does a different view create something new?

The Impact of Employee Diversity and Labor Mobility on Innovation

Does a Different View Create Something New?

Bram TimmermansDRUID/IKE, Department of Business and Management

Email: [email protected]

METEOR Seminar (TIID)

About me• Postdoc in Innovation Studies

• Department of Business and Management, Aalborg University, Denmark• Member of the IKE group (currently 11 seniors and 5 PhD. Students)• Member of DRUID (AAU, CBS, SDU)

• Coordinator of the MIKE program (MSc in innovation and entrepreneurship)• 2-year Master 20-30 students per year• Economics and Business students

• Co-organizer of the DRUID Academy (Winter) conference• Conference for PhD Students• 70-80 students, 6 invited keynotes, 17 DRUID faculty• Three days in mid-January in Cambridge: see www.DRUID.dk

• Current research interest:• Labour Mobility and Performance• Offshoring and Changes in Employment Composition• Employee Diversity and Innovation• Entrepreneurial Team Composition• Dynamics of the (Global) Roller Coaster Industry

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Presentation Overview• Introduction• Basic Idea

• Composition Study• Mobility Study

• Issue of Diversity• Some problems in measuring diversity • Theories of employee diversity and innovation• Hypotheses

• Issue of Mobility• Positive effects of mobility• Negative effects of mobility• Absorptive capacity

• Data and Method• Results• Conclusion

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INTRODUCTION

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Introduction-diversity on the labour market• Changes in the economy, industry structure, population, labor market and

work force during the last 40 years:

• Women entered the labour market• Labour markets has become more international – Immigration• Increase in the educational level• New types of educations• Increasing labour mobility

• Globalisation and technological change• International competition• Growing exports and imports• Changed production patterns (offshoring outsourcing)

• Creates an increased focus on the composition of the workforce and performance, both on innovation and other performance measures

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METEOR Seminar (TIID) 21 December 2011


Composition study Mobility study

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THE BASIC IDEA

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The Basic Idea-Composition study• Our knowledge and actions are affected by our experiences

• Categorization – related to instincts - we do not like differences and the unknown

• Cognitive models - psychology: our knowledge, world-view and the way we react depends on our experience, education, social class, gender and age

• Culture (anthropology)

• Innovation as an interactive process that involves interaction and communication between various levels of the firm (Lundvall)

• Differences in the knowledge base in a firm creates opportunities for learning and new combinations

• Employee diversity might create a broader search space, make firms more open towards new ideas and be more creative

• Intuitive idea that employee diversity is good for innovation

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The Basic Idea-Mobility study• Increasing attention on the significance of

(technological) relatedness for innovation and growth.

• Relatedness is positively associated with interactive learning of economic entities.• Diversity helps learning but it should not be too

diverse nor too similar• Mergers, acquisition and collaboration• Explanation in regional economic development

and spatial clustering of industries

• Recently this concept is used in labour market studies

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Inside or Outside• Cohen and Levinthal (1989, 1990, 1994), Joshi and Jackson (2003), and many

others

• Two knowledge dimensions of effects of employee diversity

1. Within firm• Broad knowledge base• Cross fertilization and creation of new ideas

2. Outside links• Broad outside search and networks• Increased external sourcing• Absorptive capacity – use of external knowledge

• In the composition study we neglect outside links – focus on within firm effects.

• In the mobility study we link to the outside links and relation to knowledge and skills from particular geographical regions.

