age diversity 2011

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AGE DIVERSITY AND FIRM

PERFORMANCE IN AN EMERGING

ECONOMY: IMPLICATIONS FOR

CROSS-CULTURAL HUMAN

RESOURCE MANAGEMENT

J I L I , C H R I S W A I L U N G C H U , K E V I N C . K . L A M ,A N D S T A C Y L I A O

This study tests the effect of age diversity on firm performance among

international firms. Based on the resource-based view of the firm, it argues

that age diversity among employees will influence firm performance.

Moreover, it argues that two contextual variables—a firm’s level of market

diversification and its country of origin—influence the relationship between

age diversity and firm performance. By testing relevant hypotheses in a

major emerging economy, that is, the People’s Republic of China, this study

finds a significant and positive effect of age diversity and a significant inter-

active effect between age diversity and firm strategy on profitability. We also

find a significant relationship between age diversity and firm profitability

for firms from Western societies, but not for firms from East Asian societies.

The paper concludes by discussing the implications of this study’s findings.© 2011 Wiley Periodicals, Inc.

Keywords: age diversity, firm performance, emerging economy, humanresource management, China

T

his study tests the relationship be-tween age diversity and firm perfor-mance for multinational enterprises(MNEs) competing in an overseas

market. According to the literature(Milliken & Martins, 1996; Williams &O’Reilly, 1998), age diversity can be defined asthe extent to which a group or organization isheterogeneous with respect to the age of its

members. Today, the issue of age diversity hasbecome increasingly important in humanresource management due to the aging ofworkforces throughout the world. In Britain,

for example, some 30% of the UK working-age population is older than 50, and thisnumber will increase by a further 10% in thenext 20 years (Pollitt, 2006). The same devel-opment has taken place in the United States,

Correspondence to: Chris Wai Lung Chu, China Economic Research Center, Stockholm School of Economics, Box6501, 11383 Stockholm and Work & Organisational Psychology, Aston Business School, Aston University,Birmingham, UK, Phone: +46-8-736-99747, Fax: +46-8-319-927, E-mail: [email protected]

Human Resource Management

Human Resource Management, March–April 2011, Vol. 50, No. 2, Pp. 247 – 270

© 2011 Wiley Periodicals, Inc.

Published online in Wiley Online Library (wileyonlinelibrary.com).

DOI: 10.1002/hrm.20416


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248 H UMAN R ESOURCE M ANAGEMENT , M ARCH –APRIL 2011

Human Resource Management DOI: 10.1002/hrm

where census data show that during the 1990sthe fastest-growing age group was 45- to54-year-olds, which expanded by 49% duringthat decade (Branch-Brioso, 2001; Kidwell,2003). At the same time, the development ofan aging workforce is occurring in emerging

economies. In China, for example,research indicates that three agegroups of employees, namely, 45-to 59-year-olds, 60- to 64-year-olds,and older than 65, are all increas-ing rapidly. These three groups areanticipated to increase by 21.54%,2.92%, and 3.08%, respectively, ofthe Chinese workforce in 2000, to28.69%, 7.74%, and 11.34% ofthat workforce, respectively, by2010 (Wang, 2006).

Aging workforces throughoutthe world will thus increase thelevel of age diversity in businessfirms and other organizations.Young employees may find theywork with an increasing numberof older employees. Therefore, it isimportant for firm managers tounderstand the specific issues thatrelate to this development, such ashow age diversity can influence

firm performance and what con-textual conditions or factors canmoderate the relationship betweenage diversity and firm performance.With such an understanding, man-

agers will find it easier to develop appropriatestrategies to manage age diversity in theirworkforces and encourage employees of differ-ent ages to work together more effectively togenerate a positive performance synergy.

Age diversity is also an important research

topic today for social scientists who are deal-ing with issues related to the demographicdiversity of organizations. Most studies ondemographic diversity now focus on threedimensions: age, gender, and race. In termsof visibility, these three demographics differfrom other dimensions, such as education,technical skills or abilities, functional back-ground, and tenure (Milliken & Martins,1996). In academic research, demographicdiversity scholars often assume that the

findings from studying one dimension ofdemographic diversity can be applied simi-larly to research into other dimensions.

For instance, based on information anddecision-making theories, researchers haveargued that demographic diversity, be it

diversity in age, race, or gender, should in-crease creativity and the problem-solvingcapability of groups or organizations, whichin turn should improve firm performance,given specific contextual conditions or factors(see Cox, 1993; Cox & Blake, 1991). Althoughthe empirical data from studying race diver-sity supports this argument, it is helpful totest this argument further by studying otherdimensions of demographic diversity, such asage. In other words, studying the effect of agediversity can provide new empirical evidencethat will contribute to developing theoriesregarding organizational demography.

As we discuss below, the research on agediversity is insufficient because few studieshave tested the effects of age diversity onfirm performance directly. Moreover, theexisting research on the relationshipbetween age diversity and performance wasconducted at the individual or group levelsonly (see Williams & O’Reilly, 1998, for areview), thus shedding insufficient light on

the precise relationship between age diver-sity and firm performance. Finally, even atindividual or group levels, the current re-search is insufficient because researchershave not yet tested the moderating effectsof certain relevant contextual factors. Forinstance, some authors have suggested thatcontextual factors such as firm strategymoderate the relationship between age di-versity and group performance (see Ely,2004), yet no empirical research has tested

this prediction or the effect of culture, animportant institutional factor that affectsfirm behavior and firm performance (Scott,2001). No empirical research to date, how-ever, has tested how societal culture moder-ates the relationship between age diversityand firm performance. Because an agingworkforce is now a growing key problemworldwide, it would be helpful to considerthe effects of societal culture when study-ing any issues related to age diversity.

It is important for

firm managers to

understand the

specific issues

that relate to...

how age diversity

can influence firm

performance and

what contextual

conditions or factors

can moderate

the relationship

between age

diversity and firm

performance.


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AGE D IVERSITY AND F IRM P ERFORMANCE IN AN E MERGING E CONOMY 249


Clearly, countries in different parts of theworld differ significantly in cultural values.Among these differences, the most significantone, in terms of its effect on the relationshipbetween demographic diversity and firm per-formance, is a preference for individualism or

collectivism. Western culture, including NorthAmerica and Western Europe, is considered tobe individualist, whereas the culture in theEast, including China, Japan, and Korea,is considered to be collectivist (see Hofstede,1980, for a detailed discussion). According toinstitutional theory, the culture in differentcountries or regions should influence the be-havior of organizations within that region(Scott, 2001). Nevertheless, in the research ondemographic diversity or age diversity, it re-mains unclear how cultures in different coun-tries or regions influence the performance orbehavior of MNEs.

