Entrepreneurial intention: Creativity, entrepreneurship, and university support

Anjum, Temoor; Muhammad Farrukh; Heidler, Petra; Díaz Tautiva, Julián Andres Article Entrepreneurial intention: Creativity, entrepreneurship, and university support Journal of Open Innovation: Technology, Market, and Complexity Provided in Cooperation with: Society of Open Innovation: Technology, Market, and Complexity (SOItmC) Suggested Citation: Anjum, Temoor; Muhammad Farrukh; Heidler, Petra; Díaz Tautiva, Julián Andres (2021) : Entrepreneurial intention: Creativity, entrepreneurship, and university support, Journal of Open Innovation: Technology, Market, and Complexity, ISSN 2199-8531, MDPI, Basel, Vol. 7, Iss. 1, pp. 1-13, https://doi.org/10.3390/joitmc7010011 This Version is available at: https://hdl.handle.net/10419/241596 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Journal of Open Innovation: Technology, Market, and Complexity Article Entrepreneurial Intention: Creativity, Entrepreneurship, and University Support Temoor Anjum 1,2,* , Muhammad Farrukh 2,3 , Petra Heidler 4,* and Julián Andres Díaz Tautiva 5   Citation: Anjum, T.; Farrukh, M.; Heidler, P.; Díaz Tautiva, J.A. Entrepreneurial Intention: Creativity, Entrepreneurship, and University Support. J. Open Innov. Technol. Mark. Complex. 2021,7, 11. https://doi.org/ 10.3390/joitmc7010011 Received: 30 November 2020 Accepted: 28 December 2020 Published: 31 December 2020 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Center of Post-Graduate Studies, Limkokwing University of Creative Technology Cyberjaya, Selangor 63000, Malaysia 2Faculty of Management Sciences, Department of Business Administration, LIMA University, Karachi 75190, Pakistan; [email protected] 3School of Management and Economics, Beijing Institute of Technology, Beijing 100080, China 4Department of International Business and Export Management, IMC University of Applied Sciences Krems, 3500 Krems an der Donau, Austria 5Facultad de Economía y Negocios, Universidad Del Desarrollo, Santiago 7610658, Chile; [email protected] *Correspondence: [email protected] (T.A.); [email protected] (P.H.) Abstract: To study the impact of perceived creativity disposition on entrepreneurial attitude and intentions, based on the theory of planned behavior, a model of the relationship between perceived creativity disposition and entrepreneurial intentions and attitude was constructed, relevant hypotheses were proposed, and the moderation mechanism of perception of university support on perceived creativity disposition and entrepreneurial intentions was also developed and analyzed. The study population included university business students in Pakistan. A sample of 330 students was selected from eight universities in Lahore and Islamabad, Pakistan. A random stratified sampling technique was executed. For this study, a cross-sectional and quantitative research design was used based on the survey process. The two-part questionnaire was used for data collection. Smart-PLS software version 3.2.7 was used to assess the hypothesis of this study. It was found that perceived creativity disposition and attitude toward entrepreneurship has a positive influence on entrepreneurial intention. It was also discovered that the perception of university support moderates the relationship between perceived creativity disposition and entrepreneurial intention. In this study, the moderation effect of perception of university support on the relationship between perceived creativity disposition and entrepreneurial intention was acknowledged. As a policy implication, the government should ensure students with an innovative entrepreneurial environment and well-built perception of university support are supported through different channels. Finally, a conceptual model was proposed based on adopting the theory of planned behavior, and the study ends with a conclusion and implications for future research. Keywords: perceived creativity disposition; entrepreneurial intention; attitude toward entrepreneurship; theory of planned behavior; perception of university support 1. Introduction The field of entrepreneurship is rapidly progressing and now receiving a considerable amount of attention from scholars and researchers, as it is considered the driver of economic growth. Entrepreneurs create wealth not only for themselves but also for others by creating employment. An insight into the making of successful entrepreneurs has over-arching implications for the society. What enforces an individual to be an entrepreneur has been an area of interest for entrepreneurship scholars. In this connection, one of the critical areas of research is investigating factors that predict entrepreneurial intention. We believe that understanding the factors that impact an individual’s intention to be an entrepreneur can accelerate the entrepreneurial process and support the practice and theory. Although there J. Open Innov. Technol. Mark. Complex. 2021,7, 11. https://doi.org/10.3390/joitmc7010011 https://www.mdpi.com/journal/joitmc J. Open Innov. Technol. Mark. Complex. 