Factors Influencing Returning Migrants’ Entrepreneurship Intentions for Rural E-Commerce: An Empirical Investigation in China

Abstract

Many Internet users have provided a favorable atmosphere for rural e-commerce to thrive, and the return of rural inhabitants starting their own companies has had a significant impact on rural economic development. Understanding the influencing elements for returning residents to carry out rural e-commerce operations can provide suggestions for the ongoing development of the economy in rural regions and the lack of talent faced in rural areas, especially in light of the trend of people returning to their hometowns. This work offers a research model based on the push–pull–mooring (PPM) theory to explain the factors that drive returning residents to engage in rural e-commerce entrepreneurship. The empirical results determined using the PLS-SEM method and SmartPLS 3.0 software to analyze the survey data of 151 returning residents revealed that urban employment obstacles, policy support, and infrastructure are positively connected with returning residents carrying out rural e-commerce entrepreneurship. Start-up costs are negatively correlated with rural e-commerce entrepreneurship by returning residents. Policy support plays an intermediary role in the price of starting a business and in the return of rural residents starting a rural e-commerce business. We recommend that the government strengthens policy support for returning entrepreneurs, improves rural e-commerce infrastructure, assists entrepreneurs in lowering their start-up costs, and initiates activities aimed at enhancing entrepreneurial intentions and sustaining entrepreneurial activities, based on the findings of this study.

1. Introduction

The research shows that information and communication technologies (ICT) can powerfully propel economic growth and social improvement in developing countries [1]. E-commerce is considered to be part of information and communication technology (ICT) activities [2], which can provide employment opportunities and thereby create wealth, as well as an effective means of solving economic problems in developing countries [3]. Many studies have noted that e-commerce plays a positive role in socio-economic development problems [4]. Compared to other countries, e-commerce was developed late in China, with the first online transaction order in April 1998 [5]. However, with its development, China has taken the lead in the business-to-business (B2B) and business-to-consumer (B2C) e-commerce market [6] and has the majority of the top e-commerce companies in the world [7].

Rural economic development has been a persistent challenge for developing countries [8]. Some scholars have argued that the development of rural e-commerce can effectively improve the economy of rural areas. The Chinese government has made rural e-commerce an essential strategy for rural economic development and has introduced policies that prioritize the development of rural e-commerce as a way to boost rural economic development [9]. In contrast to traditional rural economic operations, rural e-commerce does not require conventional trading spaces for commercial activities. Instead, it uses the Internet to provide instantaneous transaction information and an electronic transaction mode, making trade between sellers and buyers faster and more convenient while allowing small and medium-sized enterprises and operators to emerge. The rapid development of the rural e-commerce economy has been supported by the ubiquity of smartphones and mobile Internet services and improvements in the rural Internet infrastructure. In China, national-level poverty-stricken counties’ total online retail sales reached 301.45 billion yuan (43.7 billion dollars) in 2020, increasing 26 percent year-on-year and highlighting the country’s strong development momentum [10]. Rural e-commerce has emerged successively in other developing countries, and the development of rural e-commerce has been seen as a promising pattern for improving rural economies [11].

However, there are still many obstacles in developing e-commerce in rural areas, among which talent scarcity is particularly striking [12]. According to the Institute of Wisdom E-Commerce of China Agricultural University’s “2020 China Rural E-Commerce Talent Status and Development Report”, the shortage of Chinese rural e-commerce talents will reach 3.5 million in the next five years [13]. This shortage is primarily caused by several aspects. First, in many ways, infrastructure, transportation, and employment prospects among rural communities generally lag behind metropolitan regions, resulting in rural population exodus into more economically developed cities [14]. Second, the capitalist economy is concentrated in the urban economy and rural laborers seek higher wage income, which leads to urban–rural migration [15]. Third, many rural residents opt to migrate into urban communities to seek higher income, new employment opportunities, more access to services and infrastructure, and a higher quality of living [16]. Some scholars have proposed that the main strategy for rural economic development needs to focus on the entrepreneurs who start and develop businesses; those who are innovative and entrepreneurial are the driving force in creating new businesses [17]. Thus, addressing the issue of rural talent emigration and persuading rural residents to return to their hometowns to start their enterprises have become crucial issues for the growth and long-term sustainability of rural e-commerce. Meanwhile, what factors influence the decision to return home? What factors affect the intentions of returning migrants to launch rural e-commerce enterprises?

