300071) 13.17% [1] % [2] (Inter- May :A : (2011) (08JC630050) ( ); SCIENCE OF SCIENCE AND MANAGEMENT OF S. & T.

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1 SCIENCE OF SCIENCE AND MANAGEMENT OF S. & T. Vol.32No.5 May ( ) : 150 ; ; ; ; : ; ; ; :F :A : (2011) [3] ( ) [4] 1 8% % [1] 60% % 10 10% [2] [5] (Inter- Processes) personal [6] : : ( ); (08JC630050) : (1983-) :

2 [10] ; [7] ; [10] [7] Blatt ( ) [7] [8] (Self-categorization Theory) ; [8] Thomas Kilmann [9] : [7] [11]

3 : ; [12] : ;? [14] ; [12] Pelled ; [15] Tajfel Turner (Social Identity Theory) [13] : [16] (Intergroup Bias) (Input-Process-Output IPO) ( ) ( ) ( ) [13] 2 H1: 2.1

4 H3: [17] ; [13] ( ) [17] ( ) [20] [16] [21] H2: [12] [18] ; ISO9000 (Legitimacy) ; [19] H4:

5 [22] ; / ; / / H5: [24] 2.2 H6: H6a: 18 H6b: ; H6c: H6d: H6e: 3 Staw 3.1 [23] ; 5

6 ( ) ( ) 15~20 Blau :1- Pi 2 i Blau ; 0 : %3~5 63.3% % % % % % %51 Allison(1978) [25] % % 28.7% 16.0% 12.0% 10.0% 46.4% Teachman(1980) 7 :1- Pi(LnPi)(i=1N) N [3] 5 ;Pi 3.2 Chen (2005) 12 Steensma [10] [26] 4 4 Corley !"#$ %& ( )*+ -. / :;<=> ?@ABCD!EFGH IJ 0.660?@AD!KLMN GH L OPQRSTU VW $XYZ8[\]D^_ EGH ab cdo7efghijkl mnopqr7e8stuv abwx cdqr#yz { }~ Q qr^_k cduv L 0.564!" #$%"& () *+ -./0 1"!23$ :;./0 <=>"3?>@1"12A& !"# $%& ()* $%/ !"#$%& ()* +-./01 2#3"2& :;/01 <=!#23>?2#2<@ ( ) (Dummy variable) (Benchmark Variable) 1 0

7 A3 (Hierarchical Regression Model) (β=0.265p<0.05)h6d ; [3] 4 3 (β=-0.190p<0.05) H2 4 ; H1 A1B1C1 B3 ; A2B2C2 (β=0.218 ; A3B3C3 P<0.05)H6a ; A2 H6b (β=0.234p<0.05) H4 3 H5 H6e B2 C ** 0.38** 0.30** * ** 0.27** * ** ** * * !"# * 0.25** 0.19* ** A1 A2 A3 B1 B2 B3 C1 C2 C !" Á-0.151Á-0.169ÁÂ #$% Á0.160Á & ()& *+()& Á ** ()& /01()& 0.234Á0.243** ()& Â-0.274** 23456& Á-0.239** 0.406Á0.398*** 0.404Â0.442*** 23456& & ()& ** & *+()& ** 23456& -()& &./01()& 0.265** & 01()& R square Adjusted R square F-value Á 2.451Á Á 2.859Á ** 2.142** N df

