The impact of perceived regulatory support on social entrepreneurial intention: A survey dataset in Vietnam.

This paper presents the data that estimate the linkages between perceived regulatory support, empathy, moral obligation, social entrepreneurial self-efficacy, perceived social support, and social entrepreneurial intention among Vietnamese students. The scales were adopted from previous studies to develop the questionnaires utilizing a five-Likert scale. The sample collected from 685 undergraduate students from universities in Vietnam. A quantitative approach was utilised to examine the value of data. Specifically, some descriptive statistics was utilized to show the respondents' profiles and characteristics of variables. Cronbach' alpha, exploratory factor analysis and confirmatory factor analysis was used to test the reliability and validity of constructs before estimating path coefficients via structural equational modelling (SEM).

Specification Table

Value of the Data

The data represents the perceptions of regulatory support, empathy, moral obligation, social entrepreneurial self-efficacy, social support, and social entrepreneurial intention among Vietnamese students.

The dataset confirms that the model of Mair & Noboa [9] are suitably implemented in the context of Vietnam-an emerging economy.

The dataset reveals the correlations between perceived regulatory support, empathy, moral obligation, social entrepreneurial self-efficacy, perceived social support and social entrepreneurial intention among Vietnamese students.

The data shows that empathy, social entrepreneurial self-efficacy, perceived social support are determined as three full mediators in the linkages between perceived regulatory support and entrepreneurial intention.

The dataset can be served as valuable reference sources for researchers who take account into social entrepreneurship.

The dataset can be useful for practitioners to foster social business venture and tackle with social problems.

Data Description

Nowadays, the world is facing many serious issues and challenges than any time in history. Every day from social media, a various number of threats of global problems, including climate change, natural disasters, diseases, corruptions, environmental pollutions, poverty and so on, might be learned about. Consequently, finding the answer for the question “what we should do and how we should deal with all of those confronted hazards” [1] is more necessary for the whole community. Fortunately, social entrepreneurship can be the best healer for the society because it is “the simultaneous pursuit of economic, social, and environmental goals by enterprising ventures”, and it “is the first and foremost a practical response to unmet individual and society needs” as well [2]. A key problem to acknowledge business venture lies in investigating entrepreneurial intentions [3], [4], [5]. In the last two decades, there has been an increasing body of studies which determined social entrepreneurship as a potential strategy to deal with social needs [6]. Therefore, it is necessary to explore the factors affecting social entrepreneurial intention [7,8]. This article provides the dataset, which recruited from 685 students at universities/colleges in Vietnam, to examine the impact of perceived regulatory support on social entrepreneurial intention through four antecedents in the model of social entrepreneurial intentions (S-ENT), proposed by Mair & Noboa [9], including empathy, moral obligation, social entrepreneurial self-efficacy, and perceived social support.

The supplementary of raw dataset in that case refers to perceived regulatory support, empathy, moral obligation, social entrepreneurial self-efficacy, perceived social support, and social entrepreneurial intention among Vietnamese students. Screen scales, which are employed in this study, has been also confirmed and validated in prior studies (e.g. [10,11,13]). Firstly, the dataset aims to provide the raw data, which was collected from university students, to represent their perceived regulatory support, empathy, moral obligation, social entrepreneurial self-efficacy, and intention to engage in a social business venture. Secondly, the dataset is utilized to demonstrate the descriptive characteristics of variables as well as to present the statistical evidence of the validity and reliability of the scales in the context of Vietnam. Thirdly, the dataset also aims to confirmed that the model of Mair & Noboa [9] is appropriately applied in the context of social entrepreneurship in Vietnam. Finally, the dataset aims to illustrate the linkage between perceived regulatory supports and social entrepreneurial intention and the meditating roles of four dimensions (perceived social support empathy, moral obligation, social entrepreneurial self-efficacy, perceived social support) in this relationship. To accomplish the research objectives, all data were processed through SPSS 24.0 and AMOS 24.0.

