Consumer Ethnocentrism and Product Preferences- Indonesian Evidence

Consumer Ethnocentrism and Product Preferences: Indonesian Evidence

Hamin

Christian University of Duta Wacana, Indonesia

[email protected]

Greg Elliott

Macquarie Graduate School of Management, Macquarie University

[email protected]

Stream D (International Management); Stream Z (Other- Marketing Management)


Abstract

This paper examines the concept of “consumer ethnocentrism” (CE hereafter) and its impact on

product evaluation and preferences among Indonesian consumers. Results of a sample survey of

Indonesian consumers and discussed. Results are discussed which, firstly, show the overall level

of CE of Indonesian consumers compared with published results for a range of countries. In this

context, the level of CE for Indonesian consumers is especially high. Secondly, results of

conjoint analysis showing the relationship between CE and consumer evaluations of “Country of

Origin”, product quality perceptions and purchase intentions, for both tangible goods and

intangible services, are discussed.


Country of Origin Effects

From its birth in the 1960’s (Schooler, 1965), the country of origin effect has become probably

the most extensively researched topic in international marketing. By now, the existence of

measurable country of origin effects is widely accepted within international marketing research

and literature. Samiee (1994) defined the country stereotyping effect or country-of-origin (COO

hereafter) effects as any influence, positive or negative, that the country-of-manufacture might

have on the consumer's choice processes or subsequent behaviour. It may be created from

consumer experience when they are visiting the country, knowledge regarding the country,

political beliefs, or more general ethnocentric tendencies. It (the COO effect) is generally

understood to stand for the impact that generalisations and perceptions about a country have on a

person's evaluations of the country's products and/or brands (Nebenzahl et al. 1997 p. 28). The

generalisation of beliefs and perceptions about specific products from a country on a set of

attributes is known as country image (Bilkey and Nes, 1982). The image of countries as the

origin of products is one of the extrinsic cues that may become part of a product's total image.

This image is known variously as the 'country-of-origin' or 'made-in' phenomenon, issue, effect,

or cue in different literature. As a potential surrogate indicator, country-of-origin can be used to

stereotype products or countries.

The focus of the vast bulk of the extant country of origin research hitherto has been from the

perspective of More Developed Countries, (MDC’s hereafter) notably U.S. and Europe. The

common finding of these studies is that consumers rate products produced in their own country,

or in MDC’s, more highly than those produced in foreign and/or less developed countries

(LDC’s hereafter) (Samiee, 1994; Bilkey and Nes, 1982). From the perspective of consumers

from LDC’s, the evidence suggests that consumers from countries such as Mexico (Bailey et al.,

1997; Almonte et al., 1995), Philippines (Hulland et al., 1996), Jordan (Hussein, 1997) and

Nigeria (Okechuku and Onyemah, 1999) have been shown to evaluate imported product from

MDC’s more favourably than domestically-made products.

Consumer Ethnocentrism

Beyond the generalized preference for products manufactured in MDC’s, there is also evidence

that, regardless of their country of origin, and out of a sense of loyalty or patriotism, or because

of the perceived superiority of the home country, some consumers, particularly those from

MDC’s, will always prefer to purchase products manufactured in their home country. This

generalized preference has been referred to as “consumer ethnocentrism” (Shimp and Sharma,

1987). Shimp and Sharma (1987) found that some consumers generally believe that buying

products that are locally manufactured is morally appropriate in a normative sense. This

expression of consumer ethnocentrism can serve as an essential stimulus for the decision to

purchase domestic or local products.

There is thus growing evidence for the view that it is necessary for LDC’s to be more aware of

the issues of country-of-origin and the related concept of consumer ethnocentrism. When

considering the combined effects of country-of-origin and consumer ethnocentrism, a number of

possibilities arise. For consumers from MDC’s, it seems likely that the country-of-origin effect

and consumer ethnocentrism will both lead them to a preference for their domestically-made

products. For consumers from LDC’s however, the weight of previous research on the COO

effect and consumer ethnocentrism point to contrary expectations. The COO effect will typically

lead to a preference for foreign-made products from MDC’s. In contrast, consumer

ethnocentrism points to a preference for locally-made products. Thus, for consumers from

LDC’s, the COO effect and consumer ethnocentrism provide mixed signals and, thus, consumer

preferences and choices seem likely to be more difficult to predict. The resolution of these

competing imperatives is thus a focal question of the current study.

The Current Study

Against this background, the current study was designed to investigate the effects of country-of-

origin and consumer ethnocentrism on consumers’ perceptions of quality, price and value and,

ultimately, the consumers’ choice of tangible goods or intangible services from the perspective

of consumers in an LDC such as Indonesia.