The majority of studies on rural e-commerce entrepreneurship have been conducted at the macro level, primarily focusing on the phenomenon of rural e-commerce entrepreneurial clustering and entrepreneurial modes. Relatively few have been micro-level studies on rural e-commerce entrepreneurship. To address some research gaps and build on the literature, this study implemented a push–pull–mooring (PPM) theoretical model of factors in rural e-commerce entrepreneurship influencing the return migration into rural regions. The influence of push, pull, and mooring elements were modeled and empirically tested, contributing to a broader application of PPM theory to research. Based on the results, recommendations were formulated on how to promote and strengthen e-commerce entrepreneurship among rural communities.

The rest of this paper is arranged as follows: the second section introduces the literature review. The third section presents the theoretical background, constructs the theoretical model, and introduces the research hypothesis. The research method and empirical results are presented in the fourth section. The fifth section discusses the theoretical and practical significance of the study and proposes some recommendations. The sixth section summarizes the research conclusions.

2. Literature Review

2.1. The Concept of Return Migrants and Entrepreneurship

In academic circles, there is currently no definitive consensus on what constitutes “return migration entrepreneurship”. One working definition for “return migration entrepreneurship” is when farmers who have migrated into urban areas to work have broadened their horizons and have accumulated capital return to their hometowns to establish industrial or commercial enterprises [18].

In developing countries, the dualistic economic structure is widespread. Many production components and resources tend to agglomerate in urban areas, resulting in imbalanced growth between urban and rural communities and causing population migration. For example, when Korea vigorously implemented industrial construction in the 1960s, the rural economy entered a state of economic depression. The widening economic disparity between urban and rural areas resulted in an influx of the rural population into cities, causing significant stagnation of the rural economy [19]. Generally, more resources are concentrated in urban development in developing countries, which leads to the migration of rural labor to developed urban areas [20]. This urban–rural migration is one of the main ways to reduce poverty in developing countries, which helps to reduce the income inequality between urban and rural residents [21]. These examples demonstrate that given the urban–rural divide, many rural residents would opt to leave the countryside in order to pursue better opportunities in cities.

However, when an economic downturn occurs, return migration occurs. For example, during the global economic crisis in 2008, nearly 20 million migrant workers in coastal China were laid off and returned to the countryside [22]. In addition, social exclusion against rural residents can occur in cities due to the household registration policy [23]. Enhanced rural infrastructure, including the living environment, transportation networks, and interconnectivity, may entice rural residents to return to their hometowns [24].

Urban issues, such as pollution, congestion, increased public service costs, and price hikes, may emerge when cities grow, resulting in higher living costs and increased socio-economic pressures [25]. In China, the rate of increase in migrant worker income declined from 13.9% in 2013 to 6.8% in 2018, while the cost of urban living increased, particularly housing. In 2018, the average increase in rent in first-tier cities was more than 20%. Second-tier cities also experienced double-digit rent increases, far higher than the increase in migrant worker wages, putting a significant burden on migrants working in cities and making integration into the urban communities more difficult. Li and Long [26] also found that having parents requiring care or assistance reduces the inclination to stay in the city and motivates returning to the countryside.

2.2. Returning Entrepreneurship and Rural E-Commerce

Presently, start-ups often confront weaknesses, such as the scarcity of resources and imperfect supporting facilities [27], while returning start-ups face problems such as a poor business environment and an unstable market. By the benefit of gradually evolving rural infrastructure and huge business potential, returning entrepreneurs choose e-commerce because it offers significant benefits over the traditional brick-and-mortar business model [23]. E-commerce is an effective strategy to reduce rural poverty at the stage of economic development. Rural e-commerce can assist rural households in pursuing innovation and entrepreneurship, achieving economic progress, and overcoming poverty and wealth. Integrating e-commerce and resources in rural areas can lessen information occlusion [28].

Traditional labor-intensive foreign trade industries have been under tremendous pressure from order cancellations. In January and February 2020, the accumulated year-on-year decline in exports was 26.3%, forcing enterprises to lay off employees, many being migrant workers [29]. Xie [30] concluded that blending old and new dynamics in urban sectors could result in structural unemployment for migratory workers. Since the “machine instead of labor” initiative started in Zhejiang in 2013, two million jobs were lost by 2015, while a similar program in Dongguan has eliminated 200,000 [31].

