The accreditation process of the International Economics and Trade program at this university provides a quasi-natural experimental setting to examine the association between international accreditation and student internship performance. The program was granted IACBE candidacy status in December 2016, after which accreditation-driven reforms were implemented beginning in 2017, including adjustments to teaching conditions, assessment systems, and curriculum alignment with learning outcomes. During the same period, the Financial Engineering program within the same School of Economics did not undergo international accreditation and therefore serves as a natural comparison group. This exogenous policy change enables the application of a DID approach to estimate program-level associations. The underlying assumption is that, in the absence of international accreditation, internship performance trends of students in International Economics and Trade would have evolved in parallel with those of students in Financial Engineering; therefore, any significant change in performance observed after accreditation is interpreted as being associated with accreditation-driven reforms. Based on this logic, the study proposes the following hypothesis: educational reforms induced by international accreditation are associated with improvements in students’ internship performance.

Each student in the program undertakes a three-month internship in a company during their senior year. Guided by the IACBE’s seven core learning outcomes, an online questionnaire was developed and distributed to internship employers or supervisors. The internship evaluation questionnaire was designed as part of the university’s routine internship assessment system and is aligned with outcome-based education principles emphasized by international accreditation standards. The evaluation items cover multiple dimensions of students’ workplace performance, including applied skills, professional behavior, communication, and adaptability, thereby ensuring content validity. Each year, 190 internship supervisors were invited to complete the survey using a five-point Likert scale (Likert, 1932). Respondents were informed about the study’s purpose and provided implied consent through participation. The scale ranged from 1 to 5, where 5 indicated strong agreement (“Yes”), 4 general agreement (“Basically OK”), 3 neutral (“Not sure”), 2 disagreement (“Hardly”), and 1 strong disagreement (“Not at all”). To assess internal consistency, reliability analysis was conducted at the item level, and the overall scale demonstrated satisfactory internal consistency. The survey was administered annually each March from 2017 to 2023, with data collection concluding in April. This process resulted in a balanced panel dataset covering the period 2017–2023, allowing for robust Difference-in-Differences estimation of accreditation effects on student internship outcomes. The final sample consists of 2,594 internship evaluations, representing the full population of eligible students from both the International Economics and Trade and Financial Engineering programs who completed internships during the study period rather than a selected subsample. The multi-year and multi-cohort nature of the data ensures adequate variation for estimating accreditation effects using the DID approach.

Within the DID framework, international accreditation–driven reforms are treated as a program-level institutional intervention, while students’ internship performance serves as the primary outcome variable. Individual academic ability, language proficiency, prior performance, and engagement-related indicators are included as control variables to account for pre-existing differences among students. Heterogeneity analyses by internship industry and gender are conducted as structured extensions of this framework to examine whether the association between accreditation reforms and internship performance varies across contexts and student groups. It should be emphasized that internship evaluations are supervisor-assessed measures conducted within an institutionally structured framework, and therefore reflect perceived performance within a specific evaluation context rather than an independent or fully objective indicator of overall competence.

On the basis of constructing an evaluation index system, this study uses the entropy method to analyze the performance of the interns (Han et al., 2015; Wang and Dong, 2023). The specific steps are as follows:

First, according to the index attributes, the evaluation data are standardized with the help of the entropy method (Equation 1):

Forward standardization formula: X ij = ( X ij − X minij ) / ( X maxij − X minij ) (1) Where X ij represents the evaluation standard value, X minij represents the minimum value of the j-th item of the i-th student, and X maxij represents the maximum value of the j-th item of the i-th student.

Second, calculate the characteristic proportion of the j-th index (Equation 2): P ij = X ij / ∑ i = 1 n X ij (2)

Third, calculate the index of the information entropy (Equation 3):

The information entropy calculation formula of the j-th index of the i-th student can be expressed as: e j = − k ∑ i = 1 n P ij ∗ ln P ij (3)

Fourth, calculate the dispersion of the evaluation index (Equation 4): d j = 1 − e j (4)

Fifth, calculate the weight of the evaluation index (Equation 5): w j = d j / ( ∑ j = 1 n d j ) (5)

Sixth, according to the obtained comprehensive score of the index weight, the comprehensive index of performance is calculated (Equation 6): Score i = ∑ j = 1 n ( w j ∗ X ij ) (6) Where Score i represents the comprehensive index, and n is the number of indexes under all levels in the evaluation system, which is 7.

