Innovation and Export Activity among

Manufacturing

SMEs– Case Study of Cimahi City, West Java –

Indonesia

By Elivas Simatupang, SE (Unpar), G. Dpl (ISS of Erasmus Uni.), MSc (LSE)

Local Development Planning Board of Cimahi City

Emaill: ivas_id@yahoo.co.uk

Presented in International Seminar on “SME: The Soul of Innovation - The Role of

Innovation in Enhancing SME's Competitive Advantages towards AEC 201” - UNPAR

2015The author thank you to the Local Government of Cimahi City for supporting the data and to Mr. Dr. Bagdja, SE

from Unpad for his valuable comments and support. Errors and opinions expressed here are those of the author

and not those of Local Development Planning Board of Cimahi City.

WORLD AT NIGHT?

Source: http://www.nasa.gov/sites/default/files/images/712130main_8246931247_e60f3c09fb_o.jpg, accessed on 1 August

2014

A

S

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A

A

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Source:http://geology.com/articles/night-satellite/satellite-photo-of-asia-at-night-lg.jpg, accessed on 1 August 2014.

GIS PLOTS OF ISSUED PERMITS OF FIRMS IN 2009 AND 2010

Source: Bappeda Kota Cimahi (2014), pictures were scanned

INTRODUCTION

Sate of the Art

Linking micro economic development to macro economic development by analyzing

innovation activities done by SMEs in Cimahi city

Questions to address?

1. What kind of innovation activity exist in the economy of Cimahi city?

2. What factors influence innovation amid SMEs in Cimahi city?

3. Is there any spatial pattern of innovation of SMEs in the city?

4. What is the effect of innovation to export probability?

Arrangement:

1. Introduction and the Geography of Cimahi city

2. Macro Economy of Cimahi city

3. Geographical Economics of Cimahi City

4. Innovation among SMEs

5. Econometrics LOGIT model of innovation and export activity

6. Conclusions and recomendation

1. GEOGRAPHY

Capital : CimahiArea Size : 4025,73 hectareEast longitude : 107° 31’ 15’’ - 107°34’ 30’’South Latitude : 06 ° 50’ 00’’ - 06°56’ 00’’Height : 690 –1.075 meter

above sea levelDistance from Jakarta : 180 KmRain Fall : 1.500 MM – 3.000 MMTemperature : 18° - 29° C

BoundariesCimahi City shares borders with Bandung Municipality and Bandung Regency:

On the North, the common borders includes Parongpong, Ngamprah and Cisarua Sub Districts ofBandung Regency.

On the South, Cimahi shares borders with Margaasih, Bandung Kulon and Batujajar Sub Districts ofBandung Regency.

On the East, it share borders with Sukasari, Sukajadi, Cicendo and Andir Sub Districts of BandungMunicipality.

On the West, it shares borders with Padalarang, Batujajar and Ngamprah District of Bandung Regency.

1.1. CIMAHI IN REGIONAL

CONTEXT

Estabisished in 2002 andlocated in the BandungBasin/Plateau Area.

The Area consists of 5autonomous regions andCimahi is attached withBandung City, the Capital ofWest Java Province

forming “a compact urbanarea”.

Cimahi City and BandungCity are established as oneof national activity centers.

Cimahi is located in thecreative industry andmanufacturing industrialdistricts/corridors MasterPlan for Accelerating andExpansion of Indonesia’sEconomic Development(MP3EI).

1.2. EXISTING LAND USE •Total coverage area

: 4,061.49 Ha

•Developed Area: 61,54% (2.499, 62 Ha)

•Undeveloped Area : 38,46% (1.561,89 Ha)

•Districts (Kecamatan): 3 (North, Central and South)

•Sub-districts(Kelurahan): 15

•Population: +550.000 inhab

•Pop Desity: 14,085 inhab/km2

•Av. Pop. Growth: 0,97%

Source: Bappeda Kota Cimahi (2014), Spatial Development Planning of Cimahi city

1.3. DEMOGRAPHY

30,000 20,000 10,000 0 10,000 20,000 30,000

0-4

5-9

10-14

15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

55-59

60-64

65-69

70-74

75+

Laki-Laki Perempuan

Source: Bappeda Kota Cimahi (2014), Preliminary Report of Master plan of Ec. Development of Cimahi city

