Veröffentlichungen von Jens Mattke

Journal-Artikel (Peer Reviewed)

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) , , https://www.uni-bamberg.de/isdl/veroeffentlichungen/preprint-manuskripte/ (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.

Maier, C., Laumer, S., Joseph, D., Mattke, J., and Weitzel, T. (2021)
Turnback Intention: An Analysis of the Drivers of IT Professionals’ Intention to Return to a Former Employer
Forthcoming in: Management Information Systems Quarterly (MISQ) (VHB-JOURQUAL 3 Rating: A+)

View Abstract
Recent statistics indicate that most organizations prefer to fill IT vacancies by rehiring an IT professional who had previously worked in the organization. Less is known about what drives IT professionals to “turnback,” a term we define as returning to working for a former employer. To explain this important and rarely considered IT job mobility behavior, we build on job embeddedness theory and on the concepts of shocks and job dissatisfaction from, among others, the unfolding model of voluntary turnover to develop the theory of IT professional turnback. We perform fuzzy-set qualitative comparative analysis (fsQCA) of data collected from 248 IT professionals to draw conclusions about the intentions among IT professionals to return to work for a former employer, and develop a mid-range theory. Our results reveal two configurations contributing to high turnback intentions and three configurations contributing to low turnback intentions. Our model distinguishes between work shocks, personal shocks, and IT work shocks. IT shocks are a new category of shocks specific to the IT profession. We contribute theoretically by theorizing a behavior relevant to IT professionals and explaining attributes contributing to turnback intention.

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)

View Abstract
Integrating artificial intelligence (AI) into existing work routines involves invasive changes, and the resulting user resistance can lead to project failure. We describe a failed AI project at a large hospital to implement a cognitive agent and identify the root causes of the user resistance that led to the failure. Based on the lessons learned, we provide recommendations for addressing the causes of resistance for the three types of AI—automation, decision support and engagement.

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.

Pflügner, K., Maier, C., Mattke, J., and Weitzel, T. (2020)
Personality Profiles that Put Users at Risk of Perceiving Technostress: A Qualitative Comparative Analysis with the Big Five Personality Traits
Forthcoming in: Business & Information Systems Engineering (BISE) (VHB-JOURQUAL 3 Rating: B)

View Abstract
Some information systems research has considered that individual personality traits influence whether users feel stressed by information and communication technologies. Personality research suggests, however, that personality traits do not act individually, but interact interdependently to constitute a personality profile that guides individual perceptions and behavior. The study relies on the differential exposure-reactivity model to investigate which personality profiles of the Big Five personality traits predispose users to perceive techno-stressors. Using a questionnaire, data was collected from 221 users working in different organizations. That data was analyzed using fuzzy set Qualitative Comparative Analysis (fsQCA). Based on the results, six different personality profiles that predispose to perceive high techno-stressors are identified. By investigating personality traits in terms of profiles, it is shown that a high and a low level of a personality trait can influence the perception of techno-stressors. The results will allow users and practitioners to identify individuals who are at risk of perceiving techno-stressors based on their personality profile. The post-survey analysis offers starting points for the prevention of perceived techno-stressors and the related negative consequences for specific personality profiles.

Maier, C., Mattke, J., Pflügner, K., and Weitzel, T. (2020)
Smartphone use while driving: A fuzzy-set qualitative comparative analysis of personality profiles influencing frequent high-risk smartphone use while driving in Germany
International Journal of Information Management (55), 102207, https://doi.org/10.1016/j.ijinfomgt.2020.102207 (VHB-JOURQUAL 3 Rating: C)

View Abstract
Smartphone use while driving causes car crashes, injuries and high death rates. To date, there is little research into what motivates frequent smartphone use while driving. In this study, we draw on psychological research indicating that personality profiles defined as constellations of multiple personality traits, influence individual beliefs and behaviors. We apply fuzzy-set qualitative comparative analysis (fsQCA) to survey data to derive profiles of drivers who use their smartphone frequently while driving. Our results indicate that personality profiles affect smartphone use behavior while driving and that three equifinal profiles, i.e. distinct constellations of the big five personality traits, influence frequent smartphone use while driving. Interestingly, a single trait can be low in one profile and high in another profile and, depending on the other traits, both profiles might reflect drivers using their smartphone frequently. We contribute to the literature that frequent smartphone use while driving is, to some degree, grounded in personality and that just looking at singular traits can yield misleading results. Complementing these theoretical insights by post-survey interviews, we can reveal distinct measures that reduce frequent smartphone use for each of the three profiles.

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) , , 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.

Mattke, J., Maier, C., Hund, A., and Weitzel, T. (2019)
How an Enterprise Blockchain Application in the U.S. Pharmaceuticals Supply Chain is Saving Lives
MIS Quarterly Executive (18:4), (p. 245 - 261), http://dx.doi.org/10.17705/2msqe.00019 (VHB-JOURQUAL 3 Rating: B)

View Abstract
This article describes the MediLedger Project, which has built a blockchain ecosystem application that will prevent counterfeit pharmaceuticals from entering the U.S. pharmaceuticals supply chain. From the lessons learned, we recommend to 1) use a "benevolent dictator" and base governance on "consensus through collaboration", 2) to not store verified transactions on the blockchain but to instead store the verification on the blockchain, 3) to use zero-knowledge proofs to verify product and transaction authenticity while preserving full privacy 4) and to use blockchain application capabilities that are not found in traditional technologies, to fix ineffective IS landscapes.