Introduction

Research is, and has long been, a central activity of universities (Brew and Lucas 2009). The research productivity of universities is an important or key performance index when it comes to their ranking either at home or abroad, and it is also well recognised as an indication of their influence and competitiveness (Morze et al. 2022). Higher education (HE) institutions are engaged in a toxic race to reach the prestigious rankings that bring in revenue and status. Amidst this competitive climate, HE teachers are under pressure to perform while institutions struggle to attain the status of world-class research universities (Sondari et al. 2016). Faculty members at universities are expected to publish not only nationally but also internationally (Anderson and Shannon 1988; Lucas and Murry 2016) with the aphorism “publish or perish” used to indicate the reality of the pressures that academics endure (Zhang 2021; Nygaard 2017). Teachers’ research performance also determines their promotion and job security; therefore, teachers struggled to publish their work in peer-review journals, and most often in highly-ranked journals, those covered in indexes such as the Science Citation Index Expanded (SCIE), the Arts and Humanities Citation Index (AHCI), or the Social Sciences Citation Index (SSCI) (Zhou et al. 2022).

Given that academic publications are predominantly in English, maintaining the level of high-quality publications is a particular challenge for universities in non-English dominant countries. For example, according to the Google Scholar metrics, the top 100 journals publish research in 11 languages, including Japanese, Korean, Polish, etc., but not in Chinese. When comparing with other countries, such as Spain, India, Swiss and so on, in Google Scholar metrics, we can see that public access to Chinese academics’ publications is the lowest (51%) from 2019 to 2021. It seems that Chinese academics’ research is not as widely disseminated as that of scholars from other countries. This is mainly because Chinese EFL academics have been reported to have fewer records in research compared to teachers of other disciplines in the social sciences (Borg 2009; Peng and Gao 2019). The existing literature has revealed various factors influencing teachers’ research productivity from individual and institutional perspectives (Heng Hamid and Khan 2020). These factors include research competency (Prado 2019), research self-efficacy (Randazzo et al. 2021), research motivation (Borg 2015; Borg and Liu 2013; Stupnisky et al. 2022), socialisation of teachers (Hedjazi and Behravan 2011; Nguyen 2022), demographics (age, gender, qualification, rank), and teachers’ working experiences (Farooqi et al. 2019; Hedjazi and Behravan 2011); institutional factors involving working environments (Li and Zhang, 2022); time allocation (Barber et al. 2021); extra administrative duties and institutional support (Randazzo et al. 2021; Sakarkaya 2022; Uwizeye et al. 2022); financial support (Randazzo et al. 2021); institutional culture and inadequate mentoring (Okon et al. 2022); research skills training (Kyaw 2021) and collaboration among teachers (Owan et al. 2023). Although many scholars studied individual-level research productivity and factors that contributed to its increase (Duc et al. 2020; Gironzetti and Muṅoz-Basols 2022; Nygaard 2017), few have been reported that are relevant to an EFL context in developing countries (Noorollahi 2021; Owan et al. 2023).

As it is known, China is a developing country with many changes in its educational sector. There are 3472 higher education institutions (HEIs), including 2688 regular HEIs and 784 non-government (private) HEIs (Ministry of Education [MoE], 2020). Traditionally, these HEIs are categorised into the following types: “Project 985” universities (39 universities), “Project 211” universities (116 universities), ordinary/regular universities and colleges. “Projects 985/211” universities are considered top-tier institutions in China, with “Project 985” universities being established as elite institutions derived from the “Project 211” universities. The government allocates varying financial budgets to different types of universities, with higher-level institutions receiving larger budgets (MoE 2007). The MoE proposed the “Double First-class” university initiative in 2017, with the objective of establishing first-class universities and disciplines of the world (MoE 2017). This initiative encompasses all universities under the “Projects 985/211” umbrella. Notably, it diverges from the “Projects 985/211” framework by employing a dynamic university list subject to reassessment every five years (MoE 2017). Universities failing to meet the specified criteria are subject to removal from the “Double First-class” designation. In our current study, conventional categorisation was employed to ensure the reliability and consistency of the results.

