Management commitment to service quality and service recovery ...

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A study of frontline employees in public and private hospitals Michel Rod Department of Marketing, Sprott School of Business, Carleton University, Ottawa, Canada, and

Nicholas J. Ashill Department of Marketing, School of Business and Management, American University of Sharjah, Sharjah, United Arab Emirates Abstract Purpose – The purpose of this paper is to investigate a model of management commitment to service quality (MCSQ) and service recovery performance in the context of public and private hospitals in New Zealand. Design/methodology/approach – In a cross-sectional survey grounded in Bagozzi’s reformulation of attitude theory, frontline hospital employees (FHEs) were asked about how MCSQ impacted on their service recovery performance in both the public and private sectors. Findings – The results of the study suggest that the relationship between MCSQ and service recovery performance is mediated by organizational commitment. With the exception of the relationship between MCSQ and organizational commitment, there are no differences between FHEs in the private and public sectors. Originality/value – Very little attention has been given to a comparative examination of those managerial practices critical for improving frontline employee service recovery efforts in a public and private healthcare context. Our research addresses this paucity. Keywords Hospital management, Customer services quality, Job satisfaction, Hospitals, Private hospitals, New Zealand Paper type Research paper

International Journal of Pharmaceutical and Healthcare Marketing Vol. 4 No. 1, 2010 pp. 84-103 q Emerald Group Publishing Limited 1750-6123 DOI 10.1108/17506121011036042

Introduction In many western countries both the public and private sectors provide healthcare services. The public systems are generally free to the patients and the private systems are either paid for by the patients themselves or through some sort of medical insurance. Over the past 30 years, consumer dissatisfaction with long public waiting lists, public healthcare reforms, more contestable government funding of health agencies and increased growth in private health offerings, has resulted in substantive growth in the private sector (Fougere, 2001). Private healthcare settings are also more representative of a commercial environment than public health settings, given the notion of a paying customer, which historically has inferred more “right of complaint.” Public healthcare systems on the other hand, have traditionally been less focused on the needs of the customers although the increasing competitive environment has resulted in calls for

public healthcare facilities to become more efficient and offer higher quality (Wolfersteig and Dunham, 1998) while in many countries, public healthcare is transforming from philanthropic to more business-oriented service provision (Raja et al., 2007). Whether in a private or public context, a better understanding of conditions in the work environment that drive the delivery of service-quality and customer satisfaction is valuable to healthcare managers (Scotti et al., 2007). Frontline hospital employees (FHEs) in particular, play a key role in this delivery and patients will often judge their healthcare experience based on these interactions (Ashill et al., 2005). Patients who are content with their healthcare services are more likely to exhibit intentions that are favorable to the success of the particular healthcare provider, whereas patient dissatisfaction may lead to unfavorable behavioral intentions such as negative word-of-mouth or switching to alternative healthcare service providers (Osborne, 2004; Ramsaran-Fowdar, 2008). Past research indicates that managerial practices in the form of management commitment to service quality (MCSQ) are a critical determinant of service worker behavior in the workplace (Alexandrov et al., 2007; Babakus et al., 2003; Hartline and Ferrell, 1996). Babakus et al. (2003, p. 3) define MCSQ as “employees’ appraisal of an organisation’s commitment to nurture, develop, support and reward its employees to achieve service excellence.” However, very little research has examined the impact of MCSQ on FHEs’ service recovery efforts in a healthcare setting. This is especially important given that staff engagement is a critical component of service delivery in healthcare and FHEs are more engaged when they perceive management to be engaged (Kerfoot, 2007). With the preceding in mind, the purpose of this study is to examine the impact of MCSQ on FHE service recovery performance in both private and public sectors health service provision. This is one of the first attempts to undertake such research and in addition, as far as we are aware, this is the first study to directly assess the service recovery performance across a sample of public versus private sectors frontline healthcare employees. This is an important contribution given the increase in the provision of private healthcare globally and given the fact that there is empirical evidence that there are marked differences in both managerial style and organizational culture between public and private healthcare (Seren and Baykal, 2007) as well as differences in the work values between private and public sectors healthcare employees (Midttun, 2007). An additional contribution is the augmentation of the MCSQ construct to include a more complete set of relevant indicators of MCSQ in a healthcare environment. Babakus et al. (2003) identified three indicators of MCSQ in a study of retail banks. These are training, empowerment, and rewards/recognition and are identified as well-known human resource practices by Pfeffer (1994). However, we expand this set of MCSQ indicators to also include customer service orientation (Lytle et al., 1998). An organizational culture which focuses on strong customer service orientation is a must for sustaining healthy long-term relationships with customers because a strong service orientation is imperative for the creation and/or enhancement of good interactive marketing performance (Gro¨nroos, 1990; Yasin and Yavas, 1999) and is essential to maintain long-term working relationships (Boshoff and Allen, 2000; Yavas et al., 2003). Health care organizations are becoming increasingly more customer service orientated as patient satisfaction is increasingly recognized as an important quality improvement initiative (Darby and Daniel, 1999; Bendall-Lyon and Powers, 2001; Rashid and Jusoff, 2009; White, 2001). We begin the paper by outlining the conceptual model used to guide the study. We then outline the data collection procedure and the two-group analysis that we conducted.

