Publications by Lea Reis (formerly known as Lea Müller)

Conference Articles (Peer Reviewed)

Meier, M., Maier, C., Reis, L., and Weitzel, T. (2021)
Amazon Prime Video Yesterday, Netflix Today: Explaining Subscribers' Switching Behavior from a Retrospective
Proceedings of the 29th European Conference on Information Systems (ECIS), Marrakesch, Marokko

View Abstract
Video-on-demand (VoD) services attract millions of subscribers around the globe. Despite their popularity, practice shows the interesting behavior of subscribers of VoD services switching regularly between different providers, such as Netflix or Amazon Prime Video. To sustain their revenues due to subscriptions, providers need to understand the reasons why subscribers switched to other VoD services. While existing research with a prospective point of view explains that users develop switching intentions between different services because of, for instance, dissatisfaction, there is scant research on their actual switching behavior from a retrospective. By analyzing interviews with 23 subscribers that switched VoD services, findings reveal five switching causes and three switching barriers that together explain switching behavior between VoD services. With that, the findings contribute to switching research by identifying switching causes and switching barriers, zooming in on causes of subscribers’ dissatisfaction with VoD services, and studying switching behavior from a retrospective.

Mattke, J., Maier, C., and Reis, L. (2020)
Security Token Offerings: A Risk as Feelings Theoretic Perspective on Investment
Proceedings of the 41th International Conference on Information Systems (ICIS), Hyderabad, India
(Research in Progress)

View Abstract
Security Token Offerings (STOs) are a blockchain-enabled way for organizations to raise capital. To realize this, STO needs to base on a broad user base, which is currently not established. We take an individual-level perspective and examines why individuals decide to invest in STO. We suggest a mixed-method approach and build upon the theoretical perspective of the Risk as Feelings hypothesis to study what shapes STO investment decisions. In Study 1, we identify perceptions and anticipatory feelings. Perceptions include profit expectancy, personal need, benefit of gaining STO expertise, support of disruption, trust in financial regulator’s approval, financial flexibility, low investment barriers, and opportunity for diversification. The identified anticipatory feelings are excitement, enjoyment, anxiety, and fear of missing out that individuals experience when deciding to invest. In the ongoing Study 2, we will analyze how individuals decide when the cognitive evaluation and feelings contradict each other resulting in decisional conflict.

Mattke, J., Maier, C., and Reis, L. (2020)
Is Cryptocurrency Money? Three Empirical Studies Analyzing Medium of Exchange, Store of Value and Unit of Account
Proceedings of the ACM SIGMIS Conference on Computers and People Research, Nuremberg, Germany

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Cryptocurrencies, such as Bitcoin, Ethereum or Ripple, are discussed as a new form of money. Typically, money fulfills three core functions: 1) medium of exchange, 2) store of value, and 3) unit of account. To examine whether individuals consider cryptocurrencies as money, we conduct three studies. Study 1 (N=57) provides valid and reliable measurement items for the three core functions of money. Study 2 (N=95) shows that the general perception about the fulfillment of the core functions is rather positive for cryptocurrencies. The results from Study 3 (N=99) furthermore reveal that Bitcoin is perceived significantly better in fulfilling all three functions than Ethereum or Ripple. The findings suggest that cryptocurrency research needs to include or at least control for the basic perceptions of core functions when examining individuals’ adoption or use of cryptocurrency as money. Furthermore, the findings suggest that existing knowledge from Bitcoin use or adoption research cannot be easily transferred to the context of another cryptocurrency.

Reis, L., Maier, C., Mattke, J., and Weitzel, T. (2020)
Chatbots in Healthcare: Status Quo, Application Scenarios for Physicians and Patients and Future Directions
Proceedings of the 28th European Conference on Information Systems (ECIS), Marrakesh, Morocco

View Abstract
The implementation of chatbots in healthcare offers high potentials for patients and physicians. Among others, chatbots reduce physicians’ administrative workload and weaken the worse consequences coming along with the lack of physicians. However, to implement chatbots in healthcare successfully, we need to respect special characteristics of the domain, such that the shared data is highly sensitive and that an incorrect or incomplete chatbot answer can have far-reaching negative consequences for health and life. To examine this field of research and its specific characteristics, we perform a qualitative study with 23 physicians from different fields having experience with automation in the healthcare sector. We identify seven application scenarios for chatbots from the physicians’ perspective and seven further application scenarios physicians assess as useful for patients. Nine of them enlarge and five of them validate the existing five application scenarios in literature. We contribute to research in the stream of chatbots by offering a combined perspective of physicians and patients. We also contribute by revealing specific domain characteristics from the physicians’ perspective, such as e.g. the liability question and privacy concerns. Based on that, we offer future research directions, in terms of next steps, but also potential negative sides of chatbot implementations.

