| Summary: | This study intends to identify, within the framework of the Diffusion of Innovation (DOI) theory, an e-procurement adoption pattern in an emerging economy that will be applied in the government sector of the United Arab Emirates (UAE). The UAE is a small country in the Middle East that has an open economy with a high per capita income and a sizable annual trade surplus. It consists of seven states or "Emirates", most of which have their own e-government sites though they vary in their levels of sophistication. The literature review investigates the work related to the identification of factors that influence adoption of innovations in e-government and e-procurement; the scope is then narrowed down to the practice of complex information systems in relation to e- procurement. Prior research into the adoption of e-procurement is then examined in detail to determine which factors have particular significance. A review of diffusion of innovation theories and approaches supported by these theories is conducted to clarify how users of e-procurement can be best supported through governmental strategies. The research defines the current e-procurement environment in the UAE as a domain context for the emerging economy. The research addresses the problem of the lack of a rigorous way by which the governmental units adopt e-procurement for efficiency and effectiveness. A method is devised after identifying the factors that drive the successful e- procurement adoption in the UAE and the relative impacts of these driving factors. A development of the method is endorsed by using case studies, a survey questionnaire, and semi-structured interviews. The data collected are analysed by using two types of statistical inference to carry out the hypotheses test: one way is the analysis of variance (ANOVA), and the other is the T-test by means of two independent samples. The method is validated internally by using pattern matching and externally by using focused interviews. It is expected that the method will be disseminated in the government units in the UAE. The findings of the study show that the use of e-procurement is becoming more widespread in the UAE. The UAE has been ranked 49th out of 184 with a total e- government index of 0.535 against a world average of 0.441 in the UN e-government 2010 survey. A comparative analysis of the survey shows that the UAE has an online services index of 0.251 against a world average of 0.286; an infrastructure index of 0.543 against a world average of 0.236; a human capital index of 0.819 against a world average of 0.797; and an e-participation index of 0.129 against a world average of 0.205. The development trend of the e-government readiness index of the UAE is changing between 0.4736 and 0.5349 in the period from 2004 to 2010. The strongest e-readiness factors in the UAE are the infrastructure and human capital and the weakest factors are the e-participation and online services. The infrastructure and human capital are the leading factors in technology development. However, the adoption of e-government is different from state to state within the UAE, for several reasons including leadership, management, infrastructure, and human factors that vary across this heterogeneous country. Thus several factors affect the diffusion of e- government in one state more than in another. A sample study was conducted, consisting of 170 persons who were selected from the purchasing departments of organisations that have e-procurement systems in their work in the UAE, and their characteristics and patterns of e-procurement adoption are depicted. In order to investigate whether there is any effect by each of the components of individual readiness and/or organisation readiness on e-procurement adoption characteristics, several tests are conducted. The e-procurement adoption characteristics are measured in five groups: relative advantage, compatibility, ease of use, triability, and observability. The Individual Readiness components are measured in two ways: by measuring the basic computing knowledge, and measuring the individual category according to Rogers' model. It has been found that most of the individuals in the sample (99.4%) have basic computing knowledge. The individual categories include 15.3% laggards, 32.4% late majority, and only 4.1 % innovators. In order to explore the effect of Individual Readiness on the e-procurement Adoption, ten preliminary hypotheses are tested. The results show that there are difference among age classes, education levels, the category of using new technologies, those who have spent more years in service, those who have or do not have a computer qualification, classifying decision classes, those who have or have not attended training courses in the area of e- procurement, annual salary classes and those who have or have not attended training courses in the area of e-procurement before implementing it, in their responses on the impact of e-procurement. At the same time the results show that there are no differences among genders in their responses on the impact of e-procurement, In order to explore the effect of Organisation Readiness on the e-procurement Adoption, five preliminary hypotheses are tested. The results show that there is no difference among locations of organisations, in their responses on the impact of e-procurement, At the same time the results show that there are differences between local and federal participants, between applying an electronic procurement system and the old traditional way of purchasing, and between those who welcomed and showed enthusiasm towards implementing the adopted e-procurement system, and those who did not, and classifying category classes, in their responses on the impact of e-procurernent. The results of testing these fifteen preliminary hypotheses guide the development of a Structural Equation Model (SEM) that depicts the causal relationships among factors affecting e-procurement adoption in the UAB. The SEM assumes that the "Organisational Readiness" and the "Perceived Attributes of e-procurement Usage" predict the "Successful Implementation of e-procurement." The model explains 77% of the latent variable "Successful Implementation of e-procurernent," with a satisfactory model fit. A larger sample size is recommended whenever it is available. The SEM model results verify the following hypotheses: (1) Organisation Readiness has a significant positive effect on the e-procurement Successful Implementation, which is not rejected, (2) Perceived Attributes have a significant positive effect on the e-procurernent Successful Implementation, which is not rejected, and (3) Organisation Readiness and Perceived Attributes are positively correlated, which is rejected. The rejection of the third hypothesis, that Organisation Readiness and Perceived Attributes are positively correlated, shows that as the Perceived Attributes increase, the efforts for improving Organisation Readiness decrease. The two factors meet together at the point of successful adoption. The SEM results show that the Individual Category and the Availability of Information and Communication Technology Facilities (ICTF) have the highest impact on Organisational Readiness but the Pre-preparing and training factor has less impact on it. The ratios of the three observable variable impacts are 0.97: 0.94: 0.65. The impact of the relative advantage of using e-procurement and the compatibility of e- procurement with the system do not go along with the impacts of Ease of Use, Observability and Trialability on the Perceived Attributes of using e-procurement, The relative impacts of Ease of Use, Observability and Trialability on the Perceived Attributes of using e-procurement are 0.83: 0.96: 0.87. The Individual Satisfaction reflects the Successful Implementation of e-procurement more than the Organisational Satisfaction does. These results can guide the development of governmental policy for successful e- procurement implementation in the UAE as well as other similar countries. It will encourage more research into the area and influence the governments of emerging economies to make appropriate strategic decisions to improve the level and rate of successful adoption of e-procurement systems in their countries.
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