20091031 Mgmt205 Presentation Final

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Research project at Singapore Management University during the exchange programm.

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20091031 Mgmt205 Presentation Final

  1. 1. 20-Nov-09 The impact of size on internationalization success Romain • Benedict • Alvin • Melvin • Kendrick Background Hypothesis Model Results 1Objective & Relevance Objective 1 Evaluating the significance of firm size in successful internationalization of Singaporean firms. 2 Identifying the determinants for internationalization success Relevance 1 Challenging a common wisdom: size matters in internationalization 2 New Context: Advancing the debate on determinants of internationalization success with an Asian-based study 3 Dominance of Business Groups in Asia: Most companies with international operations tend to belong to larger business group Background Background Hypothesis Model Results 2 1
  2. 2. 20-Nov-09Firm Size & Internationalization « One of the most widely analyzed relationship » (Bonaccorsi 1992) Little consensus 1 Difference in study methodology 2 Difference in the way of measure Cavusgil 1984: 1 Number of employee : no relationship 2 Sales : strong relationship Background Background Hypothesis Model Results 3Firm Size & Internationalization Size-Related IB Theoretical Success Factors Framework Organizational Resources RBV (quality, scale and scope) Access to Supporting Resources Firm Size Risk appetite and Entry Mode Commitment Capacity to Multi-nationality manage and Performance complexity Background Background Hypothesis Model Results 4 2
  3. 3. 20-Nov-09Firm Size & Internationalization • « the larger the business the more likely it is to export » Gertner, 1987 • « Size does not affect the • Porter 1986: « big firms • Focus only on export firm’s interest in exporting have a competitive (Gertner 1987) » Swiercz 1991 advantage in the internationalization • « Size is an important process » factor when the firm is very • Focus on one kind of firm small » Cavusgil 1976 • A positive correlation is (Holzmuller and Kasper often taken as granted. 1991) • « Size has an indirect effect on the firm propensity to export in the case of the medium and large companies » Casper 1991 False past Missing Different assumption research results Background Background Hypothesis Model Results 5Data: Asian Sample Sample Europe (1) Europe (1) Region Sweden and Italy (4) Denmark (1) Austria (1) Italy UK(2) Europe (2) USA (6) North America Canada (1) Canada (1) India(1) Asia Japan (1) Time 1975 2009 Background Background Hypothesis Model Results 6 3
  4. 4. 20-Nov-09Data: Asian Sample End two decades of inconsistency 1 Using both kind of measures for the size of the firm (sales and number of employees) 2 « internationalization success » with FSTS method (Click and Harison, 2000) 3 Analysing all kind of firms: small and big in a sample from Singapore Background Background Hypothesis Model Results 7FrameworkSolving the puzzle Method Hypotheses 1 The bigger the firm, the Full Sample Regression higher is its probabiliy toDoes firm size matter succeed internationally to 2 Comparative Analysis internationalization Firm size matters up to a success? certain point but not for 3 Subsample Regression others Background Hypothesis Model Results Results 8 4
  5. 5. 20-Nov-09Hypotheses Type of Relationship Expected Outcome Results Continuous The bigger the firm, the higher is its ? Positive Linear probabiliy to succeed internationally Discontinuous Firm size matters up to a certain point ? Curvilinear but not for others Background Hypothesis Hypothesis Model ResultsThe Model Dependent Variable Independent Variable Control Variables Alternative Internationalization success = Size + Explanatory Variables International Sales Total Sales Total Sales Total Employees Background Hypothesis Model Model Results 5
