Linking International Faculty Integration to International Academic Impact: The Moderating Role of Institutional Digitization Level in Chinese Universities

Abstract

The introduction of international faculties is a crucial strategy in enhancing the talent pool of Chinese universities, yet its impact on scientific research development remains underexplored. This study investigates how the presence of an international faculty influences the international academic impact of 128 “Double First-class” Chinese universities from 2011 to 2020. Using benchmark regression models alongside endogeneity and robustness tests, the analysis incorporates moderating effects and heterogeneity to examine underlying mechanisms. The results indicate that the introduction of foreign faculty significantly enhances the international academic impact of these institutions. Furthermore, the scientific and technological human capital of a foreign faculty plays a key role in this effect. This study also finds that the universities’ level of digitalization significantly moderates the relationship between international faculty presence and academic impact. Additionally, the impact varies across regions and development levels, highlighting heterogeneity in outcomes. These findings suggest that Chinese universities should strategically strengthen the recruitment of international faculties, carefully assess their expertise, and leverage digital capabilities to maximize academic benefits. This research provides empirical evidence on the value of international faculties in advancing the global academic standing of Chinese higher education institutions.

1. Introduction

Knowledge-based talents are an important support for the high-quality development of a country’s economy and the steady improvement of its comprehensive national strength. They are also an important driving force for China to develop itself through science, education, and innovation. With the acceleration of globalization, the international flow of talent has become increasingly frequent, and the competition for high-level talent has become the focus of attention of all countries in the world. In the field of higher education, China has emphasized the importance of introducing talent overseas in the national strategic policy of the construction of world-class universities and first-class disciplines (“Double First-class” construction), which provide corresponding policy support for the introduction of talent overseas in Chinese universities. As a crucial part of the introduction of overseas talent in Chinese universities, international faculties have promoted the internationalization of teaching staff and teaching and scientific research in Chinese universities (Rhoads et al., 2014). By 2020, the number of foreign faculty members employed by Chinese universities had reached 17,693, nearly doubling compared to a decade earlier. This significant increase thus underscores the necessity for Chinese higher education institutions to critically assess the tangible impacts of international talent recruitment on their development. In the context of the globalization of higher education, many countries actively recruit high-level overseas talent to promote the internationalization of their universities and enhance academic innovation capacity (Lepori et al., 2015). While the introduction of foreign faculties has positively contributed to advancing internationalization indicators at universities, the precise extent of their contribution to the enhancement of global academic impact, as well as the underlying mechanisms, remain uncertain and may vary depending on national or regional contexts (De Wit, 2019). Therefore, it is essential to conduct focused research on the impact and mechanisms through which foreign faculty recruitment affects the international academic impact of universities within specific countries.

Reviewing the relevant literature, it has been widely confirmed that there is a promotion effect in the introduction of overseas talent on the development of university scientific research level and international impact. Lu and Zhang (2015) found through comparative research that compared with local scholars in Chinese universities, returnees have better performance in academic innovation. Xian (2015) found that scholars with degrees from foreign universities in Chinese universities had more advantages than local scholars in international research cooperation and research productivity. Cao et al. (2020) argued that returnable talent from higher education with overseas education have higher research productivity and international academic impact than local talent, and they are more inclined to produce results through international research cooperation. Based on China’s domestic research, Sun and Zhang (2021), taking China’s “Project 211” universities as an example, found that the introduction of overseas talent significantly improved the quantity and quality of scientific research output of the sample universities. As an important part of overseas talent introduction, there may be a potential connection between the introduction of international faculties and the international academic impact of Chinese universities.

The digital level of universities plays a key role in promoting international faculties to participate in teaching and research activities under the trend of global informatization development. Non-local international faculties, such as part-time distinguished professors, remote cooperative researchers and mobile teachers in Sino-foreign cooperative institutions, can achieve knowledge transfer and scientific research collaboration without long-term residence in China (Xu et al., 2022; Suguku, 2023). In addition, for international faculties working in local areas, the improvement of digital level in universities can help them more effectively obtain scientific research resources and participate in global scientific research exchanges, thus improving the efficiency and quality of scientific research (J. Wang et al., 2019). Studies have shown that the advancement of digitization level can have a multi-dimensional gain effect on the scientific research work of international faculties in Chinese universities. First, international faculties can use digital networks to bring their original academic connections into China. For example, international faculties can use social networks as “academic brokers” to promote the construction of international joint laboratories (Jacob & Meek, 2013; Gorska et al., 2020). Second, international faculties can transfer informatization of academic resources, expand the research breadth of their own and domestic cooperative researchers in the process of information exchange, and improve the richness and quality of the university’s international scientific research content (Li et al., 2023). Third, international faculties can spread internationally accepted academic standards and promote the internationalization of scientific research management system in Chinese universities (Avolio & Benzaquen, 2024).

To sum up, the breadth of research on foreign faculty is expanding, but there is still less attention paid to the practical impact of the introduction of foreign faculty on the international academic impact of universities. The boundary of the synergistic effect of the progress of information technology level and the dynamic adaptation mechanism in the efficiency transformation of talent introduction in colleges and universities also needs to be further systematically verified by multi-dimensional indicators. To address these gaps, this study takes China as a case example to examine the impact of foreign faculty introduction on the international academic impact of its universities. Specifically, the research focuses on the micro-level of individual institutions by selecting a sample of 128 universities included in China’s “Double First-Class” initiative from 2011 to 2020, excluding those specializing in national defense, arts, and physical education. These selected universities are geographically distributed across various regions of China and share relatively comparable overall development levels. Furthermore, they are subject to more direct higher-level policy guidance, which makes trends in their internationalization efforts more discernible. Together, these characteristics render the sample highly representative. Building on this foundation, the study explores the macro-level effects of both the quantity and quality of foreign faculty introduction on the international academic impact of Chinese universities. It further investigates the moderating role of universities’ digitalization levels in this relationship. Additionally, the analysis considers heterogeneity in these effects based on regional location and institutional development tiers. The findings aim to inform strategies for enhancing China’s universities’ international academic standing and strengthening their integration into the global research network. Moreover, it aims to provide insights into the development of universities globally, the refinement of overseas talent recruitment strategies, and the facilitation of this advancement through digital development.

