Reis, L., Maier, C., Pflügner, K., and Weitzel, T. (2023)
Unintended consequences of technostress mitigation: An employee perspective on the effectiveness of mitigation measures
Forthcoming in: The DATA BASE for Advances in Information Systems , , https://www.uni-bamberg.de/fileadmin/uni/fakultaeten/wiai_lehrstuehle/isdl/Pre-Prints/Reis_Pre_Press.pdf (VHB-JOURQUAL 3 Rating: B)

View Abstract

The continuous use of IT, even beyond regular office hours, is considered a cause of technostress, which impairs the health and performance of employees. To mitigate technostress, European countries have established the right to disconnect, and many organizations are struggling to identify and implement other effective measures. Based on a qualitative study with 23 IT workers, five managers, and two CIOs, this study identifies eight technological, social, and cultural measures to mitigate common techno-stressors. By focusing on the employees' perspective, the results reveal the extent to which the measures actually work, showing that well-intended countermeasures, such as email restrictions, might have unintended negative and even harmful side effects. Our analysis shows that mitigation measures seldom work in isolation and without spillover effects. We conclude that although technostress mitigation is complex and mitigation measures adopted in isolation can fail and sometimes cause additional harm, employees still appreciate the effort

Reis, L., Maier, C., and Weitzel, T. (2022)
Mixed-Methods in Information Systems Research: Status Quo, Core Concepts, and Future Research Implications
Communications of the Association for Information Systems (CAIS) (51:1), , https://doi.org/10.17705/1CAIS.05106 (VHB-JOURQUAL 3 Rating: C)

View Abstract

Mixed-methods studies are on the rise in information systems (IS) research, as they deliver robust and insightful inferences combining qualitative and quantitative research. However, there is much divergence in conducting such studies and reporting their findings. Therefore, we aim (1) to evaluate how mixed-methods studies have developed in information systems (IS) research under the existence of heavily used guidelines presented by Venkatesh et al. (2013) and (2) to reflect on those observations in terms of potentials for future research. During our review, we identified 52 mixed-methods papers and quantitatively elaborated the adherence to the three core concepts of mixed-methods in terms of purpose, meta-inferences, and validation. Findings discover that only eight adhere to all three of them. We discuss the significance of our results for current and upcoming mixed-methods research and derive specific suggestions for authors. With our study, we contribute to mixed-methods research by showing how to leverage the insights from existing guidelines to strengthen future research and by contributing to the discussion of the legislation associated with research guidelines, in general, presenting the status quo in current literature

Asbjørn , F., Araujo, T., Lai-Chong Law, E., Bae Brandtzaeg, P., Papadopoulos, S., Reis, L., Baez, M., Laban, G., McAllister, P., Ischen, C., Wald, R., Catania, F., Meyer von Wolff, R., Hobert, S., and Luger, E. (2021)
Future directions for chatbot research: an interdisciplinary research agenda
Computing (103:1), p. 2915–2942, https://doi.org/10.1007/s00607-021-01016-7 (VHB-JOURQUAL 3 Rating: k.R.)

View Abstract

Chatbots are increasingly becoming important gateways to digital services and information—taken up within domains such as customer service, health, education, and work support. However, there is only limited knowledge concerning the impact of chatbots at the individual, group, and societal level. Furthermore, a number of challenges remain to be resolved before the potential of chatbots can be fully realized. In response, chatbots have emerged as a substantial research area in recent years. To help advance knowledge in this emerging research area, we propose a research agenda in the form of future directions and challenges to be addressed by chatbot research. This proposal consolidates years of discussions at the CONVERSATIONS workshop series on chatbot research. Following a deliberative research analysis process among the workshop participants, we explore future directions within six topics of interest: (a) users and implications, (b) user experience and design, (c) frameworks and platforms, (d) chatbots for collaboration, (e) democratizing chatbots, and (f) ethics and privacy. For each of these topics, we provide a brief overview of the state of the art, discuss key research challenges, and suggest promising directions for future research. The six topics are detailed with a 5-year perspective in mind and are to be considered items of an interdisciplinary research agenda produced collaboratively by avid researchers in the field.

