Development of Word-of-Mouth Elasticity Measures for Tourism Product Categories

doi:10.4236/psych.2012.39109

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Psychology

2012. Vol.3, No.9, 722-728

Published Online September 2012 in SciRes (http://www.SciRP.org/journal/psych) http://dx.doi.org/10.4236/psych.2012.39109

722

Development of Word-of-Mouth Elasticity Measures for

Tourism Product Categories

Yimiao Chen1, Fangyi Liu2*, Li-Ming Ho2, Tom M. Y. Lin1

1Department of Business Administration, National Taiwan University of Science and Technology,

Taipei, Chinese Taipei

2Department of Marine Leisure Management, National Kaohsiung Marine University,

Kaohsiung, Chinese Taipei

Email: *[email protected]

Received June 21st, 2012; revised July 24th, 2012; accepted August 28th, 2012

This study examines the influence of word of mouth (WOM) on eight tourism products by applying eco-

nomic elasticity theory to understand the relationship between behavioral outcomes and target elements to

these behavioral outcomes (customer consumption). The elasticity model of economics was developed to

conceptualize WOM elasticity () and measure WOM effects on various products. The results of

WOM elasticity values show a significant difference between physical and service product categories. In

addition, all effective respondents in this research are highly sensitive to WOM relating to specific prod-

ucts. This shows that WOM is not only a key variable of tourism products but also validates that WOM

communications are meaningful for tourism customers. The authors contributes to tourism service and

WOM marketing effects compared by validating empirical research in eight different product categories

and providing empirical support with prior services marketing literature. Theoretical and practical impli-

cations and future research issues are discussed.

WOM

Keywords: Tourism Product Categories; Word-of-Mouth; Elasticity Logic; Purchase Drivers

Introduction

Word-of-mouth (WOM) is an important issue in marketing.

Numerous studies have demonstrated that WOM is an effective

marketing tool, for example, Lan et al. (2012) shows people

like to talk and spread information in their familiar group,

whether products are sold at street vendors, night markets, ge-

neral shops or internet auction sites, most of customers receive

in-formation from their very close acquaintances. Villanueva et

al. (2008) concluded that the lifetime value of customers ac-

quired through WOM is twice as great as that acquired through

traditional marketing tools and Trusov et al. (2009) pointed out

that WOM in website member acquisition is 30 times higher

than media appearances. Furthermore, we understand WOM

can help purchase decision making (Harrison-Walker, 2001;

Crane & Lynch, 1988), especially in innovative products (Dod-

son & Muller, 1978; Arndt, 1967); durable goods (Mahajan et

al., 1990; Kiel & Layton, 1981), and professional services (File

et al., 1994; Murray, 1991); thus, the WOM effects are vary

across products, markets (Ennew et al., 2000), and even brands.

The potential impact of WOM and its value to an organization

is thus considerable, although the dominant explanation focuses

on the role of WOM as a risk-reliever or as a risk reduction

strategy (Fang et al, 2011; Forsythe, 2003; Derbaix, 1983), the

comparison for WOM influence on different products may be

more difficult to identify. Therefore, this study will directly

combines economic elasticity theory and WOM research to

explore a comprehensive principle for not only quantifying

WOM effects but also mirroring the primary cause in various

WOM phenomena, with a one-size-fits-all standard of WOM

quantification in market research can better use this effective

marketing tool.

Price elasticity theory originates from economics, where the

sales of good X responds to a 1% change in price; that is,

xxxxx

(E is the price elasticity, P represents

product price and Q is the quantity of product sale). A number

of WOM studies have demonstrated that the sales of goods

respond to changes in WOM (Bansal & Voyer, 2000; Goges &

Mayzlin, 2004). Thus, WOM elasticity follows the same logic

to quantify the relation between WOM and the sales of goods,

that is, the extent of WOM effects.

