Zero Waste Scientific Research Evaluation: The Scientific Research Evaluation System Framework to Stimulate Scholars’ Empathy and Innovation Intention

Abstract

Based on the two-dimensional University Research Evaluation System (URES), this paper aimed to develop a comprehensive and scientific measurement scale and to empirically verify the impact of the URES on scholars’ empathy and willingness to innovate. Grounded in theory, this study analyzed the personal information and interview data of 26 university scholars publicly available online. First, through qualitative analysis (using Nvivo 12 software), we developed an initial scale for URES. Second, we tested the reliability and validity of the scale by structural equation modeling (SEM) using Mplus 8.0 software. The results show that the URES includes two dimensions: research process evaluation and investment output evaluation. The URES scale showed good reliability and validity and was confirmed to be positively correlated with scholars’ empathy and willingness to innovate. Therefore, the URES constructed in this study not only fully stimulates scholars’ empathy and innovation willingness, but also promotes the optimal use of scholars’ knowledge resources. Finally, this research helps to reduce unnecessary educational and political investment, which has important implications for the sustainable development of society.

1. Introduction

As an important source of scientific research innovation, university scholars play a pivotal role in the progress of human science and technology and social development. However, the academic, organizational, and institutional environment of scientific research and innovation in many countries and regions are facing certain problems in the process of development and reform [1]. For example, it includes random talent selection and role ambiguity, cumbersome administrative affairs, unbalanced project funding, independent development of academic creation, impetuous utilitarian research evaluation [2]. The above problems are likely to make university scholars fall into the research dilemma that mitigates their willingness to innovate in scientific research and encounter difficulties to realize “self-liberation” and “self-redemption”. These barriers are wasting vast intellectual resources of university scholars. Recent scholarly work has highlighted the importance of university research policy work and demonstrated the increased importance of the University Research Evaluation System (URES) in promoting the willingness of university scholars to be innovative in research [3,4]. At present, the URES in various countries has formed a relatively complete indicator system of scientific research achievements, such as scientific research quality [5,6], quantity [7], and influence [8]. Likewise, a few scholars have proposed the establishment of a student-centered educational model to enhance scientific research [9]. The fundamental reason for the above problems is that the formulation of the URES mainly reflects the management perspective, which is highly subjective. Few scholars build a scientific research evaluation system from the perspective of exploration and innovation intent; however, these would not conform to the laws of social development. As a result, universities’ investments in research and education are underutilized.

The evaluation indicator system constructed by “putting oneself in the position” is more likely to affect the attitude of scholars and can reflect the internal laws of scholars’ empathy and innovation intention. Taking China as a case study, this study reforms the evaluation system by “breaking the five focused points” and develops a scientific research evaluation system, and analyzes its connotations and dimensions for the category of innovation demand. According to system connotation and dimensions, we formulated a corresponding scale and verified its reliability and validity. Furthermore, we examined the impact of the scientific research evaluation system on scholars’ empathy and innovation intention. Specifically, this study was carried out as three sub-studies. In the first place, Nvivo 12 software was used to code the personal and interview data of university scholars publicly available on the Internet, and theoretical knowledge was applied to explore the dimensional composition of the URES. Second, based on the URES, this study adopted and improved the existing measurement scales in related fields, and completed the development of the initial scale independently. Third, based on this scale, we then analyzed 445 responses to a questionnaire using SEM to verify the reliability and validity of the scale and to investigate the influence mechanism between the evaluation system and scholars’ empathy and willingness to innovate.

Our study made several contributions that we summarize as follows: First, the previous research evaluation system mainly reflected the managerial perspective. The formulation process is easily influenced by subjective ideas, and the evaluation indicators are mostly formulated for the quantity [7] and quality [5,6] of research results. Prior research evaluation systems neglected the evaluation of the research process and neglected the influence of environmental factors on university scholars’ scientific research. In addition, previous studies have not developed relevant scales for evaluation systems, nor have they explored the relationship between evaluation systems and scholars’ empathy and willingness to innovate. Compared with previous studies, this study introduces the perspective of university scholars, refines the indicators of the URES through substantive analysis, and deeply integrates the quantity, quality, environment, and research process of the results. On this basis, a mixed research method combining qualitative and quantitative approaches is used for scale development, which comprehensively reveals the influence of the URES on scholars’ empathy and willingness to innovate. Second, this study enhances the understanding of the meaning and essence of the scientific research evaluation system in colleges and universities. It provides basic scales and measurement tools for subsequent empirical research and strengthens the relationship between the scientific research evaluation system and scholars themselves. Finally, the influence effect of scholars’ empathy and willingness to innovate enriches the research on scientific research evaluation systems in colleges and universities and can provide reference for research management therein. The scientific research evaluation system can fully stimulate empathy and willingness to innovate among university scholars, thereby promoting the optimal use of the knowledge resources of university scholars. Our research also provides managerial insights into reducing unnecessary investment in university research and education, which has important implications for sustainable development.

2. Literature Review and Evaluation

2.1. Concept Definition

2.1.1. Scientific Research Evaluation Systems in Universities

Research evaluation is a value judgment of the research process and its goals. Research evaluation in higher education is an evaluation of the results of knowledge creation by knowledge workers engaged in education, which is a specific form of academic evaluation [10]. Scientific research evaluation is a systematic project, which not only evaluates achievements, but also considers research projects and disciplines. It provides the assessment method of using scientific research data, and there are also other aspects that indirectly serve the scientific research evaluation system [11]. In recent years, the importance of the URES has become increasingly prominent, and its functions have been mainly reflected in scientific research guidance, value research, talent screening, incentive function, and information security [12]. In addition, the research evaluation system is also an indicator of the university’s research work, which can play a systematic role in supporting the enhancement of the university’s scientific, technological, and core competitiveness levels [13]. Therefore, the development of a research evaluation system must consider factors such as the type of university, education level, and long-term planning goals of the university. In fact, the URES has undergone continuous reform and has a more complete indicator system. For example, a few scholars have introduced indicators for scientific research, such as scientific research quality [5], quantity [7], and impact [8] of research achievements. A few scholars have also set indicators from the perspective of inclusive university development [14], resulting in a gradual shift from a quantitative bias to a qualitative bias in research.

2.1.2. Emotional Feedback of the Research Evaluation System

The scientific research evaluation system concept originated from the comprehensive evaluation activities of American higher education institutions in the 1960s [15]. People gradually realized the importance of the evaluation system and explored it continuously. During the early stages of exploring this evaluation system, the phenomenon of emphasizing quantity over quality was widespread and arguably the most serious problem [8]. Under this evaluation system, university scholars focused only on the quantity of achievements in scientific research, and became more and more impatient. As a result of the single evaluation method, university scholars have lost their pure academic fun, and their enthusiasm and autonomy in participating in academic lectures, forums and other scientific research activities have dropped sharply. Consequently, university scholars and administrators recognized the shortcomings of the evaluation system and started to change the quality of the evaluation system, such as adding dissertation indicators [3], insisting on multiple standards and quality balance [7]. However, the reform of the evaluation system has met resistance from some scholars [16] because the emphasis on quality puts higher standards on research, which undoubtedly affects the interests of some scholars. On the other hand, the evaluation system is essentially a policy and cannot be made for the benefit of all, so the focus on quality by the evaluation system can be a double-edged sword for university scholars.