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THE ISSUE OF DIVERSITY

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What is diversity and how should it be measured• Employee diversity:

• Everybody is unique, but there are many similarities• Measure depends on which factors you look at and the purpose of the

analysis

• Employees differ along a wide range of dimensions (demography, experiences, knowledge base, cognitive models, attitudes, values, norms) that are generated through complex processes

• We need measurable characteristics and the diversity measures need to be workable

• Visible or invisible differences

• Ascribed and achieved characteristics (Rueff et al. 2003)• Ascribed: demographic attributes such as gender, age, and ethnicity• Achieved characteristics: educational background, functional background,

work experience

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What is diversity and some problems in measuring diversity• Diversity has three dimensions (Stirling, 2007)

• Variety (number of different types/groups)• Balance (shares of the different groups)• Disparity (the distance between the different groups)

• Different characteristics: gender, age, education, ethnicity …• but every employee fits into multiple categories

• We define employee diversity as the distribution of differences among the employees of the firm with respect to a common attribute• Unit-level compositional construct (Harrison and Klein, 2007)

• Diversity should always been seen in context• Diversity is not always good or bad

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Diversity and Performance• There is a long tradition for studying diversity and performance

• “It is the heterogeneity of the productive services available or potentially available from its resources that gives each firm its unique character” (Penrose, 1959).

• Evolutionary economics• Firms with diversity in knowledge, experience and skills among their

employees benefits from complementarities that can foster development in other fields

• … they have broader organisational routines (Nelson&Winter)• … they have a broader search for new solutions (Dosi)• … they are better to gain and exploit external knowledge (Cohen& Levinthal)• … they are better to exploit internal knowledge through interaction and

learning (Lundvall)• Empirical studies show that technologically diverse firms survive longer and

are more innovative• Diversity is positive for innovation, but most studies focus is on technology not

human capital

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Diversity and Performance-Top Management Teams• Upper echelon theories (Finkelstein and Hambrick)

• Education, experience and demographic characteristics affects the managements interpretation of problems and their strategy, which has an effect on firm performance.

• Diversity of a larger management proved to be a predictor for firm performance.

• Top Management Team Literature and firm performance (Murray 1989, Bantel and Jackson 1989, Kilduff et al. 2000).

• Top management does not reflect composition of the entire firm.

• Firms knowledge in the form of human capital is important in explaining performance (Laursen et al. 2005).

• Diversity in the composition of employees contributes to diversity in the knowledge base.

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Diversity and Performance-Critical Perspectives• Decision making (Priem et al, 1995):

• To make good decisions when facing complex problems a degree of cognitive conflicts and different view points are needed to avoid premature consensus.

• Too much diversity could create conflict.

• Group think (Baron, 2005) • Too much cohesion in groups hinders good evaluation of ideas. • Social identity (Joshi and Jackson 2003): • Diversity in groups creates competition and conflict which reduce

cooperation and internal communication.

• Use of information (Dahlin et al, 2005)• Diversity increase the breath of information collection and use of information,

but too much diversity hinders diffusion.

• Communities of practice and learning (Wenger)• Interaction between different competencies and experiences creates learning

if the disparity is not too large.

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Positive or Negative?• William & O’Reilly (1998) 40 years of studies of demography and diversity in

organisations:• Diversity has both direct and indirect effects on processes and group

performance• These effects can be negative and positive.• But there are also many studies that find no effect

• More recent studies find similar results

• Positive effects: openness, creativity, learning, flexibility, broader search space, better problem solving, increased absorptive capacity and new combinations of knowledge

• Negative effects: distrust, conflict, dissatisfaction and increased transaction costs (interaction and communication between two different knowledge bases and groups might be difficult )

• Group membership, social interactions, power relations, organisational framework

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What is the relation between diversity and innovation?

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Inno

vati

on

Diversity


The relation between employee diversity and innovation• Performance measures:

• Productivity• Turnover or profits • Patents• Innovation

• Innovation is different (human capital is more important) • An invention and creativity phase• An implementation phase

• Selection effects • Hiring policies• Self selection• Organisational structure

• Only a few studies of innovation and they focus on TMT or a single firm and use innovation proxies, but generally finds some positive effects

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Hypotheses• Hypothesis 1: There is a positive relation between employee diversity and

the likelihood that firms innovate.

• Hypothesis 1a: There is a positive relation between gender diversity and the likelihood that firms innovate.

