The Impact of High Performance Work Systems in the Health-care Industry, Employee Reactions, Service Quality, Customer Satisfaction, And Customer Loyalty

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The impact of high-performance work systems in the health-care

industry: employee reactions, service quality, customer satisfaction,and customer loyalty

Sang M. Leea, DonHee Leea∗ and Chang-Yuil Kangb

a Management, University of Nebraska-Lincoln, CBA209, Lincoln, NE 68588, USA;

b Medical

Information, Hyechon University, 333 Boksu-dong, Seo-gu 302-715, Daejeon, Republic of Korea

( Received 16 June 2010; final version received 16 October 2010)

The purpose of this study is to empirically test the effects of high-performance work systems (HPWS) on employee attitude, service quality, customer satisfaction, and

customer loyalty in health-care organisations. The proposed research model wastested using structural equation modelling for hypotheses, based on data collectedfrom 196 pairs of employee–customer respondents in four selected hospitals withmore than 500 beds. The results indicate that hospitals can improve customersatisfaction and loyalty through efficient operations, employee engagement, andservice quality. One of the key findings of our study is that HPWS in health-careorganisations influence employee reaction and service quality.

Keywords: high-performance work systems; employee reaction; service quality;customer satisfaction and loyalty; health care

Introduction

Health-care systems operate for the diagnosis and treatment of diseases, prevention of

illness, and promotion of healthy living habits. The leaders and managers of health-care

providers try to deliver quality care, reduce medical errors, ensure patient safety, reduce

medical costs for both patients and the hospital, and provide needed patient and customer

service. They also attempt to provide workers with appropriate information systems, new

medical equipment, job skills, and incentives to achieve organisational performance

(Kling, 1995). However, human resource (HR) is the core capability and the most valuable

resource that enables such efforts (Bowen & Ostroff, 2004; Delaney & Huselid, 1996;

Wright, Gardner, Moynihan, & Allen, 2005).

HR practices have been recognised as an important factor, which influences organis-

ational performance (Bowen & Ostroff, 2004; Delaney & Huselid, 1996), such as service

quality, customer satisfaction, and employee engagement (Boxall & Macky, 2007; Dean,

2004; Evans & Davis, 2005; Purcell & Hutchinson, 2007). Bowen and Ostroff (2004)

proposed a relationship between HR management (HRM) and organisational performance,

as effective HRM promotes a favourable organisational climate, which encourages positive

employee attitudes and behaviour for organisational performance. Meyer and Collier

(2001) also reported that HRM practices are positively related to customer satisfaction in

the health-care system. Consequently, employee attitude and service quality are critical

∗Corresponding author Email: stardh04@huskers unl edu

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Vol. 32, No. 1, January 2012, 17–36


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success factors (CSFs) for improving customer satisfaction. Thus, the accumulated

experience of employees is a valuable asset for the hospital in providing quality care.

High-performance work systems (HPWS) as HR systems represent an important

concept in the workplace (Boxall & Macky, 2007; Evans & Davis, 2005). Evans and

Davis (2005) define an HPWS as ‘an integrated system of HR practices that is internally

and externally consistent and includes selective staffing, self-managed teams, extensivetraining, open communication, and performance-compensation’ (pp. 759–760). Harmon

et al. (2003) and Scotti, Driscoll, Harmon, and Behson (2007) reported a positive relation-

ship between HPWS and customer satisfaction in the health-care industry. The HPWS

affects employees’ perceptions of service quality (Scotti et al., 2007) for improving

customer satisfaction. Based on previous research, a customer satisfied with the high

quality of the service will be more likely to have intentions to engage in repeat consump-

tion (Hallowell, Schlesinger, & Zornitsky, 1996; Rust & Zahorik, 1993; Scotti et al.,

2007). While the relationship between customer satisfaction and customer loyalty has

not been widely studied (Dean, 2004; Scotti et al., 2007), Baker and Taylor (1997)

supported this relationship based on a study of outpatients in not-for-profit hospitals.Thus, a health-care system as a HPWS, with its integrated HR practices, is a critical

factor for organisational performance in the medical service industry (e.g. service

quality, customer satisfaction, and customer loyalty). Also, a HPWS requires both high-

skilled and low-skilled employees for improving organisational performance in a

health-care system (Berg & Frost, 2005; Harley, Allen, & Sargent, 2007).

Previous research on customer satisfaction focused mainly on quality of care and

employee satisfaction in HPWS. However, there has been a paucity of studies on

employees’ reaction and attitudes to improve quality of care and service. Therefore, the

purpose of this study is to empirically test the effects of HPWS on employee attitude,

service quality, customer satisfaction, and customer loyalty in health-care organisations.A research model is proposed that includes both exogenous and endogenous factors that

influence the attainment of customer loyalty, based on previous studies. Survey data are

collected and analysed from hospital employees and customers concerning disease treat-

ment and/or preventive care. The proposed research model is examined using the structural

equation modelling (SEM) and t -test approach. The rest of this paper is organised as follows:

the second section presents a review of previous studies and concepts relevant to this study;

the third section proposes a research model and hypotheses; the fourth section shows a

research methodology; the fifth section reports the result of the model; and the sixth

section presents the conclusion and limitation of the study.

Literature review

In recent years, health care has become a critical issue in the world, along with the increased

concerns for medical errors, patient safety, and increasing medical costs (Olden &

McCaughrin, 2007; Stock, McFadden, & Gowen, 2007; Tucker, 2004). The service

environment of the health-care industry is determined by not only new facility and technol-

ogy support, but also the performance of employees in the organisation. Various methods

and tools are used by medical administrators, researchers, and health-care policy makers in

an effort to find a better way to provide high quality of the service at reasonable costs.

According to Milstein and Colla (2009), the US health-care system is not competi-

tive around the world in terms of its performance or costs. The US spent approximately$7500 a year per person in 2009 on health care by care sources including government

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Germany, spend only about one-third of what the Americans spend. The customer satisfac-

tion score on care quality measurements in the US is not higher than that in other advanced

countries (Milstein & Darling, 2009). The US residentshave less access to health care, spend

more money to receive the health care they get, and have more negative outcomes than the

residents of most other developed countries. The results of a study by Milstein and Colla

(2009) show that US workers and employers receive 23% less value (e.g. cost and perform-ance) from the health-care system than the average of fiveleading economic competitors(i.e.

Canada, Japan, Germany, the United Kingdom, and France) and 46% less value than the

average of emerging competitors (e.g. Brazil, India, and China).

