The effects of industrial systems on technology adoption
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The Effects of Industrial Systems on Technology Adoption Joung Yeo No Yonsei University Industrial Systems in Technology Adoption The advantages of geographical agglomeration on knowledge spillovers and technology adoption Not only the size of cluster matters

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Industrial systems in technology adoption l.jpg
Industrial Systems in TechnologyAdoption

  • The advantages of geographical agglomeration on knowledge spillovers and technology adoption

  • Not only the size of cluster matters

  • Does the organization of economic activities within a cluster matter as well?


What is industrial systems l.jpg
What is Industrial Systems?

Relationship between the internal organization of firms and their connections to one another and to the social structures and institutions of their particular localities

Industrial system has 3 dimensions:

  • Local institutions and culture

  • Industrial organization

  • Corporate organization


Effect of industrial systems on technology adoption l.jpg
Effect of Industrial Systems on Technology Adoption

  • The innovativeness of a region depends not only on the size and density of cluster, but also on how the economic activities within a cluster are organized.

  • Silicon Valley vs. Boston’s Route 128 (Saxenian, 1994)

→ Silicon Valley - open, flexible and entrepreneurial environment

with many small-, medium-sized plants.

- decentralized regional network-based system

→ Route 128 - Rigid and hierarchical with few dominant players.

- independent firm-based system


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The Objectives

1. How the regional industrial system affects technology adoption by plants

2. How plants respond differently to geographical agglomeration and regional industrial system depending on their internal resources and information networks


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Related Literature

Three relevant strands:

3. Work on the effects of industrial systems (Saxenian 1996) – Descriptive studies on Silicon Valley and Route 128

1. Work on the sources of agglomeration

(Rosenthal and Strange 2001; Dumais, Ellison, and Glaeser 2002; Holmes 2002).

  • Work on other types of knowledge spillovers – Patent citations

  • (Jaffe, Trajtenberg, and Henderson 1993).


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Do industrial systems affect plants’ decisions to adopt technologies?


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Hypotheses

H 1a:

Adoption of advanced manufacturing technologies is more likely with an increase in employment at small plants in the region.

H 1b:

Adoption of advanced manufacturing technologies is more likely with an increase in employment at plants that are single-plant firms in the region.


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Hypotheses

H 2a:

The effect of regional industrial system is greater for small plants than for large plants.

H 2b:

The effects of regional industrial system is greater for single-plant firms than for plants that are part of multi-plant firm.


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Hypotheses

H 3a:

The effect of knowledge spillovers from prior adopters is greater for plants with less internal resources.

H 3b:

The effect of regional agglomeration is greater for plants with less internal resources.

H 3c:

The effect of knowledge spillovers from prior adopters is greater for plants that are single-plant firms.

H 3d:

The effect of regional agglomeration is greater for plants that are single-plant firms.


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Main Finding

I. Technology adoption is facilitated by the industrial system that are characterized as follow:

  • That are agglomerated with small plants

  • That are agglomerated with single-unit plants

  • That are agglomerated with plants that are similar

  • Plants with the following characteristics are more likely to benefit from the regional agglomeration and knowledge

    spillovers:

    • Plants that are small

    • Plants that are single-unit


  • Slide12 l.jpg
    DATA

    1993 Survey of Innovation and Advanced Technology

    • Unique, confidential, proprietary data

    • Adoption of 22 advanced manufacturing technologies at the plant level

    • 1902 plants covering an entire manufacturing sector across Canada

    • Panel nature: years of use for each technology (1984-1993)

      → Panel of 3 intervals: 1984-1986, 1987-1989, and 1990-1992.


    Data cont d l.jpg
    DATA (Cont’d)

    • Annual Survey of Manufactures

      • - Collects information on the universe of manufacturing plants in Canada.

    • National Input-Output Table

      • - Input supply and output demand relationships among industries

    • Census of Population

      • - Demographic information

    → Sample size: 1,902 plants, 22 technologies, 3 time periods

    ⇒ 106,188 obs.


    Estimating equation l.jpg
    Estimating Equation

    Dependent variable:

    The probability of technology adoption is a function of:

    1.  Plant characteristics

    2.  Local amenities, industry, technology and time fixed effects

    3.  Regional agglomeration effects

    4.  Technology spillovers

    5. Industrial Systems


    Estimating equation15 l.jpg
    Estimating Equation

    Pr(Adoptionpτirt)

    =f (IndustrySystemrt, KnoweldgeSpilloverτirt. RegionalAgglomerationrit, PlantCharacteristicsprit, controls)


    Technological dimension l.jpg
    Technological Dimension

    6 technology groups

    22 technologies

    Design

    &

    Engineering

    Fabrication

    &

    Assembly

    Automated

    Material

    Handling

    Manufacturing

    Information

    System

    Inspection

    &

    Communication

    Integration

    &

    Control

    • Flexible manuf.