Pflügner, K., Reis, L., Maier, C., and Weitzel, T. (2020)
Communication Measures to Reduce Techno-Invasion and Techno-Overload: A Qualitative Study Uncovering Positive and Adverse Effects
Proceedings of the 20th ACM SIGMIS Conference on Computers and People Research, Nuremberg, Germany
Best Paper Award

View Abstract
The perception of specific techno-stressors, such as techno- invasion or techno-overload, negatively influences employees' performance and organizations' profit. Therefore, it is imperative for organizations to implement specific, deliberate mitigation strategies. Among others, communication measures have the potential to reduce employees' perception of techno-invasion and techno-overload. Basing on 38 semi-structured interviews with working employees, this study identifies five communication measures and their positive and adverse effects in reducing techno-invasion and techno-overload from the perspective of employees. Enlarging related research on technostress mitigation, the results show that none of the analyzed communication measures is limitation-free. Therefore, we conclude that organizations need to introduce more elected and comprehensive communication measures, representing employees' individual needs and characteristics to reduce techno-invasion and techno-overload sustainably. Theoretically, our research enlarges prior findings on technostress and on mitigation of technostress presenting specific mitigation strategies for two specific techno-stressors as well as positive and adverse effects of these mitigation strategies.

Reis, L., Mattke, J., Maier, C., and Weitzel, T. (2020)
Conversational Agents in Healthcare: Using QCA to Explain Patients' Resistance to Chatbots for Medication
Proceedings of the Conversations 2020: 3rd International Workshop on Chatbot Research and Design, Amsterdam, Netherlands

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Complete information is very important to the accuracy of diagnosis in healthcare. Therefore, the idea to use conversational agents recording relevant information and providing it to healthcare facilities is of rising interest. A promising use case of the involvement of conversational agents is medication, as this data is often fragmented or incomplete. The paper at hand examines the hindrances in the way of patients sharing their medication list with a chatbot. Basing on established theories and using fuzzy-set qualitative comparative analysis (QCA), we identify bundles of factors that influence patients lacking willingness to interact with a chatbot. Those typologies of patients can be used to address these hindrances specifically, providing useful insights for theory and healthcare facilities.

Müller, L. (2019)
Enabling Digital Commerce: Advertising and the Influence of User Behavior
Proceedings of the 25th Americas Conference on Information Systems (AMCIS), Cancun, México

View Abstract
With the rising popularity of digital commerce and rising competition of companies with platforms like Amazon, it is especially important for companies to attract customers' attention. Advertising depicts one possibility to do that, but only if the ad can induce a certain interaction with the customer. As prior research shows that the willingness to interact with an ad depends on how the user perceives the ad, we conduct a literature review on factors shaping those perceptions and interactions. The results of 41 papers are structured along the ad delivery process, including advertisers', here the companies in digital commerce, publishers' and customers' perspectives. The results show, that to use advertising successfully to raise customers' attention and induce purchases, companies in digital commerce need to be aware of all three perspectives and need to collaborate closely with publishers to manage the display of ads to customers. We offer a precise research agenda.

Müller, L., Mattke, J., and Weitzel, T. (2019)
Not Talking to Robo-Doc: A QCA Study Examining Patients' Resistance to Chatbots for Anamnesis
Proceedings of the Special Interest Group on Adoption and Diffusion of Information Technology (DIGIT) (Pre-ICIS Workshop), Munich, Germany
Best Paper Award

View Abstract
The usage of chatbots in healthcare is rising, due to significant cost and time savings. A promising use case is the automation of the time-intensive anamnesis, however many patients are unwilling to share their personal health records with a chatbot. This paper examins patients' resistance to using a chatbot for anamnesis. We base on status quo bias perspective and its provided influencing factors and use a fuzzy-set qualitative comparative analysis (QCA) to identify configurations, thus conjunctions of the factors that when working together lead to patients' resistance of using a chatbot for anamnesis. The identified three configurations contribute to chatbot research, examining causes for resistance instead of acceptance and resistance research, identifying typologies of patients, who resist using a chatbot for anmanesis. We also provide useful insights for healthcare facilities thinking about the implementation of a chatbot for anamnesis.