It would be significant for both academicresearchers and practitioners to study these is-sues. For academic researchers, testing theseissues can improve the understanding of therelationships between age diversity and firmperformance, as well as the moderating effectsof contextual variables on that relationship.For practitioners, studying age diversity canprovide helpful information to improve the

actual management of organizational diversity.Although existing research on organizationaldemography offers some useful findings onhow to balance demographic diversity andmanage that diversity, the findings thus farmainly focus on the individual or group levelsof human resource management. Managerswould improve their effectiveness in manag-ing organizational diversity if they better un-derstood how firm-level factors, such as firmstrategy, affect the relationship between demo-

graphic diversity and firm performance.Finally, little research is available on therelationship between age diversity and firmperformance in emerging economies. Such astudy would be both important and helpful forseveral reasons. First, emerging economiestoday have some of the fastest growingmarkets critical to the recovery of the worldeconomy. Seeing the potential of thesemarkets, MNEs are all operating in theseeconomies and all face the issue of an aging

workforce in some of their markets. To helpthese MNEs overcome this difficulty, it wouldbe useful to conduct research on age diversityin emerging economies. Second, todevelop theory on demographicdiversity further, studying age di-

versity in emerging markets willhelp test the external validity offindings obtained in the West andfurther improve full understandingof the effect of country origin orculture. Finally, from the perspec-tive of business ethics, studying agediversity can ensure equal opportu-nity for employees by clearly man-aging the contributions of each agegroup. Of course, equal opportuni-ties for employees throughout theworld should always be available,regardless of age, gender, or race.

Accordingly, relevant researchshould not focus only on employ-ees in developed societies and ig-nore the conditions of employeesin emerging economies. In thissense, the literature is weak ondemographic diversity and haspaid insufficient attention to theserelevant issues for employees in

emerging economies. This study,therefore, tests the effects of firmstrategy and country of origin onthe relationship between em-ployee age diversity and firm per-formance in a major emergingeconomy: the People’s Republic ofChina. A major reason for selecting China isits large number of MNEs from both the Westand the East, all competing aggressively in itsmarkets. Considering these MNEs, the sample

size of this study can be sufficiently large foreffective empirical testing.

Conceptual Background

Research suggests that the resource-basedview (RBV) of the firm can be a powerfultheory when considering the relationshipbetween demographic diversity and firm per-formance (see Richard, 2000). According tothe RBV (Amit & Schoemaker, 1993; Barney,

From the

perspective of

business ethics,

studying age

diversity can ensure

equal opportunity

for employees by

clearly managing

the contributions

of each age group.

Of course, equal

opportunities

for employees

throughout the world

should always be

available, regardless

of age, gender, or

race.


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1986; Peteraf, 1993; Teece, Pisano, & Shuen,1997), firms must accumulate and developunique and difficult-to-copy resources (Col-bert, 2004) and formulate and implementcreative and effective strategies. Good firmperformance indeed depends on whether a

firm can rationally identify and control itsresources (Teece et al., 1997).

Applying the resource-based perspective(Amit & Schoemaker, 1993; Barney, 1986),firm resources can be divided into tangible,intangible, and human resources. Tangibleresources refer to organizational assets thatare relatively easy to identify, such as physi-cal and financial assets. Intangible resourcesare those that are difficult to identify or ac-count for, such as firm reputation, brandnames, and firm image. Finally, a firm’shuman resources are intangible assets thatexist among the firm’s employees, such asexperience, creativity, and capabilities. Thisresource-based perspective argues that humanresources are extremely valuable because theyare often unique and difficult to copy in con-trast with other resources, such as physical orfinancial. As a result, human resources areoften the crucial differentiating factor thatexplains the differences in performanceamong firms that possess similar physical

and financial resources (Pfeffer, 1994).Under certain contextual conditions, age

diversity is an important part of a firm’shuman resources. According to some re-searchers on decision-making (for example,Avery, McKay, & Wilson, 2007; Peterson &Spiker, 2005), age diversity can increase cre-ativity and capabilities in a firm, which inturn can lead to sustained competitive advan-tage. In other words, under those contextualconditions where creative and effective deci-

sion-making is critical, age diversity can be animportant factor that leads to increased com-petitive advantage. Moreover, age diversity isdifficult to copy because it is protected by bar-riers of interpersonal connections, knowledge,and experience that are highly complex so-cially (Beaver & Hutchings, 2005; Li, Fu, Liu,& Chen, 2008; Timmerman, 2000).

Further, as populations worldwide growolder, an appropriate level of age diversityamong a firm’s employees can actually improve

marketing and financial performance (Jayne &Dipboye, 2004). For example, age diversity canhelp a firm better understand the preferencesand demands of its aging customers (Morri-son, 1992), which in turn will improve firmperformance. For instance, an insurance firm

trying to sell life or medical products to mid-dle-aged and older customers may be moresuccessful if it has the right proportion of em-ployees in these same age categories. Empiri-cally, some authors have shown that it isbeneficial for a firm to adjust the demographicproportions of its human resource mix to re-flect the age spread of its target market (Cox &Blake, 1991; Richard, 2000).

Another reason age diversity is a valuableresource is that both old and young employ-ees have unique values upon which theirfirms can draw to improve performance. AsCox and his coauthors (Cox, 1993; Cox &Blake, 1991) suggested, age diversity offers abroad range of perspectives, skills, and in-sights that can enhance creativity and prob-lem-solving capabilities, thereby improvingfirm performance. Consistent with this find-ing, other research has shown that olderemployees have unique value because theycontribute to a dimension of human resourcesobtained only through many years of work-

ing in a specific organization and learning aspecific industry (see Ntatsopoulos, 2001;Peterson & Spiker, 2005). Moreover, older em-ployees contribute socially complex dynam-ics, such as social connections developedacross years of working in a given businessenvironment. Finally, older employees oftenhave a higher level of caring and responsibil-ity than do younger employees (see Ntatso-poulos, 2001; Van Yoder, 2002). Empiricalevidence supports these arguments. For ex-

ample, research from the Department forWork and Pensions of the UK governmentconducted as part of its Age Positive campaignsuggested that individuals older than 50 aremore reliable, conscientious, loyal, hard-working, and committed (Pollitt, 2006). Pre-cisely because of these characteristics, olderemployees’ contributions are unique resourcesthat are difficult for other firms to copy.

Younger employees also bring unique val-ues to their organizations, including flexibility,


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energy, and creativity (Beaver & Hutchings,2005). Younger employees are normally bet-ter educated and physically more capable(Hatfield, 2002). An appropriate level of agediversity will thus allow the value of bothgroups of employees to complement one an-

other and subsequently help the firm achievegood performance.