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Following on from this, we discuss the results of the study and provide managerial implications. The research model and hypotheses We follow the lead of Babakus et al. (2003) in using Bagozzi’s (1992) reformulation of attitude theory grounded in Lazarus’s (1991, 2001) cognitive appraisal theory of emotions, to create the theoretical underpinnings to our model. Drawing upon a critique of existing attitude theories (the theory of reasoned action, the theory of planned behavior and the theory of trying), Bagozzi’s framework reformulates attitude theory to posit a process of self-regulation where the individual will appraise past, present and future outcomes. The outcomes lead to emotions that then lead to coping responses (behaviors), hence the sequence of appraisal, emotional reactions, and coping responses (Schmit and Allscheid, 1995). For example, if an individual experiences a pleasant event he or she will experience a positive emotional response which then directs the individual to take the appropriate steps to attain that outcome. Thus, an individual’s cognitive evaluation of an event, outcome, and situation precedes his or her affective reaction, and it is these affective responses that play a determining role in directing individual behavior (Bagozzi, 1992). We classify management practices that embody MCSQ as appraisal variables. Consistent with Bagozzi (1992), these MCSQ appraisal variables are hypothesized to lead to an underlying emotional response or affect toward the organization. Specifically, the conceptual framework (Figure 1) examines the process through which MCSQ influences FHE job satisfaction (feelings toward the job) and organizational commitment (feelings toward the organization), and the relationship between these job attitudes and FHE service recovery performance (the abilities and actions of FHEs to resolve a service failure to the satisfaction of the patient). Ahmed and Parasuraman (1994, p. 85) defined MCSQ as “the conscious choice of quality initiatives as operational and strategic options for the firm, and engaging in activities such as providing visible quality leadership and resources.” A synthesis of Management commitment to service quality (MCSQ)

Affective outcomes

Performance outcomes

Employee rewards Organizational commitment Customer service training Service recovery performance Empowerment

Figure 1. Conceptual model of service recovery performance

Job satisfaction Customer service orientation Appraisal

Emotional response

Behavior

the services management literature (Bowen and Lawler, 1995; Tax and Brown, 1998) and the healthcare literature suggests that training (Young et al., 2009), empowerment (Steinke, 2008), rewards (Lee et al., 2006; Rad and de Moraes, 2009) and customer service orientation (Bendall-Lyon and Powers, 2001; Rashid and Jusoff, 2009) are relevant indicators of the construct and MCSQ is manifested through a simultaneous emphasis on all four variables.


Management commitment to service quality Employee rewards. The relationship between employee rewards and service performance has been shown to be a significant one (Parasuraman, 1987). Notwithstanding the established literature on the potential dysfunctional effects of extrinsic rewards (see Grover and Hui, 2005, for example), we favour the position that the rewards employees receive induce them to provide higher quality services and motivates them to deal better with customer complaints (Yavas et al., 2003). For FHEs that are generally low-paid, financial reward acknowledging quality is likely to matter. In addition, the healthcare sector is likely to attract staff with more intrinsic motivation to the extent that money may not be the only reward that is valued (Mee, 1999). Thus, other non-monetary rewards are likely to be appreciated also. If FHEs perceive the rewards to be tangible then this is likely to have a significant impact on job satisfaction and commitment to the organization. Through the reward system, the management can demonstrate its commitment to service quality (Rondeau, 1994). Customer service training Poorly trained employees fail to provide a high level of service quality and deal poorly with customer complaints (Bettercourt and Gwinner, 1996; Yavas et al., 2003). It is not only important to have the right employees for the right jobs but also necessary to train these employees to deal with problems and situations that arise (Boshoff and Allen, 2000). In the context of healthcare, FHEs need to be ready to deal with customers more and more prepared to vent their frustration and anger at what they perceive to be poor service. Research shows that customer service training positively impacts upon job satisfaction as it helps employees to develop the skills to handle the service failures effectively (Babakus et al., 2003; Benoy, 1996; Schneider and Bowen, 1995). Research also shows that employees able to benefit from customer service training programs are more committed to the organization (Sweetman, 2001; Tsui et al., 1997) The presence of employee training programs sends a clear signal to FHEs that the management is committed to service quality (Babakus et al., 2003). Empowerment Empowerment is when the employees are given the opportunity and motivation to develop and make the best use of their talents (Chebat and Kollias, 2000). If management empowers employees, then the employees gain control over the delivery of the service (Hartline and Ferrell, 1996) and can provide quick, appropriate remedies to dissatisfied customers (Boshoff and Allen, 2000). Research conducted in the healthcare context shows that empowerment plays a significant role in increasing employee job satisfaction (Laschinger et al., 2001; Ugboro, 2006; Upenieks, 2003) and organizational commitment (Kuokkanen et al., 2003; Laschinger et al., 2001).