The DID method is then employed to examine the association between international accreditation and students’ internship performance by exploiting temporal and cross-program variation in reform exposure. Although accreditation-driven reforms were formally initiated in 2017, the policy dummy is set to 1 only for years after 2020. This specification reflects the structure of undergraduate training and internship arrangements, as students typically complete internships in their final year of study. Students who entered the program in 2017 constitute the first cohort fully exposed to accreditation-driven reforms throughout their entire undergraduate training cycle. Consequently, cohorts graduating before 2020 were not fully exposed to the reformed learning environment throughout their period of study.¹

Accordingly, the specific model setting is as follows (Equation 7): Score it = α + β did it + γ X it + μ i + f t + ε it (7) did it = treat i × policy t (8)

Where i refers to the student and t refers to the year; and Score it is the explained variable, that refers to the internship performance. did it consists of the interaction terms of the time and grouping dummy variables ( treat i =1 if student i belongs to the International Economics and Trade program, which was exposed to accreditation-driven reforms, and 0 if the student belongs to the Financial Engineering program; policy t =1 if time t is after 2020, otherwise, it is 0). did it , calculated as Equation 8, is the key explanatory variable of the DID method. α is the constant term; β is the coefficient of did it , and its estimated value reflects the impact of the international accreditation and a series of educational reforms resulting from it; Χ it is a set of control variables; f t represents the time fixed effect, μ i repesents the individual fixed effect of each student; ε it represents the random interference term (Sun et al., 2023).

Control variables: This study selected a series of control variables to control for the impact of other factors on internship performance. Students’ ability in learning (Ability) is expressed as the logarithm of their entrance score. Foreign language literacy (CBE) is expressed as the logarithm of the average score of Cambridge Business EnglishIand Cambridge Business EnglishII. Listening and speaking ability (FTE) is expressed as the logarithm of foreign trade English listening and speaking course score. In addition, the control variables are the logarithm of the sum of the number of competitions and events in which the student participated (CE) and each student’s grade point (GP) (Supriyanto et al., 2022).

The descriptive statistical results of the main variables are reported in Table 1. The descriptive statistics of the main variables are presented in Table 1. The dependent variable, which reflects students’ overall internship performance as evaluated by supervisors, has a mean value of 0.835 and a standard deviation of 0.138. The minimum value is 0.18, while the maximum reaches 1.00, indicating that some interns received full scores in their evaluations. This suggests that a portion of students demonstrated outstanding performance during their internships. Among the control variables, the variable with the highest standard deviation is the number of internship-related events in which a student participated. This variable ranges from 0 to 6, reflecting considerable variation in student engagement—some students did not participate in any events, while others engaged in as many as six. Overall, the distribution of internship performance is relatively stable, with most students receiving evaluations clustered around the mean, indicating a generally consistent level of performance across the sample.

Model 7 estimates the association between IACBE professional accreditation-driven educational reforms and internship performance, and the regression results are reported in Table 2.

Columns 1 and 2 report the results of regression without control variables and regression with control variables under the control of time fixed effects and individual fixed effects. The empirical results indicate that the regression coefficients of DID are significantly positive at the 1% level, suggesting that international accreditation is associated with higher internship performance. Specifically, international accreditation has led to an increase of 0.072 points in internship performance scores compared to students not subject to accreditation, thereby verifying the proposed hypothesis.

The key prerequisite assumption for the validity of the DID method is the parallel trend assumption. The performance scores of the treatment group and the control group before and after international accreditation were consistent with the change of time. Therefore, this study uses the event study method for parallel trend testing (Jacobson et al., 1993), and the econometric model is specified as follows (Equation 9): Y it = α + ∑ t = − 3 3 φ t did it + γ X it + μ i + f t + ε it (9) Where did it is a set of dummy variables. If student i received the teaching resources after the educational reforms in year t, then did it =1 and 0 otherwise. Its coefficient φ t is the object of focus of the parallel trend test, reflecting the difference between the treatment group and the control group students after the international accreditation. The rest of the variables have the same meanings as those in model 7.

Based on the distribution characteristics of the sample data, the data before the international accreditation are aggregated to period −3, and the data after the accreditation are aggregated to period 3. When t < 0, φ t is the effect of the treatment group students before the accreditation. t = 0 is the processing effect of students enrolled in the year when the educational reforms began. When t > 0, φ t captures the dynamic effects of students who have accepted the educational reforms. To show the results of the parallel trend test more visually, this study draws a trend chart of the estimated coefficient of did it under a 95% confidence interval based on the regression results (Figure 1). It illustrates the estimated coefficients of the treatment effect in different periods before and after accreditation, with a 95% confidence interval represented by the dashed error bars around each point. The x-axis is divided into periods labeled from “pre3” to “post3,” where “pre” represents years before the accreditation and “post” represents years after the accreditation, with “current” denoting the year in which the education reform was implemented.

