The Chinese University stakeholder satisfaction survey: Developing a customer-centered self-assessment tool for higher education quality management

Pan, Feng; Liu, Liu; Wang, Zhen

doi:10.3389/fpsyg.2022.1043417

ORIGINAL RESEARCH article

Front. Psychol., 01 December 2022

Sec. Organizational Psychology

Volume 13 - 2022 | https://doi.org/10.3389/fpsyg.2022.1043417

The Chinese University stakeholder satisfaction survey: Developing a customer-centered self-assessment tool for higher education quality management

$\r\nFeng Pan$ Feng Pan¹

Liu Liu^1*

Zhen Wang²

¹School of Physical Education, Sichuan University, Chengdu, China
²School of Physical Education, National Huaqiao University, Quanzhou, China

Introduction: Customer-centered management theory has considerable potential for increasing the quality of higher education (HE) in China and promoting its sustainable development.

Methods: This study applied customer-centered enterprise management theory to develop an HE stakeholder satisfaction scale based on data from 1,654 students, teachers, and other staff members, including human resources personnel.

Results: The three-part stakeholder satisfaction survey consists of the China University Student Satisfaction Scale, the China University Teacher and Staff Satisfaction Scale, and the China University Graduate Human Resources Department Satisfaction Scale. All three subscales were valid, reliable, and can be used to foster management innovation, although they require adjustments to improve their coverage of different HE environments.

Discussion: Organizational self-assessment based on customer-centered corporate management theory has much to contribute to the quality and sustainability of China’s HE systems.

Introduction

In the early 21st century, the rapid growth of new universities in China’s HE sector has led to a renewed focus on the quality of the services they provide. This process has resembled similar shifts that occurred in the European HE sector between the 1950s and 1980s, in which self-assessment was used to secure funding and became a crucial means of guaranteeing teaching quality and promoting institutional development (Peter, 1997). The central argument of this paper is that the internal management of Chinese universities requires similar alterations to raise the quality of provision and that these should be informed by customer-centered contemporary corporate quality management theories, as successfully used in Europe and the United States (Cardona and Bravo, 2012; Sen et al., 2012). As numerous studies attest, self-assessment proactively improves the performance of HE organizations. For instance, Hides et al. (2004) showed that self-assessment based on the “European Quality Award,” model actively influenced the organization’s ability to respond to pressure from its board of directors and other stakeholders while nurturing a customer-centered culture. Ruben et al. (2007) demonstrated that self-assessment in HE supports the acquisition of knowledge and identifies organizational strengths and weaknesses, increasing employees’ commitment to their organization and promoting beneficial change.

Effective corporate self-assessment depends on robust and comprehensive stakeholder satisfaction surveys. In the context of HE, the key stakeholders are teachers, students, and human resources (HR) departments. The current paper describes how a satisfaction survey was developed and tested for each stakeholder type to produce a comprehensive research instrument that can be used to nurture the scientific and sustainable development of internal management in universities in China.

Customer satisfaction can be understood as a person’s emotional response to a product or service (Kotler and Koller, 2016). It is a critical concept in marketing and key to consumer purchasing decisions and behaviors (Sun, 2009). In many countries and regions, consumer satisfaction indices are now widely used to assess quality and macroeconomic development (Fei et al., 2016). The famous ISO9000 quality management system standard proposed a new approach to quality control that placed customer satisfaction at its core: “Make consumers the focus and pursue consumer satisfaction.” Consumer satisfaction has become the starting point and destination for quality strategies in the 21st century (Nan and Zhao, 2008).

Nowadays, consumer satisfaction surveys are widely used in internal HE assessments under the assumption that higher education is a service (Ostrom et al., 2011) with internal and external customers. Internal clients work to accommodate external clients (Muchira and Bett, 2018), i.e., the purchasers or recipients of products or services outside an organization. Internal customers are the individuals or organizations within the corporation itself that receive products or services and whose outputs are linked to the work or actions of other departments or individuals within the same corporation (Maguad, 2007).

The idea of customer satisfaction self-assessment had become widespread in HE in Europe and the US by the mid-to-late 1990s. Researchers believed that the customer satisfaction orientation of such organizations had raised their efficiency to extremely high levels. Indeed, the increasing commercial success of universities has since confirmed that an emphasis on customers is conducive to organizational development (Eurico et al., 2013). Correspondingly, the satisfaction levels of students, teachers, and employers are critical self-assessment indices in almost all universities.