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Customer service orientation Customer service orientation is a culture in the organization stemming from policies and procedures that support behaviors of employees geared toward delivering service excellence (Lytle et al., 1998). An organizational culture with a strong customer service orientation lets the employees know that the priorities of the organization are aligned to the priorities of the FHE. Theoretically, Jaworski and Kohli (1993) have argued that employees who work in a market-oriented organization will develop a sense of pride as the organization works towards the goal of satisfying customers and will feel that they are contributing to something worthwhile, will have a sense of belongingness and, therefore, commitment to the organization. Empirically, frontline employees perceptions of service organization customer orientation have been shown to positively influence their affective organizational commitment (Karatepe et al., 2007). Thus, employees supported by such a culture will be more committed to the organization and are likely to be more satisfied in their employment. To summarize, the conceptual model in Figure 1 posits that employee rewards, customer service training, empowerment and customer service orientation together reflect the construct MCSQ. On their own these factors are insufficient to create committed and satisfied employees (Babakus et al., 2003; Boshoff and Allen, 2000), however, when implemented simultaneously they impact upon the employees’ affective states (emotional responses) and ultimately performance. Therefore, our first set of hypotheses is as follows: H1a. For both public and private sectors FHEs, there is a positive relationship between MCSQ and FHE job satisfaction. H1b. For both public and private sectors FHEs there is a positive relationship between MCSQ and FHE organizational commitment. Organizational commitment Organizational commitment has been defined as the degree to which employees feel a sense of connection, obligation, and reward in working for the organization (Allen and Meyer, 1990). Research tells us that workers that are committed (i.e. identify and involve themselves) to their organizations perform to a higher standard (Meyer et al., 1989; Mowday et al., 1979) and with higher perceived service quality (Malhotra and Mukherjee, 2004). In the context of service recovery performance, when there is some sort of service failure then the more committed the employee is the more successful the employee should be in addressing the failure. In this way the customer will be satisfied. Thus, our next hypothesis is: H2. For both public and private sectors FHEs, there is a positive relationship between organizational commitment and service recovery performance. Job satisfaction Job satisfaction is a product of the evaluation of the job, taking into account all aspects of the job such as pay, benefits, supervisor style, communication, and discretion (Burke, 1989) and can be defined as “the favorableness or unfavorableness with which employees view their work” (Grieshaber et al., 1995, p. 18). Research suggests that there is a positive relationship between work performance and job satisfaction as well as between service quality and job satisfaction (Malhotra and Mukherjee, 2004). Further research in services suggests that job satisfaction is an antecedent of customer-oriented

behavior (Hartline and Ferrell, 1996; Yoon et al., 2001). This customer-oriented behavior is likely to include being helpful to the customer, empathising and being considerate. Service recovery involves many of these traits, therefore our final hypothesis is: H3. For both public and private sectors FHEs, there is a positive relationship between job satisfaction and service recovery performance. Public versus private sectors Although there has been little or no theoretical support advanced regarding differences between public and private sectors FHE appraisals of their organization’s commitment to service quality, there is limited empirical evidence to suggest differences may exist. In a retail banking context, Babakus et al. (2003) found that when public versus private ownership was used a control variable, it was found to be significant and their results showed that private sector FHEs had more positive perceptions of MCSQ than public sector employees. In a healthcare context, in a comparison of public versus private hospital service quality, Angelopolou et al. (1998) found patient care to be comparable but that private hospitals were better in terms of physical facilities, waiting times and admissions procedures. Many public sector hospitals are blamed and criticized for their lack of speed owing to the inflexibility of their traditional hierarchical structures in respect of their quality improvement and numerous studies have concluded that inpatients perceive public hospitals to be inferior in the quality of their service provision (Arasli et al., 2008; Kara et al., 2005; Pakdil and Harwood, 2005). As alluded to in the introduction, there is empirical evidence for the existence of differences in both managerial style and organizational culture between public and private healthcare service provision (Seren and Baykal, 2007) as well as differences in work values between private and public sectors healthcare FHEs (Midttun, 2007). These work values encompass such dimensions as professionalism, remuneration and benefits expectations as well as autonomy. Midttun (2007) found that physicians working in the private sector and physicians combining private and public work spend relatively more time on patient-assignments than their public counterparts, while public physicians allocate more time to administrative and research/educational tasks. In addition, in the context of service quality, research has shown that patients also perceive differences between public versus private sectors hospital service quality across various quality dimensions such as empathy, tangibles (equipment, facilities, hours of operation), reliability (promises versus performance), administrative responsiveness, and assurance (employee knowledge, courteousness, support) (Jabnoun and Chaker, 1993; Chowdhury, 2008) in addition to giving priority to inpatient needs, relationships between staff and patients, professionalism of staff, food and the physical environment (Arasli et al., 2008; Kara et al., 2005; Pakdil and Harwood, 2005). Against this background, we therefore tested for possible differences in the hypothesized relationships across public versus private healthcare with the expectation that the relationships between the model constructs will be stronger for FHEs in private healthcare. Research methodology Measures We adapted scales from the relevant literature for our measures. We analyzed the service recovery performance literature (Babakus et al., 2003; Boshoff and Allen, 2000;