4.45

12.12

7.88

12.38

7.25

4.27

8.982.33

3.24

6.69

4.48

9.14

7.45

5.94

3.41

Cibeber Cibeureum Leuwigajah

Melong Utama Baros

Cigugur Tengah Cimahi Karangmekar

Padasuka Setiamanah Cibabat

Cipageran Citeureup Pasirkaliki

CountyPopulation Growth per Year

2008 2009 2010 2011 2012

South Cimahi 2.51% 2.52% -4.44% 2.67% 1.94%

Central Cimahi 1.95% 1.99% -7.46% 1.58% 0.87%

North Cimahi 3.92% 3.95% -0.79% 2.49% 1.77%

Average Growth 2.70% 2.72% -4.42% 2.29% 1.57%

Number of Labour per Sector

Year

2009 2010 2011 2012

Agricultural 8,550 4,589 2,974 4,318

Manufacturing 84,342 80,540 63,923 65,457

Whose seller, retail, hotel and restaurant 54,999 53,915 65,575 63,438

Private and public services 44,790 41,961 53,102 55,915

Electricity, gas, estate, communication,

transportation, and finance40,574 32,965 40,227 36,635

Total 233,255 213,970 225,801 225,763

Source: Bappeda Kota Cimahi (2014), Preliminary Report of Master Plan of Ec. Development of Cimahi city

2. MACRO ECONOMY AND GEOGRAPHICAL ECONOMIC

2.1. MACRO ECONOMY

2.1.1. HUMAN DEVELOPMENT INDEX

No Indexes

Year

2007 2008 2009 2010 2011 2012

1 Human Development Index 74.42 74.7 75.17 75.51 76.01 76.12

2 Educational Index 89.22 89.22 89.58 89.77 90.07 90.38

3 Health Index 73.28 73.4 73.52 73.63 73.75 99.8

4 Purchasing Power Parity 60.77 61.75 62.41 63.14 63.91 64.24

Source: Statistical Biro of Cimahi city and Bappeda Kota Cimahi (2007 – 2013), Cimah in

Number

2.1.2. GROSS DOMESTIC PRODUCT (GDP)

No SectorYear

2009 2010 2011 2012

1 Agriculture 9.64 10.1 10.07 10.26

2 Mining - - - -

3 Manufacture 3729.34 3832.25 4019.59 4207.72

4 Electricity, Gas and Water 225.42 240.01 251.64 264.88

5 Construction 385.89 406.54 423.94 444.46

6 Trade, Hotel and Restaurant 1243.9 1397.54 1502.1 1587.31

7 Transportation and communication 95.78 107.98 120.54 134.27

8 Finance, estate and corporate services 128.69 141.66 149.97 173.19

9 Services 362.74 373.24 386.55 409.29

Total GDP 6181.4 6509.32 6864.4 7231.38

Source: Bappeda Kota Cimahi (2009 – 2013), Gross Domestic Bruto (GDP) of Cimahi city. Constant price year 2010

2.1.3. ECONOMIC GROWTH

4.63%

5.30%

5.45%5.35%

4.20%

6.69%6.79%

6.53%

3.50%

4.00%

4.50%

5.00%

5.50%

6.00%

6.50%

7.00%

7.50%

2009 2010 2011 2012

Kota Cimahi Jawa Barat Indonesia

Source: Bappeda Kota Cimahi (2014), Preliminary Report of Master Plan of Ec. Development of Cimahi city

2.1.4. ECONOMIC CONTRIBUTION PER SECTOR

0.16%

57.90%

3.20%

6.88%

20.60%

1.97%2.57%

6.72%

Pertanian Pertambangan & Penggalian Industri Pengolahan

Listrik, Gas & Air Bersih Konstruksi Perdagangan, Hotel & Restoran

Pengangkutan & Komunikasi Keuangan, sewa & Jasa Perusahaan Jasa-jasa

Source: Bappeda Kota Cimahi (2014), Preliminary Report of Master Plan of Ec. Development of Cimahi city