2. Conceptual Definition

In terms of the definition of international faculties in universities, some scholars believe that international faculties should be teachers who were born abroad and obtained bachelor’s degree in the country of origin (Mamiseishvili & Rosser, 2010; Kim et al., 2011). Based on the research of Chinese scholars, Shi and Yang (2014) defined international faculties as teaching or research staff employed in Chinese universities with foreign nationality. Combined with the definition of international faculty in the Measures for the Appointment and Management of International faculty (Draft for Comments) issued by the Ministry of Education of China, this study adopts the latter definition. International faculties in universities and colleges are full-time or part-time teaching and research staff with foreign nationality and employed in Chinese universities.

In terms of the definition of international academic impact, the deepening trend of scientific research globalization has expanded the scope of academic activities and achievements of universities and promoted the formation and development of a global scientific research network, in which individual universities are both “influencers” and “influenced” (Adams, 2012). To catch up with and consolidate the international frontier academic position, universities around the world have engaged in global scientific research cooperation and competition, and in this process, the concept of international academic impact of universities has been derived (Altbach & Knight, 2007). This study holds that the international academic impact of universities is the effective influence of knowledge construction, technology innovation, academic exchange and researcher mobility of universities in the world on international academic development based on the global research network under the background of scientific research globalization.

In the evaluation of universities’ international academic impact, Hazelkorn (2015) believed that the quantity of scientific research output, the efficiency of scientific research resources and the quality of scientific research results are the basic basis for constructing the evaluation framework of universities’ international academic impact. With the development of internationalization of higher education, some scholars have incorporated other indicators, such as the number of overseas students, participation in and holding of international conferences, and world ranking of universities into the evaluation system of universities’ international academic impact (Altbach, 2004b; De Wit, 2011; Hazelkorn, 2014). Under the guidance of “Double First-class” construction, creating international cutting-edge scientific research achievements is an important way to promote the high-quality development of Chinese universities. To reflect the distance between the scientific research achievements of Chinese universities and the “world first-class” level, this study focuses on the quality of international scientific research achievements of universities and analyzes the international academic impact of universities based on the theory and method of bibliometrics. At the same time, in order to overcome the inherent defects of the traditional measurement methods of academic impact (such as citation frequency, impact factor, etc.) in the measurement validity and comparability of results (Holden et al., 2005; Adams et al., 2007), this study selects the discipline standardized academic impact (CNCI) proposed by InCites platform as the specific index to evaluate the international academic impact of universities. The index can control the intervention of factors such as publication year, research field and document type on the evaluation of academic impact. Allowing comparison between research entities of different sizes and types, the calculation formula is as follows:1

$$impact=CNCI={\displaystyle \frac{\sum \frac{c}{ef\left(n\right)td}}{n}}$$

(1)

In Equation (1), c is the citation frequency of a single international journal paper, e is the expected citation rate of the paper, n is the number of disciplines involved in the paper, t is the year of publication of the paper, and d is the type of the paper. CNCI value higher than 1 indicates that the academic impact of the paper is higher than the world average, and a value lower than 1 indicates that the academic impact of the paper is lower than the world average. For an individual university with a collection of papers, its academic impact can be calculated as follows:

$${{impact}_i=CNCI}_i={\displaystyle \frac{{\sum }_{i}CNCI}{p_i}}$$

(2)

In Equation (2), i is the individual university, p is the total number of papers published by the university in that year. The international academic impact of universities therefore is the average CNCI of the total number of international journals published by colleges and universities in that year.

3. Mechanism of Action

In modern society, the external effect of economic growth brought by knowledge-based human capital has become the focus of attention of countries around the world in the process of seeking their own industrial transformation and sustainable economic development (Schultz, 1993). Bozeman et al. (2001) found that, as knowledge-based human capital, the human capital contained in research and development personnel is in addition to individual scientific research endowment; it also includes scientific and technical human capital, such as hidden knowledge, working skills and research social networks. Different from traditional human capital, scientific and technological human capital can continuously improve the scientific research productivity of the holder’s institution, and this improvement effect will increase with the evolution of the career of researchers (Dietz & Bozeman, 2005). In the field of colleges and universities, the utility of scientific and technological human capital is mainly reflected in the output of scientific research achievements, such as the publication of papers, patents and inventions, etc., and the level of scientific and technological human capital of researchers has an important impact on the quantity and quality of scientific research output in colleges and universities (M. W. Lin & Bozeman, 2006). Influenced by the global scientific research network, more and more researchers tend to further accumulate and deploy their scientific and technological human capital through cross-border cooperation and international flow. This process also promotes the improvement of the scientific research level of the introduced institutions and the progress of the introduced regional technology level (Ackers, 2005; Bozeman & Corley, 2004; Toole & Czarnitzki, 2009). Therefore, the introduction of overseas high-level scientific research talent has become an important strategy for universities to increase the stock of scientific and technological human capital, optimize the level of scientific and technological human capital, and consolidate and enhance their international academic impact.

Based on the theory of scientific and technological human capital, the introduction of international faculties can first influence the international academic impact of universities by increasing the stock of scientific and technological human capital in universities. On the one hand, international faculties can bring corresponding scientific research resources to universities in the process of knowledge transfer, which includes not only the human resources provided by international faculties in scientific research and teaching, but also the material resources transferred by international faculties themselves or their teams with the flow of personnel. Through the complementary advantages and cooperation between international faculties and imported universities, it can effectively transform the scientific research resources of universities into corresponding scientific research results, thus promoting the international academic impact of universities (Edler et al., 2011). On the other hand, the introduction of international faculties provides social capital support for universities in international scientific research exchanges and cooperation. Using formal and informal social resources such as information, authority and relationship owned by international faculties in their scientific research networks can reduce the information asymmetry faced by universities in international scientific research activities and improve the efficiency of international scientific research exchanges and cooperation. It can improve the level of scientific research and international impact (Lee et al., 2005).

Secondly, the introduction of international faculties can also have an impact on the international academic impact of universities by improving the level of scientific and technological human capital. The knowledge and technology spillover effect caused by the introduction of high-level international faculties can improve the original level of scientific and technological human capital in colleges and universities, promote knowledge innovation and technological change in colleges and universities, and thus promote the level of scientific research and international academic impact in colleges and universities (Freeman, 2010). In addition, teachers and researchers in local universities can learn and acquire international cutting-edge scientific research experience and technology through exchanges and cooperation with high-level international faculties, to improve their own scientific and technological human capital level and promote the overall scientific research level of universities (Jonkers & Cruz-Castro, 2013).