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Lucas et al., 1990; Mowday et al., 1979; Parasuraman et al., 1990; Yavas et al., 2003) and the healthcare literature (Budge et al., 2001; Lee et al., 2003; McGillis, 2003; Rafferty et al., 2001; Weiseman et al., 1981) to find the appropriate scales to adapt. Organizational commitment was measured using three items from Mowday et al. (1979). A three-item empowerment scale was adapted from Hayes (1994). Customer service orientation was measured with five items using the customer orientation section of Narver and Slater’s (1990) market orientation measure. Finally, the items for employee rewards (three items), job satisfaction (three items), customer service training (three items), and service recovery performance (three items) were drawn from Boshoff and Allen (2000). Previous work (Bitner et al., 1994; Schneider and Bowen, 1995) has shown that the perceptions of frontline staff generally converge with that of customers, therefore we measure service recovery performance via a self-report measure. All of the items were on a five-point scale anchored by “5 – strongly agree” and “1 – strongly disagree” The measures can be seen in Appendix Table AI. Data collection Data were collected from healthcare FHEs (receptionists, ward assistants and nurses) in a convenience sample of public and private hospitals in a large New Zealand city. A total of 281 questionnaires were distributed: 152 to full-time FHEs representing a range of outpatient departments/clinics in an inner-city public hospital and 129 to full-time FHEs in four inner-city private hospitals providing both secondary services and a range of specialist tertiary services to the 135,000 people who live within their catchment area. The absence of medical staff (doctors) in the sample reflects the nature of outpatient clinical areas where the first point of contact for patients coming into the hospital typically concerns administrative matters such as managing appointment arrivals and handling non-medical issues. All of the FHEs of both the public and private hospitals spent most of their time directly dealing with patients and there was comparability across the two hospitals in terms of the types of frontline staff surveyed. The research team personally distributed questionnaires. Managers of each department informed their FHEs about the confidential and anonymous self-administered survey questionnaire and encouraged them to participate. When completing the questionnaire each FHE was asked to focus on his or her frontline duties and not issues pertaining to medical treatment (such dual roles are often performed by nurses). In terms of age and tenure, the profiles of the respondents were comparable to the population of FHEs in each of the hospitals participating in the research. By the cut-off date for collection, 186 questionnaires had been received for an overall response rate of 66 percent. Of those 186, 82 were from the private sector and 104 were from the public sector. This is a 64 percent response rate for private sector FHEs and a 68 percent response rate for public sector FHEs. In the public sector sample (n ¼ 104), the majority of respondents (80 percent) were female and in a full-time position (67 percent); 26 percent were nurses, 47 percent were administrators/receptionists and 27 percent represented other frontline positions. In the private sector sample (n ¼ 82), the majority of respondents (95 percent) were also female; 31 percent were nurses, 62 percent were administrators/receptionists, and 7 percent represented other frontline positions (mainly technical support staff). These profiles are typical of most hospital non-inpatient clinical areas (both public and private), from which data for this study was drawn. Early and late respondents were compared on all variables of interest, using traditional t-tests following Armstrong and Overton’s (1977) recommendations. Unpaired t-tests were

used to compare the group and differences were not statistically significant at the 0.05 level, indicating that there were no differences between early and late respondents. Hence, it was assumed that non-response bias was not a problem. Following the recommendation of Mentzer and Flint (1997), 30 non-respondents were also contacted and asked five questions (survey items) relating to the hypotheses. There was no statistically significant difference between the answers of respondents and non-respondents to these questions.