2021,7, 11 2 of 13 is burgeoning research on EI’s antecedent, the decision process that fosters entrepreneurial behavior remains an open research issue. The past plethora of studies focused on how individual characters, such as personality traits, foster entrepreneurial intentions [ 1 – 4 ].The researchers have also highlighted the importance of interaction between the contextual and individual factors in investigating EI [ 5 ]. Similarly, scholars have also shown great interest in examining the role of cognitive elements that facilitate individuals to recognize and exploit the opportunities to start a new venture [ 6 ]. In this connection, entrepreneurship’s cognitive perspective sheds light on the importance of creativity disposition, which is the inherent quality of an individual to create a novel idea—cultivating EI of individuals. Creativity is recognized as an essential element of entrepreneurship as the individuals have to be creative to identify and exploit the opportunities. Therefore, there is no doubt that an individual’s creative disposition has a strong connection with an individual’s entrepreneurial attitude and intentions. However, we believe that the relationship between creative disposition and entrepreneurial intention might be responsive to certain environmental factors such as the perception of the support, in this study’s context, the perception of university support. However, not much has been written on the role of creative disposition and perception of university support in fostering students’ entrepreneurial intentions. Thus, to fill this research gap, this study focuses on entrepreneurship’s cognitive perspective and purposes that students with a higher level of creative disposition will have a strong attitude toward entrepreneurship and entrepreneurial intentions. We also believe that the link between creative disposition and EI is responsive to the environment; thus, the perception of university support may moderate this relationship. In the following sections, this article presents the conceptual framework of the related literature. It uses quantitative research methods to provide the necessary data collection and evaluation procedures. The results and discussion section sheds light on the findings of the study. This article ends with the contribution and political implications. 2. Literature Review 2.1. Context of the Study Pakistan’s population is approximately 220 million, with more than 60 percent of residents under the age of 30 years [7]. The country has more than 200 public and private universities, and currently, almost all offer business courses at the undergraduate and graduate levels (HEC Pakistan, 2019). Despite this, the number of unemployed individuals based on Pakistan’s educational level had reached more than 8 million people [ 8 ]. This phenomenon is ironic, given that the young, educated generation is jobless, contributing significantly to Pakistan’s unemployment. Interestingly, the rate of open unemployment tends to be higher among the highly educated labor force. Therefore, the remaining graduates accept odd jobs or are underemployed [ 6 – 9 ]. Among entrepreneurship disciplines, higher education courses have historically been aimed at cultivating positions in large companies. For young graduates, this situation often generates frustration and despair and has brought socio-economic impacts to countries like Pakistan in the face of the growing population of unemployed youth. This situation is due to students lacking adequate support and afraid to take risks and face new challenges [10]. The higher educational institutions have responded to the mandate asserted by governments in teaching entrepreneurship to develop skills necessary for self-employment and meet the demand of business sectors that desire individuals with knowledge and requisite skills to fit into the corporate world [ 11 ]. It is increasingly necessary for developing countries to establish graduate entrepreneurship education and programs to encourage new business development and enhance entrepreneurial skills. It may also be beneficial for national competitiveness and economic development [ 12 ]. In Pakistan, only a few universities are concerned about the entrepreneurship significance on these grounds [13]. Pakistani higher education institutions (HEI) (including public and private universities) have launched numerous entrepreneurship education programs. To encourage J. Open Innov. Technol. Mark. Complex. 2021,7, 11 3 of 13 student start-ups, the federal government is investing considerable resources in setting up business incubation programs [ 13 , 14 ]. The main challenges were lack of awareness and support to take the initiative to start a business. Creativity only comes through with a new start-up and with a high risk. Because ofthe lack of resources and funds, universities interested in establishing similar business activities are limited. Therefore, it is necessary to fill the knowledge gaps caused by the lack of established plans of prominent local business schools and the lack of research and efforts on the actual and practical transfer of business awareness. 