High-performance work system

Organisations develop HR practices to enhance employees’ skills, knowledge, and motiv-

ation to improve organisations’ performance (Bowen & Ostroff, 2004; Delaney & Huselid,

1996; Wright et al., 2005). Profitable firms with effective HR practices can share their

profits with employees in the form of higher pays or incentives, offer more training anddevelopment opportunities, invest in advanced technology and systems, and encourage

participation in collaboration.

As HPWS represent an HRM approach (Beltrán-Martı́n, Roca-Puig, Escrig-Tena, &

Bou-Llusar, 2008), HPWS are ‘interrelated and aligned set of core characteristics, includ-

ing involvement, empowerment, trust, goal alignment, training, teamwork, communi-

cations, and performance-based rewards’ (Scotti et al., 2007, p. 111). HPWS include

managerial practices that increase the empowerment of employees and enhance their

skills through the support of the organisation (Appelbaum, Bailey, Berg, & Kalleberg,

2000; Lawler, 2005). The goal of HPWS is to increase efficiency and effectiveness by

motivating and assisting employees to complete tasks successfully (Beltrán-Martı́net al., 2008; Whitener, 2001). HPWS emphasise customer-focused work, empowered

work environments, employee motivation, and flexible and adaptive systems (Gephardt

& Van Buren, 1996). HPWS are the result of an organisation’s willingness to support

its employees to work effectively in positive environments. Therefore, the concept of

HPWS can be applied to any workplace, such as the health-care organisation, that

strives to perform more effectively.

These reasons lead to the following definition of HPWS in the health-care system:

health-care systems as HPWS support and manage work processes at the individual,

department, or group level (e.g. physicians, nursing, technicians, and administration in

the workplace) to improve work performance. According to the studies by Huselid

(1995) and Delaney & Huselid (1996), successful implementation of HPWS may

include employee motivation (e.g. compensation) and employee skills (e.g. training).

In this study, the factors associated with HPWS are measured by employee perceptions

about organisational training and education efforts, communication, and compensation.

These measurements of HPWS in the health-care organisation are developed based on

the studies of Beltrán-Martı́n et al. (2008), Evans and Davis (2005), and Scotti et al. (2007).

Employee reactions

Hospitals usually provide care to patients in a high-contact environment. Thus, customers

have expectations of an intensive interpersonal relationship with employees for a rela-tively short duration of time (Goldstein, 2003). Thus, employees’ attitudes and behaviour

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To improve employees’ attitudes and behaviour for their work outcome and organis-

ational performance, organisations support employees to develop positive relationships

with customers. Employee attitudes and behaviour are interrelated. Thus, when an

employee has a negative perspective about the job, a supervisor, or the organisation as

a whole, then the employee is less likely to care about his/her job performance.

However, if an employee is fully engaged and motivated, he/she will take pride indoing quality work, and strives to find ways to improve organisational performance.

Therefore, organisations need to develop HR practices that promote positive employee

attitudes, emotion, and organisational loyalty.

Employee reactions are attitudes and the degree of engagement determined by

employees’ perceived organisational support, politics, compensation systems, structure,

work activities, and goal (Fedor, Maslyn, Farmer, & Bettenhausen, 2008; Michie &

West, 2004). Ferris, Adams, Kolodinsky, Hochwarter, and Ammeter (2002) suggested

that higher levels of perceived political behaviour in the organisation are associated with

positive employee reactions. Eisenberger, Armeli, Rexwinkel, Lrvch, and Rhoades

(2001) proposed a positive relationship between perceived support and employees’ attitudetowards organisational goals. The proper compensation and support for employee motiv-

ation will improve employee reactions with positive attitudes, which are significant contri-

butors to organisational performance. The improved employee reaction in this study was

measured in terms of the extent to which employees perceived that they and the hospital

together fulfilled their obligations. This study adapted measurement items of the improved

employee reaction suggested by Ferris et al. (2002).

Service quality

The increasing concern about health care indicates the emergence of a new type of health-care consumers (Bohmer, 2001). The new generation of health-care consumers (e.g.

patients, family of patients, and potential consumers) demands improved quality of

service, increased satisfaction, medical error reduction, and prevention of diseases. The

improved quality of patients’ care should be a top priority for hospital leaders and

mangers. If hospital leaders take initiatives in creating and improving service quality of

health care, their employees will benefit and patients will receive a better quality of

care from the increased value of service (Porter & Teisberg, 2004).

Service quality is influenced by employee satisfaction (Hartline & Ferrell, 1996) and is

related to customer satisfaction (Babakus, Bienstock, & Scotter, 2004). Hartline and

Ferrell (1996) presented evidence that satisfaction felt by the first-line customer-contact

employees is associated with service quality (Ennis & Harrington, 2001). Satisfied

employees tend to be more engaged in providing quality services (Hallowell et al.,

1996; Yee, Yeung, & Cheng, 2008).

A large number of studies have measured service quality with the SERVQUAL model

of Parasuraman, Zeithaml, and Berry (1988). Health-care organisations have also used a

variety of measurement tools, including employee feedback for service quality (Ennis

& Harrington, 2001). Yoon, Choi, and Park (2007) suggested that employees as internal

customers should be able to assess service quality for better patient outcome, such as

short lengths of stay in the hospital, reduced hospital infection, and reduction in

medical errors. Therefore, service quality can be measured by employees who actually

provide service to the patients. In this study, service quality is measured by employees’perception (not customers’) about the quality of service provided by the hospital, as

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assume that HPWS operate and manage work processes for improving performance (e.g.

improving service quality). Therefore, employees’ perceptions of service quality (rather

than customers’ perceptions) seem to be appropriate for this research.

Customer satisfaction and customer loyalty

The health-care industry is different from other service industries because health-care

deals with the dimension of patients’ need for disease treatment and/or improved well-

being. Also, customers in the health-care system include a group of external customers

(i.e. patients, family members of patients, and potential customers) and internal customers

(i.e. employees and the employer). As patients rarely act alone in their purchasing

decisions about care providers’ service (e.g. hospitals and physicians), concerning

disease treatment and after-care service, all members of the customer group are important

for the hospital (Bohmer, 2001). In addition, patients may want to receive a specific treat-

ment, care, or information about a disease they have received from the media or heard

from their family members and friends. In this study, however, the customer is limitedto patients and their family members.

Customer satisfaction is defined as the pleasurable emotional state of customers’ feel-

ings based on their experience from the service received in an organisation (Anderson,

Fornell, & Lehmann, 1994; Fornell, 1992). It has been empirically demonstrated that cus-

tomer satisfaction affects business performance (Mittal & Kamakura, 2001; Nagar &

Rajan, 2005) and customer loyalty (Stank, Goldsby, & Vickery, 1999; Verhoef, 2003).