Among those factors, motivation has been reported to be one of the most influential factors for teachers’ research productivity (Borg 2015; Borg and Liu 2013), teachers with a stronger research motivation show better research performance (Duc et al. 2020; Nguyen et al. 2021). Nevertheless, most available studies merely focused on teachers’ general research behaviours, few of them specialising in their research motivation in China (Liu 2016; Zhou et al. 2022). Zhang (2014) proposed that the contextual factors need to be considered when studying human dynamics because they are not isolated but associated with the culture of their organisations. Employees accomplish their work within the created context of organisational culture (Nguyen et al. 2021). When individuals show motivation naturally, it indicates that the organisation has created a conducive work environment and ambiance to promote their motivation (Duc et al. 2020). However, the level of teachers’ research motivation is various with diverse factors affecting their research motivation. These include demographic factors, gender (Tran et al. 2021), age (Henry et al. 2020; Sadeghi and Abutorabi 2017), rank (Heng et al. 2020), qualification (Nguyen et al. 2021), years of employment (Horodnic and Zait 2015), intrinsic factors including research interests (Horodnic and Zait 2015), research capability and expectation (Nguyen et al. 2021), satisfaction and acquiring new knowledge (Zhou et al. 2022), enjoyment and collaboration (Yuan et al. 2016), sense of creativity-curiosity (Chen and Zhao, 2013) and extrinsic factors involving tenure (Miller et al. 2011), solving teaching problems (Yuan et al. 2016), promotion (Heng et al. 2020), organisational support (Nguyen et al. 2021), salary increase (Horodnic and Zait 2015), rewards and punishments (Zhou et al. 2022), teachers’ education or experience (Sun and Zhang 2022), administrative post (Tran et al. 2021), and job security (Tian and Lu 2017). Although diverse factors have been studied affecting teachers’ motivation for conducting research, institutional support can be prioritised (Randazzo et al. 2021). Sakarkaya (2022) found that institutional support is one of the most prevalent barriers to teachers’ research in Turkey, which is supported by Borg and Alshumaimeri’s (2012) and Kyaw’s (2021) studies. However, Randazzo et al. (2021) found teachers’ research motivation is positively related to institutional support in the United States. It corresponds to Randazzo et al.’s (2021) study that proper institutional support significantly drives teachers’ research. With inconsistent findings from different countries, further studies are needed to explore the impact of institutional support on teachers’ research motivation in different contexts. Additionally, as existing studies mostly showed pure quantitative or qualitative conclusions (Sadeghi and Abutorabi 2017; Yuan et al. 2016), there is a need for a mixed-methods study to explore both the general situation of institutional support for Chinese EFL teachers and how it affects their research motivation (Liu 2016). Accordingly, our study investigates the influence of institutional support on motivation among academics in China, a typical EFL context in which English is seldom used as a working language or informally for daily communication. It also aims to explore the significant measures to promote Chinese EFL teachers’ research motivation.

Literature review

Teachers’ research motivation

Motivation refers to “the dynamically changing cumulative arousal in a person that initiates, directs, coordinates, amplifies, terminates, and evaluates the cognitive and motor processes whereby initial wishes and desires are selected, prioritised, operationalised, and (successfully or unsuccessfully) acted out” (Dörnyei and Ottó 1998, p.65). In other words, it initiates people’s behaviour and directs, energises, sustains, and eventually terminates the action (Graham and Weiner 2012). Motivation research in general education and applied linguistics has a history of more than 60 years (Al-Hoorie 2017). However, the study on teachers’ motivation only has a relatively short history of over 20 years (Han and Yin 2016), and these primarily focus on aspects of motivation related to teaching (Liu 2016). Teachers’ research motivation was proposed for the first time just over a decade ago by Borg (2007). To date, few studies have examined teachers’ research motivation (Liu 2016). Existing studies pay more attention to how research motivation affects teachers’ research; however, the exploration of what factors affect teachers’ research motivation becomes an urgent task (Zhou et al. 2022).

In the current study, we follow scholars’ definition of motivation, which is traditionally divided into intrinsic motivation and extrinsic motivation (Dornyei and Ushioda 2011). Intrinsic motivation refers to the internal fascination and gratification of the activity itself as the main reasons to attract people to engage in an activity, while extrinsic motivation means incentives or external pressures that attract people to pursue an activity (Reeve 1995). Both intrinsic and extrinsic motivation are essential to teachers’ research engagement but have significant differences in different contexts (Borg 2007, 2009; Borg and Alshumaimeri 2012; Borg and Liu 2013). For example, Borg (2007) found that intrinsic motivation was more significant than extrinsic motivation in Turkey. In contrast, in the replicative survey, extrinsic motivation occupied a greater position than intrinsic motivation in China (Borg and Liu 2013). However, the reasons why intrinsic or extrinsic motivation is more significant are not clear because of the lack of follow-up in-depth studies. According to Han and Yin (2016), teachers’ research motivation varies in different contexts, and the investigation into motivation in the Chinese context is a scarcity. Drawing on the previous literature, this study uses mixed methods and concentrates on the current states of Chinese EFL teachers’ research motivation and institutional factors that positively or negatively impact it.

Institutional support for research

Research support can be defined as any provided resource that can boost the ability of a faculty member’s engagement in scholarship (McGill and Settle 2012). The provided support for teachers’ research affects their research motivation. For example, the disconnect between the institutions’ rhetoric and their actual actions affected teachers’ engagement and motivation for research (Randazzo et al. 2021). In China, Luo and Hyland (2016) found that a lack of institutional support was one of the main reasons why university teachers’ manuscripts cannot be published and/or are cited less often, even if they are published. A proper organisational work environment of the department, such as effective policies, reasonable structure, and supportive resources for the job (including incentives, practical goals, skills, and staffing), is necessary for any significant research (Bland et al. 2005). Given these justifications, the current study investigates how institutional support in Chinese universities concerning time-related support, funding-related support, training-related support, and working environment support affect teachers’ research motivation and engagement.

Time-related and funding-related support

Time constraint has been regarded as one of the constraints of being research-engaged for teachers (Borg and Alshumaimeri 2012; Kyaw 2021), which is a common phenomenon in many contexts (Borg 2006). For example, although teachers in Chile were willing to access and utilise research, they collectively stated that they lacked time to search for materials, read articles, and attend conferences (Sato and Loewen 2019). In accordance with Davey’s (2013) findings, teachers complained that their formal working hours were occupied by attending school activities, which hindered teachers from indulging in research-related activities. In such a situation, teachers understandably struggled to devote their time to research. Because of that, some researchers emphasised the necessity of separating research from teaching hours in faculty time allocation (Creswell 1985). As Kyaw (2021) found, the research activities were impeded by unbalanced workloads rather than heavy teaching loads in Myanmar. As a consequence, it was imperative that universities arrange schedules that allowed teachers to have sufficient time to gather resources and conduct research (Graves et al. 1982).