  6. 6. 20-Nov-09Control Variables Numerical Variables Measure References Business Experience Age of the firm Majocchi (2005) International Experience Number of international Ekeledo & Sivakumar (2003) markets Performance Return on Assets (ROA) Gomes & Ramaswamy (1999) Physical Proximity Straight line distance Gertner (2006) Cultural Distance Hofstede’s CDI Thirkell & Dau (1998) Dummy Variable Measure References Industry Sector Binomial Categorization Grøgaard (2005) Background Hypothesis Model Model ResultsFrameworkSolving the puzzle 1 Full Sample Regression • Two measures of firm size are used: Total Sales and Total number of Employees • All data points are included in the regression Does firm size matter 2 Comparative Analysis to • Reviewing internationalization success in internationalization each sample group – by size success? • Both definitions of firm size were reviewed 3 Subsample Regression • Sample is divided by groups depending on size (<10mil, 10-100 mil, >100mil) • Both definitions of firm size are reviewed, Background Hypothesis Model Results Results 12 6
  7. 7. 20-Nov-09The Model – Total SalesIndependent Variables Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Total Sales Age of Firm Number of Markets Return on Assets Cultural Distance Physical Distance Industry Type Background Hypothesis Model Model ResultsThe Model – Total EmployeesIndependent Variables Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Total Employees Age of Firm Number of Markets Return on Assets Cultural Distance Physical Distance Industry Type Background Hypothesis Model Model Results 7
  8. 8. 20-Nov-09Data OneSource Database Over 600,000 companies globally Source Company Websites Sampling The sample size of 272 companies was randomly selected from a population of Technique Singapore incorporated companies. Initial Total Number of Companies 272 Incomplete Data 39 Sample Outliers (across various fields) 27 Final Complete data points 206 Sample Background Hypothesis Model Model Results 15Data Intl Firms CEOs # of Cultural Physical # of Sales/Total ROA Total Sales Age Age Markets Distance Proximity Employees SalesMean 54% 31.54 51.49 5.08 $0.00 $849,150 1.12 2,954.09 2,734.87Min 0% 4.00 39.00 1.00 -$0.91 $347 - - - 188.0Max 100% 0 68.00 51.00 $0.41 $29,145,190 19.49 14,767.24 45,000.00 Background Hypothesis Model Model Results 16 8
  9. 9. 20-Nov-09Summary of Results Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 ControlTotalSales -0.004 0.001 0.073 0.076 0.064 0.058 0.055 -0.070 0.012 1.065 1.123 0.942 0.827 0.786FirmAge 0.006 0.004 -0.042 -0.044 -0.056 -0.049 0.05 0.095 0.066 -0.614 -0.654 -0.818 -0.700 0.90Markets 0.135** 0.128** 0.215** 0.212** 0.228** 0.133** 2.268 2.161 3.153 3.113 3.348 2.258RoA -0.065 -0.072 -0.141** -0.139** -0.55 -1.097 -1.208 -2.055 -2.028 -0.944CulturalDistance -0.024 -0.034 0.078 -0.27 -0.393 -0.569 1.144 -0.446PhysicalDistance 0.513** 0.524** 0.517** 8.256 8.472 8.462Industry 0.083 0.087 1.404 1.482Adjusted R-Square 0.308 0.304 0.059 0.058 0.044 0.04 0.02 0.313 Firm Size is not a • Number of markets is a consistently significant variable significant variable • RoA and Physical Distance are also statistically significant Background Hypothesis Model Results Results 17Summary of Results Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8Employees 0.048 0.054 0.147** 2.136 0.131* 0.121* 0.117* 0.803 0.907 2.173 0.034 1.925 1.733 1.691FirmAge 0.008 0.006 -0.042 -0.662 -0.058 -0.051 0.05 0.130 0.110 -0.623 0.509 -0.847 -0.726 0.90Markets 0.135** 0.129** 0.217** 3.158 0.230** 0.133** 2.273 2.178 3.205 0.002 3.393 2.258RoA -0.074 -0.081 -0.144** -2.067 -0.55 -1.251 -1.369 -2.106 0.040 -0.944CulturalDistance -0.024 -0.033 0.083 -0.27 -0.398 -0.552 1.235 -0.446PhysicalDistance 0.513** 0.523** 0.517** 8.265 8.479 8.462Industry 0.075 0.087 1.274 1.482Adjusted R-Square 0.317 0.315 0.073 0.070 0.055 0.07 0.09 0.313 Firm Size is not a Number of Markets, RoA and Physical Distance are significant variable significant variable Background Hypothesis Model Results Results 18 9