2.1.3. Empathy, Willingness and Zero Waste

There is a lack of consensus on scholarly definitions of empathy. However, the literature provides various evidence on the use of empathy in academic research. Empathy focuses on personal and situational factors. There are three aspects to empathy: the process by which empathy occurs, the emotional, and the non-emotional consequences of empathy [17]. These empathy dimensions have subsequently become two recognized kinds, that is cognitive and emotional empathy. Later, both cognitive and emotional dimensions provided an idea for Davis’ empathy scale optimization [18]. It is generally believed that “willingness” and “attitude” are similar in meaning, but in past studies, psychologists have found that attitude does not explain behavior well and there is an inconsistency between attitude and behavior, so a new indicator is urgently needed to predict behavior. The concept of willingness [19,20] was developed, which can basically be regarded as a psychological disposition. Value of for objects triggers people’s willingness to cherish them [21]. For example, objects with commemorative meaning, such as a relic left behind by grandparents after their death or a gift from a good friend on an important holiday, will trigger people’s emotions and lead to the willingness to cherish them. When faced with injustice, people empathize with those wronged so increasing people’s anger and promoting the willingness to fight for justice. For instance, when seeing the poor teaching conditions in rural areas, empathy stimulates people’s willingness to donate to rural elementary schools. Moreover, empathy for life triggers people’s willingness to protect life and ecology [22]. It can be seen that empathy for objects will reduce unnecessary material use and thus lead to a greener lifestyle. Empathy for social events will lead to a positive social order, and life empathy has all the benefits mentioned above. In summary, all empathy generates a willingness to contribute to socio-ecological sustainability.

2.2. Literature Evaluation

At present, there are still many problems in the research of scientific research evaluation systems in universities. Although the indicators of the evaluation systems are related to the quantity and quality of scientific research, they do not pay attention to the relationships between the manifestation of achievements and the purpose. For example, the articles and patents of basic theoretical achievements mainly focus on the innovation of scholars. Second, there is little research on the indicator system for evaluating the scientific research process. However, the monitoring of the scientific research process plays an important role in promoting the accurate investment and use of funds and the quality assurance of scientific research results. Therefore, it is of great importance to study the indicator system for evaluation of scientific research. Third, the URES does not consider the impact of the scientific research environment on the development of innovation in scientific research, and neglects the roles of hardware equipment and the atmosphere of academic exchange on the scientific research achievements of university scholars. Finally, the indicators of the URES are not formulated based on the perspective of university scholars, and the actual effect and how this mitigate its effectiveness of the evaluation system on scholars is not measured.

Nonetheless, current research on empathy is well developed in fields such as medicine [23], psychology [24,25,26], and pedagogy [27], but there are still relatively few studies on how to integrate empathy into the evaluation system of universities. Meanwhile, most of the previous studies on empathy explore the components of empathy ability. Nonetheless, this study takes the definition of empathy as the main theoretical tool and explores the empathy of university scholars towards the university scientific research evaluation system in the process to realize better synergy.

3. Research Hypotheses

3.1. Scholar’s Empathy in University Scientific Research Evaluation

The URES are usually found in policy documents of university research management. Its promulgation will have an impact on the mental state of scholars in colleges and universities, and then affect their cognition and emotion. Policy documents are not specifically formulated for specific individuals, and their recipients are generally groups with similar characteristics [28]. The scope of influence is wide, and higher requirements are placed on the readability of the content of policy documents. In addition, the formulation and change of policies are often aimed at achieving specific goals [29], and they will be biased towards policies and measures that are conducive to the realization of goals, with distinct identification features. To adapt to the psychological state of policy changes, university scholars carefully read the relevant projects of the university scientific research evaluation system formulated by policy makers [30]. The understanding of the content is likely to trigger emotions about the content of the system [31]. If they are happy, they think the system can give them more room to grow. For example, if they are satisfied, they will consider a system that aligns with their scientific philosophy of pursuing high-quality scientific results. However, if they are not satisfied with the system, they will feel that the system sets a higher standard for scientific results, so they must spend more time and effort. Based on this, this study proposes the following hypotheses:

H1. 

The university scientific research evaluation system has a significant positive effect on scholars’ empathy.

3.2. Scholars’ Innovation Intention in University Scientific Research Evaluation

Developing the URES from a manager’s perspective can facilitate country-level policy development or reform. In recent years, the scientific research concept of “seeking quantity over quality” has seriously damaged the development of scientific research. This phenomenon has caused a sharp decline in the willingness to innovate in scientific research, resulting in many scientific research results without any major innovation [32]. Therefore, to promote scholars’ willingness to innovate, the makers of the evaluation system continue to tilt the evaluation indicators towards the quality of scientific research, so that scholars can focus on their innovative thinking and achieve scientific research results with real social significance.

On the other hand, to pursue objective evaluation, today’s scientific research evaluation system pays increasing attention to scientific research quality indicators such as the article’s impact factors and patent’s impact scope, no longer limited to the original quantitative indicators [3]. This change means that university scholars need to spend more time and energy on quality. At the same time, high-quality scientific research results often need to discover and solve long-standing unresolved social or scientific problems, and need to maintain a high degree of rigor [33]. This process paves the way for academic innovation intent [34]. We believe that unless scholars break away from their standard approaches, it will be difficult for them to bring innovation to scholarly research. Therefore, this study proposes the following hypotheses:

H2. 

The university scientific research evaluation system has a significant positive effect on scholars’ innovation intention.

3.3. Scholars’ Empathy and Innovation Intention

The basis of promoting innovation intention is that scholars can fully understand and agree with the URES. It is difficult for scholars to understand the evaluation system unless it is carefully formulated according to the method and objectives of the URES [35]. Scholar understanding was limited by the old school of thought that is “scientific research quantity”, which decreases their innovation intention [36,37]. Moreover, an increased understanding of evaluation systems triggers scholars’ negative emotions such as dissatisfaction and disgust towards the system [38]. Such emotions stem from their disapproval of the evaluation system, thinking that the system has damaged their own scientific research concepts, or that their scientific research habits are completely incompatible with the system. Such emotional reactions resulted in the scholars’ hostile attitudes towards the evaluation system. According to the self-verification theory, scholars will continue to adhere to their original scientific research concepts to make their behaviors conform to their own cognition, thus reducing the psychological imbalance [39,40]. Based on this, the study proposes the following hypothesis:

H3. 

In scientific research evaluation, the generation of scholars’ empathy has a significant positive effect on scholars’ innovation intention.

