Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Small Business Economics
Erschienen in: Small Business Economics 4/2015

01.04.2015

Supply chains and the internationalization of small firms

verfasst von: Giorgia Giovannetti, Enrico Marvasi, Marco Sanfilippo

Erschienen in: Small Business Economics | Ausgabe 4/2015

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This paper explores the relation between supply-chain participation and the internationalization of firms. We show that even small and less productive firms, if involved in production chains, can take advantage of reduced costs of entry and economies of scale that enhance their probability of exporting. The empirical analysis is carried out on an original database, obtained by merging and matching balance-sheet data with data from a survey on over 25,000 Italian firms, which include direct information on the involvement in supply chains. We find a positive and significant relation between being part of a supply chain and the probability of exporting, as well as the intensive margin of trade. The number of foreign markets served (the extensive margin), on the other hand, does not seem to be affected. We also investigate whether being in different positions along the chain, i.e., upstream or downstream, matters, and we find that downstream producers tend to benefit more. Our results are robust to different specifications, estimation methods, and the inclusion of the control variables typically used in heterogeneous firms models.
Vorheriger Artikel An international cohort comparison of size effects on job growth
Nächster Artikel Trust, transaction costs and contractual incompleteness in franchising

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Anhänge
Nur mit Berechtigung zugänglich
Fußnoten
1
In accordance with the official EU definition, in the rest of the paper, small enterprises are denoted as those with less than 50 employees.
 
2
By “relationship specific,” we mean that the value of the assets or investments is higher inside a particular relationship than outside of it.
 
3
An interesting example can be found in the value chain certification of the famous Italian brand “Gucci,” which has certified its suppliers and subcontractors. The certification involves over 600 firms from Tuscany. As a consequence, these firms, improving their reputation, have also increased their access to credit (Il Sole 24 ore online, “Intesa San Paolo e Gucci alleate per favorire l'accesso al credito delle PMI,” January 17, 2013).
 
4
The sample reduction is mainly due to microfirms and small firms for which balance-sheet data are unavailable or inconsistent across the two data sources (2-digit sector and/or region do not match). After the merge, the share of firms below 50 employee decreases to 75.3 from 86.2 %. Moreover, we lose a large number of firms in services: The share of manufacturing increases to almost two-thirds after the merge from about one-half before the merge.
 
5
The involvement in a specific production process is identified in the survey with a firm’s identification with a specific supply chain, which is different from the sector they belong to.
 
6
The aspect of participation in the final product has been added for consistency with our definition, given that it is likely to signal the “contribution of the firm to specific forms of production.”
 
7
The use of the alternative proxy for supply chain participation is also discussed when we introduce the robustness checks in Sect. 3.4, and detailed results are provided in Appendix B (Electronic Supplementary Material), and Tables B3 and B4.
 
8
The TFP estimation is based upon the Solow residuals from an econometric specification derived from a Cobb–Douglas production function. We estimated the TFP at the sectoral level, using the Levinshon and Petrin (2003) methodology, with intermediate inputs as proxies for unobservable productivity shocks. Further details on the estimation methods are provided in the “Appendix”.
 
9
Pieri and Zaninotto (2013), in a study on the Italian machinery tool industry, find that: “the most efficient builders of MTs choose integrated structures, while less efficient firms choose to outsource part of their production process by buying intermediate inputs from other firms.” (p. 413).
 
10
The construction of this variable is based upon the answer to a specific question of the survey, in which a firm is asked whether it has been involved in international activities over the past 3 years. Direct and indirect exports have been considered for the purpose of this analysis. This choice is consistent with the consideration that firms along the supply chain, upstream or downstream, have different degrees of proximity to the final market.
 
11
For consistency, the network variables that we include in the regressions are mutually exclusive. Hence, while some firms are involved in different types of networks simultaneously (e.g., local and domestic, domestic and global, or local and global), our definitions are such that each firm is univocally attributed to the wider type of network.
 
12
The matrix of correlations is available in Appendix B, Table B1, showing no concerns of collinearity between our variables.
 
