The mediating role of job satisfaction and competitive advantage between quality management practices and sustainable performance: Case of hospitals in Guangxi,China

Abstract

BACKGROUND

Ensuring medical quality and safety is the perpetual focus of healthcare management. Hospitals must prioritize quality management for sustainable growth. However, the complexity of quality management in hospitals, coupled with evolving practices, presents challenges. Achieving the integration of economic, environmental, and social benefits for high-quality development remains difficult. While quality management practices are acknowledged as strategic tools, their impact on job satisfaction, competitive advantage, and sustainable performance is not yet fully understood.

OBJECTIVE

The objective of this research was to empirically demonstrate the relationship between quality management practices, job satisfaction, competitive advantage, and sustainable performance.

METHODS

The study uses a quantitative research method. A questionnaire survey was conducted in Guangxi, China, among 171 quality management executives in secondary and tertiary hospitals, and the proposed research model was validated using PLS-SEM.

RESULTS

The results showed that quality management practices have positive direct and indirect effects on sustainable performance, confirming the partial mediating role of job satisfaction, and competitive advantage in the relationship between quality management practices and sustainable performance.

CONCLUSIONS

This study addresses a gap in quality management literature by exploring the relationship between quality management practices, job satisfaction, competitive advantage, and sustainable performance. Findings reveal that higher implementation of quality management practices correlates with increased job satisfaction, stronger competitive advantage, and enhanced sustainable performance in hospitals. These results suggest that implementing quality management practices can boost job satisfaction, enhance competitive advantage, and promote sustainable performance, offering valuable insights for hospital leaders.

Keywords

Quality management practices sustainable performance job satisfaction competitive advantage PLS-SEM

Dr. Muhammad Shahid Khan is an assistant professor at the College of Innovation and Management, Suan Sunandha Rajabhat University, Thailand. His research interests include Knowledge Management, Leadership, Innovation and Human Resource Management.

Jieru Quan is a PhD student at the College of Innovation and Management, Suan Sunandha Rajabhat University, Thailand. Her research interests include Business Performance, Hospital Management and Human Resource Management.

1. Introduction

Ensuring the quality and safety of healthcare is a constant theme of healthcare management [1]. Quality management has become one of the main measures for hospitals to cope with environmental changes [2]. In recent years, sustainable performance has received much attention among stakeholders and organizations around the world [3]. But,the relationship between quality management practices and sustainable performance has received little attention from academic scholars, even though it is widely understood that both concepts are crucial [4]. From the past literature, the relationship between quality management practices and sustainable performance has not adequately been explored [5]. In particular, with the increasing emphasis on the healthcare sector, scholars have begun to study quality management practices in healthcare, but there are fewer research findings on sustainable performance in hospitals. In fact, as some studies have shown, improving the quality of healthcare services leads to better outcomes for hospitals [6, 7].

In 2023, National Health Commission of the People’s Republic of China proposed that it would use three years to improve the level of refinement and standardization of healthcare quality and safety management and to continuously improve people’s satisfaction with healthcare services. Hospitals can only realize high-quality development by striving to satisfy patients and employees [8]. Employee performance is influenced by quality management practices. Quality management practices are a management framework in which hospitals achieve long-term success by focusing on improving quality, including all employees, as a result, achieving patient satisfaction. Medical employees are the main practitioners of quality management in hospitals and their job satisfaction is directly related to the quality and sustainable performance of healthcare services. The implementation of quality management can better perceive opportunities, seize them, and reconfigure resources to cultivate dynamic capabilities that respond to the diverse needs of today’s consumers, thereby gaining a better competitive advantage [9]. When hospitals are able to respond to patient needs faster than their competitors, it helps to provide value to patients by improving the quality of healthcare services, which in turn enhances sustainable performance.

Most researchers have found a positive correlation between quality management practices and sustainable performance. However, from an empirical point of view, existing studies have not demonstrated how job satisfaction, competitive advantage affects sustainable performance in hospitals, which is the mediating variable in our study. As the world’s largest developing country, there is a need to conduct research on the relationship between quality management practices and sustainable performance of hospitals in the Chinese context to fill the gap of one of the studies proposed by Akanmu et al., Babu & Thomas [10, 11].

Therefore, the aim of this paper is to empirically evaluate a structure that defines quality management practices, job satisfaction, competitive advantage, and sustainable performance relationships. The research question thus posed is to what extent quality management practices through job satisfaction, competitive advantage, and sustainable performance of secondary and tertiary hospitals in Guangxi, China?