Highly satisfied customers are more likely to purchase goods and services offered by

the same organisation (Anderson et al., 1994; Gronholdt, Martense, & Kristensen,

2000). Customer satisfaction also plays a critical role in improving the reputation and

the image of the organisation through word of mouth (WOM) of satisfied customers.Measurement of patient or customer satisfaction is important, especially in the health-

care industry (Friesner, Neufelder, Raisor, & Bozman, 2008). Hospitals strive to increase

patient satisfaction and secure a growing number of loyal customers. Since satisfied

patients tend to reuse (i.e. revisit or repurchase) the hospital service, repeat patients are

able to receive improved care as medical staff searches for better ways of treatment

and/or diagnosis for patients’ diseases. Herzlinger (2006) suggested that patients enjoy

sharing their experience and information on treatment with other people. Also, patients’

feelings about the hospital affect their level of satisfaction (Herzlinger, 2006). Positive

WOM from satisfied patients can create opportunities to attract potential customers to

use the hospital service, which results in improved performance of the hospital.

Customer satisfaction about health care can be measured by the perceived quality of

care (e.g. treatment, hospital selection, and satisfaction with the after-care treatment

and/or service) (Doyle & Ware, 1997; Parasuraman et al., 1988; Zifko, Georgette, &

Robert, 1997), communication (Parasuraman et al., 1988; Zifko et al., 1997), and trust

(Doyle & Ware, 1997; Parasuraman et al., 1988; Zifko et al., 1997).

Customer loyalty is defined as prospects of future repurchase or renewal by customers

for an organisation (Andreassen & Lindestad, 1997). Loyal customers help promote the

organisation and its offerings through favourable WOM and recommendations directly

or indirectly (Heskett, Sasser, & Schlesinger, 1997; Heskett, Thomas, Loveman, Sasser,

& Schlesinger, 1994). Thus, business performance of the organisation improves through

increased sales of products and services. Therefore, hospital mangers should understandhow customer loyalty is influenced by the quality of care provided, and strive to keep



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In the study, the measurements for customer satisfaction were modified based on the

previous studies of Parasuraman et al. (1988), Homburg and Stock (2004), Chung and Lee

(2005), Hay and Hill (2006), Friesner et al. (2008), and Yee et al. (2008). This study

adapted measurement items of the customer loyalty suggested by Chung and Lee

(2005) and Hay and Hill (2006).

Research model and hypotheses

Figure 1 shows the proposed research model describing how health-care HPWS affect

employee reaction, service quality, customer satisfaction, and customer loyalty. The pro-

posed research model is based on paired data of employees (i.e. care team members) and

their customers as patients and/or patients’ family members. To enhance the generalisabil-

ity of our findings, data were collected from randomly selected hospitals.

Organisations implementing HPWS practices invest significantly in HR so that their

employees are well trained and skilled to perform their work (Becker & Huselid, 1998;

Michie & West, 2004). In other words, HPWS help enhance employee skills andimprove organisational performance through employees’ attitudes and motivation.

A high level of positive employee reaction is expected when there exists a high level of

employee empowerment (Peccei & Rosenthal, 2001), which in turn leads to motivation

and positive response of employees. In summary, HPWS may affect employee reaction

(e.g. motivation and response) and service quality, such as the improved quality of care

in the health-care system. Therefore, the following hypotheses are proposed:

H1: HPWS will positively affect employee reaction. H2: HPWS will positively affect service quality.

Employee satisfaction is the result of an organisation’s support policy (Heskett et al.,

1997; Rodney & Bannister, 2001), which would lead to improved customer satisfaction. Inother words, higher quality of service leads to a higher level of customer satisfaction

through the care and/or treatment activities of health-care providers (Heskett et al., 1994).

The service quality is a CSF for improving customer satisfaction, as supported by a

number of service quality studies (Hallowell et al., 1996; Heskett et al., 1994; Zeithaml,

Berry, & Parasuraman, 1996). There is a positive relationship between customer satisfac-

tion and loyalty (Andreassen & Lindestad, 1997; Fornell, 1992). Satisfied customers are

more likely to have a positive attitude towards the organisation, provide favourable

WOM to potential customers, build customer loyalty, and improve performance (Hay &

Hill, 2006; Heskett et al., 1994). Customer satisfaction directly affects behavioural inten-

tion for repurchases (Andreassen & Lindestad, 1997; Oliver, 1997). Consequently,employee reaction and service quality are CSFs for improving customer satisfaction. Sat-

isfied customers tend to be loyal customers for the organisation. Therefore, the following

hypotheses are proposed:

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H3: Employee reaction will positively affect customer satisfaction. H4: Service quality will positively affect customer satisfaction. H5: Customer satisfaction will positively affect customer loyalty.

This study was designed to collect data from two different types of hospitals (public

and private) in order to determine whether or not there is a difference in each of the

HPWS variables. While the work environment and patient treatment protocols aresimilar in both types, the perceptions of employees regarding HPWS may be different

in public versus private hospitals. Therefore, the following hypothesis is proposed:

H6 : There will be mean differences in HPWS variables between public and private hospitals.

Research methodology

Data collection

A survey questionnaire was developed to test the proposed model. The questionnaire was

developed in English first and then translated into Korean by the operations managementfaculty in South Korea. The Korean version was translated back into English by the Amer-

ican operations management experts who are bilingual. The two English version question-

naires had no significant difference. An initial questionnaire for employees was tested in a

pilot survey involving 35 employees in five departments of a hospital in South Korea.

Another initial questionnaire for patients and/or patients’ families was tested in a pilot

survey involving 35 patients in one of the hospitals in South Korea. Participation in this

survey was totally voluntary.

In this study, we selected four hospitals for data collection: two private and two public

hospitals. Large hospitals (i.e. more than 500 beds) were selected for data collection, since

most HPWS are practised by large organisations (Appelbaum et al., 2000; Ramsay, Scho-larios, & Harley, 2000). Scotti et al. (2007) examined not-for-profit hospitals, because they

focus on ‘linking work environment to customer satisfaction’ as HPWS. Thus, they

suggested that future research would need to compare, public and private, not-for-profit

and for-profit hospitals. The hospital type and the number of beds in the hospital are

two important factors since HPWS generally operate in large hospitals. In HPWS, there

was no difference between high-skilled and low-skilled tasks for improving organisational

performance (Harley et al., 2007). Therefore, two private and two public hospitals with

more than 500 beds, each hospital with five departments, were selected for this study.

