Skip to main content
Publication records
Subject(s)
Information technology and systems; Management sciences, decision sciences and quantitative methods; Technology, R&D management
Keyword(s)
machine accuracy, decision making, human-in-the-loop, algorithm aversion, dynamic learning
Artificial intelligence systems are increasingly demonstrating their capacity to make better predictions than human experts. Yet, recent studies suggest that professionals sometimes doubt the quality of these systems and overrule machine-based prescriptions. This paper explores the extent to which a decision maker (DM) supervising a machine to make high-stake decisions can properly assess whether the machine produces better recommendations. To that end, we study a set-up, in which a machine performs repeated decision tasks (e.g., whether to perform a biopsy) under the DM’s supervision. Because stakes are high, the DM primarily focuses on making the best choice for the task at hand. Nonetheless, as the DM observes the correctness of the machine’s prescriptions across tasks, she updates her belief about the machine. However, the DM observes the machine’s correctness only if she ultimately decides to act on the task. Further, the DM sometimes overrides the machine depending on her belief, which affects learning. In this set-up, we characterize the evolution of the DM’s belief and overruling decisions over time. We identify situations under which the DM hesitates forever whether the machine is better, i.e., she never fully ignores but regularly overrules it. Moreover, the DM sometimes wrongly believes with positive probability that the machine is better. We fully characterize the conditions under which these learning failures occur and explore how mistrusting the machine affects them. Our results highlight some fundamental limitations in determining whether machines make better decisions than experts and provide a novel explanation for human-machine complementarity.
Pages
42
ISSN (Print)
1866–3494
ESMT Case Study
ESMT Case Study No. ESMT–322–0195–1
Subject(s)
Strategy and general management
Keyword(s)
General managers, middle management, digital strategy, call centers
The case tells the evolution of the call center transformation at Frontelco (a major telecom company in disguise). “Digital” and “agile” approaches to changing the way how call centers operate seem to produce different results. Debate between proponents of alternative approaches takes place across three levels of organizational hierarchy: the Managing Director seems to prefer “agile”, those close to operations in VP ranks seem to prefer “digital”, while three “managers in the middle” following each other in Senior Vice President rank seem to follow different strategies as to how to align the top and the bottom. To settle the debate, evidence-based clarity is being sought and the protagonist is tasked to design an appropriate performance measure to show the real impact of competing approaches.
buy nowbuy now
Journal Article
Review of Economics and Statistics 104 (3): 574–586
Fabian Gaessler, Stefan Wagner (2022)
Subject(s)
Technology, R&D management
Keyword(s)
patents, drugs, data exclusivity, clinical trials
JEL Code(s)
K41, L24, L65, O31, O32, O34
Volume
104
Journal Pages
574–586
Journal Article
The European Business Review May – June: 18–25
Edward W. Boon, Christoph Burger, Nora Grasselli (2022)
Subject(s)
Human resources management/organizational behavior
Keyword(s)
Leadership development, executive education, business impact
JEL Code(s)
M53
Executive Education must be seen as an investment. If we are serious about achieving business impact through training, the first question should be “What business outcomes would we like to see because of this intervention?” Next, we ask questions like “How, where, and when do we need our leaders to perform better to achieve those business outcomes” and “What specific knowledge and skills do we need to equip our leaders with to deliver the improved performance?”. We illustrate this approach through our work with one of the world’s largest commercial vehicle manufacturers, TRATON.