2. Literature review and hypothesis development

2.1. Literature review

2.1.1. Quality management practices

There many quality concepts such as six sigma, business process reengineering, lean manufacturing, lean six sigma, total quality management, etc., whose goal is always to ensure quality competition [12]. Quality management practices refers to all activities of a managerial nature carried out to achieve quality objectives, throughout the business process, ensuring that customer requirements are met at every stage, both internally and externally [13]. Quality management is a widely recognized strategic approach that prioritizes continuous improvement of organizational processes, customer satisfaction, and overall business effectiveness [14]. Bytyçi et al. [15] define total quality management as a belief system that focuses on satisfying customers’ needs, which requires organizations to create customer-centered operational techniques by investing in resources to facilitate the orientation of the customer and to satisfy their needs and desires. Quality management practice in this study is defined as a management philosophy that focuses on customer satisfaction, employee involvement and continuous improvement of work processes and enhances sustainableperformance.

2.1.2. Sustainable performance

Sustainable performance takes into account its impact on the natural environment and human society, as well as its ability to achieve economic returns without sacrificing the needs of its stakeholders [16]. In the future, the more successful a business is, the more sustainable it will be [17]. The “triple bottom line” is widely used in the measurement of sustainable performance, including economic, environmental and social performance [18]. Economic performance refers to practices that support long-term economic growth without compromising other performance, including the promotion of cost savings, profits, R&D investment, etc. [19]. Environmental performance refers to the results of resource conservation, environmental protection and pollution prevention. Social performance refers to the fulfillment of social responsibilities and contributions to the public and society, and measures the organization’s social responsibilities to multiple stakeholders (e.g., shareholders, employees, customers), such as health, safety and welfare.

A widely recognized way to express hospital sustainable performance is to balance economic, environmental and social benefits [20], which is to take into account the “triple bottom line” theory in performance issues. This research tends to define sustainable performance of hospitals as the pursuit of long-term robustness in the provision of healthcare services, while taking into account economic, social and environmental perspectives.

2.1.3. Job satisfaction

It is widely recognized by scholars that job satisfaction was first proposed by the American psychologist Hoppock [21]. In his work. Employee satisfaction is one of the psychological aspects that reflect how a person feels about his or her job. The more people love their jobs, the higher their satisfaction [22]. Oshagbemi [23] defined job satisfaction as “the positive emotional response of an individual to any given job”. In essence, job satisfaction is an individual issue. Satisfaction will vary for each employee based on each individual’s perception of the value system that applies to them [24]. Job satisfaction in hospitals is defined as the level of satisfaction of staff within hospitals with their jobs, work environment, management and organizational culture.

2.1.4. Competitive advantage

Bain (1956) discussed the characterization of competitive barriers in manufacturing, and Alderson (1965) introduced the concept of “competition by difference” to gradually establish the importance of competitive advantage for corporate strategy formulation [25]. Purwanto et al. [26] showed that industry or firm competitive advantage cannot be dependent on a single factor, whether it is the external or internal environment. Competitive advantage is an advantage over competitors gained by having the ability to do a job well. Incorporating environmental responsibility into a company’s strategic planning is a tangible competitive advantage and a significant contribution to social and environmental well-being [27]. Competitive advantage is defined as a unique advantage or capability that an organization has over its competitors in an area that provides it with sustained success and leadership.

2.2. Hypothesis development

2.2.1. Quality management practices and sustainable performance

Xiong et al. [28] conducted a study on quality management activities in hospitals and found that quality management practice significantly affect hospital performance. Tonjang et al. [6] found that both quality management practices and dimensions of innovation have a positive positive impact on sustainable performance of hospitals. Zehir et al. [7] developed that quality management practices have a significant impact on the financial and operational performance of hospitals. Quality management practices emphasize continuous improvement and process management, thereby improving the quality of healthcare by increasing workflow efficiency. This increases patient loyalty, reduces operating costs, and improves market share, which directly improves the sustainable performance of the hospital. By implementing quality management practices, service industries such as hospitals can improve sustainable performance, which is much needed to provide patient-centered care and treatment. Thus, it is hypothesised that:

H1: Quality management practices have a positive and significant impact on the sustainable performance of the hospital.

2.2.2. Quality management practices and job satisfaction

Overall, studies have shown that there is a positive correlation between effective implementation of quality management and increased employee satisfaction [29, 30]. Mostafa & Bisheer [31] found that the highest correlation between total quality management practices and employee satisfaction was employee empowerment. A study by Lepistö et al. [29] and others found that the four TQM dimensions of management/leadership, customer focus, personnel management and risk management were related to personnel satisfaction. Quality management practices can increase employee job satisfaction by promoting employee involvement, providing training, and improving the work environment and processes. Whereas, in the healthcare sector, Işik [32] found a significant correlation between total quality management and employee satisfaction. This research proposes a hypothesis:

H2: Quality management practices have a positive and significant impact on employee satisfaction.