The perspective that students are customers is controversial and many people continue to reject it. However, Guilbault (2018) used a framework of market/customer orientation and service/relationship marketing and believed that students should be considered customers in the development of marketing strategy. Hanover Research (2015) stated that “Universities are recognizing that students are also customers and that excellent customer experiences are required across the student lifecycle.” Nearly all university managers surveyed by Pitman preferred to view students as customers while all respondents surveyed by Maguad (2007) agreed that students were customers, although a few objected to this description. Overseas researchers have found students to be particularly critical internal customers of HE services (Byrnes et al., 1994). They wish to learn skills, obtain knowledge, understand the world around them better, and gain confidence and opportunities in a pleasant environment (Zhang, 2012). If universities meet such expectations, customer satisfaction tends to be high.

However, if the education system only considers students as customers and overlooks the missions of organizations, the core philosophy underpinning self-assessment is seriously compromised. Viewing students only as internal or external customers creates problems such as the one-sided accommodation of student demands and disregard for the value and function of education. This may impact the positive effects of education on students and their social responsibilities after graduating from university. After students graduate, enter society, and take on jobs, their roles change: they become employees and, as graduates whose talents have been cultivated over several years, the products of higher education (Zhang, 2012). This dual character must be recognized in universities’ self-assessment processes: an HE student is not merely an internal or external client but a unique type of customer (see Figure 1).

FIGURE 1

Figure 1. Students’ growth and role based on the quality control of higher education self-assessment (Liu, 2018).

Co-workers are internal customers who should serve external clients with speed, courtesy, and professionalism to maintain cash flows (Coscia, 2019) and improve corporate development. Teachers, meanwhile, are the pillars of any nation’s education system and are vital to the development of its students. They therefore play a pivotal role in improving the quality of educational institutions (Mansur, 2020). Kolara et al. (2018) argued for the transparency of customer- and market-oriented strategies, suggesting that educational organizations base key performance indicators on internal quality and employee satisfaction. Thus, modern management concepts and viewing teachers as an organization’s internal customers are noteworthy aspects of HE self-assessment processes. Indeed, it is not difficult to find examples of teachers acting as internal customers of universities: they use various facilities such as the university’s library, offices, laboratories, gym, and swimming pool, and they require the school’s administrative departments to provide various services such as HR, transportation, and logistics (Chen and Si, 2006).

The major task of modern HE management is to align organizational and individual goals. The existence and development of a school depend on the labor of teachers, who in turn rely on specific organizational departments to function effectively. Universities and teachers have mutual goals around which management can integrate effective processes. A focus on internal customer demands and satisfaction can encourage teachers to act as organizational members and motivate them to create and maintain competitiveness (Mohsen et al., 2019).

Employers consume the talents cultivated in universities; specifically, they are the direct external customers of the products of higher education (Sirvanci, 1996). Here, “employers” would include institutes where graduates continue their studies or science and research institutions. Rinehart (1993) maintained that service and manufacturing industries and non-profit organizations are the most direct and largest external customers of universities. Every employer hopes that high-quality HE graduates will work efficiently for them and will favor candidates from a particular university based on their previous experience with its alumni. This requires employment-oriented HE institutions—especially vocational schools—to survey levels of employer satisfaction, which is one aspect of a comprehensive quality control process.

Because university graduates increasingly opt to start their own businesses, HE institutions have shifted focus to facilitating high-quality social and technological innovation via comprehensive startup ecosystems in universities, cities, and regions (De Jager et al., 2017; Wu et al., 2021). This means that graduates are also likely to become employers, adding to their uniqueness as internal and external customers.

In summary, students, teachers, and HR units are each a distinctive type of customer that possesses different characteristics and attributes. Students, as the most direct customers of higher education (defined as special customers to distinguish them from the HR units), are both customers and products. They pay tuition fees to purchase educational resources from the school and thus act as consumers or customers at this stage. After learning for some time, however, their status shifts from customers to products that are “consumed” by HR units. Teachers are the quintessential school employee, enjoying salaries, a work environment, and services such as personal development provided by the institution. Modern corporate management theory views them as internal customers of higher education. One perspective maintains that the satisfaction of internal customers is more crucial than that of external customers to corporate survival and development (Tao, 2008; Wu et al., 2022a,b). Finally, HR units are the most direct external customers of higher education. They receive the direct products—students—as employees that serve their units, whose efficiency and performance are directly affected by the quality of the graduate products. At the same time, the levels of satisfaction expressed by HR units has a direct bearing on student employment and is therefore also a critical indicator of HE quality. Figure 2 illustrates these relationships between students, teachers, and HR units.

FIGURE 2

Figure 2. Different customers in high education (Liu, 2018).

