Innovation, open labour markets and brokerage opportunities for

knowledge workers in China’s ICT sector

Matias RamirezMatias Ramirez matias.ramirez@brunel.ac.ukmatias.ramirez@brunel.ac.uk

Peter Dickenson Peter Dickenson

DIME workshop DIME workshop ““Distributed networks and the knowledge-based economyDistributed networks and the knowledge-based economy””, , Juan-le PinsJuan-le Pins, 10, 10thth--1111thth May 2007 May 2007

Conceptualising firm level competence building through knowledge worker networks in Chinese R&D

labour markets

1. 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)

2. 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).

Dense ties run the risk of redundancy, increases Dense ties run the risk of redundancy, increases coordination costs for little benefit.coordination costs for little benefit.

Socio-centric emphasizes, not the network, but Socio-centric emphasizes, not the network, but the position of the individual in the network to fill the position of the individual in the network to fill structural holes.structural holes.

Brokering essential to create variation Brokering essential to create variation How to operationalise? By intertwining brokering How to operationalise? By intertwining brokering

activities of knowledge workers with labour activities of knowledge workers with labour market features associated with career and market features associated with career and rewards. rewards.

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).

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

Features of the Features of the Chinese Innovation Chinese Innovation system system

Size and history of the Chinese science and Size and history of the Chinese science and technology infrastructure, especially the technology infrastructure, especially the universities and C.A.S.universities and C.A.S.

Regional technology parks in china’s innovation Regional technology parks in china’s innovation system (employ 4 million knowledge workers system (employ 4 million knowledge workers and account for three-quarters of all exports of and account for three-quarters of all exports of high tech products). high tech products).

Labour markets of knowledge workers. 1 million Labour markets of knowledge workers. 1 million employed in R&D, 20m engineering graduates employed in R&D, 20m engineering graduates by 2015. by 2015.

Beijing’s Zhongguancun ParkBeijing’s Zhongguancun Park

1988 Beijing experimental zone became China’s first high 1988 Beijing experimental zone became China’s first high technology development zone. Included Founder (Beijing technology development zone. Included Founder (Beijing University), Tongfang (Tsinghua), Lenovo (C.A.S).University), Tongfang (Tsinghua), Lenovo (C.A.S).

14,000 high tech companies, 500,000 employees14,000 high tech companies, 500,000 employees Prime catalysts are NTEs (spin-offs from CAS and Prime catalysts are NTEs (spin-offs from CAS and

others). others). Financial incentives: Taxes waived first 3 years, 15% Financial incentives: Taxes waived first 3 years, 15%

thereafter (but only 50% paid for next 3 years). thereafter (but only 50% paid for next 3 years). In all science parks, 15% of firms are foreign owned, but In all science parks, 15% of firms are foreign owned, but

make up 42% of valued added.make up 42% of valued added. Surge of economic growth in 1990s appears to have by-Surge of economic growth in 1990s appears to have by-

passed Beijing, focussing mainly in Guandong, Jiangsu passed Beijing, focussing mainly in Guandong, Jiangsu and Tianjin. and Tianjin.

Beijing Beijing Zhongguancun Science ParkZhongguancun Science Park

Hypotheses

1.1. Knowledge workers will derive a wage premium for their Knowledge workers will derive a wage premium for their tenure with high technology companies.tenure with high technology companies.

2.2. ZGC Park has a highly fluid labour marketZGC Park has a highly fluid labour market, that rewards , that rewards knowledge workers for mobility and experience in the knowledge workers for mobility and experience in the labour marketlabour market

3.3. Firms in the ZGN will pay wage premiums for Firms in the ZGN will pay wage premiums for employees to collaborate and network (broker) outside employees to collaborate and network (broker) outside of the firm in innovation projects?of the firm in innovation projects?

4.4. Networking activities of knowledge workers will have a Networking activities of knowledge workers will have a positive impact on innovation performancepositive impact on innovation performance

Data analysisData analysis

Survey 1: Senior R&D managers in 71 Survey 1: Senior R&D managers in 71 Chinese ICT firms undertaking innovation.Chinese ICT firms undertaking innovation.

Survey 2: 381 knowledge workers (R&D Survey 2: 381 knowledge workers (R&D employees) from these 71 firms working employees) from these 71 firms working on specific projects.on specific projects.

Sample: Indigenous Chinese, ICT, located Sample: Indigenous Chinese, ICT, located in ZGC park, presence of R&D activity, in ZGC park, presence of R&D activity, must have introduced a new product in must have introduced a new product in past 3 years.past 3 years.

Construct Items Source Available n

         

     

     

         

Inter-organisational problem solving

Sharing knowledge with research institutes Team members 343 0.74

  Sharing knowledge with founder bodies Team members    

  Sharing knowledge with standard setting bodies

Team members    

         

Relational problem solving

Sharing knowledge with former classmates Team members 350 0.82  Sharing knowledge with colleagues Team members    

         

     

         

Scanning activity Attending conferences Team members 360 0.56  External communication via chat rooms etc Team members    

  Informal contact with external acquaintances Team members    

         

Network constructsNetwork constructs

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).

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.

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.