Using the Consumer Ethnocentric Tendency Scale (CETSCALE) measurement (Shimp and

Sharma, 1987), this study will indicate the degree of ethnocentric sentiment among Indonesian

consumers. Shimp and Sharma (1987) devised the CETSCALE instrument and conducted a

series of nomological validity tests of consumer ethnocentrism in the USA. They found that

CETSCALE is predictive of consumers' beliefs, attitudes, purchase intentions, and consumer

choice. They suggested that the higher consumers were on their scale, the more likely they would

be to choose the domestic product and the less likely they would be to choose foreign-made

products. Conversely, later research (Acharya and Elliott, 2003) has demonstrated that

consumers with a low ethnocentrism score are more likely to prefer foreign-made products.

Hence, it is of further relevance to the study of consumer ethnocentrism to look at country image

and the choice of foreign versus domestic products among consumers from an LDC, such

as Indonesia. In particular, the current study investigates, from the perspective of an LDC, how

strong is the link between the generalized sentiment of consumer ethnocentrism and the

consumers’ particular product preferences and their ultimate purchase behaviour.

The objectives of the current study can therefore be stated as follows:

To measure the level of Consumer Ethnocentrism in a Less Developed Country

(Indonesia) and to compare it with known levels in other countries;

Using Conjoint Analysis, to study the relative importance of COO across High and Low

CE groups

Research Approach

The survey involved interviewing a representative sample of Indonesian consumers who had

previously purchased the products in question, namely colour television and who had travelled

by international airlines. A total of 547 useable questionnaires were completed in face-to-face

interviews in Indonesia. (The actual sample was heavily biased to upper socio-economic groups

because of its focus on international airlines as one of the subject products. This will inevitably

distort the average CETSCALE score, but was felt to be unavoidable.) Data were analysed using

standard statistical packages (SPSS and AMOS). Respondents were asked a range of questions

covering their demographic characteristics, the CETSCALE questions together with questions

concerning their perceptions and purchasing intentions towards colour television and airline

travel.

Results

Consumer Ethnocentrism in Indonesia

Shimp and Sharma (1987) developed CETSCALE to measure the degree of ethnocentric

tendencies among a variety of cultures. Previously published studies of the psychometric

properties of CETSCALE and analysis conducted in the current research project (although not

reported here) have shown that it is a reliable scale for measuring consumer ethnocentric

tendencies generally, and in Indonesia in particular. This section will examine mean comparisons

between the current study and previous studies of ethnocentrism in other countries.

Previous studies have investigated the nature of consumer ethnocentrism in the USA (Shimp and

Sharma, 1987; Durvasula et al., 1997), Germany, France, Japan (Netemeyer et al.,

1991), Russia (Durvasula et al., 1997),New Zealand (Watson and Wright, 1999),

and Australia (Acharya and Elliott, 2003). All these studies employed the 17 items of

CETSCALE with a 7-point Likert scale. In order to have comparable results with the previous

studies, the full seventeen items of CETSCALE were also included in the survey instrument used

in the current study. The total score of the CETSCALE varies between 17 and 119, due to the use

of a 7-point Likert scale. The mean scale value of CETSCALE is taken as the indicator of the

intensity of consumer ethnocentrism, a higher mean scale value indicates higher consumer

ethnocentrism. The total mean value for the current study was 74.50 for Indonesian consumers.

This result compares with those from previous studies in several countries where the value

ranges from 32.02 for Russian sample to 85.07 for the Korean sample. See Table 1 for results of

previous CETSCALE studies. Clearly, the results for Indonesia place it at the high end of

international comparisons.

Table 1. Comparison results of CETSCALE mean by country

Author(s) Country Respondent Mean SD

Shimp and Sharma (1987)

USA Students 51.92 16.37Detroit General population 68.58 25.96Carolinas General population 61.28 24.41Denver General population 57.84 26.10Los Angeles General population 56.62 26.37

Durvasula et al. (1997)

USA Students 50.24 22.85Russia Students 32.02 12.47

Watson and Wright (1999)

New Zealand General population 62.21 25.79

Good and Huddleston (1995)

Poland General population 69.19 NA

Russia General population 51.68 NA

Sharma et al. (1995)

Korea General population 85.07 NA

Caruana (1996) Malta General population 56.80 18.20

Hult et al. (1999)

USA Students 61.50 19.3Japan General population 40.10 17.3

SwedenGeneral population and Students

38.40 18.5

Steenkamp and Baumgartner (1998)

Belgium General population 28.70 9.21Great Britain General population 30.29 9.47Greece General population 37.84 7.39

Brodowsky (1998)