In addition, the allocation of funding for research was output-driven (Nundulall and Dorasamy, 2010). According to Sadeghi and Abutorabi (2017), in Iran, lack of funds was the second main reason teachers scarcely conducted research. McGill and Settle (2012) discovered that American and Canadian teachers who received more institutional funding were more likely to engage in research. At the same time, Randazzo et al. (2021) found that the research endeavours of American researchers were limited because not many people were keen to submit grant applications. The shortage of financial support led to a lack of opportunities to attend conferences and/or seminars at home and abroad (Kızıltepe 2008), resulting in weaker research motivation. Therefore, Wang et al. (2020) appealed for more research funding to be distributed to EFL teachers to encourage them to do research. However, different countries have different ways of allocating funds. To benefit Chinese EFL teachers’ funding distribution, the exploration of the current status of Chinese EFL teachers’ funding allocation is needed to boost their research motivation.

Training-related and working environment support

Mentoring is a form of institutional support in which a more experienced member provides information, support, and guidance to a less experienced, usually new member of an institution to enhance the latter’s chances of success within or beyond the institution (Campbell and Campbell 1997). Mentors are expected to serve as role models (Wanberg et al. 2007), who would transfer skills and support continuous learning, especially when skills are scarce (Nundulall and Dorasamy 2010). With mentors’ support, inexperienced researchers build confidence in their research (Griffiths et al. 2010). As Eby and Robertson (2020) proposed, mentoring positively affects the mentee, the mentor, and the organisation. As a capacity-building initiative, mentorship programmes can increase research outputs (Nundulall and Reddy 2011). Specifically, a practitioner-oriented research support programme was highly effective in promoting teacher research (Al-Maamari et al. 2017). Teachers who never received initial and continued support from the mentor hardly engage in or sustain research activities (Borg 2006). Nevertheless, mentoring has been perceived as a grey area in universities, theoretically established but executed ineffectively due to a lack of knowledge and interest, negative perceptions of mentorship, and the absence of university networks and role models (Owan et al. 2023). According to the available literature, the extent of its promotion and application in China is still unclear. Further research is needed to explore the effectiveness of mentoring among Chinese EFL teachers. Additionally, factors such as enhanced faculty research networks and collaborations are crucial for teachers because research collaboration is a growing trend among scholars (Paul and Mukhopadhyay 2022). In their systematic review, Uwizeye et al. (2022) found that teachers in African HE institutions had limited participation in research collaboration, which hindered their research motivation and research productivity. It appears that research collaboration significantly enhances scholars’ and institutions’ publications and rankings (Paul and Mukhopadhyay 2022). Therefore, research collaboration among faculty within and across institutions is highly expected to promote teachers’ research motivation and productivity (Yuan et al. 2016). However, effective collaborative methods between/among teachers still need to be further explored.

In addition, general guidance and skill development training from the relevant technical expertise also enhance university teachers’ research involvement (Wilkins 2011). It is necessary for teachers to possess related research knowledge and skills that help them to conduct enquiries soundly and share the findings effectively (Borg 2006). Among the available studies, researchers seldom noticed the enhancement of the actual research competence and skills from the training programmes (Gelso and Lent 2000). Insufficient research skills, such as language skills, information and communications technology skills, deter Burmese teachers’ research engagement (Kyaw 2021). In their study, Kozhakhmet et al. (2020) proposed that extra training and re-learning of research skills were needed for scholars in non-Anglophone and developing countries to fully become a member of the global scientific community. However, Loewen (2019) reported that language teachers were neither paid nor trained to conduct research, as was the case with teachers in Iran (Sadeghi and Abutorabi 2017). It is necessary for HE institutions that emphasise research to cultivate expert and knowledgeable faculty members by organising in-service training (Shariatmadari and Mahdi 2012). However, it is unclear whether Chinese EFL teachers receive sufficient research training as teachers and researchers.

Finally, teachers’ working environment is vital for their research involvement. In the current study, “research environment” refers to the behaviours that include, at a minimum, shared values, assumptions, beliefs, rituals and the valued, worthwhile and pre-eminent activity with a central focus on the acceptance and recognition of research practices and outcomes (Evans 2008). It was found that faculty members’ work environments drove their productivity and prominence (Heng et al. 2023; Way et al. 2019). Limited workspace, including sharing offices with other colleagues, affected Turkish teachers’ research negatively (Kızıltepe 2008). Sadeghi and Abutorabi (2017) claimed teachers in Iran are suffering from a shortage of access to essential books and journals for conducting research. Borg (2009) found that the lack of knowledge and access to research sources was the reason why teachers do not engage in and with research. The more and better resources were provided for teachers, the higher the level of research productivity was achieved (Dundar and Lewis 1998). Therefore, it is necessary for HE institutions to provide a conducive research environment for academics to stimulate their engagement with research (Tadesse and Khalid 2022). Thus, the Chinese EFL teachers’ working environment should be studied to help institutions to provide conducive environments for motivating teachers in research. Overall, it is necessary to study the current situation of Chinese institutional support and how it motivates or de-motivates teachers’ research.

Given the above justifications, there were two research questions for the current study:

  1. 1.

    What is the relationship between the institutional support and Chinese university EFL teachers’ research motivation?