2.2. Entrepreneurship and Entrepreneurial Intentions Entrepreneurship should be a comprehensive program because of its immense contribution to the nations’ economic growth through job formation, innovation, creativity, and social development [ 15 , 16 ]. Entrepreneurship is a competitive behavior that drives the new market, employment creation, and innovation [ 17 ]. Entrepreneurship is essential as the engine of economic broadening and job creation and as the driver of innovation in a country. As a result, entrepreneurs benefit the economy, innovation itself, and the country’s total productivity [ 18 ]. Entrepreneurs have a fundamental contribution to job and wealth creation, modernization, health improvement, and even economic development. Entrepreneurship is identical to self-employment and is considered as a natural approach to solving employability problems, especially among young people [ 19 , 20 ]. Understanding the antecedents of entrepreneurial behavior has been a long-standing interest of scholars, and EI is the single best predictor of entrepreneurial behavior [21]. EI can be described as the process of seeking knowledge that can be used to attain a business drive. People eager to start a company would have a different temperament than someone reluctant to create a new business [ 22 – 24 ].Therefore, EI is a strategic determinant of an individual’s tendency to start and operate companies. If an individual is not interested in entrepreneurship, all business process-related matters will seem more severe than those involved in entrepreneurship [ 25 ]. They are seen as risk-takers with optimism and ample self-confidence who begin to realize their ideas and want to succeed independently in the business world [ 26 ]. Therefore, the unique entrepreneurial idea should be regarded as a substantial economic growth opportunity [27]. 2.3. Creative Disposition, Attitude toward Entrepreneurship and Entrepreneurial Intentions Creativity is to innovate the valuable stuff as a combination and reorganization of knowledge. Creativity is the human ability to think, modify, discover, and create [ 28 , 29 ]. Exploring and exploiting the new opportunities largely depend upon an individual’s abilities to recognize and understand connections among the ideas. The same is the case in the entrepreneurial process, where an entrepreneur has to be creative in identifying and exploiting the opportunities to start a new venture. The literature on creativity shows that creativity plays a significant role in the entrepreneurial process. The people with a higher level of creative disposition can maintain an increased self-confidence and positive attitude in the entrepreneurial process [ 30 ]. Past few studies have incorporated creativity to study individuals’ entrepreneurial intentions; for example, Hamidi et al. [ 31 ] introduced creativity in the entrepreneurial intention model. They found a positive link between creativity and EI. According to Sternberg [ 32 ], entrepreneurs tend to be more creative than non-entrepreneurs, and they also have strong mental frameworks that enforce them to think out of the box. Similarly, another study [ 33 ] found that the higher the perception of individuals regarding the creative disposition, the higher their EI. Feldman and Bolino [ 34 ] argued that Individuals with a higher level of creativity disposition are more inclined toward self-employment. Similarly, creative intelligence may significantly impact an individual attitude to start a new venture [33]. Thus, based on these arguments, we propose that J. Open Innov. Technol. Mark. Complex. 2021,7, 11 4 of 13 Hypothesis 1 (H1). There is a significant and positive relationship between Perceived Creativity Disposition (PCD) and Entrepreneurial Intention (EI). Hypothesis 2 (H2). There is a significant and positive relationship between Perceived Creativity Disposition (PCD) and Attitude Toward Entrepreneurship (ATE). 2.4. Attitude toward Entrepreneurship and Entrepreneurial Intentions The creation of a new business was taking place at the time, and the first step in the process was to form entrepreneurial intentions [ 35 ]. The three motivation factors of EI in the TPB model, the attitude toward entrepreneurship (ATE) and the perceived behavior control (PBC), have been found with the most robust indication with EI [ 36 ]. According to entrepreneurship literature, the SN is less significant to EI than the ATE and the PBC because entrepreneurs can be described as more internally oriented and less socially oriented than non-entrepreneurs [ 37 ]. In this model, we only incorporate mediation impact, which is the main strength of EI and is associated with creativity; i.e., ATE. Last shreds of evidence have considered ATE acts as an intermediary variable in a series of relationships that links individual/psychological parameters with business outcomes, such as ATE as an intermediary between personality traits and EI [ 4 ]. It is shown that ATE continuously improves EI. Students who have confidence and have the necessary entrepreneurial skills and creative thinking, and are optimistic about starting a business, are more likely to start a new career as an entrepreneur. Therefore, ATE can be a predictor of EI position, while PCD is a distant antecedent. Therefore, it is expected to directly correlate with EI and an indirect relationship between PCD and EI through ATE. Consequently, we develop the following hypotheses: Hypothesis 3 (H3). There is a significant and positive relationship between Attitude toward Entrepreneurship (ATE) and Entrepreneurial Intention (EI). Hypothesis 4 (H4). Attitude toward Entrepreneurship (ATE) mediates the relationship between Perceived Creativity Disposition (PCD) and Entrepreneurial Intention (EI). 