2.2.3. Job satisfaction and sustainable performance

Job satisfaction is significant in defining organizational success, especially in the service industry [33]. Employees are important stakeholders and job satisfaction is often considered as an important factor in sustainable performance [34]. A survey by Alrazehi et al. [35] found that job satisfaction is one of the critical factors in the performance of Yemeni international banking organizations. Job satisfaction is crucial for organizations because it affects employee motivation and productivity, which in turn affects the overall performance of the organization [36]. Satisfied employees are usually better able to meet the needs of patients and provide better quality healthcare services, which in turn improves patient satisfaction, increases patient loyalty, and generates a stable source of revenue for the hospital to support its long-term sustainable development. Therefore, regarding the relationship between job satisfaction and sustainable performance of hospitals, this research proposes the following hypothesis:

H3: Employee satisfaction has a positive and significant impact on Sustainable performance of hospitals.

2.2.4. Quality management practices and competitive advantage

It is widely recognized that quality management can generate sustainable competitive advantage [37]. Total quality management has a positive positive effect on competitive advantage [38]. The study by Elhawi [39] found a relationship between quality management practices and competitive advantage in Jordanian banks. This means that the principles and practices of quality management can influence the performance of an organization and lead it to progress and prosperity. Quality management practices enable hospitals to optimize workflow and resource allocation, and by reducing costs, minimizing waste, and improving material utilization, hospitals can provide better quality care and gain a competitive advantage. Implementing quality management can increase patient satisfaction, which leads to competitive advantage and also helps hospitals to become more sustainable [7]. The following hypothesis was set forth:

H4: Quality management practices have a positive and significant impact on competitive advantage.

2.2.5. Competitive advantage and sustainable performance

Ferreira et al. [40] stated that competitive advantage puts firms in a rare, valuable, and difficult-to-obtain position, which contributes to superior performance. Waqas et al. [41] stated that manufacturing firms should focus on their competitiveness and improve product quality performance, which contributes to the firm’s environmental performance. Elgarhy and Abou-Shouk [42] found that sustainable competitive advantage is the added value of business products and practices that help firms meet customer needs better than competitors, contributing to the realization of economic value and improved market performance. Hospitals with a competitive advantage are usually able to build a strong brand and reputation. A strong brand image and reputation increases patients’ trust in the hospital and attracts more patients to choose the hospital for their care, which in turn leads to growth and development of the hospital’s business and enhances its sustainable performance. This research proposes a hypothesis:

H5: Competitive advantage has a positive and significant impact on the sustainable performance of hospitals.

2.2.6. Mediating role of job satisfaction

Quality management practices focus on continuous improvement and quality management, which leads to improved work processes and environments, resulting in increased employee satisfaction. An improved work environment increases employee loyalty and satisfaction with the organization, which positively impacts sustainable performance. Employees’ productive behavior can mediate the effect of quality management practices on firm performance [43]. According to Trivellas et al. [44], employee satisfaction plays a mediating role between quality management practices and innovation performance. The results of Amin et al. [45] showed that quality management practices are significantly related to employee job satisfaction and hotel performance. the following hypothesis is proposed:

H6: Employee satisfaction mediate the relationship between quality management practices and sustainable performance of hospitals.

2.2.7. Mediating role of competitive advantage

Competitive advantage plays a mediating role between total quality management practices and sustainable performance [46, 47]. By implementing quality management practices, hospitals can gain a competitive advantage and thus improve their sustainable performance. A core objective of quality management practices is to improve the quality of healthcare services. Through continuous improvement and quality control, hospitals are able to provide better quality healthcare services. High-quality healthcare services can create a competitive advantage for hospitals by attracting more patients and increasing their market share, thereby improving their sustainable performance. Quality management practices reduce the cost of patient visits by improving the quality of healthcare services. Low-cost and high-quality healthcare services are key elements of a hospital’s competitive advantage, and can directly impact the sustainable performance of the hospital. Therefore, this research proposes the following hypothesis:

H7: Competitive advantage mediate the relationship between quality management practices and sustainable performance of hospitals.

Based on the explanation of the hypotheses discussed, the following is a framework for the research model used, as shown in Fig. 1.

Fig. 1

Conceptual framework. Source(s): Figure by authors.

3. Methodology

3.1. Sample and data collection

According to the “Action Plan for Comprehensively Improving the Quality of Medical Care (2023–2025)”, each business department should set up a medical quality management team headed by the main person in charge, and designate specialists to be responsible for the daily specific work. Therefore, the research object of this study are that the quality management executives of the secondary and tertiary hospitals in Guangxi, China.

This study was conducted using quantitative research methods. We collected data from secondary and tertiary hospitals in Guangxi, China. We developed a questionnaire using a structure identified in the literature and validated it by academic and healthcare industry professionals. Participants were managers involved in hospital quality management, including senior, middle and junior quality managers, who had been involved in the implementation of quality management and were aware of sustainability practices in their hospitals. Simple random sampling method was used for sampling in this thesis. Out of 215 questionnaires distributed, 191 were completed and returned with an acceptable response rate of 88.83%. 20 respondents were removed from the sample due to non-participating responses and a total of 171 usable responses were used for the final analysis(Table 1).