  2. 2.

    What is the influential institutional support for motivating Chinese university EFL teachers to do research?

Methodology

An explanatory mixed methods design was adopted to maximise the benefits of utilising quantitative analyses of large samples to provide broad trends in the population, and delving deep into the experiences of a selected group of teachers to qualitatively understand the issues they face (Bryman 2006). Using a mixed-methods approach made it possible for researchers to explore the relationship among the selected variables in-depth (Frankel et al. 2019).

Data collection methods

Anonymous user-friendly online questionnaires (Bowen et al. 2017) for EFL teachers were the data collection instruments in the quantitative phase. These questionnaires were administered online, including on social media platforms (e.g., WeChat, a popular social media platform in China). The Questionnaire on Teacher Research Motivation (QTRM) and the Questionnaire on Institutional Support for Teacher Research (QISTR) were developed by drawing on Amabile et al.’s (1994) Work Preference Inventory Scale (WPI) and Angaiz’s (2015) Institutional Support Scale. QTRM examined EFL teachers’ research motivation involving both intrinsic factors (interest in research, responsibility for conducting research, mastery of research skills, sense of achievement, and flexibility of research) and extrinsic factors (respect from others (e.g., colleagues, students) and research compensation (e.g., promotion, salary raise) with 19 items. QISTR measures mentorship support and the teachers’ working environment with 10 items. The validity and reliability of the questionnaires were examined through Confirmatory Factor Analysis (CFA).

The qualitative approach to data collection involved two methods: semi-structured interviews and teacher diaries. Semi-structured interviews entail a formal questionnaire in verbal form, consisting of questions designed to elicit concrete answers from respondents to gain their ideas, opinions, and experiences in-depth (Fraenkel et al. 2012). This method enables researchers to explore the participants’ biographies and what they value, through which participants’ attitudes, opinions, and beliefs can be probed (Cohen et al. 2011). In this study, teachers were interviewed individually to encourage them to give deeper and more personal expressions to their thoughts and opinions (Sparkes and Smith 2014). Additionally, personal diary writing was a key data source for the qualitative data as a valuable supplementary method in a mixed-method study (Bartlett and Milligan 2015). By using teacher diaries, we were able to obtain rich data about teaching events, motivations, and emotions of the participants as they regularly recorded their experiences in an unhampered way and over a period of time (Bartlett and Milligan 2015). For teachers, a record of their research enables them to shape their thinking, explore ideas and “make an important discovery” (Borg 2002, p.163). This research was conducted following the guiding ethical principles of the authors’ university.

Procedures and participants

The survey was conducted first. The snowball method to recruit the participants was employed at this stage. The authors initially contacted one volunteer through their social networks. The invitation to join the study was sent to the first participant by email. After completing the questionnaire, the first participant recommended the next participant who met the criteria. In this manner, finally, 536 teachers completed the questionnaires. The questionnaire was distributed at the beginning of the first semester of the 2020–2021 academic year and it was open for four weeks. The first 12 teachers who agreed to participate in the interviews were chosen as the interviewees, and each participant was interviewed once, and each interview lasted for approximately 60 min, at a time and venue convenient for them. Two teachers were willing to record their research experiences in diaries for the past three months voluntarily.

The demographic information of the 536 teachers who took part in the quantitative phase is displayed in Table 1. Almost half of these teachers (49.2%) were from ordinary/regular universities. The number of teachers from “Project 985” and “Project 211” universities was close to each other, and the proportion was nearly one-fifth of teachers separately. College teachers had the lowest proportion (8.9%) of the teachers. As expected, female teachers nearly tripled male teachers, with 380 female and 128 male participants. Almost 40% (199 teachers) teachers were from the age range of 41–50, which was close to the percentage of teachers from the 31- to 40-year-old age group. There were 67 (13.2%) teachers under 30 years old, who participated in this study. A total of 45 teachers (8.9%) who were over 51 answered the questionnaire. Lecturers (226, 44.5%) and associate professors (195, 38.4%) accounted for over four fifths (82.9%), with only 59 (11.6%) assistant lecturers and 28 (5.5%) full professors in this study. Over half of the participants (309, 60.8%) were from the College English department (teachers who teach non-English majors) and the rest (199, 39.2%) were from the English department (teachers who teach English majors).

Table 1 Participant information.
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Table 2 shows the demographic information of the participants in the qualitative phase. T represents the teachers who attended interviews, and D is identified as a diary writer. The number after T and D represents the sequence of their attendance in the current study. Seven teachers were from ordinary/regular universities. A quarter of the teachers came from “Projects 985/211” universities, and one of them agreed to write a diary. Nine teachers were from ordinary/regular colleges and one of them recorded her research monthly.

Table 2 Basic information of the interviewees and diary writers.
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Data analysis

Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) were used in analysing quantitative data. AMOS was used to analyse the quantitative data at this phase. CFA was utilised to specify the relationships of the observed variables to the latent variables within the measurement model. The purpose of the measurement test was to evaluate whether the observed variables accurately reflect the desired factors and to determine to what extent the measurement model fitted the empirical data. Each measurement construct was examined separately with the sample of 508 Chinese EFL teachers who participated in the online survey. The model fit evaluation was conducted in line with multiple model fit indices. The final well-fitting models for the measurement constructs were specified by the model fit and chosen as the final model. The results of evaluating the model can be found in Li and Zhang (2022).