Finally, a firm that tries to attract diversi-fied and capable human resources stands amuch greater chance of success if it main-tains balanced age diversity. As some authorshave suggested (see Beaver & Hutchings,2005), firms that capitalize on age diversityare in a better position to attain competitiveadvantage by being an employer of choice fortalented workers—both older and younger—which then positively affects firm perfor-mance. Accordingly, the following hypothesisis formulated:

Hypothesis 1: Age diversity has a significant and positive effect on firm performance.

Numerous authors (Barney & Wright,1998; Oliver, 1997) pointed out that the ef-fects of demographic diversity, including agediversity (see Caldwell, Farmer, & Fedor, 2008;Cleveland & Shore, 1992; Timmerman, 2000;

Tsui, Porter, & Egan, 2002), can be better un-derstood if additional contextual variables areconsidered. In other words, firm resources thatare unique and difficult to copy are morelikely to have a significant effect on firm per-formance when that firm is also positionedwithin the proper context, such as implement-ing a certain strategy or operating against acertain cultural background (see Miller &Shamsie, 1996; Richard, 2000). Several studiesoffer empirical evidence supporting this argu-

ment, and some have tested the effects of agediversity directly. For instance, Ely (2004)studied data from 486 branches of a bank inthe United States and found that given condi-tions of low cooperation and teamwork, agediversity had a strong positive effect on therevenue these branches derived from newsales and a weak positive relationship on totalperformance. Ely (2004) attributed this resultto “a trade-off between cooperation/teamwork and the expression of difference”

p. 775). It seems that in conditions character-ized by low cooperation, age diversity can be-come more significant as a sourceof information and experience fora given team or branch trying toachieve good performance.

Despite these documentedfindings, however, it remains un-clear how age diversity preciselyinfluences firm performance as awhole because no study hasactually tested the relationship be-tween age diversity and perfor-mance at the firm level. Relevantempirical data from past studiesrelates to the individual or grouplevels only. There are, however,studies that directly tested therelationship between firm perfor-mance and other dimensions ofdemographic diversity, such asrace or culture. For example,Richard (2000) conducted an em-pirical study showing that racialdiversity interacted with imple-menting a growth strategy forfirms in the U.S. banking industryand had a significant and positiveeffect on firm performance.

Similarly, Chatman, Polzer, Bars-ade, and Neale (1998) found thatan organization valuing collectiv-ism could moderate the relation-ship between demographic diversity andgroup performance. This result supports apossible cultural or institutional effect on therelationship between age diversity and firmperformance.

Although these studies tested the relation-ship between race diversity and firm

performance only, they produced empiricalevidence that supported a general argumentbased on the theory of demographic diversity:heterogeneity within the workforce can im-prove firm performance given certain specificcontextual factors (Cox, 1993; Cox & Blake,1991). The presence of contextual factors,such as a certain firm strategy and heteroge-neity (whether in terms of race or age), canoffer a broad range of perspectives, skills, ex-periences, and insights that enhance a firm’s

The presence of

contextual factors,

such as a certain

firm strategy and

heterogeneity

(whether in terms

of race or age), can

offer a broad range

of perspectives,

skills, experiences,

and insights that

enhance a firm’s

creativity and

problem-solving

capabilities and

thereby improve firm

performance.


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creativity and problem-solving capabilitiesand thereby improve firm performance.

To test these arguments, this study fo-

cuses on the effects of two contextual vari-

ables. One is the commonly adopted strategy

of geographic diversification, while the other

is country of origin. The data analyses testedthe effects of these two contextual variables

on the relationship between age diversity and

firm performance. Before reporting

how these analyses were con-

ducted, it is helpful to discuss rel-

evant past research.

The Effect of GeographicDiversity

According to prior research, the

strategy of geographic diversifica-tion is defined as one by whichfirms compete in multiple geo-graphic locations or markets (Kor& Leblebici, 2005). One couldargue that age diversity is morelikely to have a positive effect onfirm performance, given a highlevel of diversification. Specifi-cally, with a high level of diversi-fication, a firm should build a

workforce with different marketand product knowledge, experi-ences, and skills. It is easier for afirm that possesses a high level ofage diversity to obtain such knowl-edge and experience, whichshould help the firm obtain com-

petitive advantage when adopting the strat-egy (Kor & Leblebici, 2005). For example, astrategic issue for firms in China’s insuranceindustry is whether to focus only on certaincoastal cities that are economically more ad-vanced or diversify into inland cities that areeconomically backward. Given the signifi-cant environmental differences betweenthese two types of cities, if a firm decides toenter all cities in China, that is, to achieve ahigh level of geographic diversification, thefirm may need different market and productknowledge, experiences, and skills. As sug-gested, a high level of age diversity can helpthe firm satisfy this need. In this sense, age

diversity becomes a valuable resource becausethe firm seeks a high level of market diversi-fication.

Some empirical evidence supports thisargument. For instance, the strategy of geo-graphic diversification is often consistent

with growth strategy, a link tested by otherresearchers (see, e.g., Richard, 2000). A growthstrategy often involves selling current prod-ucts to additional or multiple geographicmarkets (Kotha & Orne, 1989). Previous re-search has suggested that when firms adopt agrowth strategy, certain dimensions of demo-graphic diversity, such as race, can have asignificant and positive effect on the firm’sfinancial performance (Richard, 2000). Thisfinding is consistent with our argument re-garding the effect of a diversification strategyon the relationship between age diversity andfirm performance.

Accordingly, we predict that the relation-ship between age diversity and firm per-formance is moderated by a strategy ofgeographic market diversification. The posi-tive effect of age diversity is more likely to beobserved given a high level of diversification.

Hypothesis 2: The relationship between age di-versity and firm performance is moderated by

the strategy of geographic market diversification,with the positive effect of age diversity on firm performance more likely to be observed in firmswith a high level of geographic diversification.

The Effect of Country of Origin

According to prior research, a firm’s countryof origin, in particular whether they arefrom a Western or East Asian society, mayalso have a moderating effect on the rela-

tionship between age diversity and firmperformance when firms compete in anemerging economy such as China. Two pri-mary reasons create this moderating effect.First, in Western societies, an ongoingmovement toward diversity awareness hasoccurred since the 1980s, and Western gov-ernments have implemented policies ofequal opportunity for business organiza-tions that encourage age diversity. Influ-enced by this institutional process, many

We predict that

the relationship

between age

diversity and firm

performance is

moderated by

a strategy of

geographic market

diversification. The

positive effect of

age diversity is more

likely to be observed

given a high level of

diversification.