2.1.5. LOCATION QUOTIENT

Sector/Sub Sector 2008 2009 2010 2011 2012 Av. Basic/Non-basic

1. PERTANIAN 0.01 0.01 0.01 0.01 0.01 0.01 Non-basic

a. Tanaman Bahan Makanan 0.01 0.01 0.01 0.01 0.01 0.01 Non-basic

b. Tanaman Perkebunan 0.00 0.00 0.00 0.00 0.00 0.00 Non-basic

c. Peternakan dan Hasil-hasilnya 0.03 0.03 0.04 0.04 0.04 0.04 Non-basic

d. Kehutanan

e. Perikanan 0.01 0.01 0.01 0.01 0.01 0.01 Non-basic

2. PERTAMBANGAN & PENGGALIAN

3. INDUSTRI PENGOLAHAN 1.28 1.35 1.36 1.36 1.39 1.35 B a s i c

4. LISTRIK, GAS & AIR BERSIH 1.69 1.52 1.58 1.65 1.63 1.61 B a s i c

a. Listrik 1.98 1.85 1.90 1.97 1.94 1.93 B a s i c

b. Gas

c. Air Bersih 0.60 0.61 0.62 0.62 0.61 0.61 Non-basic

5. BANGUNAN 1.79 1.78 1.66 1.53 1.43 1.64 B a s i c

6. PERDAG., HOTEL & RESTORAN 0.98 0.94 0.96 0.97 0.93 0.95 Non-basic

a. Perdagangan Besar & Eceran 1.01 0.97 0.99 0.99 0.94 0.98 Non-basic

b. Hotel 0.04 0.03 0.03 0.04 4.31 0.89 Non-basic

c. Restoran 0.90 0.94 0.95 0.94 0.93 0.93 Non-basic

7. PENGANGKUTAN & KOMUNIKASI 0.36 0.34 0.34 0.33 0.33 0.34 Non-basic

a. Pengangkutan 0.31 0.30 0.28 0.27 0.25 0.28 Non-basic

1. Angkutan Rel 0.26 0.28 0.28 0.30 0.00 0.22 Non-basic

2. Angkutan Jalan Raya 0.31 0.29 0.28 0.26 0.00 0.23 Non-basic

3. Jasa Penunjang Angkutan 0.77 0.82 0.80 0.74 0.00 0.63 Non-basic

b. Komunikasi 0.43 0.43 0.42 0.42 0.45 0.43 Non-basic

8. KEU. PERSEWAAN, & JASA PERUSAHAAN 0.63 0.64 0.65 0.64 0.65 0.64 Non-basic

a. Bank 0.90 0.82 0.97 0.95 0.96 0.92 Non-basic

b. Lembaga Keuangan tanpa Bank 0.08 0.08 0.09 0.09 0.10 0.09 Non-basic

d. Sewa Bangunan 0.71 0.73 0.68 0.66 0.66 0.69 Non-basic

e. Jasa Perusahaan 0.27 0.25 0.26 0.27 0.27 0.26 Non-basic

9. JASA-JASA 0.87 0.88 0.82 0.80 0.79 0.83 Non-basic

a. Pemerintahan Umum 1.20 1.22 1.23 1.28 1.37 1.26 B a s i c

b. Swasta 0.48 0.48 0.42 0.39 0.37 0.43 Non-basic

1. Sosial Kemasyarakatan 0.37 0.39 0.39 0.39 0.00 0.31 Non-basic

2. Hiburan & Rekreasi 0.15 0.15 0.14 0.13 0.00 0.11 Non-basic

3. Perorangan & Rumahtangga 0.51 0.51 0.44 0.40 0.00 0.37 Non-basic

2. 1.6. SHIFT SHARE

Sector/Sub-sectorNational

ShareIndustry Mix

Regional

ShareClassification

Basic/Non-basic

(LQ)