Materials and methods

Research methodology

The research used three methods to build the satisfaction index system. A literature review established the dimensions and items to be considered when designing the self-assessment tool. Interviews with expert informants laid the foundation for preparing the questionnaire and confirming its items and dimensions. Piloted questionnaires with various participants enabled the satisfaction survey to be tested, adjusted, and finalized.

The procedures and statistical methods for constructing the satisfaction scale in this study are as follows:

(1) Establish evaluation index database through literature.

(2) Summarize, consolidate, and streamline index.

(3) Select indicators through expert interviews and questionnaire.

(4) Select indicators through critical value and total-item analysis.

(5) Modified scale constructs use EFA.

(6) Validate model use SEM.

Research objects

The survey participants were students, teachers and staff, and employers. We recruited 1,056 students (736 men and 320 women), who completed the Survey for the Chinese University Student Satisfaction Index, the Chinese University Student Satisfaction Presurvey Scale, and the Preliminary Measurement Scale for Chinese University Student Satisfaction. We also surveyed 371 teachers and staff (220 men and 151 women) using the Survey for the Chinese University Teacher and Staff Satisfaction Index, the Chinese University Teacher and Staff Satisfaction Presurvey Scale, and the Preliminary Measurement Scale of Chinese University Teacher and Staff Satisfaction. Finally, 174 people employed in Chongqing City or Sichuan, Guizhou, Jiangxi, and Zhejiang provinces completed the Preliminary Measurement Scale of Employer Satisfaction for Chinese University Graduates (Draft Version), the Preliminary Measurement Scale of Employer Satisfaction for Chinese University Graduates, and the Survey of Employer Satisfaction for Chinese University Graduates.

The study also interviewed 53 experts (36 men and 17 women), including education experts, language experts and sports experts. And these experts come from various universities and education government departments in China (Table 1).

TABLE 1

Table 1. The research objects information.

Results

The student satisfaction survey

Determining the initial items

The Survey for the Chinese University Student Satisfaction Index was combined with a literature review to obtain 319 key indices that were subsequently merged and reduced to yield 70 items by a team of satisfaction and HE research experts. Following further review of the literature, discussions with experts, and piloting of the survey, these indices were classified into the following seven constructs: “teaching and study,” “student management and coaching,” “logistics services,” “academic cultural activities,” “learning and scientific research environments,” “school reputation and development,” and “internship and employment.”

Confirming the preliminary scale

To ensure the comprehensiveness, clarity, and rationality of the items used to measure each construct, we emailed the 70 key indices to five psychology experts to evaluate the face validity, logical validity, and language used. This allowed us to transform the 70 indices into the Chinese University Student Satisfaction Presurvey Scale, which was then tested and reduced to 67 items in the preliminary survey scale, 16 of which were included in the “teaching and learning,” construct, 13 in “student management and coaching,” 11 in “logistics services,” 6 in “academic cultural activities,” 9 in “learning and scientific research environments,” 4 in “school reputation and development,” and 8 in “internship and employment.” Responses were recorded on a 7-point Likert scale (1 = strongly disagree; 7 = strongly agree).

Analysis of the preliminary scale

Reliability analysis

The Cronbach’s α values of the constructs in the preliminary survey scale were 0.967 for “teaching and learning,” 0.952 for “student management and coaching,” 0.925 for “logistics services,” 0.940 for “academic cultural activities,” 0.946 for “learning and scientific research environments,” 0.926 for “school reputation and development,” and 0.970 for “internship and employment,” with an overall Cronbach’s α for the scale of 0.987. All these values were all greater than 0.80, indicating that the scale was reliable overall and the reliability of each construct was satisfactory.

Critical value and total-item analysis

After calculating the total scores from the samples, a low-scoring group consisting of the lowest 27% of scores (total ≤ 281) and a high-scoring group (the highest 27%, total ≥ 395) were identified. An independent samples t-test was conducted for the two groups and demonstrated that, for all items, significant differences existed at a statistical level of p < 0.1. Therefore, the critical value differences in this study were all statistically significant, and no item was removed. The correlation analysis of all items revealed that the minimum correlation coefficient was 0.658, well above the 0.30 threshold and higher than any other-item correlation, so no item required omission.

Validity analysis of modified scale constructs

Principal axis factoring was adopted in this study, with exploratory factor analysis (EFA) performed via oblique rotation and using the standard Kaiser criterion for scale data that had passed critical value screening and total-item, other-item analysis.