Table 1

Sample demographicl

Demographic Variable	Category	Frequency	Percentage
The Category of hospital where the	General	139	81.3
respondent work at	Specialized	32	18.7
The level of hospital where the	Secondary	44	25.7
respondent work at	Tertiary	127	74.3
Gender	Male	66	38.6
	Female	105	61.4
Age	≤30	16	9.4
	31–40	58	33.9
	41–50	59	34.5
	≥51	38	22.2
Years of engagement in	≤3	49	28.7
quality management	4–6	37	21.6
	7–9	24	14.0
	≥10	61	35.7
Positions	Senior	12	7.0
	Middle	117	68.4
	Grassroots	42	24.6
Department	Administrative	48	28.1
	Clinical	102	59.6
	Medical technology	21	12.3

Source(s): Table by authors.

3.2. Measurement and scales

The survey instrument consists of 47 items (Table 2). The questions related to quality management practices related questions were adapted from [6, 48]. Sustainable performance was measured using the scale of Al Qershi et al. [49–51]. Job satisfaction was measured with items from the scale developed by Weiss [52]. The measurement of competitive advantage followed the scales of Mahasneh et al. [53, 54]. The items were slightly modified to suit the hospital context and pilot tested with a sample of 40 and subsequently modified. Respondents were asked to rate each item on a scale ranging from 1 (strongly disagree) to 5 (strongly agree).

Table 2

Measurement and scale

Dimensions	Items	Author(s)
Quality Management Practices (QMP)		[6, 48]
Top leadership	TL1: Department heads in the hospital accept their responsibilities for quality improvement and work on it.
	TL2: Hospital management allocates appropriate resources (funds and time) to accomplish goals and manage the work.
	TL3: Management provides personal leadership for quality improvement.
	TL4: Hospital management is personally involved in quality improvement projects.
Training	TR1: The hospital has a comprehensive training plan consistent with the needs of employees in developing their working skills.
	TR2: Employees receive training to perform tasks to the fullest.
	TR3: Employees receive training on quality issues regularly.
Process Management	PM1:Hospital processes are being monitored using statistical process control.
	PM2: Charts are used to determine whether hospital service processes are in control.
	PM3: A large percentage of hospital processes are currently under statistical quality control.
Customer Focus	CF1:The hospital conducts customer satisfaction surveys on a regular basis.
	CF2: Satisfying our customers and meeting their expectations is considered our top priority.
	CF3: Hospital staff understands the needs of customers and seeks to achieve them.
Continuous Improvement	CI1: The hospital strives to improve the quality of its services continually rather than take a static approach.
	CI2: Feedback received from patients is used continuously to improve the work.
	CI3: The hospital adopts all aspects of continuous improvement.
Employee Involvement	EI1: Employees are responsible for error-free output.
	EI2: Employees have the decision to solve problems.
	EI3: Employees publicize the hospital’s achievements.
	EI4: Ideas from medical staff are actively used.
Sustainable Performance (SP)		[49–51]
Economic performance (ECP)	ECP1: Return on investment (ROI) has increased above the industry average during the last three years
	ECP2: Sales growth has increased above industry average during the last three years
	ECP3: Profit growth rate has increased above industry average during the last 3 years.
	ECP4: Market share has increased during the last 3 years.
Environmental Performance (ENP)	ENP1: The efficiency of the consumption has improved during the last 3 years of materials
	ENP2: The resource consumption (thermal energy, electricity, water) has decreased (e.g., per unit of income, per unit of production) during the last 3 years.
	ENP3: The percentage of recycled materials has increased during the last 3 years.
	ENP4: The waste ratio (e.g., kg per unit of product, kg per employee per year) has decreased during the last 3 years
Social Performance (SOP)	SOP1:The employees’ satisfaction has increased during the last 3 years.
	SOP2: Employee education and training (man-days per employee per year) have increased during the last 3 years.
	SOP3: The employees’ motivation has increased during the last 3 years.
	SOP4: Health and safety performance have improved during the last 3 years.
Job satisfaction (JP)		[52]
	JS1: The chance to do different things from time to time.
	JS2: The chance to be “somebody” in the community.
	JS3: The way my job provides steady employment.
	JS4: The chance to do something that makes use of my abilities.
	JS5: The feeling of accomplishment l get from the job.
	JS6: The way my boss handles his/her workers.
	JS7: My pay and the amount of work l do.
	JS8: The working conditions.
	JS9: The way my co-workers get along with each other.
	JS10: The praise I get for doing a good job.
Competitive Advantage (CA)		[53, 54]
	CA1: Quality of health care.
	CA2: Different services from other hospitals.
	CA3: Unique benefits than other hospitals.
	CA4: Services are more advanced
	CA5: Cost less.