1. PERTANIAN 2.446,76 -1.228,14 -198,28 Slow and legged Non-basic

a. Tanaman Bahan Makanan 1.360,62 -574,87 -433,07 Slow and legged Non-basic

b. Plantation 27,11 -14,42 -5,04 Slow and legged Non-basic

c. Farming and its products 988,91 -921,29 543,23 Slow and developed Non-basic

d. Forestry

e. Fishery 65,36 4,29 -2,48 Fast and legged Non-basic

2. Mining

a. Oil and gas

b. Mining without gas

c. Extraction

3. Manufacturing 952.450,10 -613.235,93 271.196,84 Slow and developed Basic

a. Gas and oil

b. Non-gas and oil 952.450,10 -604.415,03 262.375,94 Slow and developed Basic

4. LISTRIK, GAS & AIR BERSIH 56.634,62 17.039,19 -22.679,55 fast and legged Basic

a. Electricity 55.332,21 10.001,47 -15518,49 Fast and legged Basic

b. Gas

c. Water 1.302,41 8,06 -131,39 Fast and legged Non-basic

5. BUILDING 96.685,15 137.510,43 -154907,55 fast and legged Basic

6. TRADE AND SERVICES 308.323,11 348.767,57 -234281,24 fast and legged Non-basic

a. Wholesaler and retail 276.765,80 353.267,88 -246101,07 Fast and legged Non-basic

a. Hotel 259,50 -7.631,80 141759,17 Slow and developed Non-basic

a. Restaurant 31.297,81 9.495,83 -2290,37 fast dan legged Non-basic

7. TRANSPORTATION AND

COMMUNICATION24.115,53 47.082,31 -28022,95 fast and legged Non-basic

a. Transportation 13.315,95 12.483,85 -18036,69 fast and legged Non-basic

b. Communication 10.799,58 44.591,86 -19979,65 fast and legged Non-basic

8. FINANCE, RENTAL AND

ENTREPRISES SERVICES31.617,77 33.041,64 -10885,27 fast and legged Non-basic

a. Bank 15.042,96 31.494,35 -10001,19 fast and legged Non-basic

b. Non- bank 507,62 11,26 480,60 fast and developed Non-basic

c. Estate 14.125,83 8.113,46 -9262,39 Fast and legged Non-basic

a. Enterprises Services 1.941,35 2.223,39 -903,12 fast and legged Non-basic

9. SERVICES 91.991,56 30.401,39 -60548,82 fast and legged Non-basic

a. Government 68.864,85 -66.053,46 37278,25 Slow and developed Basic

b. Leasing 23.126,71 46.301,30 -47673,52 fast and legged Non-basic

c. Social 3.126,34 0,00 -14934,22 fast and legged Non-basic

d. Entertainment and Recreation 203,12 0,00 -970,30 fast and legged Non-basic

e. Private and households 19.797,24 0,00 -94569,41 fast and legged Non-basic

Source: Bappeda Kota Cimahi (2014), Preliminary Report of Master Plan of Ec. Development of Cimahi city

2.1.7. INPUT – OUTPUT ANALYSIS

Sector/Sub-sectorOuput

Multiplier

1. Fashion industry 2.32

2. Textile 2.26

3. Building construction 2.21

4. Transportation, carosery, machinery and its equipment 2.16

5. Wooden industry, bamboo, rattan and craft 2.15

6. Publishing industry 2.15

7. Rice mills industry 2.15

8. Other food and beverage industry 2.14

9. Other manufacturing industry 2.11

10. Clay and tile industry 2.07

Source: Bappeda Kota Cimahi (2014), Preliminary Report of Master Plan of Ec. Development of Cimahi city

3. GEOGRAPHICAL ECONOMICS OF CIMAHI CITY

3.1. GIS PLOTS OF GDP OF CIMAHI CITY (2002, 2009 & 2012)

Picture source: Bappeda Kota Cimahi (2014), Preliminary Report of Master Plan of Ec. Development of Cimahi city

=> Indication of localized economies. Seems it is more caused by labourpooling (Paci and Usai, 2000 and Monsey, 2009)

3.2. CONCENTRATION OF POPULATION (2002 & 2009)

=> Overall the city has become more densely but fringe areas grown faster than the Central Business District (CBD).