Non-response and common method bias We checked for non-response bias by following the recommendations of Armstrong and Overton (1977). We compared early and late respondents on all the variables of interest using t-tests. Our analysis indicated that there was no significant difference between the early and late respondents on these dimensions at the 0.05 level. Thus, we were able to conclude that non-response bias was not a problem. Owing to the self-report nature of the survey, method variance is identified as a potential issue. Spector (1987) reported that the most frequently found sources of method variance in self reports are acquiescence and social desirability bias. The survey instrument was also organized into various sections by separating the independent and dependent variables in an effort to reduce single-source method bias (Podsakoff et al., 2003). A further post hoc test for common method bias, a Harman’s (1967) one-factor test was also performed. All of the self-report items were entered into a principal components factor analysis with varimax rotation. According to this test, if a single factor emerges or one factor accounts for more than 50 percent of the variance in the variables, common method variance is present (Podsakoff et al., 2003). Our analysis showed that no general factor was present. Assessment of measures For our data analysis, we followed the steps laid out by Calantone et al. (1996) for conducting a multiple group analysis. We used EQS 6.1 for Windows. The steps laid out by Calantone et al. (1996) are a general extension of the two-step approach (Anderson and Gerbing, 1982, 1988; Bollen, 1989) with slight modifications to take account the multiple groups. We begin with a confirmatory factor analysis (CFA) for both groups individually. The purpose of these individual CFAs was to test for construct validity and to eliminate any measures with either cross-loadings or insignificant loadings. For the public hospital sample, all of the loadings of the items to the respective constructs were statistically significant ( p , 0.01) (Appendix Table AI). The results of the CFA for the public hospitals sample show a very good fit for the model (x 2 ¼ 258.165 on 209 df, comparative fit index (CFI) ¼ 0.932, non-normed fit index (NNFI) ¼ 0.918, incremental fit index (IFI) ¼ 0.936 and root mean square error of approximation (RMSEA) ¼ 0.049). As with the public hospital sample, for the private hospital sample, all of the loadings of the items to their respective constructs were statistically significant ( p , 0.01) (Appendix Table AI). The results of the CFA for the private hospital sample show another very good fit for the model (x 2 ¼ 265.707 on 209 df, CFI ¼ 0.923, NNFI ¼ 0.907, IFI ¼ 0.927 and RMSEA ¼ 0.058). These fit statistics indicate a great deal of consistency across the two models and in addition to this the two samples incorporated identical items in the models for all of the constructs. The average variance extracted scores were also above the minimum threshold of 0.5 (Hair et al., 2006)

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in both samples. Composite reliabilities ranged across both samples from 0.80 for service recovery performance to 0.90 for customer service training (Appendix Table AI). In this study, measurement invariance is limited to metric invariance (i.e. invariance of factor loadings), which indicates that members in different groups interpret and respond to measures in an identical manner (Steenkamp and Baumgartner, 1998). We conducted a two-group CFA using the private and public hospitals samples simultaneously as this would allow us to establish whether or not we had measurement equivalence across the two samples (Bollen, 1989). We ran the two-group CFA with complete constraints on the factor patterns and factor loadings. We used the Lagrange multiplier (LM) test to indicate whether any of the constraints should be released. This initial two-group CFA gave a very good overall fit (x 2 ¼ 590.201 on 456 df, CFI ¼ 0.908, NNFI ¼ 0.898, IFI ¼ 0.911, RMSEA ¼ 0.040). However, results of the LM test indicated that we should release certain constraints. We released these constraints one by one each time checking the results of the LM test to see if any more constraints should be released. The final two-group CFA had a good fit (x 2 ¼ 557.453 on 451 df, CFI ¼ 0.927, NNFI ¼ 0.918, IFI ¼ 0.930, RMSEA ¼ 0.036). The factor patterns were the same across the two groups and there was no difference in 20 out of the 22 factor loadings. This is comparable to the study by Calantone et al. (1996) that found no difference in 14 of the 16 factor loadings. From this we are able to conclude that the measurement models are invariant across the public hospital and private hospital samples (Steenkamp and Baumgartner, 1998). Structural model Our next step was to test our proposed structural model for the private and public hospitals samples individually. Through this we would be able to validate our hypothesized model from Figure 1. Although our study draws upon a small convenience sample, SEM models containing five or fewer constructs (as is the case with this research) and high item communalities (0.6 or higher) (in our research all items exhibited communalities above 0.6) can be adequately estimated with samples as small as 100-150 (Hair et al., 2006). We took the lead of Babakus et al. (2003) in using the composite scores of the items (scores summed and divided by the number of items) from customer service training, employee rewards, empowerment, and customer service orientation as indicators for the construct, MCSQ. In this way, we acknowledge the multidimensional nature of the construct (Bagozzi and Heatherton, 1994). Strong correlations among customer service training, employee rewards, empowerment and customer service orientation provided empirical justification for treating these four measures as indicators of MCSQ. We tested the individual models using EQS 6.1 for Windows. For the private hospital sample, the overall fit of the model was very good (x 2 ¼ 86.571 on 61 df, CFI ¼ 0.937, NNFI ¼ 0.919, IFI ¼ 0.939, RMSEA ¼ 0.072, standardized root mean square residual (SRMR) ¼ 0.037, goodness of fit index (GFI) ¼ 0.972). Three of the four hypothesized paths were significant and in the hypothesized direction with only the path between job satisfaction and service recovery performance not significant. For the public hospital sample, the overall fit of the model was very good (x 2 ¼ 86.915 on 61 df, CFI ¼ 0.923, NNFI ¼ 0.902, IFI ¼ 0.927, RMSEA ¼ 0.065, SRMR ¼ 0.045, GFI ¼ 0.912). The same three out of the four hypothesized paths were significant with the path between job satisfaction and service recovery performance not significant.