To have about an equal number of participants in each hospital, data were collected

from a care team member and a patient or the patient’s family member as pairs. Three

hundred questionnaires (five hospitals × 60) were distributed to care team members

(e.g. doctors, nurses, pharmacist, administrator, and technicians) who have frequent con-

tacts with patients. We contacted a manager of each department for data collection, and

then questionnaires were randomly distributed to care team members in each department.

We received 202 (67.3%) responses. Returned questionnaires with incomplete or missing

items were removed. The final sample of 196 (65.3%) valid returned questionnaires was

used for analyses.

A special process was used to collect data for this study. First, to collect data from the

participating patients: (1) we met with the patients immediately after their contact was

completed with a doctor, nurse, pharmacist, administrator, or technician, and we requested

their cooperation in responding to our survey questionnaire; (2) if the patient agreed to par-ticipate, the questionnaire was filled out in about 15–20 min. Second, to collect data from



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study, to fill out the questionnaire for each patient (they were requested to complete the

questionnaire on the same day of their contact with the patient); (2) the questionnaire

completed by a patient was matched with the one filled out by an employee to make a

paired set to minimise serious sampling bias.

The participating care team members’ characteristics are as follows: 53.6% of the

respondents were from private hospitals, while 46.4% were from public hospitals.As shown in Table 1, the majority of the customer respondents had experience of receiving

medical treatment and/or diagnosis in the past in the participating hospital (65.8%), while

34.2% did not. It means that 34.2% of the participating customers were first-time visitors.

For the patients or patients’ family members, homemaker (33.7%) was most prevalent,

followed by student (12.8%), business person (12.2), and office worker (8.2%).

In this study, we asked two kinds of questions to measure employees’ attitudes and

feelings about their hospital and important factors for their job satisfaction using seven

Table 1. Characteristics of the respondents.

Employee respondents’ characteristics Customer respondents’ characteristics

Items Frequency (%) Items Frequency (%)

Gender GenderMale 72 (36.7) Male 88 (44.9)Female 124 (63.3) Female 108 (55.1)

Age AgeRange 23– 57 Range 20–67

Work experiences in thishospital (in years)

Occupations

≤3 49 (25.0) Homemaker 66 (33.7)3, and ≤10 61 (31.1) Student 25 (12.8)10, and ≤20 61 (31.1) Business person 24 (12.2).20 16 (8.2) Office worker 19 (9.7)Missing 9 (4.6) Professional 16 (8.2)Total 196 (100.0) Sale and service 11 (5.6)

Position Administrator 7 (3.6)Physician 26 (13.3) Technician 5 (2.6)Nurse 51 (26.0) Manufacturing 2 (1.0)Medical technician 58 (29.6) Others 15 (7.6)Administrator 49 (25.0) Missing 6 (3.0)Pharmacist 12 (6.1) Total 196 (100.0)Total 196 (100.0)

Willingness to use orrecommend their ownhospital

Medical care experiences in thepast at this hospital

Yes 163 (83.2) Yes 129 (65.8)No 33 (16.8)

Ranking of items for jobsatisfactionSalary 84 (42.9)Promotion 52 (26.5) No 67 (34.2)Working time 26 (13.3)Compensation 6 (3.1)Bonus 4 (2.0)

Relationship 2 (1.0)Others 2 (1.0)Missing 20 (10 2)

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measurement items as ranking of items. Overall, employees were loyal to their respective

hospital, as 83.2% answered that if they or their family members need care, they would

visit their hospital for treatment, and that they were willing to recommend their hospital

to others. In ranking the seven items for job satisfaction, respondents seemed to consider

salary (42.9%) as the most important followed by promotion (26.5%), working schedule

(13.3%), and compensation (3.1%). Occupations of the employee respondents were asfollows: nurse, 26.0%; administrator, 25.0%; medical technician, 29.6%; physician,

13.3%; and pharmacist, 6.1%.

Variables

The questionnaire utilised five-point Likert scales to measure the main constructs. Scales

to measure each of the constructs were developed based on prior studies as much as poss-

ible. Some measures were modified to adapt to this research.

We acknowledge that the approach we used to obtain dyadic data might have brought

the systematic bias problem in the level of customer satisfaction and customer loyalty,since customers were selected in the hospital. The customers might have thought that

they should provide favourable comments about the hospital. It would lead to a positive

bias. According to Homburg and Stock (2004), different constructs, which are measured

with data collected from different parts (i.e. two parts – employees and customers),

would lead to a generally higher level of the dependent variable (i.e. customer loyalty

in this study). However, a positive bias would not affect the strength and significance of

relationships between constructs, because the causal modelling approach used in this

study for data analysis was based on the covariance between the measurements

(Homburg & Stock, 2004).

As mentioned above, different constructs in the research model were measured withthe data obtained from both sides of the pair. HPWS, employee reaction, and service

quality were measured on the basis of the care team members’ responses, while customer

satisfaction and customer loyalty were based on data collected from the customers as

patients and/or patients’ family members. As shown in Table 2, the mean for each variable

ranged from 2.58 (CP1) to 3.95 (COMM3), and the standard deviation ranged from 0.62

(COMM1) to 1.17 (CP2).

This model consists of five major components: HPWS, employee reaction, service

quality, customer satisfaction, and customer loyalty. HPWS is a multidimensional

construct with the second-order latent variables in three dimensions: training and education,

communication, and compensation. The customer satisfaction is a multidimensional

construct with the second-order latent variables in three dimensions: quality, trust, and

communication. On the other hand, employee reaction, service quality, and customer

loyalty were assessed by measurement items.

Reliability represents the variance of measurement values resulting from repeat

measurement of the same concept. It is related to non-systematic error that can be

expressed as stability, consistency, predictability, and accuracy. Reliability was tested

based on Cronbach’s a values (Table 2). All of the coefficients for the constructs exceeded

the threshold value of 0.70 for exploratory constructs (Nunnally, 1978). In the reliability

test, Cronbach’s a for HPWS was the highest (0.89), and the employee reaction was

the lowest (0.77). All of the Cronbach’s a for the five latent variables were significant

at p , 0.05.Validity refers to the accuracy of a measure. Confirmatory factor analysis (CFA) is a



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Table 2. Items of measurements and results of reliability.