Picture: Bappeda Kota Cimahi (2014). Picture scanned

3.3. GEOGRAPHICAL ECONOMICS OF INDUSTRIAL SECTOR

=> Manufacture sector has become more concentrated in the

southern part of the city

3.4. GEOGRAPHICAL ECONOMICS OF AGRICULTURAL SECTOR

=> Agricultural sector has become more concentrated in the northern part

of the city

3.5. GEOGRAPHICAL ECONOMICS OF TRADE SECTOR

=> Trade sector has become more concentrated in the middle part of the city

NOTES ON SPATIAL DISTRIBUTION OF ECONOMIC ACTIVITY

A. Low eco. Groth indicating the need for innovation

B. There seem to be a ovious spatial pattern in the distribution of

economic activityies in Cimahi city. This may be caused by two factors:

1. Localized economies. Increasing in economic of scale due to co-

location (collective efficiency) geographical proximity

2. Urbanized economy Different economic activities in different

places still gain benefits through linkages (BL and FL)

Nevertheless, economic growth of the city is tend to be stagnant at

around 4,8 %– 5% per annum therefore knowledge spillover and

innovation diffusion is needed to be enhanced.

C. Spatial economic activities=> clustering policy

D. Which cluster is more inovative or less inovative?

E. Which cluster to be developed is the question than? Knowledge

spillover and Innovation diffusion can be flourish in an industrial cluster

=> Back to part two.

4. Innovation among SMEsDefinitions:

As a driving force which determine economic growth (exogenous and endogenous

growth model)

In defining the true definitions of entrepreneurship, innovation and economic growth

is often idiosyncratic but “Innovation is a necessary condition of

entrepreneurship” Erik Stam (2008: 42).

Entrepreneurs become creative and innovative trough knowledge spillovers. Here

spatial and institutional proximity come into the equation.

Innovation can be differentiated into four forms (Mairesse and Mohnen, 2010 and

Oslo Manual 2005) :

- Product innovations (new goods or services or significant improvements of

existing ones),

- Process innovations (changes in production or delivery methods),

- Organizational innovations (changes in business practices, in workplace

organizations or in the firm’s external relations)

- Marketing innovations (changes in product design, packaging, placement,

promotion or pricing).

Hall et al (2009) divided innovation into 3 (three) types such as:

- Input Innovation : R&D Exp, Patent, and cost for

consultation/design, personnel training, and market analysis

- Process Innovation: new machine or technology or method,

marketing innovations, and organizational changes

- Output Innovation: proportion of sales of new products or new

products

Other research:

a. Adoption behaviour of innovation (Diederen et al, 2003)

b. Innovation influences probability of exporting (case of Vietnam,

Nguyen et al, 2007).

c. Innovation in developing country should be more emphasis on

technological capabilities and technology diffusion (Albu, 1997 ;

Mairesse and Mohnen, 2010; and Sauer and Zilberman, 2009).