Do knowledge workers network?Do knowledge workers network?Networking activity by hierarchy

0

10

20

30

40

50

60

IOPS REL SCAN

%

Senior

Non-senior

IOPS and REL: Some/very influential in innovation projectIOPS and REL: Some/very influential in innovation project SCAN SCAN : Moderately/very important source of learningModerately/very important source of learning

Source: R&D employees

Regression 1: Are knowledge workers paid a Regression 1: Are knowledge workers paid a premium for their networking activities?premium for their networking activities?

Earnings Function:Earnings Function:W= constant+a1EXPW= constant+a1EXPi +i +a2 EXP2a2 EXP2ii+b1TENURE+b1TENUREi i +b2TENURE2+b2TENURE2i + i + c1Number of PREVIOUS JOBSc1Number of PREVIOUS JOBS + + d1 SENd1 SEN +d2 IOPS + d3 REL + +d2 IOPS + d3 REL + d4 SCAN + f1 IOPS*SEN + f2REL*SEN +f3SCAN*SEN where:d4 SCAN + f1 IOPS*SEN + f2REL*SEN +f3SCAN*SEN where:

W = gross monthly wage including bonuses. W = gross monthly wage including bonuses. EXP = years prior experience to joining present firm, EXP = years prior experience to joining present firm,

TENURE = years in current firm, TENURE = years in current firm, SEN = level of seniority (we distinguish between manager/senior SEN = level of seniority (we distinguish between manager/senior

engineer and non-management technical/commercial). engineer and non-management technical/commercial). IOPS = inter-organisational networking, IOPS = inter-organisational networking, REL = relational networking, REL = relational networking, SCAN = general networking. SCAN = general networking. IOP*SEN, IOP*SEN, REL*SEN REL*SEN SCAN*SENSCAN*SEN

interactive terms interactive terms between seniority between seniority and different types and different types of networkingof networking

Regression results for entire sample of Regression results for entire sample of knowledge workersknowledge workers

Explanatory Variable Standardised Beta t SigConstant 7.692 .000EXP .278 2.119 .035** EXPSQ -.120 -.937 .350TENURE . 698 5.165 .000**TENURESQ -.412 -3.073 .002**SEN -.214 -1.302 .194Number PREVIOUS JOBS .174 3.174 .002**IOPS .028 .506 .613REL -.028 -.504 .615SCAN -.049 -.762 .447SCAN*SEN .371 2.207 .028 **IOPS*SEN .052 .445 .180 REL*SEN -.013 -.129 .234

Dependent Variable: gross monthly wage plus bonuses.Model summary:

R2=.253, adjusted R2=.229, F=4.872, Sig=.028 n=381

Do networking activities impact Do networking activities impact innovation performance?innovation performance?

Innovation Performance Construct (DV)Innovation Performance Construct (DV)

ConstrucConstruct t

ItemsItems SourceSource Project Project success in success in meeting meeting deadlinesdeadlines

Senior R&D Senior R&D managermanager

Project Project success in success in technical technical capabilitycapability

Senior R&D Senior R&D managermanager

Project Project success in success in market market shareshare

Senior R&D Senior R&D managermanager

Project Project successsuccess

0.620.62

Innovation Success function:= Innovation Success function:= constant+a1 Sizeconstant+a1 Size + +b1 Ownership+b1 Ownership+ c1 c1 SCANSCAN + + c2IOPS + c3REL where: c2IOPS + c3REL where:

Size = Number of employees Size = Number of employees Ownership = Dichotomous variables between cooperative enterprise and Ownership = Dichotomous variables between cooperative enterprise and privately ownedprivately ownedScanningScanningInter-organisational problem solvingInter-organisational problem solvingRelational networking Relational networking

Dependent Variable sourced from Senior R&D managers, Dependent Variable sourced from Senior R&D managers, independent variables sourced from knowledge workers. independent variables sourced from knowledge workers.

Regression results for innovation successRegression results for innovation success

Explanatory Variable Standardised Beta t Sig

Constant 39.77 .00

Size -0.15 -1.32 0.18Ownership -0.33 -3.31 0.00**Scan 0.24 2.14 0.03**IOPS -.165 -1.54 0.13REL -.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, F=4.587, Sig=.036 n=71

Discussion of results Discussion of results Firms that engage with their environment will perform better Firms that engage with their environment will perform better

than those that do not do so.than those that do not do so. Scanning carries the least cost associated with collaboration.Scanning carries the least cost associated with collaboration.

Little evidence of innovation driven by formal collaboration Little evidence of innovation driven by formal collaboration (brokering) with other firms or academic institutions or (brokering) with other firms or academic institutions or relational networks. Why? relational networks. Why?

innovation is not complexinnovation is not complex amongst Chinese firms amongst Chinese firms, therefore does , therefore does not require collaboration? not require collaboration?

High transaction costs to formal collaboration (poor social capital, High transaction costs to formal collaboration (poor social capital, low transparency of institutions?)low transparency of institutions?)

There may be high costs associated with relational networks There may be high costs associated with relational networks ((Guanxi reciprocityGuanxi reciprocity?).?).

Institutions too regimented, inflexible, resistance to reward Institutions too regimented, inflexible, resistance to reward individuals working on the margins of the organisation?individuals working on the margins of the organisation?