  10. 10. 20-Nov-09FrameworkSolving the puzzle 1 Full Sample Regression • Two measures of firm size are used: Total Sales and Total number of Employees • All data points are included in the regression Does firm size matter 2 Comparative Analysis to • Reviewing internationalization success in internationalization each sample group – by size success? • Both definitions of firm size were reviewed 3 Subsample Regression • Sample is divided by groups depending on size (<10mil, 10-100 mil, >100mil) • Both definitions of firm size are reviewed, Background Hypothesis Model Results Results 19Further AnalysisNumber of international markets - secondary measure of internationalization success Sample Breakdown by Total Sales and International Markets No. of Firms Mean International Markets 80 7.00 6.10 70 4.20 6.00 4.84 60 5.00 3.78 50 No. of Firms 4.00 40 International Markets 3.00 30 2.00 20 10 1.00 0 0.00 < $30,000 $30,000 - $89,999 $90,000 - $349,999 > $350,000 Total Sales (000) Background Hypothesis Model Results 10
  11. 11. 20-Nov-09Why size is not significant?Possible Explanations Dynamism is more important in Asia Lower speed to market Large Firms Low flexibility ASIAN MARKET Higher speed to market SMEs High flexibility The Singapore Case Strong government support for local firms to internationalize: • International Enterprise Singapore • Government Subsidy Schemes • Trade Networking Groups Background Hypothesis Model Results ResultsHypotheses Type of Relationship Expected Outcome Results Continuous The bigger the firm, the higher is its FALSE Positive Linear probabiliy to succeed internationally Discontinuous Firm size matters up to a certain point ? Curvilinear but not for others Background Hypothesis Hypothesis Model Results 11
  12. 12. 20-Nov-09FrameworkSolving the puzzle 1 Full Sample Regression • Two measures of firm size are used: Total Sales and Total number of Employees • All data points are included in the regression Does firm size matter 2 Comparative Analysis to • Reviewing internationalization success in internationalization each sample group – by size success? • Both definitions of firm size were reviewed 3 Subsample Regression • Sample is divided by groups depending on size (<10mil, 10-100 mil, >100mil) • Both definitions of firm size are reviewed, Background Hypothesis Model Results Results 23Alternative Model 1 Sales Square Background Hypothesis Model Results 24 12
  13. 13. 20-Nov-09Alternative Model 1 Sales Square Background Hypothesis Model Results 25Alternative Model 1 Sales Square Scatter plot ALL Scatter plot ex >$1billion Background Hypothesis Model Results 26 13
  14. 14. 20-Nov-09Further AnalysisRegression by sub-samples Firm Size Total Sales Total Employees Total < 10 mil ** - Firm Size Total Sales Employees 10 - 25 mil - ** < 10 mil ** - 25 - 50 mil - - 10 - 100 mil - - >100 mil - ** 50 - 75 mil - - 75 - 100 mil - - >100 mil - ** Background Hypothesis Model Results Results 27Further AnalysisSubsample < $10 million Total Sales is a statistically significant variable • Amongst firms with Total Sales < $10 million, Total Sales is positively correlated with Internationalization Success • RoA (+), Physical Distance (+) and Industry (-) are statistically significant as well Background Hypothesis Model Results 28 14