Given these changes in labor and market trends, rural e-commerce can effectively alleviate the problem of unemployment. Estimates by the Ministry of Commerce and the Ministry of Agriculture and Rural Affairs suggest that the number of people returning to their hometowns to start their own businesses has exceeded 8.5 million, of which more than 50% used “Internet+” innovation and entrepreneurship in 2019, and the number of online stores reached more than 13 million, generating 30 million jobs in rural areas [10] and demonstrating that rural e-commerce has considerable economic impact.

In recent years, rural economic development has received increased national attention, particularly rural e-commerce. In 2015, Central Document No. 1 outlined specific work requirements for the development of rural e-commerce. As a result, as of 2017, the proportion of broadband available in administrative rural villages had reached 96 percent, with 86 percent coverage among poor areas, further improving the rural information infrastructure and resulting in the rapid growth of rural e-commerce [32]. Furthermore, with the continued support from the central to local governments, improvements in the rural network infrastructure, the modernization of agricultural logistics system, and the rise in demand for green and original agricultural products [33], large e-commerce platforms (e.g., Alibaba, Jingdong, and Suning) have started investing in resources, building platforms, and providing training services in rural communities. Return migration entrepreneurship has become highly viable for many rural migrants, and e-commerce may be one of the best options for these new rural entrepreneurs.

Returning home to establish a business has become increasingly popular. According to China’s Ministry of Human Resources and Social Security, the trend of migrant workers returning to their hometowns to start their businesses has rapidly accelerated. By 2025, this number is estimated to rise to more than 15 million nationwide [34]. Based on this, the study is of practical significance. The results can be used to develop effective strategies for decision-makers to ensure that returning entrepreneurs carry out rural e-commerce entrepreneurship and achieve sustainable rural economic growth.

2.3. Intentions of Returning Entrepreneurship and Influencing Factors

Entrepreneurial intention refers to a potential entrepreneur’s subjective decision to engage in entrepreneurial activity [35]. It is impacted by personal elements, such as entrepreneurial attitude, self-efficacy, and entrepreneurial competence. The stronger the entrepreneurial intention, the more favorable the individual’s entrepreneurial attitude [36]. The external environment, including social, economic, political, and infrastructural development, impacts entrepreneurial aspirations [37]. According to Murry and MacMillan [38], an individual’s entrepreneurial intentions are influenced by psychological qualities, such as the drive to achieve, beliefs, the ability to perceive, and the ability to take advantage of chances. The factors influencing people’s entrepreneurial intentions, according to Qian [39], are divided into two levels (individual traits and personal resources) and six dimensions (achievement motivation, risk-taking, autonomy, entrepreneurial payback, resource acquisition, and future employment). Government policies and processes have also been found to have an essential role in influencing entrepreneurial activities in the social environment [40]. Likewise, a stable economy and an excellent entrepreneurial culture in society are favorable to entrepreneurial activities [41].

Individual, economic, social, and cultural issues all have a role in return migrant entrepreneurship. According to a study, solid social communication skills and literacy are crucial individual qualities that encourage migrants to return home and establish a business [42]. Chen et al. [43] conducted an empirical study on the micro and macro variables of return migrant entrepreneurship. They found that the educational environment, conditions of the place of residence, regional consumption, and local housing price levels significantly affect the entrepreneurial choices of returning migrants. Similarly, an excellent financial environment and policy support in rural areas may also have considerable impact on migrants’ entrepreneurial choices [44].

Table 1. Intentions for returning entrepreneurship and influencing factors.

Type of Factors	Influencing Factors	References
Macro factors	Government policies and institutions have a significant impact on entrepreneurial activity. The development of entrepreneurial activity is also aided by a positive entrepreneurial culture and a stable economic environment.	Stephen [40] Zhang and Yang [45]
	Farmers’ readiness to create their own companies might be boosted by a favorable financial climate and regulatory support in rural areas.	Zhu and Kang [44]
Micro factors	The more an individual’s desire to succeed in life, the greater his or her interest in entrepreneurship.	Qian [39]
	Individual qualities that increase readiness to return home to establish a business include entrepreneurial competencies such as good sociability and high literacy.	Shi et al. [42]
	Returning migrant workers’ decisions to create their enterprises are influenced by their educational environment, living conditions, level of consumption, and property prices in the region.	Chen et al. [43]

summarizes the different influencing factors for return migrant entrepreneurship from previous studies.