Nowadays, scientific research achievements that “value quantity but not quality” are everywhere, which has a great impact on the scientific research innovation atmosphere [41]. To enhance the innovation intention of scholars, reform of the scientific research evaluation system in universities has gradually focused on the scientific research quality indicators. This tendency will make scholars break the previous scientific research thinking of making up for numbers [42]. Therefore, urging them to spend more time and energy on improving the scientific research quality, and to find and solving new problems as the foothold of scientific research to exert a positive effect on the innovation intention of scholars. The role of the above-mentioned scientific research evaluation system on innovation intention is based on scholars’ awareness of the emphasis on quality evaluation indicators and their recognition of the system. Based on this, this study proposes the following hypothesis:

H4. 

In scientific research evaluation, scholars’ empathy plays a mediating role in the generation process of scholars’ innovation intention.

Based on the above hypotheses, the conceptual framework proposed in this study is shown in Figure 1.

4. Research Design and Analysis

4.1. Research Case

Based on the innovative principle of recipient selection, this study selects the reform of the URES in China as a case study. Currently, China’s scientific research evaluation system takes on the phenomenon of “five focuses”, specifically focusing on articles, ranks, professional titles, academic qualifications, and awards [43,44]. It is worth mentioning that this phenomenon not only occurs in China, but also exists around the world, which may cause great damage to the quality of scientific research results and the willingness of scholars to innovate. At present, China is taking relevant reform measures for the scientific research evaluation system of universities to “break the five focuses”, actively encouraging the URES to pay more attention to quality. The innovation process aims to achieve the purpose of promoting scientific research innovation, meeting the innovation conditions of “existing research cannot explain cases” and “innovative research can provide enlightenment for phenomena that have not been studied in the past”. “They are working to expand the scholar community’s understanding of the reform of the university’s research evaluation system. This will have an important impact on the reform of the world’s research evaluation system, so it is innovative and representative to use it as a case study.

4.2. Research Methods and Procedure Design

Based on the scale development paradigm [45], this study follows the “connotation defining, dimension identification, measurement scale construction, scale purification, scale reliability and validity test, and influential effect test” of the URES. We adopted mixed qualitative and quantitative research methods and the design idea of multiple data sources to form the theoretical framework of the scientific research evaluation system of universities. In particular, Sub-study 1 was devoted to connotation defining and dimension identification, Sub-study 2 mainly focused on the construction of measurement scale, the purification of the scale, the reliability and validity of the scale, and Sub-study 3 tested the influential effect (Research design is shown in Figure 2).

5. Study 1: Structural Analysis of Preliminary Evaluation System

In Study 1, we evaluated the original qualitative materials comprehensively and systematically. We followed the three-level coding procedure, such as refining the initial categories, then merged, summarized the similar or consistent initial categories, and finally converged the constructs to the corresponding categories.

5.1. Methods

In this study, we employed Nvivo12 version software (Developed by Professor Lyn Richards of La Trobe University, Australia) to examine three-level open, axial, and selective encoding programs. As mentioned above, we systematically combed and summarized the interview data and online data of 26 university scholars. Open coding used Nvivo12 software to obtain more than 750 original sentences and corresponding initial constructions based on in-depth analysis of original qualitative materials. In the process of categorization of initial constructions, those that occurred less than twice were removed, those repeated twice or more were retained. In axial coding, we integrated and clustered the initial categories by their relevance. Selective coding further summarized, merged, and refined the main categories according to the “storyline” and aggregates them into core categories. Based on coding, data from posts and comments for nearly three months (from 28 April to 28 July 2022) were collected on 28 July 2022. A total of 11,213 posts and 18,356 comments were obtained for the theoretical saturation test.

5.2. Results

First, Study 1 extracted 26 categories such as scientific research funding, expected benefits, project innovation, rationality of target setting, and medium-term technical indicators through open coding (see

Table 1. Open coding of research evaluation system in universities.

Initial Scope	Original Statement
Scientific Research Funding	The funds received from national, regional and cross-cutting projects will increase my investment in research
Expected Benefits	My school will take more time to think of a good project topic if the project’s expected economic, social and ecological benefits are scrutinized in the project proposal.
Project Innovation	Each project proposal template from the university needs to describe the innovation of the project
Reasonableness of goal setting	When writing the project, the research objectives need to be elaborated, especially the need to focus on the extent to which the objectives are realistic, otherwise the objectives are not feasible and the chances of success of the project will be reduced
Medium-term technical indicators	The stronger the monitoring of the completion of the mid-term milestones, the more I will follow the course of my research plan at the time of the project
Mid-term funding	My university will ask me to submit several mid-term funding reports at the mid-term of the project
High quality papers encouragement	The quality of the papers I write will be further improved if the school can supply high quality papers and research for a longer evaluation period
Application timeframe	At the end of the project, my school has a strict time limit for the project acceptance application, so I can’t procrastinate and say to the person in charge that my project will be submitted later.
Material specification	When submitting the final report, if the project is not in order, you will be sent back to rewrite it.
Authentic materials	Our school has a special staff to review the authenticity of all documents at the end of the project.
Scientific research team input funding	Every year, my school brings in talents from overseas and prestigious universities with high salaries, which puts a lot of pressure on my research.
Scientific research results award	Awards are motivational for me, and I will keep trying to get closer to them before I get them, and after I get them I will try to keep the honor I have.
Inconvenience of reporting system	The reporting process at my school is very cumbersome, and the problems that arise in the submitted reports are not addressed all at once, and often one problem is solved and then a new one is raised
Incentive mechanism for project establishment	The school has a special incentive scheme to increase the willingness of teachers to write projects after the project is established
Paper Impact Factor	The publication of papers in different divisions of JCR has a great impact on my promotion
Author Contribution	When publishing a monograph or a paper, the university is very interested in whether I am the editor-in-chief and the title of the paper
Number of scientific research papers output	When I don’t meet the university’s output, I ask my students to help me publish
Proportion of Research Fixed Assets	The university’s investment in fixed assets for research has a significant impact on my research
Number of patents granted	The more patents I create, the more I am motivated to create more patents.
Patent Influence	When I know that my patent is being used by many people, I will continue to push for the next patent that will bring convenience to the general public, because the sense of accomplishment makes me feel very honored.
Holding academic seminars	Holding academic seminars allows me to collide with other scholars’ ideas, which in turn can lead to good sources of inspiration for my papers
Hardware facilities	When I need to conduct experiments for my thesis, the equipment in the lab often makes it difficult for me to write the paper
Science and Technology Innovation Team Cultivation	My school does not pay attention to the cultivation of innovative teams, so the team building of the school has been very backward, and the research output is very inefficient
Number of domestic and international cooperation and exchange	I am very impressed with the collaboration and exchange at my school. I feel that my thinking is limited to my own country and that the opportunity to exchange is a great way to innovate my scientific thinking.
Construction of Research Facilities in Universities	The lack of research space at my school makes it difficult to find a suitable place to gather my team for group discussions or writing.
Advanced laboratory construction	The shortage of labs has prevented me from fully implementing my experimental ideas, and I need experimental data to write my thesis

). Details of all categories are shown in Table 1.

