’ attitudes towards technology as part of the overarching issue of the digital divide. Despite being a well-studied area of research, in practice, the digital divide still seems to exist and persist in many parts of the world. In my opinion, the success of remedial measures is likely to be governed by the divergent socio-cultural complexities that exist within each society. One size fits all solutions may not prove very effective in tackling such a phenomenon. In line with this practical dilemma, I propose a framework to determine the extent to which certain factors contribute towards improving or deterring individuals’ attitudes towards technology. The study is conducted in Mauritius, one of the most developed economies of the African continent, that fares well on the socio-economic and human development levels, and which does not suffer from the same malaises as the poorer side of Africa. Even so, technology is not as omnipresent in Mauritius as it is in more developed countries like the US and the UK. Incidentally, I thought that it would be an interesting contribution to the literature to observe trends in a country that sits somewhere between the two extremes of the ‘third world’ and the ‘wealthy west’. One of the primary gaps that this work intends to fill is the disconnect between technology adoption literature and digital divide literature. A lot of work has been previously conducted in both fields but works that combine the two are almost inexistent. Much of the literature that was reviewed as part of this research revealed that the primary focus of technology adoption research was on methodologies and frameworks as well as concepts of attitudes, perceptions, beliefs, behaviour, intentions and social norms. In contrast, digital divide literature seldom uses a framework. Rather, researchers in this niche employ methodologies like regression analysis to highlight the influence of predictors(often demographic variables) on information technology access and usage. Furthermore, works pertaining to the two areas are usually conducted in different contexts. For instance, technology adoption research tends to use organizational settings, while digital divide studies are based on wider and more diverse samples. It seems apparent that scholars have so far not given much thought to studying these two concepts in concert with each other. The basis for this research stems from this gap. If we think carefully about this situation, we would be able to appreciate that differentiated access to and usage of technology is what creates the digital divide. On the other hand, technology adoption theories like the theory of planned behaviour or the technology acceptance model, aim at determining how attitudes/intentions influence upon behaviours(e.g. access to or usage of technology). As such, there is a clear connection between the two areas that, however, remains to be exploited. Consequently, in this study, I propose an attitude measurement framework whose foundations lie on a multitude of concepts including the theory of planned behaviour, the theory of reasoned action, diffusion of innovation theory, generational theory, studies related to the Net Generation as well as concepts about the digital divide. After thoroughly analysing the literature, an attitude measurement framework is proposed. The hypothesized framework was expected to measure the influence of Net Generation characteristics(degree to which individuals exhibit characteristics of technology-savvy people or people born in the digital age), nostalgia proneness level and social norms on individuals’ attitudes towards technology. And, attitudes were intended to be measured on the basis seven diffusion of innovation attributes: relative advantage, compatibility, image, ease of use, visibility, result demonstrability and triability.Net Generation characteristics, however, is a construct that needed to be computed prior to being used as a determinant of attitudes. Because the construct to measure Net Generation characteristics is expected to assess the degree to which a person is prone to use information technology(IT), we name the construct ‘IT-proneness level’. Consequently, a chapter is dedicated to the construction and empirical analysis of the IT-proneness construct, which essentially measures individuals’ IT-proneness level. IT-proneness is measured along five dimensions namely digital literacy, connectedness, immediacy, experientialism and social orientation. The rationale behind developing a tool along these dimensions is that the Net Generation(or internet-savvy) individuals are said to exhibit such characteristics. Therefore, such a tool would help measure the extent to which any individual, independent of age, exhibits characteristics similar to the Net Generation. And, by deduction, it would seem logical that individuals with higher IT-proneness scores would have stronger and more positive attitudes towards technology. Similar to IT-proneness, nostalgia is another predictor in the proposed attitude measurement model that needs to be computed prior to being used. However, unlike IT-proneness, which is developed from scratch in this study, nostalgia proneness items are borrowed from the literature. Nevertheless, an entire chapter is also dedicated to understanding the behaviour of nostalgia in relation to various demographic variables as well as technology ownership and usage. After completing these prerequisites, the hypothetical model was ready to be tested. Normality tests were conducted and, scatterplots and graphs were generated to get a feel of the data. Bivariate correlation between IT-proneness and attitude elements revealed that the relationship between the two constructs was insignificant. As a consequence, the IT-proneness construct had to be excluded from the model, which meant that the only determinants of attitudes that were left were social norm and nostalgia. Exploratory factor analysis conducted for the social norm construct revealed that the variable be better split up into two components. On the basis of the specific items that each social norm component retained, it was deduced that the factor had been split up into its injunctive and descriptive subcomponents. At that point, there were three predictor variables: descriptive social norm, injunctive social norm and nostalgia, while the attitude variable was composed of seven subcomponents. Exploratory factor analysis on the attitude construct suggested that it would be sensible to exclude triability, and merge result demonstrability and visibility into the bigger observability component. This left us with five attitude elements. A preliminary path analysis revealed that the image attitude element loaded poorly with the four other elements. Therefore, it had to be discarded from the model. The final model comprised only four attitude elements: relative advantage, compatibility, ease of use and observability.The questionnaire items for attitudes were based on a technology service: the internet, and a technology product: the smartphone. Such an approach was undertaken to ensure that the proposed framework would be consistent and that practical applications of the model could be extended to various types of technology products and services. Consequently, dual models were tested; one for smartphone and one for internet. Furthermore, the empirical analysis adopted a nuanced approach to testing the relationships between variables in the hypothesized framework. Essentially, three versions of the hypothesized model were built. In the first version, only the predictors; injunctive social norm, descriptive social norm and nostalgia, and the dependent attitude variable were present. In the second version, demographic variables age, income and education were included separately to gauge their moderating effects on the relationships that were observed in the base model. And, in the third and last model, demographic variables were added as predictors(to the base model) to assess their effect on both nostalgia and attitudes towards technology. This three-model approach provided very interesting insights into the relationships that exist between the variables in the model. Findings from the analysis are critically discussed in line with issues relating to the digital divide. And as a final step, we discuss the theoretical and practical implications that the research is likely to have.Some critical discussion is also conducted with regards to the omitted variables ITproneness and image. Whilst the reason for including IT-proneness seemed to be very strong from the outset, the construct was found to be insignificant in influencing attitudes towards technology, neither in the case of the internet, nor in the case of smartphones. The most logical cause appears to be voluntariness of usage. It can be argued that unless someone is forced to use a technology, having a high or low IT-proneness score is inconsequential. In conditions where usage is mandatory, it would seem sensible to assume that people with a high IT-proneness score would be more comfortable with the technology, and have more positive attitudes, whereas people with lower IT-proneness scores would have to struggle with the technology, and thereby have more negative attitudes. Under voluntary situations, even someone with a high IT-proneness level, who does not feel particularly motivated about the technology in question may have unfavourable attitudes towards the technology. An alternative reason that was proposed for the lack of significance of IT-proneness in the model was that the dependent construct relates to attitudes rather than actual usage. As such, given that people are subject to social influence, either from friends or mass media, they are likely to have some level of awareness as to what smartphones and the internet allow people to do. Having seen what other people can do with these technologies, whether an individual uses it himself/herself or not, he/she may develop an attitude towards the technology that has nothing to do with his/her ability to use the technology. Similarly, with respect to the image attitude, it was posited that because Mauritius is a developing country where average income levels are not very high, people are more likely to assign greater value to other elements of attitudes than to the image factor. Whether the usage of the technology has advantages, whether someone truly needs it or not, whether the device is used by many(been tried and tested, and is popular) and whether it is easy to use seem to make more sense to people from the developing world, than buying something just for image enhancement.With regards to the sample, data was collected from Mauritius using an offline survey. The participants included both well-educated and low-educated people. The questionnaire IX was handed over to educated groups to be filled independently, while in the case of less-educated participants, a survey officer read out the questions to the participants in their mother tongue(Mauritian Creole) and jotted the responses for them on the spot. Even in the questionnaires handed out to the more educated participants, a narrative in Mauritian Creole was provided on the questionnaire next to the English version of the question. This ensured that everybody interpreted the questions in a consistent manner. A total of 360 questionnaires were returned, but only 302 were retained after data cleansing. The data collection process took about two months to complete.My original contributions in this work reside partly in the design and partly in the findings. First, assessment of individuals’ Net Generation characteristics required the development of a tool that assesses the IT-proneness of individuals along the dimensions of digital literacy, connectedness, immediacy, experientialism and social-orientation. To my knowledge, such a tool has never before been developed and is the first of its kind. Second, the main attitude measurement framework, taken in its entirety, is an original design albeit guided by prior designs. Its novelty lies in the association of constructs, and the usage of the diffusion of innovation attributes as dependent variables. Furthermore, the framework is implemented using structural equation modelling and presented in three different versions: a base model, a multi-group model and an extended model. The separate and comparative assessment of the three versions allows a very thorough appreciation of how different elements interact and influence attitudes towards technology. The model allowed the identification of potential influencers of attitudes, but also pointed out which factors are unlikely to impact attitudes. It was observed that Net Generation characteristics construct was insignificant in the attitude measurement model. However, when assessed as a standalone tool to gauge IT-proneness, the Net Generation characteristics measurement tool had high merits. Furthermore, results also revealed that the attitude to which people assign the highest importance is not the most influence-prone one. This is a vital finding as it informs practitioners as to which attitudes are best targeted on the basis of particular influencers. In light of my findings, I propose a set of recommendations that government agencies and other relevant stakeholders can consider in their efforts to address the digital gap. This work is expected to provide some overlap between technology adoption research and digital divide research, and thereby help to fill an insofar hidden gap in the literature.
Keywords/Search Tags:Attitudes, Diffusion of innovation, Digital divide, Net generation, Technology adoption
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