7/24



Western firms have managed age diversitymore effectively in their home countries andin their international operations (see, e.g.,Christian Science Monitor , 1993). For example,UNUM, a U.S. life insurance company, hashad a policy of diversity awareness in all of

its overseas offices and operations since the1990s (see, e.g., Center, 1996). Firms fromWestern societies generally have a greatercommitment to and more experience inmanaging age diversity, including maintain-ing the right balance of age diversity, thando firms in East Asian societies. This com-mitment and experience can moderate therelationship between age diversity, as mea-sured by the age diversity index (see Appen-dix A) and firm performance.

Second, East Asian societies are heavilyinfluenced by Confucian cultural values,which stress a family-style hierarchy of age.Research has shown that the firms in thesesocieties have more organizational institutionsthat are consistent with Confucianism thando firms from Western societies, given thefact that all these firms operate in China.This explains different firm strategies andpolicies (see, e.g., Li, Lam, & Qian, 2001). Ac-cording to Confucian institutions, the meritof years is always an important consideration

in reward and promotion systems in EastAsian organizations, and young people areoften discouraged from challenging olderpeople even when the latter is wrong. Thisinstitution has existed in Asian societies andorganizations for hundreds of years, andthere is no conclusive empirical evidence toshow that it has disappeared or changed sig-nificantly. Accordingly, we assume that thisinstitutional factor remains unchangedamong Asian firms. This factor prevents the

unique resources younger employees gener-ate from fully complementing and integratingwith those of older employees. As a result,the beneficial effect of age diversity on firmperformance may be less likely to be ob-served among East Asian firms than amongWestern firms. For these reasons, the follow-ing hypothesis is proposed:

Hypothesis 3: The relationship between age di-versity and firm performance is moderated by

country of origin, and a positive effect of age di-versity on firm performance will be more likely tobe observed among firms from Western societiesthan among those from East Asian societies.

Figure 1 illustrates our model. One can

see that we predict moderating effects of firmstrategy and home country institutions basedon the ongoing relationship between age di-versity and firm performance.

Method

Data and Sample

This study was conducted using data fromChina’s insurance industry. The main rea-son for selecting this industry is that it in-cludes the largest number of overseas firmsfrom both the West and the East, all ofwhich compete aggressively for marketshare. To test our hypotheses, we used paneldata and telephone survey data. In the sec-tion that follows, we discuss these two setsof data in detail.

Our data on the firms in China’s insur-ance industry were taken from a yearbookpublished by the Insurance Firm Associationof China, whose members include all the

major foreign and local insurance firms inthe country (N = 68 in 2006). Each of themember firms provides the same informationto this yearbook, including data about thedemography of their employees, sales fromeach geographic market in China, and finan-cial performance. An independent editorialboard consisting of representatives from thefirms and officials from China’s StatisticalBureau is responsible for the data’s validityand credibility.

The total number of observations was338 (firm/year). Because the number of in-surance firms has increased rapidly overthe years (e.g., from 2002–2007), our dataset did not constitute typical panel data. Inthe period 2002–2007, some new firmswere established every year, while some oldfirms were purchased or merged with otherfirms. As a result, the number of observa-tions and the sample firms observed eachyear could never be exactly the same.


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Specifically, the number of observationsfor each year was: N = 30 (2002); N = 49(2003); N = 58 (2004); N = 65 (2005); N =68 (2006); and N = 68 (2007). To processsuch semipanel data, we adopted an ap-proach used by other researchers (see, e.g.,Chari & Chang, 2009; Hutzschenreuter &Voll, 2008; Madhavan & Iriyama, 2009;Vermeulen & Barkema, 2001). A detaileddiscussion of this approach is providedlater in this section.

Among our sample firms (see Appendix

B), about half were from East Asian societ-ies; the remainder were from Westernsocieties. Since 1992 when the first foreigninsurer entered China, the Chinese govern-ment has granted many licenses to foreigninsurers to operate in the country. For ex-ample, in 1999, just before formally join-ing the World Trade Organization (WTO),China granted operating licenses to fouradditional foreign insurers (Wang, 1999).By 2006, there were more than 60 insur-

ance firms competing in the Chinese mar-ket.To confirm and check the data quality,

we visited the Web sites of each firm in oursample. If we found any inconsistency be-tween the Web site information and thepanel data for a given firm, we conductedtelephone investigations and talked to thecompany managers. Comparing the data inthis way showed the data to be highlyconsistent.

Measurement

Independent Variables

The strategy of geographic market diversifica-tion was measured by an entropy measure ofdiversification, the research method adoptedmost commonly (see, e.g., Hitt, Hoskisson, &Kim, 1997) as follows:

Entropy measure of market diversification

N Σ( pikln(1/ p

ik))

k

1where p

i k is the percentage of premiums

collected by firm i in the kth market (i.e., aChinese province or major city).

Age diversity was measured using the in-strument recommended by Teachman (1980),which has been widely adopted to study dif-ferent dimensions of demographic diversity,including age diversity. In this study,

H 1

i1Σ P

i(ln P

i)

where P is the proportion of a givenage group (e.g., under 25 or over 60) withinthe total number of employees. In oursample, each firm divided its employeesinto three age groups: under 25, 25–45,and over 45. Each firm reported the changesin their numbers annually. Age diversityfor this research was computed accordingto this information. According to the sim-ulation in Appendix A, when the

AgeDiversity

Firm Performance

1. Return on Assets (ROA)

2. Employee Productivity (Sales per

Employee)

Contextual Factors

1. The Strategy of Geographical

Market Diversification

2. Country of Origin

FIGURE 1. The Relationship Between Age Diversity and Firm Performance and Moderators


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proportions of the various age groups bal-anced, age diversity had the highest valueon the index.

To test the effect of this major indepen-dent variable on firm performance, we ad-opted two different testing approaches.

One was to use the diversity variable in agiven year to predict firm performances thenext year; the other used the diversity vari-able in a given year to predict firm perfor-mance in the same year. Because the resultsfrom these two tests were highly consis-tent, we only reported the results from theformer test in this article.

Finally, the firm’s country of origin wasmeasured by a dummy variable that took thevalue of 1 if the firm was a Western firm and0 if the firm was an East Asian firm. As noted,Western culture, including North Americaand West Europe, is considered individualist,whereas Eastern culture, including China, Japan, and Korea, is considered collectivist(see Hofstede, 1980). According to institu-tional theory, cultural difference should in-fluence the behavior of organizations from agiven region (Scott, 2001). We therefore con-sidered the firm’s country of origin becausebehavior may be influenced by the societalculture of the firm’s home country.

Dependent Variables

The major dependent variable tested wasfirm performance. To make our researchfindings fully comparable, we adopted themeasurements of performance that pastresearch has adopted. Relevant past re-search has adopted return on assets (ROA)and employee productivity as measures offirm performance (see, e.g., Richard, 2000);

thus, we also measured firm performancein terms of these two dimensions. Specifi-cally, ROA was measured by the ratio oftotal profit to total assets of each firm, andproductivity was measured by average salesgenerated by employees in a firm.

