The Effects of Human and Social Capital on the Development
Process of Industrial Clusters: The Case of Wooden Furniture
Cluster in Sri Lanka
H.M.Nihal Padmasiri
PhD Candidate atAichi Gakuin University

Abstract
This paper investigates how human and social capitalassists for the development of clustered and non - clusteredfirms in wooden furniture industry in Sri Lanka. The study
resulted three major findings; the most experienced andeducated entrepreneurs played important role to secure theirmarket through introducing brand name for the product; humancapital acquired through formal education and experience ishighly significant on the performances of clustered firms
than that of non - clustered firms; and irrespective ofclustered or non - clustered, performance of the firms inwooden furniture industry in Sri Lanka are significantly
relying on social capital.
1. Introduction
Many researchers and academics have realized andemphasized that accelerated industrial growth has been
crucial in reducing poverty and unemployment in developing
countries (Schumpeter 1939, Yamamura 2009, Sonobe and Otsuka
2006). Since high productivity growth considered as the basisof rising per capita income, the low income countries canonly achieve it through industrialization.
Within industrial development strategies, industrial1

clusters have earned steady position in the literature andit has a long history. Industrial clustering reduces the costin a business owing to proximity of transaction parties. Morespecifically, as additional firms locate in the samegeographic area, the lower cost of production can be achieved
through rivalry suppliers, supporting firms, and specializedlabor force. Furthermore, the greater the number of firms
located in an area, the greater the overall market to whicha business can sell its goods or services.
In the process of the development of industrial clusters
the important role played by human capital has been emphasizedin the literature by many (Yamamura, 2009, Schultz, 1961,
Padmasiri, 2011).Factors such as formal education andparticipation in ongoing training related to the workplace
help to enhance the human capital.
The concept of social capital can be defined as“features of social organization, such as trust, norms, andnetworks that can improve the efficiency of society” (Putnamet al., 1993).
This paper sees how these concepts assist for thedevelopment of business firms by studying wooden furnitureindustry in Sri Lnaka. Succinctly this study sees how humanand social capital assist in the success of businessorganization within a clustered and how it affects theperformance of non - clustered firms.

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2. Wooden Furniture Industry in Sri Lanka
Wooden furniture industry is one of the key and oldest
industries in Sri Lanka. There are over 9000 furniture andother wood working industrial plants are operating in thecountry.

Themajorityofwoodenfurniturefirms

areconcentrated around “Moratuwa” town which is popular
everywhere in the country as traditional city of carpentry.
3. Hypothesis
H1: Highly educated and experienced firm managers of clustered and non- clustered wooden furniture firms tend to use brand names for theproducts to secure their own marketing channel.
H2: The formal education of the managers of wooden furniture industry
is highly significant on their performance, in clustered firms thanin non - clustered firms.
H3: In wooden furniture, clustered firms and non - clustered firms socialcapital (measured by membership of business association and trust)significantly contribute to the business performance.

4. Method and Data Analysis
Both cross sectional and time series data of 96 active
firms related to the wooden furniture industry in Sri Lanka
is used in this study. The data set contains the information
on managers’ education, experience, social relationship andsome other basic information in addition to the annual sales,
cost of production, marketing in 2000, 2002, 2004, 2006, and2008.

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Regression Model 1
Brand Name= β0 + β1(HC)it + β2(Trust)it + β3(EXP)it +β4(Asso.Mem)it++β5(V.Training)it+β6(Asso.Mem *Trust)it +β7(EXP * Trust)it +ui,
Where; ui = error term, which captures the impact of all
the unobserved factors.

Regression Model 2Ln(Value added revenue)it =β0 + β1(HC)it + β2(Trust)it + β3(EXP)it+β4(Asso.Mem)it++β5(V.Training)it+β6(HC*EXP)it+β7(Asso.Mem *Trust)it +β8(EXP * Trust)it +ci+ uit,
Where; ci = unobserved component or random effectuit = error term, which captures the impact of all theunobserved factors.

To test Hypothesis 1 (H1), a regression model 1 was used.
Because brand name is a binary dependent variable (=1 if firm
has a brand name, = 0 otherwise), the probit regression model
was applied.
Since this study also indicates that there is no
significant difference between fixed and random effectresults (Hausman test), random effects model was used to test
hypotheses 2 and 3.
5. Estimation of Result and Discussion
In the regression, the number of years of schooling of
the managers and their operational experience within theirown business has a positive and highly significant effecton the introduction of a brand name for the products in both4

types of wooden furniture firms. These two independent
variables are statistically significant at 1% significancelevel. Also experience gained by working as managers in thefirms in the industry is also significant at the 1%
significance level. This result supports hypothesis 1 andis consistent with extant literature.
According to these results, formal education and prior
work

experienceasmanagers

aresignificant

at1%

significance level in the case of clustered wooden furniturefirms. However, in non - clustered wooden furniture firms
formal education significant only at 5% level indicating thatthe human capital contributes more to the clustered firms
than that of non - clustered firms in wooden furnitureindustry in Sri Lanka. These results support the second
hypothesis. In order to capture the social capital for theanalysis the study has used four independent variables
including two multiplicative variables. Among them thenumber of years of operation (trust) is the most importantvariable to capture the social support for the success ofany business. According to the analysis, this particularvariable is significant at 1% level in both the clusteredand non - clustered cases. In addition, the multiplicative
variable of “EXP it * Trust it” is also significant at 5% levelin both cases.

5Regression Results
Cluster

Non Cluster
Ln Value Added

Independent

Ln Value Added

Brand Name

Brand Name
(RandomVariables(Random EffectDummy (Probit

Dummy (Probit
Effectestimates)

estimates)

estimates)
estimates).11(.043)***.35(.06)***.084(.048) **.36(.061)***Years of Operation).052(.013)***.14(.05)***.044(.013)***.11(.04) ***Years of.059 (.009)***.13(.03)***.10(.025)***.12(.031) ***.019( .010)**-.01(.05).012(.011).010(.04).19(.21).33(.70).067(.22)-.056(.62)-.016(.24).99(.36)***.0009(.0003)**.007(.001)***.001(.0004)**-.006(.001)***-.46(.72)-6.68(1.24)***13.86(.68)-6.2(1.1)***Years of SchoolingExperience(EXP)
Asso.Mem *Trust
AssociationV.Ttraining

1.05(.36)***

EXP* Trust
Constant

216

Sample Size

216

211

208

Notes: Numbers in parentheses are standard errors. The symbols *** and** indicate
statistical significances at the 1 and 5 percent levels respectively.

6. Conclusion
The arguments made by the author in this paper are
clearly supported by empirical evidence. Even though thesocial capital is very difficult to measure, the author usedsocial trust as a proxy and able to reveal that the social
trust is one of the key factors that contribute positively
in the success of business. Within the broader industrial
developmentprocesshumanandsocialcapitalcanbe

considered as key production factors that influences to thefirm performance.

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