SEM, a multivariate statistical framework to model complex relationships between directly and indirectly observed variables (Stein et al. 2012), describes the relationship among various measurement model components. It can also address research questions associated with complex casual relationships among latent constructs (Nusair and Hua 2010). SEM was selected as the most appropriate analytical approach for establishing the relationship between independent and dependent variables in this study, primarily due to the following reasons: (i) the presence of multiple observed variables, as SEM is adept at examining and modelling relationships among numerous variables; (ii) consideration of measurement error, as SEM incorporates the assessment of measurement error, thereby acknowledging the validity and reliability of observed scores; and (iii) the analysis of multiple-level data, as SEM enables the examination of sophisticated theoretical models pertaining to intricate phenomena (Schumacker and Lomax 2016). The current investigation encompassed a total of 29 items, aligning with the first criterion of involving multiple observed variables.

Thematic analysis was employed for analysing and interpreting the qualitative data, with reference to the six phases of thematic analysis suggested by Braun and Clarke (2006). These phases were as follows: familiarisation with the data, generating codes, searching for themes, reviewing themes, defining and naming themes, and producing the report. Initially, the transcriptions were coded on the basis of the conceptual framework and research questions of this phase using the qualitative data software NVivo 12. The first author, who conducted the research, identified segments of the data and added a code to label the identified segments. The segments referred to a data extract with a unit of meaning related to the phenomenon under investigation, and a code meant a label that described the characters and meanings of the attached segment precisely (Braun and Clarke 2006). After coding the whole data, the researcher compared and contrasted those codes, and the similar and related codes were merged to form themes. Therefore, the redundant codes were reduced in quantity, and the themes were developed. The researcher repeatedly inspected the existing codes and original data to ensure there were no new codes. When all the themes were confirmed, the researcher reviewed the “determined” themes to guarantee their accuracy. The judgment of the themes was based on Patton’s (1990) criteria: internal homogeneity (codes within a theme should cohere meaningfully together) and external heterogeneity (different themes should be clearly and identifiably distinguished).

To ensure the trustworthiness of the findings, several steps were taken. The primary analysis was conducted by the first author and then shared and agreed upon with the other authors. Additionally, a portion of the data was coded by another independent researcher except for the authors, and an 85% rater agreement was achieved.

Results

Predictive effects of institutional support on teachers’ research motivation

To examine the effect of institutional support on teachers’ research motivation, we built a SEM. The measurement model of institutional support was used as the predictor to test its effect on teachers’ research motivation. Table 3 presents the results of the model index of SEM on research motivation, which were all in the acceptable range (χ2 = 1188.924; χ2/df = 3.240; CFI = 0.93; RMSEA = 0.066; SRMR = 0.0666; gamma hat = 0.90, TLI = 0.93). Figure 1 shows a simplified graphic representation of the SEM model with only significant paths.

Table 3 Results of the structural equation modelling (SEM) for research motivation.
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Fig. 1: Simplified Schematic Graph of Research Motivation Model to Full Sample.
figure 1

Mentorship = Mentorship Support; Working Environment = Working Environment of Teachers; Interest = Research Interest; Responsibility = Teacher Responsibility of Being Research-engaged; Achievement = Sense of Achievement; Flexibility = Flexibility of Doing Research; Respect = Respect from Others; Compensation = Compensation from Research.

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The two-factor model showed that the working environment (β = 0.344, p < 0.05) significantly influenced teachers’ research motivation. It suggests that if the working environment improves, teachers’ research motivation increases. The research motivation was explained 18.1% (R² = 0.181, f² = 0.22, p < 0.001) in total by this model. Table 4 reports the regression weights.

Table 4 Regression weights for the three-factor SEM of research motivation.
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Factors affecting teachers’ research motivation

Our qualitative analysis revealed both positive and negative findings relating to teachers’ research motivation. Teachers from “Projects 985/211” universities claimed that they had sufficient online databases support and support of building research teams as motivators to enhance their research motivation. While teachers from ordinary/regular universities reported that they were short of guidance for research, had poor working conditions, lacked time support, and experienced deficiency in academic conference funding, which waned their research motivation. We present further details on each of these themes.

Working environments of teachers

Universities are supposed to provide various support for motivating teachers to do research. Different universities set up various tasks for EFL teachers to accomplish based on their occupied resources. Top universities, such as “Projects 985/211” universities with better platforms, had higher research requirements than those ordinary/regular universities. T1, who was from a top “Project 985” university in the northeast part of China reported that her university would support them to publish in top journals, such as those covered indexes including the SSCI (Social Sciences Citation Index) and/or the CSSCI (Chinese Social Sciences Citation Index). She said that her university would invite experts from different fields to hold workshops and share their research experience with teachers. In addition, the online databases in support of T1’s university were sufficient. The library of her university provided literature-search services and supplemented to the databases when teachers required new online resources. The support of constructing research teams was also provided when it was needed. To organise a research team, the team leader was selected first, and the other members were recruited based on their research interests. Therefore, the collaboration among teachers was strengthened. While T6 from a “Project 211” university indicated that their university would give them more time but less funding support to accomplish the task of publishing a paper as compared with top “Project 985” university teachers. The research assessment of them was not as strict as with teachers in top “Project 985” universities. While their research support was sufficient for their current research requirement, the online databases were also sufficient for them to read. Teachers could choose to do more research or teaching based on their strengths. It means that teachers have the flexibility of choosing to be a researcher or a teacher.