8 H3 ; (β=-0.204p<0.05); C3 (β= P<0.05); H6c 5 [5] [4] %

9 ; [1]. : [J] : (10):3-14 [2] Song M. Success factors in new ventures: A meta-analysis [J]. Journal of Product Innovation Management200825:7-27 [3]. : [J]. 2010(3): ; [4] Chandler G N Hanks S H. An examination of the substitutability of founders' human and financial capital in emer- ; ging business ventures[j]. Journal of Business Venturing : [5] Watson W Stewart W H BarNir A. The effects of human ; capital organizational demography and interpersonal processes on venture partner perceptions of firm profit and growth [J]. Journal of Business Venturing : [6] Timmons J A. New venture creation: Entrepreneurship in the 1990s[M]. 4th ed. Homewood IL: Irwin 1994: [7] Blatt R. Build relational capital in entrepreneurial teams[j]. Academy of Management Review (3): [8] Chen G Q Liu C H Tjosvold D. Conflict management for effective top management teams and innovation in China[J]. Journal of Management Studies (2): [9] Thomas K W Kilmann R H. The social desirability variable in organizational research: An alternative explanation for reported findings[j]. Academy of Management Journal (4): ; [10] Rahim M A. A measure of styles of handling interpersonal conflict[j]. Academy of Management Journal (2): [11] Pfeffer J. Some consequence of organizational demography: Potential impacts of aging work force on formal organizations[m] / / Kiesler S B. Social change. New York: Acade- mic Press 1981: [12] Chowdhury S. Demographic diversity for building an effective entrepreneurial team: Is it important 芽 [J]. Journal of Business Venturing : [13]. [J]. 2008(11):

10 [14] Foo M D Wong P K. Do others think you have a viable business idea team diversity and judges' evaluation of ideas in a business plan competition[j]. Journal of Business Venturing : [15] Pelled L H Eisenhardt K M Xin K R. Exploring the black box: An analysis of work group diversity conflict and performance[j]. Administrative Science Quarterly (1):1-28 [16] Tajfel H Turner J C. The social identity theory of intergroup behavior[m] / / Worchel W A. Psychology of intergroup relations. Chicago: Nelson-Hall 1986: 7-24 [17] Knight D. Top management team diversity group process and strategic consensus[j]. Strategic Management Journal (5): [18] Tsui A S O'Reilly C A. Beyond simple demographic effects: The importance of relational demography in superiorsubordinate dyads[j]. Academy of Management198932: [19] Wiersema M F Bantel K A. Top management team demography and corporate strategic change[j]. Academy of Management Journal : [20]. (TMT) [J]. 2006(6):39-46 [21] Randel A E Jaussi K S. Functional background identity diversity and individual performance in cross-functional teams [J].Academy of Management Journal (6): [22] Shane S Venkataraman S. The promise of entrepreneurship as a field of research[j]. Academy of Management Review (1): [23] Staw B M Sandelands L Dutton J. Threat rigidity effects in organizational behavior[j]. Administrative Science Quarterly : [24]. : [J]. 2009(3): [25] Allison P D. Measures of inequality[j].american Sociological Review : [26] Steensma H K Corley K G. On the performance of technology-sourcing partnerships: The interaction between partner interdependence and technology attributes[j]. Academy of Management Journal (6): ( ) Demographic Characteristics and Conflict Model of New Technology Enterprise Pioneering Group WANG Rui XUE Hongzhi (Business School Nankai University Tianjin China) Abstract: There are more conflicts in start -up companies as their team members always face greater pressure to survive and develop. Existing researches usually focus on conflicts cause among management in mature companies and seldom pay attention to the formation of conflicts in start-up companies. This paper will investigate the relationship between venture team's demographics and conflict mode based on researches on 150 new technology enterprises. The result shows that existing theories are not available to star-up companies which points out that firstly functional experience heterogeneity matches cooperative conflict a higher technological uncertainty leads to fierce cooperative conflict secondly gender heterogeneity has no significant effect on conflict mode but a higher technological uncertainty leads to closer co relationship between gender heterogeneity and competitive conflict thirdly education background homogeneity rather than heterogeneity causes fierce competitive conflicts but a higher technological uncertainty can cause a transition from competitive conflict to avoiding conflict fourthly age heterogeneity has no significant effect on conflict mode finally industrial experience homogeneity rather than heterogeneity leads to avoiding conflicts. Key words: entrepreneurial team; demographics; conflict model; technological uncertainty