Control Variables

The study controlled for the effect of firmage because the relationship between firm

strategy and the dependent variables, such asfirm performance, could be moderated byhow long each firm has operated in China.The study also controlled for the effect oforganization size, which was measured as thelog number of employees in each firm for a

given year. This control variablewas included because larger firmsmight have more resources thansmaller firms, which could mod-erate the relationship betweenfirm strategy and the dependentvariables. When testing the mod-erating effect of geographic diver-sification, the effect of country oforigin was controlled; similarly,when testing the moderating ef-fect of country of origin, theeffect of geographic market diver-sification was controlled.

Finally, because of the charac-ter of our data, we controlled forthe time effects by including yeardummies in the regression, an ap-proach adopted by many authorsto handle this kind of data(e.g., Chari & Chang, 2009;Hutzschenreuter & Voll, 2008;Madhavan & Iriyama, 2009; Ver-

meulen & Barkema, 2001). Spe-cifically, each firm was assigned ayear dummy variable: 1 = 2003, 2= 2004, 3 = 2005, 4 = 2006, and 5= 2007, leaving 2002 as the refer-ence year. In addition, each firmwas given a number, and this in-formation was also entered intothe data analyses to control theeffect of observations from thesame firm over the years.

Data Analysis and Results

Table I shows descriptive statistics for thedata, which suggest interesting correlationsamong some of the variables. For example,there is a significant and positive correlationbetween country of origin and firm size,which suggests that Asian firms, whichmainly consist of local Chinese firms,are generally larger than foreign firms

Finally, the firm’s

country of origin

was measured by

a dummy variable

that took the value

of 1 if the firm was

a Western firm and

0 if the firm was

an East Asian firm.

As noted, Western

culture, including

North America

and West Europe,

is considered

individualist,

whereas Eastern

culture, including

China, Japan, and

Korea, is considered

collectivist.


10/24



operating in China. Consistent with thisfinding, there was a significant and posi-tive correlation between firm size and agediversity, which indicates that larger firmshave a higher level of age diversity than dosmaller firms.

The mean for age diversity was only 0.53,far lower than was the case for the balancedgroup (see Case 1, Appendix A). This can beexplained, however, by actual age diversityamong the sample firms. Upon checking thedata, we found that many firms had a verysmall proportion of older employees (below10%), while some firms had no employees inthis category at all. When some age groupsconstitute a very small proportion of theworkforce or are missing altogether, the Hindex is very small (see Cases 2 and 3, Appen-dix A). As a result, the mean value for thevariable becomes low, which suggests thatthe age groups in some of our sample firmswere far from balanced.

Hierarchical regression analysis wasthen conducted on the data to test the hy-potheses. The reason we selected this ap-proach was its power to test the relation-ship among dependent and independentvariables and its efficiency in making fulluse of data. Hierarchical regression analysis

was adopted in studies on similar topics,later published in top-tier journals (see,e.g., Li, Lam, Sun, & Liu, 2008; Richard,2000). We first tested the moderating effectof market diversification on the relation-ship between age diversity and ROA byadopting the same approach used in previ-ous research (see, e.g., Richard, 2000), such

that the results would be comparable.Specifically, the data of firm performanceone year later (in this case, firm profitabil-ity [ROA] one year later) was first enteredas a dependent variable (e.g., if the yearwas 2006, the ROA from 2007 was thus en-

tered), then the year dummies were entered(Model 0). Thereafter, the four control vari-ables—firm number, firm size, country of origin, and firm age were entered (Model 1). Age diversity was entered next (Model 2),then strategy of diversification (Model 3) wasadded, and finally the interaction betweenage diversity and the strategy of diversifica-tion was considered (Model 4). The interac-tion term was computed with the standard-ized data.

Table II displays the findings, which gen-erally support the hypotheses. Specifically,Hypothesis 1 is supported by the resultgenerated in Step 2 (see the S- column inTable II where the values of standardized betawere presented), which showed a significantand positive effect of age diversity on ROA.Hypothesis 2 is supported by the resultsobtained in Steps 3 and 4, in which the effectof firm strategy is found to be significant andthe interaction between age diversity andstrategy is found to have a significant effect

on ROA.To interpret this interaction, we plotted the

interaction term (see Part A, Figure 2). As Figure2 suggests, only at a high level of the moderator(i.e., diversification) do we observe a significantand positive relationship between age diversityand firm performance. Moreover, the variableof firm age has a significant and positive effect

T A B L E I Descriptive Statistics

Variable M SD 1 2 3 4 5 6 7

1 Firm Age 2003.26 1.36 1

2 Country of Origin 0.49 0.50 0.09 1

3 Firm Size 6.19 2.19 0.05 0.51** 1

4 Age Diversity 0.53 0.33 0.11 0.31** 0.5** 1

5 Market Diversification 0.99 1.21 0.02 0.67** 0.91*** 0.45*** 1

6 Return on Assets 0.01 0.24 0.13* 0.08 0.07 0.40** 0.17* 1

7 Sales per employee

(million RMB)

1.22 2.39 0.11 0.09 0.07 0.04 0.37** 0.05 1

*p


11/24



on ROA, which suggests that operatingexperience among the firms, which shouldhave a positive relationship to firm age inChina’s insurance industry, has a positive rela-tionship to firm performance.

Using a similar approach, we also tested

the moderating effect of firm strategy onthe relationship between age diversity andemployee productivity, which was another

dimension of firm performance tested inthis study. Table III shows the results ofthese analyses, from which it can be seenthat age diversity alone has no significanteffect on productivity (Step 2). When firmstrategy is entered, the regression model

improves significantly (Step 3); indeed,firm strategy has a significant and positiveeffect on productivity. The entry of the

T A B L E I I Age Diversity and Performance (ROA)

ROA (N = 337)

Standardized SE

Step 0 R 2 0.004

Control (Firm Age)

2002 47.882 0.152 90.965

2003 45.924 0.170 90.775 2004 48.466 0.182 90.445

2005 47.856 0.266 90.832

2006 60.396 0.265 90.489

Step 1 R 2 0.249**

Control

Firm Number 0.365 0.043 0.421

Firm Size 4.231 0.087 2.430

Firm Age 3.014 0.687* 0.249

Country of Origin 0.009 -0.000 0.371

Step 2 R 2 0.053*

Main Effect

Age Diversity 25.687 0.246* 4.507

Step 3 R 2 0.045*

Moderator

Market Diversification 18.883 0.215* 4.05

Step 4 R 2 0.106**

Interaction

Age Diversity Market Diversification 52.247 0.381** 0.023

Model F 3.323*

Constant 21.315 18.562

Adjusted R 2 0.289

Notes: ROA Return on assets.

