A framework for assessing trust in e-government services under uncertain environment

In this study, a novel framework was proposed to assess the trust in e-government (e-Gov) services under an uncertain environment. The proposed framework was applied in Iranian municipality websites of e-Gov services to evaluate the readiness score of trust in e-Gov services. A unique hybrid research methodology was proposed. In the first phase, a comprehensive set of indices were determined from an extensive literature review and finalized by employing the fuzzy Delphi method. In the second phase, Interval-Valued Intuitionistic Fuzzy Sets (IVIFS) was utilized to model the problem’s uncertainty with Analytic called IVIFS- Hierarchy Process (AHP) to determine the importance of indices and indicators by assigning the weights. In the third phase, the Fuzzy Evaluation Method (FEM) is followed for assessing the readiness score of indices in case studies. The findings indicated that “Trust in government” is the most significant index affecting citizen’s trust in e-Gov services while “Maintenance and support” has the least impact on user’s intention to use e–Gov services. The study is one of the few to indicate significant indices of trust in e-Gov services in developing countries. The study shows the importance of indicators and indices by assigning a weight. Additionally, the framework can assess the readiness score of various case studies. Research Implications: The study contributes by introducing a unique research methodology that integrates three phases, including Fuzzy Delphi, IVIFS AHP and Fuzzy Evaluation method. Moreover, the Fuzzy sets theory helps to reach a more accurate result by modeling the inherent ambiguity of indicators and indices. Interval-Valued Intuitionistic Fuzzy models the ambiguity of experts’ judgments in an interval. The study helps policy makers to monitor wider aspects of trust in e-Gov services as well as understanding their importance. The study enables policy makers to apply the framework to any potential case studies to evaluate the readiness score of indices and recognizing strengths and weakness of trust dimensions as well as recommending advice for improving the situation

DETERMINATION OF THE LEVEL OF RISKS IN INVESTMENT PROJECTS USING ECONOMETRIC MODEL

Particular study of the effective use of investments, including foreign investments, on technical and technological modernization of enterprises and diversification of products in the conditions of modernization of the economy, ensuring the competitiveness of manufactured products and services in the world market is one of the most important tasks of today. Today, further reforming and liberalizing the Uzbek economy should accelerate the improvement of the investment climate in the industrial sector, especially with the development of the private sector

ANFIS to Quantify Maintenance Cost of IT Services in Telecommunication Company

The maintenance cost predication of information technology (IT) regarding their important role and well-time availability in organization is valuable for IT managers. Therefore their decision originated from the predication might be great effect on organizational budgeting, planning, and strategy management. In this regard, having enough knowledge of IT system behavior and their cost forecasting may help IT managers to develop their organization. In this chapter, adaptive neuro-fuzzy inference system (ANFIS) with capability of modeling and predication is introduced, respectively, for quantifying information technology services and their maintenance cost in one of the telecommunication companies in Iran. Because of easy accessibility in finding parameters and also prevention from the complexity of information resulting from some available services in case study organization, automation services are selected by author as kind of user-involved and widely used in finding and studying on the variable data for implementation of the model

Towards measuring resilience of flood-prone communities: a conceptual framework

Community resilience has become an important policy and research concept for understanding and addressing the challenges associated with the interplay of climate change, urbanization, population growth, land use, sustainability, vulnerability and increased frequency of extreme flooding. Although measuring resilience has been identified as a fundamental step toward its understanding and effective management, there is, however, lack of an operational measurement framework due to the difficulty of systematically integrating socioeconomic and techno-ecological factors. The study examines the challenges, constraints and construct ramifications that have complicated the development of an operational framework for measuring resilience of flood-prone communities. Among others, the study highlights the issues of proliferation of definitions and conceptual frameworks of resilience, challenges of data availability, data variability and data compatibility. Adopting the National Academies’ definition of resilience, a conceptual and mathematical model was developed using the dimensions, quantities and relationships established by the definition. A fuzzy logic equivalent of the model was implemented to generate resilience indices for three flood-prone communities in the United States. The results indicate that the proposed framework offers a viable approach for measuring community flood resilience, even when there is a limitation on data availability and compatibility

A Fuzzy Inference System for the Assessment of Indoor Air Quality in an Operating Room to Prevent Surgical Site Infection

Indoor air quality in hospital operating rooms is of great concern for the prevention of surgical site infections (SSI). A wide range of relevant medical and engineering literature has shown that the reduction in air contamination can be achieved by introducing a more efficient set of controls of HVAC systems and exploiting alarms and monitoring systems that allow having a clear report of the internal air status level. In this paper, an operating room air quality monitoring system based on a fuzzy decision support system has been proposed in order to help hospital staff responsible to guarantee a safe environment. The goal of the work is to reduce the airborne contamination in order to optimize the surgical environment, thus preventing the occurrence of SSI and reducing the related mortality rate. The advantage of FIS is that the evaluation of the air quality is based on easy-to-find input data established on the best combination of parameters and level of alert. Compared to other literature works, the proposed approach based on the FIS has been designed to take into account also the movement of clinicians in the operating room in order to monitor unauthorized paths. The test of the proposed strategy has been executed by exploiting data collected by ad-hoc sensors placed inside a real operating block during the experimental activities of the “Bacterial Infections Post Surgery” Project (BIPS). Results show that the system is capable to return risk values with extreme precision

Intelligent modeling of e-Government initiatives in Greece

Over the last two years Greece has employed agile ICT solutions to reduce the administrative burden in front-office G2B transactions. This research supplements historic analysis with fuzzy cognitive maps to offer a multi-dimensional coupling of eGovernment initiatives with digital maturity assessment capabilities and a strategy alignment evaluation framework. This “intelligent x-ray” confirms that front-office technology is important in reducing administrative burden. The digital bypass of bureaucracy seems to be an effective start for Greece. However, this strategy can only serve as a short-term tactical choice. The “intelligent x-ray” provides executive level quantification and traceable reasoning to show that excessive emphasis on front- office technology will soon fail to support a strong eGovernment maturity. Organizational efficiency, interoperability, regulatory simplifications, and change management must also act as important objectives. Only then will ICT deliver its full potential, and the eGovernment maturity will improve significantly even with moderate ICT investments

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Operations Management

Global competition has caused fundamental changes in the competitive environment of the manufacturing and service industries. Firms should develop strategic objectives that, upon achievement, result in a competitive advantage in the market place. The forces of globalization on one hand and rapidly growing marketing opportunities overseas, especially in emerging economies on the other, have led to the expansion of operations on a global scale. The book aims to cover the main topics characterizing operations management including both strategic issues and practical applications. A global environmental business including both manufacturing and services is analyzed. The book contains original research and application chapters from different perspectives. It is enriched through the analyses of case studies