The past two decades have seen an implausible increase in the number of universities in Pakistan. Although this seems to be a positive sign of a thriving education sector in developing countries like Pakistan. However, there has been no substantial improvement in the performance of Pakistani universities, which is why it is often criticized by various segments of society. Instead, this dramatic increase has created immense competition among universities for survival and profitability, resulting in a compromise in the quality of education. Such a competitive environment induces university authorities to use deceptive marketing tactics to attract more students than others. Several researchers have highlighted the use of deceptive marketing strategies to attract potential students, including image manipulation and misleading claims such as exaggerating graduate employment rates and university rankings (Bradley, 2013, 2018; Ramsey and Wesley, 2015; Chiang et al., 2020). Therefore, researchers have opined that while aiming for university profitability and survival, academic quality should never be undermined (Iqbal et al., 2023). This is also supported by researchers that such performance of Pakistani universities is due to low academic quality (Iqbal et al., 2022a), particularly in three domains, teaching, research, and services (Hoodbhoy, 2009; Banuri, 2021; Murtaza and Hui, 2021). These three domains are also known as three academic roles/goals that universities must fulfill, including (1) teaching; (2) research; and (3) service or third-mission (Edgar and Geare, 2013; Agasisti and Bertoletti, 2019).

International Organization for Standardization, famously known as “ISO,” has defined teaching as “working with learners to assist and support them with learning” (ISO 21001, 2018). As for teaching performance (TP), it is comprised of outputs related to teaching and learning goals for HE systems (Agasisti and Bertoletti, 2019). TP is one of the problem areas in the Pakistani HE context, and researchers have identified several reasons including: the absence of the latest knowledge; poor teaching methods (Banuri, 2021; Murtaza and Hui, 2021); poor learning skills; poor evaluation systems (Hoodbhoy, 2009; Banuri, 2021; Murtaza and Hui, 2021); superficial hiring process of teachers with political interference (Banuri, 2021; Murtaza and Hui, 2021); student disciplinary problems, academic scams by teachers, and shorter working days (Hoodbhoy, 2009); and lack of faculty members with PhDs (Hoodbhoy, 2009; Murtaza and Hui, 2021).

Research performance (RP) implies the “research output of academic staff and HE researchers” (Agasisti and Bertoletti, 2019). RP is the knowledge acquired through research and transfers it to others (Bazeley, 2010). Many researchers have attempted to measure RP, but have mostly used secondary sources such as bibliometric approaches, systematic reviews of the literature, university ranking data, and articles extracted from various databases (Abramo et al., 2013; Aldieri et al., 2020; Javed et al., 2020). RP is weak in Pakistani universities due to many reasons including: corrupt culture; scam/fraud journals; poor criteria for evaluating research work systems (Hoodbhoy, 2009; Banuri, 2021); lack of proper (quality) research; imbalance between teaching and research; and poor research skills (Nisar, 2019).

As for service performance (SP), it is also called a third-mission performance, which means “to capture the contribution of universities to society, including the benefits outside the academic environment that arise from HE” (Agasisti and Bertoletti, 2019). SP is another weak area in the Pakistani HE context. Services are a kind of facts, processes and performances (Zeithaml et al., 2018). According to ISO, educational service is a “process that supports acquisition and development of learners’ competence through teaching, learning or research” (ISO 21001, 2018). The quality of student services in Pakistani universities is considered poor, which affects the HE system in Pakistan (Nisar, 2019). The researchers argued that multi-stakeholder involvement is the obvious reason for poor service performance in HE (Hwarng and Teo, 2001). The researchers have argued that, as part of the service industry, universities are expected to provide quality services to all customers (academic and non-academic) and any deviation from this will lead to poor service quality and thus low customer satisfaction (Iqbal et al., 2023). Similarly, university faculty are also expected to take on service roles in addition to academic roles, such as teaching and research (Brazeau, 2003; Neumann and Terosky, 2007). However, it is argued that the service role of the faculty is often ignored by the university administration, despite the fact that they spend a reasonable amount of time in various service positions at their respective universities (Throm, 2018). Service performance in a HE context is therefore a broader concept that involves services for internal and external customers, as well as faculty service roles. However, in the previous literature, there is no evidence that researchers have attempted to investigate services that combine all three of the above.

