Title: The Digital Commons
Description: The classic economic concept of the tragedy of the commons occurs when individuals overuse a public good, resulting in the complete depletion of the good. Comparatively, in the digital world public goods are non-rival and essentially infinitely abundant. However, the nearly infinite supply of a public digital good can still be tragic, albeit in a different manner. For example, the rise of the free crowdsourced digital good Wikipedia essentially destroyed billions of dollars of economic value in the encyclopedia industry. Despite this apparent destruction of value, the reduction in prices for many digital goods also represents a great opportunity. Firms are increasingly relying on the crowd to help shape future products, provide value for their customers, and build software crucial to the firm’s production process. This phenomenon is leading to a weakening of firm boundaries and a change in the nature of the firm’s innovative processes. My dissertation is comprised of four studies that explore this phenomenon to better understand the transformative nature of the digital commons.

The first chapter, “Innovating Without Information Constraints: Organizations, Communities, and Innovation When Information Costs Approach Zero” (w/ Elizabeth Altman, and Michael Tushman), explores how technological progress and reductions in information costs are leading firms to increasingly engage with external digital communities. In particular, firms are increasingly engaging with networks of developers, external labor marketplaces, and users, with the latter frequently occurring through the process of crowdsourcing. This engagement leads to a weakening of firm boundaries such that the locus of innovation and value creation moves outside the boundaries of the firm. The increase in this phenomenon motivates a reevaluation of many traditional theories of how firms organize and innovate. Specifically, we consider how shifts in information costs affect the classic organizational concepts of firm boundaries, business models, interdependence, leadership, identity, search, and intellectual property. In turn, these effects on the firm’s organization alter how the firm innovates.

The second chapter, “Digital Dark Matter and the Economic Contribution of Apache” (w/ Shane Greenstein) examines the impact of crowdsourced digital goods at a macro-level. We show that due to its reliance on price to measure value, GDP calculations do not account for “digital dark matter”, digital goods and services that are non-pecuniary and effectively limitless inputs into production. We scan 1% of the 1.5 billion IP addresses in the United States to measure the types of web servers businesses and individuals employ. We estimate the value of the free and open source nature of the predominant web server, Apache, by comparing it to the closest pecuniary alternative, Microsoft’s Internet Information Services (IIS) server. Our analysis shows that the lack of price for the Apache server leads to an underestimation of GDP by upwards of $12 billion. Although this is the value from only one piece of digital dark matter, this miscalculation represents a large proportion of all software sales and significantly alters economic growth projections.

The third chapter, “Crowdsourced Digital Goods and Firm Productivity: Evidence from Open Source Software”, empirically measures the firm-level productivity impact of managers’ decisions to use non-pecuniary digital inputs from the crowd. Existing literature examining the impact of IT on productivity does not account for investments in such goods, as their use cannot properly be captured by traditional measurement methods based on price. Therefore, their contribution to the firm’s production process is currently unexplored, despite mounting evidence that firms are increasingly relying on these types of inputs. Employing data from a survey of technology use at nearly 2,000 firms over 10 years, I find that a 1% increase in the amount of non-pecuniary open source software (OSS) used by a firm leads to a .073% increase in productivity. This translates to a $1.35 million increase in productivity for the average firm in my sample. This is more than double the magnitude of the coefficient on investments in traditional pecuniary IT capital. I find that this effect is greater for larger firms and for firms in the services industry. I use inverse probability weighting, instrumental variables, firm-fixed effects and data on managerial quality from the World Management Survey to add support to a causal interpretation of these results.

The final chapter of my dissertation, “Organizational Learning Through Contributing to Public Goods: Evidence from Open Source Software,” builds on the concepts developed in the other three to explore how firms that engage external communities and contribute to the development of crowdsourced digital goods enhance their ability to extract value from technology-related inputs via increased learning about how these complex goods operate. This study explores this mechanism by using data on firm contributions to Linux, an OSS operating system that is an important public digital good created via crowdsourcing. Using coarsened exact matching and inverse probability weighting to address endogeneity concerns, this study shows that firms who contribute to the development of OSS capture more productive value from the use of OSS than their non-contributing peers through a process similar to absorptive capacity. Further, this learning has a spillover effect that allows contributing firms to capture more productive value from all of their IT investments, not just OSS.

Together, the results of these four studies show that the digital commons can help create a great deal of economic value, but that this value is difficult to measure via standard economic methods that rely on price to reflect value. These results have important strategic implications for managers and policy makers to consider as organizations increasingly engage with external communities and ecosystems to innovate and create value.