2.5. Perception of University Support, Perceived Creative Disposition, and Entrepreneurial Intention Universities are considered as a source of fostering innovation and entrepreneurial spirit. Universities can play a significant role in positively manipulating students’ intentions and efforts toward entrepreneurship and making them able to develop a new venture [ 38 ]. Therefore, we believe that universities are a hub of nurturing entrepreneurial passion in students. It is vital to investigate the extent to which education institutes impact students’ intentions to be entrepreneurs. This, perhaps, could be done by investigating the perception of university support in impacting students’ creative disposition and their EI. Universities can provide support in specific ways by instilling the skills and knowledge necessary for business creation. Universities can also provide targeted support to the students. The targeted support may include support in concept development and business development [ 39 ]. Although creativity is conceptualized as personality traits; however, literature advocates that creativity could be responsive to the environment, which means the external factor may influence creativity [ 38 ]. Therefore, we believe that creativity may be portrayed as an outcome of personal and environmental/external settings. For example, studies argue that the university context may influence students’ creativity [ 40 ]. Thus based on these arguments, we posit the following hypothesis. Hypothesis 5 (H5). Perception of University Support (PUS) moderates the relationship between Perceived Creativity Disposition (PCD) and Entrepreneurial Intention (EI) such that this relationship is stronger for those students who have a higher perception of university support. J. Open Innov. Technol. Mark. Complex. 2021,7, 11 5 of 13 2.6. Study Framework A conceptual framework is thus constructed on the basis of the above discussion and hypothesis development as we can see in Figure 1. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 5 of 13 Hypothesis 5 (H5). Perception of University Support (PUS) moderates the relationship between Perceived Creativity Disposition (PCD) and Entrepreneurial Intention (EI) such that this relationship is stronger for those students who have a higher perception of university support. 2.6. Study Framework A conceptual framework is thus constructed on the basis of the above discussion and hypothesis development as we can see in Figure 1. Figure 1. Conceptual framework. 3. Methodology The data were collected from 330 final year students enrolled in a business degree program specializing in entrepreneurship. Eight public and private Pakistani higher education institutes were selected for data collection. The data was collected in the last quarter of 2019. They were situated in Punjab and the capital city of Pakistan (Islamabad). These students were included for two reasons. First, students taking such courses are more likely to start a business. Second, students in their final year of higher education face crucial career choices and are considered to have a good view of their future [16]. For this research, the cross-sectional and quantitative research design was used based on the survey method. Since the educational programs in Pakistan are taught in the English language; thus, the questionnaire was developed in English. Before undertaking the actual data collection, a pilot study was performed. Structural equation modeling (SEM) of partial least squares (PLS) was used to analyze the results and the Smart-PLS software version 3.2.7 to run the PLS-SEM. This method has been in marketing and management literature [41–47]. 4. Data Analysis 4.1. Measures To elicit information regarding the entrepreneurial intentions of the student EI items were taken from [16]. A scale developed by Liñán and Chen [48] was adopted to collect data about ATE whilePCD and PUS scale were borrowed from the [46,49,50]. All items were tested in the Pakistani context and found to be up to the level value of Cronbach’s α. PLS-SEM is a two-step process that involves evaluation measurement and structural models [51–54]. First, by testing the internal consistency reliability (ICR), convergent validity (CV), and discriminant validity (DV), the measurement model should be tested Figure 1. Conceptual framework. 3. Methodology The data were collected from 330 final year students enrolled in a business degree program specializing in entrepreneurship. Eight public and private Pakistani higher education institutes were selected for data collection. The data was collected in the last quarter of 2019. They were situated in Punjab and the capital city of Pakistan (Islamabad). These students were included for two reasons. First, students taking such courses are more likely to start a business. Second, students in their final year of higher education face crucial career choices and are considered to have a good view of their future [ 16 ]. For this research, the cross-sectional and quantitative research design was used based on the survey method. Since the educational programs in Pakistan are taught in the English language; thus, the questionnaire was developed in English. Before undertaking the actual data collection, a pilot study was performed. Structural equation modeling (SEM) of partial least squares (PLS) was used to analyze the results and the Smart-PLS software version 3.2.7 to run the PLS-SEM. This method has been in marketing and management literature [41–47]. 