Innovation, open labour markets and brokerage opportunities for knowledge workers in China

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Innovation, open labour markets and brokerage
opportunities for knowledge workers in Chinas
ICT sector

• Matias Ramirez
• matias.ramirez_at_brunel.ac.uk
• Peter Dickenson
• DIME workshop Distributed networks and the
  knowledge-based economy, Juan-le Pins, 10th-11th
  May 2007

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Conceptualising firm level competence building
through knowledge worker networks in Chinese RD
labour markets

• 1. Intra-firm knowledge transfer strategic
  resource-based view
• Building unique intangible resource and
  employment practices to promote
  intra-organisational knowledge sharing,
  complementarity of HR practices.
• (Ichniowski et al 1997, Osterman 1994,
  Huselid 1995, Becker and Gerhart 1996 Kleinknecht
  et at 1997, Michie and Sheehan 2000, Michie and
  Sheenhan 2003)

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• 2. Inter-firm knowledge transfer in the
  knowledge (networked) economy
• A. Inter-firm knowledge transfer and
  collaboration through firm level networks
  (Marshall etc) and/or networks of knowledge
  workers.
• Development of a division of labour
  associated with working on the boundary of the
  firm Gatekeeping, boundary spanning, specialised
  services (Coleman 1988, Lesser 2000, Grabher
  2004, Casper 2005).
• Networks of knowledge workers can be closely
  linked to concepts of social capital and
  particularly socio-centric networks linked to
  knowledge brokers activities (Burt 2005).

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• Dense ties run the risk of redundancy, increases
  coordination costs for little benefit.
• Socio-centric emphasizes, not the network, but
  the position of the individual in the network to
  fill structural holes.
• Brokering essential to create variation
• How to operationalise? By intertwining brokering
  activities of knowledge workers with labour
  market features associated with career and
  rewards.

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• B. Emphasis on inter-firm mobility (in
  Anglo-Saxon clusters at least) and flexible
  careers. Intermediary institutions at cluster
  level facilitate flexible contracts, matching
  skills and entrepreneurial opportunities. (OECD
  2001, Saxenian 1994, 1996, Arthur and Rousseau
  1996).

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3.Epistemic communities (swift innovation?
exploitation? scanning?)

• Entrepreneurial star scientists (Zucker and
  Darby 1995) emphasises start-ups and epistemic
  communities (Hakanson 2005) rather than
  collaboration on specific projects.
• Presence of high skilled labour within a
  geographical area, a milieu where knowledge
  workers and firms are able to scan on
  managerial and technological developments.
• In conclusion
• New efficiencies, a feature of network
  activity, associated with open labour markets

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Features of the Chinese Innovation system

• Size and history of the Chinese science and
  technology infrastructure, especially the
  universities and C.A.S.
• Regional technology parks in chinas innovation
  system (employ 4 million knowledge workers and
  account for three-quarters of all exports of high
  tech products).
• Labour markets of knowledge workers. 1 million
  employed in RD, 20m engineering graduates by
  2015.

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Beijings Zhongguancun Park

• 1988 Beijing experimental zone became Chinas
  first high technology development zone. Included
  Founder (Beijing University), Tongfang
  (Tsinghua), Lenovo (C.A.S).
• 14,000 high tech companies, 500,000 employees
• Prime catalysts are NTEs (spin-offs from CAS and
  others).
• Financial incentives Taxes waived first 3 years,
  15 thereafter (but only 50 paid for next 3
  years).
• In all science parks, 15 of firms are foreign
  owned, but make up 42 of valued added.
• Surge of economic growth in 1990s appears to have
  by-passed Beijing, focussing mainly in Guandong,
  Jiangsu and Tianjin.

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Beijing Zhongguancun Science Park
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(No Transcript)
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Hypotheses

• Knowledge workers will derive a wage premium for
  their tenure with high technology companies.
• ZGC Park has a highly fluid labour market, that
  rewards knowledge workers for mobility and
  experience in the labour market
• Firms in the ZGN will pay wage premiums for
  employees to collaborate and network (broker)
  outside of the firm in innovation projects?
• Networking activities of knowledge workers will
  have a positive impact on innovation performance

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Data analysis

• Survey 1 Senior RD managers in 71 Chinese ICT
  firms undertaking innovation.
• Survey 2 381 knowledge workers (RD employees)
  from these 71 firms working on specific projects.
• Sample Indigenous Chinese, ICT, located in ZGC
  park, presence of RD activity, must have
  introduced a new product in past 3 years.