Our next step was to test our structural model for the private hospital and public hospital sample simultaneously. The purpose of this test was to see if the path coefficients are invariant across the two samples. To do this we constrained all the path coefficients to be equal across the two samples and used the LM test to see if any of the constraints should be released. The results of the fully constrained model were very good (x 2 ¼ 198.400 on 136 df, CFI ¼ 0.916, NNFI ¼ 0.904, IFI ¼ 0.918, RMSEA ¼ 0.050, SRMR ¼ 0.038, GFI ¼ 0.945). The LM test was used to see which of the path coefficients differed. The results of the LM test showed us that the path between MCSQ and organizational commitment should be released. We then reran the model with this constraint released and the results of this model showed a very good fit (x 2 ¼ 193.498 on 135 df, CFI ¼ 0.921, NNFI ¼ 0.909, IFI ¼ 0.923, RMSEA ¼ 0.049, SRMR ¼ 0.044, GFI ¼ 0.954). Therefore, we are able to conclude that three out of the four structural parameter estimates are invariant across the private and public hospitals samples. Results The first set of hypotheses was supported in the analysis. As such, MCSQ was found to affect organizational commitment positively (standardized loading ¼ 0.419, p , 0.01 for the public sample and standardized loading ¼ 0.778, p , 0.01 for the private sample) and also to affect job satisfaction positively (standardized loading ¼ 0.437, p , 0.01 for both the private and public sector sample). The results of our analysis also showed that H2 was supported. Organizational commitment was found to affect service recovery performance positively in the public sector sample (standardized loading ¼ 0.678, p , 0.01) and in the private sector sample (standardized loading ¼ 0.598, p , 0.01). However, H3 was not supported as we were unable to find a significant relationship between job satisfaction and service recovery performance (standardized loading ¼ 2 0.063, p . 0.05 for the public sector sample and standardized loading ¼ 0.003, p . 0.05 for the private sector sample). Discussion This study examined the concept of MCSQ and how it is linked to service recovery performance mediated through certain affective outcomes. We extended the model proposed by Babakus et al. (2003) that used Bagozzi’s (1992) reformulation of attitude theory as its theoretical base. We tested our model using FHEs in both the public and private sectors of the New Zealand healthcare system. From our analysis it appears that MCSQ has a positive impact upon both the job satisfaction of the frontline FHEs and also their organizational commitment. This finding lends further empirical support to the underlying theoretical framework of Bagozzi’s (1992) reformulation of attitude theory, in that we see that FHE appraisal of MCSQ influences affect (i.e. their satisfaction and organizational commitment) in both public and private contexts. We can also see from our study that the simultaneous implementation of employee empowerment, employee training, employee rewards, and customer service orientation jointly affects service recovery performance through the mediating role played by organizational commitment but not through job satisfaction. Service recovery performance being partially mediated by affective responses to appraisals of MCSQ again lends support for the attitude theoretical framework utilized in this study. Whereas we did not necessarily expect differences between private and public in terms of this appraisal ! affect/emotion ! behavior sequence, we did anticipate differences in the strengths of these relationships.