Second, 7 sub-categories were extracted through axial coding (see

Table 2. Spindle coding of university research evaluation system.

Main Scope	Sub Scope	Initial Scope
Research Process Evaluation	Project establishing	Expected benefits; project innovation; reasonableness of project goal setting.
	Implementation	Mid-term technical indicators; mid-term funding; high quality papers encouraged
	Inspection	Application timeframe; standardization of materials; authenticity of materials
Research input-output evaluation	Research funding	Scientific research funding; research team investment funding; convenience of reporting system; supporting incentives for project establishment
	Scientific Research Environment	Hardware facilities; proportion of scientific research fixed assets; construction of university research sites; construction of advanced laboratories; holding of academic seminars; number of domestic and foreign cooperation and exchanges; cultivation of scientific and technological innovation teams
	Quantity of Output	The number of scientific research papers; the number of patents granted; the number of scientific research achievements awarded
	Quality of Output	impact factor of papers; contribution of authors; influence of patents.

), including project establishment, implementation, acceptance, research funding, output, and research environment. According to the correlation, it can be classified into two categories, namely scientific research process evaluation and scientific research input-output evaluation.

Finally, through selective coding, the core category was defined as the URES which promotes scholars’ empathy and innovation intention”, and its dimensional framework was “scientific research process evaluation and scientific research input and output evaluation”. Based on systematic exploration of original qualitative materials, the core categories were connected with the different levels of categories by means of “storylines”. We then established the theoretical framework of the scientific research evaluation system of universities. The scientific research process evaluation strictly controlled the process from project initiation to project conclusion. The project initiation conditions ensured the accurate investment of scientific research funds, and the medium-term monitoring ensures the scientific use of scientific research funds, and the conclusion review ensured the quality acceptance of the final results of scientific research projects. The scientific research input and output evaluation as to evaluate the input of scientific research funds and the output of achievements based on the scientific research process evaluation. The input and output results were based on the scientific research project process. Among them, the sub-dimension scientific research environment and output quality evaluation was the standard for further improving the scientific research input and output. The URES stipulates communication, hardware environment, and the quality of papers, and pays more attention to the internal development needs of university scholars and the quality of scientific research results in the field of scientific research. Therefore, this study refined the URES as the core category, and summarized the scientific research process evaluation and scientific research input-output evaluation as the main categories of the university evaluation system. Finally, the theoretical robustness was tested. The results show that the dimension of URES was rich enough. The two second-level dimensions of the scientific research process evaluation and input-output evaluation and the seven first-level dimensions of project establishment, implementation, acceptance, scientific research funding, scientific research environment, quantity, and quality did not find new components. Hence, the dimensions of the URES were theoretically saturated.

6. Study 2: Scale Development and Empirical Test of University Scientific Research Evaluation System

To design the scale for this study, we used scale development steps using a normative process [46]. The designed scale was tested for reliability and validity.

6.1. Methods

The expert group discussed and revised the existing scales and combined them to form an initial set of questionnaire items after reaching the agreement. The finalized questionnaire was then distributed to collect the data. We used SPSS 22.0 software to conduct exploratory factor analysis and applied Mplus 8.0 confirmatory factor analysis to test the reliability of the 152 questionnaires collected. The first-order variables in the study included scientific research project, scientific research execution, scientific research acceptance, scientific research funding, scientific research environment, output quantity, output quality, scientific research project, scientific research execution and scientific research acceptance. While the second-order variables included scientific research process evaluation and scientific research input-output evaluation. The sampling used for data collection is explained as following (see

Table 3. Situation of Sample Data.

Item	Classification	First-Round Data		Second-Round Data
		Frequency	Percent	Frequency	Percent
Gender	Male	75	49.3	218	49.0
	Female	77	50.7	227	51.0
Age	Under 25 years old	3	2.0	9	2.0
	26–35 years old	38	25.0	102	22.9
	36–45 years old	64	42.1	205	46.1
	46–55 years old	34	22.4	92	20.7
	56 years old and above	13	8.6	37	8.3
Monthly income	Less than 7000 RMB	4	2.6	12	2.7
	7001 RMB–11,000 RMB	25	16.4	79	17.8
	11,001 RMB–15,000 RMB	59	38.8	178	40.0
	15,001 RMB–19,000 RMB	49	32.2	131	29.4
	Above 19,001 RMB	15	9.9	45	10.1
Title	None	7	4.6	19	4.3
	Primary	24	15.8	69	15.5
	Intermediate	63	41.4	186	41.8
	Associate Senior	45	29.6	135	30.3
	Senior	13	8.6	36	8.1
School type	Private colleges and universities	31	20.4	77	17.3
	Local Universities	30	19.7	94	21.1
	Provincial Universities	30	19.7	113	25.4
	Universities in Double First Class University Plan	30	19.7	85	19.1
	Universities in Project 985	31	20.4	76	17.1

):

• Sample size and sampling method

This study used a stratified sampling technique to collect the data from respondents. The questionnaire was distributed among the universities in Jiangxi, Zhejiang and Guangdong, China, relying on the provincial science foundation project. The university scholars were approached with the help of social network relations and collected data from 152 respondents.

2

Sample size

The questionnaire respondents were 49.3% males and 50.7% females. The data were collected from different age groups, mainly 42.1% respondents aged 36–45, as main group surveyed. In terms of monthly incomes, responses include 16.4% respondents with the income of RMB 7001–11,000, 38.8% respondents with the income of RMB 11,001–15,000, and 32.2% respondents with the income of RMB 15,001–19,000. Moreover, 41.4% respondents had an academic title of middle rank. Remaining respondents came from private universities, local universities, provincial universities, universities in Double First-Class University Plan and Project 985, with a relatively even sample distribution.

6.2. Results

First, the initial two-dimensional scale (i.e., research process evaluation and research output evaluation) were constructed by referring the relevant prior scales developed by Dressel (1976) [47] and Ramsden (1979) [48]. Second, we carried out exploratory factor analysis (EFA) and the results showed a KMO value of 0.871. The approximate chi square value of Bartlett’s spherical test 4407.3 (p < 0.001) highlights the suitability of the sample for factor analysis. The measurement items with the main load lower than 0.5 were excluded. The main load of the purified scale was greater than 0.6, while the cross load was less than 0.4. The seven factors jointly explained 86.83% of the total variation (see

Table 4. Results of Exploratory Factor Analysis.

Items	1	2	3	4	5	6	7
LX1			0.902
LX2			0.912
LX3			0.905
ZX1					0.869
ZX2					0.935
ZX3					0.883
YS1							0.893
YS2							0.923
YS3							0.877
JF1						0.930
JF2						0.845
JF3						0.956
JF4						0.921
SL1				0.918
SL2				0.934
SL3				0.888
ZL1	0.942
ZL2	0.926
ZL3	0.854
HJ1	0.891
HJ2		0.884
HJ3		0.848
HJ4		0.948
HJ5		0.936
HJ6		0.930
Explaining variance (%)	25.354	18.121	12.097	10.607	7.875	7.332	5.442
Total (%)	25.354	43.475	55.572	66.179	74.054	81.386	86.828

.)