Finally, by optimizing the network efficiency of scientific and technological human capital, the improvement of the digital level of colleges and universities can enhance the academic cooperation network with international faculties as the medium, thus promoting the improvement of the international academic impact of colleges and universities. In this mechanism, the core value of scientific and technological human capital is not only reflected in the knowledge and skills of individuals but also contained in the cross-border and inter-institutional relationship network of their social capital (Djikhy & Moustaghfir, 2019). As the “bridge” of academic cooperation, international faculties’ network connection ability depends on the digital support of the universities they work for. First, digital infrastructure can strengthen the connectivity of the relationship network. For example, high-speed network facilities in universities can reduce the time and space barriers of transnational academic cooperation, enable international faculties to efficiently access international academic resources, and activate the mobility of their original relationship networks (such as overseas partners and academic communities) (Chasokela et al., 2025); Secondly, the digital sharing of scientific research resources can expand the network resource pool. Through online database procurement, digital literature sharing and data opening platforms, universities provide international faculties with the same scientific research conditions as their home country institutions, enabling them to introduce international partners into the digital resource network of universities, forming a positive cycle of “resource-cooperation-influence” (Marin et al., 2020). Thirdly, digital management tools improve the efficiency of network collaboration. The scientific research project management system and digital collaboration tools provided by universities have standardized the process of transnational scientific research cooperation, enabling international faculties to coordinate cross-regional teams more efficiently and transform loose international ties into stable institutionalized cooperation (Wolff et al., 2021). Therefore, the digital development of universities can promote the level of scientific and technological human capital of universities by empowering the network attribute of scientific and technological human capital of international faculties and finally realize the leap of international impact of scientific research.

To sum up, this study believes that the mechanism of the introduction of international faculties on the development of international academic impact of colleges and universities is mainly reflected in the promotion of scientific research level of colleges and universities by increasing the stock of scientific and technological human capital and improving the level of scientific and technological human capital of colleges and universities. Moreover, under the effect of the improvement of the digital level of colleges and universities, the academic cooperation network of colleges and universities with international faculties as the medium can be enhanced. The final effect is reflected in the development of universities’ international academic impact, and its process is shown in Figure 1. Combined with the mechanism of the introduction of international faculties, this study puts forward the following hypotheses:

Hypothesis 1:

The introduction of international faculties can promote the international academic impact of Chinese universities.

Hypothesis 2:

The impact of the introduction of international faculties on the international academic impact of Chinese universities is related to the level of scientific and technological human capital of the introduction of international faculties.

Hypothesis 3:

The impact of the introduction of international faculties on the international academic impact of Chinese universities is related to the digital level of Chinese universities.

In addition, due to the geographical location, economic development level and higher education development level, the effect of international faculties’ introduction on the international academic impact of Chinese universities may have regional and individual development level heterogeneity. For example, Dai and Liu (2009) analyzed the impact of Chinese “returnees” talent on regional technological progress and found that there were significant regional differences in the contribution rate of technological progress of talent introduction, which showed a decreasing order in the eastern, central and western regions. At the same time, based on the rounds of the construction of “Double First-class”, this study will further analyze the hierarchical heterogeneity of individual development level of colleges and universities in terms of the impact of international faculties’ introduction on the international academic impact of Chinese universities. In this regard, this study puts forward the following hypotheses:

Hypothesis 4:

There is regional heterogeneity in the impact of foreign faculty introduction on the international academic impact of Chinese universities.

Hypothesis 5:

There is hierarchical heterogeneity in the impact of foreign faculty introduction on the international academic impact of Chinese universities.

4. Empirical Approach

4.1. Model Setting

To analyze the impact of the introduction of international faculties on the international academic impact of Chinese universities, this study sets the following benchmark regression model:

$${impact}_{i,t}={\beta }_0+{\beta }_1{lnforeignfaculty}_{c,t}+\delta \sum {Controls}_{i,t}+{\gamma }_i+{\gamma }_t+{\mu }_{i,t}$$

(3)

In Equation (3), ${Impact}_{i,t}$ is the international academic impact of individual universities in the year, ${lnforeignfaculty}_{c,t}$ is the logarithm of the total number of international faculties in Chinese universities in the year, $\sum {Controls}_{i,t}$ is the control variable group, ${\gamma }_i$ and ${\gamma }_t$ is the individual fixed effect and year fixed effect, respectively, and ${\mu }_{i,t}$ is the random disturbance term. According to the types of core explanatory variables and explained variables, this study focuses on the impact of international faculties’ introduction at the macro national level on the international academic impact of individual universities at the micro level.

4.2. Data Source and Variable Description

The variable data used in this study come from 2011–2020 China Education Statistical Yearbook, China University Research Achievement Evaluation and Analysis Database Platform (CDAP) and InCites platform. The specific variable types, names and data sources are shown in

Table 1. Variable description and data sources.

Variable Categories	Variable Names and Symbols	Variable Explanation	Data Sources
Explained variable	International academic impact of universities (impact)	The academic impact of a university’s discipline in that year	InCites platform
Core explanatory variables	Total number of international faculties in Chinese universities (foreignfaculty)	Number of international faculties employed by Chinese Universities in that Year (person)	China Education Statistics Yearbook
Control variables	Double first-class batch (firDFuni)	Whether the university is the first batch of Double First-class universities (yes = 1, no = 0)	—
	Number of research fund projects in universities (funds)	Number of national and provincial projects of the university in that year (items)	CDAP platform
	Number of articles published in domestic core journals of universities (corepapers)	Number of core papers of Peking University published by universities in the same year (articles)
	Number of papers published in international conferences of universities (confpapers)	Number of international conference papers published by the university in that year (papers)
	Number of international journals published by universities (WOSpapers)	Number of articles published by universities in the Web of Science Database (articles)	InCites platform
	International research cooperation rate among universities (IRCrate)	International co-authorship rate of universities in the Web of Science database for the year (%)

.

Among them, the core explanatory variable, the total number of foreign faculty members (foreignfaculty), is sourced from the China Education Statistical Yearbook, which reports the number of foreign faculty employed by Chinese universities in the given year. This figure includes full-time foreign faculty members who have signed formal employment contracts with Chinese universities, as well as part-time long-term and part-time short-term foreign faculty members. The data of universities’ international academic impact (impact) of explained variables come from the InCites platform, and the collection strategy and process are as follows: (1) the limited institutions are 128 sample universities; (2) the limited time interval is 2011–2020; (3) the limited literature types were research Articles and Review. (4) The limited type of impact is discipline standardized academic impact (CNCI). A total of 1280 observations are obtained after retrieval and collation.