The questionnaire survey consisted of two major information sections: socio-demographic information and measurement constructs. Particularly, the first section included the information about respondents’ characteristics, including gender (1=Male, 2=Female), age (1=From 18 to 20 years old; 2= From 21 to 24 years old; 3= More than 24 years old), Fields of study (1= Economics and business management; 2= Engineering and other fields), did you used to participate in entrepreneurship courses? (0 = No; 1= Yes). Respondents’ profiles are represented in Table 1.

Table 1

Demographic statistics.

Demographic profiles		Frequency	Percentage
Gender	Male	329	48
	Female	356	52
Age	18 to 20 years old	57	8.3
	21 to 24 years old	446	65.1
	More than 24 years old	182	26.6
Fields of study	Economics and Business Management	336	49.1
	Engineering and other fields	349	50.9
Did you used to participate in entrepreneurship courses?	No	543	79.3
	Yes	142	20.7

The second section contained items which reflect perceived regulatory support, empathy, moral obligation, social entrepreneurial self-efficacy, perceived social support, and social entrepreneurial intention. Initially, all items of each variables were tested through Cronbach's alpha. However, the correlated item-total correlation of EI4 (reverse question) (“I am not determined to create a social firm in the future”) only reached 0.107 < 0.3. Thus, it should be eliminated from the scale of “social entrepreneurial intention” [12]. The final results of Cronbach’ alpha, the descriptive characteristics (mean, standard deviation, skewness and kurtosis), and exploratory factor analysis (EFA) of scales was described in Table 2. The Cronbach's alpha of all scales was higher than 0.63. Thus, all scales showed their reliabilities [13].

Table 2

Cronbach's alpha, descriptive characteristics of scales and exploratory factor analysis.

						Factor loadings
Variables and items		Mean	SD	Skewness	Kurtosis	PRS	EMP	MO	ESE	PSS	SEI
PRS	Perceived regulatory support (Farashah et al. [22])	3.8474	0.88171	-0.803	0.019
PRS1	There are sufficient government subsides available for new and growing firms	4.0496	1.13704	-1.175	0.589	0.768
PRS2	The support for new and growing firms is a high priority for policy at the local government level	4.1796	1.06438	-1.268	0.796	0.697
PRS3	Taxes and other government regulations are applied to new and growing firms in a predictable and consistent way	3.6905	1.17627	-0.684	-0.395	0.749
PRS4	Coping with government bureaucracy, regulations, and licensing requirements is not unduly difficult for new and growing firms	3.7197	1.13180	-0.660	-0.319	0.642
PRS5	There is an adequate number of government programs for new and growing businesses	3.6263	1.29344	-0.658	-0.659	0.610
PRS6	Government programs aimed at supporting new and growing firms are effective.	3.8190	1.26904	-0.910	-0.242	0.683
EMP	Empathy (Mair & Noboa [9])	3.8900	0.98704	-0.906	0.210
EMP1	When thinking about socially disadvantaged people. I try to put myself in their shoes	3.7095	1.20864	-0.674	-0.484		0.525
EMP2	Seeing socially disadvantaged people triggers an emotional response in me	4.1197	1.13824	-1.262	0.751		0.851
EMP3	I feel comparison for socially marginalized people	3.8409	1.17706	-0.805	-0.211		0.703
MO	Moral obligation (Mair & Noboa [9])	2.4389	1.20807	0.324	-1.076
MO1	It is an ethical responsibility to help people less fortunate than ourselves	2.3401	1.30213	0.566	0-.885			0.761
MO2	We are morally obliged to help socially disadvantaged people	2.5124	1.35138	0.318	-1.189			0.787
MO3	Social justice requires that we help those who are less fortunate than ourselves	2.4642	1.36710	0.389	-1.171			0.866
SES	Social entrepreneurial self-efficacy (Mair & Noboa [9])	2.6951	1.22748	0.188	-1.094
SES1	I am convinced that I personally can make a contribution to address societal challenges if I put my mind to it	2.5723	1.34081	0.362	-1.101				0.737
SES2	I could figure out a way to help solve the problems that society faces	2.7511	1.42749	0.193	-1.312				0.858
SES3	Solving societal problems is something each of us can contribute to	2.7620	1.39873	0.182	-1.263				0.880
PSS	Perceived social support (Mair & Noboa [9])	4.0365	0.94769	-0.935	0.470
PSS1	People would support me if I wanted to start an organization to help socially marginalized people	3.9737	1.14678	-.0958	0.088					0.746
PSS2	If I planned to address a significant societal problem people would back me up	4.0832	1.01037	-1.003	0.515					0.910
PSS3	It is possible to attract investors of an organization that want to solve social problems	4.0526	1.00881	-0.937	0.365					0.811
SEI	Social entrepreneurial intention (Mair & Noboa [9]; Liñán et al. [16])	3.4354	1.12566	-0.442	-0.615
SEI1	I expect that at some point in the future I will be involved in launching an organization that aims to solve social problems	3.5650	1.29120	-0.573	-0.696						0.591
SEI2	I have a preliminary idea for a social enterprise on which I plan to act in the future	3.2628	1.33700	-.0316	-0.989						0.845
SEI3	I plan to start a social enterprise	3.4759	1.31058	-0.471	-0.886						0.765
SEI5	My professional goal is becoming an entrepreneur	3.4380	1.31268	-0.462	-0.873						0.911
Cronbach's Alpha (α)						0.841	0.791	0.884	0.859	0.878	0.880
Kaiser-Mayer-Olkin Measure of Sampling Adequacy						0.811
Approx. Chi-Square of Bartlett's Test of Sphericity						3600.453
Sig. of Chi-Square of Bartlett's Test of Sphericity						231
Df						0.000
Cumulative (%)						70.704
Initial Eigenvalues						1.111