*p < .05; **p < .01; ***p < .001.


12/24



interaction term in Step 4, however, fails toimprove the model, and the effect of theinteraction remains insignificant. The com-bined results from all the steps indicatethat age diversity has no significant effecton productivity. Instead, it is market diver-sification that explains the difference inemployee productivity among the firmsstudied.

We next further considered the effect ofcountry of origin. We started by dividing the

sample into two parts based on the firms’country of origin: Western firms and firmsfrom East Asian societies. The same regres-sion analyses as discussed above were con-ducted on each subsample to test the effect ofgeographic diversification on the relation-ship between symbiotic resources and firmproductivity using similar approaches tothose discussed above.

Table IV shows the results of the dataanalyses on the firms from Western

societies. Consistent with the results inTable II, the data suggest a significant andpositive effect of age diversity on firm per-formance. Moreover, the data also suggesta significant and positive interaction effectbetween age diversity and firm market di-versification on firm profitability. Again,we plotted the interaction to help under-stand the effect of the moderator (see PartB, Figure 2).

Table V shows the results of the data

analyses on firms from East Asian societies.Distinct from the results in Table IV, thedata in this table suggest no significanteffect of age diversity on firm performance.Even the regression models are notsignificant.

Using the findings in Tables IV and V,we tested the moderating effects of countryof origin on the relationship between agediversity and firm profitability. In the re-gression analyses, we first entered the two

-0.1

0.0

0.1

0.2

-0.1

0.0

0.1

0.2

low high

low high

A

B

FIGURE 2. Interaction Between Age Diversity and Market Diversification. (A) Interaction Term as Presentedin Table II. (B) Interaction Term as Presented in Table IV. (_ _ _ _ indicates low level of the moderator; that is,the diversification; _____ indicates high level of the moderator; that is, the diversification)


13/24



sets of control variables. The geographicmarket diversification of the firms was en-tered as a control variable. The interactionbetween country of origin and age diver-sity was entered at the final stage of thehierarchical regression analyses. Table VIshows the results of these data analyses,which again suggest a significant and posi-tive effect of age diversity on firm perfor-

mance. Moreover, the data also indicate asignificant and positive interactive effectfor age diversity and country of origin onfirm profitability. Hypothesis 3 is thus sup-ported.

Finally, to understand the effect of con-textual variables such as firm strategy fur-ther, an additional two sets of hierarchicalregression analyses were conducted. In

T A B L E I I I Age Diversity and Performance (Productivity)

Sales per Employee (N = 337)

Standardized SE

Step 0 R 2 0.004

Control (Firm Age)

2002 7.096 0.042 2.665 2003 7.435 0.049 6.452

2004 7.351 0.051 5.923

2005 6.432 0.047 6.211

2006 6.687 0.061 5.071

Step 1 R 2 0.255**

Control

Firm Number 0.093 0.023 0.168

Firm Size 65.981 0.735** 3.017

Firm Age 2.998 0.278* 0.310

Country of Origin 28.034 0.255* 4.621

Step 2 R 2 0.071*

Main Effect

Age Diversity 10.711 0.081 6.507

Step 3 R 2 0.045*

Moderator


Step 4 R 2 0.081**

Interaction

Age Diversity Market Diversification 16.890 0.195 9.116

Model F 17.034**

Constant 8.012 17.098

Adjusted R 2 0.299

*p < .05; **p < .01; ***p < .001.


14/24



Analysis A, firm profitability (ROA) wasentered first as the dependent variable, fol-lowed by the control variables (Model 0,1), and finally age diversity (Model 2). InAnalysis B, ROA was again entered first asthe dependent variable, followed by thesame control variables (Model 0,1), the

strategy of diversification (Model 2), andfinally age diversity (Model 3).Table VII shows the results of these two

sets of analyses. In Part A, the effect of agediversity is tested without the firm strategyof diversification taken into account. Theseresults show age diversity has no signifi-cant effect on firm performance. Even the F -values of the regression models are insig-nificant. Part B of Table VII shows thatwhen firm strategy is entered, the regression

model improves significantly, and age di-versity has a significant and positive effecton return on assets (ROA).

In summary, the results from this studyshow that contextual variables such as firmstrategy have a significant effect on thetwo dimensions of firm performance. In

testing the relationship between age diver-sity and firm performance, the results showthat age diversity makes a significant dif-ference whether or not a contextual vari-able, such as firm strategy, is considered. Asthe data in Table VII suggest, when firmstrategy is entered, the regression modelchanges from insignificant to significant;only when firm strategy is included canone observe a significant effect of agediversity on firm performance.

T A B L E I V Age Diversity and Performance (Western Firms)

Return on Assets (N = 113)

Standardized SE

Step 1 R 2 0.153*

Control

Firm Number 0.034 0.012 0.019 Firm Size 0.301 0.377* 0.238

Firm Age 0.062 0.076 0.065

Step 2 R 2 0.282*

Main Effect

Age Diversity 1.213 0.368* 0.420

Step 3 R 2 0.244*

Moderator


Step 4 R 2 0.301*

Interaction

Age Diversity Market Diversification 1.129 0.189* 1.600

Model F 4.199*

Constant 29.987 26.721

Adjusted R 2 0.201

*p < .05; **p < .01; ***p < .001.


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Discussion and Implications

The foregoing analyses highlight the im-portance of considering specific contextualfactors when studying the relationshipbetween demographic diversity and firmperformance. By analyzing the data gath-ered from firms competing in China’s in-surance industry, this study identifies three

ways in which the contextual factor of firmstrategy can influence the relationship be-tween workforce composition and firmperformance.

First, entering a contextual factorchanges the regression model from insig-nificant to significant (see Table VII). Sec-ond, including such a factor in the regres-sion model changes the standardized beta(in this case the effect of age diversity)from insignificant to significant (see Tables

II and VII). Third, the contextual factormay also interact with a given dimensionof demographic diversity. In this study, theinteraction between age diversity and firmstrategy for geographic market diversifica-tion has a significant and positive effect onfirm performance (see Table II).

These findings are consistent with otherstudies, such as those obtained by Richard

(2000) in testing the effect of a growthstrategy on the relationship between racialdiversity and firm performance. Together,these findings show that contextual vari-ables, such as firm strategy, can moderatethe relationship between certain dimen-sions of demographic diversity, on the onehand, and dimensions of firm performanceon the other. Moreover, such factors canalso influence certain dimensions of firmperformance directly, even when a given

T A B L E V Age Diversity and Performance (East Asian Firms)


Standardized SE

Step 1 R 2 0.009

Control

Firm Age 0.034 0.120 0.019 Firm Size 5.810 0.067 4.079

Firm Age 1.007 0.105 0.417

Step 2 R 2 0.018

Main Effect

Age Diversity 12.054 -0.078 10.213

Step 3 R 2 0.071

Moderator


Step 4 R 2 0.029

Interaction

Age Diversity Market Diversification 23.932 0.242 14.995

Model F 0.199

Constant 79.555 68.236

Adjusted R 2 0.009

*p < .05; **p < .01; ***p < .001.