In this study, control variables are set from two aspects: the level of scientific research development and the level of scientific research internationalization in colleges and universities: In terms of the level of university scientific research development, the Double First-class batch (firDFuni) is used to distinguish whether an individual university belongs to the first batch of “Double First-class” construction universities, and it is set as a dummy variable (the first batch of “Double First-class” construction universities = 1, non-first batch of “Double First-class” construction universities = 0). The number of university scientific research fund projects (funds) reflects the strength of university scientific research support, specifically the number of national and provincial foundation projects of natural science, humanities and social sciences in the same year; The number of papers published in domestic core journals (corepapers) is used to reflect the comprehensive scientific research level of colleges and universities, which is specifically the number of papers published in core journals (Chinese Core Journals Overview). In terms of the level of internationalization of university scientific research, the number of papers published in international conferences of colleges and universities (confpapers) is the number of papers collected in the data source of international conferences on the CDAP platform in the same year. The number of papers published in international journals of universities (WOSpapers) is the number of papers published in the Web of Science database of universities in that year. The international research cooperation rate of universities (IRCrate) is the international co-authorship rate of theses in the Web of Science database of universities in the same year.

After data sorting, the descriptive statistics of each variable are shown in

Table 2. Descriptive statistics of variables.

Variables	Observations	Average	Standard Deviation	Minimum	Maximum	VIF
impact	1280	1.088	0.236	0.295	3.002	-
lnforeignfaculty	1280	9.693	0.117	9.487	9.826	1.49
lnfunds	1280	4.990	0.831	1.098	7.190	3.83
lncorepapers	1280	7.142	0.807	0	8.717	2.22
lnconfpapers	1280	4.235	1.143	0	6.773	1.79
lnWOSpapers	1280	7.078	1.242	1.386	10.128	3.36
IRCrate	1280	0.257	0.078	0.070	0.750	1.08

. The average value of the explained variable (impact) is 1.088, the standard deviation is 0.236, the minimum value is 0.295, and the maximum value is 3.002, indicating that the international academic impact of the sample universities can be slightly higher than the international average level in general, but the range between the observed data is large. This indicates that there are some differences in the development of international academic impact within the sample universities. Furthermore, after transforming certain independent variables into their logarithmic forms, the Variance Inflation Factor (VIF) test was conducted. The results show that all VIF values are below 4, indicating no significant multicollinearity issues among the independent variables.

5. Results

5.1. Benchmark Regression

The benchmark regression analysis results of this study are shown in

Table 3. Regression results of the benchmark.

Variables	Impact
	(1)	(2)	(3)	(4)
lnforeignfaculty	0.925 ***	1.250 ***	1.061 ***	0.772 ***
	(0.052)	(0.067)	(0.086)	(0.226)
firDFuni			0.476 ***	0.323
			(0.136)	(0.198)
lnfunds			0.081 **	0.027
			(0.034)	(0.023)
lncorepapaers			−0.045	−0.087
			(0.067)	(0.066)
lnconfpapers				0.005
				(0.008)
lnWOSpapers				0.054
				(0.044)
IRCrate				0.659 ***
				(0.148)
Constant term	7.874 ***	10.626 ***	9.425 ***	6.526 ***
	(0.503)	(0.642)	(1.034)	(1.931)
Observations	1280	1280	1280	1278
adj. R2	0.210	0.727	0.731	0.757
Individual fixed effects	NO	YES	YES	YES
Time fixed effects	NO	YES	YES	YES

Note: *** p < 0.01, ** p < 0.05, and figures in parentheses are robust standard errors.

. Individual and time fixed effects, control variables of university scientific research development level and control variables of university scientific research internationalization level are added in turn from column (1) to column (4) of the model. The regression coefficients of the logarithm of the total number of international faculties in Chinese universities (lnforeignfaculty) on the international academic impact of Chinese universities are all significantly positive, which indicates that the introduction of international faculties in Chinese universities has a positive effect on the promotion of international academic impact of Chinese universities, which initially supports Hypothesis 1 proposed in this study.

5.2. Endogeneity Test

The results of the benchmark regression analysis in this study may have endogenous problems, which are mainly caused by two aspects: first, the reverse causality problem. As the “Double First-class” construction universities with high comprehensive development level of scientific research in China, the improvement of the international academic impact of the sample universities may form a “pulling force” for the introduction of international faculties, thus promoting an increase in the number of international faculties in China. The second is the problem of missing variables. Although some control variables have been included in the benchmark regression, the accuracy and validity of the benchmark regression analysis results still need to be further improved due to the influence of other variables that are difficult to observe and obtain. Based on this, the endogeneity test was conducted on the benchmark regression results, and the test results are shown in

Table 4. Endogeneity test results.

Variables	Impact
	Panel Two-Way Fixed Effects	TWFE + 2SLS	First-Stage
	(1)	(2)	(3)
lnforeignfaculty	0.772 ***	0.317 ***
	(0.282)	(0.086)
firDFuni	0.323 *
	(0.167)
lnfunds	0.027	0.002	0.002
	(0.031)	(0.022)	(0.003)
lncorepapaers	−0.087 ***	−0.049	−0.014 ***
	(0.023)	(0.044)	(0.004)
lnconfpapers	0.005	−0.008	0.019 ***
	(0.011)	(0.006)	(0.001)
lnWOSpapers	0.054	0.176 ***	0.007 **
	(0.053)	(0.020)	(0.003)
IRCrate	0.659 ***	0.432 ***	−0.003
	(0.156)	(0.160)	(0.019)
Constant term	6.526 ***
	(2.462)
Value of observation	1278	1023	1023
Within R2/Centered R2	0.546	0.563
Individual fixed effects	YES	YES	YES
Time fixed effects	YES	YES	YES
Kleibergen-Paap rk LM		356.689
		[0.000]
Kleibergen-Paap rk Wald F		1617.717
Hansen J statistic		4.568
		[0.102]
lnstucome_ndL0			0.364 ***
			(0.018)
lnstucome_ndL1			−0.776 ***
			(0.023)
lnstucome_ndL2			0.946 ***
			(0.020)

Note: *** p < 0.01, ** p < 0.05, * p < 0.1, and figures in parentheses are robust standard errors. This notation is consistent throughout all subsequent tables in the study; the critical values of Stock–Yogo weak ID test were 13.91 (5% level), 9.08 (10% level) and 6.46 (20% level); the values within square brackets under the Kleibergen–Paap rk LM and Hansen J statistic are their p-values.

.