13
Results are robust to the inclusion of each regressor separately and consistent also/even when the model is estimated on the whole sample of 25,090 firms (i.e., not merged with balance-sheet data). As a robustness check, all the estimations presented in the paper have been performed also on the whole sample of 25,090 firms (without checking for the TFP and FDIs). For space reasons, results are available in Appendix B, Tables B6–B8.
 
14
Replacing the SEs dummy with the logarithm of the number of employees produces similar results, with the coefficient of the latter being positive. Regressions with the SEs dummy, however, are more consistent with the following analysis, in which we split the sample between SEs and MLEs.
 
15
Note that using the initial productivity level and the change in productivity helps also to avoid concerns over a possible simultaneity bias with the dependent variables. Moreover, there is general consensus among trade economists that the direction of causality mainly goes from productivity to export, via self-selection effects à la Melitz (2003).
 
16
Average marginal effect and marginal effect at the mean, respectively.
 
17
The prediction is considered to be correct if the predicted probability is >50 % and the firm is indeed exporting or if the predicted probability is below 50 % and the firm is not exporting (Hosmer and Lemeshow 2000).
 
18
The full set of results for six different regressions for small firms (up to 50 employees) and six for larger firms (from 50 employees) are reported in Tables 10 and 11 in the Appendix. For simplicity, we report regressions up to 50 employees for SEs and over 50 employees for large firms. Above 50 employees, the two sets of regressions produce very similar results. Regressions for all the different thresholds are available from the authors.
 
19
The negative and significant effect found for firms with at least 300 employees (Column 6, Table 11) should be taken with caution, since in this subgroup most firms are already exporting (62 %), the number of observations is rather small, and the confidence interval is quite large.
 
20
Detailed results from the regressions with the interaction term, not reported here for reasons of space, are available in Appendix B, Table B2. In addition, we also run separate regressions for firms in a supply chain. For this subsample, the initial level of TFP is expected to show a lower correlation with the probability of exporting, and, indeed, the coefficients from the regressions are found to be lower and non-significant. However, the number of observations is rather small, making the introduction of an interaction term more appropriate.
 
21
The extensive margin index goes from 0 (non-exporters) to 8. The different destinations for which we have data are as follows: EU, EXTRA-EU, North America, China, India, rest of Asia, South America, other.
 
22
In our case, the definition of binary variables is preferable to the use of the actual shares of total sales. In fact, the latter is likely to contain measurement errors, i.e., the observed shares are only indicative and extreme values are indeed prevalent in the sample.
 
23
The results of these robustness checks, not included here for reasons of space, are available in Appendix B, Tables B3–B8.
 
24
To run regressions on the whole sample, however, we cannot control for TFP.
 
25
Though service firms are likely to take advantage from supply chain participation, in our sample, they are less represented both in absolute terms (they are one third of the merged sample) and especially as far as supply chain involvement is concerned (only <17.7 % of firms in a supply chain operate in services, and <7.3 % of firms in services report to be part of a supply chain). Finally, most of the services firms in our sample are localized (i.e., not easily exportable) services, including business services and transportation.
 
26
For a detailed discussion of the methodology, see Caliendo and Kopeinig (2008), Becker and Ichino (2002), Dehejia and Wahba (1999), Heckman et al. (1998), Rosenbaum and Rubin (1983).
 
27
The propensity score matching models and the ATTs estimations have been performed also on the whole survey as a robustness check. Estimated ATTs are similar (slightly higher) to those reported in the paper, but the matching procedure was more problematic. Details are available in Appendix B, Tables B9, and B10.
 
