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Publication records

Journal Article
Forthcoming

Getting AI implementation right: Insights on challenges and solutions from a global survey

California Management Review
Rebecka C. Ångström, Michael Björn, Magnus Mähring, Linus Dahlander, Martin W. Wallin
Subject(s)
Human resources management/organizational behavior; Information technology and systems; Strategy and general management
Keyword(s)
Artificial intelligence, AI, implementation challenges, implementation solutions, AI experienced firms, AI newcomers, global survey, diagnostic AI implementation framework, value creation
Journal Article
Forthcoming

Hybrid platform model: Monopolistic competition and a dominant firm

The RAND Journal of Economics
Simon P. Anderson, Özlem Bedre-Defolie
Subject(s)
Economics, politics and business environment
Keyword(s)
Trade platform, hybrid business model, antitrust policy, tax policy
JEL Code(s)
D42, L12, L13, L40, H25
We provide a canonical and tractable model of a trade platform enabling buyers and sellers to transact. The platform charges a percentage fee on third-party product sales and decides whether to be "hybrid", like Amazon, by selling its own product. It thereby controls the number of differentiated products (variety) it hosts and their prices. Using the mixed market demand system, we capture interactions between monopolistically competitive sellers and a sizeable platform product. Using long-run aggregative games with free entry, we endogenize seller participation through an aggregate variable manipulated by the platform's fee. We show that a higher quality (or lower cost) of the platform's product increases its market share and the seller fee, and lowers consumer surplus. Banning hybrid mode benefits consumers. The hybrid platform might favor its product and debase third-party products if the own product advantage is sufficiently high. We also provide some tax policy implications.
Commentary
Forthcoming

Einwurf – Kann Deutschland seine eID noch retten? [Commentary: Can Germany still save its eID?)]

HMD Praxis der Wirtschaftsinformatik
Isabel Skierka, Peter Parycek
Subject(s)
Economics, politics and business environment
Keyword(s)
digital identity, e-government, digital transformation
Journal Article
Forthcoming

Is your machine better than you? You may never know.

Management Science
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 is subject to a so-called verification bias such that the DM verifies the machine’s correctness and updates her belief accordingly only if she ultimately decides to act on the task. 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. These findings provide a novel explanation for human-machine complementarity and suggest guidelines on the decision to fully adopt or reject a machine.
© 2023, INFORMS
Journal Article
Forthcoming

Can technology startups hire talented early employees? Ability, preferences, and employee first job choice

Management Science
Michael Roach, Henry Sauermann
Subject(s)
Entrepreneurship; Human resources management/organizational behavior; Technology, R&D management
Keyword(s)
startup early employees, technology entrepreneurship, human capital, job choice, scientists and engineers
Early-stage technology startups rely critically on talented scientists and engineers to commercialize new technologies. And yet, they compete with large technology firms to hire the best workers. Theories of ability sorting predict that high ability workers will choose jobs in established firms that offer greater complementary assets and higher pay, leaving low ability workers to take lower-paying and riskier jobs in startups. We propose an alternative view in which heterogeneity in both worker ability and preferences enable startups to hire talented workers who have a taste for a startup environment, even at lower pay. Using a longitudinal survey that follows 2,394 science and engineering PhDs from graduate school into industrial employment, we overcome common empirical challenges by observing ability and stated preferences prior to first-time employment. We find that both ability and career preferences strongly predict startup employment, with high ability workers who prefer startup employment being the most likely to work in a startup. We show that this is due in part to the dual selection effects of worker preferences resulting in a large pool of startup job applicants, and startups “cherry picking” the most talented workers to make job offers to. Additional analyses confirm that startup employees earn approximately 17% lower pay. This gap is greatest for high ability workers and persists over workers’ early careers, suggesting that they accept a negative compensating differential in exchange for the non-pecuniary benefits of startup employment. This is further supported by data on job attributes and stated reasons for job choice.
© 2022, INFORMS
Journal Article
Forthcoming