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On the whole, we found no difference between private and public sectors, although the path between MCSQ and organizational commitment was different with the standardized coefficient almost double for the private sector sample. This might be explained by private healthcare “culture” being perceived as more collaborative and less power-focused (Seren and Baykal, 2007). Alternatively, this substantially larger coefficient could be as a result of the intrinsic differences that exist between those FHEs working in private hospitals and those employed in public hospitals. One may expect FHEs of public institutions to be more driven by a belief in helping those in need as compared to those FHEs in private healthcare institutions who may see it as more of a job than vocation. This difference between public versus private sectors employee motivation has been demonstrated empirically (Jurkiewicz et al., 2007) and motivation is often operationalized as an aggregate construct including such concepts as organizational commitment, job satisfaction, and job involvement (Locke and Latham, 2004; Moynihan and Pandey, 2007). Slovensky et al. (1998) have argued that increasing dissatisfaction with the complexity, fragmentation, inefficiency, and cost of current public healthcare systems may also cause FHEs to be less committed to their organizations than their private sector counterparts. We are not surprised to see that there is a strong relationship between organizational commitment and service recovery performance in both public and private sectors samples. When the frontline FHEs of the organization are heavily committed to the goals of the organization is seems completely plausible that they would want the organization to do well. The one way in which these FHEs are able to contribute to the success of the organization is through their own individual performance. Thus, one of the ways that the commitment manifests itself is through improved service recovery performance. An interesting finding is the non-significant relationship between job satisfaction and service recovery performance. It may be the case in this study that our definition and measurement of the job satisfaction construct was too narrow. Despite the fact that the positive link between job satisfaction and behavior is well established in the literature, where there are contrary findings, the consensus seems to be that it is based on how job satisfaction is measured (Williams et al., 2007). When we conceptualized this construct we focused on extrinsic measures of job satisfaction but we acknowledge that service workers in the healthcare industry may be more motivated by intrinsic factors possibly due to their nature in being drawn to healthcare work. Extrinsic job satisfaction may not be important to people in a “carer” role. What might be more important to these individuals is the satisfaction derived from knowing they are alleviating patient/customer problems and distress. Research shows that FHEs working in healthcare organizations are motivated by the desire to care for other people (Hayes, 1993). This intrinsic motivation that exists in frontline healthcare employees could be what drives them in their work. If so this would go a long way toward explaining the lack of support for H3. Our findings suggest several guidelines for managerial action. MCSQ is a significant predictor of FHE job satisfaction and organizational commitment in both public and private healthcare settings with the impact of MCSQ on organizational commitment being almost twice as strong for the private healthcare setting. Only organizational commitment is a significant predictor of FHE service recovery performance in both settings. Given this finding, organizational commitment should be identified as a critical work lever and receive priority from management in both healthcare settings and especially in the public sector where the impact of FHE

organizational commitment is not as strong. Public and private healthcare managers should also explicitly design and establish organizational policies pertaining to employee empowerment, education/training, and reward systems and so on in order to develop a system that will facilitate a higher level of commitment to the hospital and therefore service-orientated service recovery performance. Internal marketing within the hospital environment in both settings should emphasize hospital management commitment to training, empowerment, rewards, and customer service orientation and communicate clear organizational policies about each. By not taking into consideration all of these variables, managerial action to improve individual and organizational performance may fail (Babakus et al., 2003; Lytle and Timmermann, 2006). For example, Bowen and Lawler (1995) and Argyris (1998) state that empowerment cannot be effective if it is not aligned with appropriate rewards and training. In other words, training and rewards systems are necessary for empowered frontline hospital staff to be effective in their jobs. Similarly, Hart et al. (1990) and Forrester (2000) argue that training is unlikely to produce the intended results unless reward mechanisms are also in place. Conclusions and future research In this study, we have used Bagozzi’s (1992) reformulation of attitude theory (Bagozzi, 1992) to frame our study of how service recovery performance is influenced by MCSQ. We contribute to the extant services literature by examining a model linking MCSQ variables, affective job outcomes and service recovery performance in the novel context of public versus private healthcare. Recently, no attention has been given to a comparative examination of those managerial practices critical for improving FHE service recovery efforts in a public and private healthcare context. Our research addresses this paucity. We were able to validate our model showing that Bagozzi’s (1992) reformulation can be used in the service recovery performance context. With the exception of the relationship between MCSQ and organizational commitment, our findings demonstrate that there are no differences between the public and private sectors suggesting that any future privatization efforts are unlikely to run into problems of the service recovery kind. There are some limitations to our study. We did not measure possible differences in compensation and benefits received, locus of control, or service delivery procedures across public versus private FHEs which should be addressed in future research. The data we collected was cross-sectional therefore we are unable to infer causality. To remedy this future research should try and make use of longitudinal data. In addition we used a self-report measure for service recovery performance. Future research should incorporate actual service recovery performance with the way to do that through collecting data from the patients who suffered the service failure. In addition, the respondents were drawn from a small convenience sample with the sample of private hospital FHEs falling short of the minimum recommended by Hair et al. (2006). Our sample of FHEs also comes from the outpatient departments of five metropolitan hospitals which limits the generalizability of the study results to other hospital settings. References Ahmed, I. and Parasuraman, A. (1994), “Environmental and positional antecedents of management commitment to service quality: a conceptual framework”, in Swartz, T.A.,