USA General population 61.68 NA

Acharya (1998) Australia Students 56.40 NA

Conjoint Analysis Results

Two groups of respondents were defined to be high and low with respect to ethnocentricity. The

purpose of this analysis is to compare and contrast consumer judgements of product (television

and airline) attributes for the two groups using conjoint analysis. Conjoint analysis produced

various utility models to explain the impact of country image cues on perceptions of product

quality and purchase decisions. The extrinsic cues of country image such as brand, price,

country-of-assembly, and country-of-design were employed as product attribute judgements. In

this discussion, results will be presented for the Conjoint Analysis showing the relative

Importance of Country-of-Origin (COO) across Low and High Ethnocentrism Groups. These

results are discussed for both tangible goods in which COO is broken down into Country of

Design (COD) and Country of Assembly (COA) and intangible services (for which only Country

of Origin is meaningful).

An important issue in assessing the conjoint analysis is to select a part-worth relationship type.

Conjoint analysis has three alternative part-worth relationships, ranging from the most restrictive

(a linear relationship) to the least restrictive (separate part-worths), with the ideal point, or

quadratic model, falling in between. Hair et al. (1998) noted that the part-worth model is most

general and calculated for each level of the corresponding part-worth ('discrete' as used in SPSS

10.0) estimates. The part-worth (discrete) model can be used when attribute levels are categorical

and no assumption is made about the relationship between the factor and the scores or ranks

(Hair et al, 1998). In this study, all attribute levels were specified as discrete part-worth except

for the attribute levels of price. For price, a linear model was used, because data was assumed to

be linearly related to the attribute and this is because higher prices generally correspond to lower

utilities of purchase intention and also generally correspond to higher utilities of consumer

perception of product quality. The linear model is the simplest, but most restrictive as only a

single part-worth (similar to regression coefficient) multiplied by the level's value is estimated.

Table 2 Part-worth estimates and relative importance of product attributes in perceived quality

for tangible goods and Table 3 Part worth estimates and relative importance of product attributes

in purchase intentions for tangible goods show results of the conjoint analysis for tangible goods.

Table 2 Part-worth estimates and relative importance of product attributes in perceived quality for tangible goods

Country-of-origin design parameters

Type of Data

Ethnocentric TendencyLow Level High Level Overall

Part worth estimates(n = 125)

Relative importance (percent)





BrandPart-worth

31.53 34.72 32.87

Polytron-0.1514

-0.0381

-0.1025

Sony 0.2142 0.1417 0.1704

Philips-0.0628

-0.1036

-0.0679

PriceLinear

13.27 13.88 14.40

Rp. 5.000.000

0 0.0053 0.0105

Rp. 6.000.000

0 0.0107 0.0211

Rp. 7.500.000

0 0.0160 0.0316

COAPart-worth

23.82 25.53 25.01

Malaysia-0.0213

-0.109-0.0809

Indonesia-0.1056

0.139 0.0342

South Korea

0.1268-0.0301

0.0467

COD Part- 31.39 25.86 27.71

worthJapan 0.2094 0.0484 0.1155Netherlands

0.1207-0.0514

0.0188

Indonesia-0.3301

0.003-0.1343

Pearson's R

0.981 0.999 0.987

p-value 0 0 0Kendall's Tau

0.771 0.994 0.889

p-value 0.0022 0.0002 0.0004

Table 3 Part worth estimates and relative importance of product attributes in purchase intentions for tangible goods


Type of Data








BrandPart-worth

31.49 32.00 31.61

Polytron -0.184 -0.0331 -0.0996Sony 0.2747 0.1671 0.2099Philips -0.0907 -0.1339 -0.1103

PriceLinear

14.73 17.22 16.47

Rp. 5.000.000

-0.1314 -0.0984 -0.1031

Rp. 6.000.000

-0.2627 -0.1968 -0.2061

Rp. 7.500.000

-0.3941 -0.2952 -0.3092

COAPart-worth

22.15 26.74 24.94

Malaysia -0.0163 -0.1651 -0.1137Indonesia -0.0681 0.2163 0.1036South Korea

0.0844 -0.0513 0.01

COD Part- 31.63 24.04 26.98

worthJapan 0.2398 -0.0358 0.1143Netherlands

0.1042 -0.0004 0.0298

Indonesia -0.344 0.0362 -0.144Pearson's R 0.967 1 0.995p-value 0 0 0Kendall's Tau

0.833 1 0.889

p-value 0.0009 0.0001 0.0004

Table 4 Part-worth estimates and relative importance of product attributes in perceived quality

for intangible services and Table 5 Part-worth estimates and relative importance of product

attributes in purchase intentions for intangible services summarise the utility values of the levels

of the two attributes of intangible service for each of these three groups and the whole sample.

The relative importance of two attributes for the three groups and overall sample is shown in

both tables.