3.3. Data analysis technique

This research used PLS to analyze the data. PLS is a powerful analytical method because it does not assume current data with a certain scale measurement, the number of samples is small [55]. We used the partial least squares (PLS) model of the nonparametric analysis software Smart PLS 4 [56] as a statistical tool to test the measurement and structural models because it does not require the assumption of normality, and survey studies are not usually normally distributed [57].

This research followed the recommendations of Anderson and Gerbing [58] and used a two-step approach to test the models developed. First, we tested the measurement model following the guidelines of Hair et al. [59] and Ramayah et al. [60] to test the validity and reliability of the instruments used, and then we ran the structural model to test the hypotheses presented.

It’s worth noting that the lower-order components are reflections of the higher-order component (reflective-reflective model), and the model type is critical for subsequent reporting and for choosing an appropriate modeling approach for hierarchical latent variable models [61]. The approach we use to estimate the hierarchical latent variable model is the two-stage approach. The two-stage approach, categorized as the embedded two-stage approach [56] and the disjoint two-stage approach [61, 62], which slightly differ in their model specification in both stages. As both versions of the two-stage approach led to similar results [63], this study used the embedded two-stage approach. Researchers save scores of low-order components in the first stage. In the second stage, these scores are subsequently used to measure higher-order structures [64].

4. Results and data analysis

4.1. Sample demographic

Table 1 shows the demographic information of the study participants. 139 (81.3%) of the respondents were from general hospitals and 32 (18.7%) from specialized hospitals; 44 (25.7%) were from secondary hospitals and 127 (74.3%) were from tertiary hospitals. In terms of gender, 105 (61.4%) of the 171 respondents were female and 66 (38.6%) were male. In terms of age, 117 (68.4%) of the 171 persons were 31–5 years old. For position, 7% of the participants were senior managers, 68.4% were middle managers, and 24.6% were junior managers. In terms of department, 102 (59.6%) doctors and nurses from clinical departments participated in the survey, followed by 48 (28.1%) managers from administrative departments of the hospital, and 21 (12.3%) from medical technology. In terms of years of experience in quality management work, 122 participants with more than 3 years of experience, accounting for 71.3% of the valid number, were the majority of those who participated in this study. Finally, 171 people participated in the study.

4.2. Common method bias

We first tested the common method bias problem by testing for full collinearity as suggested by Kock and Lynn [65] and Kock [66]. The test for full collinearity was performed using SPSS Version 26 software. In this method, all variables will be regressed against a common variable and if VIF≤3.3, there is no bias from single source data. The analysis yields VIF values for PM,CF,CI that are higher than 3.3 but still under 5 (Table 3), so single-source bias is not significant in our data. The VIF threshold used in the common method bias test should be slightly higher than 3.3 when using the factor-based PLS-SEM algorithm, and can be 5 when using an algorithm that includes measurement error.

Table 3

Full collinearity testing

	TL	TR	PM	CF	CI	EI	JS	CA	ECP	SOP	ENP
VIF	2.171	3.215	3.363	3.639	4.313	2.373	2.167	1.914	1.731	1.896	2.151

Note:Dependent variable: Random. Source(s): Table by authors.

4.4. Measurement model

First, we focused on the reflective measurement model of the lower-order components. Cronbach’s alpha values above 0.70 can be considered statistically reliable. CR values greater than 0.70 can be considered statistically significant, while AVE should be greater than 0.50 to be considered statistically significant [67]. Factor loading values should be ≥0.7. As shown in Table 4, these models met all relevant criteria. Cronbach’s alpha was all above 0.7, AVE was all above 0.5, and CR were all above 0.70 and less than 0.95. Byrne [68] stated that first order constructs should be explained adequately by the hypothesized second-order constructs while being distinct. We also assessed the validity and reliability of second-order constructs. The second-order measures were also valid and reliable, and the results are shown in Table 4.

Table 4

Reliability and validity results

First-order Constructs	Items	Loadings	Ca	CR	AVE
Top Leadership	TL1	0.848	0.919	0.942	0.804
	TL2	0.923
	TL3	0.924
	TL4	0.887
Training	TR1	0.923	0.914	0.946	0.853
	TR2	0.912
	TR3	0.937
Process Management	PM1	0.917	0.915	0.946	0.855
	PM2	0.932
	PM3	0.924
Customer Focus	CF1	0.906	0.911	0.944	0.849
	CF2	0.937
	CF3	0.921
Continuous Improvement	CI1	0.916	0.896	0.935	0.828
	CI2	0.912
	CI3	0.901
Employee Involvement	EI1	0.882	0.907	0.935	0.782
	EI2	0.901
	EI3	0.866
	EI4	0.888
	TL	0.779	0.924	0.941	0.726
	TR	0.872
	PM	0.881
	CF	0.865
	CI	0.906
	EI	0.801
Economic Performance	ECP2	0.928	0.819	0.883	0.661
	ECP3	0.880
	ECP4	0.843
Environmental Performance	ENP1	0.702	0.841	0.895	0.682
	ENP2	0.849
	ENP3	0.903
	ENP4	0.837
Social Performance	SOP2	0.799	0.729	0.830	0.551
	SOP3	0.740
	SOP4	0.741
	ECP	0.791	0.729	0.846	0.648
	ENP	0.852
	SOP	0.769
Job satisfaction	JS1	0.760	0.931	0.942	0.621
	JS2	0.706
	JS3	0.794
	JS4	0.877
	JS5	0.867
	JS6	0.864
	JS7	0.718
	JS8	0.822
	JS9	0.736
	JS10	0.710
Competitive	CA1	0.874	0.889	0.918	0.693
Advantage	CA2	0.874
	CA3	0.843
	CA4	0.790
	CA5	0.775