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Employee rewards (a ¼ 0.86 public a ¼ 0.83 private) Staff of this hospital are rewarded for dealing effectively with patient problems I am rewarded for satisfying complaining patients I receive visible recognition when I excel in serving patients Customer service training (a ¼ 0.90 public, a ¼ 0.82 private) Staff in this hospital receive continued training to provide good service Staff in this hospital receive extensive patient service training before they come into contact with patients Staff of this hospital receive training on how to serve patients better Empowerment (a ¼ 0.83 public, a ¼ 0.81 private) I am encouraged to handle patient problems by myself I do not have to get management’s approval before I handle patient problems

Construct and items

10.8 9.6 12.1 14.7 11.1 14.9 11.1 11.6

0.71 0.65 0.80 0.88 0.73 0.89 0.73 0.75

Scale items, reliabilities, and CFA results for public sample Standardized loadings t-values

0.67

0.77

0.83

0.74

0.94

0.82

0.68 0.68

9.6 (continued)

10.8

13.2

10.4

16.8

12.9

9.6 9.6

Scale items, reliabilities, and CFA results for private sample Standardized loadings t-values

Appendix


Table AI.

Table AI.

I have control over how I solve patient problems Customer service orientation (a ¼ 0.82 public, a ¼ 0.81 private) This hospital measures patient satisfaction on a regular basis This hospital sets objectives in terms of patient satisfaction This hospital is totally committed to serving its patients well A reputation for good service is stressed in my hospital Organizational commitment (a ¼ 0.82 public, a ¼ 0.84 private) I really care about the future of the hospital I am proud to tell others that I work for this hospital I am willing to put in a great deal of effort beyond that normally expected in order for this hospital to be successful Job satisfaction (a ¼ 0.89 public, a ¼ 0.86 private) I am satisfied with the amount of pay I receive for the job I do I am satisfied with my working conditions Given the work I do, I feel I am fairly paid. Service recovery performance (a ¼ 0.82 public, a ¼ 0.80 private) Considering all the things I do, I handle dissatisfied patients quite well I do not mind dealing with complaining patients No patient I deal with leaves with problems unresolved

15.7 9.2 13.4 11.9 8.2 10.4 8.2 7.9 16.9 14.5 11.8 10.2 10.8 11.0

0.92 0.64 0.83 0.78 0.60 0.70 0.60 0.59 0.97 0.87 0.77 0.69 0.71 0.72

0.82

0.62 0.80

0.93 0.86 0.90

0.64

0.73 0.72

0.57

0.70

0.71

0.93

0.91

12.9

8.0 12.6

16.6 13.8 16.2

8.4

10.3 10.2

7.2

9.9

10.1

16.6

16.2

Scale items, reliabilities, and CFA results for private sample Standardized loadings t-values

102

Construct and items

Scale items, reliabilities, and CFA results for public sample Standardized loadings t-values

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About the authors Michel Rod, PhD, is an Associate Professor in Marketing in the Sprott School of Business at Carleton University, Canada. His research interests include service recovery performance, burnout, the development and management of collaborative relationships amongst university, industry, and government organizations within the health sciences sector as well as the commercialisation of university-developed intellectual property. He has published articles in Journal of Services Marketing, Journal of Strategic Marketing, Journal of Retailing and Consumer Services, Marketing Intelligence and Planning, Managing Service Quality, International Journal of Pharmaceutical and Healthcare Marketing, Qualitative Market Research: An International Journal, Journal of Information and Knowledge Management, Journal of Entrepreneurship and Innovation, Management Research News, Journal of Transnational Management Development, and Science and Public Policy. Michel Rod is the corresponding author and can be contacted at: [email protected] Nicholas J. Ashill, PhD, is an Associate Professor in Marketing at the American University of Sharjah, United Arab Emirates. He has contributed to such journals as the Journal of Management, European Journal of Marketing, Decision Sciences, Journal of Services Marketing, Journal of Strategic Marketing, Journal of Marketing Management, Marketing Intelligence and Planning, Managing Service Quality, International Journal of Pharmaceutical and Healthcare Marketing, Qualitative Market Research: An International Journal, Journal of Asia-Pacific Business, Journal of Business and Management, International Journal of Bank Marketing, and the International Review of Public and Non Profit Marketing.

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