It has been preliminarily confirmed that the seven first-order dimensions of the scale have good discriminant validity and convergent validity. Finally, a university scientific research evaluation system scale with 25 measurement items formed (shown in

Table 5. Measurement Scale after Purification.

Second Order Dimension	First Order Dimension	Items
Scientific Research Process Evaluation	LX1	What is the strength of your university’s research evaluation system in terms of the expected economic, social and ecological benefits of the project?
	LX2	How strong is the research evaluation system at your university in terms of the degree of innovation of the project?
	LX3	How strong is the research evaluation system of your university in reviewing the reasonableness of the project objectives?
	ZX1	How strongly does your university’s research evaluation system enforce the completion of mid-term technical indicators?
	ZX2	How strongly does your university’s research evaluation system enforce the implementation of the mid-term funding calculation?
	ZX3	Does the university provide a long evaluation period for the emergence of high-quality papers and research, and how strongly does it encourage the output of high-quality papers?
	YS1	How strongly does your university’s research evaluation system enforce the timeliness aspect of acceptance applications?
	YS2	How strongly does the research evaluation system of your university enforce the standardization of acceptance materials?
	YS3	How strongly does the research evaluation system of your university enforce the authenticity of the acceptance materials?
Scientific Research Output Evaluation	JF1	How strongly does your university’s research evaluation system reward the adequacy of research funds received?
	JF2	How strong is the research evaluation system at your university in terms of funding for research team building?
	JF3	How convenient is the reporting system at your university?
	JF4	How strong is the incentive mechanism for project funding in your university’s research evaluation system?
	HJ1	How strong is the scientific research system of your university in terms of evaluation of academic seminars?
	HJ2	What is the evaluation of your university’s research system in terms of domestic and international cooperation and exchange?
	HJ3	What is the evaluation of your university’s scientific research system on the cultivation of scientific research innovation team?
	HJ4	What is the evaluation of your university’s scientific research system in terms of the proportion of new scientific fixed assets?
	HJ5	What is the evaluation of the research system of your university in terms of hardware facilities?
	HJ6	What is the strength of your university’s scientific research system in terms of the construction of scientific research sites?
	SL1	What is the evaluation of your university’s research system in terms of the number of papers produced?
	SL2	How is your university’s research system evaluated in terms of the number of patents granted?
	SL3	What is the evaluation of your university’s research system in terms of the number of scientific research awards?
	ZL1	What is the evaluation of your university’s research system in terms of impact factor of papers?
	ZL2	What is the evaluation of your university’s scientific research system in terms of author contribution ranking?
	ZL3	How strongly does your university’s research system evaluate the impact of patents?

).

Next, we used the structural equation software Mplus to estimate the parameter values in the model by the maximum likelihood method. The model fitting results are highlighted in

Table 6. Scale Goodness of Fit.

Fitting Index	χ2/df	RMSEA	CFI	TLI	SRMR
Coefficient	1.869	0.076	0.950	0.941	0.055

, wherein, the absolute fit index χ²/df is 1.869, RMSEA 0.076 and SRMR 0.055, both are less than 0.08. The results further highlights the CFI value 0.950 and TLI value 0.941, both greater than 0.9. Overall, these show a well-fitted model (see Table 6).

The internal consistency coefficient of the first-order variable, Cronbach’s α, and the composite reliability (CR) are between 0.906 and 0.979 (both higher than 0.7). This indicates that the measurement items of the first-order variables have strong reliability. While the standard load of the measurement items of each variable is higher than 0.7, and the AVE value is greater than 0.5, which indicates that the scale has strong aggregation validity. The results further highlight the greater AVE value of each variable than the correlation coefficient between variables. This indicates that each variable has a strong discrimination (see

Table 7. Results of Aggregation Validity Test.

	CR	AVE	LX	ZX	YS	JF	HJ	SL	ZL
LX	0.952	0.868	0.932
ZX	0.922	0.799	0.435	0.894
YS	0.911	0.774	0.372	0.199	0.880
JF	0.942	0.803	−0.186	−0.075	0.027	0.896
HJ	0.964	0.818	0.060	−0.161	0.085	0.087	0.904
SL	0.891	0.732	−0.005	−0.013	0.137	0.256	0.336	0.856
ZL	0.942	0.844	0.045	−0.134	0.035	0.064	0.381	0.333	0.919

Oblique diagonal is the square root of AVE value of each variable.

).

The fitting degree of the second-order model indicates that the absolute fitting index χ²/df is 1.890, RMSEA and SRMR are 0.077 and 0.076, respectively, both less than 0.08. Further the values of CFI (0.946) and TLI (0.940) are both greater than 0.9. In conclusion, the overall fitting of the second-order model is good (see

Table 8. Second-order Model Goodness of Fit.

Fitting Index	χ2/df	RMSEA	CFI	TLI	SRMR
Coefficient	1.890	0.077	0.946	0.940	0.076

, and variable abbreviations see

Table 9. Variable Abbreviations.

Abbreviation	Variable Name	Abbreviation	Variable Name
GC	Scientific Research Process Evaluation	HJ	Scientific Research Environment
LX	Research Project	SL	Quantity of outputs
ZX	Research execution	ZL	Quality of output
YS	Research Acceptance	GQ	Scholars’ empathy
TC	Research Input and Output Evaluation	RZ	Cognitive empathy
JF	Research Funding	QX	Emotional empathy

). Secondly, the weights of the second-order formative factors are between 0.400 and 0.965, both of which are larger than the minimum standard of 0.2, which indicates that all the first-order factors have significant contributions to the corresponding second-order factors, and the degree of explanation is high (see Figure 3). To sum up, it shows that the overall fitting of the second-order model is good.

7. Study 3: Verification of the Influential Effect of the University Scientific Research Evaluation System

This sub-study explored the influence mechanism between the university scientific research evaluation system and scholars’ empathy and innovation intention. This verified the reliability and validity of the scale of the university scientific research evaluation system that helped in enriching the empirical research on the evaluation system and scholars’ empathy and innovation intention.

7.1. Methods

The independent variables of the research model were adopted and developed from the university research evaluation system. This consisted of 25 items in total. The scholars’ empathy scale was adopted from the ACME empathy scale [18] two dimensions of cognitive empathy and emotional empathy included six items of cognitive empathy and eight items of emotional empathy, 14 items in total. The willingness to innovate scale was adopted from the Innovation Scale [49], with a total of eight items. The questionnaire was designed using a 5-point Likert scale, with “1” indicating “strongly disagree” and “5” indicating “strongly agree”.

