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Article

The Impact of Risk Perception Difference of Members of a Scientific Research Project Team on Information Adoption: The Moderating Effect of Knowledge Inertia

by
Haoyang Song
,
Jianhua Hou
,
Xiucai Yang
and
Yang Zhang
*
School of Information Management, Sun Yat-sen University, Guangzhou 510275, China
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(13), 7749; https://doi.org/10.3390/su14137749
Submission received: 13 May 2022 / Revised: 19 June 2022 / Accepted: 22 June 2022 / Published: 24 June 2022
(This article belongs to the Special Issue Sustainable Employee Management)
Browse Figures
Versions Notes

Abstract

:
A scientific research project is always full of uncertainties and risks. In this condition, full exchange and complementarity of information resources among project team members are necessary and important to meet the information needs for project risk management and even affect the success of the project. The differentiated risk perception of members with various professional backgrounds can contribute to the communication and complementary of the necessary information within the team. However, too much difference in perceptions of project risks may cause members’ information conflicts, which may hinder the adoption of various information and do harm to the risk management. Considering the limited research on this “contradictory” relationship, especially for the scientific research project team, a special group, this study explores the impact of the risk perception differences of the scientific research project team members on information adoption behavior through the large sample empirical statistical method. The results show the hat risk perception difference of members positively affects the learning willingness and information adoption behavior but does not show a negative effect, and there is no inverted U-shaped relationship. Further, learning willingness plays a mediating role between both, while learning inertia and experience inertia positively and negatively moderate the positive effects of risk perception differences on learning willingness, respectively. From the cognitive perspective, this study further reveals the internal influence mechanism of risk perception difference of scientific research project team members on information behavior and provides a theoretical reference for improving the efficiency of information communication and optimizing collaborative team management.

1. Introduction

The implementation of scientific research projects involves the characteristics of a long development cycle, high technical requirements, and complex development systems, and is full of many risk factors [1]. The understanding and judgment of scientific research project risk and its management is an important premise for carrying out scientific research innovation activities. It not only needs sufficient information exchange between members, but there are also more requirements through the understanding of mutual information, judgment, choice, and acceptance of a series of adoption behaviors to achieve the integration and utilization of team information and an effective response to the project risk. That is, scientific research collaboration is essentially the collaboration of information [2]. The team carries out the division of labor and cooperation around the scientific research tasks [3,4] and jointly solves the problems of scientific research projects through the flow of information and knowledge among members [5]. Correspondingly, in the face of various risks in the internal and external environment of the project, how to promote the exchange and adoption of information among members is an important topic of risk management practice and theoretical research in scientific research projects.
As a cognitive behavior, the motivation for information adoption originates from the subjective cognitive state [6]. Scientific research project team members often habitually adopt their own inherent research paradigms, problem epistemology, and solution methodology. Each member may have different judgments and attitudes towards the same risk in the face of a certain situation. This forms a differentiated risk perception and further affects the behavior and decision-making of the team members [7]. On the one hand, differentiated views contribute to the communication and complementary of diverse and rich information and then improve the comprehensive and systematic understanding of project risk and benefit project risk management performance. On the other hand, different understanding and ideas of project risks among team members may increase communication costs and hinder information communication, and even produce information conflicts. This is especially true when team members are used to sticking to their own ideas instead of being open to new ideas and knowledge. Existing studies on this “contradiction” have yet to have a thorough interpretation of the internal relationship mechanism between risk perception and information adoption, especially in the context of risk management of scientific research projects. Exploring the internal connection between the two can deeply reveal the formation and characteristics of information adoption behavior from the cognitive level, help to guide the information coordination in the scientific research project team, and improve the efficiency of scientific research and innovation.
Given the good explanation for the differentiated behavior and decision-making of individuals in the same situation, risk perception difference has been gradually applied in the fields of psychology, management, and other fields to study its impact on the behavioral decisions of various subjects, such as farmers [8,9], controllers [10,11], consumers [12,13], and doctors and patients [14], and its relationship to social elements such as commitment [15]. Scholars have also begun to integrate risk with cognitive concepts to reveal the laws of information behavior, such as the relationship between health risk perception and information behavior [16,17,18,19,20], user-perceived risk and network information search behavior [21], and mobile media network user’s risk perception and information search behavior [22]. In general, the information behavior research under the existing cognitive perspective is rich and gradually refined, which focuses on the behavioral characteristics and rules of subjects with special information needs. However, few studies have paid attention to the relationship between risk perception and information behavior of team members of a scientific research project.
The innovation advantages of a scientific research project team come from the integration of knowledge and information between individuals in multi-majors and fields. An individual’s desire for new knowledge and willingness to learn play an important role in this process. It is the internal factor connecting cognition and behavior [23] and constitutes the internal motivation for individual behavior. At the same time, the heterogeneous knowledge structure and the problem-solving tendency of researchers are reflected as the knowledge inertia of individuals; that is, an inertia characteristic at the cognitive level [24], which reflects the structure of individual knowledge resources, and has a complex and multi-directional influence on the individual consciousness, will, and even behavior [25,26,27,28,29]. Thus, the theory of knowledge inertia also provides new clues to reveal the relationship between risk perception and behavior.
Therefore, this study focuses on the risk management situation of scientific research projects and integrates organizational learning and knowledge inertia theory to analyze the impact of the risk perception differences of the project team members on their information adoption behavior. In theory, this study explores the relationship between risk perception difference and information adoption behavior and further reveals the role of learning willingness and knowledge inertia in view of the risk management situation of scientific research projects. In practice, our findings show that the risk management awareness of scientific research projects should be strengthened from the cognitive level. Actually, the information behavior of team members should be guided by two aspects: the improvement in learning willingness and the cultivation and supervision of knowledge inertia. Based on these, the innovation performance can be benefited through improving the coordination level of cognition and behavior of scientific research project team members.

