Devolution in a Virtual Enterprise

E-Government as a virtual enterprise, having many vertical portals, works i

A Formal Model for Electronic and Mobile Government Service Delivery Success Factors

Previous studies investigating the success of electronic and mobile government service delivery (EMGSD) have identified the factors that promote or mitigate against realisation of the benefits of such delivery. Models have lacked formality and have generally ignored the complexity of relationships between factors and factor sets. The studies have generally been concerned with EMGSD in a developed country. This paper reports on research-in- progress to address these areas. A preliminary formal model is presented with indicative examples of modelled relationships, together with a brief description of how the usefulness of the model will be validated for developing countries

Towards Culture Influenced Virtual Learning Environment Trust (CIVLET) Framework

At present the common model of virtual education involves the delivery of courses via the internet as compliment to traditional classroom learning. This model is widely adopted in traditional institution. In a more advanced model, all courses are offered solely through the internet, and on satisfactory completion students are awarded degrees. A virtual learning provider still has to find a way to earn students’ trust. This paper presents the framework for modelling trust in virtual learning environment. Our propose framework relies on existing behavioural related information system research theories. However, since participants of virtual learning environment are often geographically distributed and the trust dimensions vary, we propose the inclusion of culture as a key construct in our framework

An Exploratory Analysis of E-Government Development in the Caribbean

Digital divide is, despite all efforts in research and practice, a matter of fact in most societies. In search for specific strategies to promote digital inclusion, one has to ask for what are the specific reasons and factors behind the problem. Here, the field of E-Government features several particular characteristics, including high privacy and security demands or high complexity of administrative processes, which might hinder the societal inclusiveness of such electronic public service delivery. Addressing the question of what could be possible explanations for a lack of inclusiveness in E-Government, we develop an E-Government-inclusion-gap-model and conduct a quantitative analysis of statistical data on E-Government usage in Germany, taking into account specific social digital divide groups, such as senior citizens, people with low education or people without employment. Here, we contrast E-Government usage with E-Commerce and internet usage. Specific inclusion gaps in E-Government and their underlying issues are analysed and specific recommendations given

Intelligent data sources and integrated data repository as a foundation for business intelligence analysis

Abstract: Data mining and data analysis in general demonstrate high dependency on data quality. Gathering the right data of high enough quality takes most of researcher’s time and often demonstrates need for some additional data to be parsed. In order to eliminate or at least reduce required effort for this first phase of every analysis, authors of this paper present the idea of Integrated Data Repository and Intelligent Data Source. Concepts of those components are presented and approach to their development is suggested together with the high-level view of the system architecture. Finally, an experimental implementation is described

Risks and Hidden Costs: A Study of 26 Outsourced Projects

Despite the current unfavorable outlook of the larger economy, there has been a steady increase in information systems outsourcing by organizations which is projected to reach $97.9 billion in 2012. Ordinarily, organizations outsource their software projects to avoid the risks associated with developing the software internally and to control costs. However, a study of twenty six outsourced projects indicates that such organizations face unique risks and hidden costs that are particular to software outsourcing. This paper describes research done to estimate the effort expended by organizations in overseeing and participating in outsourced software projects and the implications for identifying risks and predicting costs of such projects. For many of the organizations that participated in the survey, uncovering the actual costs and risks of an outsourced project was an eye opener: the hidden costs and risks are surprisingly significant and are typically not managed by the organization

Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction

Over the past decades, the Least Squares Support Vector Machines (LSSVM) has been widely utilized in prediction task of various application domains. Nevertheless, existing literature showed that the capability of LSSVM is highly dependent on the value of its hyper-parameters, namely regularization parameter and kernel parameter, where this would greatly affect the generalization of LSSVM in prediction task. This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. The lvABC algorithm is introduced to overcome the local optima problem by enriching the searching behaviour using Levy mutation. On the other hand, the cmABC algorithm that incorporates conventional mutation addresses the over- fitting or under-fitting problem. The combination of lvABC and cmABC algorithm, which is later introduced as Enhanced Artificial Bee Colony–Least Squares Support Vector Machine (eABC-LSSVM), is realized in prediction of non renewable natural resources commodity price. Upon the completion of data collection and data pre processing, the eABC-LSSVM algorithm is designed and developed. The predictability of eABC-LSSVM is measured based on five statistical metrics which include Mean Absolute Percentage Error (MAPE), prediction accuracy, symmetric MAPE (sMAPE), Root Mean Square Percentage Error (RMSPE) and Theils’ U. Results showed that the eABC-LSSVM possess lower prediction error rate as compared to eight hybridization models of LSSVM and Evolutionary Computation (EC) algorithms. In addition, the proposed algorithm is compared to single prediction techniques, namely, Support Vector Machines (SVM) and Back Propagation Neural Network (BPNN). In general, the eABC-LSSVM produced more than 90% prediction accuracy. This indicates that the proposed eABC-LSSVM is capable of solving optimization problem, specifically in the prediction task. The eABC-LSSVM is hoped to be useful to investors and commodities traders in planning their investment and projecting their profit

Marketing mix drivers of clients satisfaction in technology-enabled service: Study of Nigerian GSM subscribers

Rapid diffusion of mobile telephone services is accompanied with low satisfaction and high switching behavior many markets.Despite the popularity of technology diffusion studies in marketing literature, limited research concentrate on the impact of marketing mix variables vis-à-vis clients’ satisfaction. Much fewer studies were conducted in developing nations.This paper investigates the influence of marketing mix on clients’ satisfaction with innovation adoption in Nigerian GSM market.Building on Technology Adoption Life-Cycle Model and extensive literature review, six constructs were theoretically developed and statistically validated.Multiple regression run on a sample of 373 subscribers drawn from four universities, indicates the five marketing mix variables predict 52% of the variance on clients’ satisfaction.Furthermore beta coefficients revealed Core Service (0.38) makes the strongest unique contribution in explaining clients’ Satisfaction followed by Pricing at 0.22, while Distribution (0.072) is the only variable not making significant contribution to the model