The term motivation originated from the word “motive” and is conceptualized in terms of a person’s wants, needs, desires, and drives (Badura et al., 2020). Motivation is an urge or mobilization force that can drive, direct, and organize human behaviors (Inceoglu et al., 2012). Similarly, motivation is also described as the provision of incentives to encourage people to act in accordance with their desires (Certo, 2019). Motivation can be divided into two forms of intrinsic and extrinsic motivation, depending on the characteristics or subject matter of the various factors that trigger the behavior (Deci et al., 1975). IMOT is defined as the task undertaken based purely on the inherent satisfaction of an individual rather than depending on some consequence (Zeng et al., 2022). Simply put, IMOT is an internal desire that drives an individual to produce more and better (Mazllami, 2020). People are said to be intrinsically motivated when they act because of the attraction or satisfaction associated with a particular activity (Rita et al., 2018). Some researchers have investigated the influence of IMOT and EMOT factors on organizational performance, and the results found that IMOT is more influential than EMOT in relation to organizational performance (Senanayake and Gamage, 2017; Olugu et al., 2018). Researchers believe that a lack of IMOT may lead to poor job performance, which in turn negatively impacts organizational performance (Kusumah et al., 2021). This is consistent with some recent findings that IMOT strongly affects employee/job performance (Kuvaas et al., 2017; Tran et al., 2021; Jnaneswar and Ranjit, 2022).

In the context of HE, little evidence is available regarding IMOT and organizational performance. For instance, a researcher in her qualitative research conducted at a private sector university in Dhaka, Bangladesh, found that most faculty believe IMOT is a way to stimulate enthusiasm for teaching and research, continually improve quality of teaching and maintain satisfaction (Rahnuma, 2020). Conversely, some empirical studies have also been conducted to examine the association between IMOT and faculty performance, but their results are not consistent. For instance, a study conducted at Romanian public universities showed that IMOT was positively associated with the research productivity of faculty members (Horodnic and Zait, 2015). However, this study has some limitations. First, the survey only involved faculty members from the Department of Economics and Business Administration of 22 Romanian public universities. Second, the study ignored faculty members at private universities. Furthermore, the study aimed to examine the relationship between IMOT, EMOT, and faculty research performance, which is just one performance aspect among others, including teaching, assessment, and service roles. Therefore, the results of the study cannot be generalized to faculty members of other disciplines, nor to private universities around the world. While another study conducted at three technical/vocational colleges in Lagos, Nigeria, did not show a significant relationship between IMOT and instructor performance (Olushola and Adewumi, 2021). However, the context of this study was quite different from that of Romanian public universities. Romania is a European country, so faculty members at Romanian public universities can get good salaries, fringe benefits, and a more favorable environment. Conversely, the Nigerian counterpart vocational and technical colleges (instructors) may lack such resources and facilities due to Nigeria’s weak economy. They may have a hard time meeting their basic needs, so their priority may be meeting their monetary needs and then following their inner drives. Given the limited studies involving IMOT and HEP, and the lack of sufficient empirical evidence in the context of HE, the following hypothesis is proposed:

Extrinsic motivation involves valuing or complimenting someone’s behavior as a tool, so the satisfaction obtained does not come from the activity, but as an external result leading to the activity (Rita et al., 2018). According to another definition, EMOT relates to performing an activity to obtain some separable result rather than engaging in an activity solely for its instrumental value (Zeng et al., 2022). EMOT is primarily expressed in terms of various financial incentives such as wages, salaries, bonuses, promotions, and other fringe benefits that an organization offers its employees to improve their performance (Jeni et al., 2020). In prior literature, many researchers attempted to determine the relationship between EMOT and employee and/or organizational performance, however, the results were inconsistent. For example, some studies have shown that EMOT has a positive and significant effect on employee performance (Makki and Abid, 2017; Jeni et al., 2020; Mazllami, 2020; Noorazem et al., 2021). In contrast, few studies have indicated that EMOT does not affect employee performance (Olafsen et al., 2015; Kuvaas et al., 2017; Nurenny and Hidayat, 2020). Similarly, in a relatively new study, researchers found that EMOT had no effect on the work engagement of nurses in Japanese welfare and healthcare institutions (Zeng et al., 2022).