The parallel trend test plot in Figure 1 demonstrates that the coefficient is not significant when t < 0. These results indicate that, prior to international accreditation, there was no significant difference in the internship performance between the treatment group and control group. The parallel trend test shows that did it coefficient for students enrolled after accreditation becomes statistically significant at the 1% level. Starting from the internship of senior students in 2020, the estimated coefficient becomes statistically significant at the 1% level, suggesting that international accreditation-driven reforms are associated with improved internship performance and may exhibit cumulative effects over time. A plausible explanation is that, since 2017, the Department of International Economics and Trade has implemented a series of educational reforms aligned with IACBE professional accreditation standards, including optimizing outcome-based teaching objectives, enhancing teaching methods, refining evaluation systems, improving faculty teaching skills, and integrating teaching resources. Collectively, these initiatives contributed to a more structured and supportive learning framework—characterized by clearer outcome-based objectives, improved teaching practices, and strengthened mentoring and feedback arrangements, which may facilitate students’ translation of learning into internship performance. Students who enrolled in 2017 and participated in internships in 2021 benefited from 4 years of this holistic learning system, which may help explain their higher internship performance.

To make the results more robust, a placebo test is carried out. Non-repeated random sampling was conducted for 190 students and policy time in the sample. A total of 190 students were selected each time as the virtual treatment group and its corresponding random policy time point, and the remaining students were taken as the virtual control group. This process was repeated 500 times to obtain 500 estimated coefficients of new _ treat it × new _ policy it . The cumulative distribution of coefficients are shown in Figure 2. The estimated coefficients based on random sample regression are distributed around 0, completely independent of the benchmark regression coefficient (0.07), most experiments have p-values more significant than 0.1, indicating that the observed association is unlikely to be driven by random assignment. In summary, the association between international accreditation and internship performance appears stable across specifications.

To examine whether the association between international accreditation and internship performance varies across internship industries (Tommy, 2013; Jung and Lee, 2016), students’ internship placements were categorized into technology, manufacturing, trade and logistics, finance and insurance services, education and healthcare, and other industries. The results are shown in columns 1 to 6 of Table 4. The findings indicate that the association between accreditation-driven reforms and supervisor-evaluated internship performance is statistically significant in finance and insurance services, trade and logistics, manufacturing, and technology sectors, whereas no statistically significant association is observed in education and healthcare placements. These differences may reflect variation in sector-specific evaluation norms, supervisory expectations, task structures, or the degree of alignment between curriculum arrangements and workplace assessment criteria. For example, accreditation-driven reforms emphasized outcome-based objectives, analytical reasoning, and structured evaluation practices, which may be more closely aligned with the performance dimensions commonly assessed in finance, trade, manufacturing, and technology contexts. In contrast, industries such as education and healthcare may place greater emphasis on context-dependent interpersonal or service-oriented dimensions that are less directly captured by the structured internship evaluation framework used in this study. Therefore, the observed heterogeneity should not be interpreted as definitive evidence of differential reform effectiveness across industries. Rather, it reflects context-specific patterns within internship evaluation settings, where institutional reforms and workplace assessment practices may interact differently across sectors.

Following Campbell et al. (2013), students were categorized into female and male interns. The results of group regression shown in columns 7 and 8 of Table 4, indicate that the association between accreditation exposure and supervisor-evaluated internship performance is statistically significant among female students, while the corresponding coefficient for male students is comparatively smaller and less precisely estimated. Several factors may contribute to this observed difference. Variations in supervisory evaluation standards, role assignments during internships, or patterns of workplace interaction could influence how performance is assessed across gender groups. In addition, accreditation-driven reforms placed greater emphasis on structured learning objectives, collaborative learning arrangements, mentoring, and feedback mechanisms. Such structured supports may facilitate the alignment between classroom preparation and internship evaluation criteria and may interact differently with students’ engagement patterns in internship settings. As a result, differences across gender groups could reflect variation in how students engage with or navigate these structured learning and evaluation environments.

This study employs the DID method to examine the association between international accreditation and students’ internship performance. Using supervisor- or employer-rated internship evaluations from 2017 to 2023, the results indicate that accreditation-driven educational reforms are associated with higher internship performance. The results suggest a pattern of sustained performance differences over time, which may reflect cumulative exposure to the reformed instructional and evaluation arrangements.

The findings suggest that international accreditation may function as a catalyst for institutional adjustment rather than merely a reputational signal. Through clearer learning objectives, stronger curriculum alignment, and more systematic evaluation practices, accreditation-driven reforms are associated with improved internship performance within the observed institutional framework. The timing of the estimated effects further suggests that sustained implementation and full exposure across students’ training cycles may be important in shaping internship outcomes. Internship performance in this study reflects observable workplace behaviors and applied competencies assessed during a single internship episode and should be interpreted as a context-bound outcome rather than a comprehensive measure of broader employability.