EQPPQ 

For the purpose of examining the usage of WOM elasticity,

the authors found the power of word-of-mouth (recommenda-

tion by friends and family) is the most credible for leisure tra-

velers (Murphy et al., 2007; Alvarez & Asugman, 2006). For

tourists, this recommendation of a product/service from a friend

or family member is the most powerful information source

available. It is also the least expensive. In the same time, lot of

literatures emphasis the influence of travel blogs as a commu-

nications tool to travel information (as an electronic word-of-

mouth) about travel experience (Pan et al., 2007; Schmallegger

& Carson, 2008). And the continuing rise of the internet as a

WOM communications tool for travel and tourism presents

challenges for tourism enterprises. After leisure travelers obtain

travel information either online or offline, many still need the

validation of a travel professional, especially for more complex

travel. It is essential for travel marketers to realize the sale is

not consummated at time of booking or final deposit. Rather, it

is after the customer consumes the travel experience of others.

So, how to understand the real effect of the travel experience

WOM? Thus, the authors choose 8 product categories of tour-

*Corresponding author.

Y. M. CHEN ET AL.

ism industry to calculate the WOM elasticity values and com-

pare the WOM effects on these product categories, and hope

the results can generalized to other industries.

This study is organized as follows. The authors first devise a

WOM sales function to integrate two major variables: tourism

product sales and its WOM. Second, the authors use question-

naires to collect product purchasing information from experi-

enced consumers. Third, the authors investigate two types

(physical vs service) of products mentioned in the literature.

Finally, the authors calculate the WOM elasticity value of the 8

product categories. Finally, the authors present the results and

discuss the limitations and implications of how WOM and its

effects impact each product category.

Measuring Word-of-Mouth Influences

Elasticity The ory for Qu ant i fi cati o n and Comparison

To understand the concept of WOM elasticity as applied to

WOM marketing research; it is useful to briefly review previ-

ous marketing research within the elasticity framework. For

example, Assmus et al. (1984) examined the elasticity frame-

work and noted the absolute value of price elasticity is eight

times that of advertising elasticity. Olivera-Castro (2008) ap-

plied price elasticity theory to brand selection; and Trusov et al.

(2009) used the elasticity indicator to estimate that WOM is 20

times as effective as marketing events and 30 times as effective

as media appearances. In general, these studies followed the

elasticity theory to describe variables and compare their effect-

tiveness, and used the concept to integrate research themes and

the variables of demand, sale, market share, and so forth, to

discuss marketing effects. Moreover, some researchers add a

time variable to understand elasticity trends in determining

marketing strategies. Overall, academics support elasticity as a

very useful concept that can be applied to the study of WOM.

WOM Elasticity Logic

WOM behavior means the number of people told about a

product experience (Halstead & Droge, 1991). Many WOM

studies have found that a considerable proportion of consumers

seek product WOM from the Internet or friends before buying

goods (Bloch et al., 1986; Katona & Mueller, 1954). Many of

these studies have determined that positive WOM can increase

the probability of product purchase (Ardnt, 1967; Katz &

Lazarfeld, 1955), and negative WOM can negatively influence

purchasing decisions (Homburg et al., 2005; Mittal et al., 1998).

That’s means the product sales as a function of WOM as fol-

lowing:







xx xxx

SalesQf WOM , other factorfWOM

where Qx is the sales of product X, x is the WOM of

product X, and other factorx is other variables (assumed to be

fixed here) that can affect the product sales,

WOM

According to the WOM sales function above, the definition

of the WOM elasticity of product X is as follow:

xxx x

WOM

xx xx

QQQ WOM

EWOM WOMWOMQ







where Qx is the sales of product X, is the WOM of pro-

duct X,

WOM

shows how QX changes as x

changes, and this expression for shows how the sales

of X responds to a 1% change in X’s WOM.

Research Hypotheses

As above, WOM elasticity value (WOM ) can directly meas-

ure and compare WOM effects, shows that the differences in

WOM effects are then related to differences in WOM elasticity.