However, as mentioned above, there are a number of different findings between teachers from “Projects 985/211” universities and ordinary/regular universities. In the ensuing section, findings from ordinary/regular university teachers are reported and as will be evident soon, these findings often show the negative side about research support.

Shortage of mentorship for teachers

The lack of mentors was an obstacle for teachers to get involved in research. Teachers usually did research alone. As T10 presented, she did not know how and who she could turn to for help when she encountered problems while doing research. She had to struggle with these problems herself, which would decline her positivity in doing research.

“How I wished that someone could help me with my research instead of working alone. However, even now, with high research pressure for teachers, there was no mentor for us. I suffered enough from doing research and wanted to stop now.” (Excerpt from the interview of T10)

Teachers urgently needed to engage in more research with the research pressure of “publish or perish.” To help them achieve the research engaged goal, the arrangement of mentors was pressing for universities. The research team was supposed to be a kind of impetus for teachers to engage in research. Different universities provided diverse support for organising a research team. Some universities explicitly encouraged teachers to set up research teams to establish better cooperation without a need for help. As displayed in T12’s interview, teachers had to explore the process of building up the research team themselves.

“Doing research alone was a little bit lonely. With the encouragement of the university, I applied for a research team at our university. What I did was to organize those teachers who had the same hobbies (planting) as me together. The university did nothing during this process.” (Excerpt from the interview of T12)

Other universities had no clear policy and support for establishing a research team, and teachers tried to organise a research group through their social networks. T3 reported the university hardly issued any policies to encourage them to discuss research. Teachers could only ask other teachers for help proactively.

“Because my rank was associate professor, I could apply projects as an organizer. Teachers who were willing to join me would be invited to join my team. The department provided no support for building a research team, and I used my social network merely to find research cooperators.” (Excerpt from the interview of T11)

It can be seen from the interviews of T11 and T3 that teachers were eager to have research teams that would benefit their research. The help from other teachers in the research team was valuable, especially for novice teachers. For teachers, the provided office from the university guaranteed their work efficiency. They could concentrate on their work in a proper space they could call their own. However, not all of the teachers were provided with the office, as reflected in T5’s interview:

“Our university provided no office for teachers. I had to go back home after teaching every time. It was hard for me to engage in research at home because I had no energy to do research after teaching and the long trip home. We did not have a place to prepare for our teaching, let alone do research. Our department was ignored by our university because we a liberal arts major in a polytechnic university.” (Excerpt from the interview of T5)

As one of the basic conditions of guaranteeing teachers’ research work, the provided offices for teachers needed to be awesome auxiliary support. It was found that teachers’ research motivation was influenced by database support. Some universities never provided database support for teachers. For example, T5 said that her university scarcely provided any databases for teachers, even the CNKI (China National Knowledge Infrastructure). She could not read the latest literature except by borrowing her friends’ accounts from other universities to download. It was very inconvenient. Therefore, she seldom did research.

Other universities supplied certain databases which were insufficient for teachers. The lack of sufficient online database support has been a common obstacle for teachers to engage in research. We can see from T4’s interviews that it was so hard for them to read the latest research in their areas of interest. If they wanted to read the latest literature, they needed to download it themselves and pay for it. It might be a financial burden to some teachers due to their low salaries, and they were unwilling to do it in this way.

“The basic Chinese databases were supplemented, such as CNKI and some other top Chinese journals. However, it was tough to search for the English databases. When I needed some foreign materials, I had to pay for them myself.” (Excerpt from the interview of T4)

Lack of time support for teachers’ research engagement

Five interviewees reported the heavy workload hindered their research engagement. According to these teachers, the teaching load was too heavy for them to do research. Teachers could only do research during vacations or weekends. For example, T12 said the daily reading habit was cultivated unsuccessfully because of the workload during each semester. A vacation was the time when she would read and write because she did not need to teach and attend various activities at the university.

Similarly, T7 reported that she had over 20 classes a week. There was no energy in her to discuss research after teaching. Besides, she needed to organise and take students to various competitions. Most of her work time was occupied by diverse workloads making her have no time to consider research. She said it was common for Chinese university teachers to struggle to be teachers and researchers at the same time.

Administrative meetings would influence teachers’ research engagement in different aspects, as shown in T7’s interview. On the one hand, the meeting was time-consuming for teachers. Their task was to sit quietly and listen to leaders’ speeches or briefings. If they were absent from the meeting, their salary would be deducted. It took up a lot of time; therefore, teachers had to allocate less time to research. On the other hand, these meetings seldom provided teachers with substantial, meaningful content for study. Teachers could not learn anything that benefited their research. Administrative meetings were necessary because of the need to manage a university. However, too many meetings became a burden for teachers, resulting in their research time deduction.

Deficiency in academic conference funding or opportunities

Generally, academic conferences made teachers engage in research more. However, it was found that T4’s university held few conferences, and she had fewer opportunities to communicate with other scholars and/or share her research with others. Although communication with other scholars would help teachers involve in research more often, the support for teachers to attend academic conferences was not enough. Teachers had few opportunities to attend conferences with little support from their university. Compared with other teachers who had enough support for participating in academic conferences, it was a disadvantage for those teachers with less support to be research-engaged.