Table 4 Part-worth estimates and relative importance of product attributes in perceived quality for intangible services


Type of Data








COO

Part-worth

68.75 59.04 61.45

Indonesia

-0.3622

0.0619

-0.1426

Australia

0.3622

-0.0619

0.1426

PriceLinear

31.25 37.21 37.51

$535-0.0449

0.1000

0.0034

$585-0.0897

0.2000

0.0069

Pearson's R

0.995 0.988 0.991

p-value0.0023

0.0062

0.0044

Kendall's Tau

0.667 1 0.667

p-value0.0871

0.0208

0.0871

Table 5 Part-worth estimates and relative importance of product attributes in purchase intentions for intangible services


Type of Data








COOPart-worth

64.77 61.82 61.01

Indonesia

-0.375 0.2913 0.008

Australia

0.375-0.2913

-0.008

PriceLinear

35.23 36.51 37.99

$535-0.3182

-0.1198

-0.2701

$585-0.6364

-0.2395

-0.5401

Pearson's 1 0.9980 0.999p-value 0 0.0009 0.0005Kendall's 1 1 1

Taup-value 0.0208 0.0208 0.0208

In the evaluation and analysis of conjoint models, testing the consistency of results and

validation of the model is a crucial issue. Shepherd et al. (2002) employed and advocated

Pearson R and the rank correlation coefficient of Kendall's (tau) parameter to examine the

consistency and validation of the model. Pearson R parameter was used to examine the

consistency of the results The value of the rank correlation coefficient (Kendall's ) was

employed to serve as a "goodness-of-fit" measure of the agreement between observed and

(according to the estimated parameters) predicted rankings or scores of the stimuli profiles. As

shown in Tables 2, 3, 4, and 5, the Pearson R parameters and Kendall's (tau) parameters had a

value of 1 or close to 1 and were all significant at the 0.01 level. The Pearson R parameters

indicate that, for the most important attribute levels' utilities, the models were a good fit. In other

words, the final model obtained is consistent for both prediction and inference purposes. In

addition, the significant Pearson's R and Kendall's tau parameters indicate that the data

exhibited high goodness-of-fit and thus high internal validity.

Discussion of Results

Results for tangible goods, tables 2 and 3, show generally consistent findings. In both cases,

brand is most important, followed by Country of Design, then by Country of Assembly and by

price as least important. This is in terms of both “relative quality” (table 2) and purchase

intention (table 3). The rank ordering of attributes is generally common in both tables with the

exception of COA for purchase intentions in the high CE group. In that case, COA ranks before

COD, although this finding is not surprising as it shows how important COA is, in principle, to

the high CE group when purchasing. Conversely, that the low CE group ranks COD before COA

in relation to purchase intentions is again consistent with expectations.

For intangible services, tables 4 and 5, results are largely consistent with those for tangible goods

in that COO is more important than price for both high and low CE, both in terms of quality

perceptions and purchase intentions. There is an important distinction however. Because COO

can serve as a proxy indicator of brand, it is much more important for services than for tangible

goods. In the current example, the brands Garuda and QANTAS are indistinguishable from their

respective COO’s (just as Citibank and Holiday Inn would be practically indistinguishable from

their COO). It is readily conceded that this result could be an artefact of the research design

which did not incorporate “brand” within the services model. This was necessary as it would be

nonsensical to talk of a non-Indonesian (COO) Garuda or a non-Australian QANTAS. Similarly,

the distinction between COD and COA in services is also largely vacuous. Notwithstanding,

these results suggest COO for services is perhaps more important than COD/COD for tangible

goods.

There are a number of important implications which flow from these findings. Firstly, the high

level of CE for Indonesia, an LDC, is contrary to earlier theory which suggests that consumers in

LDC’s will evaluate products from MDC’s more highly. These results show that consumers

in Indonesia are, if anything, more concerned with COO and are potentially more receptive to

“Buy Local” promotional campaigns and messages. Secondly, notwithstanding their high CE

scores, Indonesian respondents rated COA and COD of tangible goods behind brand in

importance (but before price). This suggests that the impact of brand will probably overpower

COD and COA when consumers choose tangible goods. These results also suggest that strong

brands and local COA will be very attractive to high CE consumers although low CE consumers

will prefer the foreign COD. Thirdly, although our results are somewhat speculative, they

suggest that COO might serve as a powerful defacto brand for intangible services. If so, those

with high CE will choose the locally-owned service provider while those with low CE will prefer

the foreign provider. Fourthly, these results also suggest that the COO effect for services may be

more important than for tangible goods. This is certainly a worthy topic for COO researchers in

future.

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Consumer Ethnocentrism and Product Preferences- Indonesian Evidence