2. Theoretical Basis and Research Assumptions

2.1. Risk Perception Difference and Information Adoption Behavior

Risk perception is a misnomer and not an abstract concept. Actually, it is the characteristics of risk sources that lead to feelings of danger or safety. This way, risk perception can be understood as the attitude and judgment of the subject towards the objective risks contained in the environment and is subjective. In a broad sense, it includes general assessment and response to the type of risk, probability of occurrence, and confidence in dealing with it [30]. Its formation is affected by many factors such as risk attributes, individual characteristics, psychological phenomena, social culture, etc. [31], and then it presents differences between individuals, that is, risk perception difference [32,33]. This study defines the differences in risk perception among team members of scientific research projects as the differences in attitudes and views among team members towards various risks in the process of project implementation. It stems from the differences in the knowledge base and cooperation goals among members of the scientific research project team [23], which are mainly due to the different understandings and judgments on risk issues such as project time, cost, and responsibility allocation [34]. From the perspective of the risk management process, it is manifested as cognitive differences in risk sources, probability of occurrence, degree of impact, and confidence in dealing with it. As a cognitive element, risk perception is the result of an individual’s judgment on the connotation and value of risk information and can further affect an individual’s behavior and preferences [35,36,37]. On the other hand, information adoption is a process in which the subject selects, evaluates, accepts, and utilizes information purposefully [38]. It connects information seeking, selection, retrieval, and utilization and is embodied as an information adoption behavior to achieve information acceptance, judgment, selection, decision-making, and acceptance [39]. In this process, the subject’s perception of information becomes the key to influencing its adoption behavior. Especially in scientific research projects, members selectively pay attention to the risk factors and events, which are considered important based on their own self-judgment of project risk information, and thereby form differentiated attitudes and judgments.
Perception difference is the embodiment of group cognitive diversity, which helps to generate creative friction and avoid collective consensus thinking. Then, this subjective perception can stimulate the exchange and cooperation of scientific researchers with different professional backgrounds and heterogeneous knowledge and effectively promote the exchange of information between individuals [40]. This is also the opportunity for the scientific research project team to solve scientific research problems and achieve innovation. Especially in the context of scientific research project risks, when members realize that they have different attitudes, ideas, and judgments about project risks and their management, they will have more uncertainty and fall into a state of chaos [41]. In order to effectively solve potential problems and smoothly advance the project process, team members will generate new information needs, actively search for information [42], and realize the interaction of knowledge and information in different fields and professions through more and deeper communication [42]. This will form complementary or supplementary knowledge and information interaction among members to eliminate the sense of incongruity between them and restore the balance of cognition [3]. Then, the project risk information and methods of risk management can be enriched, which promotes the in-depth processing of information among team members [43,44]. On the basis of mutual adoption of risk information, team members can more comprehensively identify potential risks, accurately assess the probability of risks and influence, and generate new ideas and new programs [43]. This way, the increase in risk perception difference may lead to more communication of information among team members and promote information adoption behavior to deal with project risks.
However, excessive perception difference may lead to cognitive gaps among members, which is not conducive to the exchange and in-depth processing of information between individuals [44]. Only moderate perception difference is conducive to promoting individual cooperation [45]. Similarly, too large a difference in risk perceptions is likely to intensify the heterogeneity of information among members, making it difficult to reach a consensus on team cognition and actions. This way, excessive perception difference may form information opposition or even conflict among members, inhibiting individual communication willingness and cooperation atmosphere on risk issues [46]. This is not conducive to the understanding and adoption of each other’s information. In other words, when the risk perception difference exceeds a certain range, it may cause negative effects on information adoption behavior. Therefore, this study proposes the following hypothesis:
Hypothesis 1.
There is an inverted U-shaped relationship between the risk perception difference of scientific research project team members and their information adoption behaviors.

