April, 11th, 2022

16:00 CEST

Joe Valacich

(University of Arizona, US)

Rigor, Relevance and Practical Significance: A Real-Life Journey to Organizational Value (Article)

In this presentation, I will briefly describe a research journey focusing on how to analyze mouse cursor movements, typing fidelity, and data from other human-computer interaction (HCI) devices to better understand the end-user online experience. I will begin by describing a research journey, from achieving statistical and practical significance, to explaining how we crossed the chasm between academic research and successful commercialization (i.e., organizational value). I will conclude by describing the process one can follow to develop an initial prototype—the minimal viable product (MVP)—and how demonstrations with potential customers provide continuous insight and validation for product capabilities to meet ever evolving customer and industry needs.

May, 10th, 2022

12:30 CEST

Thomas Kude

(ESSEC Business School, FR)

Responding to platform owner moves: A 14-year qualitative study of four enterprise software complementors

Complementors participate in software platform ecosystems to access complementary resources provided and controlled by a platform owner. Complementors use these resources to create innovative software applications that serve a wide variety of needs. Despite the undeniable benefits of the platform model, platform partnerships are characterized by extreme power asymmetries. Without having to consult with complementors, platform owners can therefore engage in unilateral moves. Being independent and self-directed companies in their own right, complementors will then respond to these moves. Informed by both the competition and the cooperation perspectives on value co-creation in platform ecosystems, this study focuses on complementor responses to two types of platform owner moves: (1) Platform owner entry into the niche occupied by a complementor and (2) the impairing of resource access making it more difficult for complementors to create innovative niche solutions. Building on a14-year longitudinal investigation of 24 move-response pairs from four platform partnerships, our findings unpack the drivers, dimensions, and logic of complementor responses to platform owner moves. Complementors respond to platform owner moves in various ways, either tying their business closer to the platform owner—through ‘insisting’ on resource access or ‘doubling down’ in case of dyadic competition—or loosening their link to the platform owner—through ‘escaping’ the focal platform ecosystem or by ‘spreading out,’ in terms of diversifying activities within the focal ecosystem. Our findings have important implications for research interested in managing the complexities and dynamics of coopetition in platform-based co-creation, point to the importance of complementor responses for creating resilient software ecosystems, and inform the current discussion around platformization of incumbent firms.

May, 23th, 2022

12:30 CEST

Abayomi Baiyere

(Copenhagen Business School, DK)

The Digital X Phenomena

It is hard to deny that we live in a time where digital technologies are reshaping many aspects of business and social life around us. This is challenging traditional assumptions about established modes of operation in organizations. Scholars and practitioners are increasingly using the label “digital” to signify that there is something different. So much so that many long-established business concepts are now expressed in the formulaic form of “digital X” – where X can stand for innovation, strategy, transformation, infrastructure, etc. In the Information Systems discipline and beyond, digital is emerging as an oft-used conceptual label to characterize age-long phenomena that hitherto have been described by the IT label. Yet, there is a sense in the community that digital and IT are not mere synonyms, but there is something fundamentally different being signaled when the digital label is invoked. This talk is focused on tracing the intellectual roots, and foundations of the growing use of digital as a conceptual label in the field as well as the implications that it holds for future scholarship.

June, 7th, 2022 (Tuesday)

16:00 CEST

Spillovers in Shopping from Superchargers

As electric vehicles(EV) increase in popularity, EV charging stations are becoming more common. Unlike gas stations which need larger spaces, monitoring, refueling, and maintenance, these charging stations can be placed in existing parking lots and garages. In this work, we explore the impact such placement of a particular kind of EV station, Tesla Superchargers, has on the foot traffic to proximate retail businesses. We find that rapid charging stations have positive spillovers on businesses while urban stations have no significant impact. The impact is not just on the volume of customers but on who they are, where they come from, and how much they can spend. We offer practical implications for businesses and EV charging providers and add to the literature by exemplifying how offline retail businesses may benefit from partnering with well-established online consumer networks.

June, 20th, 2022

12:30 CEST

Alexander Benlian

(TU Darmstadt, DE)

Algorithmic Management: Bright and Dark Sides, Current Studies, and Research Opportunities

The U.S.-based service company Uber offers platform-based transportation services in more than 70 countries. To this end, the company manages a global network of around 3.5 million freelance drivers who performed over 7 billion trips in 2019 alone. Still, most Uber drivers never personally interact with an Uber manager. How is that possible? The answer is: through algorithmic management.

Algorithmic management has been defined as “the large-scale collection and use of data on a platform to develop and improve learning algorithms that carry out coordination and control functions traditionally performed by managers” (Möhlmann et al. 2021, p. 2001). As such, a key distinguishing feature of algorithmic management (vis-à-vis traditional management approaches) is the use of increasingly intelligent algorithms in conjunction with digital technologies (e.g., mobile apps and sensors embedded in smartphones) not only to support, or informate, but also to automate the execution of coordination and control tasks with little to no human involvement. While the use of algorithms to manage freelance workers is already an established practice in the platform economy, algorithms are also increasingly used to manage permanent employees, including full-time employed delivery drivers, parcel carriers, and warehouse workers in traditional organizations.

In my talk, I will present examples for the growing application of algorithmic management in platform and traditional work environments and speak about its bright and dark side implications for companies and workers. As the core of my talk, drawing on recent publications in IS literature, I will make the case for Information Systems research being a discipline predestined to shape critical conversations on algorithmic management. I will conclude my talk with a research agenda that outlines future research opportunities.

July, 4th, 2022

12:30 CEST

Rodrigo Belo

(Rotterdam School of Management, NL)

Algorithmic Explanations and Human Decision-Making: A Randomized Field Experiment in a Public Employment Agency

We examine the extent to which explanations change human behavior. We model how humans react to changes in explanation sets provided by algorithms and delve into the mechanisms that may lead to the observed outcomes. We use data from a randomized field experiment in a public employment agency in which counselors are presented with a new algorithm that predicts individual candidates' risk for long-term unemployment. Counselors in the control group got access only to the predictions of the algorithm, whereas those in the treatment group were also shown explanations for the algorithm's predictions. We show that counselors, when presented with explanations that are not part of their mental model, are less likely to adjust the risk assessment provided by the algorithm, are less confident about their assessment, and perform worse than the algorithm. On the balance, when explanations are part of their mental model, counselors are more likely to adjust the algorithm's assessment, become more confident on their decisions, and improve on the algorithm's predictions. These results underline the tension between explainability and performance. Whereas explanations that are part of the human model can help increasing confidence and performance, showing explanations that are not part of the human model may lead to a decrease in confidence and to worse predictions, ultimately destroying value.