4.1. SMES OF CIMAHI CITY

NO URAIAN

TAHUN

2007 2008 2009

1 Number of MSMEs 1.112 1.770 2.625

Micro 778 1.149 1.466

Small 333 566 904

Medium 1 50 256

2 Labour 2.624 7.516 11.561

Micro 1.556 2.297 2.100

Small 998 1.713 2.381

Medium 70 3.506 7.080

3 Sales 174.959.680.000 436.181.100.000 1.202.499.375.000

Micro 38.920.000.000 57.436.500.000 73.276.875.000

Small 133.039.680.000 228.471.600.000 361.410.000.000

Medium 3.000.000.000 150.273.000.000 767.812.500.000

4.1.1. REGISTERED MSMES, ISSUED BY ONES STOP SERVICE OFFICE OF CIMAHI CITY YEAR 2008 -

2013

Scale

Number PERCENTAGE

South

Cimahi

Center

Cimahi

North

CimahiTOTAL

South

Cimahi

Center

Cimahi

North

CimahiTOTAL

Micro 159 165 113 437 8,5 8,8 6,0 23,3

Small 420 380 342 1142 22,4 20,3 18,2 60,9

Medium 47 93 114 254 2,5 5,0 6,1 13,6

Large 26 13 2 41 1,4 0,7 0,1 2,2

TOTAL 652 651 571 1874 34,8 34,7 30,5 100

4.1.2. DATA OF NUMBER OF LABOUR OF MSMEs 2008 – 2013

Scale

NUMBER OF WORKERS PERCENTAGE

South

Cimahi

Center

Cimahi

North

CimahiTOTAL South Cimahi Center Cimahi North Cimahi TOTAL

Micro 4.335 717 565 5.617 7,16 1,18 0,93 9,28

Small 5.802 3.659 2.739 12.200 9,58 6,04 4,52 20,15

Medium 13.497 643 643 14.783 22,29 1,06 1,06 24,41

Large 26.743 1.042 171 27.956 44,16 1,72 0,28 46,17

TOTAL 50.377 6.061 4.118 60.556 83,19 10,01 6,80 100,00

4.1.3. NUMBER OF CAPITAL OWEND BY MSMEs 2008 – 2013 (NOMINAL)

Skala Usaha

CAPITAL PERCENTAGE

South Cimahi Center Cimahi North Cimahi TOTALSouth

Cimahi

Center

Cimahi

North

CimahiTOTAL

Micro 5.532.206.000 5.346.664.670 3.460.400.00014.339.27

0.6700,12 0,12 0,08 0,32

Small 92.418.111.600 78.897.608.900 75.475.102.500246.790.8

23.0002,05 1,75 1,67 5,47

Medium 303.122.498.100 214.166.634.700 64.160.462.800581.449.5

95.6006,72 4,75 1,42 12,89

Large 2.042.591.510.000 1.594.677.210.000 32.513.000.0003.669.781.

720.00045,27 35,34 0,72 81,33

TOTAL 2.443.664.325.700 1.893.088.118.270 175.608.965.3004.512.361.

409.27054,15 41,95 3,89 100,00

1. SMEs encountered for 97.8% of all business units in Cimahi

2. Composition of SMEs in Cimahi is predominately by small enterprises (61%).

3. Most enterprises in the south are more labour intensive significantly. Despite its bigger proportion of capital accumulated in the centre areas, proportion of enterprises are capital intensive as well.

4. Overall, SMEs are labour intensive (53.8%) while large companies are more capital intensive. (81%).

5. Number of SMEs has augmented significantly (±52%) and unemployment has descended (±9,4 %) but have not been followed by a significant (local) Ec. Growth. This may show a “shopkeepers” or “refugee” effect and or low innovation level among the SMEs.

NOTES ON SMES OF CIMAHI CITY

5. Small enterprises mostly located in the middle of the city

and capital and labour is concentrated more in the south.

6. Northern area are most legged in ec. production factor

utilization. Developing agriculture sector is imperative.

7. There has been a consistency between data of number of

business enterprises with the IO Tabel and SAM Tabel

and also consistent with the GIS plots of Economic

growth.

8. Because of its big proportion and role in absorbing labour

force therefore encouraging innovation is important to

boost the economy growth.

4.2. INDUSTRIAL CLUSTERS OF SMES

D E F I N I T I O N S :

" C L U S T E R S A R E G R O U P S O F I N D U S T R I E S R E L A T E D B Y

K N O W L E D G E , S K I L L S , I N P U T S , D E M A N D A N D O T H E R

L I N K A G E S I N A R E G I O N ( P O R T E R , 2 0 0 3 A N D D E L G A L D O E T

A L , 2 0 1 3 )

C O N C E N T R A T I O N S O F F I R M S T H A T O P E R A T E I N T H E S A M E

S U B S E C T O R ( S A N D E E A T A L L : 2 0 0 2 ) .

