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Small Business Economics

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06.01.2018

Initial submarket positioning and firm survival: evidence from the British automobile industry, 1895–1970

verfasst von: Zhao Rong, David C. Broadstock, Yuanyuan Peng

Erschienen in: Small Business Economics | Ausgabe 4/2018

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Abstract

A firm’s initial choice of its submarket may have a long-lasting influence on its subsequent performance. By examining the duration of firm survival in the British automobile industry between 1895 and 1970, we find that a firm’s initial submarket positioning (defined by the quality level of its first-launched model) influenced its subsequent survival. Additionally, we find that the initial positioning also helped firms to survive a major shakeout, and argue that innovation and path-dependence were two possible channels through which the benefits of initial positioning were felt.

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Boschma and Wenting (2007) explain the uniqueness in Great Britain as the result of small producers filling market niches with the production of high-priced, high-quality cars, which suggests that firms’ product positioning may have influenced their subsequent survival.

However, it may have to wait until a dominant design/submarket arises before this first-mover advantage from R&D can be materialized, as pointed out by Bhaskarabhatla and Klepper (2014).

Engine capacity is a parameter widely used to identify submarkets in the automobile literature (e.g., Dobrev et al. 2001; Argyres and Bigelow 2007; Argyres et al. 2015).

Studies also find that the survival rate increases with firms’ entry size of employment (Audretsch et al. 2000). Unfortunately, we do not have such entry information in our data.

In contrast, Christensen et al. (1998) present an opposing story: in the US disk drive industry the shakeout resulted in new entrants displacing early incumbents.

It is possible that foreign companies enter the domestic market by first introducing their low-end models (like Honda’s market positioning when entering the US market). This entry bias would make the competition in low-end market more severely. However, this is not the case in Great Britain. In the first stage of the industry, British automobile market was dominated by luxuriant buyers, who preferred foreign cars, especially French cars, even though the domestic cars had a lower price with a comparable quality. It seems that imports affected the high-end submarket more than the low-end submarket at that time. In the second stage, with government tariff protection, domestic makers were able to “make up the ground loss during the war” (WW I). In the last stage of the industry, Britain became the largest motor exporter in Europe and remained so until 1955. Thus, we do not expect the import effect is the major force that leads to our estimation results.

Though it seems intuitive, we have as yet been unable to incorporate the fact that firms are producing differentiated products into Klepper’s (2002a) dynamic model. For technical reasons, his model regards firms as price takers, making it impossible to address the above issue with only a minor revision to his model.

A dominant design is defined as “the concepts that define how the components of the product interact or relate to each other” (Christensen et al. 1998).

The horsepower tax imposed heavy taxation on cars with high-powered engines, making these cars even less attractive.

As mentioned by Bowden and Turnen (1993), in the USA, the successful experience of Ford and General Motors (GM) was that there were two ways to create a mass market for cars: (1) by lowering the car price as Ford did, or (2) by lowering the initial payment by making credit available as GM did.

It may also be useful to consider the role of transport infrastructure development. In Britain, as well as in the USA, the railroad system was well established before the automobile industry. In the USA, the railroad system was less dense, with just few lines covering long distances and with few inter-connections. In contrast, the railroad system in Britain was far denser covering many parts of the land and therefore the demand for cars was less urgent initially. At the beginning, the automobile was a luxury item for the wealthier parts of society and was not so much required for transport, as much as it was demanded as a status symbol. This could help in part to explain the difference in market structure and its evolution when compared to the USA. A further source of distinction in the markets comes in terms of the labor unions which played an important role in the evolution of the British automobile industry. Because of the influence from labor unions, the adoption of mass production somehow was arguably slower. With these facts in mind, our estimation result does not and should not simply replicate the survival consequence.

We also relieve this restriction and use the 375 firms to rerun the regressions. The major results persist. See details in Appendix Table 9.

We also turn to the dataset used by Boschma and Wenting (2007) who identify mergers and acquisitions, and adjust the exit year in our dataset accordingly.

Noting that the loadings imply speed is negatively related to the principal component, as for instance a higher quarter mile speed contributes positively to this factor, while a faster acceleration contributes negatively.

Prestige is inferred from the fact that the components imply a preference towards vehicles with larger engines that are less fuel efficient, but are not correlated with vehicle speed.