2.2. Mediation Role of Learning Willingness

Scientific research teams usually gather members with diverse and specialized knowledge. The exchanges and learning of different knowledge among members are the norm for teams to carry out innovation activities and the basis for team innovation. Conflicts among members caused by perception difference will activate the process of balancing cognition, and thereby promote individual participation in learning and collaborative knowledge construction, which can stimulate individuals’ willingness to learn [40]. When faced with viewpoints that are different from their own judgments, in order to solve project problems and achieve the innovative tasks of scientific research projects, team members will conduct discussions and exchange activities around project risks and their management and perfect their own judgment on project risk information. However, the differences in risk perception are fundamentally due to the differences in the individual cognitive structures of members. Individuals’ judgment and selection of information are expressed in the form of cognitive structure matching and concept matching. Individuals are more inclined to choose information that is more compatible with their own cognitive structure [39]. If the risk perception difference among members is too large, it probably means that the cognitive structure among members is too different. At this time, members are more insistent on their own judgments rather than learning and understanding opposing viewpoints and ideas. Therefore, this study proposes the following hypothesis:
Hypothesis 2.
There is an inverted U-shaped relationship between perception difference of scientific research project team members and their learning willingness.
In scientific research projects, team members need to parse information from the “noisy” project environment, and judge, select, and process effective information. As the recipients of different cognitive concepts and ideas, the improvement in team members’ willingness to learn will help them understand different perceptions, thereby realizing the transformation and optimization of their own knowledge and cognitive structure [47], which is conducive to innovation [48,49] and is more likely to demonstrate adoptive behavior. On the contrary, if the individual’s willingness to learn is insufficient, it is easy to cause negative emotions in the process of information reception and digestion, resulting in the failure of knowledge or information transfer [23]. Then, team members will adhere to the inherent concept, and refuse to accept new information. Therefore, this study proposes the following hypotheses:
Hypothesis 3.
The learning willingness of the scientific research project team members positively affects their information adoption behavior.
Hypothesis 4.
The learning willingness of the scientific research project team members plays a mediation role between risk perception difference and information adoption behavior.

2.3. Moderation Role of Knowledge Inertia

Knowledge inertia refers to the tendency of the individual to use habitual problem-solving procedures, familiar sources of knowledge, past experience or knowledge to solve new problems [50]. This tendency keeps the knowledge system in its original state, and thus generates inertial problem-handling procedures, experiences, and thinking patterns, which form the thinking habits derived from the individual’s cognition and learning methods. It mainly includes two dimensions: learning inertia and experience inertia. Learning inertia refers to the tendency to learn new methods and knowledge to solve problems and break the constraints of inertial thinking when using knowledge to solve problems [51]; experience inertia refers to adopting existing knowledge, experience, procedures, and resources when facing new situations or problems to be processed [25,52].
On the one hand, learning inertia reflects the thinking habit of team members to actively explore new knowledge and methods. Members with a higher level of learning inertia are more willing to take the initiative to understand different viewpoints, which helps to stimulate their inner willingness to learn [50]. Especially when there are differences in risk perception among team members, a high level of learning inertia can encourage members to actively communicate and learn and integrate knowledge and information to solve project risk problems [26]; that is, to positively regulate the positive relationship between risk perception difference and learning willingness. On the other hand, the existence of experience inertia will make team members no longer willing to carry out innovative activities and reject the absorption and learning of new knowledge. This cautious approach to change further strengthens inertial cognition and forms a vicious circle. Thus, when the members of the scientific research project have strong experience inertia, they will stick to their existing judgments. Even if there is a certain risk perception difference from others, they still rely on past experience to take actions and are unwilling to take the initiative to learn and understand others’ ideas, which hinders communication with each other. Conversely, members with weaker experience inertia are more likely to receive and understand different concepts and new knowledge. This way, the experience inertia positively regulates the positive relationship between risk perception difference and learning willingness. Therefore, this study proposes the following hypotheses:
Hypothesis 5a.
Learning inertia of scientific research project team members positively plays a moderation role between risk perception difference and learning willingness.
Hypothesis 5b.
Experience inertia of scientific research project team members negatively plays a moderation role between risk perception difference and learning willingness.
In conclusion, this study constructs the relationship between risk perception difference and information adoption behavior of the scientific research project team members based on the theories of risk perception difference, information adoption, knowledge inertia, and organizational learning, as shown in Figure 1.

3. Method

3.1. Participants

Combined with the characteristics of research objective and scientific research project, this study designed a structured questionnaire (paper and electronic), and conducted anonymous surveys with researchers (masters, doctors, lecturers, associate professors, professors, etc.). The respondents were asked to answer questions based on their recent research project experiences. This survey process began in early November 2020 and was completed at the end of March 2021, which lasted nearly 5 months. A total of 700 questionnaires were distributed, and 583 were recovered. After removing the invalid and substandard samples, we finally had 412 valid questionnaires and reached an efficiency of 71%. The basic information of samples is shown in Table 1, with more men (55%), mainly 30–35 (161), 35–40 (132) years old, most of whom have obtained a Master’s (161) and Doctorate degrees (144) and participated in 3–5 (173) or 6–10 (165) scientific research projects. Meanwhile, most participants were selected from eight research fields, which all are the scientific research fields with rapid development in China. The number of respondents in each field was basically similar to ensure the balance of sample distribution. The research samples were reasonable and represented the main groups engaged in scientific research projects.

3.2. Procedure

This study adopted the method of large-sample statistical empirical research, obtained sample data by means of a questionnaire survey, and used SPSS24.0 and Amos7.0 software to carry out regression model analysis to test the proposed hypothesis model. Based on the above samples and scale tools, we first completed the reliability and validity analysis of the scale, and the results are shown in Table 2. After that, hierarchical regression analysis was used to test the proposed hypothesis model, and the results are shown in Table 3. The Johnson–Neyman technique was used to map the corresponding moderation effect, to reveal the conditional effect of knowledge inertia, as shown in Figure 2 and Figure 3.

