dissertation in pdf-format - Aalto-yliopisto

More documents

Recommendations

Info

3 Research methodology The data used in Article IV included the original data set for 567 growing businesses from which 466 firms in urban and 101 in rural areas were identified. The data were used to identify the most rapidly growing industry sector and distinguishing characteristics of that sector relative to other sectors during the examination period of 2002-2005. High-growth and high success variables were used as dichotomous variables in order to find out distinguishing characteristics of diverse branches of growing firms. Firms were classified as high-growth and highly successful if their turnover grew by more than 30% in consecutive years in 2002-2005 and their Success Index was at least 80 points, respectively. In Articles I and II the lower value of the success index was used to meet the need for sufficient observations in different branches of industry and the group of HGS firms. It was discovered that the most rapidly growing industry branch was services, including the KIBS-sector, hence survey data for KIBS firms were included in the analysis. These data were obtained from a questionnaire delivered to all of the 1,143 small KIBS firms located in Northern Savo (Eastern Finland) at the time. 213 firms returned questionnaires that could be used for identifying the kinds of innovations that have affected growth of the firms. Moreover, in order to identify the small KIBS firms’ requirements for regional innovation support services data were collected from 12 small T-KIBS firms located in Eastern Finland. The key informants approach was used to collect data from case firms that used at least three different kinds of innovation support services during the preceding two years. 3.3.2 Analytical methods In Article I the objective was to identify the factors that differentiate innovative growing SMEs from other firms. Five hypotheses, derived from previous theory and empirical studies, were constructed to test if location, age, size, success and public R&D funding differentiate innovative from non-innovative growth firms. Logistic regression analysis (LRA) was used to analyse the data because the dependent variable was dichotomic and in maximum likelihood modelling it is recommended to use LRA when the explanatory independent variables are not only nominal or ordinal but also scale variables. Moreover, results obtained through basic regression analysis (RA) can be misleading when dealing with data relating to growth and patent registrations (Coad and Rao, 2008). The preliminary purpose of Article II was to analyse simultaneous growth and success characteristics of the firms. However, this inquiry also led to consideration of the methodological problems of the analysis. Thus, Article II focused on the characteristics of HGS SMEs and possible problems of different approaches and methods. Regression (RA), discriminant (DA) and 40
41 3 Research methodology logistic regression analyses (LRA) were used to examine the data. The growth and success of the firms were used as dependent variables in the RA models. In the DA- and LRA-analyses the classification of simultaneous growth and success of firms was used as a dependent variable. First, both DA- and LRA-models were estimated, ignoring the a priori probabilities of the firms’ growth and success (Model 1), then matched pair comparisons (cross-validation) were applied (Model 2). Explanatory variables included branch of industry, age and size of the firm, innovativeness (measured by IPRs), public R&D funding and region, as a dichotomous variable (urban vs. rural). In Article III the purpose was to identify and understand potential prerequisites for, and consequences of, the HGS stage of SMEs. The empirical paths of the firms were followed, based on the entrepreneurs’ judgement and perceptions of the processes. Thus, the unit of analysis was the owner/manager/entrepreneur rather than the firm, although financial development and job creation were analysed as firm level phenomena. Since the frequencies of HGS SMEs proved to be very small and no robust statistical analysis could have been performed, a multiple case approach was selected as the method of analysis. The primary data for the study was collected through thematic interviews. The themes (derived from prior research and theory) included the attitudes and behaviour of the entrepreneur, management, ownership, finance, markets and customers, strategic choices and growth strategies, success and future challenges. Content analysis was the primary method of analysing the acquired interview data. Combined quantitative and qualitative analyses (mixed methods) were used in Article IV to examine the innovation support requirements of small, technology and knowledge-intensive, high-growth firms in Eastern Finland. LRA-analysis was used when studying the distinguishing factors of the service sector with other branches of industry. Moreover, the study identified innovation-related activities of one high-growth service sector (KIBS firms). Content analysis with categorization was the main method used when analysing the small T-KIBS case firms’ requirements for regional innovation support services.