    • cell or system

    • NC/CNC

    • Materials

    • working laser

    • Pick & place

    • robots

    • Other robots

    • Automated

    • storage and

    • retrieval

    • system

    • Automated

    • guided

    • vehicle

    • system

    • Automated equip. for

    • inspection of in-process

    • Automated equip. for

    • inspection of final

    • LAN for technical data

    • LAN for factory use

    • Intercompany computer

    • networks

    • Programmable controller

    • Computer for factory floor

    • Material

    • requirement

    • planning

    • (MRP)

    • Manufacturing

    • resource

    • planning

    • (MRP II)

    • Computer

    • integrated

    • manufacturing

    • (CIM)

    • Supervisory

    • control & data

    • acquisition

    • Aritifial

    • intelligence &

    • expert systems

    • CAD/CAE

    • CAD/CAM

    • Digital rep. of

    • CAD output

    • used in

    • procurement





    Pick and place robot pharmaceutical l.jpg
    Pick and Place RobotPharmaceutical



    Geographical dimension l.jpg
    Geographical Dimension

    10 provinces

    68 Economic Regions

    290 Census Divisions

    Province

    Economic Region

    Census

    Division

    Rest of Country



    Functional and industrial dimension l.jpg
    Functional and Industrial Dimension

    1. Industrial Dimension

    • based on industry classification

      2-digit (22) and 3-digit (169) SIC

      2. Functional Dimension

    • based on similarities in input purchases


    A measure of related industries l.jpg
    A measure of ‘related’ industries:

    I develop a measure of ‘related’ industries based on the similarity

    of input purchases across industries.

    ρij = correlation between industry i and industry j in terms of

    pattern of input purchases

    For each industry i, all other industries are classified into three groups:

    Similar industries : 0.5 ≤ ρij

    Moderatelysimilar industries: 0.2 ≤ ρij < 0.5

    Different industries: ρij < 0.2



    Slide28 l.jpg

    Industrial Systems

    Knowledge Spillovers

    Technology

    Adoption

    Factor Conditions

    OrganizationalCharacteristics

    Related and Supporting Industries

    Demand Conditions


    Plant characteristics l.jpg
    Plant Characteristics

    is a vector of plant characteristics which includes

    {Size, No. of commodities, Diversity, Foreign ownership,

    Single- or Multi-plant firm status}


    Fixed effects l.jpg
    Fixed Effects

    • Region

    • Industry

    • Technology

    • Time


    Agglomeration effects l.jpg
    Agglomeration Effects

    Employment in region r at time t-1

    Share of scientists & engineers in in the population in region r

    attime t-1

    Value of output of industry i’s input suppliers in region r at

    time t-1.

    Value of output of industry i’s output demanders in region rat

    time t-1.


    Technology spillovers l.jpg
    Technology Spillovers

    # of adopters of tech τ in Similar industries in region r at time t-1.

    # of adopters of tech τ in Moderately similar industries in region r

    at time t-1.

    # of adopters of tech τ in Different industries in regionr at time t-1.


    Empirical results l.jpg
    Empirical Results

    I. Effects of Industrial Systems on Technology Adoption

    1. Based on Plant Size

    2. Based on Plant Status

    II. Effects of Regional Agglomeration Conditional on

    Organizational Capabilities

    1. Plant Size

    2. Plant Status


    1 main results l.jpg
    1. Main Results

    Dependent variable: ADOPTIONpτirt

    Notes: 1) * χ2 statistically significant atp < 0.05

    2) Also included are plant characteristics, agglomeration effects, and fixed effects.


    Plant characteristics35 l.jpg
    Plant Characteristics

    Dependent variable: ADOPTIONpτirt






    Ii effects of regional agglomeration conditional on plant size l.jpg
    II. Effects of Regional Agglomeration Conditional on Plant Size


    Ii effects of regional agglomeration conditional on plant status l.jpg
    II. Effects of Regional Agglomeration Conditional on Plant Status


    Conclusion l.jpg
    Conclusion

    I. Technology adoption is facilitated by the industrial system that are characterized as follow:

    • That are agglomerated with small plants

    • That are agglomerated with single-unit plants

    • That are agglomerated with plants that are similar

  • Plants with the following Characteristics are more likely to benefit from the regional agglomeration and knowledge

    spillovers:

    • Plants that are small

    • Plants that are single-unit


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