April, 20th 2023

Thursday

Jeffrey Nickerson
(Stevens Institute of Technoloty)

Title: AI Blends

Abstract: AI tools, including language and image models,  can be combined with hardware and software tools as well as with human minds and bodies. Recent studies based on language and image models used in journalism will provide a background for a discussion of the design space of apps that combine human and machine processes, including examples drawn from research on video games, simulations, and autonomous driving. 

May, 2nd 2023

Tuesday

Title: Does Editorial Discretion Improve on Reviewer Recommendations in Journal Peer Review?

Abstract: Editors at most peer-reviewed journals have the authority to overturn reviewer recommendations and discretionarily reject or accept submissions. But does editorial discretion improve on reviewer recommendations? Using data from Manufacturing & Service Operations Management, we find that editorial discretion in general does not improve on reviewers in terms of post-publication impact. Submissions discretionarily accepted or invited for revision are not more impactful than reviewer-rejected submissions and most discretionarily rejected submissions are not less impactful than reviewer-accepted or invited submissions. While editorial discretion leads to a decrease in Type I errors (incorrect acceptances or invitations to revise), it comes at the cost of more Type II errors (incorrect rejections). In contrast, reviewer recommendations significantly predict future impact, especially for very high-impact submissions.

May, 16th 2023

Tuesday

Title: The technology-behavioral compensation effect: Unintended consequences of health technology adoption

Abstract: In their pursuit of public health goals, policymakers increasingly turn to innovative apps as complements to existing health measures. Nevertheless, findings from previous research in non-IT health contexts indicate that individuals may compensate for new interventions (e.g., start exercising) by reducing existing preventive health behaviors (e.g., eating less healthy foods). However, the findings are inconclusive, and it is unknown when people tend to engage in behavioral compensation. Building on this observation, we draw on rational choice theory to substantiate the subjective rationality of compensation behavior and develop a utility maximization model that suggests circumstances under which the adoption of technological innovation may lead to users reducing existing preventive health behaviors. This research provides evidence from a multi-wave study on COVID-19 contact-tracing apps that confirms the existence of what we term the technology-behavioral compensation effect: Individuals who perceive the app to be highly useful or actively use it reduce other preventive health behaviors (e.g., social distancing) after app adoption. Ironically, this technology-behavioral compensation effect indicates a hitherto-overlooked tension between two established IS design goals (i.e., perceived usefulness and active use) and the successful exploitation of technology to support users’ health. We expand research on dark side effects of IS use by revealing a previously neglected type of unintended consequence and elaborate on its implications for research well beyond the health context.

June, 6th 2023

Tuesday

Title: Attention and Negativity in Online News

Abstract: In this study, we merge a dataset of 170,000 full-text articles from major German online news sources with Natural Language Processing (NLP) techniques to analyze the effect of negativity on online news consumption. Our data allows for a more detailed examination of three facets of news consumption than previous research: the number of article views, the duration of reading time as an indicator of reader engagement, and the frequency of article shares on social media. Our results show that articles with a negative tone tend to attract more views and are shared more frequently on social media. However, readers spend more time on articles with a positive tone. This pattern persists even after accounting for the specific news events covered and the location of the articles on the home pages of online news portals. These findings imply that news platforms, when aiming to maximize views and social media shares, may be inclined to emphasize negative news. Incorporating reading time into their engagement metrics however, could aid news platforms in producing a more balanced and less skewed depiction of news events.

June, 16th 2023

Thursday

Title: Anticipatory Architectural Search: Designing Interfaces for Innovation Ecosystem Development with Emergent Complements

Abstract:  Innovation ecosystems are built upon a technical architecture that defines the interfaces connecting an organization's offerings with complementary components provided by others. Consequently, organizations have to engage in "architectural search" processes to innovate in ecosystems and guide interface decisions within the technical architecture. However, existing literature often assumes that architectural search begins with existing architectures, where components are already known. In our study, we present a longitudinal case study that focuses on architectural search with emergent complements. Specifically, we examine the development of an innovation ecosystem for a desktop 3D printer company that is shifting its strategy to a new market that requires a novel ecosystem with emergent complements. Our study suggests that in light of these emergent complements, focal organizations rely on a process we label anticipatory architectural search. This process involves the intensive use of proxies to iteratively explore potential complementarities, experiment with complements, and instrument new interfaces. Through iterative cycles of anticipatory architectural search, organizations can gradually define a complementarity space that complementors can navigate to identify opportunities for providing complementary offerings that create value for users of an ecosystem. We discuss theoretical implications for literature on architectural search and innovation ecosystems. 

June, 27th 2023

Tuesday

Title: Designing bot action triggers for information curation on Twitter: Lexical semantics, social tagging, and query expansion

Abstract: Bots are widespread on social media, yet little is known about how they curate information for dissemination. Action triggers, such as hashtagged words, play a crucial role in bot information curation, but their design is poorly understood. We draw on two research streams and the findings of a randomized field experiment on Twitter to investigate the impact of action triggers based on lexical semantics, social tagging, and query expansion on the volume, diversity, and relevance of information curated by bots. Our results show that social tagging is the most critical dimension of action triggers, while query expansion can contribute to curating diverse and relevant documents. Our study provides practical insights for bot design and enhances our understanding of bot information curation on social media.

July, 4th 2023

Tuesday

Title: DEVIANT AFFORDANCES: WHEN TENSIONS, DEADLOCKS, AND NONCONFORMANCE GENERATE PERFORMANCE

Abstract: Novel information technologies (ITs), such as ChatGPT and third-party cloud services, offer users an increasing variety of action possibilities, i.e., affordances. Organizational IT policies, however, often specify their actualization—i.e., turning those affordances into action—as undesired. Organizations face the challenge that to reach their goals, employees still frequently take advantage of these affordances by using undesired ITs and thereby deviate from IT policies. Although prior work has extensively studied how goal-oriented users actualize affordances that are associated with outcomes that support organizational goals, little attention has been paid to the structures, mechanisms, and conditions underlying affordances that deviate from organizational IT policies.
In her talk, she will present how we conceptualized these affordances as deviant affordances. Leveraging the orders of change framework and using a multimethod research design integrating interview and experimental studies, she further identified three key mechanisms underlying deviant affordances—i.e., tension, deadlock, and actualization mechanisms—that can link together to produce a deviant outcome supporting both the users’ individual goal and an organizational goal. In the end, she will explain the importance of users’ perceived deadlock in stimulating the generation of deviant outcomes that support organizational goals through improving task, contextual, and innovative job performance.