Literatur
Accetturo A., Giunta A., & Rossi S. (2011). The Italian firms between crisis and the new globalization. Questioni di Economia e Finanza (Occasional Papers) 86, Bank of Italy, Economic Research and International Relations Area. doi:10.​2139/​ssrn.​1849865.
Agostino, M., Nugent, J. B., Scalera, D., Trivieri, F., & Giunta, A. (2014). The importance of being a capable supplier: Italian industrial firms in global value chains. International Small Business Journal,. doi:10.​1177/​0266242613518358​.CrossRef
Becattini G. (1990). The Marshallian industrial district as a socio-economic notion. In F. Pyke, G. Becattini, & W. Sengenberger (Eds.), Industrial district and inter-firm cooperation in Italy (pp. 37–51). International Institute for Labour Studies, Geneva. ISBN:929014467X, 9789290144670.
Becker, S. O., & Caliendo, M. (2007). Sensitivity analysis for average treatment effects. Stata Journal, 7(1), 71–83.CrossRef
Becker, S. O., & Ichino, A. (2002). Estimation of average treatment effects based on propensity scores. Stata Journal, 2(4), 358–377.CrossRef
Brusco S., & Paba S. (1997). Per una storia dei distretti industriali italiani dal secondo dopoguerra agli anni novanta. In F. Barca (Ed.), Storia del capitalismo italiano dal dopoguerra ad oggi (pp. 265–333). Donzelli Editore Roma. ISBN:9788860364616.
Cerrato, D., & Piva, M. (2012). The internationalization of small and medium-sized enterprises: The effect of family management, human capital and foreign ownership. Journal of Management and Governance, 16(4), 617–644. doi:10.​1007/​s10997-010-9166-x.CrossRef
Di Giacinto, V., Gomellini, M., Micucci, G., & Pagnini, M. (2014). Mapping local productivity advantages in Italy: industrial districts, cities or both? Journal of Economic Geography, 14, 365–394. doi:10.​1093/​jeg/​lbt021.CrossRef
Federico, S. (2012). Headquarter intensity and the choice between outsourcing versus integration at home or abroad. Industrial and Corporate Change, 21(6), 1337–1358. doi:10.​1093/​icc/​dts006.CrossRef
Grossman, S. J., & Hart, O. D. (1986). The costs and benefits of ownership: A theory of vertical and lateral integration. Journal of Political Economy, 94, 691–719. doi:10.​1086/​261404.CrossRef
Grossman, G. M., & Helpman, E. (1991). Innovation and growth in the global economy. Cambridge, MA: MIT Press. ISBN 0-262-57097-1.
Leuven E., & Sianesi B. (2003). PSMATCH2: Stata module to perform full mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Statistical Software Components S432001, Boston College Department of Economics, revised February 12, 2014.
Navaretti G. B., Bugamelli G., Schivardi F., Altomonte C., Horgos, D., & Maggioni D. (2011). The global operations of European firms: The second EFIGE policy report. Bruegel Bluepring Series. ISBN:978-9-078910-20-6.
Norton, E. C., Wang, H., & Ai, C. R. (2004). Computing interaction effects and standard errors in logit and probit models. Stata Journal, 4(2), 154–167.CrossRef
OECD. (2012). Fostering SMEs’ participation in global markets: Final report. OECD Centre for SMEs, Entrepreneurship and Local Development, Paris.
Park, A., Nayyar, G., & Low, P. (Eds.). (2013). Supply chain perspectives and issues: A literature review. World Trade Organization and Fung Global Institute. ISBN:978-92-870-3893-7.
Metadaten
Titel
Supply chains and the internationalization of small firms
verfasst von
Giorgia Giovannetti
Enrico Marvasi
Marco Sanfilippo
Publikationsdatum
01.04.2015
Verlag
Springer US
Erschienen in
Small Business Economics / Ausgabe 4/2015
Print ISSN: 0921-898X
Elektronische ISSN: 1573-0913
DOI
https://doi.org/10.1007/s11187-014-9625-x

Weitere Artikel der Ausgabe 4/2015

Small Business Economics 4/2015 Zur Ausgabe

OriginalPaper

Causal ascriptions and perceived learning from entrepreneurial failure

OriginalPaper

Firm growth in the course of mergers and acquisitions

OriginalPaper

Shaker A. Zahra: pioneering entrepreneurship scholar

OriginalPaper

Cluster development policy, SME’s performance, and spillovers: evidence from Brazil

OriginalPaper

Local financial development and the trade credit policy of Italian SMEs

OriginalPaper

What drives environmental practices of SMEs?

Premium Partner

    Bildnachweise