Müller, L., Mattke, J., Maier, C., Weitzel, T., and Graser, H. (2019)
Chatbot Acceptance: A Latent Profile Analysis on Individuals' Trust in Conversational Agents
Proceedings of the 19th ACM SIGMIS Conference on Computers and People Research, Nashville, Tennessee,USA

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According to industry reports, the lack of trust in non-human interaction prevents widespread Chatbot acceptance. Since the willingness and the ability to trust varies between individuals, this study examines to what extent the trust in Chatbots varies accordingly to different personality profiles. Drawing on the HEXACO dimensions of personality, we apply a latent profile analysis and identify three distinct personality profiles, which significantly vary in their trust in Chatbots. A high level of trust in Chatbots, e.g. Alexa, is mainly affected by the two personality dimensions Extraversion and Agreeableness and only slightly by Honesty-Humility. To prevent commercial underperformance and the shutdown of their Chatbot, providers should make sure that users trust in their Chatbot. This can be accomplished, if the Chatbot treats each user based on his or her membership in one of the three profiles identified in this study.

Mattke, J., Müller, L., and Maier, C. (2019)
Paid, Owned and Earned Media: A Qualitative Comparative Analysis revealing Attributes Influencing Consumer's Brand Attitude in Social Media
Proceedings of the 51th Hawaii International Conference on System Sciences (HICSS), Hawai

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This paper examines how companies can use paid media (referring to sponsored posts), owned media (company posts) and earned media (influencer post) to create a positive brand attitude. Based on the advertising value model, this paper takes a configurational approach and uses fuzzy set qualitative comparative analysis (fsQCA). The analysis reveals a typology of five types of media, which influence consumers' brand attitude positively. We contribute to research by providing a typology of paid, owned and earned media, which can guide companies to create a positive brand attitude.

Mattke, J., Maier, C., Müller, L., and Weitzel, T. (2018)
Bitcoin resistance behavior: a QCA study explaining why individuals resist bitcoin as a means of payment
Proceedings of the 39th International Conference on Information Systems (ICIS), San Francisco

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Bitcoin could revolutionize the system of payments, yet most individuals do not use Bitcoin as a means of payment. As the success of Bitcoin as a means of payment depends upon a high number of individuals using Bitcoin, this study examines why individuals resist Bitcoin as a means of payment. We draw on the status quo bias perspective and take a configurational approach, using fuzzy set qualitative comparison analysis (fsQCA). The analysis reveals a typology of four types of resistant users, who resist Bitcoin as a means of payment: the regret driven resistant user, the uncertainty driven resistant user, the transition cost driven resistant user and the cost driven resistant user. We contribute to resistance research and Bitcoin research by providing a typology of resistant users and identifying equifinal configurations of influencing factors leading to individual's resistance to Bitcoin as a means of payment.

Müller, L., Mattke, J., and Maier, C. (2018)
Online Advertising Research Through the Ad Delivery Process: A Literature Review
Proceedings of the 18th ACM SIGMIS Conference on Computers and People Research, Buffalo-Niagara Falls, New York, USA

Müller, L., Mattke, J., and Maier, C. (2018)
#Sponsored #Ad: Exploring the Effect of Influencer Marketing on Purchase Intention
Proceedings of the 24th Americas Conference on Information Systems (AMCIS), New Orleans, Louisiana, USA

Mattke, J., Müller, L., and Maier, C. (2018)
Why do Individuals Avoid Social Media Advertising: A Qualitative Comparison Analysis Study
Proceedings of the 26th European Conference on Information Systems (ECIS)

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Companies spend billions of dollars in social media advertising, yet some social media users actively avoid social media advertising for instance by scrolling over ads. To understand that, this research builds upon the advertising avoidance model and applies a qualitative comparison analysis (QCA) to identify configurations of perceptions of avoidance. We reveal disruption, distraction, excessiveness and lack of incentive as perceptions that are necessary - yet not sufficient for evoking the avoidance of social media advertising. Furthermore, we reveal three distinct configurations of perceptions that are sufficient and lead to avoidance of social media advertising. This research contributes by uncovering the influence of configurations on social media advertising avoidance and companies can use these findings to reduce the effect of social media users actively avoiding social media advertising.