Exploratory factor analysis was conducted three times in this study: the factor loadings were too low in the first two iterations and two-factor loadings were observed, which were then removed. The removal of the seventh factor left one construct containing only a single item, which was also removed following Wu (2000) recommendation that constructs with fewer than three items should be cut. Subsequently, EFA was conducted a third time (KMO = 0.972, Bartlett’s Sphericity Test p = 0.00). After oblique rotation, we discovered that six factors had eigenvalues larger than 1 (Table 2). The amount of variance each explained was 54.466, 4.677, 3.065, 2.545, 2.266, and 1.527%, and their cumulative contribution was 68.545%. For all constructs, all items had a factor loading of 0.3 or more.

TABLE 2

Table 2. Total explained variance of the third exploratory factor analysis (EFA).

After rotation, the component matrix revealed that all 58 remaining items could be discretely categorized into six constructs. Constructs 1, 2, 3, 4, 5, and 6 contained 16, 11, 9, 6, 6, and 10 items, respectively. The names of the constructs were “teaching and learning,” “logistics services,” “internship and employment,” “learning and scientific research environments,” “academic culture and life,” and “student management and coaching.” After comparison with the preliminary test scale, the “school reputation and development” construct was deleted.

Hypothetical model of student satisfaction

Based on the item analysis results from the preliminary test scale, we hypothesized a second-order, seven-factor model of student satisfaction within a particular university. The first order contained teaching and learning, logistics services, internship and employment, learning and scientific research environments, and student management and coaching. The second order consisted of these six related first-order satisfaction constructs combined into one factor: student satisfaction.

Construct validity of the revised student satisfaction scale, based on exploratory factor analysis

Reliability analysis

The Cronbach’s α values of the constructs in the revised scale were 0.955, 0.908, 0.953, 0.927, 0.929, and 0.930, respectively. The Cronbach’s α of the overall scale was 0.979. Because the Cronbach’s α values of each construct and the overall scale were all greater than 0.80, the scale was considered entirely reliable The correlation coefficient of each construct was between 0.534 and 0.744, showing their strong interrelationships and relative independence from one another.

Construct validity analysis and verification of the hypothetical model

The item analysis retained 58 items in the formal scale to collect data for EFA using structural equation modeling software (AMOS 17.0). Maximum likelihood was used to estimate the model, and a covariance matrix was used. Raw data were obtained from a sample of 382 people. The large number of items was reduced to 18 in order to reduce the number required for processing.

The analysis showed that X2/DF = 2.66 (343.120/129) and p = 0.00 < 0.01, thereby falling within the 1–3 range proposed by Ho et al. (2004). The non-normed fit index (NNFI) was 0.968, the goodness of fit index (GFI) was 0.911, the adjusted goodness of fit index (AGFI) equaled 0.881, and the comparative fit index (CFI) was 0.973. All these indices reached or approached 0.90, the standard proposed by Finlay (1996). The root mean square error (RMSE) was 0.066, smaller than 0.08, thereby indicating an acceptable model fit (Finlay, 1996). Both the overall model fit and the scale’s construct validity were acceptable.

The standardized estimate model of the measurement model is shown in Figure 3. Each item (combined item) had relatively high factor loadings (>0.8) in their corresponding constructs. The factor loadings of the six constructs were 0.83, 0.83, 0.88, 0.73, 0.90, and 0.88 while their predictability values were 0.69, 0.69, 0.77, 0.53, 0.81, and 0.77, respectively. Figure 3 also revealed that the “academic culture and life” construct had the largest factor loading and the highest predictability in the student satisfaction survey.

FIGURE 3

Figure 3. Standardized estimation model of Chinese University student satisfaction scale.

Summary

In the first part of this study, we used software to compile an online survey and paper questionnaire that were distributed to 1,056 university students. After data analysis, the China University Student Satisfaction Scale was finalized. The scale comprised 58 items over 6 dimensions: “teaching and learning,” “logistics services,” “internship and employment,” “learning and scientific research environments,” and “student management and coaching.” The reliability and validity analyses and model validation all returned positive results. Furthermore, each index of the hypothetical model based on the scale achieved the required standard to confirm the goodness of fit.

The teacher satisfaction survey

Confirming the initial items

The Survey for the Chinese University Teacher Satisfaction Index was used to conduct surveys and relevant literature analysis, with 187 key indices reduced into 58 items by an expert team consisting of five satisfaction researchers and three HE scholars. The literature review and survey results enabled all indices to be classified into the following eight constructs: “basic work situations,” “social acknowledgment,” “salary,” “logistics services,” “scientific research and management,” “relationships with each administrative level,” “a humanistic environment,” and “overall school development.”