This paper develops a new method to study how workers’ career and wage profiles are shaped by internal labor markets (ILM) and job hierarchies in firms. We tackle the conceptual challenge of organizing jobs within firms into hierarchy levels by proposing a data-driven ranking method based on observed worker flows between occupations within firms. We apply our method to linked employer–employee data from Norway that record fine-grained occupational codes and track contract changes within firms. Our findings confirm existing evidence that is primarily based on case studies for single firms. We expand on this by documenting substantial heterogeneity in the structure and hierarchy of ILMs across a broad range of large firms. Our findings on wage and promotion dynamics in ILMs are consistent with models of careers in organizations.

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.

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.

Problem description: Classical models of queueing systems with rational and strategic customers assume queues to be either fully visible or invisible while service parameters are known with certainty. In practice, however, people only have “partial information” on the service environment in the sense that they are not able to fully discern prevalent uncertainties. This is because assessing possible delays and rewards is costly as it requires time, attention, and cognitive capacity which are all limited. On the other hand, people are also adaptive and endogenously respond to information frictions. Methodology: We develop an equilibrium model for a single-server queueing system with customers having limited attention. Following the theory of rational inattention, we assume that customers optimize their learning strategies by deciding the type and amount of information to acquire and act accordingly while internalizing the associated costs. Results: We establish the existence and uniqueness of a customer equilibrium and delineate the impact of service characteristics and information costs. We numerically show that when customers allocate their attention to learn uncertain queue length, limited attention of customers improves throughput in a congested system that customers value reasonably highly, while it can be detrimental for less popular services that customers deem rather unrewarding. This is also reflected in social welfare if the firm's profit margin is high enough, although customer welfare always suffers from information costs. Managerial implications: Our results shed light on optimal information provision and physical design strategies of service firms and social planners by identifying service settings where they should be most cautious for customers' limited attention. Academic/practical relevance: We propose a microfounded framework for strategic customer behavior in queues that links beliefs, rewards, and information costs. It offers a holistic perspective on the impact of information prevalence (and information frictions) on operational performance and can be extended to analyze richer customer behavior and complex queue structures, rendering it a valuable tool for service design.

© 2021 INFORMS

Negotiations can end with a successful deal or with an impasse. To minimize the impasse risk, how assertive and precise should negotiators’ first offers be? Recent studies diverge in their findings as to the advantages and disadvantages of making round vs. precise offers. Based on over 25 million eBay negotiations, the present research establishes correlational evidence that buyer offers at round percentages of the seller’s list price—for instance, exactly 50% (75%, 90%, etc.)—coincide with a markedly smaller impasse risk than offers just above (e.g., 50.1%) or just below (49.9%) these round percentages. We also find that buyers who mimic sellers’ list price precision (e.g., offering $89.95 for a product listed at $99.99) and exact price endings ($30.13 for a list price of $40.13) incur markedly smaller impasse risks. Our findings show that the effectiveness of buyers’ round vs. precise offers depends on the roundness of the seller’s list price, therefore extending previous research that focused on offer precision without taking opponents’ list price into account. Multiple robustness checks—examining negotiators’ experience, price levels, product demand, etc.—corroborate the reported findings. We discuss promising avenues for future research on the interpersonal effects of offer precision and priceending mimicry.

With permission of Elsevier