Gains and Losses in Functionality – An Experimental Investigation of the Effect of Software Updates on Users’ Continuance Intentions

Although software updates are ubiquitous in professional and private IS usage, their impact on user behaviors has received little attention in post-adoption research. Based on expectation-confirmation-theory and the IS continuance model, we investigate the effects of gaining and loosing features through updates on expert and novice users’ continuance intentions (CI). In a vignette based experiment, we find that updates which add features to software after its release increase novices’ CI above and beyond a level generated by a monolithic software package that contains the entire feature set from the beginning. With diminished CI, experts show a contrary reaction to the same update. Losing features through an update, on the other hand, severely diminishes CI for experts and novices alike. Mediation analysis reveals positive disconfirmation of previous expectations as psychological mechanism behind novices’ counter-intuitive and somewhat non-rational responses to gaining features through an update. Implications for research and practice are derived

Users’ Loyalty to Agile Information Systems

Over the past few years, across many industrial sectors, Information Systems (IS) developed with the help of agile methods have become the rule rather than the exception. Because of their high flexibility, such Agile IS development methodologies help firms to keep pace with emerging market requirements. At the same time, customers are also gaining increasing market power due to an expanding digitalization of services and products, which decreases switching barriers and increases transparency. As a result, it has become crucial for firms to develop IS that continuously provide sufficient value to customers. This is one of the main reasons why firms regularly deliver increments of Agile IS for users to update outdated software versions. By doing so, firms try to bind and engage customers lastingly to capture current and future revenue streams and stay competitive. Agile IS and software updates (that deliver increments of Agile IS to users) have been researched thoroughly, however mostly from a technical point of view. Nevertheless, because updates change a system while it is already in use, they have the potential to impact users’ beliefs, attitudes, behaviors, and in particular, loyalty to a software in the post-adoption phase. However, despite the importance of better understanding user responses to Agile IS to provide an adequate theoretical framework, research from a user’s perspective on Agile IS, and especially software updates, is still scarce. Against this backdrop, this thesis presents four empirical studies that were conducted to investigate whether and how Agile IS affect users’ loyalty to IS, to identify potential moderators, and to understand how Agile IS should be designed to facilitate potential positive effects. In these studies, increments of Agile IS are operationalized as software updates and customer loyalty as a user’s continuance intention with a system. By drawing on the IS Continuance Model in a scenario-based online experiment, the first two studies reveal empirically how Agile IS have the potential to increase user continuance intentions. Users of Agile IS show greater IS continuance intentions, despite that some functionality is provided only later on, as compared to a consistently feature-complete traditional IS. This effect is diminished somewhat when the software is introduced with an extensive feature set right from the beginning. Nevertheless, the size of an update does not seem to play a significant role. The second study reveals that this positive effect of updates only emerges if the user is not very knowledgeable regarding the software, because experts in contrast to novices seem to devalue Agile IS (their continuance intentions decrease with Agile IS in comparison to traditional IS). Additionally, the second study shows that the removal of features through updates reduces continuance intentions even more than the equivalent addition of features when considering the absolute magnitude of change. With empirical data from a laboratory experiment, the third study identifies update frequency and update type as further moderators of the effect, and confirms the hypothesized mediation mechanism presumed by the IS Continuance Model. The fourth study examines the role of update delivery strategies, i.e., the timing and presence of a notification and an installation choice. In this study, feature and security updates are distinguished, as both seem to have different characteristics with respect to the delivery strategy (i.e., users ‘need’ security but ‘want’ to add functionality). The findings show that both update types should be announced to users, in the case of a security update, only after successful installation, while presenting an installation choice to users prevents any positive effect for all types of updates. Overall, this thesis highlights the importance of understanding Agile IS and software updates from the user’s perspective. First, the results show that Agile IS have the potential to affect user’s continuance intentions, thereby contributing to a comprehensive theoretical foundation on Agile IS. Also the findings put the user more at the center of investigations in IS. Second, the empirical findings provide evidence in support of a necessary fine-grained understanding of IT Artifacts as malleable compositions of specific features and characteristics. This answers the call of several researchers to put the IT Artifact more at the focus of IS research (Benbasat and Zmud 2003). Third, the results reveal that changes in IS might change users’ attitudes and behaviors over time, which extends the predominant view of IS in post-adoption literature from a mostly static to a more dynamic perspective. With this finding, we answer the call of several IS scholars to consider the evolution of IS more thoroughly (e.g., Jasperson et al. 2005; Benbasat and Barki 2007). For practitioners, the findings of this thesis provide empirically backed rationales to inform management decisions concerning the deployment of Agile IS and offer guidance on strategic or design considerations. Overall, the results show how and when the value provided by IS from a user’s perspective may be increased by the deployment of Agile IS and software updates

Extending the Expectation-Confirmation Theory: How do Software Updates Change Continuance Intention?

