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Pan-Pacific Conference XXXIV. Designing New Business Models in Developing Economies

This publication represents the Proceedings of the 34th Annual Pan-Pacific Conference being held in Lima, Peru May 29-31, 2017. The Pan-Pacific Conference has served as an important forum for the exchange of ideas and information for promoting understanding and cooperation among the peoples of the world since 1984. Last year, we had a memorable conference in Miri, Malaysia, in cooperation with Curtin University Sarawak, under the theme of “Building a Smart Society through Innovation and Co-creation.” Professor Pauline Ho served as Chair of the Local Organizing Committee, with strong leadership support of Pro Vice-Chancellor Professor Jim Mienczakowski and Dean Jonathan Winterton.

This publication represents the Proceedings of the 34th Annual Pan-Pacific Conference being held in Lima, Peru May 29-31, 2017. The Pan-Pacific Conference has served as an important forum for the exchange of ideas and information for promoting understanding and cooperation among the peoples of the world since 1984. Last year, we had a memorable conference in Miri, Malaysia, in cooperation with Curtin University Sarawak, under the theme of “Building a Smart Society through Innovation and Co-creation.” Professor Pauline Ho served as Chair of the Local Organizing Committee, with strong leadership support of Pro Vice-Chancellor Professor Jim Mienczakowski and Dean Jonathan Winterton.

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the largest number of research studies; the majority<br />

applied the SERVQUAL model, which is the most<br />

used <strong>in</strong> an academic environmental. It was created<br />

by Parasuraman et al. (1985) and refers to a<br />

multiple-scale of values that identifies the difference<br />

between the customers’ expectations and<br />

perceptions. There is another model called<br />

SERVPERF, developed by Cron<strong>in</strong> & Taylor (1992),<br />

which focuses on the study of quality <strong>in</strong> the results.<br />

The SERVPERF model uses the 22 items with the<br />

7-po<strong>in</strong>t Likert scale of the SERVQUAL model, but<br />

without the expectations column.<br />

Loyalty studies have mostly focused on consumer<br />

behavior toward tangible goods and to a lesser<br />

extent on service brands. There is loyalty <strong>in</strong><br />

situations where the consumer evaluates several<br />

brands of similar category and makes the purchase<br />

decision. These <strong>in</strong>ternal processes allow<br />

dist<strong>in</strong>guish<strong>in</strong>g the loyalty from other repetitive<br />

purchase behaviors (Bloemer & Kasper, 1995). Two<br />

basic approaches describe loyalty, accord<strong>in</strong>g to the<br />

research studies: the attitudes and behaviors<br />

approach. The three ma<strong>in</strong> theoretical orientations<br />

were developed based on these two approaches: The<br />

behavioral approach, the attitud<strong>in</strong>al approach, and<br />

the mixed attitude-behavioral approach. In contrast,<br />

loyalty via customer satisfaction differentiates<br />

satisfaction as a goal, but the objective is to build<br />

loyalty, consequently, the customer needs to be<br />

satisfied <strong>in</strong> order to build the customer loyalty.<br />

Vasquez-Párraga & Alonso (2005) proposed that to<br />

build the customer loyalty, a strong commitment—<br />

either with the product, service, or company—is<br />

needed.<br />

The <strong>in</strong>struments used for the measurement of<br />

loyalty led to a series of proposals to measure<br />

loyalty were grouped <strong>in</strong> two types: behavioral or<br />

operational, and attitud<strong>in</strong>al-behavioral. Colmenares<br />

& Saavedra (2007) described behavioral or<br />

operational measures as post-action (buy) measures<br />

that show their performance or actual outcome<br />

(effects). They base the loyalty <strong>in</strong> the cont<strong>in</strong>uous<br />

choice of a same alternative of purchase over time.<br />

In terms of attitude-behavioral measures, the same<br />

authors (Colmenares & Saavedra, 2007) expla<strong>in</strong>ed<br />

that they measure the degree of commitment that the<br />

<strong>in</strong>dividual has developed toward the brand,<br />

demonstrated by preference and purchase <strong>in</strong>tention.<br />

They are measured through observation, <strong>in</strong>terview<br />

and attitude scales. Zeithaml et al. [11] developed a<br />

13 item-scale to measure loyalty as a behavioral<br />

<strong>in</strong>tention. This scale was classified <strong>in</strong> five<br />

dimensions: loyalty, switch, price sensitivity,<br />

external, and <strong>in</strong>ternal compla<strong>in</strong>ts. The measurement<br />

<strong>in</strong>strument of this study is based on this rat<strong>in</strong>g scale.<br />