The research team conducted a questionnaire survey between 14 May and 25 July 2022. This survey collected 512 questionnaires (445 of them valid), excluded those with missing key information and apparently random answers. First, we used validation factor analysis to test the reliability and validity of the first-order reflective constructs in the model. Second, we assessed the validity of the second-order factor structure of the university research evaluation system and scholars’ empathy using the significance of path coefficient. Next, we used the second-order model to measure the predictive ability and overall goodness of fit of the model. Lastly, we tested the structural model of the research hypothesis. The first-order variables include research project, research execution, research acceptance, research funding, research environment, output quantity, output quality, cognitive empathy and emotional empathy, research project, research execution, and research acceptance form. While the second-order variables consisted of research process evaluation, research funding, research environment, output quantity, and output quality form the second-order variables of research output evaluation. Cognitive empathy and emotional empathy form the second-order variables of Scholars’ empathy. The sample data were selected as follows (see Table 3).

• Sample size and sampling method

This study used a combination of online and offline modes to distribute the questionnaire. However, the questionnaire was collected through diverse channels to avoid homophily bias. The research samples were collected from the following sources: (1) recruiting university scholars from friends, family, and classmates to participate in the online questionnaire research by snowball sampling; (2) placing electronic questionnaires in university classroom discussion groups, study exchange groups and other relevant social media sites; (3) distributing paper and electronic questionnaires in universities in different regions by using project resources. In addition, to encourage and increase the respondent’s participation in survey, we prepared red packets as reward for online respondents and exquisite gifts to offline respondents as a token of appreciation.

2

Sample size

The largest group of study respondents were university scholars mainly aged 36–45 accounted for 46.1%. Most of the respondents i.e., 40.0% have monthly income of RMB 15,001–19,000. In terms of job titles, intermediate titles accounted for 41.8%, followed by associate senior titles accounting for 30.3%. Moreover, the types of schools of the university scholars surveyed were relatively even.

7.2. Results

The study results showed that the CR value of the first-order latent variable lay between 0.832 and 0.985, which indicates strong reliability. The standard load of all measurement items was higher than 0.7, and the AVE value of each variable was greater than 0.5. this indicates the strong aggregation validity. Moreover, the square root of AVE value of each variable was greater than the correlation coefficient between this and other variables. This shows the average variance explained by the measurement items of the 10 first-order latent variables (i.e., 7 first-order constructs of the university scientific research evaluation system scale, 3 first-order constructs of scholars’ empathy and innovation intention) was greater than the correlation coefficient between each latent variable and all other variables in the model. The first-order latent variables of the measurement model had strong discrimination validity. The absolute fit indicators of the second-order model all met the criteria, with the absolute fit index χ²/df of 1.784 and RMSEA of 0.072. These both were less than 0.08. The CFI value was 0.923 and TLI 0.937 and both were greater than 0.9. Although the SRMR of 0.084 was greater than 0.08, it was within the acceptable range, indicating that the overall fitness of the model was good (see

Table 10. Scale Goodness of Fit.

Fitting Index	χ2/df	RMSEA	CFI	TLI	SRMR
Coefficient	1.784	0.072	0.923	0.937	0.084

).

The path coefficient between the second-order factor and the first-order factor was between 0.254 and 0.628 (p < 0.001) (see Figure 4). This indicates the high degree of explanation of the first-order factor for the second-order factor. The absolute fitting index of the second-order model reached the standard. We analyzed the overall fit of the structural equation model again. The results showed that overall model fit indicators met the criteria, with the fit index χ²/df of 2.534, RMSEA of 0.081, SRMR of 0.086. This was greater than 0.08 but still within the acceptable range. The value of CFI was 0.915 and of TLI 0.924, that were greater than 0.9. In summary, this indicates that the overall fitness of the model was good (see

Table 11. Scale Goodness of Fit.

Fitting Index	χ2/df	RMSEA	CFI	TLI	SRMR
Coefficient	2.534	0.081	0.086	0.915	0.924

).

The hypothesis test results showed a significant positive effect of evaluation of the scientific research process on the empathy and innovation intention of scholars (β1 = 0.048, p < 0.05; β2 = 0.172, p < 0.001). While Scientific research input and output evaluation had a significant positive effect on innovation intention (β = 0.674, p < 0.05). Scholars’ empathy also significantly positively affected innovation intention (β = 0.151, p < 0.05). However, Scholars’ empathy had no mediating effect between the evaluation of scientific research process and innovation intention, nor between the evaluation of scientific research input and output and innovation intention (see

Table 12. Results of Hypothesis Test.

	Estimate	S.E.	Est./S.E.	p-Value	Lower Confidence Limit (2.5%)	Upper Confidence Limit (97.5%)
GC→GQ	0.048	0.025	1.888	0.039	0.068	0.154
TC→GQ	−0.047	0.036	−1.949	0.069	−0.148	0.041
GC→CX	0.172	0.083	2.077	0.038	0.096	0.149
TC→CX	0.674	0.096	3.869	0.000	0.428	0.723
GQ→CX	0.151	0.042	2.899	0.004	0.091	0.206
GC→GQ→CX	0.002	0.004	0.013	0.348	−0.001	0.006
TC→GQ→CX	0.006	0.005	0.342	0.171	−0.007	0.012

).

8. Research Conclusions

8.1. Conclusions

At present, China’s scientific research evaluation system has the phenomenon of “Five Only”, that highlights the focus of scholars is only on publishing papers, getting honors, obtaining titles, their personal academic improvement, and winning awards. The reform measures related to “breaking the five only” university scientific research evaluation system have been taken to actively encourage the university managers to pay more attention to quality and process. Hence the purpose of promoting scientific research innovation can be achieved. Targeted at university scholars, this study defined the meaning of the university scientific research evaluation system based on a literature review that identified and refined its two-level dimensions through grounded theory and formed a two-level theoretical framework. This framework consisted of two secondary dimensions (i.e., scientific research process evaluation and scientific research output and input evaluation) and seven primary dimensions. Furthermore, this study designed the measurement items of scientific research evaluation in universities. The initial scale of scientific research evaluation system in universities was developed by using the expert method to iteratively correct the items. This process was aligned with the grounded theory and measurement scales of the prior literature.