Note that some variables, such as BHP, appear in more than one PC. In fact, each of the estimated PCs in PCA are a combination of all variables that are included in the analysis, but with varying weights. In mechanical terms, each of the PC measures are orthoganalized, and therefore independent to each other by construction. Hence, the inclusion of BHP in more than one PC poses no special concern for estimation.

The interpretation of these vectors as product quality is a matter of convenience in describing the results. One may simply refer these vectors as characteristics rather than quality.

Regarding the entry year, according to the Catalogue, “the years during which a car was available from the manufacturers are not always clearly defined—especially in the early days of motoring. Some cars, though available on paper for a considerable span of time, may only have been produced in any quantity during the first one or 2 years. The converse is also true. Examples of certain models are still running today which were first registered 2 or even 3 years after production was supposed to have ceased! The dates given in the tables are those during which the model was, according to contemporary sources, available from the manufacturers. Where a single date is quoted, this is, in almost all cases, the date of introduction of the model, although is possible that examples of some models were available in the year(s) before it was listed as a production car. A single date (especially before 1920) does not necessarily indicate that production was limited to that year alone, as cars were almost invariably assembled from components for some time after the initial production period. However, after 1920, it can be generally assumed that models given a single date were available only during that year.”

This conclusion is, of course, based on the assumption that the R&D productivity distributions are similar across different cohorts. For the discussion when it is not the case, please refer to Klepper (2002a).

See Thompson (2005, 2007), Klepper (2001, 2002a, 2002b), Klepper and Thompson (2006), Helfat and Lieberman (2002), Cantner et al. (2006), Boschma and Wenting (2007), and Christensen et al. (1998).

Among the 375 firms, there are 278 firms with only one entry model, 64 firms with two entry models, 19 firms with three, and 14 firms above three.

Similarly, Sorenson and Audia (2000) find that new US footwear manufacturers located close to their incumbents despite the fact that their failure hazard increased when local firm density was higher.

For further details, please refer to Boschma and Wenting (2007). There are 218 firms in our data set with valid values of these two variables based on the data set provided by Boschma and Wenting (2007). To ensure the regression with the same sample size, we literately define the two variables equal to zero if their values are missing. To capture the effect of invalid observations, we include a validity dummy. The validity dummy indicates whether a firm has these two variables with valid values; it equals one if so, and zero otherwise. We also repeat the regression by including the log-variable of the number of years the parent firm produced cars as Boschma and Wenting (2007). The major results persist.

We do not need this requirement when initial PC%s are examined. However, this requirement is necessary when current PC%s are examined. To make the sample size comparable between these two settings, we impose this restriction even when initial PC%s are examined. We reach similar results when this restriction is not imposed.

To check the robustness of the results under other specifications, we repeat the regression by using the probit and logit specifications and receive similar results. We also repeat the regression by split the sample based on firm age, and find that the positive PC5% effect is only significant among old firms, which is consistent with the comparative advantage story.

In their study on the shakeout of the US automobile industry, Argures and Bigelow (2007) find that the number of a firm’s models had a negative effect on its exit hazard. They argue that there may be economies of scope across models during the interwar period.

Our patent data are from the April 2016 version of the EPO Worldwide Patent Statistical Database (PATSTAT). It is now widely used in the innovation literature.

We use the following keywords to identify an applicant name as a firm: “COMPANY,” “CORPORATION,” “CO.,” “INCORPORATED,” “INC.,” “LTD.,” and “LIMITED.”

We do find that when we drop patent counts and model counts from the estimation, the coefficient on the Coventry dummy becomes significantly negative.

Changing this threshold to four or 6 years has little influence on our major results because the threshold just lies in WW I.

Notice that the effect of firm age on innovation is significantly positive, which is consistent with Klepper’s (2002a) theory that it is more pro-innovation at the early stage of an industry.

We also confirm the path dependence of other three PC%s as shown in Appendix Table 10.

There are also papers such as Cantner et al. (2012), in which submarkets for the automobile industry are derived from standard industry definitions (e.g., regarding “compact cars” as a submarket). Comparatively, our identification is a relative one and thus more stable over time.

We also find that capacity% is path-dependent in Online Appendix Table 4.