Discussion

The quantitative and qualitative analysis of the influence of institutional support on their research motivation, as described in the preceding section, indicated opposite findings. An explanation for this discrepancy may be that participants responded to the questionnaires within a short time, which might have led to an inaccurate recall of their experiences. Brewer et al. (2004) claimed that participants may provide purposefully, or accidentally, imprecise recall and responses because of a lack of time to fully recall information. This section discusses the explanation of the consistency and inconsistency of the findings in relation to the literature.

Both the quantitative and qualitative results showed that working environments provided for teachers significantly affect teachers’ research motivation. According to Way et al. (2019), the drive for early-career faculty members to be research-engaged was where they worked rather than where they were trained. This emphasises the importance of teachers’ working environment as a facilitator for motivating them to be research-engaged, which aligns with Heng et al.’s (2023) findings. Nguyen et al. (2021) found that lecturers’ research motivation in Vietnam was positively affected by organisational support directly and indirectly. If teachers can access whatever they want for their studies, they then might be motivated to do research because they do not have to worry about lacking anything, such as materials and basic equipment. In the present study, the teachers from “Projects 985/211” universities claimed that an appropriate working environment guaranteed the auxiliary support for research, making them more willing to be research-engaged. Teachers from “Projects 985/211” universities seemed to have a supportive working environment with high research motivation, except for T5, who was from a polytechnic “Project 211” university. The unequal resource distribution within her university demotivated her from conducting research. Besides, the government unequally distributed its financial budget based on the university types in China, reflecting the reality that liberal arts majors are not valued in polytechnic universities and are even ignored. One possible explanation is that these universities are pressurised by the government to innovate and have research productivity in their strong disciplines (e.g., science, engineering, architecture). Therefore, more resources, such as independent offices, funding, online databases, among other things, are distributed to the science and engineering majors. Without sufficient institutional support, teachers of the liberal arts majors may gradually lose passion for conducting research due to a lack of funding, time, and latest databases support etc.

One unanticipated qualitative finding was that most teachers from ordinary/regular universities and colleges reported insufficient institutional support in their institutions. Teachers’ research motivation varied based on the university type, which is a new finding compared to previous related studies (e.g., Kızıltepe, 2008; Way et al. 2019). This inconsistency may be due to the unequal distribution of resources from the central government, including funding, research training, etc., in Chinese universities. The allocation of the financial budget of the government depends on the university type. The “Projects 985/211” universities usually received more funding support than those ordinary/regular universities and colleges. As McGill and Settle (2012) found, increased research funding could promote teachers’ research motivation. Funding support is a common method to stimulate teachers to be research-engaged in universities (e.g., Faribi, 2019). Therefore, EFL teachers who work in “Projects 985/211” universities may show higher research motivation than others. However, the number of EFL teachers who work in “Projects 985/211” universities is quite limited, and most Chinese EFL teachers are from ordinary/regular universities. The relatively low research motivation among ordinary/regular university/college teachers could result in their lower research productivity. This might be the main reason for the fewer research records of Chinese EFL teachers.

On the other hand, without ample financial support, ordinary/regular universities might have fewer opportunities to either host or attend academic conferences. Thus, teachers have limited opportunities to stay updated with the latest development of their field, which may decrease their research motivation and research productivity. Another possible explanation for this is that research training is deficient for EFL teachers in ordinary/regular universities/colleges with inadequate financial support. Although there are many free online research training classes, they might not be sufficient or necessary for those teachers to conduct research. The needed research training might require substantial financial investment. It is also possible that the research training programmes may not be helpful for teachers’ development of research skills, and, in certain universities, there may be a lack of research training altogether. To some extent, teachers have to learn to conduct research themselves, which is challenging because it is hard to find systemic knowledge about research in their field (Yuan et al. 2016). The acquired resources might be unsystematic, and teachers may lack the patience to seek the resources they need for their studies. The complex learning process means teachers had no robust drive to engage in and with research. Therefore, teachers’ research motivation is negatively affected due to the lack of necessary research training. According to the qualitative data from ordinary/regular university/college EFL teachers, their universities/colleges seldom provided teachers with time support. Teachers in ordinary/regular universities/colleges have multiple roles: teachers, researchers and administrators. Many of them have a heavy teaching load and administrative responsibilities, which leaves little time for them to do research. With limited time, teachers’ motivation to conduct research gradually declines.

The quantitative data analysis corroborated findings that mentorship had no impact on teachers’ research motivation. It could be deduced that most universities/colleges in China might not offer adequate mentorship support for teachers’ research engagement. The follow-up qualitative findings also revealed that teachers were not allocated enough mentors in their universities, which demotivated teachers to do research when initial and continuing support was removed from mentors (Borg 2006). This corroborated Owan et al.’s (2023) study, which suggested that mentorship is a grey area in universities. The probable explanation is that the research policies about mentorship in Chinese universities were not practical. Mentorship programmes may have been unreasonably designed and implemented to support teachers’ research. Current university research policies mostly focused on assessing the research outputs, with few clear rules for allocating mentors to teachers and helping them transition smoothly to becoming researchers, and it is especially true for novice teachers. In such a situation, teachers had to rely on their own networks to seek guidance and collaboration, which gradually led to a reluctance to engage in research due to limited networks. Although some universities provided mentorship for teachers, the mentorship offered to these teachers was a general guidance rather than customised guidance when teachers encountered difficulties during their research. Such practices highly likely would negatively affect research motivation (Owan et al. 2023). It is clear that there is a need for teachers to have pertinent research mentors. Despite mentor allocation being achieved in a few universities, there was a lack of regulatory systems for the mentoring process between experienced mentors and novice teachers (Nundulall and Dorasamy 2010). The validity of mentorship was difficult to measure and test. Furthermore, teachers did not know how to connect the mentors’ experiences to their own research. The shared experiences of those mentors might not be suitable for the practices of the teacher under instruction, which would lead to a gradual decline in teachers’ research motivation due to failures in their own research experiences.

