Earticle

e-Government is an innovative phenomenon around the globe for refurbishing public administration. Research to date, however, has been deficient in empirical studies of the factors that emerge out of the interplay of structure and human interactions responsible for successful implementation of e-Government projects. From the perspective of structuration theory, this study examines and explains the impact of this interplay in the implementation of an e-Government system, eSeva for local administration at one of the Indian state, The results suggest that the success of implementation of e-Government projects can be conceptualized as the outcome of persisting constructive interrelationships among the human, programmatic and institutional elements of e-Government and the critical learning and adaptation as a result of efforts at the structuration level.

Conventional Support Vector Machines (SVMs) have been utilized as classifiers for binary classification problems. However, certain real world problems, including corporate bond rating, cannot be addressed by binary classifiers because these are multi-class problems. For this reason, numerous studies have attempted to transform the original SVM into a multiclass classifier. These studies, however, have only considered nominal classification problems. Thus, these approaches have been limited by the existence of multiclass classification problems where classes are not nominal but ordinal in real world, such as corporate bond rating and multiclass customer classification. In this study, we adopt a novel multiclass SVM which can address ordinal classification problems using ordinal pairwise partitioning (OPP). The proposed model in our study may use fewer classifiers, but it classifies more accurately because it considers the characteristics of the order of the classes. Although it can be applied to all kinds of ordinal multiclass classification problems, most prior studies have applied it to finance area like bond rating. Thus, this study applies it to a real world customer level classification case for implementing customer relationship management. The result shows that the ordinal multiclass SVM model may also be effective for customer level classification.

As an engineered product, a software package has multiple dimensions that must be designed judiciously to enhance its competitive viability. Functionality, reliability and price are three such common dimensions. However, many software products are sold as bundles of individual components and the competitive impact of bundling has received less attention in the research literature. In this paper, we examine the implications of software vendors using bundling as an element of competitive strategy. A game theoretic model of the actions of an incumbent and a new entrant is developed and the impact on vendor and consumer welfare is analyzed. Numerical experiments with the model show that (i) increasing bundle size is an effective strategy for the incumbent to increase its payoff at the cost of the entrant's payoff and consumer surplus, especially when the entrant's quality is low (ii) in the presence of bundling, the entrant can still increase its own payoff and consumer surplus at the cost of the incumbent's payoff, by increasing product quality up to the level that best segments market demand with the incumbent and (iii) an increase in bundle size by the incumbent, or an increase in quality by the entrant, can both result in an increase of total surplus. Similar results are observed in a related case where the entrant offers free software bundles. Our results provide insights into how software vendors may strategically use bundling and quality as additional product dimensions in order to stay competitive in the market. These results also inform the competing vendors of the impact of bundling related public policy actions on their respective payoffs.