First, this study uses the panel two-way fixed effect model to control each variable in Column (1), and the results show that the regression coefficient of the core explanatory variable (lnforeignfaculty) on the explained variable (impact) remains significantly positive, with a 95% confidence interval of [0.3292, 0.4004], and the coefficient value is consistent with the benchmark regression results in Column (4) of Table 3. However, the panel two-way fixed effects model cannot overcome the endogeneity problem of variables, and the results may still be biased and inconsistent. Therefore, this study further introduces instrumental variable (IV) to test the endogeneity problem.

In selecting the IVs, this study employs the number of non-degree international students in China (lnstucome_ndL0) along with its one- and two-period lagged variables (lnstucome_ndL1, lnstucome_ndL2) as IVs for the total number of foreign faculty members in Chinese universities (lnforeignfaculty) in the period. The selection approach draws on the findings of Yin and Zong (2022), who demonstrated that the positive effect of international students on the international academic development of Chinese universities diminishes as the students’ academic level decreases. Specifically, when the academic level corresponds to an associate degree or non-degree education, this effect becomes statistically insignificant. Based on this insight, non-degree international students in China were chosen as IVs for foreign faculty. These students primarily engage in language, culture, and other non-degree courses without pursuing formal degrees. While they share characteristics of international mobility and thus relate to foreign faculty presence, their non-academic learning objectives and curriculum render their influence on the international academic standards of Chinese universities slight. This rationale satisfies the IV requirements of relevance and exogeneity.

Following this framework, the study further assesses the validity of the selected IVs through quantitative tests for under-identification, weak identification, and over-identification. The results are reported in column (2). For under-identification and weak identification, the Kleibergen-Paap rk LM statistic yields p-values below 0.01, and the Kleibergen-Paap rk Wald F statistic substantially exceeds the Stock-Yogo weak ID critical thresholds, indicating that the IVs are sufficiently correlated with the endogenous regressors. Regarding over-identification, given that the number of IVs exceeds the number of key endogenous variables and the model includes certain dummy variables, the Hansen J test was employed. The p-value of the Hansen J statistic exceeds 0.1, supporting the null hypothesis that the IVs are jointly exogenous. In summary, this study combines the panel fixed effect model and the instrumental variable method to test the endogeneity of the benchmark regression analysis results. The results show that the coefficient of core explanatory variable decreases from 0.772 to 0.317, with a 95% confidence interval of [0.1495, 0.4847], yet it remains significantly positive. This finding further confirms that the introduction of foreign faculty in Chinese universities has a positive effect on enhancing their international academic impact.

5.3. Robustness Test

Based on the results of the endogeneity test, to further improve the reliability of the benchmark regression analysis results, this study conducts a robustness test on the obtained results from four aspects: replacing the explained variables, winnow processing, increasing the control effect of provinces and shortening the sample time window (see

Table 5. Results of the robustness test.

Variables	lncite	Impact_tr	Impact
	Replace the Explained Variable	Winsorization	Controlling for Province Effects	Shorten the Time Window
	(1)	(2)	(3)	(4)
lnforeignfaculty	8.756 ***	0.654 ***	0.772 ***	1.411 ***
	(0.238)	(0.139)	(0.226)	(0.488)
Control variables	YES	YES	YES	YES
Constant term	83.337 ***	5.794 ***	6.177 ***	12.831 ***
	(2.042)	(1.309)	(1.847)	(4.499)
Observations	1278	1278	1278	511
adj. R2	0.995	0.791	0.757	0.711
Individual fixed effects	YES	YES	YES	YES
Time fixed effect	YES	YES	YES	YES
Province fixed effects	NO	NO	YES	NO

Note: *** p < 0.01.

).

5.3.1. Replace the Explained Variable

Based on the calculation formula of the international academic impact of universities, this study selects the logarithm of the cumulative citation frequency2 (lncite) of universities in the current year as the proxy variable of the explained variable (impact) to examine the impact of the introduction of international faculties on the international academic impact of universities without calculation constraints. The results are shown in Column (1). It can be found that the coefficient of the variable of the number of international faculties is significantly positive, and the introduction of international faculties has a positive effect on the cumulative citation frequency of colleges and universities in that year.

5.3.2. Winsorization

In the descriptive statistics, the range of the international academic impact of the sample universities is relatively large. To avoid the interference of extreme values on the benchmark regression analysis results, the explained variable (impact) is winsowled by 1% and the regression analysis is carried out again. The results are shown in Column (2). The results are shown in Column (2). The core explanatory variables still play a significantly positive role in promoting the international academic impact of universities (impact_tr) after the winnowed.

5.3.3. The Effect of Province Is Controlled

In the benchmark regression analysis, this study only controls the individual effect of colleges and universities and the year effect. To control the influence of region effect on the benchmark regression analysis results, this study further adds the provincial fixed effect into the benchmark model, and the regression results are shown in Column (3). The coefficient of the core explanatory variable is still significantly positive, and the results are basically consistent with the benchmark regression analysis results.

5.3.4. Shorten the Time Window

During the observation period of the benchmark regression analysis, the proposal of the Belt and Road policy may have an impact on the development trend of the international academic impact of Chinese universities. To exclude the potential intervention of policy shocks on the analysis results, this study selects the data from the time window before the formal establishment of the Belt and Road Initiative (2011–2014) as a sub-sample for robustness test. The results are shown in Column (4). It can be found that the coefficient of the variable of the number of international faculties is significantly positive, which supports the results of the benchmark regression analysis.

Through the above four robustness tests, the results of the benchmark regression analysis have been further consolidated, and the hypothesis that the introduction of international faculties has a promoting effect on the international academic impact of universities has been effectively supported.

5.4. Analysis of Moderating Effect

5.4.1. Moderating Effect Analysis Based on the Educational Level of International Faculties

To investigate the impact of the introduction of international faculties with different levels of scientific and technological human capital on the international academic impact of universities, this study takes the educational background of teachers as the stratification basis of scientific and technological human capital level. The proportion of international faculties with a doctor’s degree (docrate), the proportion of international faculties with a master’s degree (masrate) and the proportion of international faculties with a bachelor’s degree or below (bacrate) in the total number of international faculties introduced in China in that year are selected as moderator variables, and their interaction terms with the core explanatory variables are formed.3 Subsequently, the panel fixed effect model is used to analyze the moderating effect of the level of scientific and technological human capital of international faculties on the introduction of international faculties, and the results are shown in

Table 6. Analysis of the moderating effect of international faculties’ educational level.