This study conducted two rounds of questionnaire surveys and related work to verify the reliability and validity of the scale and test the influential effect of the scientific research evaluation system of universities. First, the reliability and structural validity of the scale was verified by exploratory factor analysis and confirmatory factor analysis. Second, this study constructed a theoretical relationship model between the university scientific research evaluation system and scholars’ empathy and innovation intention that was based on the theory and literature of scholars’ empathy and innovation intention. We used a structural equation model to test the measurement model and structural model, and verified the reliability and structural validity of the scale. This further confirmed the effect of university scientific research evaluation system on scholars’ empathy and innovation intention and the predictive validity of the scale. Through the empirical test of the effect of the university scientific research evaluation system on the empathy and innovation intention of scholars, this study draws the following conclusions: (1) The scientific research process evaluation has a significant positive effect on the empathy and innovation intention of scholars. This study also holds that the scientific research process can be divided into three stages, namely, project initiation, implementation, and acceptance. In the process of project initiation, the higher the expected economic and social benefits or benefits brought by the scientific research project (vertical) by the university, the more scholars will spend on refining their own projects. We further contend that the high-quality projects need to be based on innovative thinking. In the implementation stage and the acceptance stage, university scholars are given more time to produce high-quality works. Additionally, the award of scientific research achievements will promote scholars’ recognition of the university scientific research system. (2) The scientific research input and output evaluation has a significant positive effect on innovation intention. The conclusion of this study can also be explained by cognitive evaluation theory, as evaluation and coping are core concepts of this theory, where, evaluation refers to the process in which individuals constantly search for information needed in the environment and possible threats. It is further to conduct multiple rounds of uninterrupted evaluation of the stimulus time that is meaningful to them. Meanwhile, the re-evaluation process includes coping strategies and consequences. The university’s investment in scientific research and hardware equipment are related to the interests of scholars. That enables scholars to use these favorable factors to approach potential interests including the use of favorable scientific research environment and equipment to expand their scientific research achievements. In addition, the emphasis on the quality of scientific research results will also cause scholars to have crisis consciousness. Scholars will think about coping strategies and make efforts to improve the quality of their scientific research, and then enhance their innovation consciousness. (3) Scholars’ empathy has a significant positive effect on innovation intention. Scholars’ recognition of the scientific research evaluation system of colleges and universities will make their scientific research road closer to the evaluation system. For example, the reform of “breaking the five focuses” enables the scientific research evaluation system of universities to pay more attention on quality. While scholars will keep consistent with the evaluation system constantly by means of improving the quality of their scientific research results. That must be dependent on the innovation intention of scholars.

8.2. Discussion

8.2.1. Study 1 Discussion

The evaluation system of scientific research is still a policy in essence. Therefore, its formulation is mostly based on the perspective of managers [50]. The formulation process is easily influenced by the subjective ideas and does not take into account the perceptions of university scholars about the evaluation system. Hence, it causes the scholars’ cognitive biases about the evaluation system. It is similar to the diffusion of new technologies that will promote the development of society [51]. The discomfort of university scholars with new technologies will still lead to resistance [16]. Therefore, “no matter how good a policy is, it needs the approval and support of its implementers.” There are many policies of caring for people; they have gained high policy satisfaction, and at the same time, they have stimulated people’s production efficiency, made full use of human resources, and slowed down the waste of resources. This rule is also reflected in policy formulation and implementation. For example, a series of favorable policies involving farmers in formulation have improved farmers’ production efficiency [52]. If students are allowed to participate in the formulation of the education system as managers, the education system will also get sustainable development [53]. Therefore, to make full use of the knowledge resources of university scholars, the establishment of scientific research evaluation system in universities should also involve scholars fully. Consequently, the sample respondents in this study were restricted to the Chinese university scholars to strengthen the emotional connection between the evaluation system and scholars. Moreover, we used a bottom-up approach to conceptualize and create dimensions for the evaluation system based on theoretical research. By arranging and classifying the importance of the evaluation system indicators by scholars, the concept, and dimensions of the evaluation system of scientific research in colleges and universities in this study are worked out, to meet the needs of formulating the evaluation system of URES from the perspective of scholars and change the previous perspective of administrators and establishing the university evaluation system from the perspective of Chinese scholars. However, China’s scientific research dilemma not only occurs in China, but also exists in other countries around the world, for example, the scientific research policies of all countries around the world are based on the perspective of managers. Therefore, this research can bring some reference significance to the formulation of international scientific research evaluation system.

8.2.2. Study 2 Discussion

In the field of scientific research, it is a common phenomenon that the evaluation system of scientific research focuses on results over processes [7]. University managers often use tasks and achievements as the criteria for judging academic research achievements [3], while ignoring the changes of thinking process, learning skills, emotional attitude, and subjective experience in the process of scientific research. However, the policy implementation only considers the effects and cannot implement what is advocated in the field of scientific research. Based on grounded theory, this research obtained two secondary dimensions: input-output evaluation and scientific research process evaluation. This not only satisfies the classification of the scientific research evaluation system from the perspective of university scholars, but also includes process evaluation, and then provides a new perspective for the formulation of the scientific research evaluation system. The construction and improvement of an index system of scientific research process quality evaluation can guide the scientific development of an evaluation system, indirectly promote the development of advanced learning evaluation concepts and principles, and thus promote the sustainable development of the scientific research evaluation system in universities. In addition, previous studies on university research evaluation systems have focused on indicator development [8], influencing factors [54], and research outcomes [55]. At present, the scholarly efforts on scale development for evaluation systems are relatively sparse. Whereas this study followed the standardized scale development procedure [46] and based on the previous research on the concept and dimensions of the URES, developed the scale of URES. Therefore, it can provide measurement tools for scientific research measurement in universities and can also provide reference for follow-up research.

8.2.3. Study 3 Discussion

Previous studies on the effects of research evaluation systems have mostly focused on scholars’ research quality [5], research quantity [7], and the changes of behavioral attitude [56]. Relatively, less scholarly efforts have been applied to examine the effects of research evaluation systems on scholars’ empathy and willingness to innovate. Based on previous exploration, this study used a quantitative analysis method to explore the causal logic from university research evaluation system to scholars’ empathy to innovation willingness. By innovatively introducing scholars’ empathy into it, it comprehensively revealed the influence effect of the university research evaluation system on innovation willingness, enriched and expanded the antecedent mechanism of scholars’ innovation willingness, not only avoided the subjectivity of this study, but also re-verified the effect of the university research evaluation system explored by this research, which was scientific. The conclusion that “the evaluation of scientific research process has a significant positive impact on scholars’ empathy and innovation willingness” also reflects the importance of process evaluation to university scholars and gives a different perspective of scientific research policy making. At the same time, this study deepened the cross-research between system formulation and psychology. The effect verification of university scientific research evaluation system shows that it can fully stimulate scholars’ empathy and innovation willingness, thus promoting the full utilization of university scholars’ knowledge resources and having a new perspective and reference significance for the formulation of scientific research evaluation system.

8.2.4. Conclusive Discussion

Primarily, by the nature, the research evaluation system of the university is still a management system, mainly established by the university policy makers. Therefore, any evaluation system is constructed from a subjective perspective of managers [47]. Accordingly, it lacks the views and suggestions of the university scholars, easily leading to the scholars’ cognition bias of the evaluation system. Besides, university’s research evaluation system could be very complex and dynamic. However, the prior evaluation system of university research was only specialized for the quality [5], the quantity [7] of research, or impact factor [8] of researchers’ papers. That did not consider the everchanging process of evaluation system. This dynamic process cannot be reflected by these static indicators in a one-dimensional way. In addition to the insufficiency of prior research evaluation systems, no authoritative scale is available. Additionally, the relationship between the university research evaluation system and scholars’ empathy and willingness to innovate has not been discussed.