Note: The dataset for EFA was 343.

Next, the dataset of this study was split into two (343 and 342 responses, respectively) to carry out Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) separately. The KMO and Bartlett test of sphericity were used to determine the appropriateness of factor analysis. The result (KMO = 0.811, Sig. of Bartlett test of Sphericity < 0.001) demonstrated that good appropriateness to perform Confirmatory Factor Analysis (CFA) [14].

In addition, the reliability and discriminant validity of scales were tested through Confirmatory Factor Analysis (N=342). Several indices reflect the model fit, including Chi-Square, CMIN/DF; CFI, GFI, TLI and RMSEA, were represented in Fig. 1. The results illustrate that all indices match with expected values: Chi-Square (194) = 330.658; Chi-Square/df = 1.704; GFI = 0.920; CFI =0.967; TLI =0.961; RMSEA = 0.045 [14,15].

Fig. 1

Confirmatory Factor Analysis.

Although perceived regulatory support (PRS) has an AVE of 474 < 0.5. However, Fornell & Larcker [17] suggested that if AVE is less than 0.5, but composite reliability is higher than 0.6 (CR of PRS is 0.844), the convergent validity of the construct is still adequate. Thus, the reliability, convergent validity and discriminant validity of all constructs has been confirmed and illustrated in Table 3.

Table 3

The reliability, convergent and discriminant validity of constructs.

	CR	AVE	MSV	PSS	PRS	MO	EMP	SES	SEI
Perceived social support (PSS)	0.898	0.745	0.299	0.868
Perceived regulatory support (PRS)	0.844	0.477	0.041	0.202⁎⁎	0.690
Moral obligation (MO)	0.919	0.790	0.011	-0.053	0.099⁎⁎	0.889
Empathy (EMP)	0.807	0.583	0.462	0.408⁎⁎	0.182⁎⁎	-0.104⁎⁎	0.764
Social entrepreneurial self-efficacy (SES)	0.862	0.677	0.258	0.282⁎⁎	0.042⁎⁎	0.077⁎⁎	0.336⁎⁎	0.823
Social entrepreneurial intention (SEI)	0.893	0.676	0.462	0.547⁎⁎	0.103⁎⁎	0.002	0.680⁎⁎	0.508⁎⁎	0.822

Note: CR: composite reliability; AVE: Average variance extracted; MSV: Maximum shared variance.