3.3. Instrument

This study involved four core variables. Their measurement tools were developed or adjusted and revised based on existing research results, and Five-point Likert scale tools were designed. Most studies mainly developed and used the measurement scales of risk perception, and few studies focused on the degree of difference in risk perception. Thus, based on risk perception and cognitive difference theory [34,53], and combined with the characteristics of project risk and research team, the measurement scale of risk perception difference was designed from four aspects: risk source, occurrence probability, impact degree, and coping confidence, with 12 items in total. Items mainly measure the degree of difference in risk perception according to the above four core contents of project risk management. Based on the existing relevant scales [38,54,55], the measurement scale of information adoption behavior was adjusted and revised to measure the tendency and external characteristics of scientific research project team members, with a total of 4 items. Learning willingness refers to the study of Lv [56], and the learning interest tendency of scientific research project team members was measured, including a total of 4 items. Last, the two-dimensional scale of knowledge inertia was designed based on the study of Liao, Fei, and Liu [25]. However, their scales measure the knowledge inertia from three aspects: routine problem-solving procedures, stagnant sources for new knowledge, and following past knowledge or experience, which does not divide the dimensions of knowledge inertia. Furthermore, their scales included too many items with similar meanings which may be difficult to answer. Thus, based on the definitions of learning and experience inertia, we designed a new two-dimensional scale of knowledge, including 10 items in total. Among them, there were 2 items from routine problem-solving procedures, 5 items from stagnant sources for new knowledge, and 3 items from following past knowledge or experience in the study of Liao, Fei, and Liu [25]. Moreover, the 10 items were adjusted and revised to be suitable for scientific research project team members, which avoided too similar meanings while ensuring the measurement range.

3.4. Data Analysis

3.4.1. Reliability Analysis

The internal consistency index of each variable scale, Cronbach’s alpha coefficient, was calculated (Appendix A). The Cronbach’s alpha values of the four sub-dimensions of risk perception difference were 0.869, 0.812, 0.851, and 0.850, respectively. The overall Cronbach’s alpha value was 0.827. The Cronbach’s α values of learning and experience inertia were 0.855 and 0.850, respectively, and the overall one of knowledge inertia was 0.731. The Cronbach’s α value of learning willingness was 0.907, and the Cronbach’s α value of information adoption was 0.941. Meanwhile, the Cronbach’s α value of each item after deleting any item in each variable was smaller, and the Corrected Item-Total Correlation (CITC) of all items was much larger than the standard of 0.5. This indicated that all variable measurement scales had reached a reasonable level of reliability.

3.4.2. Validity Analysis

Since most of the scales in this study were derived from appropriate adjustments to mature scales, they had good content validity. Therefore, this study focused on testing convergent validity and discriminant validity. First, exploratory factor analysis was performed on each variable scale and the whole. The results showed that there were four extracted factors (KMO = 0.801, Bartlett’s test = 2255.901, p = 0.000), corresponding to risk source, risk probability, risk impact, and risk response as four sub-dimensions; knowledge inertia (KMO = 0.830, Bartlett’s test = 1685.530, p = 0.000) can be extracted into two factors, corresponding to learning inertia and experience inertia respectively; learning willingness (KMO = 0.840, Bartlett’s test = 1064.147, p = 0.000) and information adoption behavior (KMO = 0.867, Bartlett’s test = 1486.300, p = 0.000) can be extracted into one factor, respectively. Moreover, through extracting factors for all variable items, a total of eight common factors (KMO = 0.891, Bartlett’s test = 7301.052, p = 0.000) were obtained, corresponding to the four variables and their dimensions, respectively. Further, the loading coefficients of the items of each variable on the measured factors were all greater than the standard of 0.5, and there was no cross-loading phenomenon, indicating that the scales of each variable had good convergent and discriminant validity.
Second, AMOS software was used to carry out confirmatory factor analysis. On this basis, the structural validity of the scale was further analyzed by calculating the combined reliability (CR) and the average variable extraction (AVE), as shown in Table 2. The combined reliability of each variable was 0.957 (RPD), 0.855 (LI), 0.850 (EI), 0.907 (LW), and 0.941 (IA), which were all greater than the critical value of 0.70; the AVE values were 0.648 (RPD), 0.541 (LI), 0.632 (EI), 0.709 (LW), and 0.800 (IA), which were all greater than the critical value of 0.50, and the square root of the AVE values was greater than the correlation coefficients with other latent variables. Meanwhile, the factor loadings of each observed variable also significantly met the relevant test criteria. In conclusion, each variable in this study had good convergent validity, discriminant validity, and construct validity.
Table
Table 2. Maximum/minimum value, mean value, CR, AVE and its square root, and correlation coefficient of each latent variable.
Table 2. Maximum/minimum value, mean value, CR, AVE and its square root, and correlation coefficient of each latent variable.
VariableMinMaxMeanCRAVERPDLIEILWIA
RPD1.584.583.810.9570.6480.805
LI1.205.003.650.8550.5410.253 **0.736
EI1.205.002.630.8500.632−0.124 *−0.0710.795
LW1.255.003.820.9070.7090.512 **0.388 **−0.288 **0.842
IA1.005.003.590.9410.8000.528 **0.321 **−0.340 **0.694 **0.895
Note: The diagonal elements (i.e., bold values) are the square roots of AVEs. Unadjusted correlations appear below the diagonal. ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).