Note: ECP1and SOP1 were deleted due to low loading. ECP1 loading = 0.546 < 0.7, SOP1 loading = 0.686 < 0.7. Source(s): Table by authors.

Then, we first assessed the discriminant validity using the HTMT criterion proposed by Henseler et al. [69] and updated by Franke and Sarstedt [70]. The stricter criterion is that the HTMT value should be ≤0.85, and the less stringent criterion is that the HTMT value should be ≤0.90. Tables 5, and 6 show the discriminant validity of the first-order structural model and the second-order structural model, respectively. As shown in Table 5, the HTMT values for the first-order structure have only two values below the stricter criterion (≤0.85), but still ≤0.90, so we can conclude that the respondents perceived the constructs as different. As shown in Table 6, the HTMT values for the second-order constructs are below the stricter criterion (≤0.85). Secondly, according to Fornell and Larcker’s (1981) criterion, the square root of the AVE should be greater than the square root of the correlation between the dimensions, so the discriminant validity test was confirmed. Discriminant validity refers to the extent to which items differ across concepts [71]. The results showed (Tables 7, 8) that the values for each construct supported discriminant validity. In summary, both validity tests indicated that the measurement items were valid and reliable.

Table 5

Discriminant validity (HTMT) for first order constructs

Source(s): Table by authors.

Table 6

Discriminant validity (HTMT) for the second order constructs

Source(s): Table by authors.

Table 7

Fornell-larcker criterion for first order constructs

Constructs	CA	CF	CI	ECP	EI	ENP	JS	PM	SOP	TL	TR
CA	0.832
CF	0.401	0.921
CI	0.454	0.814	0.910
ECP	0.452	0.275	0.342	0.813
EI	0.447	0.619	0.697	0.347	0.884
ENP	0.509	0.378	0.445	0.601	0.518	0.826
JS	0.611	0.489	0.580	0.409	0.523	0.502	0.788
PM	0.466	0.703	0.733	0.306	0.641	0.444	0.509	0.924
SOP	0.407	0.582	0.565	0.434	0.505	0.473	0.515	0.488	0.742
TL	0.359	0.619	0.650	0.291	0.479	0.377	0.504	0.635	0.431	0.896
TR	0.474	0.674	0.715	0.335	0.625	0.460	0.529	0.781	0.498	0.651	0.924

Source(s): Table by authors.

Table 8

Fornell-larcker criterion for the second order constructs

	CA	JS	QMP	SP
CA	1.000
JS	0.611	1.000
QMP	0.511	0.614	0.852
SP	0.567	0.580	0.609	0.805

Source(s): Table by authors.

4.5. Structural model

After established the validity of the first-order structure and second-order structure of the reflectivity measurement model, we now evaluate the inner structure model. As stated in Cain et al. [72], we first calculated multivariate skewness and kurtosis using software on WebPower. The output of the Mardia multivariate showed that the data collected was not multivariate normal, Mardia’s multivariate skewness (β= 33.106, p < 0.01) and multivariate kurtosis (β= 19.395, p < 0.01). Thus following the suggestions of Becker et al. [73] we reported the path coefficients, the standard errors, t-values and p-values for the structural model using a 10,000-sample re-sample bootstrapping procedure [60]. Also based on the criticism of Hahn and Ang [74] that p-values are not good criterion for testing the significance of hypothesis and suggested to use a combination of criterions such as p-values, confidence intervals and effect sizes. The results are shownin Fig. 2.

Fig. 2

Structural model results.

First, we examined the impact of quality management practices on job satisfaction, and competitive advantage. It can be suggested that path coefficients (β) in the structural model ranging from 0 to 0.10, 0.11 to 0.30, 0.30 to 0.50, and >0.50 are indicative of weak, modest, moderate, and strong effect sizes [59]. Quality management practices were positively associated with both job satisfaction (β= 0.614, p < 0.001) and competitive advantage (β= 0.511, p < 0.001), thus H2 and H4 were supported(Table 9). While initial model estimations can draw on a smaller number of bootstrap subsamples (e.g. 1,000), the final analysis should use at least 10,000 subsamples[59].

