Manja Jonas

1
Direct investments as an engine of technological
change in Malaysia The role of networked policy

• Globelics Academy
• in Lisbon, 02-11 May 2007

2
A. Motivation

• FDI-based development strategy Aim leveraging
  foreign technology for local development
• But Mixed results.
• Study question How can developing countries
  facilitate effective technology diffusion from
  FDI to local industry?
• ? Innovation Systems (IS) as key facilitators of
  technology diffusion (Freeman 1987 Freeman,
  Nelson et al. 1988 Lundvall 1992 Nelson 1993)
• ? Midwifery role of economic policy (Evans 1995)
• ? Greater social interaction leads to higher
  levels of cooperation for the provision of local
  public goods (White and Runge 1995 Molinas 1998)

3
B. Policy learning as network embedded
collective action

• - Policy learning as the process by which
  consensual knowledge is used to specify causal
  relationships in new ways so that the result
  affects the content of public policy (Haas 1990
  23)
• - Respecification effort as a communicative
  process of sense-making (Nedergaard 2006)
• frequent communication leads to a certain
  convergence of beliefs
• Public good character of individual investments
  in interaction and IS development (assuming a
  certain commonality in the preferences and causal
  relationship models of MNEs in the same industry)
• ? collective action problems
• socially constructed trust and reputation may
  facilitate collective action to build economic
  institutions (Ostrom 2000, Tang 1994)
• network management activities to facilitate
  interaction activation, framing, mobilizing,
  synthesizing (Carlsson 2000 Keast, Mandell et
  al. 2005 Meier and O'Toole 2001 Klijn 1996
  Klijn and Koppenjan 2000)
• ? public network management may overcome
  collective action problems

4
C. A unified framework of FDI embeddedness in
policy learning networks
5
D. Theoretical propositions

• Proposition 1 If collective action problems are
  solved, MNEs integrate themselves into the local
  policy network.
• Proposition 2 If the state actively manages the
  policy network, interactive policy learning is
  facilitated.
• Proposition 3 Technology policy is more
  effective, if it builds on interactive policy
  learning.

6
F. Data collection methodology

• Industry survey among 400 foreign-owned
  enterprises from the US, Japan and Germany in the
  electronic industry (response rate so far 10),
  questionnaire administered over the phone or in
  person by a professional survey company, whenever
  possible use of tested survey instruments on
  their technology-related networking
• 22 personal semi-structured interviews with
  representatives of Business associations,
  training institutes in public-private
  partnership, and public agencies on their
  networking patterns with foreign-owned
  enterprises in Malaysia

7
F. Innovation system issues
Business services Supplier base Infrastru
cture HR Regulation
Notes n27 values normalized from 5-point
Likert scale
8
G. Commitment and activism of FDI
Notes n28 A minimum value of zero denotes that
responses were on average not above the lowest
value, i.e. no special agreement on the matter.
The maximum is 4.0. Acquiescence bias was
eliminated by including two positively and two
negatively formulated items in each category, and
subsequently adjusting to the mean. Since the
items are heavily loaded with value judgements,
social desirability bias had to be controlled,
too. This was achieved by discounting the minimum
adjusted value for each respondent.
9
Proposition 1 If collective action problems are
being solved, MNEs integrate themselves into the
local policy network.

• Network Management by BAs
• Activation ?, private benefits
• Framing ?, unilateral or collectively
• Motivation ?, reputation mechanisms
• Synthesizing ?, interaction platforms,
  equal contribution schemes
• Examples of embeddedness council participation
  ASIALICS PSDC

10
Proposition 2 If the state actively manages the
policy network, interactive policy learning is
facilitated. (the national level)

• Network management by national level public
  agencies
• Activation - ?, phone calls based on databases
• Framing -?, participatory (general
  government- business meetings) or
  top-down (dedicated councils)
• Motivation ?, some use reputation
  mechanisms, others remuneration
• Synthesizing -?, equal contribution schemes
• Examples of interactive policy learning NPC

11
Proposition 2 If the state actively manages the
policy network, interactive policy learning is
facilitated. (the state level)

• Network management by (successful) local level
  public agencies
• Activation ?, private benefits
• Framing ?, participatory
• Motivation ?, reputation mechanisms, private
  benefits
• Synthesizing ?, equal contribution schemes,
  networking platforms
• Examples of interactive policy learning PSDC,
  InvestPenang

12
Proposition 3 Technology policy is more
effective, if it builds on interactive policy
learning.

• Comparison between the evolution of industrial
  training in PSDC (co-operative approach) and
  SHRDC/KISMEC (top-down approach)
• Comparison between supplier development
  activities of InvestPenang (co-operative
  approach) and SMIDEC (top-down approach initially
  )

13

• Thank you very much!