Software updates have enabled developers the possibilities to fix bugs or add features after the initial software release. The phenomenon of using such updates to enhance software, is a relatively new trend that has not received much attention in the Information Systems (IS) literature. However, because software updates influence the interaction between users and developers, they are directly connected to sales and revenue. Based on a conducted literature review, this research idea consists of two parts and proposes an approach to measure and analysis the effects of software updates on users. First, a longitudinal, panel study is conducted to gain qualitative knowledge and extend the expectation-confirmation framework proposed by the existing literature. Second, a self-developed Android app will be used in an experimental setting to test and validate the research model and gain knowledge on how developers can keep users happy and increase continuance intention through functional software updates

Influence of Software Updates on Hedonic Software Users

Lately, a more and more frequently used method to enhance and maintain software is through software updates. These updates are distributed over the Internet in order to fix bugs, improve base-software, or add new functionalities. This research paper extends theory in the IS topic of post-adoption and examines the effect of software updates on the individual hedonic software user. We develop a digital game and use it in a web-based experiment with 225 participants who are randomly assigned to three distinct groups. We adapt the IS continuance model and assess the effects of a functional software update and a placebo update notification through inter group comparisons. Our study unveils that while a functional software update leads to an increase in perceived enjoyment, satisfaction, continuance intention, and disconfirmation, albeit the placebo update notification does not. Finally, implications for research and practice are discussed

User Expectations of Hedonic Software Updates

Software updates have recently become a common phenomenon in software development and maintenance. This is due to the rise of ubiquitous and interconnected IT that enables developers to frequently fix bugs, enhance features, or even add new functionalities. This paper contributes to the post-adoption topic of IS research by investigating the understanding of how users perceive software updates of hedonic software. The focus is to understand how and what users perceive and expect from upcoming updates. Pokémon GO is the IT artifact that will be examined with the paper as it is a prime example of an innovative and trending game that was released relatively unfinished, but is constantly improved via updates. We use the IS continuance model to evaluates the players perception on: expectations before the initial use, confirmation or disconfirmation, perceived ease of use, perceived enjoyment, expectations for upcoming software updates, and continuance intention

The Influence of Design Updates on Users: the Case of Snapchat

Today’s smartphone apps are regularly updated and enhanced through software updates. The case at hand is the popular social multimedia messaging app Snapchat that released a design overhaul in February 2018. While the update neither changed any features nor caused any relevant bugs or crashes, it led to an uproar of Snapchat’s users and significantly decreased its app store ratings and consequently revenue. As a result, Snap Inc., the company behind Snapchat, was forced to reverse design changes to appease their users. The initial adverse effects of the update were surprising; however, after using difference-in-difference tests in combination with sentiment analysis, our results indicate that design updates can be perceived negatively by users. We contribute to IS literature by evaluating the effect of design changes and the role of perceived ease of use in the post-adoption stage

DESIGN AND EXPLORATION OF NEW MODELS FOR SECURITY AND PRIVACY-SENSITIVE COLLABORATION SYSTEMS

Collaboration has been an area of interest in many domains including education, research, healthcare supply chain, Internet of things, and music etc. It enhances problem solving through expertise sharing, ideas sharing, learning and resource sharing, and improved decision making. To address the limitations in the existing literature, this dissertation presents a design science artifact and a conceptual model for collaborative environment. The first artifact is a blockchain based collaborative information exchange system that utilizes blockchain technology and semi-automated ontology mappings to enable secure and interoperable health information exchange among different health care institutions. The conceptual model proposed in this dissertation explores the factors that influences professionals continued use of video- conferencing applications. The conceptual model investigates the role the perceived risks and benefits play in influencing professionals’ attitude towards VC apps and consequently its active and automatic use

An Empirical Investigation Of The Influence Of Fear Appeals On Attitudes And Behavioral Intentions Associated With Recommended Individual Computer Security Actions

Through persuasive communication, IT executives strive to align the actions of end users with the desired security posture of management and of the firm. In many cases, the element of fear is incorporated within these communications. However, within the context of computer security and information assurance, it is not yet clear how these fear-inducing arguments, known as fear appeals, will ultimately impact the actions of end users. The purpose of this study is to examine the influence of fear appeals on the compliance of end users with recommendations to enact specific individual computer security actions toward the amelioration of threats. A two-phase examination was adopted that involved two distinct data collection and analysis procedures, and culminated in the development and testing of a conceptual model representing an infusion of theories based on prior research in Social Psychology and Information Systems (IS), namely the Extended Parallel Process Model (EPPM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). Results of the study suggest that fear appeals do impact end users attitudes and behavioral intentions to comply with recommended individual acts of security, and that the impact is not uniform across all end users, but is determined in part by perceptions of self-efficacy, response efficacy, threat severity, threat susceptibility, and social influence. The findings suggest that self-efficacy and, to a lesser extent, response efficacy predict attitudes and behavioral intentions to engage individual computer security actions, and that these relationships are governed by perceptions of threat severity and threat susceptibility. The findings of this research will contribute to IS expectancy research, human-computer interaction, and organizational communication by revealing a new paradigm in which IT users form perceptions of the technology, not on the basis of performance gains, but on the basis of utility for threat amelioration