B E N E F I T S :

- K N O W L E D G E S P I L L O V E R

- I N N O V A T I O N D I F F U S I O N

- I N T E G R A T E D V A L U E C H A I N

- E A S Y N E S S I N M A N A G I N G S M E S A C T I V I T I E S

4.3. STAGES OF DEVELOPING A CLUSTER

Slide BI

4.4. Manufacturing Industrial clusters of SMEs

1.Textile and fashion industrial clusters

2.Culinary clusters

3.Craft clusters

4.Printing cluster

(source: business directory of Cimahi City 2014)

4.5. SUB-SECTOR CLUSTERS OF SMES OF CIMAHI CITY

1.Hot Cassava chips cluster (Keripik Setan)

Setiamanah District

2.Milk Cow cluster in Cipageran District

3.Puppets Dolls Cluster in Melong District

4.Muslim Fashion Cluster in Cibeureum and

Cigugur Tengah Districs

5.Concrete Tile (Batako) Cluster in Cibeber

District

6.Jeans and T-shirt Cluster in Melong DistrictThese are 6 out of 21 potential traditional (product-based) clusters in Cimahi city

5. ECONOMETRICS MODEL OF INNOVATION AND EXPORT ACTIVITIES

a. Data taken form In-depth Business Directory of Cimahi city (2014)

b. Sample number = 504 (α = 4%) and analyzed using SPSS v.22

c. Limited dependent variable model (Binary Logit model):

d. Dependent variables:

- Output innovation: if producing new product in the last three years

- Process innovation: if changing management in the last three years or

Improving in quality in the last three years or

Using new machine in the last three years or

Changing supplier in the last three years or

Conducting pricing method (promotion, placement and

product pricing).

- Dummy variable of exporting abroad

1

u

i u

eY

e

0 1 1

ˆ( 1| )ln ln

ˆ(1 ( 1| )) (1 )

P Y Xb b X

P Y X

0 1 1 2 2

ˆln

ˆ(1 )k kb b X b X b X

f. Independent variablesFor Innovation

- Education level of the owner

- Main sales

- Frequency of innovation

- Respond towards source of knowledge or information internally (worker

or member of the family).

- Social capital using a proxy for blood donor.

- Dummy variable for cooperation or training form a university

- Dummy variable for cooperation or training form local government of

Cimahi city

- Logarithm of total asset (excluding land and house)

- 3 dummy variables of regions (south, middle and north)

- 4 dummy variables of clusters

For export

- Expected value of process and output innovation

5.1. Innovation and export regression results

5.1.1. Output innovation

Variables in the EquationEquation1 Equation2

B Sig. Exp(B) B Sig. Exp(B)

Constant -9,088 0 0 -8,255 0 0

EDUCATIONOFOWNER 0,208 0,017 1,231 0,183 0,039 1,201

OMZEMAIN 0 0,024 1 0 0,042 1

FREQINNOVATION 0,48 0 1,615 0,467 0 1,595

DGOV 0,554 0,063 1,741 0,591 0,053 1,806

DUNIV 0,943 0,041 2,569 0,956 0,039 2,601

LASSET 0,624 0,002 1,866 0,641 0,002 1,899

INTERNALINFO 0,368 0,007 1,444 0,394 0,005 1,483

BLOODDONOR -0,217 0,075 0,805 -0,217 0,082 0,805

DSOUTH -0,582 0,036 0,559

DNORTH -0,613 0,075 0,541

DTEXTILE -1,683 0,034 0,186

DCULINARY -1,128 0,148 0,324

DCRAFT -1,586 0,049 0,205

in eq. 1 base group is DMIDDLE and in eq.2 base group is DPRINTING

Output Innovation = producing new product in the last three years

5.1.2. Process innovation

Variables in the EquationEquation3 Equation4

B Sig. Exp(B) B Sig. Exp(B)

Constant-0,104 0,881 0,901 -1,412 0,09 0,244

EDUCATIONOFOWNER0,189 0,013 1,208 0,164 0,035 1,178

OMZEMAIN0 0,032 1 0 0,074 1

FREQINNOVATION0,221 0,001 1,248 0,219 0,001 1,245

INTERNALINFO0,057 0,598 1,058 0,039 0,714 1,04

BOODDONOR-0,288 0,004 0,75 -0,277 0,005 0,758

DUNIV0,815 0,232 2,259 0,487 0,108 1,627

DGOV0,404 0,175 1,498 0,838 0,212 2,312

LASSET0,177 0,013 1,193

DSOUTH-0,795 0,001 0,452

DNORTH-0,171 0,601 0,843

DTEXTILE0,027 0,921 1,027

DCRAFT-0,375 0,149 0,687

DPRINTING-0,417 0,586 0,659

in eq. 3 base group is DMIDDLE and in eq. 4 base group is DCULINARY

5.3. Export Probability

Dependent variables are estimated probability of product innovation in eq. 1 and estimated probability of process innovation in eq. 2