Agarwal, R. (1996). Technological activity and survival of firms. Economics Letters, 52(1), 101–108. https://doi.org/10.1016/0165-1765(96)00837-3.CrossRef

Agarwal, R., & Audretsch, D. B. (2001). Does entry size matter? The impact of the life cycle and technology on firm survival. Journal of Industrial Economics, 49(1), 21–43 https://doi.org/10.1111/1467-6451.00136.CrossRef

Agarwal, R., & Gort, M. (1996). The evolution of markets and entry, exit and survival of firms. Review of Economics and Statistics, 78(3), 489–498 https://doi.org/10.2307/2109796.CrossRef

Agarwal, R., & Gort, M. (2002). Firm and product life cycles and firm survival. American Economic Review, 92(2), 184–190 https://doi.org/10.1257/000282802320189221.CrossRef

Allison, P. D. (1995). Survival analysis using SAS system: A practical guide. SAS Institute.

Anderson, S. P., De Palma, A., & Thisse, J. F. (1987). The CES is a discrete choice model? Economics Letters, 24(2), 139–140. https://doi.org/10.1016/0165-1765(87)90239-4.CrossRef

Argyres, N., & Bigelow, L. (2007). Does transaction misalignment matter for firm survival at all stages of the industry life cycle? Management Science, 53(8), 1332–1344. https://doi.org/10.1287/mnsc.1070.0706.CrossRef

Argyres, N., Bigelow, L., & Nickerson, J. A. (2015). Dominant designs, innovation shocks, and the follower’s dilemma. Strategic Management Journal, 36(2), 216–234. https://doi.org/10.1002/smj.2207.CrossRef

Atanassov, J., Nanda, V., & Seru, A. (2007). Finance and innovation: The case of publicly traded firms. Working Paper: University of Oregon.

Audretsch, D. B. (1991). New-firm survival and the technological regime. Review of Economics and Statistics, 73(3), 441–450 https://doi.org/10.2307/2109568.CrossRef

Audretsch, D. B. (1995). Innovation and industry evolution. MIT Press.

Audretsch, D. B., Houweling, P., & Thurik, A. R. (2000). Firm survival in the Netherlands. Review of Industrial Organization, 16(1), 1–11. https://doi.org/10.1023/A:1007824501527.CrossRef

Audretsch, D. B., & Mahmood, T. (1994). The rate of hazard confronting new firms and plants in US manufacturing. Review of Industrial Organization, 9(1), 41–56. https://doi.org/10.1007/BF01024218.CrossRef

Audretsch, D. B., & Mahmood, T. (1995). New firm survival: New results using a hazard function. Review of Economics and Statistics, 97–103. https://doi.org/10.2307/2109995.CrossRef

Bernard, A. B., & Jensen, J. B. (2007). Firm structure, multinationals, and manufacturing plant deaths. Review of Economics and Statistics, 89(2), 193–204. https://doi.org/10.1162/rest.89.2.193.CrossRef

Bhaskarabhatla, A., & Klepper, S. (2014). Latent submarket dynamics and industry evolution: Lessons from the US laser industry. Industrial and Corporate Change, 23(6), 1381–1415. https://doi.org/10.1093/icc/dtt060.CrossRef

Boschma, R. A., & Wenting, R. (2007). The spatial evolution of the British automobile industry: Does location matter? Industrial and Corporate Change, 16(2), 213–238. https://doi.org/10.1093/icc/dtm004.CrossRef

Bowden, S. M. (1991). Demand and supply constraints in the inter-war UK car industry: Did the manufacturers get it right? Business History, 33(2), 241–267. https://doi.org/10.1080/00076799100000055.CrossRef

Bowden, S., & Turner, P. (1993). The demand for consumer durables in the United Kingdom in the interwar period. Journal of Economic History, 53(02), 244–258. https://doi.org/10.1017/S0022050700012894.CrossRef

Buenstorf, G., & Klepper, S. (2010). Submarket dynamics and innovation: The case of the US tire industry. Industrial and Corporate Change, 19(5), 1563–1587. https://doi.org/10.1093/icc/dtq044.CrossRef

Cantner, U., Dreßler, K., & Krüger, J. J. (2006). Firm survival in the German automobile industry. Empirica, 33(1), 49–60. https://doi.org/10.1007/s10663-006-9006-z.CrossRef