Personalized services directly and indirectly acquire personal data, in part, to provide customers with higher-value services that are specifically context-relevant (such as place and time). Information technologies continue to mature and develop, providing greatly improved performance. Sensory networks and intelligent software can now obtain context data, and that is the cornerstone for providing personalized, context-specific services. Yet, the danger of overflowing personal information is increasing because the data retrieved by the sensors usually contains privacy information. Various technical characteristics of context-aware applications have more troubling implications for information privacy. In parallel with increasing use of context for service personalization, information privacy concerns have also increased such as an unrestricted availability of context information. Those privacy concerns are consistently regarded as a critical issue facing context-aware personalized service success. The entire field of information privacy is growing as an important area of research, with many new definitions and terminologies, because of a need for a better understanding of information privacy concepts. Especially, it requires that the factors of information privacy should be revised according to the characteristics of new technologies. However, previous information privacy factors of context-aware applications have at least two shortcomings. First, there has been little overview of the technology characteristics of context-aware computing. Existing studies have only focused on a small subset of the technical characteristics of context-aware computing. Therefore, there has not been a mutually exclusive set of factors that uniquely and completely describe information privacy on context-aware applications. Second, user survey has been widely used to identify factors of information privacy in most studies despite the limitation of users’ knowledge and experiences about context-aware computing technology. To date, since context-aware services have not been widely deployed on a commercial scale yet, only very few people have prior experiences with context-aware person-alized services. It is difficult to build users’ knowledge about context-aware technology even by increasing their understanding in various ways: scenarios, pictures, flash animation, etc. Nevertheless, conducting a survey, assuming that the participants have sufficient experience or understanding about the technologies shown in the survey, may not be absolutely valid. Moreover, some surveys are based solely on simplifying and hence unrealistic assumptions (e.g., they only consider location information as a context data). A better understanding of information privacy concern in context-aware personalized services is highly needed. Hence, the purpose of this paper is to identify a generic set of factors for elemental information privacy concern in context-aware personalized services and to develop a rank-order list of information privacy concern factors. We consider overall technology characteristics to establish a mutually exclusive set of factors. A Delphi survey, a rigorous data collection method, was deployed to obtain a reliable opinion from the experts and to produce a rank-order list. It, therefore, lends itself well to obtaining a set of universal factors of information privacy concern and its priority. An international panel of researchers and practitioners who have the expertise in privacy and context-aware system fields were involved in our research. Delphi rounds formatting will faithfully follow the procedure for the Delphi study proposed by Okoli and Pawlowski. This will involve three general rounds: (1) brainstorming for important factors; (2) narrowing down the original list to the most important ones; and (3) ranking the list of important factors. For this round only, experts were treated as individuals, not panels. Adapted from Okoli and Pawlowski, we outlined the process of administrating the study. We performed three rounds. In the first and second rounds of the Delphi questionnaire, we gathered a set of exclusive factors for information privacy concern in context-aware personalized services. The respondents were asked to provide at least five main factors for the most appropriate understanding of the information privacy concern in the first round. To do so, some of the main factors found in the literature were presented to the participants. The second round of the questionnaire discussed the main factor provided in the first round, fleshed out with relevant sub-factors. Respondents were then requested to evaluate each sub factor’s suitability against the corresponding main factors to determine the final sub-factors from the candidate factors. The sub-factors were found from the literature survey. Final factors selected by over 50% of experts. In the third round, a list of factors with corresponding questions was provided, and the respondents were requested to assess the importance of each main factor and its corresponding sub factors. Finally, we calculated the mean rank of each item to make a final result. While analyzing the data, we focused on group consensus rather than individual insistence. To do so, a concordance analysis, which measures the consistency of the experts’ responses over successive rounds of the Delphi, was adopted during the survey process. As a result, experts reported that context data collection and high identifiable level of identical data are the most important factor in the main factors and sub factors, respectively. Additional important sub-factors included diverse types of context data collected, tracking and recording functionalities, and embedded and disappeared sensor devices. The average score of each factor is very useful for future context-aware personalized service development in the view of the information privacy. The final factors have the following differences comparing to those proposed in other studies. First, the concern factors differ from existing studies, which are based on privacy issues that may occur during the lifecycle of acquired user information. However, our study helped to clarify these sometimes vague issues by determining which privacy concern issues are viable based on specific technical characteristics in context-aware personalized services. Since a context-aware service differs in its technical characteristics compared to other services, we selected specific characteristics that had a higher potential to increase user’s privacy concerns. Secondly, this study considered privacy issues in terms of service delivery and display that were almost overlooked in existing studies by introducing IPOS as the factor division. Lastly, in each factor, it correlated the level of importance with professionals’ opinions as to what extent users have privacy concerns. The reason that it did not select the traditional method questionnaire at that time is that context-aware personalized service considered the absolute lack in understanding and experience of users with new technology. For understanding users’ privacy concerns, professionals in the Delphi questionnaire process selected context data collection, tracking and recording, and sensory network as the most important factors among technological characteristics of context-aware personalized services. In the creation of a context-aware personalized services, this study demonstrates the importance and relevance of determining an optimal methodology, and which technologies and in what sequence are needed, to acquire what types of users’ context information. Most studies focus on which services and systems should be provided and developed by utilizing context information on the supposition, along with the development of context-aware technology. However, the results in this study show that, in terms of users’ privacy, it is necessary to pay greater attention to the activities that acquire context information. To inspect the results in the evaluation of sub factor, additional studies would be necessary for approaches on reducing users’ privacy concerns toward technological characteristics such as highly identifiable level of identical data, diverse types of context data collected, tracking and recording functionality, embedded and disappearing sensor devices. The factor ranked the next highest level of importance after input is a context-aware service delivery that is related to output. The results show that delivery and display showing services to users in a context-aware personalized services toward the anywhere-anytime-any device concept have been regarded as even more important than in previous computing environment. Considering the concern factors to develop context aware personalized services will help to increase service success rate and hopefully user acceptance for those services. Our future work will be to adopt these factors for qualifying context aware service development projects such as u-city development projects in terms of service quality and hence user acceptance.