Component Variable (Likert-type five-point scale, 1 ¼ very bad;

HPWS Training and education(ED)

Opportunities for education and training (ED1) Training for current and future skills (ED2) Overall support for education and training (ED3)

Communication (CO) Employee suggestion systems (CO1) Communication network (CO2) Open communication with supervisors or colleagues (CO

Compensation (CP) Merit-based bonus (CP1) Level of pay is higher than that of other hospitals of about Equitable rewards system (CP3)

Employee reaction Employee reaction (ER) My obligation has been fulfilled (ER1) Have fulfilled my obligation during my task (ER2)

My organisation has fulfilled all of its obligations (ER3) Service quality Service quality (SQ) A good health-care environment for providing treatment/

Our patients trust our hospital (TRU) We are very pleased with our services delivered to patien

Customer satisfaction(CS)

Quality Well satisfied with the degree of treatment (Q1) Well satisfied with the degree of hospital selection (Q2) The overall degree of satisfaction after treatment (Q3)

Trust Delivers on its promises to the patient (TR1) Explanation of follow-up care opportunities (TR2) Degree of belief patients develop in doctors (TR3)

Communication

(COMM)

Understanding the degree of the patient’s requirements (C

Concerns for individual patients (COMM2) Quickly responding to the patient’s complaints or concern

Customer loyalty (CL) Customer loyalty(CL) Would you come to this hospital again? (LOY1) Would you recommend this hospital to your friends? (LOOverall, are you satisfied with the hospital service rather

hospital service? (LOY3)


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can provide evidence of the convergent and discriminant validity of theoretical constructs

(Brown, 2006). The statistics of CFA are shown in Table 3 and Figures 2–4. As shown in

Figure 4, there are measurement models: employee reaction, service quality, and customer

loyalty. The standardised factor loading and t -value for measurement variables on SEM

analysis using the M+5.1 program are presented in Table 3. All variables proposed in

the study were statistically significant at the 0.05 level, with the range of the standardisedfactor loading from 0.61 to 0.97.

Based on a recommendation by Brown (2006), the CFA method is used. The measure-

ment model has good fits in first order: x 2(288) ¼ 510.148, p , 0.0000, comparative fit

index (CFI ¼ 0.925), Tucker–Lewis index (TLI ¼ 0.914), root mean square error of

approximation (RMSEA ¼ 0.063), and standardised root mean square residual (SRMR

¼ 0.049), and in second order: x 2(308) ¼ 582.351, p , 0.000, CFI ¼ 0.913, TLI ¼

0.901, RMSEA ¼ 0.067, and SRMR ¼ 0.060.

The bottom part in Table 4 presents the square roots of average variances extracted

(AVE) for latent variables, while the off-diagonal elements are the correlation coefficients

between latent variables. For adequate discriminant validity, the square root of AVE of any latent variable should be greater than the correlation between the particular latent

variable and other latent variables (Barclay, Thompson, & Higgins, 1995). The statistics

shown in Table 4 satisfy this requirement, lending evidence to the discriminant validity.

Also, the results of the correlation between each variable are shown in Table 4.

To use a second-order factor, Beltrán-Martı́n et al. (2008, p. 1025) suggested the fol-

lowing: ‘(a) each observed variable will have a nonzero loading on the factor, (b) error

Table 3. Fit indices for CFAs.

Measurement model x 2

df p-Value CFI TLI RMSEA SRMR

First-order CFAs 510.148 288 0.000 0.929 0.914 0.063 0.049Second-order CFAs 582.351 308 0.000 0.913 0.901 0.067 0.060



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terms associated with each observed variable will be uncorrelated, (c) the first-order

factors will be correlated, and (d) covariation among the first-order factors and the obser-

vable variable will be explained fully by their regression onto the second-order factor’.

In this model, HPWS and customer satisfaction are intercorrelated latent variables that

are measured by the second-order factor method using SEM. To measure a second-order

factor, the first-order factors operate as dependent variables. It means that their variances

and covariances are no longer the estimated parameters in the model (Beltrán-Martı́n et al.,

2008). The HPWS second-order CFAs are indicated in Figure 2. These results provide an

Figure 4. Measurement models of CFAs of ER, SQ, and CL.

Figure 3. The second-order CFAs of customer satisfaction.

Table 4. Correlation matrix and AVE.

Components HPWS ER SQ CS CL

HPWS 1ER 0.574∗∗ 1SQ 0.522∗∗ 0.376∗∗ 1CS 0.493∗∗ 0.452∗∗ 0.715∗∗ 1CL 0.669∗∗ 0.440∗∗ 0.416∗∗ 0.390∗∗ 1CR 0.804 0.542 0.658 0.847 0.697AVE 0.925 0.777 0.852 0.941 0.873Sqrt (AVE) 0.961 0.881 0.923 0.970 0.934

CR (critical ratio) ¼

(factor loading2

)/(

(factor loading2

) +

(error)).AVE ¼

(factor loading)2 /(

(factor loading)2 +

(error)).

∗∗ p , 0.01.

28 S.M. Lee et al.


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evidence of an internal fit among the HPWS dimensions. Also, customer satisfaction

second-order CFAs (Figure 3) indicate the existence of an internal fit among the customer

satisfaction dimensions.

As shown in Figure 2, single-headed arrows leading from the second-order factor

(HPWS) to its first-order factors (ED, CO, and CP) indicate the prediction of these dimen-

sions. Also, in Figure 3, arrows leading from customer satisfaction (CS) to each of its first-order factors (quality, trust, and communication) show the prediction of these dimensions.

Consequently, fit statistics related with this model confirm the proposed structure of

HPWS and customer satisfaction constructs (Table 3 and Figures 2 and 3). The suggestions

of Beltrán-Martı́n et al. (2008) for using the second-order factor for HPWS and customer

satisfaction were satisfied (Figures 2 and 3). As shown in Figure 4, the standardised

regression weights of CFAs of ER, SQ, and CL were all greater than 0.6.

Results

SEM and t -test were used to test the hypotheses. M+5.1 and SPSS 17.0 program werechosen for this study. This section presents the results of hypothesis tests including the

standardised coefficient of each path in the model. The results of goodness-of-fit test for

the study model are summarised in Table 5. The value of chi-square (x 2) was 671.652,

degrees of freedom (df ) 313, CFI 0.910, TLI 0.892, and p-value 0.000. Compared with

the recommended values for the goodness-of-fit tests, the values of CFI (0.910), SRMR

(0.077), RMSEA (0.068), x 2 (671.652), and p-value (0.000) were all satisfied, while

TLI (0.892) was not.

The results of significance tests for paths of the model are shown in Table 6 and

Figure 5. For H1 test, the standardised path coefficient between HPWS and employee reac-

tion was 0.701 and statistically significant at the 0.001 level. Thus, H1 was supported.