Table 9

Hypothesis testing direct effects

Hypothesis	Relationship	Std Beta	Std Error	t-values	p-values	BCI LL	BCI UL	f²	VIF	Conclusion
H1	QMP ->SP	0.348	0.080	4.356	p<.001	0.215	0.476	0.138	1.686	Supported
H2	QMP ->JS	0.614	0.060	10.272	p<.001	0.503	0.700	0.606	1.000	Supported
H3	JS ->SP	0.205	0.073	2.788	0.003	0.079	0.322	0.041	1.987	Supported
H4	QMP ->CA	0.511	0.059	8.627	p<.001	0.401	0.599	0.353	1.000	Supported
H5	CA ->SP	0.264	0.070	3.749	p<.001	0.143	0.377	0.080	1.673	Supported

Note:We used 90% confidence interval with a bootstrapping of 10,000. Source(s): Table by authors.

We next tested the effects of quality management practices, job satisfaction, and competitive advantage on sustainable performance Quality management practices (β= 0.348, p < 0.001), job satisfaction (β= 0.205, p < 0.01), and competitive advantage (β= 0.264, p < 0.001) are all positively associated with sustainable performance, thus H1, H3, and H5 are supported (Table 9).

To test the mediation hypothesis, we bootstrap the indirect effects as suggested by Preacher and Hayes [75, 76]. If the confidence interval does not cross 0, then we can conclude that there is a significant mediation effect. As shown in Table 9, QMP ->JS ->SP (β= 0.126, p < 0.01) and QMP ->CA ->SP (β= 0.135, p < 0.01) are significant. The bias-corrected 95% confidence intervals also did not show any intervals across 0, thus confirming our findings, which were also supported for H6 and H7.

Moreover, the variance accounted for (VAF) also examined the mediating influence of tests the mediating effect of JS, CA between QMP and SP, respectively. The following VAF criteria are suggested to decide the type of mediation, less than 20% (no mediation), between 20 and 80% (partial mediation) and greater than 80% (full mediation). Table 10 shows that the mediating effect of JS is 20.690%, CA is 22.167%, indicating that both JS and CA partially mediate the relationship between QMP and SP. Hence, H6 and H7 is partially mediated.

Table 10

Hypothesis testing indirect effects

Hypothesis	Relationship	Std Beta	Std Error	t-values	p-values	BCI LL	BCI UL	VAF	Conclusion
H6	QMP ->JS ->SP	0.126	0.048	2.615	0.009	0.036	0.225	20.690%	Partial mediation
H7	QMP ->CA ->SP	0.135	0.040	3.365	0.001	0.063	0.221	22.167%	Partial mediation

Note: We used 95% confidence interval with a bootstrapping of 10,000. Source(s): Table by authors.

After ensuring that the model had no covariance issues and that the paths made sense, we assessed the R² (0.480) for the final outcome variable sustainable performance, indicating that all predictors explained 48% of the variance in sustainable performance. In the field of PLS-SEM, it is known as in-sample predictive power because when calculating the algorithm solution, all the sample data are used to calculate the R² [77]. Researchers emphasize that R² values are contextually relevant and should be interpreted with reference to the field of study being examined. R² values between 0 and 0.10, 0.11 and 0.30, 0.30–0.50, and >0.50 indicate weak, modest, moderate, and strong explanatory power, respectively [59]. These rules of thumb should provide general guidance rather than strict guidance, and further research is needed as the magnitude of R² may also represent overfitting [55].

Although R² provides useful information about the relationships between all the variables included in a structural and measurement model, it does not assess out-of-sample predictive power as measured by the retained sample approach [55, 78]. When the traditional R² metric is interpreted as a measure of a model’s predictive performance, it is actually the in-sample strength of fit-which evaluates and explains the relationship between all the variables used to construct the model, and is therefore inherently interpretable [79]. However, the R² metric does not indicate the out-of-sample predictive performance of the model because the analysis does not predict sample data that are not included in the initial computation of the model solution. To obtain out-of-sample predictive metrics, researchers must apply the retained sample method [59].

Shmueli et al. [78] proposed PLS-Predict, a retained-sample based procedure that utilizes PLS-Predict to generate case-level predictions at the item or construct level and checks for predictive relevance using a 10-fold procedure. Shmueli et al. argued that if all item variances (PLS-LM) are below predictive capacity, the predictive power is high; if all item variances are above the predictive power, the predictive relevance cannot be confirmed; if most item variances are below the predictive power, the predictive power is moderate; and if most item variances are below the predictive power, the predictive power is low. According to the results in Table 11, we can conclude that our model has a stronger predictive power.