4. Results

4.1. Correlation and Collinearity Analysis

From the correlation results of each variable, it can be seen that risk perception difference was positively correlated with learning willingness (r = 0.512, p < 0.05) and information adoption behavior (r = 0.528, p < 0.05); learning willingness and information adoption behavior were positively correlated (r = 0.694, p < 0.05); learning inertia and experience inertia were positively (r = 0.388, p < 0.05) and negatively (r = 0.321, p < 0.05) correlated with learning willingness, respectively. Therefore, it can be preliminarily judged that the models and assumptions of this study were reasonable to a certain extent.
In this study, the independent variables and the moderation variables were centralized, and the square term of the independent variables and the interaction terms of the two were constructed. On this basis, hierarchical regression analysis was performed on the sample data according to the hypotheses to test Models 1–10. The results are shown in Table 3. Meanwhile, the variance inflation factor (VIF) diagnosis was performed when analyzing each model. The results showed that the VIF value of each model was lower than 3.0, and there was no serious collinearity problem.
Table
Table 3. Hierarchical regression analysis results.
Table 3. Hierarchical regression analysis results.
Dependent VariableIALW
ModelsModel 1Model 2Model 3Model 4Model 5Model 6Model 7Model 8Model 9Model 10
Control Variable
Age0.0680.059−0.017−0.0060.0460.0980.0910.0970.0840.083
Education−0.015−0.0660.0710.034−0.060−0.099−0.139−0.125−0.142−0.135
Experience0.001−0.013−0.013−0.017−0.0050.0160.0050.0090.0090.010
Independent Variable
RPD 1.177 *** 0.511 ***1.569 *** 0.923 ***0.891 ***0.958 ***1.166 ***
RPD2 0.361 *** 0.223 **
Mediation Variable
LW 0.871 ***0.721 ***
Moderation Variable
LI 0.333 ***
EI −0.312 ***
Moderation Effect
RPD x LI 0.459 **
RPD x EI −0.617 ***
R20.0030.2820.4840.5220.3080.0110.2780.3590.3590.294
Adjusted R2−0.0040.2750.4790.5160.2990.0030.2710.3500.3490.285
F Change0.397158.099 ***379.333 ***220.746 ***89.375 ***1.471150.974 ***73.471 ***73.346 ***81.379 ***
D-Wtest1.5371.4811.3901.4091.4731.4811.3761.2631.3061.352
Note: *** Correlation is significant at the 0.001 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed).
Furthermore, Models 1 and 5 respectively reflect the relationship between control variables and information adoption behavior and learning willingness. The results showed that there was no significant causal relationship between control variables and independent variables and mediation variables.

4.2. The Influence of Risk Perception Difference

Comparing the results of Model 2 and Model 5, risk perception difference and its square term had a significant positive impact on information adoption behavior. Thus, risk perception difference only played a positive role in both, and Hypothesis 1 failed the test. Likely, the regression results of Model 7 and Model 10 showed that risk perception difference had a significant positive impact on learning willingness (β = 0.923, p < 0.001), and Hypothesis 2 failed the test.

4.3. The Mediation Effect of Learning Willingness

The results of Models 2 and 3 showed that both risk perception difference and learning willingness had a significant positive and direct impact on information adoption behavior (β = 1.177, p < 0.001; β = 0.871, p < 0.001), and Hypothesis 3 passed the test. Further, combined with the results of Model 4, its R2 and the adjusted R2 were significantly improved compared with the ones of Model 2, and the explanatory power of Model 4 was stronger. Although the impact of risk perception difference was still significant, its regression coefficient was decreased compared with Model 2 (β = 0.511, p < 0.001). This indicates that learning willingness played a partial mediating role between risk perception difference and information adoption behavior, and Hypothesis 4 passed the test.

4.4. The Moderation Effect of Knowledge Inertia

On the basis of Model 7, learning inertia, experience inertia, and their interaction terms were added to form Models 8 and 9. The results showed that compared with Model 7, the R2 and adjusted R2 of Models 8 and 9 were significantly improved, and the latter two had stronger explanations. At the same time, learning inertia can positively moderate the relationship between risk perception difference and learning willingness, while experience inertia negatively moderates the relationship between risk perception difference and learning willingness. Hypotheses 5a and 5b passed the test.
To quantify the conditional effect of knowledge inertia on risk perception difference and learning willingness and test the statistically significant interval of the effect, the Johnson–Neyman technique was used to map the corresponding moderation effect, as shown in Figure 2 and Figure 3. The results showed that when learning inertia exceeded −1.048, the conditional effect interval of risk perception difference on learning willingness (LLCI = 0.000, ULCI = 0.696) did not include 0, which indicated that risk perception difference had a significant positive effect on learning willingness. Conversely, there was no significant positive effect. That is, when the learning inertia exceeds −1.048, it plays a positive moderation role between risk perception difference and learning willingness. Similarly, when the experience inertia was less than 1.0377, the conditional effect interval of risk perception difference on learning willingness (LLCI = 0.000, ULCI = 0.592) did not contain 0, indicating that risk perception difference had a significant positive effect on learning willingness. Conversely, there was no significant positive effect. That is, when the experience inertia is less than 1.0377, it plays a negative moderation role between risk perception difference and learning willingness.

