Xunhua Guo

Impact of Perceived Fit on E-Government User Evaluation: A Study with a Chinese Cultural Context

Based on information technology adoption theories and considering Chinese cultural characteristics, this article proposes a user centric IT/IS evaluation model composed of three determinants, namely perceived usefulness, perceived ease of use, and perceived fit, for investigating the e-government systems application and management in China. By empirically validating the model with survey data, it is demonstrated that the perceived fit has significant impacts on the end users’ evaluation towards e-government systems, due to the special element of Hexie in the Chinese culture. The results also indicate that the reasons for failures in e-government systems application in China largely lie in the lack of fit, which may root in the long power distance characteristic of the Far Eastern culture. The findings will provide scholars and practitioners with better understanding of the user evaluation regarding e-government systems in a Chinese cultural context.

Why adoption and use behavior of IT/IS cannot last?--two studies in China

It is often observed in China that the user acceptance of a new information technology starts satisfactorily well when it is strongly promoted or even enforced to be used, but declines sharply after the initial stage. Based on an extended model derived from the Technology Acceptance Model (TAM), this paper presents two studies in academic and governmental contexts respectively to analyze such phenomena from a post-adoption perspective. Results from structured equation model (SEM) analyses demonstrate the ability of the model to interpret the IT acceptance behavior of Chinese users both during and after the initial stage. It is then inferred that the initial rise of user acceptance is usually driven by mandatory instructions due to the managerial characteristics of long power distance in Chinese organizations, while the drop in the second period is caused by changes that occur in some of the recognition factors in the model, which may reflect the lack of fit between technology and work style. In the two specific cases studied in the paper, the lack of compatibility and facilitating conditions made the user acceptance decline after the initial period when the effects of training and mandatory instructions faded away.

Internet diffusion in Chinese companies

The Internet is increasingly indispensable to national economies worldwide. Here, we focus on the Internet diffusion process in Chinese businesses and its link to the general growth of IT spending throughout the Chinese economy. Our results are based on our 10-year investigation of IT adoption in Chinese companies and industry-specific patterns of Internet diffusion and related IT spending growth. IT applications in China were introduced relatively late in Internet evolution compared to those in the developed countries, forcing business managers to contend with a lack of experience, know-how, and infrastructure. This late start has also meant that Chinese companies are able to choose from relatively more advanced technologies, learn from the experience of others, and be less bothered by the problems associated with legacy systems. In addition, because China generally uses IT differently from other countries, it is worth investigating the process through which Chinese companies adopt new technology, as well as any patterns that have emerged within it, so as to better understand how IT affects the overall Chinese economy.

IDT-TAM integrated model for IT adoption

Two classical theories, the technology acceptance model (TAM) and the innovation diffusion theory (IDT), were integrated into a model for analyzing individual information technology (IT) adoption behavior. In this IDT-TAM framework, the perceived characteristics of innovation are categorized as subjective evaluation, objective conditions, and interaction factors. The cognitive mechanisms that drive user IT acceptance are analyzed based on the patterns through which these characteristics influence individual user IT adoption behavior. The model was tested using an empirical survey regarding the adoption and use of e-mail in China. Results from a structural equation model analysis illustrate that the model provides meaningful insights for understanding, explaining, and predicting the IT adoption behavior of Chinese users.

Extended Information Technology Initial Acceptance Model and Its Empirical Test

Abstract Based on the literature on the technology acceptance model (TAM) and related efforts in technology adoption research, this paper proposed an extended model for analyzing initial IT acceptance behavior of Chinese users. To empirically test the model, we conducted a survey regarding the recognition and adoption of an English e-learning system in the freshmen of a business school. Results from structural equation model (SEM) analyses illustrated that most of the factors in the proposed model have direct or indirect significant influence on both short-term and long-term intention of use. Therefore, it was demonstrated that the model possesses the ability to interpret the initial IT acceptance behavior of individual Chinese users. Grounded on the results, future work will be focused on longitudinal studies.

