This paper examines Britain’s process of electrification following a disruptive stock market boom and bust in 1882. This is done by noting the companies that raise finance on British stock exchanges, the amounts raised, and the returns earned on that money. It also examines the impact of the Lighting Act of 1882, finding that the Act inhibited investment, but with important exceptions. We find the Act was not a barrier to entrepreneurs alert to the possibilities of electrification. However, the limited British electrical investment after the 1882 crash was more heavily and successfully concentrated on supplying electricity to end users than on developing electrical equipment. When electrification began in earnest after 1888, upon the amendment of the 1882 Lighting Act, there existed only a very weak engineering base to support it, leading to slow, expensive, and unimaginative electrification.

Ex ante, my primary concerns were about implementation across the wide expanse of federal applications, supporting the supplemental use of distributional weighting, trying to find a supportable middle ground on discounting using the expected value of bounds and a more consistent scope of analysis. Ex post, I felt heard if not followed, perhaps not uncommon for reviewers.

The sharing economy has expanded rapidly, reshaping consumption, labor, and service delivery across sectors. While much research highlights its benefits, critical perspectives on its limitations remain fragmented. This study addresses that gap through a systematic literature review, identifying and categorizing the main drawbacks of the sharing economy across five dimensions: social, legal, technological, economic, and environmental. By synthesizing these critiques into a cohesive framework, the study offers a more comprehensive understanding of the structural challenges associated with sharing economy platforms. It draws on interdisciplinary perspectives to highlight issues such as platform power asymmetries, regulatory gaps, and labor precarity – concerns that have intensified in the wake of the COVID-19 pandemic. The paper contributes to theory by integrating insights across academic domains and to practice by offering targeted recommendations for policymakers and managers. These include differentiated regulation and improved governance strategies to support fairer, more sustainable platform models.

A new form of human–machine collaborative capabilities has been called to complement traditional capabilities to ensure higher but more responsible performance. We reviewed the extant literature on leadership in the artificial intelligence context to identify the leaders’ essential artificial intelligence-driven capabilities and synthesize the systematic review findings into an integrated conceptual framework to highlight how artificial intelligence-driven organizations could lead more responsibly. We conducted the systematic review and thematic analysis based on 37 papers identified from Emerald Insight, EBSCOhost Business Source Complete, and ScienceDirect databases. We found organizational leaders require technical, adaptive, and transformational capabilities to lead in an artificial intelligence-driven disruptive organizational environment. Our findings contribute to dynamic managerial capability and responsible leadership for performance theories by showing how these three uncovered capabilities enable organizational leaders to deploy dynamic managerial capabilities – sensing, seizing and reconfiguring more responsibly.

Epidemiological and economic (Epi-econ) models account for endogenous interactions between the epidemic and the economy. We explore the applicability of an Epi-econ model to isolate the effects of lockdown policies during coronavirus disease 2019 in the Netherlands. To this aim, we recalibrate the seminal Epi-econ model of Eichenbaum and colleagues with updated parameters specific to the Dutch context. We find that the model performs poorly in replicating observed Epi-econ trends under baseline assumptions. Next, we explore possibilities to improve model fit by relaxing policy and transmission parameters, and by incorporating observed “random noise” in infectivity parameters. This approach spectacularly improves model performance in replicating observed trends. Finally, we test the performance of the model in simulating alternative policy scenarios. We use the Containment and Health Index from the Blavatnik School of Government to replace Dutch policy parameters with exemplary countries on opposite sides of the stringency spectrum. We find that a more stringent lockdown policy would reduce peak prevalence, while aggravating peak economic contraction, but with little effect on overall trends. Conversely, a more lenient lockdown policy was estimated to increase the peak and overall prevalence, with little effect on economic outcomes. We conclude that while rigorous adjustments to existing models were required, a combined Epi-econ model could be informative to policymakers in assessing alternative lockdown policy options.

In an era of fragmented global production and domestic decentralization, middle-income countries confront the complex challenge of industrial upgrading. While national governments remain central to industrial policy design and funding, upgrading unfolds through multi-level interactions between state and business actors across international, national, and subnational spheres. This raises a critical question: How do local political-economic coalitions between firms and governments shape the implementation of national industrial policies and leverage them for upgrading?

This paper moves beyond the predominantly national-level analysis of industrial policy, which often treats implementation as straightforward. Instead, it presents a novel theoretical framework that emphasizes how the interplay of executive leadership, business cohesion, and bureaucratic quality fundamentally shapes industrial upgrading outcomes in today’s globalized, decentralized economy. The framework is tested and refined through a longitudinal comparative study of a key technology sector industrial policy (Prosoft) in two Mexican states - Nuevo León and Puebla - from 2000 to 2015. Drawing on semi-structured interviews with key stakeholders and secondary sources, the analysis demonstrates how distinct regional state-business configurations critically influence both policy implementation and upgrading trajectories.

We find that firms enlarge the executive pay gap when executive mobility is constrained by more enforceable noncompete agreements. We interpret this finding as evidence that firms increase tournament incentives to keep executives incentivized after the loss of valuable outside employment options. Consistent with this argument, we observe more significant increases in pay gaps for executives with greater ex ante mobility options. However, shocks reducing enforceability have a weaker, less robust impact on pay gaps, contributing to asymmetric effects. Following restrictions to mobility, equity portfolios that long (short) firms that boost (do not boost) executive pay gaps generate positive alphas.