5. Discussion

The positive impact of risk perception difference of scientific research project team members on learning willingness and information adoption behavior was verified, which is consistent with the study of Chen, Liu, and Zhang [44], further revealing the positive role of perception difference for learning willingness and information adoption behavior. However, there was no significant inverted U-type relationship between them; that is, Hypotheses 1 and 2 failed the tests. This result is not consistent with the studies of Chen, Liu, and Zhang [44], Liang, Li, Lu, Kim, and Na [57], and Moskaliuk, Kimmerle, and Cress [45]. There are two reasons for this. First, the scientific research project team is composed of knowledge-based personnel with high education and professional knowledge background [5]. The heterogeneity of goals, knowledge, information, concepts, etc., is the core advantage of such a team. It is the basis and premise of integrating multiple knowledge and professional advantages, carrying out knowledge and technology exchanges and complementary [40] and collaborative innovation. The learning and acquisition of new knowledge and information are not only the task needs of team members but also the internal driving needs of members to achieve self-growth [42], especially learning from colleagues is an important way for knowledge workers to improve their own abilities [58]. Therefore, even in the face of large risk perception difference, there is no decrease in team members’ willingness to learn and information adoption behavior. Second, the establishment of the team is on the premise of ensuring the project implementation and meeting the project needs. Although the scientific research project team has cross-field and cross-professional characteristics, in order to carry out cooperation, there are certain consensus or similarities in strategic consensus, collective responsibility, and sub-groups [3,59,60,61]. The differences in risk perception among the research project team members may not reach the threshold for causing negative effects and may not reach the significance of the data test results. Therefore, due to the characteristics of the scientific research project team and its members, the increase in risk perception difference may not cause a decrease in their learning willingness or information adoption behavior. This also verifies that it is necessary to consider the characteristics of the research objective and situation when studying the relationship between cognition and behavior.
Further, Hypotheses 3, 4, 5 all passed the tests. Among them, the improvement in the learning willingness of the scientific research project team members is conducive to promoting the members’ information adoption behavior, indicating that the learning and acquisition of new knowledge and information can stimulate the individual information adoption behavior [48,49], and realize the learning and information interaction of individuals and teams as a whole [62]. At the same time, learning willingness plays a mediating role between risk perception difference and information adoption behavior, which is consistent with the relevant results of social cognitive theory. This once again showed that individual psychological factors are the key link connecting their cognition and behavior [63,64]. Meanwhile, it also further revealed the internal influence process of risk perception difference on behavior [35,36,37]. That is, the differentiated perceptions can positively stimulate the subject’s learning willingness, and then promote the formation of information adoption behavior, which deepens the current research on the effect of risk perception difference.
Moreover, knowledge inertia played an important moderation role in the relationship between risk perception difference and learning willingness, which once again validates the complex influence of knowledge inertia on willingness [25,53,65]. Among them, the improvement in learning inertia helps to play a positive role in risk perception difference and further strengthens its positive value to the learning willingness [51]. That is when researchers have a high level of learning inertia, the expansion of risk perception difference can more effectively stimulate their internal learning motivation and strengthen the willingness to acquire new knowledge [26,50], On the contrary to experience inertia, the fixation on previous knowledge and experience will reduce the positive effect of risk perception difference on learning willingness. That is, the members of the scientific research project team with high experience inertia do not have a strong motivation to learn from others [52], even if they have realized the differences in ideas.
In a word, the existence of learning inertia can significantly strengthen the positive effect, and further promote the learning willingness stimulated by risk perception difference and the adoption of knowledge and information. Although experience inertia helps improve the efficiency of problem-solving, it suppresses the positive effect of risk perception difference on learning willingness, hinders the stimulation and cultivation of learning willingness, and limits the interaction between members of new knowledge and information. Therefore, it was shown that the existence of inertia can cause bad results. Furthermore, learning inertia and experience inertia can play the exact opposite role, respectively. Specifically, constructing and perfecting knowledge inertia, can have a positive influence on learning inertia, reduce the rigid and negative effect of empirical inertia, and then promote the positive development of will and even behavior from the cognitive level. This result also deepens the research on the role of knowledge inertia.
For scientific research project teams, this study verified the risk perception difference in information adoption behavior and learning willingness, instead of the inverted U-shaped relationship. This way, the “contradictory” relationship is further clarified, and it also revealed the importance of context and object characteristics to the relationship between variables. Moreover, the positive effect of learning willingness on information adopt behavior was further confirmed, and the differential influence of different dimensions of knowledge inertia was also revealed.

