The Dynamics of Real-Time Online Information and Disease Progression: Understanding Spatial Heterogeneity in the Relationship

The re-emergence of infectious diseases such as measles and polio is creating logistics challenges for the state authorities to curb their spread and contain them. (CL, 2015) Real-time surveillance of infectious diseases is important to detect possible epidemics in advance to prevent shortages of medications (FDA, 2018). The outbreak of an infectious disease creates panic in the community and is accompanied by a sudden increase in the online interest in knowing more about the disease and its symptoms. Prior studies have found a strong relationship between web-based information and disease outbreak but the influence of dynamics of web-based information in real-time is often not considered (Zhang, 2017). The dynamics or rate of change of the online interest in a disease can inform or misinform about perspective cases of the disease in a region. Oftentimes, especially in this connected world individuals overreact to the situation which may send spurious online signals regarding the disease progression. Hence, we study the relationship between the dynamics of online information and the infectious disease outbreak. We also investigate if this relationship could be influenced by regional demographic factors. We analyze weekly online interest dynamics for five infectious diseases over a period of three years across 50 states of the United States. We control for several factors (including weather, demographics, and travelers) and utilize hierarchical functional data models to incorporate real-time dynamics and clustering at the regional level. Preliminary findings suggest that online interest dynamics have a significant relationship with disease outbreak and the effect is segregated at the regional level. These findings are important to develop a system for real-time surveillance and account for the influence of heterogonous online interest during an endemic outbreak

Do Pair Programming Approaches Transcend Coding? Measuring Agile Attitudes in Diverse Information Systems Courses

Agile methods and approaches such as eXtreme programming (XP) have become the norm for successful organizations not only in the software industry but also for businesses seeking to improve internal software processes. Pair programming in some form is touted as a major functionality and productivity improvement. However, numerous studies show that simply placing two programmers side by side in front of a single computer screen is not enough. We must look at other factors such as programmer expertise, project preparation, and perceived solution quality to understand pair programming’s promises and pitfalls. In our study, we apply tailored programming challenges to a multifaceted group of first-year through senior Information Systems (IS) and non-IS majors to analyze how participant attitudes and perceived benefits of pair programming change from pre- to post-study, as well as determine whether the quality and functionality of the solutions differ across education levels and disciplines. Our findings show a strong interaction effect of gender and major composition (CIS vs. non-CIS majors) in all four dimensions of the ATMI attitude scale. Findings also suggest that experience in problem solving and solution formation are more important than prior specific domain knowledge. Finally, participants’ perceived ability, sense of accomplishment, and completion of the assigned work, regardless of background or demographic, determined their performance outcome on the pair-programming tasks, which suggests that not all forms of attitude and perceived benefits contribute to the performance outcome

The Role of Organizational Support and Problem Space Complexity on Organizational Performance - A Business Intelligence Perspective

Background: In today’s business environment, BI systems are frequently bundled together or built with a good connection to existing ERP systems. Businesses implementing BI alone may not receive its full benefit if the necessary support structure and a fit of it to its problem domain are not in place. Methods: In this study, we explored organizational support and problem space complexity in three models (base, direct-effect and moderation models) to study BI’s effect on organizational performance. Results: The moderation model explains the most variance of the dependent variable – organizational performance. Problem space complexity had both a direct effect on organizational performance and the relationship between BI implementation and this dependent variable. Organizational support along with its first-order factors did not have statistical significance on organizational performance. Conclusions: The resulting moderation model provides the best explanation of organizational performance among the three models tested. The confirmed effects of problem space complexity show that matching BI implementation to the complexity of the problem in hand drives business performance. Organizational support may not be consistently required throughout all stages of BI adoption. As the BI literature has shown, the effect of organizational support on BI implementation could very much be on individuals in areas of affective commitment, extra-role performance and end-user satisfaction. Our work provides the beginning empirical evidence that such effects on individuals may not always result in business performance. Available at: https://aisel.aisnet.org/pajais/vol12/iss1/1

Dissonance Reduction Strategies in Ride-Sharing Apps- A Case of Uber

Ride-sharing apps have both positive and negative impact in our daily lives. To study the negative impacts especially personal safety issues, this study explores the reaction of ride-sharing app users to such safety issues. We contextualize our study using a scenario-based survey. We found empirical support to all the hypotheses by surveying 421 individuals. This study contributes to the information systems literature in providing ways to apply dissonance reduction techniques that are a strong predictor of satisfaction. In addition, this study also addresses the safety issues faced by riders using ride-sharing apps and how co- creation would help address these issues

Website Usability: A Re-Examination through the Lenses of ISO Standards

The original conceptualization of usability was ease of use, this was later expanded into a multi-dimensional construct in ISO standards and usability literature. Such an expansion is seen as an improvement, since cross-study comparison or benchmarking cannot objectively be done without a common set of usability components being defined. The current issue lies in how these components are operationalized, measured and validated. Although ISO standards ties usability to contextual situations, recent research has started to also recognize psychographic and demographic variations within the same context. The purpose of this study is to review web site usability as it relates to ISO standards (more specifically ISO 9126, ISO 9241 and ISO/IEC 25010) and existing usability studies. Implications for researchers and practitioners are provided