• Hypothesis 1b: There is a negative or neutral relation between age diversity and the likelihood that firms innovate.

• Hypothesis 1c: There is a positive relation between diversity in ethnicity and the likelihood that firms innovate.

• Hypothesis 1d: There is a positive relation between educational diversity and the likelihood that firms innovate.

• Hypothesis 2: The likelihood that firms innovate decreases for high levels of employee diversity.

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THE ISSUE OF LABOUR MOBILITY

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Labour Mobility- the positive effects

• Labour mobility is often regarded as a mechanism that enhances the competitiveness of firms (and regions)• Labour mobility is considered an important mechanism for

the dissemination of (tacit) knowledge (e.g. Almeida and Kogut, 1999; Pinch and Henry, 1999).

• Overall, the benefits of labour mobility exceed the negative effects.

• These studies assume that new employees get integrated without major frictions.• Contribute to internal learning processes and the well being

of the firm.

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Labour Mobility- the negative effects

• There are negative impacts of labour mobility • Studies have shown that high level of

labour mobilit have a negative impact on firm performance (Faggian and McCann, 2006; Boschma 2009).

• Challenges with integration of people with a very different profile

• There is little attention on the type of knowledge and skills that are transferred as a result of labour mobility.

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Labour Mobility- Absorptive Capacity• Firms require absorptive capacity to understand external

knowledge.

• Not only the level of absorptive capacity is important but also the proximity of this external knowledge compared to the existing knowledge base is important, i.e. not too far nor too close.

• This has been applied to a Swedish study on labour mobility (Boschma, 2009).

• This mobility study focuses, in addition to the level of relatedness, also on the geographical location where the worker has obtained the knowledge and skills.

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DATA AND METHOD

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Database• The Danish Integrated

Database for Labour Market Research (IDA)

• detailed information on all Danish firms and all individuals on the labour market from 1980 onwards

• information on the characteristics of individuals

• Information on the performance and characteristics of firms and plants

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Innovation survey


Sample

Composition study• Disko4 innovation

questionnaire survey on organisations, employees and research and development strategies in Danish firms

• Innovation activity in the period 2003-2005 • sent to stratified sample of

4.136 companies, • 1.775 answers • response rate of 42.9

percent• we use 1.648 observations

Mobility study• Plants in the period 1999-2003

that experienced an inflow of skilled labour (N=16,709)

• Human characteristics• Mean taxable income• 25 yrs of age• at least 20 hours a week• registered to change plant• hold a university degree of belong

to the top 20 percent wage earners.

• Plant characteristics• plants active in manufacturing and

services• firms with accounting data• No new plants/start-ups

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Dependent Variable

Composition study• Innovation• Innovation is defined

as whether the firm has introduced a new product or service during the period 2003-2005, excluding minor improvements on already existing products and service.

Mobility study• Labour productivity

growth on the plant level• Value added per worker

• Data not available on the plant level• 6,402 (38.31 percent)

multiple plant firms• Determining the value

added per plant based on the distribution of wages

• two year lag to determine labour productivity growth

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Control Variable

Composition study• Industry: Two digit

NACE industries • Size• Firm age• Organisational change• Diversity policy • Dummy variables for

high intensity collaboration along the value chain

Mobility study• Industry: Two digit

NACE industries • Size• Firm age • Employment growth• Growth in fixed assets• High education ratio• Region• Year

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Independent Variable

Composition study• Entropy measures

GenderEthnicityEducation

• Standard error• Age

• Categories• Gender• Academics

• Share• Academics

Mobility study• Identify the high-skilled inflow

workers• Identify the industry

experience of the workers in the last 5 yrs.