Cantner, U., Krüger, J. J., & Söllner, R. (2012). Product quality, product price, and share dynamics in the German compact car market. Industrial and Corporate Change, 21(5), 1085–1115. https://doi.org/10.1093/icc/dts002.CrossRef

Cantner, U., Krüger, J. J., & Von Rhein, K. (2011). Knowledge compensation in the German automobile industry. Applied Economics, 43(22), 2941–2951. https://doi.org/10.1080/00036840902762738.CrossRef

Christensen, C. M. (1993). The rigid disk drive industry: A history of commercial and technological turbulence. Business History Review, 67(04), 531–588. https://doi.org/10.2307/3116804.CrossRef

Christensen, C. M. (2013). The Innovator’s dilemma: When new technologies cause great firms to fail. Harvard Business Review Press.

Christensen, C. M., Suárez, F. F., & Utterback, J. M. (1998). Strategies for survival in fast-changing industries. Management Science, 44(12-part-2), S207–S220. https://doi.org/10.1287/mnsc.44.12.s207.CrossRef

Clark, K. B., & Fujimoto, T. (1991). Product development performance: Strategy, organization, and management in the world auto industry. Harvard Business Press.

Culshaw, D., & Horrobin, P. (2006). The complete catalog of British cars 1895–1975. Veloce Publishing Ltd..

Dixit, A. K., & Stiglitz, J. E. (1977). Monopolistic competition and optimum product diversity. American Economic Review, 67(3), 297–308.

Dobrev, S. D., Kim, T. Y., & Hannan, M. T. (2001). Dynamics of niche width and resource partitioning. American Journal of Sociology, 106(5), 1299–1337. https://doi.org/10.1086/320821.CrossRef

Ejermo, O., & Xiao, J. (2014). Entrepreneurship and survival over the business cycle: How do new technology-based firms differ? Small Business Economics, 43(2), 411–426. https://doi.org/10.1007/s11187-014-9543-y.CrossRef

Esteve-Pérez, S., & Ma-ez-Castillejo, J. A. (2008). The resource-based theory of the firm and firm survival. Small Business Economics, 30(3), 231–249. https://doi.org/10.1007/s11187-006-9011-4.CrossRef

Foreman-Peck, J., Bowden, S., & McKinlay, A. (1995). The British motor industry. Manchester University Press.

Foster, L., Haltiwanger, J., & Syverson, C. (2008). Reallocation, firm turnover, and efficiency: Selection on productivity or profitability. American Economic Review, 98(1), 394–425. https://doi.org/10.1257/aer.98.1.394.CrossRef

Franco, A. M., Sarkar, M. B., Agarwal, R., & Echambadi, R. (2009). Swift and smart: The moderating effects of technological capabilities on the market pioneering–firm survival relationship. Management Science, 55(11), 1842–1860 https://doi.org/10.1287/mnsc.1090.1061.CrossRef

Gans, J. (2016). The disruption dilemma. MIT Press. https://doi.org/10.7551/mitpress/9780262034487.001.0001.

Georgano, N. (2000). The Beaulieu encyclopedia of the automobile. Taylor & Francis.

Hall, B. H., & Lerner, J. (2009). The financing of R&D and innovation. NBER Working Paper No. 15325.

Hannan, M. T., Carroll, G. R., Dundon, E. A., & Torres, J. C. (1995). Organizational evolution in a multinational context: Entries of automobile manufacturers in Belgium, Britain, France, Germany, and Italy. American Sociological Review, 509–528. https://doi.org/10.2307/2096291.CrossRef

Helfat, C. E., & Lieberman, M. B. (2002). The birth of capabilities: Market entry and the importance of pre-history. Industrial and Corporate Change, 11(4), 725–760. https://doi.org/10.1093/icc/11.4.725.CrossRef

Klepper, S. (2001). The evolution of the U.S. automobile industry and Detroit as its capital. Mimeo: Carnegie Mellon University.