Variables in the Equation

B S.E. Wald Df Sig. Exp(B)

Step 1a PRE_42,260 ,703 10,323 1 ,001 9,584

Constant-3,690 ,368 100,631 1 ,000 ,025

a. Variable(s) entered on step 1: PRE_4.

b. Independent variable is estimated probability of product innovation

Variables in the Equation

B S.E. Wald Df Sig. Exp(B)

Step 1a PRE_75,442 1,571 12,003 1 ,001 230,811

Constant-7,067 1,291 29,982 1 ,000 ,001

a. Variable(s) entered on step 1: PRE_7.

b. Independent variable is estimated probability of process innovation

Variables in the Equation

Items B S.E. Wald df Sig. Exp(B)

Step 1a

PREDICTEDOUTPUTINNOV 0,337 1,168 0,083 1 0,773 1,4

PREDICTEDPROCESSINNOV 4,777 2,453 3,791 1 0,052 118,732

Constant -6,654 1,643 16,406 1 0 0,001

**** = insignificant

*** = significant at α = 10%

6. CONCLUSION

a. Informal institution (i.e social capital) does significantly

influence innovation among manufacturing SMEs

b. Human recourses is important in enhancing innovation

c. Higher frequency of conducting innovation leads to

higher probability to be innovative. This means

continuity is important.

d. The role of government (local) and universities is

prominent in pushing product innovation diffusion

among SMEs in Cimahi city but not process innovation.

e. The middle part of the city is the most innovative and the

southern part of the city is the least innovative.

f. Textile cluster produce less new products (less out put

innovative) but together with printing cluster are more

process innovative than the other two counterparts.

h. Financial aspects influence innovation significantly.

i. There seem to be a sequence process of innovation in Cimahi. A firm can produce a new product and can export when are some improvements in the process. Most new product can not be exported directly.

j. Only process innovation will increase the probability of SMEs in the city to involve in international trade. Hence, to be able to compete in ASEAN free trade era, improving process innovation is imperative.

k. Tacit knowledge significantly influence innovation. This is proved by the significant influence of internal source of information and knowledge.

l. Region defines more innovation especially in output process. This proves that in the case of Cimahi city localised economies is more dominant than urbanasied economies.

m. There is autocorrelation between regions and clusters. This depicts the persistence of innovation spatially.

n. Simulation, moving from region to clusters gives a hint that geography does matter

o. Overall, micro ec. anlayisis is consistent with the macro ec. analysis of the city.

9. RECOMMENDATION

a. Local government and university can improve innovation through providing training, therefore leveraging technical skill. University can become the source of information and knowledge. Unfortunately, their influences are limited in the process because cooperation may tend to be ‘project oriented’ or limited in duration. Cooperation should be designed for longer time.

b. Exploiting social capital through community development

c. The smaller of the regions propose an idea to simulate the influence of sub-sector clusters in relation to innovation level among SMEs. This also support policy to develop sub-sector or product based clusters i.e. ‘sentra’.

d. This research may indicate that urbanized economy is still weak therefore developing value chain between clusters is urgent.

e. Policy to push (process) innovation is imperative so to be able to compete in the globalised competition era.

f. As labour variable does not influence innovation, call for a need to use an aggregate variable like number of labour force or concentration of population in the regions to indicate pooling of labour.

g. Different results given by the region and cluster variables may indicate that a smaller scope area variable like product based cluster dummies veriables give more significant improvements in the model. If so, this depicts the significant role of product based cluster to competitiveness of the city. The analysis will move from sector-cluster to region then to product based cluster (sentra).

h. A call for developing a panel data analysis or spatial econometrics model of innovation among SMEs in Cimahi city.

Think globally and act locally, think locally

and act globally