Accordingly, WOM becomes an intermediate indicator inte-

grating all influenced factors except WOM to WOM sale func-

tion so that can help us better understand WOM effects (see

Figure 1). Thus, the first hypothesis in this study is concerned

with the WOM elasticity value in tourism industry, this ex-

pected a positive value will be observed for all categories we

will investigate. And second hypothesis is subjected to empiri-

cal examination of difference of WOM elasticity value between

the service and physical products; in here the authors expected

a larger value for service than physical products in this paper.

Methodology

To Get the WOM Elasticity Values

The economic theory logic is used to calculate the WOM

elasticity value; thus, we must assume the other conditions are

unchanged and the system is a closed economy (without foreign

purchases). Therefore, the consumption equal product sale, the

relation between a product’s variables of consumption (C) and

WOM is Equation (1).

Mathematical Notations





QCfWOM (1)

WOM

ΔQQ ΔCC

EΔWOM WOMΔWOM WOM

 (2)



βε

CAWOMe (3)





lnClnA βln WOMε





(4)

WOM

dlnC

βE

dlnWOM



1 (5)

i1i1 i1

i2i2 i2

ipip ip

inin in

lnClnWOM ε

αβ

lnClnWOM ε



 



 



 



 

 



 



 



 



 



 



 

(6)

where Q is the product sales; C is the consumption of goods, an

independent variable in this study’s framework; and WOM is

the product WOM, a dependent variable. Given Equation (1),

1Setting ln A = , a constant, we differentiate Equation (4) by WOM as α

follows:

dlnC dαdlnWOM dε

dWOM dWOMdWOMdWOM

1dC 1

Þ0β0

CdWOM WOM

 



where WOM

1CdC dWOMdC C

βE

1 WOMdWOMWOM





ΔQΔWOM WOM

WOM

E

Y. M. CHEN ET AL.

Price

Product

Category

Income

Other

Factors

Purchasing

Situation

Preference

WOM

Advertise-

ment

Consump-

tion

Function

consumpti

Figure 1.

Mechanism of WOM influence. Original state: Consumption function is

influenced by many factors; Present state: Assuming other independent

variables are fixed. *The outer circle are independent variables, the

centre circle is dependent variable.

the definition of WOM elasticity (WOM ) is Equation (2), where

ΔQ is the change in the amount of sales, ΔC is the change in the

consumption, and ΔWOM is the change in WOM.

Finally, as in Equation (3), a basic function type is set as a

Cobb-Douglas functional form, which is very easy to manipu-

late and has been widely used in prior studies in various fields

(e.g., Costrell & Loury, 2004; Wirjanto, 2004); In Equation (3),

where e is an exponential, A and β are constants, and ε is a

random variable. We then take the natural logarithm (ln) to plus

on both sides of Equation (3) to obtain a simple linear regres-

sion equation as Equation (4).

In Equation (5), is the value of continuous WOM elastic-

ity (WOM ). When the samples are from the same distribution,

the logarithm of consumption of product categories and WOM

has a linear relation, as in Equation (6), an econometric model

specification.

In Equation (6), where





ip ip

EεWOM 0;









ip ip

Var εWOM σhomoskedasticity,

α and β are the estimated regression coefficients, ε represents

the error term, n is the number of effective samples, ip

is the WOM evaluation of consumer p of product i (equal to the

degree consumer p is influenced by the WOM of product i),

ip is the amount of product i consumed by consumer p, and

is the in product i’s category.

WOM

βWOM

Samples and Data Collections

For the tourism this research concerned, the authors screen 8

different categories of physical product and service to enhance

our understanding of WOM effects among different products,

including transportation, accommodation, meals, guiding, sou-

venir, admission, travel agency, scenic spots as objectives for

this investigation. We subsequently designed an appropriate

questionnaire and deliver to 300 customers in tourism site (ho-

tel and restaurant) for two week, and then we successfully col-

lect travel experiences of 241 tourists who consumed all or

some of these product categories. The questionnaire example

for all product categories is as following: (a group of three

questions for one product; X is transportation or accommoda-

tion or meals or…).