Software as a service (SaaS) is one of the most-talked about trends in IT. Unlike traditional perpetual licensing model, software applications are sold on subscription bases and services are provided over web by the vendors. It is said that SaaS can make vendors to invest more on R&D than on marketing while offering its customers better quality software applications at lower costs. By empirically comparing vendors providing their software applications either by SaaS or by traditional perpetual licensing model, we examine whether or not SaaS really increases overall customer benefits in terms of cost efficiency, software quality, and customization. We show that SaaS may not provide better quality or cost efficient software applications than perpetual licensing does. Then we provide two practical tools which are useful for customers to evaluate whether SaaS is better than perpetual licensing for the purposes of software applications they want to adopt.

Social communications using information and communication technologies (ICT) for social interactions have been making a significant impact on task performance in organizations. However, most of the existing studies on ICT (e.g., telephone and email) have only focused on technical improvement of communication efficiencies (e.g., information exchange and storage). In this paper, we claim that ICT may be another alternative source of knowledge creation that enables employees to work, find solutions, and achieve their goals faster and better. We investigate the impact of ICT in terms of both tasks and social aspects with knowledge creation as task performance. Also, we investigate the moderating effect of media synchronicity on these relationships. This study contributes to the understanding of contemporary communications media usage and its performance in organizations. We collected and analyzed survey data of 248 company employees, using PLS. The results indicate that task urgency and social influence directly affect ICT usage, and even knowledge creation. Also the media synchronicity moderates the relationship between the characteristics of a given task and ICT usage and the relationship between ICT usage and knowledge creation. Theoretical and practical implications of these findings are also discussed in the paper.

Ontologies have been adopted in various business and scientific communities as a key component of the Semantic Web. Despite the increasing importance of ontologies, ontology developers still perceive construction tasks as a challenge. A clearly defined and well-structured methodology can reduce the time required to develop an ontology and increase the probability of success of a project. However, no reliable knowledge- engineering methodology for ontology development currently exists; every methodology has been tailored toward the development of a particular ontology. In this study, we developed a Graduation Screen Ontology (GSO). The graduation screen domain was chosen for the several reasons. First, the graduation screen process is a complicated task requiring a complex reasoning process. Second, GSO may be reused for other universities because the graduation screen process is similar for most universities. Finally, GSO can be built within a given period because the size of the selected domain is reasonable. No standard ontology development methodology exists; thus, one of the existing ontology development methodologies had to be chosen. The most important considerations for selecting the ontology development methodology of GSO included whether it can be applied to a new domain; whether it covers a broader set of development tasks; and whether it gives sufficient explanation of each development task. We evaluated various ontology development methodologies based on the evaluation framework proposed by Gómez-Pérez et al. We concluded that METHONTOLOGY was the most applicable to the building of GSO for this study. METHONTOLOGY was derived from the experience of developing Chemical Ontology at the Polytechnic University of Madrid by Fernández-López et al. and is regarded as the most mature ontology development methodology. METHONTOLOGY describes a very detailed approach for building an ontology under a centralized development environment at the conceptual level. This methodology consists of three broad processes with each process containing specific sub-processes: management (scheduling, control, and quality assurance); development (specification, conceptualization, formalization, implementation, and maintenance); and support process (knowledge acquisition, evaluation, documentation, configuration management, and integration). An ontology development language and ontology development tool for GSO construction also had to be selected. We adopted OWL-DL as the ontology development language. OWL was selected because of its computational quality of consistency in checking and classification, which is crucial in developing coherent and useful ontological models for very complex domains. In addition, Protégé-OWL was chosen for an ontology development tool because it is supported by METHONTOLOGY and is widely used because of its platform-independent characteristics. Based on the GSO development experience of the researchers, some issues relating to the METHONTOLOGY, OWL-DL, and Protégé-OWL were identified. We focused on presenting drawbacks of METHONTOLOGY and discussing how each weakness could be addressed. First, METHONTOLOGY insists that domain experts who do not have ontology construction experience can easily build ontologies. However, it is still difficult for these domain experts to develop a sophisticated ontology, especially if they have insufficient background knowledge related to the ontology. Second, METHONTOLOGY does not include a development stage called the "feasibility study." This pre-development stage helps developers ensure not only that a planned ontology is necessary and sufficiently valuable to begin an ontology building project, but also to determine whether the project will be successful. Third, METHONTOLOGY excludes an explanation on the use and integration of existing ontologies. If an additional stage for considering reuse is introduced, developers might share benefits of reuse. Fourth, METHONTOLOGY fails to address the importance of collaboration. This methodology needs to explain the allocation of specific tasks to different developer groups, and how to combine these tasks once specific given jobs are completed. Fifth, METHONTOLOGY fails to suggest the methods and techniques applied in the conceptualization stage sufficiently. Introducing methods of concept extraction from multiple informal sources or methods of identifying relations may enhance the quality of ontologies. Sixth, METHONTOLOGY does not provide an evaluation process to confirm whether WebODE perfectly transforms a conceptual ontology into a formal ontology. It also does not guarantee whether the outcomes of the conceptualization stage are completely reflected in the implementation stage. Seventh, METHONTOLOGY needs to add criteria for user evaluation of the actual use of the constructed ontology under user environments. Eighth, although METHONTOLOGY allows continual knowledge acquisition while working on the ontology development process, consistent updates can be difficult for developers. Ninth, METHONTOLOGY demands that developers complete various documents during the conceptualization stage; thus, it can be considered a heavy methodology. Adopting an agile methodology will result in reinforcing active communication among developers and reducing the burden of documentation completion. Finally, this study concludes with contributions and practical implications. No previous research has addressed issues related to METHONTOLOGY from empirical experiences; this study is an initial attempt. In addition, several lessons learned from the development experience are discussed. This study also affords some insights for ontology methodology researchers who want to design a more advanced ontology development methodology.