3. Theoretical Model and Research Hypothesis

3.1. PPM Theory

The PPM theoretical framework refers to people’s decisions to move from one geographic area to another, as influenced by various push, pull, and mooring factors [46]. It models population migration by capturing the factors and motivations that influence people to move [47]. This theoretical model is shown in Figure 1 [47].

According to the PPM theory, push factors are negative aspects that make a particular location less appealing and cause people to relocate to a new area. Examples include a lack of natural resources, poor development, poor employment opportunities, limited personal prospects, and natural disasters like floods, earthquakes, fires, or epidemics [48]. Pull factors mainly refer to positive elements that attract people to move to a particular area, such as healthy economic development conditions, good employment prospects, excellent employment opportunities, higher income levels, quality education, favorable environment, and living conditions [49]. Moreover, moorings factors generally refer to individual and social factors that constrain or facilitate migration, like migration costs, personal ability, and life security and safety [47].

PPM theory has been used in various research topics. Jang (2017) used PPM theory as the core to study the factors influencing the intention to switch mobile telecommunication services in China [50]. Handarkho (2019) used PPM theory to study the intention of physical stores to adopt mobile payment [51]. Huang (2020) explored the factors that influence crowd worker engagement behaviors within the framework of PPM theory [52].

Previous studies based on PPM theory have similarities to the present study. In particular, there are harmful elements in urban areas that encourage migrants to return and engage in rural entrepreneurship, positive aspects in rural areas that encourage return migrant entrepreneurship, and personal and social factors limiting or encouraging rural residents to return to entrepreneurship. This study used PPM theory as a framework to investigate the factors that drive rural inhabitants to return to their hometowns to engage in rural e-commerce entrepreneurship.

3.2. Research Model

The factors driving rural inhabitants to return to their hometowns to engage in rural e-commerce entrepreneurship are classified into three groups based on the PPM theoretical framework: push, pull, and mooring. Figure 2 presents the research model. In particular, six factors that could affect rural return migration entrepreneurship are analyzed in this study.

3.3. Research Hypothesis

This paper examines the different variables that drive rural inhabitants to return to their hometowns and pursue e-commerce entrepreneurship using the PPM theory. Employment obstacles and a sense of belonging in the city were used as the push factors; policy support and infrastructure were the pull factors; entrepreneurial network capacity and start-up costs were the mooring factors.

3.3.1. Push Factors

Push factors are primarily adverse circumstances that prompt rural migrants to leave the city and return to the countryside. Employment obstacles and a sense of belonging to the city were the push factors analyzed in this study.

• Employment obstacles

Returning to the countryside normally occurs when an economic crisis occurs and the economic situation in the cities deteriorates. For example, due to the global economic crisis in 2008, around 20 million migrant workers in coastal areas of China were laid off and returned to the countryside [22]. The global coronavirus epidemic has affected traditional labor-intensive foreign trade industries, primarily migrant workers, with severe pressures from order cancellations. Exports fell by a cumulative 26.3 percent year-on-year from January to February 2020, forcing enterprises to lay off employees and leaving a large number of migrant workers jobless [29]. Many migrant laborers were unable to find work in cities and were prompted to return to their hometowns to seek employment. Entrepreneurship (i.e., starting own business) is a popular option for migrant workers once they return to their hometowns [53]. Based on these arguments, the following hypothesis is proposed.

Hypothesis 1 (H1).

Urban employment obstacles are significantly positively correlated with rural residents returning to their hometowns to engage in rural e-commerce entrepreneurship.

2.

Sense of belonging to the city

Under the current urban–rural dual system, institutional social exclusion is often at odds with the desire and ability of migrant workers to integrate, identify with, and belong to a new city [54]. According to a National Bureau of Statistics poll, the larger the city, the more difficult it is for migrant workers to assimilate and the lower their sense of belonging is to the community [55]. Factors such as salary level, cost of living, and pressure to buy a property may influence a migrant’s sense of belonging [56]. According to studies, a sense of urban belonging is crucial in the migrant worker’s decision to settle in cities [57]. Based on these arguments, the following hypothesis is proposed in this research.

Hypothesis 2 (H2).

A sense of urban belonging is negatively correlated with rural migrant return entrepreneurship.

3.3.2. Mooring Factors

The term “mooring factors” refers to the influencing variables that may either encourage or discourage returning locals from engaging in rural e-commerce business. Entrepreneurial network capability and start-up costs are the two mooring factors explored in this study.

