Panel: IS has outgrown the need for reference discipline theories, or has it?

In the decade since the creation of wireless handheld devices, mobile commerce (m-commerce) has become a ubiquitous channel for accessing information and conducting business. Mobile users can now access information anytime and anywhere. Mobile advertising, retailing, and gambling are popular, and gradually the competition among mobile services providers turns fierce. Hence, some services providers adopt personalization technologies to customize content for their users. This paper explores the opportunities and challenges of the use of personalization technologies in m-commerce. Although the effectiveness of personalization on the web is well-examined, there is little work on personalization in mobile services. The debates regarding the effectiveness of personalization and technological limitations and privacy concerns motivate us to conduct focus groups with mobile users, and explore the opportunities and challenges of personalized mobile services. The focus groups findings illustrate that mobile users are very concerned about their privacy and spam. We then extract a list of personal information from the focus groups findings. This list of personal information is highly related to mobile users’ privacy concerns. We conduct an online survey to gain a better understanding of which piece of information mobile users are more willing to share with services providers and we perform a multi-dimensional scale analysis

Partial Least Squares Structural Equation Modeling Approach for Analyzing a Model with a Binary Indicator as an Endogenous Variable

In this paper, we focus on PLS-SEM’s ability to handle models with observable binary outcomes. We examine the different ways in which a binary outcome may appear in a model and distinguish those situations in which a binary outcome is indeed problematic versus those in which one can easily incorporate it into a PLS-SEM analysis. Explicating such details enables IS researchers to distinguish different situations rather than avoid PLS-SEM altogether whenever a binary indicator presents itself. In certain situations, one can adapt PLS-SEM to analyze structural models with a binary observable variable as the endogenous construct. Specifically, one runs the PLS-SEM first stage as is. Subsequently, one uses the output for the binary variable and latent variable antecedents from this analysis in a separate logistic regression or discriminant analysis to estimate path coefficients for just that part of the structural model. We also describe a method—regularized generalized canonical correlation analysis (RGCCA)—from statistics, which is similar to PLS-SEM but unequivocally allows binary outcomes

Characteristics of Advertisements and Interactivity of Videos in Online Video Websites

This research-in-progress intends to investigate the characteristics of online advertisements and online videos in the online video websites. Specifically, we investigate how advertisements with different types and sizes can cause online users to perceive the advertisements to be intrusive and lead them to closing the advertisements. Based on the psychological reactance theory, we theorize how the interactivity of online videos can strengthen the effects of perceived intrusiveness of advertisements. We will conduct an experiment to test the hypotheses and evaluate the proposed research model. This study intends to contribute to the human-computer interaction literature by investigating how advertisements’ characteristics can interact and jointly influence online users’ perception of advertisements in the online video websites. Moreover, it intends to contribute to the digital advertising literature by studying the aversive effects of advertisements in the specific context of online video websites

Opportunities and Challenges in Healthcare Information Systems Research: Caring for Patients with Chronic Conditions

To prepare for the 2030 “baby-boomer challenge”, some governments have begun to implement healthcare reforms over the past two decades. These reforms have led healthcare information systems (HIS) to evolve into a major research area in our discipline. This research area has an increasing individual, organizational, and economic impact. Due to the 2030 “baby-boomer challenge”, the number of elderly individuals continues to increase, and they may have chronic illnesses, such as eye problems and Alzheimer’s disease. Given the practical need for HIS that support chronic care, we decided to conduct a literature synthesis and identify opportunities for HIS research. Specifically, we present the chronic care model and analyze how IS researchers have discussed HIS to address the needs of patients with chronic illness. Further, we identify research gaps and discuss the research topics on HIS that future work can extend and customize to support these patients. Our results stimulate and guide future research in the HIS area. This paper has the potential to strengthen the body of knowledge on HIS

ICT Business Case Approach in Public-Sector: A Case Study of the Australian Federal Government

Many private organisations and public sector agencies develop information and communication technology (ICT) business cases, and utilise them for better ICT investment decision making. The development of ICT business cases in private sector is relatively ad hoc and compact in size. In contrast, agencies in public sector are accountable to taxpayers for their use of public funds and to ensure that public money is spent efficiently and value for money is obtained. This accountability in the public sector has cultivated a norm of increased control over public agencies’ spending and led to the requirement for a robust and evidence-based ICT business cases. So far, scant research has investigated the development and utilisation of ICT business cases in the public sector. To fill this gap, this research-in-progress proposes a study to take a closer look at ICT business case approach in the public sector and its related benefits and disadvantages perceived by ICT business case experts. Preliminary data was collected from archival data and interviews with ICT business case experts working at a professional services firm. Our preliminary findings show that a structured and complex two-pass ICT business case approach was adopted in the Australian Federal Government. This research-in-progress briefly outlines benefits and disadvantages which business case practitioners can adopt to enhance their related ICT business case approach