Variables	Impact
	Proportion with Doctoral Degrees	Proportion with Master’s Degree	Proportion with Bachelor’s Degree or Below
	(1)	(2)	(3)
lnforeignfaculty	−0.731 ***	1.660 *	0.369
	(0.246)	(0.895)	(0.225)
docrate	−14.388 **
	(5.742)
lnforeignfaculty × docrate	1.455 **
	(0.567)
masrate		62.823 **
		(31.555)
lnforeignfaculty×masrate		−6.525 **
		(3.246)
bacrate			14.307 **
			(5.674)
lnforeignfaculty × bacrate			−1.408 **
			(0.575)
Control variables	YES	YES	YES
Constant term	−66.530 *	−65.588 **	−86.524 **
	(39.205)	(25.761)	(33.144)
Observations	1278	1278	1278
Within R2	0.544	0.544	0.544
Individual fixed effects	YES	YES	YES
Time trend term	YES	YES	YES

Note: *** p < 0.01, ** p < 0.05, * p < 0.1.

.

By examining the coefficients of the interaction terms between the proportion of teachers with different degrees and the core explanatory variables in columns (1) to (3), it can be seen that the interaction terms of the proportion of international faculties with a doctorate degree are significantly positive, indicating that the increase in the proportion of international faculties with a doctorate degree will promote the effect of the introduction of international faculties on the international academic impact of universities. In addition, there may be some substitution between the main effect and the moderating effect, that is, with the increasing proportion of high-level international faculties, the international academic impact of universities will be more affected by the “quality” of international faculties. The interaction term of the proportion of international faculties with master’s degree is significantly negative, indicating that the increase in the proportion of international faculties with master’s degree inhibits the effect of the introduction of international faculties on the international academic impact of universities. Finally, the cross-multiplication term of the proportion of international faculties with bachelor’s degree or below is significantly negative, indicating that the increase in the proportion of international faculties with bachelor’s degree or below will also inhibit the impact of international faculties on the international academic impact of universities. In conclusion, the introduction of international faculties at different levels has different moderating effects on the main effect. The introduction of international faculties with a doctor’s degree has a promoting effect on the promotion of the international academic impact of universities, while the introduction of international faculties with a master’s degree or below has a negative moderating effect, which confirms Hypothesis 2 proposed in this study.

5.4.2. Moderating Effect Analysis Based on the Digitalization Level of Universities

To examine the extent to which the level of university digitalization moderates the effect of foreign faculty recruitment on the international academic impact of universities, this study establishes moderating variables based on the theoretical analysis of the underlying mechanisms. They include university digital literature sharing platform (DLSP), research project professional software (RPPS), research data sharing platform (RDSP), research project assistance and exchange platform (RAEP), high performance computing center (HPCC) and large-scale instrument online access and reservation system (IORS).4 These variables are measured as the percentage of institutions participating in the construction or application of specific digital technology relative to the total number of universities.

Specifically, DLSP refers to an integrated, collaboratively built system for academic literature resources that provide services such as retrieval, delivery, and knowledge discovery. RPPS comprises standardized or customized software tools that support the entire research process, covering functionalities such as literature management, data analysis, and disciplinary simulation. RDSP serves as an infrastructure for the collection, storage, and open sharing of scientific data, facilitating interdisciplinary data reuse and collaboration. RAEP is a collaborative system designed to promote interdisciplinary team matching and resource integration. HPCC functions as a centralized hub offering large-scale parallel computing resources. Finally, IORS is an open-access platform for large-scale research instruments, enabling fully digitalized processes for booking, billing, and usage management.

As shown in

Table 7. Analysis of moderating effect of digitization level in universities.

Variables	Impact
	Proportion of DLSP	Proportion of RPPS	Proportion of RDSP	Proportion of RAEP	Proportion of HPCC	Proportion of IORS
	(1)	(2)	(3)	(4)	(5)	(6)
lnforeignfaculty	0.445	−1.109 ***	0.063	−0.597 **	−0.819 ***	−0.869 **
	(0.597)	(0.382)	(0.315)	(0.278)	(0.278)	(0.375)
DLSP	−1.424
	(1.149)
lnforeignfaculty × DLSP	−0.004
	(1.606)
RPPS		−18.766 **
		(7.382)
lnforeignfaculty × RPPS		1.947 **
		(0.761)
RDSP			−16.842
			(11.378)
lnforeignfaculty × RDSP			1.737
			(1.167)
RAEP				−16.310
				(11.982)
lnforeignfaculty × RAEP				1.710
				(1.240)
HPCC					−5.942
					(15.701)
lnforeignfaculty × HPCC					0.643
					(1.633)
IORS						7.789
						(14.256)
lnforeignfaculty × IORS						−0.757
						(1.471)
Control variables	YES	YES	YES	YES	YES	YES
Constant term	−74.915 ***	−53.819 ***	−70.123 ***	−46.614 **	−48.760 ***	−55.846 ***
	(20.956)	(18.378)	(19.374)	(17.997)	(17.184)	(18.863)
Value of observation	1278	1278	1278	1278	1278	1278
Within R2	0.542	0.544	0.542	0.543	0.542	0.545
Individual fixed effects	YES	YES	YES	YES	YES	YES
Time trend term	YES	YES	YES	YES	YES	YES

Note: *** p < 0.01, ** p < 0.05.

, except for the interaction term of research project professional software (RPPS), which is positively significant, the other five interaction variables are all insignificant. This indicates that only RPPS has a positive moderating effect on the impact of the introduction of foreign faculty on the international academic impact of universities, while the remaining digitalization indicators show no significant effect. Therefore, although not all digitalization variables exhibit positive moderating effects, it can be confirmed that some variables representing the level of digital application and infrastructure in universities play a positive facilitating role in this relationship. Hypothesis 3 is thus partially supported.

5.5. Heterogeneity Analysis

In this section, this study will further discuss whether the impact of the introduction of international faculties on the international academic impact of colleges and universities will be heterogeneous due to the differences in the regions where colleges and universities are located and the individual development levels of colleges and universities. The specific analysis results are shown in

Table 8. Results of heterogeneity analysis.