Table 5. The results of goodness-of-fit test.

Model x 2 df p-Value CFI TLI SRMR RMSEA

Model 671.652 313 0.000 0.910 0.892 0.077 0.068Recommended value .0.9 .0.9 ,0.08 ,0.08

Table 6. The results of significance test of the model.

PathPath

coefficient SEt -

Value p-Value Hypothesis

HPWS employee reaction 0.701 0.060 11.771 0.000∗∗∗ Supported H1HPWS service quality 0.676 0.054 12.537 0.000∗∗∗ Supported H2Employee reaction customer

satisfaction0.187 0.066 2.879 0.004∗∗ Supported H3

Service quality customersatisfaction

0.855 0.049 17.434 0 .000∗∗∗ Supported H4

Customer satisfaction customerloyalty

0.560 0.061 9.155 0.000∗∗∗ Supported H5

Mean differences of HPWS variables between public and private

hospitals

0.000∗∗∗ Supported H6

∗∗ p , 0.01.



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Improving employee perceptions of HPWS components, such as perceptions of organis-

ational training and education, communications, and compensation, are associated with

higher levels of employee reaction effectively fulfilling work obligations by the employeeand the organisation.

For H2 test, the standardised path coefficient between HPWS and the service quality

was 0.676 and statistically significant at the 0.001 level. H2 was supported. High levels of

employee perceptions regarding HPWS components are associated with employee percep-

tions of service quality. It means that organisational support of employees for improving

their work is important for service quality in the health-care industry.

For H3 test, the standardised path coefficient between employee reaction and customer

satisfaction was 0.187 and statistically significant at the 0.01 level. H3 was supported.

Employee perceptions about effectively fulfilling work obligations by the employee and

the organisation are associated with customer satisfaction. According to previousstudies (Chung and Lee, 2005; Heskett et al., 1994, 1997; Rodney & Bannister, 2001),

employee satisfaction can increase customer satisfaction. Employee satisfaction positively

influences employee reaction through employee motivation (Fedor et al., 2008; Ferris

et al., 2002; Purcell & Hutchinson, 2007).

For H4 test, the standardised path coefficient between service quality and customer sat-

isfaction was 0.855 and statistically significant at the 0.001 level. Therefore, H4 was sup-

ported. This result is similar to the result reported by previous studies (Babakus et al.,

2004; Hartline & Ferrell, 1996). Employee perceptions of service quality are positively

associated with customer satisfaction.

For H5, the standardised path coefficient between customer satisfaction and customer

loyalty was 0.560 and statistically significant at the 0.001 level. Thus, H5 was supported.

Figure 5. The coefficients of the path analysis of the model.

Table 7. Mean differences of HPWS variables between public and private hospitals.

Variables of HPWS Hospital N MeanMean

differenceStandarddeviation

Standard errormean

Education (ED) Public 91 3.4029 0.4504 0.71062 0.07449Private 105 2.9524 0.67055 0.06544

Communication

(CO)

Public 91 3.3114 0.5241 0.70238 0.07363

Private 105 2.7873 0.74410 0.07262Compensation (CP) Public 91 3.1758 0.9758 0.83347 0.08737

Private 105 2.2000 0.84555 0.08252

30 S.M. Lee et al.


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Table 8. Independent samples test of HPWS.

Variables of HPWS

Levene’s test forequality of variances t -Test for equalit

F -value Significance

t -Value df

Significance(two-tailed) Mean difference

EDEqual variances assumed 1.046 0.308 4.563 194 0.000 0.45055 Equal variances not assumed 4.544 186.426 0.000 0.45055

COEqual variances assumed 0.708 0.401 5.047 194 0.000 0.52405 Equal variances not assumed 5.068 192.568 0.000 0.52405

CPEqual variances assumed 0.003 0.958 8.111 194 0.000 0.97582 Equal variances not assumed 8.120 190.796 0.000 0.97582


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In most of the previous studies, a strong relationship between service quality and customer

satisfaction was reported. Also, customer satisfaction has a strong relationship with custo-

mer loyalty. This study has a similar result as previous studies (Anderson et al., 1994;

Gronholdt et al., 2000; Stank et al., 1999; Verhoef, 2003). Thus, it is evident that satisfied

customers are more likely to be repeat customers.

For H6 , the t -test assessed whether the means of the two groups were statisticallydifferent from each other as HPWS. The results of the t -tests are shown in Tables 7

and 8. The comparison between the public and private hospitals indicates that there

were significant differences in HPWS variables: education (t ¼ 4.544, p ¼ 0.000), com-

munication (t ¼ 5.068, p ¼ 0.000), and compensation (t ¼ 8.120, p ¼ 0.000). Therefore,

H6 was supported (Table 6). HPWS variable in the public hospitals scored higher than

those in the private hospitals.

As shown in Tables 7 and 8, employees of public hospitals may have more educational

opportunities to improve their work skills and other support from their hospitals. Data in

our study indicate that public hospitals showed higher levels of both communication and

compensation as well. Harley et al. (2007) reported that in HPWS, there was no differencebetween high-skilled and low-skilled tasks for improving organisational performance.

Table 6 presents the result of significance test for the research model, as well as the

summary of the hypothesis test.

Conclusions

Today, the medical service industry is the focus of reform throughout the world. Medical

leaders and managers believe that improving quality of care, reducing medical error, and

cost containment can happen through better systems and/or technologies. Medical service,

however, is a system that can best be characterised as follows: by the people, for thepeople, and of the people. It means that employees, especially medical staffs, are of critical

importance in the health-care system.

Our study proposed a research model to investigate how HPWS influence customer

satisfaction and customer loyalty for health-care organisations. The six hypotheses in

this model were tested using data collected from 196 pairs of respondents at four hospitals

in South Korea.

The results of the study shed new insights about how hospitals can improve their oper-

ations, customer satisfaction, and customer loyalty through HPWS. Perhaps, the most

notable findings of our study are that health-care HPWS are associated with improved

employee reaction (0.701) and improved service quality (0.676). This result seems reason-

able in that all of the efforts to improve customer satisfaction and customer loyalty are

related to perceptions and attitudes of medical staff. Thus, it is essential for hospitals to

improve employee reaction to organisational support for their work through training

and education, communication, and compensation.

The health-care industry is a labour-intensive industry. From the results (Table 1), we

noticed that salary and promotion were ranked first and second, respectively, as important

factors for job satisfaction among the seven items presented in the study. Therefore, organ-

isation leaders and managers should focus on effective HRM, especially providing proper

compensation to improve employees’ job satisfaction.