Transaction-Driven Personalization: The Moderating Effects of Personality Traits

With transaction-driven personalization engines online merchants can use knowledge gained from an individual customer’s past transactions to match web content to the customer’s individual interests and preferences. Prior research in this area has focused on how to maximize knowledge mined from transaction logs to generate recommendations which are highly similar to the individual’s past preferences. However, it remains an empirical question as to whether a recommendation closely matched with previous transactions is most likely to influence choice behavior? In this study, we postulate that a recommendation closely matched with previous transactions may not be the most efficient in biasing an individual. In the consideration and choice process, an individual’s personality traits play a pivotal role in moderating the effect of personalized content. Drawing on prior work in marketing, we examine two key personality traits, need for cognition and variety seeking, and explore their effects on choice behavior in the context of transaction-driven personalization. Research hypotheses are tested using 2,294 pre-selected subjects in an online field experiment based on a ring tone download website. Our findings establish that personality traits of an individual moderate content consideration and choice. Theoretical and practical implications of the findings are discussed

The Effects Of Malfunctioning Personalized Services On Users’ Trust And Behaviors

Online merchants adopt web personalization to customize web content to match online users’ needs. Prior research has only looked at the “success” side of web personalization. Little research examines the “problematic” side of web personalization. The objective of this research is to explore how “malfunctioning” personalized web services influence an online user’s trust in the personalization agent and the behavioral intention of that user. In particular, this research looks at two types of malfunctioning personalization: irrelevant recommendations and biased recommendations. We draw on trust theories to develop seven hypotheses to predict the effects of malfunctioning personalized web services. We conducted a study with a personalized music download website. We found that irrelevant recommendations led to low trust in the personalization agent’s competence and integrity, and biased recommendations led to low trust in the integrity of the personalization agent. These findings provide empirical evidence of the possible problems of malfunctioning personalization and help firms understand and quantify the challenges and limitations of incorporating web personalization in their websites

Understanding the Whistle-blowing Intention to Report Breach of Confidentiality

We examine the factors that encourage employees to whistle-blow wrongdoings in relation to confidentiality breaches. We investigate how their anticipated regret about remaining silent changes over time, how such changes influence their whistle-blowing intentions, and what employee characteristics and organizational policies moderate this relationship. Drawing on attribution theory, we develop three hypotheses. Our experiment findings show that: 1) employees’ perceptions of the controllability and intentionality (but not stability) of the wrongdoing act affect how their anticipated regret evolves, 2) anticipated regret increases employees’ whistle-blowing intentions, 3) anticipated regret has a stronger effect on whistle-blowing intentions when organizations implement policies that promote efforts to protect information confidentiality, and 4) employees with information technology knowledge have a stronger intention to whistle-blow. Theoretically, our study extends the organization security literature’s focus to individuals’ whistle-blowing and highlights an IS research agenda around whistle-blowing in relation to confidentiality breaches. Practically, it informs organizations about how to encourage employees to whistle-blow when they observe confidentiality breaches

The Role of mHealth in Facilitating Prediabetic and Diabetic Patients’ Involvement in Health Interventions

Health interventions are useful tools for preventing and alleviating diabetes which show low adherence in medical practice for prediabetic and diabetic patients. mHealth technologies have the potential to facilitate health management and improve prediabetic and diabetic patients’ self-management outcomes. Building on Social Cognitive Theory, this research-in- progress paper proposes a research model to account for the role of physician’s recognition in promoting self-management behaviors for prediabetic and diabetic patients through mHealth technologies. To test the research model, authors developed a mobile diabetes management application and cooperated with a large tertiary hospital in China. In this research-in-progress, we propose to recruit 280 subjects who are in the prediabetic or diabetic conditions. This study is expected to contribute to the research on and practice of the health interventions through mHealth technologies

Does Chatting Really Help? Tweet Analytics and Analyst Forecast Dispersion

Financial analysts use tweet analytics to prepare their forecasts, yet little information that describes how they do so exists. To address this gap, we scrutinize the associative relationships between tweets about a company’s service and the dispersion of analyst forecasts about the same company’s financial performance. We developed three sets of hypotheses. We extracted tweets related to airlines from the Twitter data from Archive Team and analyst forecast data from Institutional Brokers’ Estimate System Academic. We obtained airline-related tweets from nearly 200,000 individual Twitter users about 10 airlines during a 55-month study period and ran multiple regressions to test the associations between tweet characteristics and forecast dispersion. Our results suggest that, when more posters generate more tweets about a company’s service, analysts make less dispersed forecasts. In addition, negative (or non-verified) tweets reduce forecast dispersion to a greater extent than positive (or verified) tweets do. Theoretically, this paper confirms that Twitter can be a useful data source to provide analysts with additional information to prepare their forecasts. Practically, our findings provide empirical evidence about how Twitter data is associated with analyst forecast dispersion. We encourage stakeholders (such as analysts from small firms and individual investors) to extract data from Twitter as a supplement to market information when analyzing data