Page 3 and 4: Aalto University publication series
Page 5: Author Tomi Heimonen Name of the do
Page 9 and 10: Acknowledgements This dissertation
Page 11 and 12: CONTENTS PART 1: Overview of the di
Page 13: List of Articles This thesis is bas
Page 16 and 17: 1 Introduction Some scholars claim
Page 18 and 19: 1 Introduction In addition, the dur
Page 20 and 21: 1 Introduction Figure 1: Framework
Page 22 and 23: 1 Introduction factors that affect
Page 24 and 25: 1 Introduction 1.4 Key concepts and
Page 26 and 27: 2 Literature review and conceptual
Page 46 and 47: 3 Research methodology Constructivi
Page 48 and 49: 3 Research methodology and the meth
Page 52 and 53: 3 Research methodology 3.4 Models a
Page 54 and 55: 3 Research methodology reliable. Se
Page 56 and 57: 3 Research methodology concluded th
Page 58 and 59: 4 Results, evaluation of the studie
Page 70 and 71: References Abetti, P. A. (2001). Ac
Page 72 and 73: References Bhide, A. (2000). The or
Page 74 and 75: References Creswell, J. W. (2003).
Page 76 and 77: References Golafshani, N. (2003). U
Page 78 and 79: References Leitch, C., Hill, F., an
Page 80 and 81: References Pellikka, J. and Laurone
Page 82 and 83: References Storper, M. (1992). The
Page 84 and 85: Appendixes Overview: Appendix 1: Ke
Page 86 and 87: Appendixes High growth When examini
Page 88 and 89: Appendixes profitability, liquidity
Page 90 and 91: Appendixes Appendix 1 Continued (Ke
Page 92 and 93: Appendixes Appendix 2 Construction
Page 94 and 95: Appendixes Appendix 2 Continued (Co
Page 96 and 97: not increased compared to Eastern F
Page 98 and 99: ___________________________________
Page 100 and 101:
propensity for risk taking (Covin a
Page 102 and 103:
2. Former studies and derivation of
Page 104 and 105:
firm’s annual sales growth (Arund
Page 106 and 107:
H4. Firm success has an impact on t
Page 108 and 109:
other branches in which employment
Page 110 and 111:
and Rao, 2008). Because of the unev
Page 112 and 113:
Table 1. Characteristics of the dat
Page 114 and 115:
firms from other firms. The data in
Page 116 and 117:
Table 2. Logistic Regression analys
Page 118 and 119:
Public R&D funding was shown to inc
Page 120 and 121:
References Achtenhagen, L., Naldi,
Page 122 and 123:
Kanter, R. (1985), “Supporting in
Page 124 and 125:
Appendix 1. Corporate population ch
Page 126 and 127:
Appendix 3. Distribution of personn
Page 128 and 129:
12 Int. J. Business and Globalisati
Page 130 and 131:
14 T. Heimonen and M. Virtanen we u
Page 132 and 133:
16 T. Heimonen and M. Virtanen suff
Page 134 and 135:
18 T. Heimonen and M. Virtanen Glan
Page 136 and 137:
20 T. Heimonen and M. Virtanen 3.2.
Page 138 and 139:
22 T. Heimonen and M. Virtanen diff
Page 140 and 141:
24 T. Heimonen and M. Virtanen sepa
Page 142 and 143:
26 T. Heimonen and M. Virtanen Tabl
Page 144 and 145:
28 T. Heimonen and M. Virtanen All
Page 146 and 147:
30 T. Heimonen and M. Virtanen 5.2
Page 148 and 149:
32 T. Heimonen and M. Virtanen Tabl
Page 150 and 151:
34 T. Heimonen and M. Virtanen The
Page 152 and 153:
36 T. Heimonen and M. Virtanen Davi
Page 154 and 155:
38 T. Heimonen and M. Virtanen Appe
Page 156 and 157:
40 T. Heimonen and M. Virtanen 100
Page 158 and 159:
___________________________________
Page 160 and 161:
412 M. Virtanen and T. Heimonen “
Page 162 and 163:
414 M. Virtanen and T. Heimonen gro
Page 164 and 165:
416 M. Virtanen and T. Heimonen 6 f
Page 166 and 167:
418 M. Virtanen and T. Heimonen Fig
Page 168 and 169:
420 M. Virtanen and T. Heimonen The
Page 170 and 171:
422 M. Virtanen and T. Heimonen the
Page 172 and 173:
424 M. Virtanen and T. Heimonen 4.6
Page 174 and 175:
426 M. Virtanen and T. Heimonen exc
Page 176 and 177:
428 M. Virtanen and T. Heimonen Dav
Page 178 and 179:
430 M. Virtanen and T. Heimonen The
Page 180 and 181:
432 M. Virtanen and T. Heimonen Cha
Page 182 and 183:
392 Int. J. Entrepreneurial Venturi
Page 184 and 185:
394 J. Siikonen et al. firms’ gro
Page 186 and 187:
396 J. Siikonen et al. generally re
Page 188 and 189:
398 J. Siikonen et al. determinants
Page 190 and 191:
400 J. Siikonen et al. 3.1 National
Page 192 and 193:
402 J. Siikonen et al. 2 the firm
Page 194 and 195:
404 J. Siikonen et al. 4 Results 4.
Page 196 and 197:
406 J. Siikonen et al. innovation a
Page 198 and 199:
408 J. Siikonen et al. the responde
Page 200 and 201:
410 J. Siikonen et al. activities i
Page 202 and 203:
412 J. Siikonen et al. Eastern Finl
Page 204 and 205:
414 J. Siikonen et al. Delmar, F.,
Page 206 and 207:
416 J. Siikonen et al. Oerlemans, L
Page 208 and 209:
418 J. Siikonen et al. Appendix 1 V
Page 211:
9HSTFMG*afacab+
show all

dissertation in pdf-format - Aalto-yliopisto

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?