Qiqi Jiang

Enhancing user-game engagement through software gaming elements

User-game engagement is vital for building and retaining a customer base for software games. However, few studies have investigated such engagement during gameplay and the impact of gaming elements on engagement. Drawing on the theoretical foundation of engagement, we meticulously deduced two cognitive-related gaming elements of a software game, namely, game complexity and game familiarity, and argued that these elements have individual and joint effects on user-game engagement. This research adopted multimethod empirical investigations to validate our conceptions. The first investigation used electroencephalography and a self-report survey to study quantitatively the cognitive activities of user-game engagement. The second investigation adopted the qualitative interview method to triangulate the findings from the quantitative data. This research contributes to theory in two ways, namely, conceptualizing and empirically examining user-game engagement as well as theorizing and demonstrating how the two gaming elements affect user-game engagement. This work contributes to the gaming practice by providing a set of design principles for gaming elements.

Knowledge seekers’ and contributors’ reactions to recommendation mechanisms in knowledge management systems

We examined the behavior of knowledge seekers and contributors to an internal Knowledge Management System (KMS) in a multinational organization. The system has two selection mechanisms, based on semantic algorithms and user ratings. The first utilizes an algorithm to ‘measure’ the quality of knowledge contributions and ranks them accordingly, while the second averages the ratings that knowledge items receive from KMS users. Building on appraisal theory, we found that knowledge seekers and contributors reacted differently to the two mechanisms. The rating-based rankings positively influenced knowledge seekers’ tendency to access, comment on, and spread the knowledge shared in the KMS, while the algorithm-based ranking positively influenced knowledge contributors’ to continue sharing knowledge via the system. Moreover, shorter (or longer) time delay between the time that the knowledge was shared and the time when knowledge contributors received their first comments seemed to positively (or negatively) influence the contributors’ tendency to continue sharing knowledge via the KMS. Our study adds to the existing KMS literature by investigating knowledge seekers’ and contributors’ reactions to the two different knowledge recommendation mechanisms, and recommends that managers understand the importance of implementing algorithm-based rankings in their KMS as well as the simpler and more commonly adopted rating-based ranking.

Remarkable advocates

This study investigates crowdfunding projects using their advocates.Crowdfunding projects could benefit from leveraging remotely located advocates.Social capital accumulated from advocates social networking site (SNS) is conducive to the success of the project.Findings support interaction effect between geographic distance and social capital.Several practical suggestions for crowdfunding entrepreneurs are provided. This study investigates the advocates of crowdfunding projects. Advocates refer to individuals who have invested in a project, and the information of such endorsement is spread through their social networks. By using a combined set of sizable data, this research empirically examines the relationships between two attributes of advocates, namely their geographical distance and social capital, and funding performance. Results reveal that higher funding can be secured with advocates who are (1) of further geographical distance and (2) of higher social capital. Additionally, the relationship between advocates social capital and funding performance is further enhanced with a lower geographical propinquity.

Understanding Chinese online users and their visits to websites: Application of Zipf's law

Competition for consumers to visit company websites has intensified in recent years. An important indicator of website popularity (and consequent survival) is the extent to which the website can draw consumer visits vis-a-vis other websites. A majority of the current understanding on consumer visits is limited to a single website, and leaves little knowledge on the performance of one website compared with others. In tracking the Internet usage behavior of 200 individuals in Mainland China for 30 consecutive days, we applied Zipfs law to identify the divergence points separating popular websites from non-popular ones. Two measurements were used, namely, visit traffic (number) and visit engagement (time spent). We observed that 94.87% of the entire visit traffic is devoted to 15.08% of all visited websites, whereas 84.63% of engagements are on the top 6.16% visited websites. These findings suggest that few websites accounted for the bulk of online traffic and time. Further, we segmented the dataset based on two key proxy variables of user demographics, which are gender and occupation. The findings on visit traffic remained salient after considering user segments, but the findings on website engagement varied across different user segments. Our further analysis, which categorized the visited websites by their main service, revealed the type of Internet users attracted to popular websites.

Embedding the Social Features into E-learning System: A Review

E-learning has received considerable attentions in both universities and enterprises. However, a few related studies have advocated the benefits of social features as an important factor of E-learning but have not explored much further. In this work, we utilize social support theory to argue that embedding the social features into e-learning system is necessary and appropriate. Collectively, potential direction of e-learning has been simple summarized from theoretical and practical prospect. We hope our reviews on current literatures can benefit both scholars and practitioners.

Accelerating Individual Innovation: Evidence from a Multinational Corporation

With the understanding that individual innovativeness plays an important role in organizations, both practitioners and researchers are interested in finding ways to promote individual innovation. Based on the theoretical lens of Structural Holes Theory and Social Cognitive Theory, we examined the impact of network positions, degree of participation and social interaction on individual innovativeness based on the archival data of an organization’s online system. The results reveal that individuals who have more structural holes contribute more innovative ideas in the online community, and more responding from peers encourages more future innovation contribution. Implications for research and practice are discussed.

Mobile Application Development in FLOSS Platform: A Collaborative Network Approach

We are deluged by wide variety of mobile applications (thereafter terms as mobile apps) to run on our mobile devices such as smartphones and tablets. However, few studies have been conducted to investigate the issue of how mobile applications are developed in academia so far. In order to bridge such gap, we collected data on mobile application development projects from the largest FLOSS (Free and open-source software) platform, i.e., SourceForge, longitudinally. Four key indicators, graph density, reciprocity, modularity, and dyad census asymmetry, which had been drawn from previous social network literatures, were adopted to investigate the collaborative network. We found that the interactive collaboration was especially important for mobile application development process. Developers formed centralized/mutual structure for collaboration instead of several collaborative subdivisions.