6. Conclusions

Scientific research project risk management is specific to the cognitive object and fits the characteristics of high risk. This study focused on this situation to explore the influence of risk perception difference of project team members on internal information adoption behavior from the cognitive perspective. It not only revealed the mediation role of learning willingness but analyzed the impact of the experience inertia and learning inertia on the relationship between risk perception difference and learning willingness. The results showed that in the risk management situations of scientific research projects and teams, differences in members’ risk perceptions positively affect team members’ willingness to learn and information adoption behavior. It did not show an inverted U-shaped effect on the latter. Members’ willingness to learn plays an important mediation role between risk perception difference and information adoption behavior and positively affects information adoption behavior. Knowledge inertia plays an important role in the relationship between risk perception difference and information adoption behavior. Its complexity is reflected in the multi-directional effects; that is, learning inertia helps to strengthen the positive influence, while experience inertia plays a negative moderating effect.

6.1. Theoretical Contribution

This study indicated that different views, attitudes, and judgments will cause the formation of an information “imbalance” state, which stimulates members’ learning willingness, and promotes more frequent and close knowledge and information communication. This way, the heterogeneous professional background, knowledge, and information among scientific research project members play an important role, and indeed are the advantage of this type of team to deal with risk management. Meanwhile, due to the characteristics of knowledge-based employees and the particularity of innovation activity needs, risk perception difference did not have a negative impact on learning willingness and information adoption behavior. This revealed the uniqueness of information adoption behavior and improved the effectiveness and pertinence of research conclusions. Furthermore, based on the theory of social cognition, this study further analyzed the pre-cognitive factors of information exchange and adoption among the scientific research project team members and explored the important factors between cognition and behavior in the project risk management situation, namely learning willingness. This further revealed the mechanism of the internal relationship between cognition, willingness, and behavior at individual levels, and enriched the related theoretical research. Last, based on the theory of knowledge inertia, we further analyzed the positive and negative moderation effects of learning and experience inertia on the relationship between risk perception difference and learning willingness. This revealed the influence of knowledge inertia, an important cognitive factor, by focusing on the characteristics of knowledge and the research paradigm of research team members and promoted the integration of knowledge inertia theory and the deepening of research.

6.2. Practical Contribution

Based on the conclusions of this study, several suggestions can be provided for the effective exchange, adoption, and management of information among scientific research project team members. On the one hand, the positive impact of risk perception difference of the scientific research project team members on learning willingness and information behavior shows that by moderately expanding the risk perception difference of the members, the internal learning drivers of the members can be stimulated, and the information communication and adoption behavior can be promoted. For example, in terms of team formation, we can build the basis of risk perception difference by expanding the heterogeneity of professionalism, culture and project experience; in terms of the team operation, building formal and informal learning channels can support the value of the members’ learning willingness, and create a free team atmosphere to ensure the efficient evolution from “unbalanced” to “balance” information among members. Meanwhile, as for the team leader, it is necessary to properly introduce heterogeneous knowledge and information from outside or various risk factors and information, so as to continuously reshape the knowledge structure of members and ensure that risk perception differences among members can be maintained at a certain level.
On the other hand, the multi-directional moderation effects of the knowledge inertia of scientific research project team members showed that the formation and cultivation of learning willingness can be better promoted through the cultivation of learning inertia and inhibition of experience inertia. For example, we can create a continuous learning team culture, build channels and platforms to obtain new knowledge and new information to shape the learning inertia of research project team members. Moreover, constructing a team interactive memory system, shared mental models, and other team cognitive foundations, can also reduce the adverse impact of experience inertia, and avoid the solidification of experience knowledge and behavior. Especially in the process of project risk management, team learning can be formed by encouraging members to constantly contact and learn new knowledge, so as to better identify the types and sources of risks and develop corresponding solutions. On the contrary, although previous experience and knowledge are valuable, new uncertainties and risks in the project require members to keep a learning attitude rather than completely borrowing the knowledge base of the past. Thus, therefore, it is necessary to encourage members to contact new information and change their original thinking.

6.3. Research Limitations

Aimed at the particularity of scientific research project teams and their members, this study focused on project risk management situations to explore the impact of risk perception difference on information adoption behavior and revealed the mediating and moderating effects of learning willingness and knowledge inertia, respectively. There are certain limitations: (1) This study did not confirm the inverted U-type effect of risk perception on willingness and behavior. Although the underlying reasons were analyzed, further research is still needed, and the findings can be further corroborated by the comparison of samples of different research subjects; (2) In the aspect of sample collection, due to the limitations of time, financial resources and ability, this study mainly focused on young researchers with experience in less than 10 projects, but there is no restriction on the cross-field and cross-professional level of the project. Further studies may refine the sample types and the project experience of the respondents in order to achieve a deeper theoretical excavation.

Author Contributions

Conceptualization, H.S.; methodology, H.S.; formal analysis, H.S. and X.Y.; investigation, X.Y.; resources, H.S. and Y.Z.; data curation, H.S. and X.Y.; writing—original draft preparation, H.S.; writing—review and editing, J.H.; project administration, H.S.; funding acquisition, H.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Natural Science Foundation of China [grant number: 72104256], the 68th General Program of China Postdoctoral Science Foundation [grant number: 2020M683150], and the Youth Project of Philosophy and Social Sciences of Guangdong Province, China [grant number: GD21YTS02].

