This paper analyzes how entrepreneurs fare in an intermediary market segment when the segment is closely attached to a single supplier market. While focusing on two structural constraints, organizational structure and competitive pressure, I build off of the fact that in the past thirty years in the U.S. beer industry, as the number of beer producers (i.e. brewers) proliferated, their intermediaries (i.e. wholesalers) declined. Using establishment-level restricted-access economic microdata from the Longitudinal Business Database, I examine what happens with intermediaries when (some) producers start competing on product variety instead of competing on scale. Piecewise exponential survival models show that Stinchcombe's 'liability of newness' principle can get suspended and certain newcomers have better survival chances than industry incumbents. I call this effect the potential of newness under which entrepreneurial establishments fare better if they are part of well-resourced multiunit firms. Furthermore, I show that these resource-rich entrepreneurs benefit from the potential of newness especially in areas with competition-laden history and where the industry experiences shakeouts. For market incumbents, the more competition-laden the history of the local market, the higher the hazards of current time establishment failure. For multiunit entrepreneurs, however, a more competition-laden history of the local market is associated with a decrease in the hazards of current time establishment failure. This paper highlights that market structure not only enables but sometimes traps already existing organizations and make them less adaptive to changing logics of competition. The results highlight how organizational factors and geography create inequalities among intermediary organizations.
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The Dynamics of Market Structure and Market Size in Two Health Services Industries
October 2007
Working Paper Number:
CES-07-26
The relationship between the size of a market and the competitiveness of the market has been of long-standing interest to IO economists. Empirical studies have used the relationship between the size of the geographic market and both the number of firms in the market and the average sales of the firms to draw inferences about the degree of competition in the market. This paper extends this framework to incorporate the analysis of entry and exit flows. A key implication of recent entry and exit models is that current market structure will likely depend upon history of past participation. The paper explores these issues empirically by examining producer dynamics for two health service industries, dentistry and chiropractic services. We find that the number of potential entrants and past number of incumbent firms are correlated with current market structure. The empirical results also show that as market size increases the number of firms rises less than proportionately, firm size increases, and average productivity increases. However, the magnitude of the correlations are sensitive to the inclusion of the market history variables.
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Do Market Leaders Lead in Business Process Innovation? The Case(s) of E-Business Adoption
April 2011
Working Paper Number:
CES-11-10
This paper investigates the relationship between market position and the adoption of IT-enabled process innovations. Prior research has focused overwhelmingly on product innovation and garnered mixed empirical support. I extend the literature into the understudied area of business process innovation, developing a framework for classifying innovations based on the complexity, interdependence, and customer impact of the underlying business process. I test the framework's predictions in the context of ebuying and e-selling adoption. Leveraging detailed U.S. Census data, I find robust evidence that market leaders were significantly more likely to adopt the incremental innovation of e-buying but commensurately less likely to adopt the more radical practice of e-selling. The findings highlight the strategic significance of adjustment costs and co-invention capabilities in technology adoption, particularly as businesses grow more dependent on new technologies for their operational and competitive performance.
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Brighter Prospects? Assessing the Franchise Advantage using Census Data
January 2017
Working Paper Number:
CES-17-21
This paper uses Census micro data to examine how starting a business as a franchise rather than an independent business affects its survival and growth prospects. We first consider the factors that influence the business owner's decision about being franchised, and then use different empirical approaches to correct for selection bias in our performance analyses. We find that franchised businesses on average benefit from higher survival rates and faster initial growth relative to independent businesses. However, the effects are not large and, conditional on first-year survival, the differences basically disappear. We briefly discuss potential mechanisms to explain these results. U.S. Census Bureau. All results have been reviewed to ensure that no confidential information is disclosed. Support for this research at the Michigan Census Research Data Center is gratefully acknowledged.
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Whose Neighborhood Now? Gentrification and Community Life in Low-Income Urban Neighborhoods
June 2024
Working Paper Number:
CES-24-29
Gentrification is a process of urban change that has wide-ranging social and political impacts, but previous studies provide divergent findings. Does gentrification leave residents feeling alienated, or does it bolster neighborhood social satisfaction? Politically, does urban change mobilize residents, or leave them disengaged? I assess a national, cross-sectional sample of about 17,500 respondents in lower-income urban neighborhoods, and use a structural equation modeling approach to model six latent variables pertaining to local social environment and political participation. Amongst the full sample, gentrification has a positive association with all six factors. However, this relationship depends upon respondents' level of income, length of residency, and racial identity. White residents and those with shorter length of residency report higher levels of social cohesion as gentrification increases, but there is no such association amongst racial minority groups and longer-term residents. This finding aligns with a perspective on gentrification as a racialized process, and demonstrates that gentrification-related amenities primarily serve the interests of white residents and newcomers. All groups, however, are more likely to participate in neighborhood politics as gentrification increases, drawing attention to the agency of local residents as they attempt to influence processes of urban change.