Key issues in information systems management in China

Purpose – To reveal and analyze the key issues concerning information systems management in Mainland China.Design/methodology/approach – Based on data collected from 286 Chinese companies, 12 top key issues in information systems management in Mainland China are ranked and compared with the results of an earlier study, as well as those from western countries.Findings – While the top three critical issues remain unchanged, largely due to the centralized decision‐making mechanism, mandatory management style, and less experience of IT/IS applications, there are distinguishable changes that took place in the past few years. Furthermore, there are different results between different sectors of companies, reflecting respective characteristics and historical development processes of the sectors.Research limitations/implications – Extended data and measures are required for in‐depth investigation in specific individual industries.Practical implications – The study could be helpful for understanding the situations...

Prediction uncertainty in collaborative filtering

Personalized product ranking provides support to the decision making of online consumers and helps improve their satisfaction, since consumers always face a large volume of choices when they are shopping online. Recommender systems with collaborative filtering techniques are commonly used for this purpose, wherein products are ranked according to their predicted ratings. However, this kind of ranking approaches (namely, Ranking by Collaborative Filtering, RCF for short) have generally ignored the impacts of prediction uncertainty. This paper proposes a novel ranking approach called RPU (Ranking with Prediction Uncertainty), which utilizes posterior rating distribution and confidence level of prediction as two key factors for prediction uncertainty. Serving as a critical component of the generalized ranking framework, RPU aims to improve the accuracy of personalized product ranking through incorporating the uncertainty information. Experiments using real-world data of movie ratings show that RPU achieves higher ranking performance compared to traditional RCF and the results are robust in terms of sparse data. We propose a novel approach (RPU) for personalized online product ranking.RPU improves the accuracy of ranking by considering prediction uncertainty.Posterior distribution and confidence level are used as key factors for uncertainty.Experiments using real-world data show that RPU achieves advantageous performance.The results are robust in terms of sparse data.

Novice-based data collection methods for the study of IOIS: practice probes and learning communities

In response to the increasing influence of practice theory perspectives for studying organisational and inter-organisational information systems, we demonstrate that an important dilemma from this perspective for data collection methods is between authentic access to practices and the ability to thematize knowledge of practices. We propose a promising new approach to this dilemma that uses the learning experiences of novice practitioners to collect data as they are progressively enrolled in the practice, and describe two instantiations of this new approach, practice probes and learning communities.

User Attitude Towards Mandatory Use of Information Systems: A Chinese Cultural Perspective

Accumulated literature on technology adoption research has suggested that cultural factors have important impacts on the cognition and behavior of information systems users. In this paper, the authors argue that cultural factors should be treated as aggregate characteristics at the population level instead of personal attributes at the individual level. The authors also propose that theoretical models could be developed for specific cultural contexts when examining IT/IS user behavior. In this regard, a model for analyzing user attitude toward mandatory use of information systems is proposed. Drawing on generally recognized cultural characteristics of China, three factors are introduced as determinants of user attitude-leader support, technology experience, and perceived fit. An empirical study is conducted with regard to the acceptance of a mobile municipal administration system in Beijing, China, for validating the proposed model with survey data and analyzing the adoption mechanism of the target system. The moderating roles of gender, age, and education level on the model are explored by interaction effect analyses and the findings provide helpful insights for related studies in other cultural contexts.

Corporate Blogging and Job Performance: Effects of Work-related and Nonwork-related Participation

Abstract Corporate blogs are expected to facilitate communication, knowledge sharing, and collaborative innovation within organizations. However, empirical evidence has yet to be found illustrating whether and how such applications have affected job performance. Drawing upon social network theory, we postulate a conceptual model suggesting that employees’ online social relationships accumulated through work- and nonwork-related blog participation will engender different effects on job performance. The model is empirically tested using digital trace and archival data collected from two in-practice systems of a large telecommunications company. The results reveal that, in the work-related blog network, the structural and cognitive dimensions of social relationships positively affect job performance, whereas the relational dimension shows a negative influence. Meanwhile, participation in nonwork-related blog network benefits job performance for employees with a high level of performance in the previous time period, but is detrimental for other employees. The findings uncover the influencing mechanism of corporate blogging on job performance and offer practical advice for managers to better exploit the value of intraorganizational social media.