Significant at the 0.01 level (2-tailed), the dataset for CFA was 342.

The common method variable was employed to guarantee that common method bias was not a major problem in our dataset. First, Harman's one-factor test with unrotated factor solutions was utilized. The result has been showed that there was no problem with common method bias in this study since the total variance extracted by single factor for sample was only 22.280%, this value was much lower than the recommended threshold of 50% [17]. Second, Harman's one-factor was also utilized to conduct CFA, the results showed the very poor data fit (Chi-Square (209) = 4918.632; Chi-Square/df = 23.534; GFI = 0.555; CFI =0.369; TLI =0.303; RMSEA = 0.182) [18,19]. Last, the common latent variable test was carried out and the standardized regression weights of all items for two models (Figs. 1 and 2) has been compared, the results confirmed that there was no major difference between item loadings (Δ < 0.2). Thus, there was not existing common method variance with this data [20].

Fig. 2

Common marker variable.

The structural equational model (SEM) was used to examine the relationship between perceived regulatory support, empathy, moral obligation, social entrepreneurial self-efficacy, perceived social support, and social entrepreneurial intention among Vietnamese students. The detailed structural path analysis was presented in Fig. 3.

Fig. 3

Structural path analysis.

Table 4 described the correlations between variables, which revealed the estimation of the relationships between constructs in the structural model. The results of structural equational model (SEM) analysis demonstrate that perceived regulatory support has strong effects on empathy (γ = 0.199; p-value < 0.001), moral obligation (γ = 0.176; p-value = 0.007 < 0.01), social entrepreneurial self-efficacy (γ = 0.191; p-value = 0.004 < 0.01), and perceived social support (γ = 0.217; p-value < 0.001). However, it is not found to have direct association with social entrepreneurial intention (γ = 0.014; p-value = 0.782 > 0.05). The results also show that empathy has very strong impact on social entrepreneurial intention (γ = 0.629; p-value < 0.001), followed by social entrepreneurial self-efficacy (γ = 0.207; p-value < 0.001) and perceived social support (γ = 0.280; p-value < 0.001), yet it is not significant statistically evidence to show that there was the link between moral obligation and social entrepreneurial intention (γ = 0.017; p-value = 0.575 > 0.05).

Table 4

The correlations between variables.

Direct associations			Estimates	S.E	C.R	P-value
Perceived regulatory support	→	Empathy	0.199	0.051	3.932	⁎⁎⁎
Perceived regulatory support	→	Moral obligation	0.176	0.066	2.689	0.007
Perceived regulatory support	→	Social entrepreneurial self-efficacy	0.191	0.066	2.909	0.004
Perceived regulatory support	→	Perceived social support	0.217	0.045	4.819	⁎⁎⁎
Perceived regulatory support	→	Social entrepreneurial intention	0.014	0.049	0.277	0.782
Empathy	→	Social entrepreneurial intention	0.629	0.054	11.616	⁎⁎⁎
Moral obligation	→	Social entrepreneurial intention	0.017	0.030	0.561	0.575
Social entrepreneurial self-efficacy	→	Social entrepreneurial intention	0.207	0.032	6.535	⁎⁎⁎
Perceived social support	→	Social entrepreneurial intention	0.280	0.046	6.134	⁎⁎⁎

Note: N =685.

< 0.001.

Moreover, bootstrapping method with interval confidence of 90% was employed to estimate the indirect correlations (see Table 5). The results revealed that empathy (γ = 0.0968; p-value < 0.05), social entrepreneurial self-efficacy (γ = 0.0455; p-value < 0.05) and perceived social support (γ = 0.0791; p-value < 0.05) played the full mediating role in the linkage between perceived regulatory support and entrepreneurial intention whereas moral obligation did not.

Table 5

Indirect coefficients estimated through bootstrapping method.