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Network constructs
 
   
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• Inter-organisational problem solving
• Benefits from collaboration with suppliers,
  customers, research institutes, academic
  institutes and joint ventures. Division of labour
  includes boundary spanners bridging cognitive
  gaps (Leonard Barton 1995).

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• Relational networks
• Networking that relies on personal relations
  of knowledge workers and ties of individuals
  knowledge workers. Also lowers cost of mobility.
  Embeddedness of labour markets (Macdonald and
  Piekkari, 2005, Casper 2005, Granovetter (1988,
  1995). Lowers the cost of labour mobility and may
  help innovation, but knowledge belongs to
  employee.

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• Scanning Activity
• Search and scan activity (Allen 1979,
  Leonard-Barton 1995, Macdonald 1994, Bucher 2003)
  associated with learning and understanding latest
  technologies, managerial techniques, potential
  for alliances and benchmarking and gate keeping
  activity.

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Do knowledge workers network?
IOPS and REL Some/very influential in innovation
project SCAN Moderately/very important source
of learning
Source RD employees
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Regression 1 Are knowledge workers paid a
premium for their networking activities?

• Earnings FunctionW constanta1EXPi a2
  EXP2ib1TENUREi b2TENURE2i c1Number of
  PREVIOUS JOBS d1 SEN d2 IOPS d3 REL d4
  SCAN f1 IOPSSEN f2RELSEN f3SCANSEN
  where
• W gross monthly wage including bonuses.
  EXP years prior experience to joining present
  firm,
• TENURE years in current firm,
• SEN level of seniority (we distinguish
  between manager/senior engineer and
  non-management technical/commercial).
• IOPS inter-organisational networking,
• REL relational networking,
• SCAN general networking.
• IOPSEN,
• RELSEN
• SCANSEN

interactive terms between seniority and different
types of networking
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Regression results for entire sample of knowledge
workers

• Explanatory Variable Standardised Beta
  t Sig
• Constant 7.692 .000
• EXP .278 2.119 .035
• EXPSQ -.120 -.937 .350
• TENURE . 698 5.165 .000
• TENURESQ -.412
  -3.073 .002
• SEN -.214
  -1.302 .194
• Number PREVIOUS JOBS .174
  3.174 .002
• IOPS .028 .506 .613
• REL -.028
  -.504 .615
• SCAN -.049
  -.762 .447
• SCANSEN .371 2.207
  .028
• IOPSSEN .052
  .445 .180
• RELSEN -.013
  -.129 .234
• Dependent Variable gross monthly wage plus
  bonuses.
• Model summary
• R2.253, adjusted R2.229, F4.872, Sig.028
  n381

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Do networking activities impact innovation
performance? Innovation Performance Construct
(DV)
Construct Items Source ?
Project success in meeting deadlines Senior RD manager
Project success in technical capability Senior RD manager
Project success in market share Senior RD manager
Project success 0.62
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Innovation Success function constanta1
Size b1 Ownership c1 SCAN c2IOPS c3REL
whereSize Number of employees Ownership
Dichotomous variables between cooperative
enterprise and privately ownedScanningInter-orga
nisational problem solvingRelational networking
Dependent Variable sourced from Senior RD
managers, independent variables sourced from
knowledge workers.
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Regression results for innovation success

• Explanatory Variable Standardised Beta
  t Sig
• Constant 39.77 .00
• Size -0.15 -1.32
  0.18
• Ownership -0.33 -3.31 0.00
• Scan 0.24 2.14 0.03
• IOPS -.165 -1.54 0.13
• REL -.12
  -1.11 0.27
• Dependent Variable Success on innovation project
  as measured by degree of success in meeting
  deadlines, market
• share and technical capability.
• Model summary
• R2.20, adjusted R2.17, F4.587, Sig.036 n71

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Discussion of results

• Firms that engage with their environment will
  perform better than those that do not do so.
• Scanning carries the least cost associated with
  collaboration.
• Little evidence of innovation driven by formal
  collaboration (brokering) with other firms or
  academic institutions or relational networks.
  Why?
• innovation is not complex amongst Chinese firms,
  therefore does not require collaboration?
• High transaction costs to formal collaboration
  (poor social capital, low transparency of
  institutions?)
• There may be high costs associated with
  relational networks (Guanxi reciprocity?).
• Institutions too regimented, inflexible,
  resistance to reward individuals working on the
  margins of the organisation?