This study adopted a bottom-up approach to conduct the interviews with the university scholars, based on the background of “breaking the five focus” in China’s scientific academia. These interviews were from the perspective of Chinese university scientific research evaluation, expecting the university scientific research evaluation system to be more suitable for those university scholars. In addition, this study treats university research evaluation as a dynamic system and includes the research process into it. The sub-dimensions of scientific research process include project approval, execution, and acceptance, all of which make the evaluation system more dynamic and enhance the inclusiveness of the formulation process. This study, based on the developed university research evaluation system scale, infers the mechanism of the impact of the university research evaluation system on scholars’ empathy and willingness to innovate. It also deepens the intersection of two fields in evaluation systems and psychology.

This study is based on China’s national conditions to discuss the university research evaluation system. However, it is also possible to appreciate that prior scholars focusing on paper publishing, ranks gaining, professional titles, academic qualifications and awards is not the only occurring phenomenon in China. It is a relatively common research dilemma, which has greatly jeopardized the willingness of scholars to innovate throughout the country and across the world. It has slowed down the pace of improving the level of scientific research for human beings, that makes this study an important reference value for the world research reform.

8.3. Theoretical Implications

This study offers multiple theoretical implications. First, the current study has constructed a two-level theoretical framework for the scientific research evaluation system of universities. This enriches the theoretical horizon of the scientific research evaluation system of universities, promotes the integration of the new era background and the scientific research evaluation system of universities. This study systematically explored and evaluated the literature of the scientific research evaluation system in universities. It further analyzed the unique characteristics of the scientific research evaluation system in universities from the process and the result dimensions defining its connotation. Furthermore, targeted at university scholars, the two-level dimensions of university scientific research evaluation system were identified based on the grounded theory research method.

In comparison with the prior research, this paper extracts the two new dimensions of university research evaluation system based on the Chinese university scholars’ perspectives, scientific research process evaluation and input and output evaluation. Most previous studies developed the scientific research evaluation system of universities from the perspective of managers, while this study introduced the perspective of university scholars. It extracted the indicators of the scientific research evaluation system of universities through qualitative analysis of the interview data obtained from Chinese university scholars and online public data. It further analyzed the effect of the evaluation system on the empathy and innovation intention of scholars, highlighting the characteristics of group wisdom. Next, the current evaluation system mainly focuses on the quantity and quality of achievements, ignoring the effect of scientific research process evaluation and environmental factors on scientific research of university scholars. The interaction between university scholars and scientific research is an interactive process. The current study integrated the quantity, quality, environment, and scientific research process of the results to establish a complete scientific research evaluation system of universities. Which further reflects the core connotation of the scientific research evaluation system of universities in the new era.

Second, based on scholars’ perspective, the scale of university scientific research evaluation system with strong reliability and validity was developed. This provided a scientific, comprehensive, and accurate measurement tool for the evaluation system research. Simultaneously, it promotes the accurate use of educational investment in scientific research in colleges and universities. At present, the scale of university scientific research evaluation system is still under development. This study focused on the two-level characteristics of university scientific research evaluation system and developed the scale of university scientific research evaluation system. This was achieved through obtaining the interview data of Chinese university scholars and public data as the objects of the grounded research. Based on ensuring the integrity of the contents of the scale, it strengthened the close contact between university scholars and scientific research evaluation system. That makes the scale of scientific research evaluation system of universities more accurate and universal. Thus, the blind investment in scientific research, and education in colleges and universities in the past has been altered. As it plays an important role in sustainable development of knowledge. At the same time, it has an important reference significant for promoting the development of the research evaluation system of universities in the world.

Third, this study revealed the effect of the scientific research evaluation system on scholars’ empathy and innovation intention. That provides a deepened understanding of the cross research between the evaluation system and psychology promoting the full use of knowledge resources of university scholars. The study findings established a theoretical relationship model between the university scientific research evaluation system and scholars’ empathy and innovation intention. It empirically tested the effect of the university scientific research evaluation system on scholars’ empathy and innovation intention. The current results provide an empirical basis for accurately predicting the effect of university scientific research evaluation system on scholars’ empathy and innovation intention. They also provide a basis for prospective analysis of the contributing factors and promotion paths of scholars’ innovation intention from the perspective of university scientific research evaluation system. The evaluation system can simultaneously stimulate the empathy and innovation will of university scholars, leaving a positive impact on the research output of scholars. Thus, this fosters the utilization efficiency of university scholars’ knowledge resources.

Fourth, the current study adopted data-driven and theory-driven research paradigms. It not only considered the mixed research method of combining qualitative and quantitative methods in establishing the scale of the scientific research evaluation system of universities, but also used rich data sources and collected many topic text data for more accurate data analysis in the era of bigdata. This is helpful in the provision of new ideas to explore new paradigms of scale development and diversified research methods in the big data paradigm. Based on the classical scale development paradigm proposed by Mackenzie et al. (2011) [45], this study has contributed in different ways. First, from the theory-driven perspective, it integrated existing theories and literature science to define the theoretical domain of university scientific research evaluation theory. Then it formed a two-level dimension of university scientific research evaluation system from the data driven perspective to refine the dimension more in line with the research situation and theoretical aggregation. Second, this study considered the interview data of university scholars and online public data as the data sources for grounded research. Provided that, the qualitative materials are more abundant, diverse, and comprehensive, and more suitable for exploratory analysis.

8.4. Practical Implications

This study has the following practical implications. First, in the scientific research evaluation system, universities should integrate the dynamics of the interaction between scientific research and scholars and the scientific research environment. This would provide a deep understanding of the connotation of the scientific research evaluation system of universities in the present era. That mainly includes the scientific research process evaluation and input and output evaluation. The scientific research field pursues the basic scientific research results with the rapid development of science and technology. It further pays more attention to the quality, environment, and process of scientific research results.

Second, enterprises should reflect the concept of multidimensional scientific research management in scientific research evaluation. University administrators can evaluate and optimize scientific research achievements according to the complete scale of university scientific research evaluation system. They should stimulate the empathy and innovation intention of university scholars mobilizing their resources and building a virtuous cycle of the ecosystem including “university, scholars, and scientific research”.

Third, university administrators can promote and realize the quality reforms in the field of scientific research by using the evaluation system of university scientific research as the medium. Although universities have recognized the strategic significance of innovation intention. However, they still lack a clear idea of a specific path to promote scholars’ innovation intention. This study found the two dimensions of the university scientific research evaluation system, that significantly enhance the innovation intention of university scholars. Therefore, universities could promote the innovation intention of scholars from the process, input, and output dimensions in a bid to improve the competitiveness of scientific research of colleges and universities.

8.5. Deficiency and Prospect

With the strong scientific research reform, the scientific research evaluation system of universities is considering a dynamic change tendency. As a traditional measurement tool, the scale used in the current study was unable to capture the randomness and dynamics of the evaluation system. Future research can use other measurement methods (such as algorithms) to explore the evolution of the scientific research evaluation system in universities.