 A) When you go traveling, have you ever bought product X

over because of its word of mouth? → If your answer is yes,

then continue to answer the next two questions.

 B) By what degree were you influenced by word of mouth

of product X? (Please evaluate your feeling about X’s

WOM, in the range 1 - 100).

 C) How much did you spend purchasing product X? (new

Taiwan dollars).

Since the objective measurement of WOM is complex, the

alternative of the extent to which WOM recipients were influ-

enced by WOM (Bansal & Voyer, 2000) is the standard of

WOM measurement (degree 1 - 100) in this questionnaire. Af-

ter two weeks data collected by random sampling, there are 241

effective samples for calculating the WOM elasticity values of

the 8 products in tourism.

For each product, a group of three questions was designed.

Because this questionnaire is measured differently from the

traditional scale, the past instrument is not suitable for testing

the validity of this questionnaire. When we focus on the single

independent factor WOM that is simply understand the goal of

this questionnaire. Every product must be regarded as a differ-

ent aspect from others in this study, and the three questions can

construct to an independent questionnaire that is not necessary

to test the validity. Maybe in the future, when an extended

questionnaire is developed and the expert validity could verify

to detect the new developing scale.

The authors sample randomly to raise the reliability, and

screened 19 effective responders to test-retest to observe the

correlation coefficient to observe the reliability for this ques-

tionnaire (the period of test-retest is interval of two weeks). The

results of test-retest method are in Table 1, fortunately, the

authors found the correlation coefficients are large enough to

rely on; thus we can rule out the matter of no response set and

external validation and expect to increase samples is not appa-

rent to rise contribution.

In this study, the theoretical parameter values of both re-

search variables (WOM and C) are unknown. In addition, the

findings of previous literature conclude in lack of consensus in

tourism product. Thus it is hard to test the representativeness of

samples by statistic method, but we collect data in tourism site

724

Y. M. CHEN ET AL.

Table 1.

The test-retest reliability results.

Product category Correlation coefficient

Total point of WOM

evaluation and

consumption

Transportation 0.93

Accommodation 0.85

Meals 0.87

Guiding 0.84

Travel agency 0.89

Total point of WOM

evaluation and

consumption

Admission 0.87

Souvenir 0.96

Scenic spots 0.90

Total 0.89

(hotel and restaurant) for suitable sample is acceptable and, the

WOM evaluation is a subjective variable and consumption is

depended on consumer’s purchasing pattern is already under-

standing, too.

Results

Following the mathematical notations in page 3, the authors

obtain results by simple linear regression method. Table 2 pre-

sents the results of data analysis for a closed economy, where β

is a direct measure of the WOM elasticity of the 8 product

categories. The results clearly show that the β value of all cate-

gories of goods is greater than zero, and in which findings of all

product categories are significant except scenic spots, then

results in WOM with a positive enhancement can promote

product consumption.

The WOM elasticity results for the product categories are

different, proving that WOM effects vary across products.

Therefore, WOM elasticity is a considerable source of influ-

ence that leads to different WOM effects. Furthermore, the

empirical analysis examined that 1% changes in WOM have a

positive percentage impact on the sales of goods, except scenic

spots.

Our results indicate that these goods are services have WOM

elasticity values ranging from 0.58 to 1.29. Murray (1991)

found that consumers use personal sources of information more

when looking for service providers than when looking for

physical goods, and the more expert the product knowledge, the

greater the WOM influence on consumer decision making

(Bansal & Voyer, 2000; Gilly et al., 1998; Rabaglietti et al,

2011), and the more lasting the effects (Berry, 1995). For most

of the product of tourism, experience goods (Smith & Swinyard,

1982) also have a large influence like the travel agency, guiding

or accommodation.

However, these goods are physical have lower WOM elastic-

ity values ranging from 0.21 to 0.64, even that the result of

scenic spots is not significant, for three possible reasons. First,

as the post research speaking that physical good with less

WOM influence; second, the consumption of these products is

not necessary in traveling; and third, the tourists’ evaluation of

scenic spots have great response difference.