16/24



dimension of organizational demography,such as age diversity, has no significanteffect (see Table III).

The data also show that a given dimen-sion of organizational demography, such asage diversity, may influence only certain

dimensions of firm performance and haveno effect on others. Specifically, the data sug-gest that age diversity does not affect dimen-sions of performance equally. For example,although age diversity may improve firmprofitability, it has no effect on sales peremployee (i.e., labor productivity). The ex-planation for this result seems to be thatproductivity is more independent than prof-itability for the quality of human resources

in a firm. If an insurance firm is determinedto increase its sales, for example, then it cansimply cut the prices of its policies, even ifthis cut may affect its short-term profits. In-creasing profitability, however, may be muchmore difficult, especially if the firm lacks

unique and difficult-to-copy human re-sources that confer a competitive advantage.This is especially true of firms that adopt astrategy of market diversification, whichmay put an emphasis only on sales growth innew markets. Given this strategy, it is possi-ble that only firms that manage their humanresources well, including maintaining theright balance of age diversity, can achieve ahigh level of profitability.

T A B L E V I The Moderating Effect of Country of Origin on the Relationship Between Age Diversity andPerformance (ROA)


Standardized SE

Step 1 R 2 0.052*

Control Firm Name 0.465 0.033 0.378

Firm Size 65.981 0.634*** 0.009

Firm Age 2.988 0.317** 0.267

Diversification 28.034 0.156* 4.631

Step 2 R 2 0.044*

Main Effect

Age Diversity 15.670 0.086* 2.087

Step 3 R 2 0.057*

Moderator

Country of Origin 27.976 0.156* 4.604

Step 4 R 2 0.064*

Interaction

Age Diversity Country of Origin 53.532 0.234** 14.604

Model F 3.421*

Constant 24.111 20.147

Adjusted R 2 0.209

Notes : ROA = Return on assets

*p < .05; **p < .01; ***p < .001.


17/24



The results from this study also show asignificant moderating effect of country oforigin on the relationship between age diver-

sity and firm performance. This findingsuggests a new issue for further study of de-mographic diversity and its effect on firm

T A B L E V I I Regressions With and Without Firm Strategy

(A) Without Firm Strategy


Model 1 Model 2

Standardized Standardized

Control VariablesFirm Number 0.043 0.042

Firm Size 0.634*** 0.619***

Firm Age 0.267* 0.249*

Country of Origin 0.156** 0.156**

Independent Variable

Age Diversity 0.046

Overall Model F 150.466 138.115

Multiple R 0.868 0.869

R 2 0.753 0.755

Adjusted R 2 0.743 0.750

Standard Error 45.016 44.863

(B) Without Firm Strategy


Model 1 Model 2 Model 3

Standardized Standardized Standardized

Control Variables

Firm Number 0.051 0.043 0.044

Firm Size 0.634*** 0.594*** 0.585***

Firm Age 0.267** 0.239** 0.226**

Country of Origin 0.156* 0.151* 0.173**

Independent Variables

Market Diversification 0.130* 0.128*

Age Diversity 0.089*

Overall Model F 150.466*** 143.826*** 132.476***

Multiple R 2 0.868 0.873 0.874

R 2 0.753 0.763 0.764

Adjusted R 2 0.748 0.757 0.758

Standard Error 45.016 44.179 44.108

*p < .05; **p < .01; ***p < .001.


18/24



performance, namely, the effect of firmcommitment to adequately managingdemographic diversity or diversity awareness.As the data in Tables IV, V, and VI suggest, theeffect of age diversity on performance forfirms from Western societies is much stronger.

These results can be explained by assumingthat diversity awareness is higher in Westernsocieties than in East Asian societies. As dis-cussed, evidence suggests that firms from agiven country or region may have a higher orlower degree of diversity awareness due tothe influence of the country or region’s insti-tutional environment, including governmentpolicies and the societal value placed ondemographic diversity. According to thisargument, firms from the West are likely tohave a higher level of diversity awarenessthan are those from East Asia.

Additional evidence supports this con-tention. For example, for the past 50 years,scholars in the West have been makinggreat efforts to study the issue of demo-graphic diversity (see Williams & O’Reilly,1998, for a review of this tradition), andmany Western firms have made similar ef-forts to improve diversity awareness, in-cluding age diversity (see, e.g., Wagner,2007, and Wong, 2008, for recent exam-

ples). Yet the same is not true in Easternsocieties. Such developments inthe West are likely to lead to institutionalchanges or differences in social institutionsbetween the West and the East regardingdiversity awareness. If this assumption iscorrect, then the findings from this studysuggest that to understand the effects ofdemographic diversity on firm perfor-mance, one should not merely considerdemographic proportions or the value of a

certain diversity index. Instead, it is thefirms’ commitment and effort to maintainthe right balance of age diversity and im-prove diversity awareness that can make adifference in the relationship between thediversity index and firm performance. Moreempirical evidence related to this issuewould be useful for both academic re-searchers and practitioners.

Our results also have other implicationsfor empirical studies across organizations,

such as the diversity of top managementteams or ethnic diversity across firms. Insuch cases, it is more appropriate to con-sider the effects of organizational demogra-phy, together with contextual variablessuch as firm strategy, because firm perfor-

mance can be influenced by both firmstrategy and certain dimensions of organi-zational demography, as the data from thisstudy indicate. Because of the direct andindirect effects of contextual factors, suchas firm strategy on firm performance, re-searchers should avoid attributing firmperformance only to certain parts or di-mensions of organizational demography,such as the diversity of the top manage-ment or ethnic diversity, which are oftenmeasured by diversity indexes.

Implications for Practitioners

Practitioners may also find it useful tolearn more about the relationship amongfirm strategy, age diversity, and firm perfor-mance. Consistent with the results of pre-vious research, this study’s findings suggestthat demographic diversity, of which agediversity is a part, may provide a firm withbetter or more diverse resources with which

to meet the demands of geographic marketdiversification, which in turn improvesfirm profitability. This finding is very rele-vant to certain overseas firms, particularly Japanese firms that discriminate againstolder employees when operating in emerg-ing economies (Li et al., 2008). Althoughgovernments in emerging economies nor-mally pay little attention to the issue of agediscrimination, employing only youngpeople may not be in the best interests of

firms because, as the data here suggest, agediversity can actually have a positive effecton profitability, at least in the finance andinsurance industries.

