Research Interests: competitive strategy, dynamic capabilities, formal modeling, resource based view
Phebo Wibbens is a doctoral candidate in Management, subfield Strategy, at The Wharton School, University of Pennsylvania. He applies formal modeling to empirical data in order to better understand how resource dynamics shape long term company returns. His dissertation committee consists of Nicolaj Siggelkow (advisor), Dan Levinthal (chair) and David Hsu. Before joining Wharton, Phebo worked for 8 years at Bain & Company in Amsterdam and Boston, first as a consultant and more recently leading the research team in the Global Strategy Practice. He is the writer and co-author of a Dutch management book studying iconic organizations such as the Royal Concertgebouw Orchestra (translated in 2016 as Iconic: How to create a virtuous circle of success). Phebo holds a M.Sc. degree in Management from the Wharton School, University of Pennsylvania as well as M.Sc. degrees (cum laude) in both Physics and Mathematics from the University of Groningen (The Netherlands). In September 2018, Phebo will take on a position as Assitant Professor at INSEAD in Fontainebleau (France).
Please refer to the Research tab for more detailed information by project, which for some projects also includes data for download (e.g., LIVA for all US companies 1980-2015).
Phebo Wibbens (Draft), The dynamics of resource competition: implications for firm and industry components of returns.
Abstract: This study introduces a dynamic model of resource competition to better understand the mechanisms behind firm-specific and industry-level variations in returns. The model is based on a dynamic game in which two firms continuously invest money to compete for a finite amount of resources. The model shows that the investment dynamics for scarce resources amplify any idiosyncratic shocks, thus explaining the empirical regularity that variations in return are mainly firm or business specific. Moreover, the model predicts that several industry-level resource characteristics, such as depreciation rate and scale economies, affect the extent to which variations in returns are driven by firm versus industry effects. Empirical results from a hierarchical analysis of stock market returns indeed indicate clear differences across industries that are persistent over time and broadly consistent with the predictions of the model.
Phebo Wibbens (Under Review), Performance persistence in the presence of higher order resources.
Abstract: This paper introduces a formal model of how higher order resources affect profit persistence. Higher order resources are resources that do not affect profits directly, but can affect other resources that in turn affect profits over time. The model shows that higher order resources lead to persistence not only in the level of profits, but also in their growth. The derived stochastic time series structure of profits provides an empirical test for the presence of higher order resources. Empirical estimation of the model using both classical and Bayesian hierarchical methods on a 30-year panel of more than 2,400 US firms provides support for the importance of higher order resources in shaping profit persistence.
Phebo Wibbens and Nicolaj Siggelkow (Under Revision), Introducing LIVA to measure long-term firm performance.
Abstract: In this paper we introduce lifetime (or long-term) investor value appropriation (LIVA) to measure firm performance, defined as the ex post value of discounted cash flows over a firm’s lifetime. Unlike other commonly used measures of firm performance, such as return on assets, Tobin’s q, economic profit, or total shareholder return, LIVA captures long-term returns vis-à-vis the cost of capital, profitable growth, as well as the size of the economic impact in a single metric. Moreover, we show that LIVA can be equivalently operationalized using cash flow data, accounting profits, or shareholder return data. Finally, two exploratory empirical studies illustrate how LIVA can be operationalized and provide new strategic insights beyond currently used measures.
Description: For this paper, we make available a database with the LIVA by year for all publicly listed US firms from 1980 to 2015, based on the CRSP database. It is in CSV format, which can be opened in R, Stata, Excel, etc. The LIVA is calculated in billion (000,000,000) US dollars, and is indexed by the CRSP identifiers permno and permco. For any given company, its LIVA can be calculated by adding the annual LIVA in the database over all years in the time period of interest. The LIVA in each year has been calculated using monthly total shareholder return and market capitalization data, using the market return as the cost of equity [see equation (2) in the AoM Best Paper proceedings version of the paper]. Please refer to the paper for further details on calculating and interpreting LIVA. A short version of the paper has been published in the AoM Best Paper proceedings 2017, and a full version is available from the authors. Please cite the paper when using these data, and reach out to the authors for any questions. The database can be downloaded under Related.
Abstract: Competitive advantage, a central construct in the strategy field, has been defined in two distinct ways in the contemporary literature: based on superior performance, or based on superior value creation. These two definitions are, however, neither necessary nor sufficient for each other. Instead of trying to find a universal, single definition of competitive advantage, we propose the notion of a ladder of competitive advantage that describes three different kinds of advantages that differ in terms of scope and time horizon: at the single-transaction level, at the business unit-year level, and at the firm-lifetime level. The ladder can help resolve existing confusions in the literature, as well as provide a deeper insight in how managers can create and appropriate long-term value.
Xavier Bekaert, Gillis Jonk, Jan Raes, Phebo Wibbens, Iconic: How to create a virtuous circle of success (2013)
We all spend much of our lives in organizations. Most of us are born in organizations, educated in organizations, and work in organizations. Organizations emerge because individuals can't (or don't want to) accomplish their goals alone. Management is the art and science of helping individuals achieve their goals together. Managers in an organization determine where their organization is going and how it gets there. More formally, managers formulate strategies and implement those strategies. This course provides a framework for understanding the opportunities and challenges involved in formulating and implementing strategies by taking a "system" view of organizations,which means that we examine multiple aspects of how managers address their environments, strategy, structure, culture, tasks, people, and outputs, and how managerial decisions made in these various domains interrelate. The course will help you to understand and analyze how managers can formulate and implement strategies effectively. It will be particularly valuable if you are interested in management consulting, investment analysis, or entrepreneurship - but it will help you to better understand and be a more effective contributor to any organizations you join, whether they are large, established firms or startups.