Buying under Pressure: Purchase Pressure Cues and their Effects on Online Buying Decisions

Although purchase pressure cues (PPC) that signal limited time (LT) or limited product availability (LPA) are widely used features on e-commerce websites to boost sales, research on whether and why PPCs affect consumers’ purchase choice in online settings has remained largely unexplored. Drawing on the Stimulus-Organism- Response (S-O-R) model, consumer decision-making literature, and prospect theory, we conducted a controlled lab experiment with 121 subjects in the context of Deal-ofthe- Day (DoD) platforms. We demonstrate that while LT pressure cues significantly increase deal choice, LPA pressure cues have no distinct influence on it. Furthermore, our results show that perceived stress and perceived product value serve as two serial mediators explaining the theoretical mechanism of why LT pressure cues affect deal choice. Complementary to these results, we provide evidence that higher perceived stress is accompanied by significant changes in consumers’ physiological arousal. Further theoretical and practical implications of our findings are discussed

Keeping Software Users on Board - Increasing Continuance Intention Through Incremental Feature Updates

Although feature updates are a ubiquitous phenomenon in both professional and private IT usage, they have to date received little attention in the IS post-adoption literature. Drawing on expectation-confirmation theory and the IS continuance literature, we investigate whether, when and how incremental feature updates affect users’ continuance intentions (CI). Based on a controlled laboratory experiment, we find a positive effect of feature updates on users’ CI. According to this effect, software vendors can increase their users’ CI by delivering updates incrementally rather than providing the entire feature set right with the first release. However, we also find that CI diminishes when the number of updates exceeds a tipping point in a given timeframe, disclosing update frequency as crucial boundary condition. Furthermore, we unveil that the beneficial effect of feature updates on CI operates through positive disconfirmation of expectations, resulting in increased user satisfaction. Implications for research and practice as well as directions for future research are discussed

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

The Role of Cognitive Biases for Users' Decision-Making in IS Usage Contexts

Human cognition and decision-making related to information systems (IS) is a major area of interest in IS research. However, despite being explored since the mid-seventies in psychology, the phenomenon of cognitive biases has only recently gained attention among IS researchers. This fact is reflected inter alia in the lack of a comprehensive literature review of research on cognitive biases in IS, on which authors could build their work upon. Against this backdrop, this thesis presents a scientometric analysis of 12 top IS outlets covering the time period between 1992 and 2012, providing a comprehensive picture of the current state of research on cognitive biases in IS. Building on its results and considering the current trends in IS usage practice, this thesis further presents three articles in the IS usage contexts ‘personal productivity software’ and ‘e-commerce’. These articles investigate the influence of cognitive biases on IS users’ decision-making and the potential reasons thereof on the example of software updates and purchase pressure cues. The first two studies draw on expectation-confirmation theory and the IS continuance literature. Within the first study, a laboratory experiment reveals that feature updates have a positive effect on users’ continuance intention (CI) – the update-effect. According to this effect, software vendors can increase their users’ CI by delivering updates incrementally rather than providing the entire feature set right with the first release. However the results show that the update-effect only occurs if the number of updates does not exceed a tipping point in a given timeframe, disclosing update frequency as crucial boundary condition. Additionally, the study indicates that this effect operates through positive disconfirmation of expectations, resulting in increased user satisfaction. The second study expands the focus of the first study by considering feature as well as non-feature updates and elaborating on the explanatory role of satisfaction (SAT), perceived ease of use (PEOU) and perceived usefulness (PU). Besides update frequency, the findings demonstrate update type as another boundary condition to the repeatedly identified update-effect, that is, it occurs only with functional feature updates and not with technical non-feature updates. Moreover, by analyzing the practice of employing purchase pressure cues (PPCs) on commercial websites, the third study provides another example of the effect of cognitive biases on users’ decision making in the IS usage context ‘e-commerce’. The results show that while limited time (LT) pressure cues significantly increase deal choice, limited product availability (LPA) pressure cues have no distinct influence on it. Furthermore, perceived stress and perceived product value serve as two serial mediators explaining the theoretical mechanism of why LT pressure cues affect deal choice. Overall, the thesis highlights the role of human cognition and decision-making, and specifically of cognitive biases, for IS related users’ decisions. It further emphasizes the importance of an alterable and malleable IS for the occurrence of biased decision-making. Moreover, the findings shed light on the underlying explanatory mechanisms of how and why biased decision-making takes place, thus answering several calls for research and elaborating on existing theories from psychology and IS. Software vendors and online retailers may use the findings described in the thesis to better understand how and why cognitive biases can be applied in a targeted way to achieve positive revenue effects. Specifically, software vendors are advised to distribute software functionality over time via updates, because feature updates can induce a positive state of surprise, which, in turn, increases users’ CI. However, while the thesis’ results disclose the update-effect as a useful measure for software vendors to achieve customers’ satisfaction regarding a software product, it is also necessary to consider its boundary conditions in order to achieve the desired outcomes. Finally, online retailers are advised to carefully select the PPCs on their websites. While the thesis’ results show that some of them are cost-effective solutions to stimulate positive value perceptions, which in turn impact online purchases, they also reveal that others have no effect on users’ purchase decisions and can even be perceived as an attempt at deception

COGNITIVE BIASES IN INFORMATION SYSTEMS RESEARCH: A SCIENTOMETRIC ANALYSIS

Human cognition and decision-making related to information systems (IS) is a major area of interest in IS research. However, despite being explored since the mid-seventies in psychology, the phenomenon of cognitive bias has only recently gained attention among IS researchers. This fact is reflected in a comparatively sparse set of mostly disconnected publications, sometimes using inconsistent theory, methodology, and terminology. We address these issus in our scientometric analysis by providing the first review of cognitive bias-related research in IS. Our systematic literature review of 12 top IS outlets covering the past 20 years identifies 84 publications related to cognitive bias. A subsequnt content analysis shows a strong increase of interest in cognitive bias research in the IS discipline in the observed timeframe, yet uncovers a highly unequal distribution across IS fields and industry contexts. While previous research on perception and decision biases has already led to valuable contributions in IS, there is still considerable potential for further research regarding social, memory and interest biases. Our study reveals research gaps in bias-related IS research and highlights common practices in how biases are identified and measured. We conclude with promising future research avenus with the intent to encourage cumulative knowledge-building

When Updates Make a User Stick: Software Feature Updates and their Differential Effects on Users’ Continuance Intentions

Although software updates are extensively used to enhance software while already being used, their impact on users’ post-adoption beliefs and attitudes has received little attention. Drawing on expectation-confirmation-theory and the IS continuance model, we investigate if and how feature updates affect users’ continuance intentions (CI) and what role initial feature endowment and update size play. In an online experiment, we find a positive effect of feature updates on users’ CI. According to this effect, software vendors can increase users’ CI by delivering features later, through updates instead of providing them right with the first release. While this positive effect persists despite a small update size and high initial feature endowment, the latter diminishes the effect. We also unveil positive disconfirmation of previous expectations regarding the updated software as crucial mediating mechanism between feature updates and CI. Implications for research and practice as well as directions for future research are discussed