4. Data Analysis 4.1. Measures To elicit information regarding the entrepreneurial intentions of the student EI items were taken from [ 16 ]. A scale developed by Liñán and Chen [ 48 ] was adopted to collect data about ATE whilePCD and PUS scale were borrowed from the [ 46 , 49 , 50 ]. All items were tested in the Pakistani context and found to be up to the level value of Cronbach’s α . PLS-SEM is a two-step process that involves evaluation measurement and structural models [ 51 – 54 ]. First, by testing the internal consistency reliability (ICR), convergent validity (CV), and discriminant validity (DV), the measurement model should be tested [55,56] . The degree to which ICR test subjects measure latent structures and the evaluation are done through composite reliability (CR) score. The study results showed that all the constructs’ CR scores exceeded the standard threshold of 0.70, indicating that the study’s scale has a high internal consistency [ 57 ]. The composite reliability (CR) should be 0.708 or greater, and 0.70 is considered similar enough to be appropriate [ 56 ].The threshold value of 0.5 was also met by the average variance extracted (AVE) scores of all constructs, suggesting a good CV [ 57 , 58 ]. The factor loadings (FL), CR, and AVE scores are shown below in Table 1. J. Open Innov. Technol. Mark. Complex. 2021,7, 11 6 of 13 Table 1. Measurement model (FL, CR, and AVE). Latent Variables Factor Loading CR AVE Perceived Creativity Disposition 0.926 0.612 PCD1 0.785 PCD2 0.758 PCD3 0.715 PCD4 0.811 PCD5 0.825 PCD6 0.857 PCD7 0.725 PCD8 0.771 Attitude Towards Entrepreneurship 0.884 0.605 ATE 1 0.756 ATE2 0.714 ATE3 0.825 ATE 4 0.854 ATE 5 0.729 Entrepreneurial Intention 0.886 0.611 EI1 0.718 EI2 0.799 EI3 0.714 EI4 0.816 EI5 0.850 Perception of University Support 0.870 0.572 PUS1 0.751 PUS2 0.723 PUS 3 0.741 PUS 4 0.749 PUS 5 0.814 The next step for the assessment of the measurement model is the evaluation of discriminant validity. It is a level where one variable differs from the variable in the model. We have three main methods to evaluate the DV, i.e., cross-loading, Fornell–Larcker criterion, and heterotrait–monotrait ratio (HTMT). The cross-loading and the Fornell– Larcker criterion limitations were planned to use the HTMT ratio to test the DV [ 59 ]. Thus, we used the HTMT ratio for evaluating the DV in this analysis. The values in Table 2 indicate that all the constructs’ HTMT ratiosare far below the 0.85 thresholds [59]. Table 2. Discriminant validity by heterotrait–monotrait ratio (HTMT). PCD EI ATE PUS PCD 0.000 0.000 0.000 0.000 EI 0.326 0.000 0.000 0.000 ATE 0.411 0.319 0.000 0.000 PUS 0.407 0.557 0.418 0.000 J. Open Innov. Technol. Mark. Complex. 2021,7, 11 7 of 13 4.2. Structural Model Assessment The structural model assessment evaluates the latent constructs’ relationship and checks the conceptual model [ 60 ]. The structural model outcomes are then presented after determining the validity and reliability of the measurement model. The path coefficients were evaluated using a bootstrap re-sampling approach based on 5000 replicates and 300 instances. After considering the measurement model, the path coefficient’s significance was analyzed with the bootstrapping function of Smart-PLS to test the hypothesis. The results are shown in Table 3. Table 3. Direct effect. Hypothesis Path Path Coefficient t-Statistics p-Values H1 PCD →EI 0.325 4.125 0.000 H2 PCD →ATE 0.215 2.987 0.002 H3 ATE →EI 0.379 4.125 0.001 4.3. Mediation Analysis (Indirect Effect) The bootstrapping approach was used to calculate the indirect effect. Bootstrapping will not infer the sampling distribution of the statistical data or the distribution of variables; for small sample sizes, it can also be used confidently [ 57 ]. Therefore, for the PLS-SEM method, a bootstrapping strategy to test the indirect effects is very suitable. The results in Table 4indicate that ATE mediates the interaction between PCD and EI. Both direct and indirect impacts are important and point in the same direction [ 57 ]. The method of mediation will be complementary mediation and counted as complementary mediation in the present analysis. Table 4. Indirect effect. Hypothesis Path Path Coefficient t-Statistics p-Values H4 PCD →ATE →EI 0.115 4.987 0.001 4.4. Moderation Analysis Moderation defines a condition in which the relationship is not constant between the two constructs but depends on the third variable’s value, called the moderator variable. In the model, the moderator variable adjusts the intensity or direction of the interaction between the two structures. A product indicator approach was used to run the PUS moderation analysis on the relationship between PCD and EI [ 57 ]. Table 5shows the results of the moderation analysis that indicate that PUS moderates PCD-EI linkages. The result of moderation has to compare with the direct impact between PCD and EI, where we can see it has become more assertive with the PUS. Table 5. Moderation effect. Hypothesis Path Path Coefficient t-Statistics p-Values H5 Moderating Effect 1 →EI 0.278 2.970 0.000 Interpretation of moderation analysis is considered a challenging issue. Therefore, a graphical representation of the relationship may help to conclude. In Figure 2, we present the slope of moderation analysis. The green line represents a high perception of university support, while the red line represents a low perception of university support. We can see that the slope of high perception is steeper than that of low perception. This means that the relationship between PCD and EI is stronger for the high perception of university support. J. Open Innov. Technol. Mark. Complex. 