Institutional Review Board Statement

In this study, all subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki. However, in China, there is no mandatory requirement for relevant research to be conducted and approved by the Ethics Committee. Meanwhile, the relevant Ethics Committee department does not issue a formal approval document. Therefore, the ethics statements can only be expressed through the authors’ relevant statements. We confirm that all participants in the study were clearly and accurately informed about how the data were used before receiving the questionnaire survey, and they agreed to participate in the research process.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Not applicable.

Acknowledgments

Special thanks also go to the respondents who volunteered to answer the questionnaires.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. The reliability metric analysis of each variable scale.
Table A1. The reliability metric analysis of each variable scale.
Variables and Their QuestionsCITCStandardized
Factor Load		Cronbach’s α
Risk perception difference0.827
RS1 Our understandings of the time required for the project are widely inconsistent.0.7680.8540.869
RS2 We disagree widely on the adequacy of the project funds.0.7640.856
RS3 We have large different views on the reasonability of project scope.0.7150.78
RP1 Our understandings of the likelihood of time risk occurring are inconsistent.0.6760.7730.812
RP2 Our understandings of the likelihood of capital risk occurring are inconsistent.0.6570.775
RP3 Our understandings of the likelihood of project scope risk occurring are inconsistent.0.6550.757
RI1 We have a large gap in judging the impact of project time risk.0.7240.8190.851
RI2 We have a large gap in judging the impact of project capital risk.0.7100.797
RI3 We have a large gap in judging the impact of project scope risk.0.7280.814
RR1 Our understandings of time risk response are widely divergent.0.7300.8260.850
RR2 Our understandings of funding risk response are widely divergent.0.7160.805
RR3 Our understandings of scope risk response are widely divergent.0.7140.797
Knowledge inertia0.731
Learning inertia
LI The team does not give me the opportunity to learn new concepts and methods.0.6990.7710.855
LI2 I won’t use new methods to solve the new problems.0.6530.716
LI3 I will not try to learn new ideas to change my original ideas and behavior.0.6460.718
LI4 I will not actively seek new sources of knowledge.0.6500.712
LI5 I do not need to learn new knowledge and experience in this project.0.6920.761
Experience inertia
EI1 I am used to turning to the same resource for new knowledge.0.6890.7660.850
EI2 I am very dependent on my past knowledge and experience.0.6170.671
EI3 The past knowledge and experience affect my acceptance of new knowledge.0.6650.748
EI4 The past knowledge and experience can improve my productivity.0.6450.704
EI5 I will solve the same problem in the same way.0.6810.754
Learning willingness0.907
LW1 I am always interested in the knowledge or views of the other members.0.8140.877
LW2 I always take the initiative to learn from the other members.0.7640.804
LW3 I would like to invest my time in learning from other members.0.7790.823
LW4 It is my habit to learn from others.0.7990.861
Information adoption behavior0.941
IA1 I often accept suggestions or ideas from other members.0.8740.911
IA2 I often learn from the knowledge and methods of other members.0.8560.887
IA3 I always agree with the views or ideas of the other members.0.8670.903
IA4 The views of the other members can always inspire me.0.8420.877

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Figure 1. The hypothesis models.
Figure 1. The hypothesis models.
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Figure 2. The positive moderating effect of learning inertia on the relationship between risk perception difference and learning willingness.
Figure 2. The positive moderating effect of learning inertia on the relationship between risk perception difference and learning willingness.
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Figure 3. The negative moderating effect of experiential inertia on the relationship between risk perception difference and learning willingness.
Figure 3. The negative moderating effect of experiential inertia on the relationship between risk perception difference and learning willingness.
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Table
Table 1. Sample Basic Information Table.
Table 1. Sample Basic Information Table.
ItemClassValueNumberPercentageMeanVariance
MaleMan122755%0.5510.248
Woman018545%
Age≤30 years old17418%2.3590.810
>30 years old and ≤35 years old216139%
>35 years old and ≤40 years old313232%
>40 years old44511%
Academic degreeBachelor15814%2.4470.768
Master’s216139%
Doctor314435%
Post-Doctoral44912%
Number of projects participated in≤21338%2.5190.610
3–5217342%
6–10 316540%
≥1144110%
Research FieldsClinical medicine15213%——
Biological sciences25513%
Astronomy35513%
Physics44411%
Chemical55814%
Computer and Engineering64711%
The social sciences75112%
Economics and Business84210%
Others982%
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Song, H.; Hou, J.; Yang, X.; Zhang, Y. The Impact of Risk Perception Difference of Members of a Scientific Research Project Team on Information Adoption: The Moderating Effect of Knowledge Inertia. Sustainability 2022, 14, 7749. https://doi.org/10.3390/su14137749

AMA Style

Song H, Hou J, Yang X, Zhang Y. The Impact of Risk Perception Difference of Members of a Scientific Research Project Team on Information Adoption: The Moderating Effect of Knowledge Inertia. Sustainability. 2022; 14(13):7749. https://doi.org/10.3390/su14137749

Chicago/Turabian Style

Song, Haoyang, Jianhua Hou, Xiucai Yang, and Yang Zhang. 2022. "The Impact of Risk Perception Difference of Members of a Scientific Research Project Team on Information Adoption: The Moderating Effect of Knowledge Inertia" Sustainability 14, no. 13: 7749. https://doi.org/10.3390/su14137749

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