The results means WOM wields considerable influence on

Table 2.

Results of the data analysis of the 8 product categories.

Attribute Product

category α β (EWOM) p value Significant

(ρ < 0.1)

Transportation3.83 0.58 0.03 **

Accommodation4.24 0.78 0.06 *

Meals 2.53 0.75 0.05 **

Guiding 3.03 1.03 0.02 **

Service

Travel agency5.53 1.29 0.09 *

Admission 4.40 0.21 0.03 **

Souvenir 6.82 0.33 0.10 *

Physical

Scenic spots 7.57 0.64 0.23

Average

of total 4.740.65 0.076 *

The sign of two stars (**) is ρ < 0.05 that represent the result is very significant,

and one stars (*) is 0.05 ≦ ρ < 0.1 that represent the result is significant.

consumer purchases in tourism product categories, and the

average evaluation of WOM for all product categories is 77.89

(highest score is 100, see Table 3), which reveals that the con-

sumer would purchase goods if he or she had a stronger feeling

about the WOM and ensures that WOM is an effective market-

ing tool in tourism. The power of WOM observed in this

study’s results echoes previous researchers who emphasized

that WOM can make the difference between product success

and failure (e.g., Godes & Mayzlin, 2004; Laczniak et al.,

2001).

Discussion

Theoretical Implications

The most important theoretical implication in this study is

the concept of WOM elasticity was designed to an intermediate

indicator to integrate all factors which may affect the product

sales, then used to calculate and compare the WOM influence

on product sales. Although prior research has greatly taken the

use of elasticity theory to increase our understanding of social

science, most studies have focused solely on single event

(product) appearance or on a variety of products.

Remarkably, we have no one-size-fits-all standard to quan-

tify WOM to estimate WOM elasticity value; however, we can

bypass WOM measurement by using each recipient's personal,

subjective assessment of WOM influence. Note that the WOM

recipients (consumers) are the purchase decision makers

(Sweeney, 2008) evaluating how WOM affects their decision

making and expectations of consumptions (Devlin et al., 2002;

Webster, 1991).

This scale of WOM elasticity limits the ability of academics

to copy with the complex of WOM variable (e.g. negative

WOM), and hope to develop improved technology (construct

the panel data base for long term) for future use. One implica-

tion from the findings is that although consumers can be put

into segmented classes according to their purchase expenditures

it may not translate into purchase quantity. However, the intro-

duction of the concept of economic elasticity as an implement

to provide a simple method to quantify and compare WOM

effects that found WOM elasticity values showed a statistical

difference and that it has a significant WOM influence on ser-

Y. M. CHEN ET AL.

726

Table 3.

Results of the data analysis of the 8 product categories (continued).

Attribute Product

category

Mean of WOM Evaluation

(0 < μ < 100)

standard deviation of WOM

Evaluation (σ) effective sample (n) Ratio of effective sample (n/241)

Transportation 80.48 18.81 207 86%

Accommodation 74.56 13.78 223 93%

Meals 77.12 19.73 181 75%

Guiding 90.07 15.64 122 51%

Service

Travel agency 84.72 14.83 173 72%

Admission 66.53 22.29 109 45%

Souvenir 71.29 16.25 138 57% Physical

Scenic spots 78.34 17.13 215 89%

Average of total 77.89 171 71%

vice purchase than physical product purchase in tourism; thus,

we can incorporate them into a variety of product categories of

tourism of marketing strategies.

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Transportatio n

Accommodatio n

Meals

Guiding

Travel agency

Admis sion

Souvenir

Scenic spots

Product Category

Percentage of Responder

Managerial Implicati o ns

The present study illustrates the differences in WOM elastic-

ity impact on WOM influences. The purpose of this study is to

explore the WOM origins so that we can quantify the relation

between product sales and WOM, which offers an approach for

tourism managers to compare WOM effects with those of other

marketing tools. After product WOM spread, firms of tourism

relative should collect consumers’ WOM evaluations over time

to estimate the WOM variation to calculate the immediate,

short-term, and long-term WOM elasticity values of products of

tourism. Managers can consider product WOM elasticity to

develop marketing strategies and increase the effectiveness of

marketing resource allocation.