2021,7, 11 8 of 13 J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 8 of 13 Interpretation of moderation analysis is considered a challenging issue. Therefore, a graphical representation of the relationship may help to conclude. In Figure 2, we present the slope of moderation analysis. The green line represents a high perception of university support, while the red line represents a low perception of university support. We can see that the slope of high perception is steeper than that of low perception. This means that the relationship between PCD and EI is stronger for the high perception of university support. Figure 2. Slope plot for moderation analysis. 4.5. Coefficients of Determination (R2) R2 calculates the model’s predictive precision and, as illustrated by the model’s independent variables, represents the percentage of variance in the dependent variable(s). For each independent variable, path coefficients indicate the degree of change in the dependent variable [57]. Therefore, the R2 value obtained could interpret the structural model’s strength, indicating the exogenous variables’ explanatory variance in the endogenous variable. The combined effect of variables on endogenous latent variable EI is 0.559. On mediator ATE, its value is 0.570, which means that the model’s variables’ total impact shows a good relationship. 5. Discussion: Entrepreneurial Intention and Open Innovation Drawing the motivation from the theory of planned behavior, this study aims to test the role of perceived creativity disposition and entrepreneurship on students’ entrepreneurial intentions. In addition, the moderating role of perceived university support in the relationship between perceived creativity disposition and EI is tested. Given the growth of new businesses worldwide, entrepreneurship is now seen as a solution to socio-economic growth [61]. However, college students’ intention to start a business has steadily increased, but it has not yet reached the level needed to solve youth joblessness. This is why areas with the highest unemployment rates have seen an increase in entrepreneurs in recent years, particularly across the country [7,62]. In this context, the open innovation (OI) approach was introduced, involving students, teachers, graduates, and companies in decision-making. As a result, motivation, learning, and professional outcomes can be improved [63]. This issue has hardly been functional in prior literature despite being a chance for advanced education. Therefore, the introduction of open inFigure 2. Slope plot for moderation analysis. 4.5. Coefficients of Determination (R2) R 2 calculates the model’s predictive precision and, as illustrated by the model’s independent variables, represents the percentage of variance in the dependent variable(s). For each independent variable, path coefficients indicate the degree of change in the dependent variable [ 57 ]. Therefore, the R 2 value obtained could interpret the structural model’s strength, indicating the exogenous variables’ explanatory variance in the endogenous variable. The combined effect of variables on endogenous latent variable EI is 0.559. On mediator ATE, its value is 0.570, which means that the model’s variables’ total impact shows a good relationship. 5. Discussion: Entrepreneurial Intention and Open Innovation Drawing the motivation from the theory of planned behavior, this study aims to test the role of perceived creativity disposition and entrepreneurship on students’ entrepreneurial intentions. In addition, the moderating role of perceived university support in the relationship between perceived creativity disposition and EI is tested. Given the growth of new businesses worldwide, entrepreneurship is now seen as a solution to socioeconomic growth [ 61 ]. However, college students’ intention to start a business has steadily increased, but it has not yet reached the level needed to solve youth joblessness. This is why areas with the highest unemployment rates have seen an increase in entrepreneurs in recent years, particularly across the country [ 7 , 62 ]. In this context, the open innovation (OI) approach was introduced, involving students, teachers, graduates, and companies in decision-making. As a result, motivation, learning, and professional outcomes can be improved [ 63 ]. This issue has hardly been functional in prior literature despite being a chance for advanced education. Therefore, the introduction of open innovation (OI) for students, faculty, and stakeholders (universities and companies) will be a motivation and additional benefit [64]. Further, the results also confirm the influence impact of perceived creativity disposition on entrepreneurial attitude and intention. According to Amabile [ 19 ], creativity results from different behavior qualities and combinations of sociated creative skills. These findings support the hypothesis proposed in earlier studies [ 9 , 24 ]. The results of H1 showed that PCD has a substantial and positive effect on EI. So PCD is a predictor of EI. The PCD