Mattke, J., Maier, C., Reis, L., and Weitzel, T. (2021)
In-app advertising: a two-step qualitative comparative analysis to explain clicking behavior
European Journal of Marketing (55:8), p.2146-2173, https://doi.org/10.1108/EJM-03-2020-0210 (VHB-JOURQUAL 3 Rating: C)

View Abstract

Individuals only click on a very small fraction of the in-app advertisements (ads) they are exposed to. Despite this fact, organizations spend generously placing in-app ads without theoretical knowledge of how the structure and the semantics of in-app ads influence individuals’ clicking behavior. This study aims to identify how the processing of structural and semantic factors leads to clicking behavior. Based on the limited capacity theory, this paper proposes that the sequential processing of structural and semantic factors leads to clicking behavior. To mirror the sequential process, this paper applies a process-oriented configurational approach and performs a two-step qualitative comparative analysis (QCA) using 262 incidents of exposure to in-app ads. The results support the proposed sequential processing and show that neither structural nor semantic factors alone lead to clicking behavior. This paper reveals four different paths of sequential processing of in-app ads that lead to clicking behavior. The results show that individuals click on non-animated in-app ads even though these are perceived as irritating or privacy-concerning. When the in-app ads are animated, individuals do only click on them when these are not irritating, privacy-concerning and personalized. Organizations can use these findings to improve their in-app ads and generate more clicks. This study recommends that organizations place in-app ads in a prominent location, design them similar to the design of the app and use bright colors. The advertising message needs to have new and relevant information in a credible and entertaining way. Depending on the degree of personalization, organizations should use different sizes of the in-app ad and only use animation if it is unlikely that the in-app ad caused irritation or privacy concerns. Organizations can use these findings to improve their in-app ads and generate more clicks. This paper recommends that organizations place in-app ads in a prominent location, design them similar to the design of the app and with bright colors. The advertising message needs to have new and relevant information in a credible and entertaining way. Depending on the degree of personalization, organizations should use different sizes of the in-app ad and only use animation if it is unlikely that the in-app ad caused irritation or privacy concerns. From the in-app ad perspective, this study is the first to theoretically develop and empirically show the sequential processing of structural and semantic factors of in-app ads. From the methodological perspective, this study applies an advanced configurational two-step QCA approach, which is capable of analyzing sequential processes and is new to marketing research.

Maier, C., Laumer, S., Tarafdar, M., Mattke, J., Reis, L., and Weitzel, T. (2021)
Challenge and hindrance IS use stressors and appraisals: Explaining contrarian associations in post-acceptance IS use behavior
Journal of the Association for Information Systems (JAIS) (22:6) , p.1590-1624, http://dx.doi.org/10.17705/1jais.00709 (VHB-JOURQUAL 3 Rating: A)

View Abstract

Post-acceptance IS use is the key to leveraging value from IS investments. However, it also poses many demands on the user. Drawing on the challenge-hindrance stressor framework, this study develops a theory to explain how and why IS use stressors influence post-acceptance use. We identify two different types of IS use stressors: challenge IS use stressors and hindrance IS use stressors. We hypothesize that they are appraised through challenge IS use appraisal and hindrance IS use appraisal, respectively, through which they influence routine use and innovative use. We evaluate our hypotheses by surveying 178 users working in one organization and analyze the data collected using consistent partial least square (PLSc). We find that challenge IS use stressors positively influence routine use and innovative use via challenge IS use appraisal. Hindrance IS use stressors negatively influence routine use via hindrance IS use appraisal. We then dive deeper into these findings using a two-step fuzzy set qualitative comparative analysis (fsQCA), identifying the presence of challenge IS use stressors and challenge IS use appraisal as necessary conditions for high innovative use. We also reveal that the presence of hindrance IS use stressors and hindrance IS use appraisal only influences routine use and innovative use in the absence of challenge IS use stressors and challenge IS use appraisal. We discuss the practical relevance and transferability of our findings based on a comprehensive applicability check. Our findings advance IS scholarship of IS use stress and post-acceptance use by showing how routine use and innovative use emanate from IS use stressors.

Reis, L., Maier, C., Mattke, J., Creutzenberg, M., and Weitzel, T. (2020)
Addressing User Resistance Would Have Prevented a Healthcare AI Project Failure
MIS Quarterly Executive (19:4), p. 279-296, http://dx.doi.org/10.17705/2msqe.00038 (VHB-JOURQUAL 3 Rating: B)

Mattke, J., Maier, C., Reis, L., and Weitzel, T. (2020)
Herd behavior in social media: The role of Facebook likes, strength of ties, and expertise
Information & Management (57:8), 103370, https://doi.org/10.1016/j.im.2020.103370 (VHB-JOURQUAL 3 Rating: B)

View Abstract

When do social media users click on sponsored content or intend to visit the website at a later time? A qualitative comparative analysis (QCA) using arguments based on herd theory, strength of ties, and social distance shows that only “likes” from socially close and knowledgeable users can consistently generate click-through or view-through intentions. Considering social tie strength in a herd behavior context, the analysis of sufficient configurations for click- and view-through intentions provides a nuanced perspective on social media user behavior and social influence. For instance, click-through intention requires observing a “like” from a close person, while view-through intentions can also develop after observing “likes” from less close acquaintances, yet in the last case only if the user assumes the acquaintance is better informed regarding the sponsored content. In addition, a “like” from a close friend deemed better informed can even make a user click on a sponsored content that was not considered valuable before.