• Take the most related industry experience

• Measure the degree of similar, related and unrelated variety

• Make a distinction between intra- and interregional experience

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Diversity in more detail• Gender diversity

• Entropy

• Gendergroups (1–5) based on the share of the most represented gender: Group 1: 90–100% of the same gender, Group 2: 80–90% of the same gender, Group 3: 70–80% of the same gender, Group 4: 60–70% of the same gender and Group 5: 50–60% of the same gender

• Ethnicity (EthnDiv) we use the individual’s country of origin.• divided into six different groups: Danish, Nordic, EU15 and Swiss, other

Europeans, other western countries, and the rest of the world• Education

• 16 different higher education categories making a distinction between Bachelor’s, Master’s and Ph.D. degrees

• social sciences, humanities, food and health science, engineering, and natural sciences, high-school teachers and officers in the army, navy, and air force

• dummy variable on the presence of at least one highly educated employee (HighEducDummy)

• Share of share of highly educated employees in the firm (HighEducShare).

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Relatedness in more detail• Similar

• Most related experience in the same 4 digit NACE industry class• inflow (count)

• Relatedness• Revealed Relatedness vs. NACE relatedness• NACE relatedness measure makes a distinction based on the 2 and 4

digit industry classes• Revealed Relatedness method described in Neffke and Henning (2009)

makes a distinction based on Swedish labour mobility patterns.

• Unrelated Variety• All the inflows that are not similar or related

• We make a distinction on whether these inflows are from the same labour market region or not.

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Danish Labour Market Regions

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CLMA vs. Rest of Denmark

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RESULTS

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Composition study


Results-Composition Study• Hypothesis 1a. There is a positive relation between gender diversity and the likelihood that firms innovate.

• Positive effect• Generally overlooked in the innovation literature

• Hypothesis 1b. There is a negative or neutral relation between age diversity and the likelihood that firms innovate.• Negative relation

• Hypothesis 1c. There is a positive relation between diversity in ethnicity and the likelihood that firms innovate.• No significant relation• Labour market dominated by Danes• Routine work

• Hypothesis 1d. There is a positive relation between educational diversity and the likelihood that firms innovate.• Positive relation• Most important diversity dimension • Human capital• Professional identity

• Hypothesis 2. The likelihood that firms innovate decreases for high levels of employee diversity.• Not supported• Self selection, HRM policies, generally no extreme diversity

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Issues• What about related variety?• What about tenure (length of service) ,

experience and positions• How to deal with mobility• Who is actually involved in the innovation

process

• Self reported data• Sample bias• Causality

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Mobility study


CONCLUSION

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Composition Study

Conclusion• The study of 1,648 Danish firms shows that

employee based on the characteristics of all employees have a effect on their likelihood to innovate

• Employee diversity matters for firms’ innovative performance

• Employee diversity in terms of gender, age, education has an effect on the likelihood that firms innovate with controls for other factors

• Strongest effect of education• Followed by gender• Negative effect for diverse age

distribution• No effect on ethnicity• No indication for curvilinear effects

• Similar findings in other innovation-diversity studies (education and age).

Future Research• Consider other factors that make the human

capital composition of a firm to a success - not only at the demographic composition

• Diversity management and management culture

• Better measure of teams involved in innovation

• Persistent innovators and diversity• Causality for the link between diversity and

innovation

• Including various types of work organisation, innovation modes (DUI/STI) and strategies

• Types of jobs and mobility

• Regional differences and regional characteristics

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Results-Mobility Study

Conclusion• Related variety has a positive

impact on labour producitivy growth

• Similarity has a negative impact on firm performance

• Does not apply to the Copenhagen area• Might be the more dominant role

of service• Statistical artifact since services

are more broadly defined.• Lots of variety within the same

industry

Future research• The particular findings of the Copenhagen

region require attention

• How does the issue of related variety impact particular sector and on different stages in the industry life-cycle?

• How do different regions react on similarity, related and unrelated variety.

• Investigate whether regions with high labour mobility enhance regional growth in general?

• Investigate the black box of interaction within firms between employees with similar, related and unrelated skills.

21 December 2011

[email protected]

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