Closing open innovation

Strategic Management Review
Marcus Holgersson, Martin W. Wallin, Henry Chesbrough, Linus Dahlander
Subject(s)
Strategy and general management; Technology, R&D management
Keyword(s)
alliance termination; disintegration, innovation strategy, open innovation closure, relationship dissolution, tie dissolution
ISSN (Online)
2688-2639
ISSN (Print)
2688-2612
Journal Article
Forthcoming

Networking a career: Individual adaptation in the network ecology of faculty

Social Networks 77 (May 2024): 166–179
Lanu Kim, Daniel A. MacFarland, Sanne Smith, Linus Dahlander
Subject(s)
Human resources management/organizational behavior
Keyword(s)
network ecology; networking styles; academic collaboration; multiplex networks; sociology of knowledge
Volume
77
Journal Pages
166–179
Journal Article
Forthcoming

Tax incidence and tax avoidance

Contemporary Accounting Research
Scott Dyreng, Xu Jiang, Martin Jacob, Maximilian A. Müller
Subject(s)
Finance, accounting and corporate governance
Keyword(s)
Tax avoidance, tax burden, tax incidence
JEL Code(s)
H20, H25
ISSN (Online)
1911-3846
ISSN (Print)
0823-9150
Journal Article
Forthcoming

When you talk, I remain silent: Spillover effects of peers' mandatory disclosures on firms' voluntary disclosures

The Accounting Review
Matthias Breuer, Katharina Hombach, Maximilian A. Müller
Subject(s)
Finance, accounting and corporate governance
Keyword(s)
Mandatory disclosure, voluntary disclosure, information spillovers, crowding-out
JEL Code(s)
M41, M48, G38
We predict and find that regulated firms’ mandatory disclosures crowd out unregulated firms’ voluntary disclosures. Consistent with information spillovers from regulated to unregulated firms, we document that unregulated firms reduce their own disclosures in the presence of regulated firms’ disclosures. We further find that unregulated firms reduce their disclosures more the greater the strength of the regulatory information spillovers. Our findings suggest that a substitutive relationship between regulated and unregulated firms’ disclosures attenuates the effect of disclosure regulation on the market-wide information environment.
Journal Article
Forthcoming

Naivete-based discrimination

The Quarterly Journal of Economics 132 (2): 1019–1054
Paul Heidhues, Botond Kőszegi
Subject(s)
Economics, politics and business environment
Keyword(s)
Sophistication, naivete, first-degree, price, discrimination, third-degree price discrimination, big data, privacy
JEL Code(s)
D21, D49, D69, L19
We initiate the study of naivete-based discrimination, the practice of conditioning offers on external information about consumers’ naivete. Knowing that a consumer is naive increases a monopolistic or competitive firm's willingness to generate inefficiency to exploit the consumer's mistakes, so naivete-based discrimination is not Pareto-improving, can be Pareto-damaging, and often lowers total welfare when classical preference-based discrimination does not. Moreover, the effect on total welfare depends on a hitherto unemphasized market feature: the extent to which the exploitation of naive consumers distorts trade with different types of consumers. If the distortion is homogenous across naive and sophisticated consumers, then under an arguably weak and empirically testable condition, naivete-based discrimination lowers total welfare. In contrast, if the distortion arises only for trades with sophisticated consumers, then perfect naivete-based discrimination maximizes social welfare, although imperfect discrimination often lowers welfare. And if the distortion arises only for trades with naive consumers, then naivete-based discrimination has no effect on welfare. We identify applications for each of these cases. In our primary example, a credit market with present-biased borrowers, firms lend more than socially optimal to increase the amount of interest naive borrowers unexpectedly pay, creating a homogenous distortion. The condition for naivete-based discrimination to lower welfare is then weaker than prudence.
This is an open access article.
Volume
132
Journal Pages
1019–1054