Impacts of Techno-Dependence in The Mobile Instant Messaging Environment

Mobile Instant Messaging (MIM) services such as LINE, WhatsApp, Facebook Messenger and WeChat have already established a mobile communication environment that extends beyond words and sounds. As MIM provides an effective way to communicate, it can improve workplace efficiency, whether within an organization or among offices spread around the world. Nowadays, MIM has been widely accepted as both a social and work tool. The social interaction overload generated by SNSs contributes to emotional exhaustion. Emotional exhaustion, on the other hand, leads to dissatisfaction and discontinuous usage intentions. In the context of MIMs (since they are relative new apps), users whether are likely to experience emotional exhaustion that is generated by social interaction overload, and therefore discontinue their use of MIMs. In contrast to traditional research on IS continued use in the past which defines dependence as a routine and unconscious usage pattern. MIMs offer a communication method that is faster and easier than phone calls or SMS. It is possible that MIMs bring people closer by allowing their users to understand more of the situational matters related to their friends or family, without being limited by distance. Specifically, social-group functions offered by LINE can encourage users to join certain social groups (for instance, family, colleagues, classmates, or friends). Group members can not only discuss common topics, they can also share their “photo albums,” enabling members to enhance their sense of belonging. At the same time, they have the opportunity to feel a sense of being valued, loved, and needed. Although the mobility and accessibility of mobile devices allow users to instantly contact each other on MIMs and on real-time basis, excessive use of MIMs, or MIM techno-dependence, is likely to generate social-related stress among their users. Therefore, this research attempts to explore the possibility that MIM techno-dependency can have non-detrimental effects, and considers the positive and healthy results from MIM techno-dependency due to an increased sense of belonging. The questions explored include: do MIMs users develop a positive techno-dependence? Does this positive emotional reaction encourage MIMs users to continue their use of MIMs? Since LINE is a relative newcomer to MIM, there is still a dearth of research needed to explore issues related to using MIM as a research tool. This study considers how LINE combines a diverse range of communication approaches—such as voice, texts, maps, pictures, photos, locations, video, and audio—with a variety of community groups such as friends chat, group chat, dynamic news, and official accounts. It seems worthwhile to study characteristics of LINE’s users in order to further explore the issues related to MIM. Through the hypotheses development and a survey research on 685 LINE users, this study inferred that users make frequent use of LINE in the long-term mainly because of four kinds of techno-dependence: people, fun, information, and work. Such techno-dependence generates positive and negative consequences concurrently. On the one hand, because the user’s dependence on LINE enhances his or her belongingness through friends, colleagues, and family, this positive social and emotional reaction will make users satisfied with LINE, and thus increase continuous usage intention for LINE. On the other hand, the user’s dependence on LINE means that they experience social interaction overload resulting in emotional exhaustion. Dependence on LINE leads to users experiencing pressure from both social message overload and social demand overload, resulting in social interaction overload. This negative social and emotional reaction will cause a decrease in user satisfaction with LINE, thereby reducing the continuous usage intention of LINE. Based on these findings, we suggest that LINE-related techno-dependence can enable users to increase their sense of positive social belongingness, but can also cause negative social interaction overload. It is concluded that the consequences of techno-dependence are characterized by both positive and negative emotions. Users’ evaluations of LINE are simultaneously affected by positive and negative social and emotional factors

An East-West Comparison of IS Professionals\u27 Performance and Knowledge/Skills: An Empirical Study of USA vs Taiwan

The outsourcing literature suggests that the capabilities of partners involved in outsourcing or off-shoring projects are a crucial factor for the success of the projects. This paper studies the capabilities of IS professionals from the USA and Taiwan on issues such as performance, time spent on IS related activities, and required skills vs. skills possessed. The goal is to determine the differences among these two groups in their core IT capabilities and to offer practitioners an empirical reference for carrying out their IS development decisions. Findings from the current study indicate that Taiwanese professionals tended to focus more on the technical issues and hardware/software details, while American professionals were proficient in business modeling, inter-personal communication, and end-user training. These findings present an opportunity for partnership between the two countries to develop low-cost but high quality IS projects. Other business implications are also discussed

HOTEL RECOMMENDATION SYSTEM BASED ON REVIEW AND CONTEXT INFORMATION: A COLLABORATIVE FILTERING APPRO

In most organizations, knowledge sharing is often lacking when it comes to business systems success. This paper investigates factors affecting business systems success in Saudi organisations. Data were collected from private organisations in Saudi Arabia and Partial Least Square approach has been applied to analyse the data. The results show that organisational culture influence knowledge sharing towards business systems success. In addition, both intrinsic motivation and perceived usefulness has positive influence on business system success. This indicates that business system success is built upon the concept of knowledge sharing and user motivation

Cyberbullying Detection on Social Network Services

Social networks such as Facebook or Twitter promote the communication between people but they also lead to some excessive uses on the Internet such as cyberbullying for malicious users. In addition, the accessibility of the social network also allows cyberbullying to occur at anytime and evoke more harm from other users’ dissemination. This study collects cyberbullying cases in Twitter and attempts to establish an auto-detection model of cyberbullying tweets base on the text, readability, sentiment score, and other user information to predict the tweets with harassment and ridicule cyberbullying tweets. The novelty of this study is using the readability analysis that has not been considered in past studies to reflect the author\u27s education level, age, and social status. Three data mining techniques, k-nearest neighbors, support vector machine, and decision tree are used in this study to detect the cyberbullying tweets and select the best performance model for cyberbullying prediction