Mattke, J., Maier, C., Reis, L., and Weitzel, T. (2020)
Bitcoin investment: a mixed methods study of investment motivations
European Journal of Information Systems (EJIS) (30:3), p. 261-285, https://doi.org/10.1080/0960085X.2020.1787109 (VHB-JOURQUAL 3 Rating: A)

View Abstract

Bitcoin is a well-established blockchain-based cryptocurrency that has attracted a great deal of attention from media and regulators alike. While millions of individuals invest in bitcoin, their motivations for doing so are less clear than with traditional investment decisions. We argue that the technical nature of bitcoin investments gives it unique characteristics and, consequently, that we lack a thorough understanding of how this affects the motivations behind bitcoin investment. We use a mixed method approach consisting of qualitative (n = 73) and quantitative (n = 150) studies and fuzzy-set qualitative comparative analysis (fsQCA) to identify seven bitcoin-specific motivations (profit expectancy, ease of bitcoin acquisition, support of bitcoin ideology, investment skills, risk affinity, anticipated and experienced inaction regret) and how configurations of them explain bitcoin investment. The findings reveal, among others, that some individuals invest in bitcoin because they support the bitcoin ideology. Contrary to the traditional investment literature, profit expectancy is not a necessary condition to the extent that there is one empirical configuration of motivations that explains that individuals also invest in bitcoin even if they do not expect profits. The results disclose non-trivial investment motivation configurations and lay the groundwork for future studies of the role of cryptocurrencies in society.

Konferenz-Artikel (Peer Reviewed)

Reis, L. (2022)
Information Overload and Presented Lifestyle in Social Media: A Stress-Perspective on the Effects on Mental Health
Proceedings of the 22nd ACM SIGMIS Conference on Computers and People Research, Atlanta (GA), United States

View Abstract

To counteract the increasing number of people showing symptoms of depressive disorders since the outbreak of COVID-19, among others, the WHO suggests using social media more intensively to stay in contact and receive positive messages. However, existing literature indicates that this can have the opposite effect. Based on social comparison theory and technostress literature, we examine the impact of the constant confrontation with the overly optimistic presented lifestyle of social media influencers on Instagram on depression. Our quantitative study (N=191) based on structural equitation modeling indicates that influencers' presented lifestyle has a substantial positive indirect effect on depression mediated through negative emotions. In contrast, positive self-esteem can help to reduce depression. We contribute to technostress literature, research on social comparison, and mental health research.

Reis, L. and Maier, C. (2022)
Artificial Intelligence in Mental Health: A Qualitative Expert Study on Realistic Application Scenarios and Future Directions
Proceedings of the 22nd ACM SIGMIS Conference on Computers and People Research, Atlanta (GA), United States

View Abstract

What can we do to address the rising numbers of people suffering from mental health problems facing the lack of mental health professionals? This study uses 15 qualitative expert interviews to identify six realistic application scenarios for artificial intelligence in mental health that reduce mental health professionals’ workload and improve treatment. We classify the application scenarios concerning the type of intelligence they embed (mechanical, analytical, emotional) and the type of task they support (automation, decision support, engagement) to assess their implementation readiness and success. Based on this classification, we develop four application scenarios with the potential for immediate implementation and two possible future directions. Our results contribute to the research stream of artificial intelligence in general and in mental health.

Reis, L., Maier, C., and Weitzel, T. (2022)
Chatbots in Marketing: An In-Deep Case Study Capturing Future Perspectives of AI in Advertising
Proceedings of the 22nd ACM SIGMIS Conference on Computers and People Research, Atlanta (GA), United States

View Abstract

A personalized customer approach in marketing offers many benefits to customers and organizations. With chatbots, personalized marketing could reach the next level as they gather, analyze, and use customer data while communicating with them. Based on qualitative data collected with a start-up in the field, this in-depth case study evaluates the potential of chatbots from an industry perspective, identifying significant benefits, challenges, and future directions that organizations can use to engage in chatbots in marketing. Our main results indicate that chatbots offer optimized customer approaches that are less intrusive and provide a better identification and segmentation of customers. We also see that organizations should avoid bombarding customers with advertising messages because the chatbot enables them to approach the customer directly, so use this communication channel wisely. In the future, chatbots can optimize access to a wholesome customer experience that fits customers’ preferences.

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
Claudio Ciborra Award Nominee

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

View Abstract

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

View Abstract

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

View Abstract

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

View Abstract

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

View Abstract

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)

View Abstract

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

View Abstract

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

View Abstract

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

View Abstract

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.

Veröffentlichungen von Lea Reis (geb. Lea Müller)

Journal-Artikel (Peer Reviewed)

Konferenz-Artikel (Peer Reviewed)