Rapid development of information technology has generated a new industry and market. In particular, network technology such as the Internet and other computer networks made transaction activities switched from traditional offline commerce to e-commerce. Among them, digital content is bit-based object which is created and distributed through electronic environment. In particular, many entertainment contents such as the music, the movies, and the computer game softwares are main products. Although digital content commerce has high potential demand, it lacks the consideration about the factor related to maintaining existing customer such as customer loyalty and switching costs. There has been a number of research on customer loyalty and other factors affecting it in the traditional electronic commerce environment, but there is a lack of research which examines the characteristics of digital content. The study about the effect of switching costs on customer loyalty in digital content commerce is necessary because the customers of digital content commerce market are from those of other e-commerce market or traditional offline commerce market. In addition, customer loyalty and switching costs are important factors because they may build up greater customer retention. For that reason, this study focused on examining the relationships among switching costs, antecedents for switching costs, and customer loyalty in online digital music service industry. The study has three major purposes: (1) to find antecedents of switching costs on digital content commerce and examine effect of antecedents for switching costs; (2) to identify effect of switching costs on customer loyalty in digital content commerce and examine moderating effects of alternative attractiveness; (3) to identify the differences of antecedents for switching costs by contents transmission type(streaming service and downloading service). And, the online digital music service industry is selected in this study since there are many users and transactions incurring. To accomplish these purposes, a survey questionnaire was developed and distributed to 256 informants. Survey instrument was developed based on previous research and pre-established survey items. Total of 206 surveys are collected and used in the data analysis. Among the respondents, 56.8% is male and 43.2% is female. Also, 86 responses were streaming service user group and120 responses were download service user group. These data was analyzed using regression analysis. Major findings of empirical analysis can be summarized as follows. First, switching costs have positive effect on customer loyalty in digital content commerce environment. Second, the influence of switching costs on customer loyalty increases under conditions of high alternative attractiveness. Third, DRM convenience and breadth of use have positive effect on switching costs. The findings imply that the digital content provider should pay more attention to switching costs in addition to customer satisfaction in order to attract customers. Also, increasing the convenience of DRM use by securing the convenience of user interface and expanding the support device and increasing the service use scope by providing diverse value-added service helps to create a switching barrier. The result of the study can become a practical use in marketing strategy for maintaining existing customer. In particular, switching barrier is very important under conditions of high competition in the online music service market. This study can be used as a basis for further studies about customer retention in digital content commerce.