Heterogeneity analysis indicates that the association between accreditation exposure and internship performance differs across student groups and internship contexts. Variation by industry and gender suggest that observed performance differences are shaped by contextual factors within internship evaluation settings. Industry-specific results show statistically significant associations in sectors such as finance, trade, manufacturing, and technology, whereas no significant associations are detected in education and healthcare placements. Similarly, differences across gender groups indicate heterogeneous patterns in supervisor-evaluated internship performance. These findings should be interpreted cautiously, as the study does not directly examine the mechanisms underlying industry or gender differences. Rather than demonstrating differential reform effectiveness, the results reflect context-specific patterns within structured internship evaluation environments.

The innovation of this research lies in three aspects. First, it provides empirical evidence from China, where studies examining the association between international accreditation and student-level outcomes remain limited. By treating IACBE accreditation as an institutional policy intervention within a quasi-experimental framework, this study integrates entropy and DID methods to estimate program-level associations, thereby offering a methodologically robust contribution to higher education research. Second, it extends the analytical lens of accreditation research from institutional or reputational dimensions to student-level internship performance, illustrating how accreditation-driven reforms are associated with measurable differences in internship performance. Third, the study further contributes by identifying heterogeneity in the observed associations across internship industries and gender groups, showing that accreditation exposure interacts with sectoral contexts and student characteristics within structured internship evaluation environments.

This study has several limitations. First, although mentoring, feedback practices, and reflective learning are discussed as potential explanatory pathways, they are not statistically tested as mediating mechanisms. Instead, these elements are conceptualized as part of the broader educational context through which accreditation-driven reforms may be associated with changes in internship performance. Second, the empirical analysis is based on data from a single university in China, which may limit the external validity and generalizability of the findings. Future research could address these limitations by employing causal mediation analysis and using multi-institutional or cross-regional data to further examine underlying mechanisms and broader applicability.

Based on the findings of the empirical study, the following recommendations are proposed:

For higher education institutions, the findings suggest that accreditation-driven reforms may be associated with improvements in structured internship performance, particularly when reforms are sustained and coherently implemented. As internships represent a core form of work-integrated learning, institutions should prioritize curriculum alignment, transparent learning objectives, and systematic evaluation arrangements that support structured internship preparation. Rather than viewing accreditation as a one-time certification process, universities should treat it as an ongoing framework for instructional reflection and assessment refinement. Faculty collaboration, peer review of teaching practices, and alignment between coursework and internship expectations can help ensure consistency between academic preparation and workplace evaluation standards (Wanangwa, 2024; Wrobel et al., 2026). Investments in digital infrastructure, faculty development, and learning analytics may further support more coherent instructional and assessment processes (Mwila, 2024; Seyoum et al., 2024). Given the observed heterogeneity across industries and gender groups, institutions should also remain attentive to context-specific differences in internship evaluation environments (Monteiro et al., 2016). Structured mentoring, feedback mechanisms, and role clarity during placements may help reduce variation arising from misalignment between academic preparation and workplace assessment practices. Such structured support may also contribute to the development of transferable competencies valued in early career contexts (Ramírez-Montoya et al., 2025).

With respect to accrediting bodies, accreditation frameworks should continue to emphasize clarity in learning outcomes, alignment between curriculum structures and experiential components, and structured documentation of internship evaluation processes. At the same time, accreditation standards may benefit from allowing flexibility across disciplinary and sectoral contexts, recognizing that internship evaluation practices vary by industry (Malau-Aduli et al., 2020). Encouraging dialogue between institutions and employers can help improve coherence between accreditation expectations and workplace assessment realities, without imposing overly standardized models across diverse sectors.

From a policy perspective, the integration of data analysis and digital literacy into the curriculum remains important in light of broader labor market dynamics. Although employment potential is a broad concept encompassing future employability and labor market readiness, prior research suggests that internship performance can function as an observable and early indicator associated with post-graduation employment trajectories. Internship evaluations capture students’ applied skills, professional behavior, and adaptability in real work settings, and have been linked in prior studies to subsequent employability and early career development (Jackson, 2015; Silva et al., 2018). In this context, policymakers may support institutional efforts to strengthen structured internship preparation, supervision, and evaluation systems, including transparent monitoring mechanisms and industry–university collaboration. Encouraging the use of data analysis tools and digital platforms throughout coursework may further enhance alignment between academic preparation and workplace performance expectations (Zheng et al., 2024). Importantly, given that the present study focuses on supervisor-evaluated internship performance within a single institutional setting, broader conclusions regarding long-term employment outcomes require further longitudinal and multi-institutional investigation.