• Entrepreneurial networking capabilities

Network competence (NCC) is a company’s fundamental competency. It primarily relates to managing relationships with suppliers, consumers, and other organizations, recognizing external opportunities, and getting scarce resources to lower business operating expenses and increase operational efficiency [58]. Entrepreneurial network capability is the ability to integrate, coordinate, and build internal and external resources to gain a competitive advantage [59]. Returning entrepreneurs face numerous challenges when starting a business [27], and they frequently find themselves becoming passive and disadvantaged due to having low resources, which are highly critical to the survival and development of start-ups [60]. Network capability may determine whether the business of a returning migrant succeeds or fails [61]. Entrepreneurs can effectively employ networking capabilities to obtain market knowledge, find opportunities, and accumulate resources [62], thus improving confidence and performance. Murry and MacMillan [38] found that the identification and utilization of opportunities may influence entrepreneurial ambitions. Based on these arguments, the following hypothesis is proposed.

Hypothesis 3 (H3).

Entrepreneurial networking capabilities are positively correlated with rural residents returning to their hometowns to engage in rural e-commerce entrepreneurship.

2.

Start-up costs

When city-dwellers return to rural areas to pursue rural e-commerce entrepreneurship, they face numerous challenges with switching costs. According to Burnham et al. [63], switching costs are divided into three categories—(1) procedural switching costs, which refer to time and effort costs; (2) financial switching costs, which constitute financially quantifiable resources; (3) relational switching costs, which refer to the psychological or emotional aspects. Returning entrepreneurs have to devote time, energy, and money to start their businesses. This requires time to learn about rural e-commerce, identify the resources accessible in the area, re-acclimate to the rural environment, and invest money in a platform or website creation and daily operational expenditures. Previous research has found that time, money, and effort affect people’s desire to relocate and transfer (e.g., Bolton et al., Jones et al.) [64,65]. It is worth noting that the benefits of start-up costs are the main motivation for rural migrant return entrepreneurship [66]. The following hypothesis is proposed based on these arguments.

Hypothesis 4 (H4).

Start-up costs are negatively correlated with rural residents returning to their hometowns to carry out rural e-commerce ventures.

3.3.3. Pull Factors

Pull factors refer to the favorable factors in rural areas that promote and motivate returning migrants to carry out rural e-commerce ventures. The pull factors explored in this paper include policy support and infrastructure.

• Policy support

Part of the entrepreneurial environment, policy support refers to relevant policies and measures that can stimulate entrepreneurial enthusiasm or promote entrepreneurial activities, such as entrepreneurial systems, tax policies, project support, financial policies, and government services [44]. Studies have shown that policy support can motivate entrepreneurship and reduce entry barriers [67]. Meanwhile, macro-government policies, such as lowering institutional barriers, providing financing support, providing tax and preferential incentives, and providing entrepreneurial training and consulting services, can stimulate the flow of projects, technologies, and resources, increasing entrepreneurial motivation and promoting new business [68]. Policy support may also lower the costs and risks of starting a business, which can help motivate new entrepreneurs [44], particularly in countries where the cost of starting a business is high and restrictive [69]. Based on the discussion, the following hypothesis is proposed.

Hypothesis 5 (H5).

Policy support is positively correlated with rural residents returning to their hometowns to engage in rural e-commerce.

2.

Infrastructure

Infrastructure can be divided into economic and social. Economic infrastructure refers to permanent works, equipment, and facilities used for production and services, such as electricity, communication, and road networks. Social infrastructure encompasses business services, health care, education, and culture [70]. Previous studies have shown that the state of the infrastructure can influence return migrant entrepreneurship. The better the infrastructure, the stronger the willingness to return and engage in entrepreneurship [71]. Improvements in rural infrastructure facilitate the utilization of existing resources, introduce external resources, and improve production efficiency, boosting farmer confidence in entrepreneurship [72]. The better the infrastructure environment, the easier the physical and information transfer, which can boost willingness to start a business [73]. Based on this, the following hypothesis is proposed in this paper.

Hypothesis 6 (H6).

Infrastructure is positively correlated with rural return migrants engaging in rural e-commerce entrepreneurship.

3.