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Entry, Exit, and the Determinants of Market Structure
September 2009
Working Paper Number:
CES-09-23
Market structure is determined by the entry and exit decisions of individual producers. These decisions are driven by expectations of future profits which, in turn, depend on the nature of competition within the market. In this paper we estimate a dynamic, structural model of entry and exit in an oligopolistic industry and use it to quantify the determinants of market structure and long-run firm values for two U.S. service industries, dentists and chiropractors. We find that entry costs faced by potential entrants, fixed costs faced by incumbent producers, and the toughness of short-run price competition are all important determinants of long run firm values and market structure. As the number of firms in the market increases, the value of continuing in the market and the value of entering the market both decline, the probability of exit rises, and the probability of entry declines. The magnitude of these effects differ substantially across markets due to differences in exogenous cost and demand factors and across the dentist and chiropractor industries. Simulations using the estimated model for the dentist industry show that pressure from both potential entrants and incumbent firms discipline long-run profits. We calculate that a seven percent reduction in the mean sunk entry cost would reduce a monopolist's long-run profits by the same amount as if the firm operated in a duopoly.
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Survival Patterns Among Newcomers to Franchising
January 1997
Working Paper Number:
CES-97-01
This study analyzes survival patterns among franchisee firms and establishments that began operations in 1986 and 1987. Differing methodologies and data bases are utilized to demonstrate that 1) franchises have higher survival rates than independents, and 2) franchises have lower survival rates than independent business formations. Analyses of corporate establishment data generate high franchisee survival rates relative to independents, while analyses of young firm data generate the opposite pattern. In either case, the franchise trait is one of several determinants of survival prospects. The larger-scale, more established firms consistently stay in operation more frequently than smaller-scale, younger firms. Analysis of all corporate establishment restaurant units opened in 1986 or 1987 that use paid employees in 1987 helps to reconcile the seeming inconsistencies reported above. Most of the young franchisee units were not owned by young firms: rather, their parents were multi-establishment franchisees, and most of them were mature firms. Among the true newcomers, franchise survival rates are low; among the entrenched multi-establishment franchisees, survival rates were high.
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Survival Patterns Among Newcomers To Franchising
May 1997
Working Paper Number:
CES-97-05
This study analyzes survival patterns among franchisee firms adn establishments that began operations in 1986 and 1987. Differing methodologies and data bases are utilized to demonstrate that 1) franchises have higher survival rates than independents, and 2) franchises have lower survival rates than independent business formations. Analyses of corporate establishment data generate high franchisee survival rates relative to independents, while analyses of young firm data generate the opposite pattern. In either case, the franchise trait is one of several determinants of survival prospects. The larger-scale, more established firms consistently stay in operation more frequently than smaller-scale, younger firms. Analysis of all corporate establishment restaurant units opened in 1986 or 1987 that use paid employees in 1987 helps to reconcile the seeming inconsistencies reported above. Most of the young franchisee units were not owned by young firms: rather, their parents were multi-establishment franchisees, and most of them were mature firms. Among the true newcomers, franchise survival rates are low; among the entrenched multi-establishment franchisees, survival rates were high.
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Exploring New Ways to Classify Industries for Energy Analysis and Modeling
November 2022
Working Paper Number:
CES-22-49
Combustion, other emitting processes and fossil energy use outside the power sector have become urgent concerns given the United States' commitment to achieving net-zero greenhouse gas emissions by 2050. Industry is an important end user of energy and relies on fossil fuels used directly for process heating and as feedstocks for a diverse range of applications. Fuel and energy use by industry is heterogeneous, meaning even a single product group can vary broadly in its production routes and associated energy use. In the United States, the North American Industry Classification System (NAICS) serves as the standard for statistical data collection and reporting. In turn, data based on NAICS are the foundation of most United States energy modeling. Thus, the effectiveness of NAICS at representing energy use is a limiting condition for current
expansive planning to improve energy efficiency and alternatives to fossil fuels in industry. Facility-level data could be used to build more detail into heterogeneous sectors and thus supplement data from Bureau of the Census and U.S Energy Information Administration reporting at NAICS code levels but are scarce. This work explores alternative classification schemes for industry based on energy use characteristics and validates an approach to estimate facility-level energy use from publicly available greenhouse gas emissions data from the U.S. Environmental Protection Agency (EPA). The approaches in this study can facilitate understanding of current, as well as possible future, energy demand.