There are some limitations of our study. First, this study considered a customer and an

employee as one set for the data. Since the study has shown that HPWS has higher scoresin public hospitals than in private ones, differences between the two hospital groups were

32 S.M. Lee et al.


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comes from the method of collecting data from both the patients and employees. Second,

the survey data used in this study were collected from four hospitals with more than 500

beds in South Korea. Since there are many small-sized hospitals, a comparative study of

small versus large in terms of HPWS might yield interesting results. Third, there was a

time lapse between contact and completion of the survey for both groups. Patients com-

pleted the questionnaire immediately after the contact with employees, while employeeswere given more time to complete their questionnaire on the same day. Thus, the gener-

alisability of this study’s results may be limited.

Future research should consider our limitations mentioned above and also include

cross-cultural study using different sizes and types of hospitals (e.g. medical tourism

hospitals) in a wider range of countries. In addition, as organisational culture in each

department of a hospital might be different, such sub-culture of each department should

be incorporated in the future study. Also, to reduce potential bias, a systematic approach,

such as the person-by-person method, is needed. Future research might gain insight from

comparing hospitals that have been characterised as high– low-performance facilities

before data collection. The analysis of the data that are distributed and collected accordingto these characteristics, including a longitudinal investigation, may provide outcomes that

can be more useful for strategic management in the health-care industry.

References

Anderson, E., Fornell, C., & Lehmann, D. (1994). Customer satisfaction, market share, and profit-ability: Findings from Sweden. Journal of Marketing, 58(3), 53–66.

Andreassen, T., & Lindestad, B. (1997). Customer loyalty and complex services: The impact of cor-porate image on quality, customer satisfaction and loyalty for customers with varying degreesof Service expertise. International Journal of Service Industry Management , 8(4), 1–32.

Appelbaum, E., Bailey, T., Berg, P., & Kalleberg, A. (2000). Manufacturing advantage: Why high- performance work systems pay off . Ithaca, NY: ILR Press.

Babakus, E., Bienstock, C., & Scotter, J. (2004). Linking perceived quality and customer satisfactionto store traffic and revenue growth. Decision Sciences, 35(4), 713–737.

Baker, T., & Taylor, A. (1997). Patient satisfaction and service quality formation of customers’future purchase intentions in competitive health service settings. Health MarketingQuarterly, 15(1), 1–15.

Barclay, D., Thompson, R., & Higgins, C. (1995). The partial least squares (PLS) approach to causalmodeling: Personal computer adoption and use as an illustration. Technology Studies, 2(2),285–309.

Becker, B., & Huselid, M. (1998). High performance work systems and firm performance: A syn-thesis of research and managerial implications. In G.R. Ferris (Ed.), Research in personnel

and human resource management (Vol. 16, pp. 53–101). Greenwich, CT: JAI Press.Beltrán-Martı́n, I., Roca-Puig, V., Escrig-Tena, A., & Bou-Llusar, J. (2008). Human resource flexi-

bility as a mediating variable between high performance work systems and performance. Journal of Management , 34(5), 1009–1044.

Berg, P., & Frost, A. (2005). Dignity at work for low wage, low skill service workers. Relations Industrielles/Industrial Relations, 60(4), 657–682.

Bohmer, R. (2001). The customers in health care. Harvard Business School, Note 600-118, 1–16.Bowen, D., & Ostroff, C. (2004). Understanding HRM-firm performance linkages: The role of the

‘strength’ of the HRM system. Academy of Management Review, 29(2), 203–221.Boxall, P., & Macky, K. (2007). High-performance work systems and organizational performance:

Bridging theory and practice. Asia Pacific Journal of Human Resources, 45(3), 261–270.Brown, T. (2006). Confirmatory factor analysis for applied research (pp. 5–71). New York, NY: The

Guilford Press.Chung, S., & Lee, D. (2005). Impacts of TQM activities on employee’s satisfaction in the support of task process, and on business performance in medical service industry. Journal of Korea



18/21

Dean, A. (2004). Links between organizational and customer variables in service delivery: Evidence,contradictions, and challenges. International Journal of Service Industry Management , 15(4),332–350.

Delaney, J., & Huselid, M. (1996). The impact of human resource management practices onperceptions of organizational performance. Academy of Management Journal, 39(4),949–969.

Doyle, B., & Ware, J. (1997). Physician conduct and other factors that affect consumer satisfactionwith medical care. Journal of Medical Education, 52(10), 793–801.

Eisenberger, R., Armeli, S., Rexwinkel, B., Lrvch, P., & Rhoades, L. (2001). Reciprocation of perceived organizational support. Journal of Applied Psychology, 86, 42–51.

Ennis, K., & Harrington, D. (2001). Quality management in Irish healthcare. The Service Industries Journal, 21(1), 149–168.

Evans, W., & Davis, W. (2005). High performance work systems and organizational performance:The mediating role of internal social structure. Journal of Management , 31(5), 758–775.

Fedor, D., Maslyn, J., Farmer, S., & Bettenhausen, K. (2008). The contribution of positive politics tothe prediction of employee reactions. Journal of Applied Social Psychology, 38(1), 76–96.

Ferris, G., Adams, G., Kolodinsky, R., Hochwarter, W., & Ammeter, P. (2002). Perceptions of organizational politics: Theory and research directions (pp. 179–254). Amsterdam: JAI/

Elsevier Science.Fornell, C. (1992). A national customer satisfaction barometer: The Swedish experience. Journal of

Marketing, 92(1), 6–21.Friesner, D., Neufelder, D., Raisor, J., & Bozman, C. (2008). When patients are already satisfied: A

continuous process improvement approach. Hospital Topics: Research and Perspectives on Healthcare, 87 (1), 24–40.

Gephart, M.A., & Van Buren, M.E. (1996). Building synergy: The power high-performance work systems. Training & Development , 50, 22–36.

Goldstein, S. (2003). Employee development: An examination of service strategy in a high-contactservice environment. Production and Operations Management , 12(2), 186–203.

Gronholdt, L., Martense, A., & Kristensen, K. (2000). The relationship between customer satisfac-tion and loyalty: Cross-industry differences. Total Quality Management , 11(8), 509–514.

Hallowell, R., Schlesinger, L., & Zornitsky, J. (1996). Internal service quality, customer and jobsatisfaction: Linkages and implications for management. Human Resource Planning, 19(2),20–31.