In the HE context, some researchers conducted an exploratory study to examine the various IMOT and EMOT factors of teacher motivation at 5 public universities in Pakistan. The results of the study showed that extrinsic factors including (1) wages, (2) job design and work environment, (3) performance management system, and (4) training and development positively influence the motivation of teachers in public sector universities in Pakistan (Rasheed et al., 2016). In addition, a couple of empirical studies were conducted in the Nigerian educational context, and their findings revealed a positive relationship between EMOT and teacher performance. For instance, a study conducted in Nigerian colleges of education has revealed that monetary and non-monetary incentives positively influence teachers’ job performance (Alade and Okeke, 2021). Likewise, another study conducted in three technical/vocational colleges in Lagos, Nigeria, revealed that EMOT is positively and significantly related to instructor performance (Olushola and Adewumi, 2021). On the contrary, in another study, the researchers found that although IMOT is positively correlated with the research productivity of academic staff in Romanian public universities, however, the relationship between EMOT and academic staff’s research productivity was negative (Horodnic and Zait, 2015). This could be due to contextual differences such as the availability of resources, facilities, environment, and salary packages given to academic staff from universities operating in Nigeria and Romania. Given both contexts, it can be argued that faculty members at Nigerian universities seem to be more influenced by monetary and non-monetary benefits, while academic staff at Romanian universities tend to perform their tasks for inner reasons like fun and enjoyment. Besides, the results of another study based on a literature review show that although there is no conclusive evidence on which motivation approach is better for driving a performance culture within an organization, the role of employees is definitely important in this regard. The study further added that EMOT often has a tendency to attract employees, but organizational leaders must clearly communicate to employees what they need to do so that leaders can motivate them externally (Turner, 2017). Based on the above discussion, inconsistent findings, and lack of sufficient evidence the following hypothesis has been proposed:

Quality culture is a “set of group values that guide how improvements are made to everyday working practices and consequent outputs” (Harvey, 2004). Quality culture is a continuous improvement process where the entire organizational community is responsible for maintaining a favorable work environment leading to organizational excellence (Trewin, 2002). QC in the context of HE is understood as “the overall attitude of an institution, which focuses on the concept of quality and applies it to all aspects of its activities” (Ali and Musah, 2012). Researchers have examined QC as an independent variable in relation to organizational performance and found a positive relationship (Yusof and Ali, 2000; Ali and Musah, 2012; Wu, 2015). In a recent study, researchers examined the effect of QC on service quality (SQ) at public and private universities in Pakistan. The results showed that QC strongly affects SQ in both types of universities, however, this effect is stronger in private than public universities (Iqbal et al., 2023). Likewise, in another study, QC was examined in relation to Kenyan research university performance, and the findings showed a strong association (Katwalo and Asienga, 2015). However, since this study was only conducted at a single university in Kenya; therefore, the results need to be verified with a larger population. Similarly, the effect of QC was also found to be significant in relation to university performance in the context of Nigerian universities. However, the results revealed that QC predicted only 30.4% of the variation in university performance, while the scope of the study was also restricted to Nigerian universities. Therefore, the authors have recommended future researchers to introduce other predictor variables and to conduct a study on a broader spectrum (Hilman et al., 2017). Given the weaknesses of prior studies as discussed above, the following hypothesis can be formulated:

Several studies in the previous literature investigated IMOT and EMOT as predictor variables, but not in relation to QC. However, only a few studies have examined employee motivation in relation to organizational culture (OC). OC is a broader term that consists of shared values, beliefs, attitudes, customs, and norms found within an organization that shapes the behaviors and decisions of its members, but still, there is no agreed definition (Gautam and Basnet, 2021). For instance, “organisational culture is the way that things are done in an organisation, the unwritten rules that influence individual and group behaviour and attitudes” (Chartered Management Institute, 2015). By contrast, QC is a subset of OC (Dellana and Hauser, 1999) and focuses specifically on shared values and commitment to quality (Bendermacher et al., 2017).

Some researchers investigated employee motivation as the dependent variable in relation to OC, and the results showed that OC was strongly correlated with employee motivation (Yusof et al., 2016). While few studies examined motivation as a mediator, however, the findings on OC and motivation were conflicting. Such as, researchers have found an insignificant and negative effect of OC on the IMOT of employees at a coal company in Indonesia (Hariadi et al., 2022). Likewise, in another study, researchers have found an insignificant effect of OC on the motivation of employees working in the “Employment Social Security Administering Agency” located in Tangerang City, Indonesia (Riyanto et al., 2021). However, both studies have different scenarios, and their samples are not truly representative of their population.