Table 11

PLS – Predict

Items	Q²predict	PLS-SEM_RMSE	LM_RMSE	PLS – LM
CA	0.251	0.871	0.898	–0.027
JS	0.370	0.801	0.815	–0.014
ECP	0.097	0.958	0.981	–0.023
ENP	0.255	0.870	0.882	–0.012
SOP	0.307	0.840	0.846	–0.006

Source(s): Table by authors.

5. Conclusion

5.1. Discussion

This study explores the interplay between quality management practices, job satisfaction, competitive advantage, and sustainable performance in hospitals. It is one of the few empirical investigations to simultaneously examine these relationships. Findings reveal that effective quality management practices, including top leadership, training, process management, customer focus, continuous improvement, and employee involvement, positively impact sustainable performance. Hospitals with well-implemented quality management practices are more likely to achieve sustainable growth. This finding confirms similar studies conducted in service and manufacturing industries in different parts of the world [49]. Quality management practices in service-oriented industries like hospitals can enhance sustainable performance, vital for delivering patient-centered care. These practices positively influence job satisfaction and competitive advantage by implementing comprehensive quality improvement programs, thereby fostering positive stakeholder perceptions. Competitive advantage refers to an organization’s superior position in the market compared to competitors [38]. Quality management practices can be used as an internal marketing tool for hospitals among their employees to create a positive image among existing employees and increase employee job satisfaction. This study confirms previous studies done in manufacturing and service organizations [29, 30]. This study reaffirms prior findings, emphasizing the positive influence of job satisfaction and competitive advantage on sustainable performance. Enhancing employee job satisfaction and organizational competitive advantage can lead to favorable outcomes, thereby bolstering hospitals’ sustainable performance.

Regarding the relationship between quality management practices and sustainable performance, this study found that job satisfaction and competitive advantage moderated the relationship between quality management practices and sustainable performance to some extent [46, 47]. Partial mediation occurs when the relationship between the independent variable (quality management practices) and the dependent variable (sustainable performance) changes due to the introduction of mediating variables (job satisfaction, competitive advantage). It is possible to delineate the causal effect of quality management practices on sustainable performance (a) as an indirect effect through the mediating variable (a * b) and a direct effect (path c). In both cases, the paths are essentially positive and significant, hence the presence of partial mediation rather than no or complete mediation at all. Furthermore, this finding suggests that hospitals aiming to improve sustainable performance through quality management practices need to focus on improving employee job satisfaction and competitive advantage.

5.2. Implications

This study has some managerial and academic significance. It underscores that quality management practices can elevate sustainable performance, enhance job satisfaction, and bolster hospital competitive advantage. These practices ensure ongoing quality improvement across all hospital functions and foster stakeholder engagement, prioritizing customer satisfaction. In today’s business landscape, where skilled and dedicated employees are scarce, quality management and job satisfaction are crucial. Patients often rely on word-of-mouth recommendations, particularly in human resource-intensive sectors like healthcare. Thus, attracting quality talent is pivotal for hospitals’ service delivery. This study advocates for a quality management-based hospital strategy to enhance job satisfaction, competitive advantage, and sustainable performance. For governmental agencies, the empirical countermeasure suggestions presented here offer valuable insights for policy formulation in medical and healthcare system reforms. Moreover, this study breaks new ground by applying structural equation modeling (SEM) to analyze the impact of quality management practices on sustainable performance in hospitals, bridging the gap between theory and practice. It also sheds light on the moderating roles of job satisfaction and competitive advantage in this relationship, underscoring their significance in achieving sustainable performance. This localized research in the Chinese context contributes to the broader understanding of quality management practices’ influence on hospital performance globally.

5.3. Limitations and future research

While extensive efforts were made to ensure the reliability and validity of the findings, this study acknowledges several limitations that warrant attention in future research. The sample size, comprising 171 QM practitioners from secondary and tertiary hospitals in Guangxi, China, may limit the generalizability of the results, prompting the need for broader representation across hospitals. Control variables such as hospital size, age, and employee demographics were not included due to sample constraints. The use of cross-sectional data from key employees may introduce subjective bias, suggesting the consideration of longitudinal studies to capture temporal changes. Future research could explore this model across hospitals in diverse regions of China or other countries for broader applicability. Furthermore, incorporating additional QM practice dimensions into the measurement model may enhance future studies, urging researchers and academics to delve deeper into the connections between quality management practices.

Footnotes

Acknowledgments

The authors have no acknowledgments.

Author contributions

CONCEPTION: Muhammad Shahid Khan, Jieru Quan

METHODOLOGY: Muhammad Shahid Khan, Jieru Quan

DATA COLLECTION: Jieru Quan

INTERPRETATION OR ANALYSIS OF DATA: Jieru Quan, Muhammad Shahid Khan

PREPARATION OF THE MANUSCRIPT: Jieru Quan, Muhammad Shahid Khan

REVISION FOR IMPORTANT INTELLECTUAL CONTENT: Muhammad Shahid Khan

SUPERVISION: Muhammad Shahid Khan.

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