First, current approaches to the construction of industrial taxonomies are summarized along with their usefulness for industrial energy modeling. Unsupervised machine learning techniques are then used to detect clusters in data reported from the U.S. Department of Energy's Industrial Assessment Center program. Clusters of Industrial Assessment Center data show similar levels of correlation between energy use and explanatory variables as three-digit NAICS codes. Interestingly, the clusters each include a large cross section of NAICS codes, which lends additional support to the idea that NAICS may not be particularly suited for correlation between energy use and the variables studied. Fewer clusters are needed for the same level of correlation as shown in NAICS codes. Initial assessment shows a reasonable level of separation using support vector machines with higher than 80% accuracy, so machine learning approaches may be promising for further analysis. The IAC data is focused on smaller and medium-sized facilities and is biased toward higher energy users for a given facility type. Cladistics, an approach for classification developed in biology, is adapted to energy and process characteristics of industries. Cladistics applied to industrial systems seeks to understand the progression of organizations and technology as a type of evolution, wherein traits are inherited from previous systems but evolve due to the emergence of inventions and variations and a selection process driven by adaptation to pressures and favorable outcomes. A cladogram is presented for evolutionary directions in the iron and steel sector. Cladograms are a promising tool for constructing scenarios and summarizing directions of sectoral innovation.
The cladogram of iron and steel is based on the drivers of energy use in the sector. Phylogenetic inference is similar to machine learning approaches as it is based on a machine-led search of the solution space, therefore avoiding some of the subjectivity of other classification systems. Our prototype approach for constructing an industry cladogram is based on process characteristics according to the innovation framework derived from Schumpeter to capture evolution in a given sector. The resulting cladogram represents a snapshot in time based on detailed study of process characteristics. This work could be an important tool for the design of scenarios for more detailed modeling. Cladograms reveal groupings of emerging or dominant processes and their implications in a way that may be helpful for policymakers and entrepreneurs, allowing them to see the larger picture, other good ideas, or competitors. Constructing a cladogram could be a good first step to analysis of many industries (e.g. nitrogenous fertilizer production, ethyl alcohol manufacturing), to understand their heterogeneity, emerging trends, and coherent groupings of related innovations.
Finally, validation is performed for facility-level energy estimates from the EPA Greenhouse Gas Reporting Program. Facility-level data availability continues to be a major challenge for industrial modeling. The method outlined by (McMillan et al. 2016; McMillan and Ruth 2019) allows estimating of facility level energy use based on mandatory greenhouse gas reporting. The validation provided here is an important step for further use of this data for industrial energy modeling.
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THE DYNAMICS OF LATINO-OWNED BUSINESS WITH COMPARISIONS TO OTHER ETHNICITIES
January 2016
Working Paper Number:
CES-16-33
This paper employs the Michigan Census Research Data Center to merge three limited-access Census Bureau data sets by individual firm and establishment level to investigate the factors associated with the Latino-owned Business (LOB) location and dynamics over time. The three main LOB outcomes under analysis are as follows: (1) the probability of a business being Latino-owned as opposed to a business being Asian-owned, Black-owned, or White-owned; (2) the probability of new business entry and exit; and (3) LOB employment growth. This paper then compares these factors associated with LOB with past findings on businesses that are Asian-owned, Black-owned, and White-owned. Some notable findings include: (1) only Black business owners are less associated with using personal savings as start-up capital than Latinos; (2) the only significant coefficient on start-up capital source is personal savings and it increases the odds of survival of a Latino business by 4%; (3) on average, having Puerto Rican ancestry decreases the odds of business survival; and (4) LOB are relatively likely to start a business with a small amount of capital, which, in turn, limits their future growth.
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The Extent and Nature of Establishment Level Diversification in Sixteen U.S. Manufacturing Industries
August 1990
Working Paper Number:
CES-90-08
This paper examines the heterogeneity of establishments in sixteen manufacturing industries. Basic statistical measures are used to decompose product diversification at the establishment level into industry, firm, and establishment effects. The industry effect is the weakest; nearly all the observed heterogeneity is establishment specific. Product diversification at the establishment level is idiosyncratic to the firm. Establishments within a firm exhibit a significant degree of homogeneity, although the grouping of products differ across firms. With few exceptions, economies of scope and scale in production appear to play a minor role in the establishment's mix of outputs.
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