In contrast, there is little evidence that researchers have investigated employee motivation as an independent variable in relation to QC or even OC. For example, few researchers have sought to determine the influence of teacher motivation on the OC of undergraduate universities in the city of Bangalore, India, and the results found that teacher work motivation is positively related to OC (George and Sabhapathy, 2014). Given the distinct roles of motivation in relation to OC identified by these investigators, it has become apparent that these studies suffer from fragmentation as no agreement has been reached on a specific role of motivation in relation to OC. Based on the above-mentioned discussions, this study has proposed the following hypotheses:

Even though QC is a widely used term, its meaning remains unclear due to a lack of consensus (Nygren-Landgärds et al., 2022). In previous literature, researchers mainly investigated QC in qualitative studies (Adina-Petruţa, 2014; Njiro, 2016; Bendermacher et al., 2017; Lycke and Tano, 2017; Tutko, 2019). While in quantitative studies QC has been mainly investigated as a predictor variable in relation to organizational performance, and the results showed a positive effect on organizational performance (Ali and Musah, 2012; Katwalo and Asienga, 2015; Wu, 2015; Ullah et al., 2016; Hilman et al., 2017). Furthermore, some studies explored QC as dependent variable, and the results showed a positive association with TQM practices (Al-Otaibi, 2015); IQA (Do et al., 2020); and visionary leadership (Herminingsih et al., 2020). However, only a handful of studies have examined QC as a mediator, and the results showed that QC mediates between: talent management (two of the three dimensions) and university performance (Abubakar and Hilman, 2017); TQM practices and competitiveness of Saudi contractors (Alotaibi and Islam, 2013); while partial mediation between QMP and innovation performance (Alotaibi et al., 2016). Given the ambiguity regarding the exact role of QC and based on the guidance of the previous researcher (Al-Otaibi, 2015); current researchers have decided to investigate QC as a mediator in the relationship between IMOT, EMOT, and HEP in the Pakistani HE context. The aim was to examine the underlying mechanism in the relationship between IMOT, EMOT, and HEP, and to explain why this relationship exists. Given the above discussions, the following hypotheses have been postulated:

Given the gaps identified in the existing literature, a conceptual framework has been proposed based on the resource-based view (RBV) theory. RBV theory holds that a firm’s resources and capabilities are the primary sources of its competitive advantage and economic value creation. The present study has underpinned the RBV theory, so that universities can use their unique resources, such as IMOT, EMOT, and QC, as key determinants of their long-term performance and competitive advantage (Wernerfelt, 1984; Barney, 1991). The framework consists of two independent variables (IMOT and EMOT), a mediator (QC) and a dependent variable (HEP). The conceptual framework is shown below in Figure 1.

This study employed a survey-based quantitative cross-sectional research design. Survey-based design is highly effective and has many advantages, such as its ability to cover geographically dispersed areas, its ethical nature, and because it implies economy and rapid response time in data collection (Creswell, 2014; Fowler, 2014). Similarly, the cross-sectional approach is more suitable for collecting data at a certain time (Sekaran and Bougie, 2016) since it reduces time, cost, and effort.

The study population (N = 226) consisted of public and private universities in Pakistan, with institutions as units of analysis and administrative managers (such as VCs, Deans, Directors, and HODs) as respondents. Considering the institution as the unit of analysis, only one respondent from each randomly selected university was selected. The sample size was determined as 144 universities based on the formula of previous researchers (Krejcie and Morgan, 1970). However, the questionnaires were administered at 150 randomly selected universities using proportional stratified random sampling techniques by dividing the entire population into seven strata based on provinces/administrative units across Pakistan. Stratified sampling is a highly precise and cost-effective technique that allows researchers to collect data from subgroups (Lynn, 2019). In addition, the stratified sampling technique was employed to maximize the random participation of universities located throughout the country to collect data and increase the generalizability of the results. The questionnaires were administered via online surveys and in-person visits. The questionnaires were distributed in person at 20 universities located in “Punjab” (one of the seven strata) that were relatively close to one of the authors. While online survey method was employed to collect data from 130 universities located in distant areas (the rest of the six strata) across Pakistan. The response rate recorded for the in-person method was 70% and for the online surveys, it was 74.6%. The response rate of the online survey was slightly higher than that of the in-person method (pencil and paper questionnaires). This is because the online survey is considered more convenient and easily accessible via a laptop or even a cell phone and takes less time than the in-person method. Of the 150 questionnaires administered, 111 were returned, of which 105 were usable, resulting in a valid response rate of 70.0%. The details regarding sample distribution and the response rate are shown in Table 1. The data were collected from March 2022 to May 2022.