  15. 15. 20-Nov-09Further AnalysisSubsample > $100 million Total Employees is a statistically significant variable • Amongst firms with Total Sales > $100 million, Total Employees is positively correlated with Internationalization Success • RoA (-) and Physical Distance (+) are statistically significant as well • The negative value of RoA coefficient is unexpected Background Hypothesis Model Results 29Further AnalysisRegression by sub-samples Firm Size Variable** Explanation Very Small Total Sales • Costly external financing • Reliant on internal sources • Insufficient scale of sales Middle None • Highly contingent conditions for middle-sized firms Very Large Total Employees • Both internal and external financing are possible • Constraint for internationalization would be managerial resources total number of employees Background Hypothesis Model Results Results 30 15
  16. 16. 20-Nov-09Further AnalysisRegression by sub-samples Internal Retained earnings Internationalization Financing Success sources External Loans, bonds & investments • Unequal access to financial resources • Differentiated outcome Background Hypothesis Model Results Results 31Limitations 1. Singapore-only dataset – not representative of the region 2. Missing fields – led to datapoints being dropped 3. Generalizations: • Markets are defined as regions • Physical distance are taken as euclidian distance 4. Internationalization success need not be measurable by export intensity Background Hypothesis Model Results Results 32 16
  17. 17. 20-Nov-09Conclusions 1 Firm size as measured by Total Sales or Total Employees are not statistically significant factors in influencing internationalization success • No clear positive linear relationship was observed • Thus, size should not be a barrier to internationalization (Calof 1994) 2 Firm size, however, seems to have an impact when the firm either too small or very large, but the significant independent variable differ in the two cases • Total Sales matters for very small firms • Total Employees matter for very large firms Background Hypothesis Model Results Results 33 The impact of size on internationalization Q&A Background Hypothesis Model Results 34 17
  18. 18. 20-Nov-09Variable Map Management Experience Market Resource Experience advantage Resource Advantage Internationalization Success Physical Distance Information Cultural Distance Advantage Domestic Knowledge Base Background Hypothesis Model Model ResultsCorrelation Matrix CulturalD PhysicalD Success TotalSales Employees FirmAge Markets RoA istance istance Industry ** ** **Success Pearson Correlation 1 .050 .114 -.038 .234 -.182 .083 .557 .127 Sig. (2-tailed) .451 .083 .586 .000 .005 .207 .000 .052 N 235 234 234 212 235 233 232 235 235 ** *TotalSales Pearson Correlation .050 1 .776 .066 -.019 .084 .053 .126 .052 Sig. (2-tailed) .451 .000 .328 .766 .195 .410 .050 .417 N 234 243 242 220 241 241 240 243 243 ** *Employees Pearson Correlation .114 .776 1 .074 -.026 .095 -.017 .152 .082 Sig. (2-tailed) .083 .000 .276 .683 .140 .787 .018 .204 N 234 242 244 221 241 242 241 244 244FirmAge Pearson Correlation -.038 .066 .074 1 .038 .094 -.025 -.077 -.048 Sig. (2-tailed) .586 .328 .276 .579 .166 .716 .253 .479 N 212 220 221 222 219 221 219 222 222 ** **Markets Pearson Correlation .234 -.019 -.026 .038 1 -.059 -.015 .204 -.051 Sig. (2-tailed) .000 .766 .683 .579 .366 .819 .001 .429 N 235 241 241 219 242 240 239 242 242 ** *RoA Pearson Correlation -.182 .084 .095 .094 -.059 1 -.004 -.130 -.123 Sig. (2-tailed) .005 .195 .140 .166 .366 .948 .043 .055 N 233 241 242 221 240 243 240 243 243 **CulturalDistance Pearson Correlation .083 .053 -.017 -.025 -.015 -.004 1 .230 -.100 Sig. (2-tailed) .207 .410 .787 .716 .819 .948 .000 .120 N 232 240 241 219 239 240 242 242 242 ** * * ** * **PhysicalDistancePearson Correlation .557 .126 .152 -.077 .204 -.130 .230 1 .088 Sig. (2-tailed) .000 .050 .018 .253 .001 .043 .000 .169 N 235 243 244 222 242 243 242 245 245Industry Pearson Correlation .127 .052 .082 -.048 -.051 -.123 -.100 .088 1 Sig. (2-tailed) .052 .417 .204 .479 .429 .055 .120 .169 N 235 243 244 222 242 243 242 245 245 Background Hypothesis Model Results 36 18

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