Variables	Impact
	East	Central	West	Northeast	First Batch	Second Batch
	(1)	(2)	(3)	(4)	(5)	(6)
lnforeignfaculty	1.008 ***	−0.318	0.827 **	0.659 *	0.016	0.835 ***
	(0.350)	(0.472)	(0.316)	(0.388)	(0.242)	(0.304)
Control variables	YES	YES	YES	YES	YES	YES
Constant term	−8.529 ***	3.793	−7.953 ***	−6.010	0.286	−7.120 ***
	(3.048)	(4.294)	(2.779)	(3.979)	(2.165)	(2.507)
Value of observation	708	190	270	110	410	868
adj. R2	0.751	0.786	0.750	0.648	0.814	0.711
Individual fixed effects	YES	YES	YES	YES	YES	YES
Time fixed effects	YES	YES	YES	YES	YES	YES

Note: *** p < 0.01, ** p < 0.05, * p < 0.1.

.

5.5.1. Heterogeneity Analysis Based on the Regional Division of Universities

To test whether there is regional heterogeneity in the impact of the introduction of international faculties on the international academic impact of universities, this study classifies the sample universities into the eastern region, the central region, the western region and the northeastern region based on the four economic regions of China for heterogeneity analysis. The analysis results are shown in Columns (1) to (4).5 It can be found that the coefficients of core explanatory variables in the sub-samples of the eastern region are significantly positive, indicating that the international academic impact of the sample colleges and universities in the eastern region is significantly affected by the promotion effect of the introduction of international faculties. The coefficients of the core explanatory variables in the sub-samples of the central region failed to pass the significance level test, indicating that the introduction of international faculties has no significant impact on the international academic impact of the universities in the central region. The coefficients of core explanatory variables in the subsamples of western and northeastern regions have a significant positive impact, indicating that the international academic impact of universities in western and northeastern regions is also positively promoted by the introduction of international faculties. In conclusion, there are regional differences in the impact of the introduction of international faculties on the international academic impact of universities in the eastern, western and northeastern regions. The introduction of international faculties has a significant positive impact on the international academic impact of universities in the eastern, western and northeastern regions, but has no obvious effect on the international academic impact of universities in the central region, which verifies Hypothesis 4. That is, there is regional heterogeneity in the impact of the introduction of international faculties on the international academic impact of universities.

5.5.2. Heterogeneity Analysis Based on the Batch of “Double First-Class” Universities

The batch in which sample universities were designated as “Double First-Class” universities serves as a critical criterion for distinguishing their comprehensive development levels. The first batch of world-class university construction institutions was announced earlier and compared to the second batch, possesses greater advantages in research resources, talent, and internationalization. Consequently, there exists an objective gap in research development levels between the two batches of “Double First-Class” universities. To investigate the impact of individual development level differences on the effect of recruiting foreign faculty, this study uses the batch designation of “Double First-Class” universities as a classification criterion and conducts regression analyses on two subsamples, with results presented in columns (5) and (6). The findings indicate that, in the subsample of the first batch of “Double First-Class” universities, the coefficient of the core explanatory variable does not pass the significance test, suggesting that the recruitment of foreign faculty has an insignificant effect on the international academic impact of these institutions. In contrast, in the subsample of the second batch of “Double First-Class” universities, the coefficient of the core explanatory variable is significantly positive, indicating that the recruitment of foreign faculty significantly enhances the international academic impact of these institutions. In summary, compared to the first batch of “Double First-Class” universities, which have relatively advanced research development levels, the international academic impact of the second batch, which lags behind in research development, is more significantly affected by the recruitment of foreign faculty. The continued increase in foreign faculty has a less pronounced effect on the international academic impact of the first batch of “Double First-Class” universities, which already exhibit higher research levels. This suggests a “diminishing marginal utility” phenomenon in the impact of foreign faculty recruitment on the international academic impact of universities, thereby supporting Hypothesis 5.

6. Discussion

6.1. Analysis and Discussion

This study uses data from 128 Chinese “Double First-class” universities (2011–2020) and information on international faculties to examine how the number and quality of international faculties affect the universities’ international academic impact. It also considers differences across regions and university development levels. The main findings are as follows:

• Introducing international faculties significantly improves the international academic impact of Chinese universities.
• The level of international faculties moderates this effect. Hiring international faculties with doctoral degrees enhances academic impact, while those with master’s degrees or lower reduce this positive effect.
• The level of digital infrastructure construction in universities exerts a significant moderating effect on the relationship between the introduction of foreign faculty and the enhancement of academic impact. Specifically, the construction and application of research project professional software (RPPS) significantly strengthens the positive impact of foreign faculty introduction on international academic impact. However, the regression coefficients of the interaction terms for the remaining five moderating variables are not significant, indicating that their moderating effects on the impact of foreign faculty introduction on universities’ international academic impact are not evident.
• The impact varies by region and development level. International faculties boost academic impact in eastern, western, and northeastern regions, but not significantly in the central region. Similarly, the effect is significant in the second batch of “Double First-class” universities but not in the first batch.

The findings of this study provide a new theoretical perspective and practical enlightenment for understanding the mechanism of the introduction of international faculties on the international academic impact of universities. Combined with the human capital theory of science and technology and social network theory, the following discussions can be further deepened:

Firstly, the dual attributes of international faculties as scientific and technological human capital. Based on the theory of scientific and technological human capital, international faculties have the dual functions of “knowledge carrier” and “network node” (Djikhy & Moustaghfir, 2019). This study found that levels of international faculties significantly promote the knowledge spillover effect of human capital, carrying frontier disciplinary knowledge, international research experience, and cross-cultural research methods. Through mechanisms such as joint supervision and academic discussions, tacit knowledge transfer occurs, enhancing the domestic scientific research teams’ capacity for technology absorption and re-innovation (Boyle et al., 2012; Przytula, 2024). However, the inhibitory effect of international faculties with master’s degrees or below reveals the risk of human capital mismatch: when the skill structure of imported talent does not align with universities’ scientific research needs, it may lead to a resource crowding-out effect, especially in scenarios involving shared research equipment and team collaboration (McGuinness et al., 2018). This finding extends traditional human capital theory by highlighting its boundary conditions in the context of higher education internationalization.

Secondly, the moderating mechanism of social network embeddedness. From the perspective of social capital theory, the academic impact of international faculties is closely related to the depth of social network embeddedness (N. Lin, 2017). The significant effectiveness of international faculties in universities located in the eastern region may be attributed to the mature international academic networks present there, which provide international faculties with the advantage of occupying “structural holes” (Burt, 2017). This position enables them to quickly access channels of global knowledge flow and become key linkers between local teams and international academia (Matthews et al., 2015). Conversely, the non-significant effect observed in the central region may result from the closure of regional academic networks: when international faculties face difficulties breaking through entrenched local collaboration habits, their bridging function weakens, reducing the efficiency of knowledge diffusion (Lu & McInerney, 2016). This suggests that the effectiveness of international faculties depends not only on individual qualities but also on the openness and inclusiveness of the organizational social network environment.

