Classification of information systems research revisited: A keyword analysis approach

A number of studies have previously been conducted on keyword analysis in order to provide a comprehensive scheme to classify information systems (IS) research. However, these studies appeared prior to 1994, and IS research has clearly developed substantially since then with the emergence of areas such as electronic commerce, electronic government, electronic health and numerous others. Furthermore, the majority of European IS outlets - such as the European Journal of Information Systems and Information Systems Journal - were founded in the early 1990s, and keywords from these journals were not included in any previous work. Given that a number of studies have raised the issue of differences in European and North American IS research topics and approaches, it is arguable that any such analysis must consider sources from both locations to provide a representative and balanced view of IS classification. Moreover, it has also been argued that there is a need for further work in order to create a comprehensive keyword classification scheme reflecting the current state of the art. Consequently, the aim of this paper is to present the results of a keyword analysis utilizing keywords appearing in major peer-reviewed IS publications after the year 1990 through to 2007. This aim is realized by means of the two following objectives: (1) collect all keywords appearing in 24 peer reviewed IS journals after 1990; and (2) identify keywords not included in the previous IS keyword classification scheme. This paper also describes further research required in order to place new keywords in appropriate IS research categories. The paper makes an incremental contribution toward a contemporary means of classifying IS research. This work is important and useful for researchers in understanding the area and evolution of the IS field and also has implications for improving information search and retrieval activities

E-commerce and its impact in logistic management: A state of art

Logistics management is defined as that part of the supply chain process that plans, implements, and controls the efficient, effective flow and storage of goods, services, and related information from the point of origin to the point of consumption in order to meet customers' requirements. Traditional logistical issues may be amplified by an e-commerce venture. Adopting e-commerce may greatly expand the marketplace. The organization needs to be concerned with its ability to deliver its product to potential customers. Realizing the importance of E-commerce in logistic management, an attempt has been made in this paper to review the existing literature with the objective to gain insights into the impact of E-commerce in logistic management. The advantages of the E-commerce in logistic management are offered. Finally, summary of findings and calculations are presented

Managing Wireless Networks in the Healthcare Sector: Emerging Experiences of Cultural Impacts

The existing body of knowledge has generally supported that organizational culture plays a significant role in shaping group identity, work pattern, communication schemes, and interpersonal relations; all of these cultural elements are important organizational factors that shape workplaces and operational routines. In the context of emerging information technology, it has also been suggested that organizational culture could affect IT implementation and management. However, little is known about how emerging information technology shapes organizational culture, which in turn helps reshape the organization as a whole. The purpose of this paper is thus to build empirical understanding of how IT in general and emerging wireless networks in particular reshapes organizational culture. Case studies conducted in two hospitals situated in southwest U.S.A. illustrated that the implementation of wireless networks indeed helped shape and/or reshape organizational culture in the healthcare sector and in turn enhance healthcare organizations’ competitiveness in the marketplace. For IT managers and practitioners in healthcare institutions, effective strategy to plan and manage emerging ITs such as wireless networks will thus have long-term implications on cultivating organizational culture that could eventually reshape workplace and competitiveness

Fuzzification of quantitative data to predict tumour size of colorectal cancer

Regression analysis has become more popular among researchers as a standard tool in analyzing data. This paper used fuzzy linear regression model (FLRM) to predict tumour size of colorectal cancer (CRC) data in Malaysia. 180 patients with colorectal cancer received treatment in hospital were recorded by nurses and doctors. Based on the patient records, a triangular fuzzy data will be built toward the size of the tumour. Mean square error (MSE) and root mean square error (RMSE) will be measured as a part of the process for predicting the size of the tumour. The degree of fitting adjusted is set between 0 and 1 in order to find the least error. It was found that the combination of FLRM model with fuzzy data provided a better prediction compared to the FLRM model alone. Hence, this study concluded that the tumour size is directly proportional to several factors such as gender, ethnic, icd 10, TNM staging, diabetes mellitus, Crohn’s disease

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

An Empirical Investigation of the Level of Users’ Acceptance of E-Banking in Nigeria

Nigeria was depicted to be the fastest growing telecommunications nation in African. Presently, all members of the Nigeria banking industry have engaged the use of Information and Communication Technology (ICT) as a platform for effective and efficient means of conducting financial transactions. This paper focuses on determining the level of users’ acceptance of the electronic banking services and investigating the factors that determine users’ behavioral intentions to use electronic banking systems in Nigeria. The survey instrument employed involved design and administration of a total of 500 survey questionnaires within the Lagos metropolis and its environs. An extended Technology Acceptance Model (TAM) was employed as a conceptual framework to investigate the factors that influence users’ acceptance and intention to use electronic banking. To test the model, data was collected from 292 customers from various commercial banks in Nigeria. The model measured the impact of Perceived Credibility (PC), Computer Self-Efficacy (CSE), Perceived Usefulness (PU), and Perceived Ease of Use (PEOU) on customer attitude and customer attitude on customer adaptation. The result of this research shows that ATM still remains the most widely used form e-Banking service. Banks’ customers who are active users of e-Banking system use it because it is convenient, easy to use, time saving and appropriate for their transaction needs. Also the network security and the security of the system in terms of privacy are the major concerns of the users and constitute hindrance to intending users

A Decision Technology System To Advance the Diagnosis and Treatment of Breast Cancer

Geographical variations in cancer rates have been observed for decades. Described spatial patterns and trends have provided clues for generating hypotheses about the etiology of cancer. For breast cancer, investigators have demonstrated that some variation can be explained by differences in the population distribution of known breast cancer risk factors such as menstrual and reproductive variables (Laden, Spiegelman, and Neas, 1997; Robbins, Bescianini, and Kelsey, 1997; Sturgeon, Schairer, and Gail, 1995). However, regional patterns also may reflect the effects of Workshop on Hormones, Hormone Metabolism, Environment, and Breast Cancer (1995): (a) environmental hazards (such as air and water pollution), (b) demographics and the lifestyle of a mobile population, (c) subgroup susceptibility, (d) changes and advances in medical practice and healthcare management, and (e) other factors. To accurately measure breast cancer risk in individuals and population groups, it is necessary to singly and jointly assess the association between such risk and the hypothesized factors. Various statistical models will be needed to determine the potential relationships between breast cancer development and estimated exposures to environmental contamination. To apply the models, data must be assembled from a variety of sources, converted into the statistical models’ parameters, and delivered effectively to researchers and policy makers. A Web-enabled decision technology system can be developed to provide the needed functionality. This chapter will present a conceptual architecture for such a decision technology system. First, there will be a brief overview of a typical geographical analysis. Next, the chapter will present the conceptual Web-based decision technology system and illustrate how the system can assist users in diagnosing and treating breast cancer. The chapter will conclude with an examination of the potential benefits from system use and the implications for breast cancer research and practice