3 METHODOLOGY<br />

This is a cross-sectional quantitative study and a<br />

non-experimental descriptive-correlational research,<br />

s<strong>in</strong>ce the data was collected without manipulat<strong>in</strong>g.<br />

The sample size was 381 people to be surveyed. The<br />

data was obta<strong>in</strong>ed through surveys and the<br />

<strong>in</strong>strument was a questionnaire composed of two<br />

groups: the first group <strong>in</strong>cluded 25 service quality<br />

questions <strong>in</strong> accordance with the dimensions of the<br />

SERVQUAL model of Parasuraman et al. (1988):<br />

tangibility, reliability, responsiveness, security and<br />

empathy. But only the respondents’ perceptions<br />

were evaluated so that the scale became<br />

SERVPERF proposed by Cron<strong>in</strong> & Taylor (1992).<br />

The second group <strong>in</strong>cluded 11 loyalty questions<br />

based on the behavioral approach <strong>in</strong>corporat<strong>in</strong>g the<br />

measurements subsequent to the purchase. Several<br />

items were <strong>in</strong>cluded <strong>in</strong> the “behavioral <strong>in</strong>tention”<br />

scale developed by Zeithaml et al. (1996), to<br />

measure the customer’s loyalty. Both groups were<br />

measured us<strong>in</strong>g the 5-po<strong>in</strong>t Likert scale from 1 to 5.<br />

Additionally, some variables were adapted for the<br />

purpose of the <strong>in</strong>vestigation. Variable 1: Quality of<br />

service. The six dimensions of the model<br />

elaborated by Parasuraman et al. (1988), were<br />

adapted to the hotel market: (a) tangible and<br />

technological equipment; (b) accessibility; (c)<br />

professionalism of staff; (d) security; (e)<br />

competitive hotel offer; and (f) empathy. Variable<br />

2: Consumer loyalty. Measured as the <strong>in</strong>tention of<br />

behavior. The <strong>in</strong>dicators proposed by Zeithaml et al.<br />

(1996) were used: (a) fidelity; (b) change; (c) price<br />

sensitivity; (d) external compla<strong>in</strong>t; and (e) <strong>in</strong>ternal<br />

compla<strong>in</strong>t. The hypotheses developed <strong>in</strong> this study<br />

are based upon the SERVQUAL / HOLSER<br />

/SERVPERF models.<br />

4 RESULTS<br />

The construct validity and its dimensionality was<br />

studied , us<strong>in</strong>g the Kayser Meyer & Olk<strong>in</strong> (KMO)<br />

test that yielded a value of 0.95, which is rated as<br />

“excellent” <strong>in</strong> a range from 0 to 1. The Bartlett's test<br />

for sphericity was also used to evaluate the<br />

applicability of the factorial analysis for service<br />

quality. This test yielded a value of 2290.3 for X 2<br />

with a significance level of 0.000, which reflects the<br />

significant <strong>in</strong>tercorrelations among the variables<br />

justify<strong>in</strong>g the evaluated construct. The pr<strong>in</strong>cipal<br />

component analysis was used to identify three<br />

components or factors, from which the extracted<br />

factor No. 1 (location and personnel<br />

professionalism), expla<strong>in</strong>ed 50.7% of the service<br />

quality total variance; factor No. 2 (comfortable<br />

facilities and efficient service) 5.0%; and factor No.<br />

3 (superior hotel offer) 4.8%. The Cronbach’s<br />

Alpha coefficient was used to verify the service<br />

quality reliability. The values fluctuated from zero<br />

to one. The three extracted factors were highly<br />

reliable (α >.800). These were: “Location and<br />

personnel professionalism”—which was the factor<br />

that obta<strong>in</strong>ed the highest reliability (α: .932)—<br />

followed by “Comfortable facilities and efficient<br />

service” with (α: .895) and f<strong>in</strong>ally “Superior hotel<br />

offer” with (α: .850).<br />

For Loyalty, the pr<strong>in</strong>cipal components extraction<br />

resulted <strong>in</strong> three components: (a) Factor 1<br />

“Behavior - loyalty,” which expla<strong>in</strong>s 34.4% of the<br />

total expla<strong>in</strong>ed variance; (b) Factor 2 “Behavior -<br />

switch”, which expla<strong>in</strong>s 16.6%; and (c) Factor 3<br />

“Behavior - <strong>in</strong>ternal compla<strong>in</strong>t,” which expla<strong>in</strong>s<br />

11.1%. The validity is, therefore,correct<br />

The item-scale correlations are higher than 0.3 <strong>in</strong> all<br />

cases, which reflects a good relationship among the<br />

75

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