The data also highlight the importanceof diversity awareness for improving firmperformance. As suggested, age diversityawareness both allows older employees tocontribute and gives full play to the initiativeand creativity of young people. This combi-nation is more likely to lead to better overall


19/24



firm performance, as is the case with Westerninsurance firms in China. Without thisawareness, however, age diversity may nothave a significant and positive effect on firmperformance, as the data in Table V suggest.

Because certain contextual variables,

such as firm strategy, do moderate the rela-tionship between a given dimension ofdemographic diversity and firm perfor-mance, firm management should considerthis moderating effect when implementingcertain strategies. For example, when as-sessing the pros and cons of a given strat-egy, management should take into accountthe possible short-term and long-term ef-fects of that strategy on the relationshipbetween demographic diversity and firmperformance. With such an understanding,managers will develop better human re-source management policies that maintainthe right balance of demographic diversityand improve firm performance in thefuture.

Limitations

Finally, some findings from this studyshould be interpreted with caution becausethey reflect a specific industry in a specific

country, namely, the insurance industry inChina. In China, the insurance industrywas previously underdeveloped with only afew firms operating with a very small num-ber of professional employees. After Chinaopened its insurance markets in the 1990s,more than 70 new insurance firms, manyoverseas-funded, were established. All thesefirms needed experienced local profession-als with local experience and an under-standing of the market environment. As a

result, experienced local professionals,many of whom had reached middle or oldage, suddenly became a rare resource andone difficult to replicate. This situationmay have been distinct from that in thedeveloped countries where older insuranceprofessionals might be easier to source. Be-cause of this industry characteristic inChina, however, one should avoid overlygeneralizing the findings from this researchto other areas or settings, such as other

industries in Western societies. Because nodata was gathered to allow a comparisonwith other industries or other countries,the external validity of the find-ings here remain somewhat un-clear. Future studies, and espe-

cially studies using cross-nationalempirical data, will be necessaryto address this issue.

For firms competing inemerging economies, the lack ofexperienced local professionalswill be a persistent difficulty inthe coming decades. Because ofthis difficulty, in fast-growingoverseas markets, firms that canmore easily attract older andmore experienced professionalsto their workforces will hold acompetitive edge over their ri-vals. In this sense, the findingsfrom this study will still be rele-vant and particularly interestingfor future studies.

In conclusion, this studysuggests that age diversity andits management are likely tobecome increasingly importantin countries throughout the

world. In the presence of certaincontextual factors or under cer-tain conditions, such as whenfirms adopt a certain strategy orcompete in industries with cer-tain characteristics, age diver-sity can improve performance,including financial perfor-mance. Future studies shouldmake further efforts to identifythe precise contextual factors

relevant to the effect of age di-versity and test the influence ofthese factors on the ongoing re-lationship between age diversityand firm performance. The find-ings from this research enrichthe theory of organizationaldiversity and provide usefulknowledge for firm managers toimprove the quality of humanresource management.

In the presence of

certain contextual

factors or under

certain conditions,

such as when firms

adopt a certain

strategy or compete

in industries

with certain

characteristics, age

diversity can improve

performance,

including financial

performance. Future

studies should make

further efforts to

identify the precise

contextual factors

relevant to the effect

of age diversity and

test the influence

of these factors

on the ongoing

relationship between

age diversity and firm

performance.


20/24



JI LI is a professor of Management in the School of Business Administration in Hong

Kong Baptist University. He obtained his Ph.D. from the Rotman’s School of Management

at the University of Toronto. His research areas include international HRM and strategy.

CHRIS W. L. CHU is an doctoral candidate at Aston University. He is currently working in

the China Economic Research Center at the Stockholm School of Economics. His research

interests include work-family interface, employee-organization relationship, strategic hu-man resource management, and organizational behavior issues in China.

KEVIN C. K. LAM is an associate professor in the Faculty of Business Administration in

the Chinese University of Hong Kong. He obtained his Ph.D. from the Rotman’s School

of Management at the University of Toronto. His research areas include international

management, finance, and accounting.

STACY LIAO is an HR manager at China State Construction International Holdings Ltd.

She received her M.Phil. in the Department of Management from the Hong Kong Baptist

University and B.Phil. in the Department of Philosophy from Renmin University of China.

Her research covers strategic management and human resources management.

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A P P E N D I X A Simulation Using the Diversity Index Recommended by Teachman (1980)

Assuming that an organization has four age groups—under 25; 26–35; 36–50; and over50—we considered the proportion of those aged 36–50 in three cases: (1) when the propor-tion is at a “balanced” level, (2) when the proportion is very small or at a “token” level, and(3) when the proportion is very large so that the age group is overrepresented in the orga-

nization. By applying the diversity index formula

H 1

i1Σ P

i(ln P

i)

we obtain the following results.

1) Balanced Proportion

Lnp plnp*1 H Sum of plnp* 1

Over 50 0.25 1.38629 0.346574

36–50 0.25 1.38629 0.346574

26–35 0.25 1.38629 0.346574

Under 25 0.25 1.38629 0.346574

Diversity H1.386294

2) Small Proportion


Over 50 0.01 4.60517 0.046052

36–50 0.01 4.60517 0.046052

26–35 0.97 0.03046 0.029545

Under 25 0.01 4.60517 0.046052

Diversity H0.167701

3) Large Proportion


Over 50 0.00 0 0

36–50 0.98 4.60517 0.046052

26–35 0.01 0.0202 0.019799

Under 25 0.01 4.60517 0.046052

Diversity H0.111902

As a result of this simulation, one can see that when the proportions of employee agegroups are at a “balanced” level, the diversity index reaches almost the highest level. In

contrast, when a given group, such as the 36–50 group, has a very small or very large pro-portion, the index is at its lowest.


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A P P E N D I X B Firms Sampled

Company Foreign Country Involved License

AIA U.S. Shanghai, 1992

Manulife Sinochem Canada Shanghai, 1996

China Pacific-Aetna U.S. Shanghai, 1997Allianz Dazhong Germany Shanghai, 1998

AXA-minmetal France Shanghai, 1999

China Life Colonial Mutual Australia Shanghai, 2000

John Hancock - Tian An U.S. Shanghai, 2001

Prudential CITIC U.K. Guangzhou, 2000

Sun Life Financial Everbright Canada Tianjin, 2002

The Ming An Insurance Co. (China) Ltd. Hong Kong Shenzhen, 1982

Yokio Marine Nichido China Japan Shanghai, 1994

Mitsui Sumitomo Insurance (China) Co. Ltd. Japan Shanghai, 2001

Samsung Fire & Marine Insurance Korea Shanghai, 2001

age diversity 2011

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