A Study on Chinese Firms in Hamburg by Oliver Lieber Introduction Why Hamburg? Agenda Location Factors and Regression Model Cluster Analysis SWOT Analysis 2007 11 21 2
Why did I choose this topic? Many Chinese Companies go abroad Few studies look at Chinese firms outside of China Hamburg is the largest cluster of Chinese firms in Europe The development of the cluster in Hamburg is very dynamic 2007 11 21 3 Questions that shall be answered: What are the characteristics of the China cluster in Hamburg? Which factors are important for Chinese firms in Hamburg and is it possible to rank them according to their magnitude? 2007 11 21 4
The Location of Hamburg in Europe 2007 11 21 5 2007 11 21 6
Which Location Factors are important for Chinese Firms in Hamburg? 16 Location Factors were identified after a literature review With these factors a survey has been conducted More than 150 Chinese companies in Hamburg were contacted by email, phone or fax They were asked to state their satisfaction with the 16 location factors In addition to that the firms were asked to state their overall satisfaction with Hamburg as a business location 50 (fully answered) questionnaires have been returned 2007 11 21 7 2007 11 21 8
Image Living quality Functioning of HWF and COC Port of Hamburg Proximity to markets Availability of services Tax level Functioning of public authorities Overall Satisfaction in Hamburg Flight connections Chinese institutions Subsidies Chinese network Availability of local employees Availability of Chinese employees Rental prices Wage level 2007 11 21 9 Creating the Regression Model Problems occur: Not enough observations (only 50) Multicollinearity Some variables are not significant Some variables have to dropped The resulting regression equation therefore is: 2007 11 21 10
Image Living quality Functioning of HWF and COC Port of Hamburg Proximity to markets Availability of services Tax level Functioning of public authorities Overall Satisfaction in Hamburg Flight connections Chinese institutions Subsidies Chinese network Availability of local employees Availability of Chinese employees Rental prices Wage level 2007 11 21 11 Regression Outcome: Ranking: 1.Port of Hamburg 2.Chinese network in Hamburg 3.Rent level 4.Access to markets 2007 11 21 12
A Study on Chinese Firms in Hamburg Distribution of Chinese Firms in Hamburg in 2007 327 Chinese companies are included Red dots show companies that were already there before 2002 The blue dots show newly arrived firms The firms are not weighted The dots are anonymous 2007 11 21 13 A Study on Chinese Firms in Hamburg The Density of Chinese Firms in Hamburg in 2007 The firms are not weighted in any way Three clusters are visible Cluster Mundsburg Alster Lake Elbe River Cluster Hamm Cluster City Center 2007 11 21 More Firms in the eastern part of Hamburg Distribution is relatively disperse 14
The China Cluster in Hamburg Training Workshops by HWF Legal Advice Trade Fairs Hamburg Messe Conferences China Summit Specialized Press Hamburg China News Consulting Services Imports Logistics Companies Other Import / Export Companies Warehouses Chinese Import / Export Companies Distributors Public Administration Direct Sales Manufacturers Independent Retailers Customers Other Services Marketing Institiutions HWF Chamber of Commerce Supporting Associations Asien Institut Ostasiatischer Verein e.v. Wholesalers 2007 11 21 15 SWOT Analysis 2007 11 21 16
The idea of a China Town in Hamburg 2007 11 21 17 Thank You! 2007 11 21 18
Regression Outcome: Regression statistic R squared 0,540261668 Adj. R squared 0,499396038 Standard deviation 0,60713094 Observations 50 Correlation coefficients RENT CONN NETW PORT RENT 1 CONN 0,11925965 1 NETW 0,01678167 0,4465231 1 PORT 0,08212991 0,39527333 0,16843525 1 ANOVA Dergrees of freedom (df) Sum of squares (SS) Regression 4 19,49264097 Residue 45 16,58735903 Total 49 36,08 Coefficients Standard deviation t statistic P value Lower 95% Upper 95% Intercept 0,211453019 0,735636697 0,287442183 0,77509335 1,27019532 1,69310136 RENT 0,206984267 0,112978953 1,832060405 0,07356557 0,02056702 0,43453556 CONN 0,190427591 0,097377033 1,955569856 0,05674221 0,00569982 0,386555 NETW 0,211843269 0,091267931 2,321113959 0,02486878 0,02802022 0,39566632 PORT 0,391983298 0,101083382 3,877821368 0,00034039 0,18839092 0,59557568 2007 11 21 19 Multicollinearity Multicollinearity can be defined as a linear functional relationship between two or more independent variables that is so strong that it can significantly affect the estimation of the coefficients of the variables. (Studenmund, 2001, pg. 247) The consequences of multicollinearity (Studenmund, 2001) are: Estimates will remain unbiased The variances and standard errors of the estimate will increase The computed t scores will fall Estimates will become very sensitive to changes in specifications The overall fit of the equation and the estimation of nonmulticollinear variables will be largely unaffected 2007 11 21 20
Where Chinese live 2007 11 21 21 2007 11 21 22
Further Characteristics of Chinese Firms in Hamburg 2007 11 21 23 Tourism 2007 11 21 24
A Study on Chinese Firms in Hamburg 2007 11 21 25 A Study on Chinese Firms in Hamburg 2007 11 21 26
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2007 11 21 29 Different Strategies Strengths Weaknesses Opportunities S O Strategy W O Strategy Threats S T Strategy W T Strategy 2007 11 21 30