Diffusion and Evaluation of E-Government Systems: A Field Study in China

As IT/IS application in governmental organizations gains more and more attention from both academics and practitioners in China, the diffusion of e-government systems has become one of the central research issues in this fast growing economy. In this paper, we follow a conceptual model consisting of two dimensions to evaluate the IT/IS application status of Chinese governments. With a field study conducted in a local government in Beijing, the capital of China, we utilize the model to determine the e-government development level in this administrative district. Furthermore, a behavioral research model for analyzing the factors influencing e-government systems evaluation in the Chinese cultural context is proposed based on classical IT/IS adoption theories. In the light of survey data, the relationships between ease of use, usefulness, fitness, and user evaluation towards egovernment systems are validated, providing us with more in-depth understanding about the characteristics and process of e-government diffusion in such Chinese organizations

Adoption and Penetration of e-Government Systems: Conceptual Model and Case Analysis based on Structuration Theory

The study of IT/IS adoption has by far largely relied on social psychological theories which lack the capability to explain why and how systems continue to be used after they are adopted. Incorporating Structuration Theory from the sociology realm, this paper proposes a “structure-pattern” conceptual model for analyzing the adoption and application practice of e-Government systems from an organizational level perspective. Based on this model, a case study with regard to the practice of an e-Government application in Chaoyang District of Beijing City is conducted, so as to validate the interpretive ability of the model, as well as to reveal the evolution process of typical e-Government applications. Results from this case study may provide helpful insights for related practice. It is also demonstrated that Structuration Theory based Concepts and the case study methodology are promising for tackling the long existing difficulties in the traditional IT/IS research

PREDICTING CONSUMER INFORMATION SEARCH BENEFITS FOR PERSONALIZED ONLINE PRODUCT RANKING: A CONFIDENCE-BASED APPROACH

Product ranking mechanism is an important service for e-commerce that facilitates consumers’ decision-making process. This paper studies online product ranking under uncertainty. Different from previous studies that generally rank products merely based on predicted ratings, a new personalized product ranking method is proposed based on estimating consumer information search benefits and taking prediction uncertainty and confidence into consideration. Experiments using real data of movie ratings illustrate that the proposed method is advantageous over traditional point estimation methods, thus may help enhance customers’ satisfaction with the decision-making process and choices through saving their time and efforts

ADOPTION OF OPEN SOURCE SOFTWARE IN GOVERNMENTAL CONTEXT: A POSITIVISTIC CASE STUDY IN CHINA

As the rapid development of open source software (OSS) has deeply impacted global software industry, government agencies in different countries all over the world have started to realize the huge potentials of OSS application. Based on the TOE framework for organizational level IT/IS adoption, this paper proposes a conceptual model for examining the adoption of open source software in the governmental organizational context. A positivistic case study is conducted in the government agencies of Beijing, China, so as to validate and develop the proposed model, as well as to investigate the adoption status and related influence mechanisms. Findings from the analysis demonstrate the explanatory validity of the model, and provide potentially helpful insights for future practice

THEORIZING A TWO-SIDED ADOPTION MODEL FOR MOBILE MARKETING PLATFORMS

From a two-sided market perspective, this paper is aimed at proposing a conceptual model for analyzing user adoption behaviors towards mobile marketing platforms. Both the consumer side and the merchant side of the platforms are modeled based on extending classical theories with newly introduced factors reflecting cross network effects, and the two sides are integrated in the overall model which reveals the dynamic interaction between the evolution processes of the two user groups through the platform. An experimental investigation and a survey study are conducted to test the consumer side and the merchant side of the model, respectively, both using the structural equation modeling (SEM) method for statistic analysis. Results from the empirical tests demonstrate that the two-sided perspective is promising for interpreting the adoption and evolution mechanisms of mobile marketing platforms. The proposed model extends the current research theme of information systems adoption to a more comprehensive viewpoint of two-sided markets, while contributes to the literature of two-sided market theories by introducing behavioral considerations

PREDICTING CONSUMER INFORMATION SEARCH BENEFITS FOR PERSONALIZED ONLINE PRODUCT RANKING: A CONFIDENCE-BASED APPROACH

Abstract: Product ranking mechanism is an important service for e-commerce that facilitates consumers' decision-making process. This paper studies online product ranking under uncertainty. Different from previous studies that generally rank products merely based on predicted ratings, a new personalized product ranking method is proposed based on estimating consumer information search benefits and taking prediction uncertainty and confidence into consideration. Experiments using real data of movie ratings illustrate that the proposed method is advantageous over traditional point estimation methods, thus may help enhance customers' satisfaction with the decision-making process and choices through saving their time and efforts