A SURVEY ON FIRM INNOVATION

Get Complete Project Material File(s) Now! »

Innovation

Summarizing the survey responses, Table 4 shows that 46% of all respondents in the survey consider their firm to be innovative in some aspect. There are three categories of innovation: product, service and process. 26% of all firms from the survey has product innovation, 30% service innovation and 26% does process innovation. In this analysis, we are interested to see if the innovativeness differs among firms in the groups. From the firms interviewed, 36,25% belongs to group A, 30,05% belongs to group B, and 33,70% belongs to group C. The percentage of firms being innovative is going down in each group with 56% of the interviewed firms in group A is innovative, 41% in group B, and 38% in group C. These results are not surprising looking at previous literature. Cities are more dense and diverse and knowledge moves quickly between people and firms. This means that large, dense locations inspire knowledge flows and knowledge exchange, thus facilitating the spread of new knowledge that brings innovation and the creation of new goods and new ways of producing existing goods (Carlino, 2001). Young people who are eager to learn move to the cities to study and cities attract college-graduates with their amenities. It is a challenge for rural places to attract and to keep highly educated personnel.

ECONOMETRIC METHODS

The purpose of this study is to analyze the impact broadband availability has on the innovative activity among firms in Sweden. The prime interest is whether firms are innovative or not regarding innovation performance. Accordingly, the dependent variable becomes binary: taking the value of one if the firm is innovative and the value of zero otherwise. The most used empirical strategy in this situation is to use a logistic regression model which estimates the logit transformed probability of the relationships through a maximum likelihood method.
This paper explores if the availability of broadband affect firms’ innovativeness. Either, process, service or product innovation. Two types of explanatory variables are used to explain the probability that a firm does innovation: firm characteristics and characteristics of the locality. In this equation, they are expressed as two vectors of predictor groups. Broadband is a local characteristic and is therefore included in that vector. An error term is included. The relationship is specified as:
Logit (Pinnov) = log (??????(1−??????)) =αi + βi(Firm characteristics) + ϒi(Local characteristics) + εi
The availability of broadband is assumed to shift firm i’s probability to innovate.
A firm’s Broadband Internet use is possibly endogenous with respect to firm innovation since it might be a part of the firm’s strategy. Put it like this, highly innovative firms may be more likely to adopt and start using broadband Internet compared to firms who are not innovative. Possibly indicating a reverse causality. Bertschek et al. (2013) tackle this problem by applying an instrumental variable approach. For this study, broadband Internet use is instrumented by the availability of an internet speed with at least 100mbit/s among firms at the municipality level in Sweden. Hence, the availability of broadband is observed at the municipality level instead of the firm level due to endogeneity.
The analysis is based on survey data, the distribution of firms in the survey sample must be considered and compared with the distribution of the whole population. Deviation between the sample and true firm distribution need to be treated by adding sampling weights to reduce biases in the regression estimates. The sample is weighted for firms’ geographical location, firm size and firm industry since agricultural firms are over represented in the sample, so is rural and small firms. The regression is clustered at the municipality level to correct for heteroskedasticity. We know that multicollinearity is not present after performing a variance inflation factor (VIF) test. Please see Appendix Table 17.

1. INTRODUCTION
2. THEORY AND PREVIOUS RESEARCH
2.1 What drives innovation?
2.2 Agglomeration theories
2.3 The importance of cities
2.4 Possibilities at rural places
2.5 The importance of Broadband
3. A SURVEY ON FIRM INNOVATION .
3.1 Data.
3.1.1 Broadband
3.1.2 Innovation
4. ECONOMETRIC METHODS 
5. EMPIRICAL RESULTS
5.1 Firm Characteristics and Urban vs Rural Municipalities
5.2 Local and Regional Characteristics. CONCLUSIONS
7. REFERENCES
8. APPENDIX

GET THE COMPLETE PROJECT
Patterns of Innovation among Urban and Rural Firms