Conclusions, implications and limitations

This study was designed to investigate the influence of mentorship and working environments on EFL teachers’ research motivation in Chinese universities. The first research question is about the relationship between institutional support and Chinese university EFL teachers’ research motivation. The results reflected the positive influence of the working environment on teachers’ research motivation, especially in “Projects 985/211” universities, and mentorship has no influence on their research motivation. The second research question is about how institutional support affects teachers’ research motivation. We found that the working environment of “Projects 985/211” universities is far better than ordinary/regular universities and colleges with timely academic workshops, sufficient online databases, supportive research communities, etc. The third research question explores the influence of institutional support on motivating Chinese university EFL teachers to do research. In the current study, the working environment is more influential than mentorship in motivating teachers to do research.

Theoretically, we explored the influence of institutional support on teachers’ research motivation in the Chinese context. We investigated the mentorship and working environments in different types of higher education institutions, providing researchers and teachers with a new perspective to understand teachers’ research motivation more directly at granular levels. Methodologically, we employed a mixed-methods approach to examine the influence of mentorship and working environments on Chinese university EFL teachers’ research motivation. This approach offered a new perspective on understanding the extent to which institutional factors would affect teachers’ research motivation. It also shed light on Chinese EFL teachers’ professional development related to research.

Practically, administrators of these universities can establish research guidelines based on the current research findings. On the one hand, administrators are expected to fulfil the necessary needs of faculty members for their research. More research support, such as funding, time, and technical guidance for teachers to do research projects, could be provided (e.g., Faribi 2019). On the other hand, the performance appraisal could be adjusted to examine not only the final number of the research productivity annually but also the time that teachers spend being research-engaged. Universities could develop time-counting systems to record teachers’ research time. Teachers could also self-report their concrete time of reading the literature, analysing data, writing papers or project applications etc. through Excel, Word files, etc. Then these universities could give teachers rewards based on their research time. Thus, teachers’ research motivation could be boosted, especially those teachers who are motivated by external rewards. Additionally, administrators could formulate the achievement assessment system based on their university type and faculty members’ diversity of personality. Some teachers might be motivated by the incentives, and others probably care more about the promotion. Hence, the administrators could develop different forms of assessment for teachers of different characteristics. Besides, as the front-line teachers expect more opportunities to communicate with experienced scholars, the administrators could provide more opportunities for teachers to attend international and domestic conferences, research training programmes, and their targeted seminars. With these opportunities, teachers could accumulate more knowledge about research and may solve many research problems in their studies. In this way, their confidence in conducting research may be enhanced, which will strengthen their research motivation. Finally, as Sadeghi and Abutorabi (2017) proposed, raising teachers’ awareness of the benefits of research was the first step in motivating teachers to be research-active. This could be achieved through institutional management and constructing a rich research culture inside the education system. The supplement of substantial resources by the institutions might encourage teachers to research actively by guaranteeing their basic research needs.

From a national policy-making perspective, the distribution of research resources is unbalanced, including the allocation of the research funding. Policymakers could seek ways to balance the resource distribution among various types of universities. Even though the government may not be able to supply enough resources to every university in China, the policy of encouraging cooperation between the “Projects 985/211” and ordinary/regular universities could be proposed to help those universities with poor research atmospheres promote teachers’ research endeavours. It might be useful, especially for teachers at ordinary/regular universities, to be given opportunities and resources to learn how to do research from “Projects 985/211” teachers. Mentorship programmes between different types of universities could be established. “Projects 985/211” universities could provide research training programmes for teachers from different ordinary/regular universities. These programmes could be non-profit training, funded by the government. After training, teachers might acquire the research skills they need and build their research networks. Thus, research collaboration among different teachers from different universities could be promoted. After teachers establish stable research networks, their research productivity could be increased continuously, and teachers’ research motivation could be promoted. As teachers establish stable research networks, their research productivity could continuously increase, thereby promoting their research motivation. To enhance teachers’ motivation, future research could explore the cooperation methods and practical research training modes between “Projects 985/211” and ordinary/regular universities. Other influential environmental factors on teachers’ research motivation, such as research culture and university research policy for different disciplines, could be investigated to enhance Chinese EFL teachers’ research motivation.

We acknowledge the limitations of the study. Using the snowball sampling method, we recruited enough participants for the current study. Although this method is not a random selection method and may involve unrepresentative participants (Heckathorn 1997), the authors utilised it because it was the most economical way of collecting sufficient data during the pandemic. The generalisability of the study was compromised by its reliance on referrals within participants’ personal networks. Snowball sampling, thus employed, may result in a sample that inadequately reflected the broader population, potentially limiting the study’s applicability to other populations. Future studies could adopt random sampling to collect data for its representativeness. Also, the current study collected data for one semester without observing these teachers’ daily research activities. Therefore, the dynamic change in teachers’ research motivation cannot be obtained. To compensate for this shortcoming, in future studies researchers could adopt the observation method to collect data to clarify any dynamic changes in teachers’ research motivation.