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Beyond the Privacy Calculus: Dynamics Behind Online Self-Disclosure

Self-disclosure is ubiquitous in today’s digitized world as Internet users are constantly sharing their personal information with other users and providers online, for example when communicating via social media or shopping online. Despite offering tremendous benefits (e.g., convenience, personalization, and other social rewards) to users, the act of self-disclosure also raises massive privacy concerns. In this regard, Internet users often feel they have lost control over their privacy because sophisticated technologies are monitoring, processing, and circulating their personal information in real-time. Thus, they are faced with the challenge of making intelligent privacy decisions about when, how, to whom, and to what extent they should divulge personal information. They feel the tension between being able to obtain benefits from online disclosure and wanting to protect their privacy. At the same time, firms rely on massive amounts of data divulged by their users to offer personalized services, perform data analytics, and pursue monetization. Traditionally, privacy research has applied the privacy calculus model when studying self-disclosure decisions online. It assumes that self-disclosure (or, sometimes, usage) is a result of a rational privacy risk–benefit analysis. Even though the privacy calculus is a plausible model that has been validated in many cases, it does not reflect the complex nuances of privacy-related judgments against the background of real-life behavior, which sometimes leads to paradoxical research results. This thesis seeks to understand and disentangle the complex nuances of Internet users’ privacy-related decision making to help firms designing data gathering processes, guide Internet users wishing to make sound privacy decisions given the background of their preferences, and lay the groundwork for future research in this field. Using six empirical studies and two literature reviews, this thesis presents additional factors that influence self-disclosure decisions beyond the well-established privacy risk–benefit analysis. All the studies have been published in peer-reviewed journals or conference proceedings. They focus on different contexts and are grouped into three parts accordingly: monetary valuation of privacy, biases in disclosure decisions, and social concerns when self-disclosing on social networking sites. The first part deals with the value Internet users place on their information privacy as a proxy for their perceived privacy risks when confronted with a decision to self-disclose. A structured literature review reveals that users’ monetary valuation of privacy is very context-dependent, which leads to scattered or occasionally even contradictory research results. A subsequent conjoint analysis supplemented by a qualitative pre-study shows that the amount of compensation, the type of data, and the origin of the platform are the major antecedents of Internet users’ willingness to sell their data on data selling platforms. Additionally, an experimental survey study contrasts the value users ascribe to divulging personal information (benefits minus risks) with the value the provider gets from personal information. Building on equity theory, the extent to which providers monetize the data needs to be taken into account apart from a fair data handling process. In other words, firms cannot monetize their collected user data indefinitely without compensating their users, because users might feel exploited and thus reject the service afterwards. The second part delineates the behavioral and cognitive biases overriding the rational tradeoff between benefits and privacy risks that has traditionally been assumed in privacy research. In particular, evaluability bias and overconfidence are identified as moderators of the link between privacy risks and self-disclosure intentions. In single evaluation mode (i.e., no reference information available) and when they are overconfident, Internet users do not take their perceived privacy risks into account when facing a self-disclosure decision. By contrast, in joint evaluation mode of two information systems and when users are realistic about their privacy-related knowledge, the privacy risks that they perceive play a major role. This proof that mental shortcuts interact with privacy-related judgments adds to studies that question the rational assumption of the privacy calculus. Moving beyond privacy risks, the third part examines the social factors influencing disclosure decisions. A structured literature review identifies privacy risks as the predominantly studied impediment to self-disclosure on social networking sites (SNS). However, a subsequent large scale survey study shows that on SNS, privacy risks play no role when users decide whether to self-disclose. It is rather the social aspects, such as the fear of receiving a negative evaluation from others, that inform disclosure decisions. Furthermore, based on a dyadic study among senders and receivers of messages on SNS, it is shown that senders are subject to a perspective-taking bias: They overestimate the hedonic and utilitarian value of their message for others. In this vein, these studies combine insights from social psychology literature with the uniqueness of online data disclosure and show that, beyond the potential misuse of personal information from providers, the risk of misperception in the eyes of other users is crucial when explaining self-disclosure decisions. All in all, this thesis draws from different perspectives – including value measuring approaches, behavioral economics, and social psychology – to explain self-disclosure decisions. Specifically, it shows that the privacy calculus is oversimplified and, ultimately, needs to be extended with other factors like mental shortcuts and social concerns to portray Internet users’ actual privacy decision making