The results show that, a proportion (see Figure 2) of the re-

spondents are highly influenced by product WOM, which

means that consumers will consume the tourism product if they

feel good about its WOM. However, managers cannot object-

tively measure consumers’ feelings of WOM if a standard

measurement of consumer perception does not exist. This study

introduces the subjective measurement of WOM as a measure-

ment of utility and makes it easy to screen out the target con-

sumer group of tourism WOM marketing. Thus, firms should

include in their after-purchase surveys a questionnaire item for

WOM, under “the evaluation of WOM when you have con-

sumed,” in addition to the question on reason for purchase.

Efforts to study the WOM evaluation of consumers who are

easily influenced by WOM will effectively increase product

revenue. Furthermore, we even suggest applying WOM elastic-

ity in customer relations management to gauge WOM effects

on individual customers to analyze their buying patterns.

Figure 2.

Ratio of consumption responding to WOM.

First, we integrated the influenced factor on WOM to quan-

tify the relation between product sales and WOM. Second, we

examine the responses of 241 tourists for 8 product categories

were proved with different WOM influences on product sales

due to the different WOM elasticity of product. And the WOM

elasticity of services is much greater than physical products.

Third, we substitute the WOM recipients’ evaluations for

WOM communicators’ spread quantities (Brown et al., 2005;

Harrison-Walker, 2001) to measure WOM, turning an objective

variable into a subjective one, firms should find calculations of

WOM elasticity of product categories to be helpful in managing

the marketing resources for their products, then to establishing

a trend of WOM elasticity would be a powerful tool in the

management of WOM marketing on the products like travel

agency, guiding and accommodation.

Conclusion

The concept of WOM elasticity can be established to quan-

tify WOM influences, and the value of WOM elasticity can be

calculated by a subjective measure of WOM, the literature on

WOM elasticity definitions (Trusov et al., 2009) have been

receiving increased attention. This study increases our under-

standing of this potential issue for future research. The main

conclusions of this study are as follows.

Further Research

This study the concept of WOM elasticity had applied to the

tourism industry, otherwise, we must use indicator of WOM

elasticity to estimate the WOM effects on products of other

industries for generalization. In practice, we provide a simple

and useful method for measuring WOM variations without any

Y. M. CHEN ET AL.

quantitative units (number or length of time). WOM can be

subjectively measured on the premise that consumers under-

stand their own perceptions and preferences, so firms can esti-

mate product WOM elasticity directly by asking consumers

feelings about WOM. Moreover, it will be helpful to add a time

variable to analyze WOM effects in the short and long run for

further research.

Another issue is that WOM affects not only product catego-

ries but other factors, such as consumer loyalty and communi-

cation sites. In addition, the indicator of WOM elasticity can be

used to compare the effectiveness of WOM marketing activities

with other marketing tools (such as price promotion or adver-

tising), this is also a worthwhile issue for future study.

Finally, the concept of WOM elasticity can be extended to

quantify WOM influences among brands. Taylor (1997) found

that cross-brand WOM also affects consumer attitudes and

behavior (Libai et al., 2009). Therefore, we can apply cross-

price elasticity theory to constructing the concept of “cross-

WOM elasticity” for WOM among the different brands.

The present study illustrates the differences in WOM elastic-

ity impact on WOM influences. The purpose of this study is to

explore the WOM origins so that we can quantify the relation

between product sales and WOM, which offers an approach for

tourism managers to compare WOM effects with those of other

marketing tools.

Acknowledgements

We would like to thank the anonymous referees for their

valuable comments and suggestions. The authors can be con-

tacted at fion@ccms.nkfust.edu.tw or

[email protected].

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