Managing in turbulence: how the capacity for resilience influences creativity

How do companies manage to compete in a marketplace marked by turbulence, and not be outcompeted? In our study we assess the resources used to create resilience in organizations and how each of these resources relates to organizational creativity. We show that organizational resilience is positively related to organizational creativity. Specifically, our study highlights that cognitive, emotional, and structural resources are important resources for organizations wanting to become creative. Our results are based upon a pilot in‐depth qualitative case study followed by a survey of medium‐sized firms. The results in our study advance the emergent literature on resilience and on the practical applications of resilience in organizations. From a practical point of view, managers may realize that they have to develop a capacity for resilience (i.e. what they have to do) in order to have a creative organization, but a far bigger challenge is to understand the how; how the capacity for resilience is built. Our research shows that if managers truly want to manage in turbulence and still have a creative organization, they need to put a strong emphasis on the soft skills in the organization, in addition to the structural resources.     

Managerial Incentives and Stock Price Manipulation

We present a rational expectations model of optimal executive compensation in a setting where managers are in a position to manipulate short‐term stock prices and the manipulation propensity is uncertain. We analyze the tradeoffs involved in conditioning pay on long‐ versus short‐term performance and show how manipulation, and investors' uncertainty about it, affects the equilibrium pay contract and the informativeness of prices. Firm and manager characteristics determine the optimal compensation scheme: the strength of incentives, the pay horizon, and the use of options. We consider how corporate governance and disclosure regulations can help create an environment that enables better contracting.     

Corporate governance performance ratings with machine learning

We use machine learning with a cross-sectional research design to predict governance controversies and to develop a measure of the governance component of the environmental, social, governance (ESG) metrics. Based on comprehensive governance data from 2,517 companies over a period of 10 years and investigating nine machine-learning algorithms, we find that governance controversies can be predicted with high predictive performance. Our proposed governance rating methodology has two unique advantages compared with traditional ESG ratings: it rates companies' compliance with governance responsibilities and it has predictive validity. Our study demonstrates a solution to what is likely the greatest challenge for the finance industry today: how to assess a company's sustainability with validity and accuracy. Prior to this study, the ESG rating industry and the literature have not provided evidence that widely adopted governance ratings are valid. This study describes the only methodology for developing governance performance ratings based on companies' compliance with governance responsibilities and for which there is evidence of predictive validity.     

Welfare Effects of Changing Technological Efficency in Regulated Open-Access Fisheries

Environmental and Resource Economics - Small-scale fisheries often operate under conditions of regulated open access; that is, the fishery is subject to natural or regulatory constraints on fishing...     

Affective Computing in Marketing: Practical Implications and Research Opportunities Afforded by Emotionally Intelligent Machines

After years of using AI to perform cognitive tasks, marketing practitioners can now use it to perform tasks that require emotional intelligence. This advancement is made possible by the rise of affective computing, which develops AI and machines capable of detecting and responding to human emotions. From market research, to customer service, to product innovation, the practice of marketing will likely be transformed by the rise of affective computing, as preliminary evidence from the field suggests. In this Idea Corner, we discuss this transformation and identify the research opportunities that it offers.

     

Is the US Phillips curve stable? Evidence from Bayesian vector autoregressions*

It has been claimed that the fall in US inflation during the Great Recession was surprisingly small. One possible explanation for this is that the Phillips curve is unstable and that its slope was lower around the Great Recession. We investigate the importance of time-varying parameters using Bayesian vector autoregressions for inflation and unemployment. We find support for time variation in the inflation equation and an unstable Phillips curve that was somewhat flatter between 2005 and 2013. However, conditional forecasts mostly suggest that inflation was not unexpectedly high around the Great Recession, which puts the claim of a “missing disinflation” into question.     

Students’ knowledge of emerging technology and sustainability through a design activity in technology education

International Journal of Technology and Design Education - The purpose of this study is to explore whether, and if so how, a design activity could encourage students to express and develop...     

Vox Populi,Vox Dei? Tacit collusion in politics

We study competition between political parties in repeated elections with probabilistic voting. This model entails multiple equilibria, and we focus on cases where political collusion occurs. When parties hold different opinions on some policy, they may take different policy positions that do not coincide with the median voter's preferred policy platform. In contrast, when parties have a mutual understanding on a particular policy, their policy positions may converge (on some dimension) but not to the median voter's preferred policy. That is to say, parties can tacitly collude with one another, despite political competition. Collusion may collapse, for instance, after the entry of a new political party. This model rationalizes patterns in survey data from Sweden, where politicians on different sides of the political spectrum take different positions on economic policy but similar positions on refugee intake—diverging from the average voter's position, but only until the entry of a populist party.     

A note of caution on the relation between money growth and inflation

We assess the bivariate relation between money growth and inflation in the euro area and the United States using hybrid time-varying parameter Bayesian VAR models. Model selection based on marginal likelihoods suggests that the relation is statistically unstable across time in both regions. The effect of money growth on inflation weakened notably after the 1980s before strengthening after 2020. There is evidence that this time variation is related to the pace of price changes, as we find that the maximum impact of money growth on inflation is increasing in the trend level of inflation. These results caution against asserting a simple, time-invariant relationship when modeling the joint dynamics of monetary aggregates and consumer prices.