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Government initiatives are continuously being designed to create stable and supportive environments for developing new industries. Presents a conceptual model for use by…
Government initiatives are continuously being designed to create stable and supportive environments for developing new industries. Presents a conceptual model for use by governments in creating and sustaining an appropriate climate that facilitates the national adoption of e‐business. It focuses specifically on the needs of small and medium‐sized enterprises (SMEs). Also suggests six categories of e‐business readiness metrics and measures to be used for assessing how a country is performing in terms of providing a positive e‐business readiness climate. Examples of innovative initiatives are provided from Canada, The Netherlands, Norway, and Singapore. Concludes that a balance among attention to infrastructure components has not yet been achieved in these countries.
Although the Boolean combination of keywords and/or subject codes is the predominant access method for the retrieval of passages from full‐text databases, menu access is…
Although the Boolean combination of keywords and/or subject codes is the predominant access method for the retrieval of passages from full‐text databases, menu access is an attractive alternative. The selection of an access method and the ensuing satisfaction with the results is based on the type of query and on the experience and knowledge of the user. This paper describes a prototype system which has integrated Boolean, menu, and direct access methods for the retrieval of passages from full‐text databases. The integration is based on the hierarchical structure inherent in such databases as legal statutes and regulations and engineering standards. The user may switch freely among access methods in order to develop the most appropriate search strategy. The retrieved passages are presented to the user within the context of the hierarchical structure.
The graphical representation of a finite element model (undirected graphs) imposes some constraints on the choice of storage techniques and data structures; first, the…
The graphical representation of a finite element model (undirected graphs) imposes some constraints on the choice of storage techniques and data structures; first, the storage structure must deal efficiently with sparse matrices; second, the retrieval method of an edge, of a finite element model, around selected nodes must minimize the multiple occurrences of the same edge if plotting efficiency is to be achieved; and third, the insertion and extraction of edges in a data structure must be independent of the selected nodes identification scheme. This paper evaluates the relative merit of elementary storage methods and data structures in terms of the time and space costs required to satisfy the above constraints. The theoretical costs are derived and the experimental costs are evaluated and compared. Depending on the homogeneity of the degree of the nodes, a static data structure or a linked list data structure using listed or sectioned hashing techniques are shown to yield the minimum time and space costs.
This study aims at contributing to the discussion related to what causes Canadian small and medium‐size enterprises (SMEs) to be reticent about accepting internet and…
This study aims at contributing to the discussion related to what causes Canadian small and medium‐size enterprises (SMEs) to be reticent about accepting internet and e‐business technologies (IEBT) in their operations. The research also seeks to gain an understanding of the relative importance of each of the selected factors in the research setting.
A survey was conducted in the Atlantic region of Canada. Questionnaires were mailed to key SMEs' informants. Data analysis was performed using the partial least squares (PLS) approach. A research framework based on the technology‐organization‐environment (TOE) frameworks was used to guide the research effort. Such contingent factors as perceived benefits, management commitment/support, organizational IT competence, external pressure, information systems (IS) vendor support, and availability of financial support, were used to develop relevant hypotheses.
The study's findings indicated that perceived benefits, management commitment/support, and external pressure are significant predictors of IEBT acceptance in the sampled SMEs; the results did not show that organizational IT competence, IS vendor support, and availability of financial support positively influence IEBT acceptance in the sampled SMEs.
Policy makers, industry leaders, and small business operators wishing to understand some of the reasons why certain SMEs in the country lag in the adoption of IEBT and related technologies can benefit from the information provided in this study. The study also alerted the attention of local IS vendors and financial institutions to what can be done to strengthen IS adoption in Canadian small businesses.
A handful of previous research in Canada has researched IEBT adoption; however, some of these studies are dated. A such, this current investigation of IEBT acceptance in a less endowed part of the country is timely and welcoming; it also serves to complement other prior studies in the country and elsewhere. A scan of the extant literature indicates that no previous study in the country has modeled some of the factors (e.g. the availability of financial support) as were used herein. The inclusion of such a factor enriches insight in this area of study.
This article aims to seek to provide a performance measurement scale for customer relationship management (CRM) software. The CRM concept is wide, yet prior literature…
This article aims to seek to provide a performance measurement scale for customer relationship management (CRM) software. The CRM concept is wide, yet prior literature offers only specific approaches. This scale goes beyond specific scenarios, to cover the various perspectives on CRM and provide quantitative validation of the measures.
This paper describes the complete process for conceptualizing and operationalizing this reflective second-order construct, including a thorough literature review, qualitative research and a quantitative study with 208 companies that have implemented CRM software.
Three main, interconnected constructs emerge to measure CRM software performance: customer life cycle, firm performance and operational performance. Retention, loyalty and satisfaction indicators form the customer life-cycle dimension. Firm performance refers to market share, efficiency, product adaptation, and new product launch indicators. The operational dimension includes improvement in sales performance, marketing campaigns, customer service and analysis of customer information.
This scale guides every element involved in CRM software implementation, toward a common objective.
The CRM scale supports CRM software industry players and firms that intend to implement CRM software. The three model constructs provide guidelines about which improvements should be noted with a CRM implementation.
This scale help the companies who intend to implement CRM software conduct their agreement with the other parts involved (consultants, software developers and the firm).
This paper meets an identified need, namely, to provide a CRM software performance measurement scale. The huge, unique sample is exclusive and obtained from a dedicated CRM software developer.
Describes an approach automatically to classify and evaluate publicly accessible World Wide Web sites. The suggested methodology is equally valuable for analyzing content…
Describes an approach automatically to classify and evaluate publicly accessible World Wide Web sites. The suggested methodology is equally valuable for analyzing content and hypertext structures of commercial, educational and non‐profit organizations. Outlines a research methodology for model building and validation and defines the most relevant attributes of such a process. A set of operational criteria for classifying Web sites is developed. The introduced software tool supports the automated gathering of these parameters, and thereby assures the necessary “critical mass” of empirical data. Based on the preprocessed information, a multi‐methodological approach is chosen that comprises statistical clustering, textual analysis, supervised and non‐supervised neural networks and manual classification for validation purposes.