Third, the heterogeneous effects observed in digital infrastructure development highlight the crucial role of technological infrastructure in facilitating the integration and functionality of social networks within universities. Among the digital indicators analyzed for moderating effects, only the research project professional software (RPPS) demonstrated a significant impact. In Chinese universities, RPPS refers to various specialized, non-hardware digital tools designed to support the full lifecycle management of research projects, aiming to enhance researchers’ efficiency, standardize administrative processes, and effectively facilitate data analysis and decision-making. According to the China Education Informatization Development Report, unlike other indicators such as data-sharing or exchange platforms that emphasize domestically developed solutions, a considerable number of Chinese institutions prefer to procure licenses for internationally developed project management software and provide access to faculty. This strategy not only meets universities’ demand for high-quality research management tools but also secures substantial governmental financial support, providing a solid basis for the positive moderating role of RPPS (Huang & Sharif, 2015; X. Wang et al., 2018).

On one hand, these globally oriented research project management tools commonly feature multilingual support, which effectively reduces language barriers for foreign faculty and facilitates their swift integration into research teams and project workflows (Melo-Pfeifer, 2020; Specht et al., 2024). On the other hand, such software is typically designed based on internationally accepted research paradigms and standards, aligning well with the operational habits and research trajectories of foreign academics. This alignment lowers adaptation costs arising from cultural and institutional differences, demonstrating strong “tool adaptability” (Straub et al., 1997). Researchers’ cognitive adaptability to these tools can directly influence their usage effectiveness, consistent with the core constructs of the Technology Acceptance Model (TAM)—perceived ease of use and perceived usefulness (Davis, 1989).

Fourthly, the phenomenon of diminishing marginal utility in the heterogeneity of development level echoes the “threshold effect” of human capital accumulation. When the international academic network of the first batch of universities is approaching saturation, it is difficult to simply increase the number of international faculties to break through the constraints of structural holes, so it is necessary to turn to the precise introduction of top talent such as international high-impact scholars. However, the regional heterogeneity exposes the spatial imbalance of social capital. The positive effect of universities in the western region may be due to the network transition opportunity under the “latecomer advantage”, that is, the leap forward development of academic impact through international faculties’ access to non-overlapping networks. These findings provide micro evidence for optimizing the theory of regional innovation systems.

Fourthly, the phenomenon of diminishing marginal utility in the heterogeneity of development level echoes the “threshold effect” of human capital accumulation (Zeng & Zhang, 2022). When the international academic network of the first-tier universities approaches saturation, simply increasing the number of international faculties is insufficient to overcome the constraints of structural holes. Instead, precise recruitment of top talent such as internationally high-impact scholars becomes necessary (Altbach, 2004a). However, regional heterogeneity exposes spatial imbalances of social capital. The positive effect observed in universities in the western region may be explained by the network transition opportunity under the “latecomer advantage,” where academic impact leaps forward through international faculties’ access to non-overlapping networks (Hong, 2008; Ye et al., 2020). These findings provide micro-level empirical evidence for optimizing the theory of regional innovation systems.

6.2. Suggestions

To enhance the international academic impact of universities worldwide, this study proposes the following policy recommendations based on the research findings:

Firstly, universities worldwide are encouraged to strengthen the recruitment of international faculties. The introduction of international faculties significantly enhances the global academic impact of institutions. Universities could intensify efforts to attract diverse international talent by providing robust material, organizational, and cultural support systems that facilitate integration and professional development across different cultural contexts. It is recommended that a rigorous and transparent selection process be implemented, evaluating candidates’ professional expertise, research capabilities, and teaching ethics to ensure the recruitment of high-caliber talent. Additionally, universities may consider integrating international faculty management into their broader human resource frameworks, adopting regular assessments of teaching and research performance to maintain quality and accountability across diverse academic environments.

Secondly, universities can prioritize the following directions in digital development: optimizing multilingual support and user experience design of research project management platforms to improve cross-cultural adaptability and usability, thereby lowering barriers for international faculties and facilitating their research collaboration; enhancing the integration of software with internal university data resources to enable efficient circulation and intelligent analysis of research data, supporting scientific decision-making and resource allocation. Furthermore, regarding the other five digital variables in this study that did not demonstrate significant positive effects, universities can promote data sharing and collaborative work across different systems by strengthening the interoperability and standardization of digital infrastructure, thereby enhancing the synergistic effects of the overall digital ecosystem. At the same time, emphasis should be placed on digital literacy training and cultural adaptation support to help faculty and staff effectively utilize various digital resources and improve the practical application of digital technologies.

Thirdly, universities internationally are encouraged to foster global research networks. International research collaboration is critical for institutions to engage with cutting-edge global research and elevate their academic reputation. International faculties serve as vital connectors in this process, facilitating academic exchanges and fostering the growth of local researchers. To maximize these benefits, universities should establish robust domestic and international research networks, leveraging international faculties as bridges to accelerate the dissemination of advanced knowledge and technology. This strategy is especially important in contexts where regional disparities exist in the impact of international faculty recruitment, ensuring more equitable academic development.

Fourthly, universities globally are advised to optimize the allocation of international talent resources. The study identifies a “diminishing marginal utility” in the influence of international faculty recruitment on academic impact. For institutions at earlier stages of development, proactive recruitment of international faculties, informed by comprehensive analyses of the global talent market, can significantly boost their international academic standing. Conversely, for highly developed universities, it is advisable to strategically plan the scale and composition of talent recruitment to avoid redundancy of resources, focusing instead on cultivating and attracting high-impact researchers worldwide and leading scholars to achieve high-quality, sustainable growth in international impact.

6.3. Limitations

Finally, this study is primarily constrained by data availability, which limits the robustness of the quantitative analysis. First, the selection of IVs requires further refinement to better ensure their exogeneity. Second, certain control variables have been omitted, such as university governance patterns, strengths in academic disciplines, and the level of English-taught courses, which should be incorporated in future research to provide a more comprehensive analysis. Third, the categorization of foreign faculty needs further differentiation to examine potential heterogeneity in the effects of different employment types, job responsibilities, and research fields, etc., on the international academic impact of universities. These currently missing elements require targeted data collection through detailed surveys and fieldwork to be integrated into subsequent analyses, thereby yielding more precise and reliable results.