Klepper, S. (2002a). Firm survival and the evolution of oligopoly. RAND Journal of Economics, 33(1), 37–61. https://doi.org/10.2307/2696374.CrossRef

Klepper, S. (2002b). The capabilities of new firms and the evolution of the US automobile industry. Industrial and Corporate Change, 11(4), 645–666. https://doi.org/10.1093/icc/11.4.645.CrossRef

Klepper, S., & Thompson, P. (2006). Submarkets and the evolution of market structure. RAND Journal of Economics, 37(4), 861–886. https://doi.org/10.1111/j.1756-2171.2006.tb00061.x.CrossRef

Klepper, S., & Simons, K. L. (2005). Industry shakeouts and technological change. International Journal of Industrial Organization, 23(1), 23–43. https://doi.org/10.1016/j.ijindorg.2004.11.003.CrossRef

Lin, P. C., & Huang, D. S. (2008). Technological regimes and firm survival: Evidence across sectors and over time. Small Business Economics, 30(2), 175–186. https://doi.org/10.1007/s11187-006-9026-x.CrossRef

Manjón-Antolín, M. C., & Arauzo-Carod, J. M. (2008). Firm survival: Methods and evidence. Empirica, 35(1), 1–24. https://doi.org/10.1007/s10663-007-9048-x.CrossRef

Mata, J., & Portugal, P. (1994). Life duration of new firms. Journal of Industrial Economics, 42(3), 227–245. https://doi.org/10.2307/2950567.CrossRef

Oba, S., Sato, M. A., Takemasa, I., Monden, M., Matsubara, K. I., & Ishii, S. (2003). A Bayesian missing value estimation method for gene expression profile data. Bioinformatics, 19(16), 2088–2096. https://doi.org/10.1093/bioinformatics/btg287.CrossRef

Porter, M. E. (1980). Competitive strategy: Techniques for analyzing industries and competitors. New York: Free Press.

Rhee, M., Kim, Y. C., & Han, J. (2006). Confidence in imitation: Niche-width strategy in the UK automobile industry. Management Science, 52(4), 501–513. https://doi.org/10.1287/mnsc.1050.0494.CrossRef

Sorenson, O., & Audia, P. G. (2000). The social structure of entrepreneurial activity: Geographic concentration of footwear production in the United States, 1940–1989. American Journal of Sociology, 106(2), 424–462. https://doi.org/10.1086/316962.CrossRef

Stiglitz, J. E. (1985). Credit markets and capital control. Journal of Money, Credit and Banking, 17(2), 133–152 https://doi.org/10.2307/1992329.CrossRef

Strotmann, H. (2007). Entrepreneurial survival. Small Business Economics, 28(1), 87–104. https://doi.org/10.1007/s11187-005-8859-z.CrossRef

Thompson, P. (2005). Selection and firm survival: Evidence from the shipbuilding industry, 1825–1914. Review of Economics and Statistics, 87(1), 26–36. https://doi.org/10.1162/0034653053327531.CrossRef

Thompson, P. (2007). Founder quality and firm performance: Implications for local development strategies. Australian Economic Review, 40(1), 97–105 https://doi.org/10.1111/j.1467-8462.2007.00445.x.CrossRef

Thoms, D., & Donnelly, T. (1985). The motor car industry in Coventry since the 1890's. Taylor & Francis.

Tsvetkova, A., Thill, J. C., & Strumsky, D. (2014). Metropolitan innovation, firm size, and business survival in a high-tech industry. Small Business Economics, 43(3), 661–676. https://doi.org/10.1007/s11187-014-9550-z.CrossRef

Tveterås, R., & Eide, G. E. (2000). Survival of new plants in different industry environments in Norwegian manufacturing: As semi-proportional Cox model approach. Small Business Economics, 14(1), 65–82. https://doi.org/10.1023/A:1008189411442.CrossRef

Utterback, J. M., & Abernathy, W. J. (1975). A dynamic model of process and product innovation. Omega, 3(6), 639–656. https://doi.org/10.1016/0305-0483(75)90068-7.CrossRef

Titel: Initial submarket positioning and firm survival: evidence from the British automobile industry, 1895–1970
verfasst von: Zhao Rong
David C. Broadstock
Yuanyuan Peng
Publikationsdatum: 06.01.2018
Verlag: Springer US
Erschienen in: Small Business Economics / Ausgabe 4/2018
Print ISSN: 0921-898X
Elektronische ISSN: 1573-0913
DOI: https://doi.org/10.1007/s11187-017-9970-7

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