Mattke, J., Müller, L., Maier, C., and Graser, H. (2018)
Avoidance of Social Media Advertising: A Latent Profile Analysis
Proceedings of the 18th ACM SIGMIS Conference on Computers and People Research

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Some individuals actively avoid social media advertising, for instance by scrolling over ads or ignoring ads. Therefore, this research aims to identify distinct profiles of individuals avoiding social media advertising. We build upon the advertising avoidance model and take a person-centered approach, using latent profile analysis to identify different profiles of individuals, who avoid social media advertising. We identified three distinct profiles of individuals, differing in their perception and their level of avoidance: unconcerned users, playful avoiding users and goal-oriented users. We contribute by characterizing individuals avoiding SMA, so that companies can use these profiles to derive different strategies how to deal with different profiles of individuals.

Mattke, J., Müller, L., Maier, C., and Weitzel, T. (2017)
Engagement with Social Ads: Explaining the Influence of Herding in Social Media Advertising
Proceedings of the Special Interest Group on Adoption and Diffusion of Information Technology (DIGIT) (Pre-ICIS Workshop), Seoul, South Korea
(Research in Progress)
Best Paper Nominee

View Abstract
Social media uses social ads that are enriched with social media likes (SMLs). Yet, existing research on advertising cannot explain how SMLs influence individuals' engagement with social ads. We build upon herding literature and the theory of the strengths of ties and explain how the observation of social ads enriched with SMLs influences individuals' intention to engage with the social ad. This paper explains the effect 1) of the pure number of SMLs of a social ad and 2) the effect of SMLs from strongly or weakly tied friends on individuals' engagement with social ads. We thereby contribute to a better understanding why individuals click on social ads and provide practical implications for social media marketing' campaigns.

Müller, L., Mattke, J., Maier, C., and Weitzel, T. (2017)
The Curse of Mobile Marketing: A Mixed Methods Study on Individuals' Switch to Mobile Ad Blockers
Proceedings of the 38th International Conference on Information Systems (ICIS), Seoul, Korea

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Mobile marketing investment continues to rise steadily even though online publishers have not realized the desired returns, due to increased use of mobile ad blockers. In this study, we take a mixed methods approach, embracing qualitative, quantitative and configurational approaches, to understand why individuals switch to using mobile ad blockers. We draw on the pull-push-mooring model to evaluate what configurations of pull, push and mooring factors influence individuals' decision to switch to using mobile ad blockers, identifying four distinct configurations of influencing factors resulting in the intention to switch. Furthermore, we specify the unequal effects of influencing factors and validate the quality of our results. Our research deepens the theoretical understanding of the phenomenon of switching to mobile ad blockers and provides valuable implications to online publishers facing the challenge of rising mobile ad blocker use.

Mattke, J., Müller, L., and Maier, C. (2017)
Why do individuals block online ads? An explorative study to explain the use of ad blockers
Proceedings of the Twenty-third Americas Conference on Information Systems (AMCIS), Boston, MA, USA

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Ad blockers are a challenging trend for online publishers, as an increasing number of individuals use ad blockers. To understand why individuals switch to the use of ad blockers, this research presents empirical findings that explain why individuals develop switching intentions. Based on migration theory, we explain that individuals' intention to switch to the use of ad blockers are grounded in factors that pull individuals to use ad blockers, push them away from not using ad blockers, and mooring factors either hinder switching intention or determine how pull and push factors are translated in switching intentions. We conducted 42 interviews and identified relative user experience, increased performance, improved privacy protection and improved security as pull factors, dissatisfaction with online ads as push factor and computer self-efficacy as mooring factor. This contributes to theory by providing an explanation why individuals develop to ad blocker users.