Journal Pages
18–25
Subject(s)
Economics, politics and business environment; Strategy and general management
Keyword(s)
corporate structures, industrial companies, globalization, supply chain, headquarters, global trade
ISSN (Print)
0015-6914
Journal Article
Research Policy 51 (4): 104491
Susanne Beck, Tiare-Maria Brasseur, Marion Poetz, Henry Sauermann (2022)
Subject(s)
Diversity and inclusion; Health and environment; Technology, R&D management
Keyword(s)
Crowd science, citizen science, crowdsourcing, problem solving, problem finding, agenda setting, organization of science
Scientists are increasingly crossing the boundaries of the professional system by involving the general public (the crowd) directly in their research. However, this crowd involvement tends to be confined to empirical work and it is not clear whether and how crowds can also be involved in conceptual stages such as formulating the questions that research is trying to address. Drawing on five different “paradigms” of crowdsourcing and related mechanisms, we first discuss potential merits of involving crowds in the formulation of research questions (RQs). We then analyze data from two crowdsourcing projects in the medical sciences to describe key features of RQs generated by crowd members and compare the quality of crowd contributions to that of RQs generated in the conventional scientific process. We find that the majority of crowd contributions are problem restatements that can be useful to assess problem importance but provide little guidance regarding potential causes or solutions. At the same time, crowd-generated research questions frequently cross disciplinary boundaries by combining elements from different fields within and especially outside medicine. Using evaluations by professional scientists, we find that the average crowd contribution has lower novelty and potential scientific impact than professional research questions, but comparable practical impact. Crowd contributions outperform professional RQs once we apply selection mechanisms at the level of individual contributors or across contributors. Our findings advance research on crowd and citizen science, crowdsourcing and distributed knowledge production, as well as the organization of science. We also inform ongoing policy debates around the involvement of citizens in research in general, and agenda setting in particular.
With permission of Elsevier
Volume
51
Journal Pages
104491
ESMT Case Study
ESMT Case Study No. ESMT–322–0196–1
Subject(s)
Strategy and general management
Keyword(s)
General managers, middle management, cross-functional teams, digital strategy, disruptive business model
The case tells the story of a project at Frontelco (a major telco company in disguise) aiming at defining and piloting a business model (Network as a Service, NaaS) in response to the advancement of a new technology (5G). It is written from the perspective of a “trusted advisor” who had been invited by the protagonist to provide methodological support to the project team. The team, which primarily represents the perspective of product management, spends significant time and effort on developing a methodical approach to their own work, leaving the substantive issue (business model innovation) to be defined only vaguely, under the dominant influence of a few team members. In the follow up to the case we learn that by the time concerns emerge that the team does not seem to have developed any presentable output, they find out that their key competitor has already made significant progress and the technology department, their “internal rival”, has also moved ahead with a concept that allows them to claim ownership for a major corporate-level project.
buy nowbuy now
Subject(s)
Diversity and inclusion; Human resources management/organizational behavior
Keyword(s)
Diversity, equity and inclusion, DEI, global workforce, pandemic, employee well-being, corporate value, women

The pandemic has not wholly derailed DEI as much as feared. The insights from the DEI officers of globally active companies demonstrate optimism and inspiration for those designing DEI strategies in 2022.
ISSN (Print)
0015-6914
Journal Article
Harvard Business Review


Hannes Gurzki (2022)
Subject(s)
Marketing
Keyword(s)
Luxury, digital, innovation, branding
Traditional luxury goods companies have treated digital as a channel. But they’re now starting to treat it as a marketplace in its own right, thanks largely to Blockchain technology, which has delivered the Non-Fungible Token. Today, the key ingredients of luxury – rarity, exclusivity, and cost — can also apply to virtual products, as companies like Balenciaga, Louis Vuitton, and Gucci have realized.
ISSN (Print)
0017-8012
ESMT Working Paper
ESMT Working Paper No. 22-01
Mirko Kremer, Francis de Véricourt (2022)
Subject(s)
Management sciences, decision sciences and quantitative methods
Keyword(s)
congestion, diagnostic accuracy, experiments, partially observable markov decision process, path-dependent decision making, undertesting, task completion bias
To study the effect of congestion on the fundamental trade-off between diagnostic accuracy and speed, we empirically test the predictions of a formal sequential testing model in a setting where the gathering of additional information can improve diagnostic accuracy, but may also take time and increase congestion as a result. The efficient management of such systems requires a careful balance of congestion-sensitive stopping rules. These include diagnoses made based on very little or no diagnostic information, and the stopping of diagnostic processes while waiting for information. We test these rules under controlled laboratory conditions, and link the observed biases to system dynamics and performance. Our data shows that decision makers (DMs) stop diagnostic processes too quickly at low congestion levels where information acquisition is relatively cheap. But they fail to stop quickly enough when increasing congestion requires the DM to diagnose without testing, or diagnose while waiting for test results. Essentially, DMs are insufficiently sensitive to congestion. As a result of these behavioral patterns, DMs manage the system with both lower-than-optimal diagnostic accuracy and higher-than-optimal congestion cost, underperforming on both sides of the accuracy/speed trade-off.
Pages
40
ISSN (Print)
1866–3494