Harley, B., Allen, B., & Sargent, L. (2007). High Performance work systems and employee experi-ence of work in the service sector: The case of aged care. British Journal of Industrial

Relations, 45(3), 607–633.Harmon, J., Scotti, D., Behson, S., Farius, G., Petzel, R., Neuman, J., & Keashly, L. (2003). Effects

of high-performance work systems on employee satisfaction and services costs in Veteranshealthcare. Journal of Healthcare Management , 48(6), 393–405.

Hartline, M., & Ferrell, O. (1996). The management of customer contact service employees: Anempirical investigation. Journal of Marketing, 60(4), 52–70.

Hay, J., & Hill, A. (2006). Service guarantee strength: The key to service quality. Journal of Operations Management , 24(6), 753–764.

Herzlinger, R. (2006). Innovating in health care-framework. Harvard Business School, Note306–342, 1–54.

Heskett, J., Sasser, W., & Schlesinger, L. (1997). The service profit chain: How leading companieslink profit and growth to loyalty, satisfaction, and value . New York, NY: The Free Press.

Heskett, J., Thomas, O., Loveman, G., Sasser, W., & Schlesinger, L. (1994). Putting the service-profit chain to work. Harvard Business Review, 72, 164–174.

Homburg, C., & Stock, R. (2004). The link between salespeople’s job satisfaction and customersatisfaction in a business-to-business context: A dyadic analysis. Journal of the Academy of

Marketing Science, 32(2), 144–158.Huselid, M. (1995). The impact of human resource management practices on turnover, productivity,

and corporate financial performance. Academy of Management Journal, 38(3), 635–672.Kling, J. (1995). High performance work systems and firm performance. Monthly Labor Review,

118, 29–36.Lawler, E. (2005). Creating high performance organisations. Asia Pacific Journal of Human

Resources 43(1) 10–17

34 S.M. Lee et al.


19/21

Meyer, S., & Collier, D. (2001). An empirical test of the causal relationships in the Baldrige healthcare pilot criteria. Journal of Operations Management , 19(4), 403–425.

Michie, S., & West, M. (2004). Managing people and performance: An evidence based framework applied to health service organizations. International Journal of Management Reviews,5 – 6 (2), 91–111.

Milstein, A., & Colla, C.H. (2009). Tracking the Contribution of U.S. Health Care to the GlobalCompetitiveness of American Employers and Workers: 2009 Business Roundtable HealthCare Value Comparability Study. Mercer Health & Benefits, February 28.

Milstein, A., & Darling, H. (2009). Better U.S. health care at lower cost. Issues in Science and Technology, The University of Texas at Dallas, Dec. 21. Retrieved from http://www.issues.org/26.2/milstein.html

Milstein, A., & Hoverman, A. (2009). 2009 Business roundtable health care value comparabilitystudy. Mercer Health & Benefits, Business Roundtable.

Mittal, V., & Kamakura, W. (2001). Satisfaction, repurchase intent, and repurchase behaviour:Investigating the moderating effect of customer characteristics. Journal of Marketing

Research, 38(1), 131–142.Nagar, V., & Rajan, M. (2005). Measuring customer relationships: The case of the retail banking

industry. Management Science, 51(6), 904–920.

Nunnally, J. (1978). Psychometric theory (2nd ed., pp. 245–246). New York, NY: McGraw Hill.Olden, P., & McCaughrin, W. (2007). Designing healthcare organizations to reduce medical errors

and enhance patient safety. Hospital Topic: Research and Perspectives on Healthcare, 85(4),4–9.

Oliver, R. (1997). Satisfaction: A behavior perspective on consumer . New York, NY: McGraw-Hill.Parasuraman, A., Zeithaml, V.A., & Berry, L.L. (1988). SERVQUAL: A multiple-item scale for

measuring customer perception of service quality. Journal of Retailing, 64(1), 12–40.Peccei, R., & Rosenthal, P. (2001). Delivering customer-oriented behavior through empowerment:

An empirical test of HRM assumptions. Journal of Management Studies, 38(6), 831–857.Porter, M., & Teisberg, E. (2004). Redefining competition in health care. Harvard Business Review,

82(6), 64–76.Purcell, J., & Hutchinson, S. (2007). Front-line managers as agents in the HRM performance causal

chain: Theory, analysis and evidence. Human Resource Management Journal, 17 (1), 3–20.Ramsay, H., Scholarios, D., & Harley, B. (2000). Employees and high-performance work systems:Testing inside the black box. British Journal of Industrial Relations, 28(4), 501–531.

Rodney, M., & Bannister, A. (2001). Business performance measurement and change managementwithin a TQM framework. International Journal of Operations & Production Management ,21(1/2), 88–107.

Rust, R., & Zahorik, A. (1993). Customer satisfaction, customer retention, and market share. Journalof Retailing, 69(2), 193–215.

Scotti, D.J., Driscoll, A.E., Harmon, J., & Behson, S.J. (2007). Links among high-performance work environment, service quality, and customer satisfaction: An extension to the healthcare sector.

Journal of Healthcare Management , 52(2), 109–124.Stank, T.P., Goldsby, T.J., & Vickery, S.K. (1999). Effect of service supplier performance on satis-

faction and loyalty of store managers in the fast food industry. Journal of Operations Management , 17 (4), 429–447.

Stock, G.N., McFadden, K.L., & Gowen, C.R., III (2007). Organizational culture, critical successfactors, and the reduction of hospital errors. International Journal of ProductionEconomics, 106 (2), 368–392.

Tucker, A. (2004). The impact of operational failures on hospital nurses and their patients. Journal of Operations Management , 22(2), 151–169.

Verhoef, P. (2003). Understanding the effect of customer relationship management efforts oncustomer retention and customer share development. Journal of Marketing, 67 (4), 30–45.

Whitener, E. (2001). Do ‘high commitment’ human resource practices affect employee commit-ment? A cross level analysis using hierarchical linear modeling. Journal of Management ,27 (5), 515–535.

Wright, P., Gardner, T., Moynihan, L., & Allen, M. (2005). The relationship between HR practices

and firm performance: Examining causal order. Personnel Psychology, 58, 409–446.Yee, R., Yeung, A., & Cheng, T. (2008). The impact of employee satisfaction on quality and profit-

ability in high-contact service industries Journal of Operations Management 26(5) 651–668



20/21

Yoon, S.J., Choi, D., & Park, J. (2007). Service orientation: its impact on business performance in themedical service industry. The Service Industries Journal, 27 (4), 371–388.

Zeithaml, V., Berry, L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31–46.

Zifko, B., Georgette, M., & Robert, F. (1997). Managing perceptions of hospital quality. Marketing Health Service, 17 (1), 28–35.

36 S.M. Lee et al.


21/21

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