rammer - measuring output of process innovation at the firm level
TRANSCRIPT
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Measuring Output of Process Innovation at the Firm Level:
Results from German Panel Data
Christian RammerCentre for European Economic Research (ZEW)
Mannheim, Germany
OECD Blue Sky Forum III
19-21 September 19-21, 2016, Ghent
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Background(1) Process innovation is a main part of firms’ innovation activities
(204,000 product innovators vs. 187,400 process innovators)
(2) No established measure for measuring the output of process innovation (in contrast to product innovation)
(3) Theoretical models of R&D/innovation often use cost reduction as result variable
(4) Oslo Manual mentions cost reduction and quality improvement as potential output measures
(5) Some national innovation surveys did implement cost reduction and other output measures (BE, CA, CH, DE, NO)
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Objectives- Present empirical evidence on the relevance and reliability of
quantitative measures of process innovation output
- Analyse data on process innovation output collected over the past 20 years as part of the German innovation survey:- share of unit cost reduction owing to process innovation- share of sales growth resulting from quality improvements
- Evaluate the usefulness of these measures for better understanding the innovation process in firms and its impacts
Structure: 1) measurement issues (item non-response, consistency)2) determinants of process innovation output3) performance impacts of process innovation output
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Process Innovation Output:Conceptual Issues
- Process innovation often associated with changing the cost function (but leaving products unchanged)
- But process innovation often targets quality aspects: increasing flexibility, ensuring constant quality
- In services, product and process innovation often go hand in hand, altering both product quality and process efficiency
- Lean management and total quality management have developed a large set of process output indicators (lead time, processing time, on-time delivery, customer satisfaction, defect rate, accuracy rate, reworking rate, scrap rate, number of steps needed)
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Process Innovation Output Measures in the German CIS
- Main challenge: using simple measures that can be applied to all types of firms and sectors
- Cognitive testing resulted in the following design:
annually since 1994
annually since 2002
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Item Non-Response by no. of Responses
0
2
4
6
8
10
12
14
16
1 2 3 4 5 6 7 8 9 10 11 12* 13 14 15 16 17 18+Number of survey responses w ith process innovation "yes"
Shar
e of
item
non
resp
onse
(%)
cost reduction (y/n)
quality improvement (y/n)
Yes/no part
* For quality improvement: 12 or more responses
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Item Non-Response by no. of ResponsesQuantitative part
* For quality improvement: 11 or more responses
0
5
10
15
20
25
30
35
40
1 2 3 4 5 6 7 8 9 10 11* 12 13+Number of survey responses w ith cost reduction / quality improvement "yes"
Shar
e of
item
non
resp
onse
(%)
share of cost reduction (%)
increase in sales due to quality improvement (%)
sales share of product innovations (%)
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Item Non-response by Size/SectorYes/no part Quantitative part
0 2 4 6 8 10 12 14
NACE 5 to 24
NACE 25 to 33
NACE 35 to 53
NACE 55 to 93
5 to 9 employees
10 to 19 employees
20 to 49 employees
50 to 99 employees
100 to 249 employees
250 to 499 employees
500 to 999 employees
1,000+ employees
Share of item non response (%)
cost reduction (y/n) quality improvement (y/n)
0 5 10 15 20 25 30 35 40 45 50 55Share of item non response (%)
cost reduction (%)
quality improvement (%sales increase)
sales share productinnovations (%)
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Variety of Responses by no. of Responses
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
1 2 3 4 5 6 7 8 9 10 11 12 13 14+Number of responses to share of cost reduction/increase in sales due to quality improvement/sales
share of product innovations
Num
ber
of d
iffer
ent v
alue
s pe
r re
spon
ding
firm
share of cost reduction
change in sales due to quality improvement
sales share of product innovations
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Determi-nants 1:yes/no(probit)
1) These models include all variables of part 1.All models include 12 year dummies and 45 sector dummies.* / **: significant at the 0.05 / 0.01 level
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Determi-nants 2:quanti-tativeif yes(OLS)
1) These models include all variables of part 1.All models include 12 year dummies and 45 sector dummies.* / **: significant at the 0.05 / 0.01 level
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Impacts1:ExportShare(OLS)
1) These models include all variables of part 1.All models include 12 year dummies and 45 sector dummies.* / **: significant at the 0.05 / 0.01 level
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Impacts2:ProfitMargin(Int-reg)
1) These models include all variables of part 1.All models include 12 year dummies and 45 sector dummies.* / **: significant at the 0.05 / 0.01 level
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Conclusions(1) Both process innovation output measures work quite well
(2) Share of item non-response for quantitative part high and not falling with response frequency
(3) Responses to the quantitative part are categorical in nature
(4) Weighted data of the two indicators for the German enterprise sector provides meaningful results
(5) Determinants of process innovation output (y/n) largely the same as for product innovation output, but level of output difficult to explain
(6) Process innovation output positively associated with performance
it is possible and useful to collect process innovation output data
Using measures that can be applied across industries limits explanatory power of data, but a differentiated approach would restrict comparability
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Appendix
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0 2 4 6 8 10 12 14 16 18 20 22
0>0, <1
1>1, <2
2>2, <3
3>3, <4
4>4, <5
5>5, <6
6>6, <7
7>7, <8
8>8, <9
9>9, <10
10>10, <15
15>15, <20
20>20, <25
25>25, <30
30>30, <50
40>40, <50
50>50, <60
60>60, <70
70>70, <80
80>80, <90
90>90, <100
100>100
Res
pons
e va
lue
(%)
Share in total responses (%)
cost reduction
change in sales due to quality improvement
sales share of product innovations
Response Values on Quantitative Measures
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ProcessInnovationOutputMeasuresbySector(2014)
Weighted results.
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Process Innovation Output by Size (2014)
0 10 20 30 40 50 60 70
5-9
10-19
20-49
50-99
100-249
250-499
500-999
1,000+
Size
cla
ss (n
o. o
f em
ploy
ees)
Share of f irms (%)
Firms w ith cost reduction
Firms w ith quality improvements
0 1 2 3 4 5 6Share of cost reduction/increase in sales (%)
Share of cost reduction
Increase in sales due toquality improvements
Weighted results.
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Process Innovation Output 1993-2014
0
1
2
3
4
5
6
7
8
'93 '94 '95 '96 '97 '98 '99 '00 '01 '02 '03 '04 '05 '06* '07 '08 '09 '10 '11 '12 '13 '14
Shar
e in
all f
irms
(%)
Share of cost reduction - manufacturing
Share of cost reduction - services
Increase in sales due to quality improvements - manufacturing
Increase in sales due to quality improvements - services
Weighted results. - Manufacturing: divisions 5 to 33 (NACE 2), divisions 10 to 37 (NACE 1); Services: divisions 35-39, 46, 49-53, 58-66, 69-74, 78-82 (NACE 2), divisions 40-41, 51, 60-67, 72-74, 90 and groups 92.1, 92.2 (NACE 1).* Break in series due to change in economic classification systems (from NACE 1 to NACE 2) and change in the statistical source for total firm population figures (introduction of the official business register in 2006).
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Determi-nants 3:quanti-tativemea-sures(tobit)
1) These models include all variables of part 1.All models include 12 year dummies and 45 sector dummies.* / **: significant at the 0.05 / 0.01 level