Since all statements of the questionnaire were adapted from previous studies, it was necessary to pre-test the questionnaire. Therefore, the initial questionnaire was pre-tested by six experts working in leading universities in Pakistan or participating in TQM consulting activities. Overall, the experts agreed with most of the statements in the questionnaire. However, they did suggest modifications to improve the understanding and clarity of some statements, such as avoiding long, negative, and double-barreled statements, and standardizing the wording of all statements as much as possible. In addition, they suggested contextualizing QC statements from an HE perspective, reframing motivational statements from the perspective of academic staff, and rephrasing HEP statements from an institutional perspective.

Based on expert feedback, the questionnaire was refined and subsequently subjected to a pilot study involving 30 respondents. The results of the pilot study revealed that Cronbach’s alpha values for all constructs were greater than 0.70 and were therefore considered satisfactory (Hair et al., 2017). Such as IMOT (0.939), EMOT (0.911), QC (0.842), and HEP, including TP (0.914), RP (0.920) and SP (0.909), respectively. In summary, all the statements in the questionnaire were found to be reliable, demonstrating that the questionnaire design and the sequence of the statements were acceptable for conducting a large-scale study.

As for the structure and design of the questionnaire, it consisted of nine demographic questions, while 47 questions related to latent variables such as IMOT, EMOT, QC, and HEP. The items used to measure the latent variables were based on a 5-point Likert scale, where 1 = strongly disagree and 5 = strongly agree. The detail of the adapted scales and their items is as follows: IMOT and EMOT were measured using two scales, with nine items for each scale, and were developed by previous researchers (Mertler, 2001; Cruz et al., 2009; Hung, 2020). Similarly, QC was measured by adapting a four-item scale (Wu, 2015). The HEP consisted of three dimensions, the five items of the TP were adapted from two studies (Goos and Salomons, 2017; Dicker et al., 2019); five RP items adapted from a previous study (Yaakub and Mohamed, 2020); and 15 SP items were adapted from several studies (Nedwek and Neal, 1994; Hui et al., 2003; Badri and Abdulla, 2004; Asif et al., 2013; Asif and Searcy, 2014).

The demographic characteristics of the respondents from the participating universities are presented in Table 2. Of the 105 participating universities, 59 universities were from the public sector (56.2%) and 46 (43.8%) were from the private sector. Most of the universities were 36 (34.3%) from Punjab while 23 (21.9%) were from Sindh, 20 (19%) from KPK, 17 (16.2%) from Islamabad, 5 (4 0.8%) from Balochistan, 3 (2.9%) from Azad Jammu Kashmir and 1 (1%) from Gilgit Baltistan, respectively. As for the gender of the respondents, there were 81 males (77.1%) and 24 females (22.9%). Also, most respondents were HODs 67 (63.8%), Deans 17 (16.2%), and QEC Directors 13 (12.4%), followed by respondents in other positions.

The mean, median, and standard deviation values for all the variables based on the perceptions of the administrative managers were as IMOT (M = 3.43, Mdn = 3.44, SD = 0.73), EMOT (M = 3.31, Mdn = 3.28, SD = 0.76), QC (M = 3.32, Mdn = 3.25, SD = 0.88) and HEP (M = 3.37, Mdn = 3.41, SD = 0.72), respectively. The IMOT mean and median scores were the highest, followed by HEP, QC, and EMOT. The descriptive statistics of all the variables are presented in Table 3.

When data is collected from a single source and/or at the same time, the analysis could suffer from common method bias (Podsakoff et al., 2012). Thus, we applied Harman’s single-factor test to assess whether CMB is present, and the results showed that a one-factor solution explained only 41.12% of the total variance, which is below the 50% threshold. This is followed by another “Full Collinearity Test” recommended by a previous researcher (Kock, 2015); all resulting VIF values (Table 4) were found to be below 3.3, i.e., the threshold. Given the results of both tests, it can be assumed that the results of present study are not affected by CMB.

The evaluation of the structural model (Figure 3) is the second stage in the PLS-SEM; and was based on determining the explanatory power (R², f²) of the model, PLSpredict (Q²), and then the significance of the paths.