							90% interval of confidence
Indirect coefficients					Indirect impact	SE	LLCI	ULCI
PRS	→	EMP	→	SEI	0.0968*	0.0268	0.0453	0.1498
PRS	→	MO	→	SEI	-0.0010	0.0060	-0.0137	0.0112
PRS	→	SES	→	SEI	0.0455*	0.0178	0.0122	0.0833
PRS	→	PSS	→	SEI	0.0791*	0.0367	0.0387	0.1234

Note: N =685.

< 0.05.

Experimental Design, Materials and Methods

Three primary constructs in this survey were measured using scales which developed by previous studies. The scale measured perceived regulatory support (six items), was adapted from Farashah et al. [13] while four antecedents, including empathy (three items), moral obligation (three items), social entrepreneurial self-efficacy (three items), perceived social support (three items), was adopted from Mair & Noboa [9]. The scale of “social entrepreneurial intention” (five items) was modified from Mair & Noboa [9] and Liñán et al. [16]. The valid items are summarized in Table 2. Also, because the target respondents are Vietnamese youths, therefore, the scale items were first transformed into Vietnamese from the English version. Some words have been adjusted to be more appropriate to the context and culture of Vietnam. Then, the questionnaire instrument was back-translated into English to guarantee the consistence of original and translational versions. The questions were rated in a five Likert-type format from 1 (strongly disagree) to 5 (strongly agree). The survey carried out during the period from from 12 January, 2021 to 02 March, 2021 using convenience sampling technique through an online questionnaire. At this period, despite most of cities in Vietnam have been allowed to relax social or physical distancing measures, some certain restrictions, such as staying at least 6 feet, wearing facemasks, closing public entertainment services (bars, game centers) have still been performed by the government. Therefore, utilizing online data collecting tool during the covid-19 pandemic is more suitable [20,21]. 25000 online questionnaires have been distributed to personal Emails, Zalo, and Facebook, and LinkedIn to invite students to participate in the survey. However, only 715 questionnaires have been answered (28.6%) while 30 responses wave not completely fulfilled. Thus, we decided to eliminate these questionnaires to increase the quality of the dataset. Finally, the sample with the valid data includes 685 undergraduate students recruited from universities in Vietnam.

The quantitative analysis was carried out to analyze the data. To specific, the Cronbach's alpha, exploratory factory analysis (EFA), and confirmatory factor analysis (CFA) were employed to test the internal reliability, validity of each variables, and the fit of model. Then, structural equation modelling (SEM) was carried out to explore the path coefficients that was identified as the most appropriate and efficient estimations of multiple regression analysis.

Ethics Statement

Official permission was obtained from Department of Higher Education (DHE) as an authorized unit under Ministry of Education and Training (MOET), Vietnam before data collection from universities. This study was a voluntary survey. The responses were fully anonymous. The authors kept to all ethical concerns during the data gathering process and ensured that all information was used for research purposes and was absolutely confidential. We confirm that informed consent of all participants has been obtained.

CRediT Author Statement

Duong Quy Hoa: Conceptualization, Methodology, Data collection, Draft preparation; Nguyen Thi Bich Ngoc: Data collection, Investigation; Nguyen Thi Kim Chi: Data collection, Visualization.

Declaration of Competing Interest

The authors affirm that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article.

Subject	Social Sciences
Specific subject area	Social entrepreneurship
Type of data	Primary data, tables, and figures
How data were acquired	The development of survey questionnaires was based on the previous studies. Dataset was collected utilizing an online survey platform (google forms). The questionnaire was provided as a supplementary file.
Data format	Raw and analysed statistical dataset.
Parameters for data collection	The sample was gathered from 685 Vietnamese undergraduate students with internet access. Participants decided to participate in the survey voluntarily.
Description of data collection	The dataset was obtained through an online questionnaire, which was delivered to undergraduate students in Vietnam employing convenience sampling technique helped to collect the data. The data consisted of 685 valid responses. The process of data collection started from 12 January, 2021 to 02 March, 2021.
Data source location	City/Town/Region: Hanoi, Quy Nhon and Ho Chi Minh cityCountry: VietnamLatitude and longitude for collected samples/data: 16.812913; 107.108177
Data accessibility	Dataset and the questionnaire survey are available in this article.