The role of policy support in mediating between the cost of starting a business and the return of rural residents to carry out rural e-commerce ventures

In the previous section, we hypothesized that policy support and start-up costs directly impact the growth and expansion of rural e-commerce among returning migrants. Likewise, these variables may also introduce some indirect effects. Implementing entrepreneurship protection laws may lower start-up costs, such as capital expenses, taxes, and training costs, which would then incentivize and encourage returning migrants to start a business [66,73]. If protection measures, policies, and incentives are not adopted, returning migrants may have to pay considerable amounts to engage in entrepreneurial activity, reducing the favorable mediating effect of policy assistance. The following hypothesis is proposed based on these arguments.

Hypothesis 7 (H7).

Policy support can mediate the relationship between start-up costs and rural e-commerce entrepreneurship.

4. Research Methodology and Results

This study analyzed the elements that influence returning residents’ willingness to engage in rural e-commerce entrepreneurship. The framework was developed based on literature review, theoretical analysis, model construction, and hypothesis development, as shown in Figure 3. The five main steps in the methodology are as follows: questionnaire development, pretest, data collection, data analysis, and identification of the influencing factors for rural e-commerce entrepreneurship among returning migrants.

4.1. Questionnaire Design

The questionnaire had two main sections. The first contained the respondent’s basic information, such as gender, age, education level, region, urban living experience, occupation, and time before starting a rural e-commerce business. The second involved the quantitative evaluation of seven latent variables measured using a five-level Likert scale (strongly disagree, disagree, neutral, agree, and strongly agree) [74].

Table 2. Variables and measurement question items.

Variables	Items	References
Employment obstacles (EO)	1a: I think it is getting harder and harder to get a job in the city.	Huang et al. [52]; Punch et al. [75]
	1b: I have difficulty finding employment in the city.
	1c: City employment is very demanding for me.
Sense of belonging to the city (SoB)	2a: The city’s salary level does not meet my requirements.	Zhu and Yang [57]
	2b: The cost of living in the city is too high for me.
	2c: The price of the city is more than I can afford.
Entrepreneurial networking capabilities (ESA)	3a: I am good at maintaining the relationship resources necessary to start a business.	Li et al. [76]; Liu and Chen [59]
	3b: I can access entrepreneurial resources through the proper channels.
	3c: I was able to learn the necessary entrepreneurial skills from my partners.
Start-up costs (SC)	4a: I think it takes a lot of effort to carry out a rural e-commerce business.	Ye and Kankanhalli [77]; Bin et al. [78]
	4b: I think to start a rural e-commerce business, I need to receive more training.
	4c: I think to carry out rural e-commerce business, I need to invest more money.
Policy support (PS)	5a: I think the government should provide preferential policies to support.	Globe Entrepreneurship Monitor [79]; Zhu and Kang [44]
	5b: I think the government should provide financial support or subsidies.
	5c: I think the government should simplify the registration, registration, and approval process for business start-ups.
Infrastructure (IN)	6a: I think the improvement of rural infrastructure is conducive to production and marketing.	Zheng and Lu [72]
	6b: I think rural e-commerce businesses must rely on a sound logistics infrastructure.
	6c: I think the improvement of Internet communication facilities provides convenient trading channels.
Rural e-commerce entrepreneurship intention (REEI)	a: I had the idea for a rural e-commerce business a long time ago.	Huang et al. [52]; Gao and Liu [80]
	b: I am ready for a rural e-commerce business.
	c: I want to contribute to rural e-commerce.

summarizes the latent variables and measurement questions used in this study.

4.2. Questionnaire Pretest

We conducted a pretest to assess questionnaire reliability and validity and avoid issues like imprecise phrasing and semantic ambiguities. The questionnaire was given to 20 returning migrants (10 each from Jieyang City and Zhanjiang City) who started a rural e-commerce business. The respondents were mainly contacted using mobile applications (i.e., SMS, WeChat, QQ) and were asked whether they would participate in the study. Those who said yes were sent a link to the online questionnaire. Upon completion, each pretest respondent was then interviewed about their thoughts regarding the comprehensibility and readability of the questionnaire. The respondents were asked if there were confusing or ambiguous texts and if they had suggestions on improving the questionnaire. In the initial survey, our goal was to conduct an initial test of the research questionnaire with the goal of collecting 20 valid questionnaires (10 from each surveyed region). With the efforts of our team members, we visited a total of about 46 people, all of whom were relevant practitioners, and finally achieved the goal. The questionnaire was then reviewed and revised based on the pretest results.

4.3. Data Collection and Descriptive Statistics

Figure 4 presents the study area of Junpu Village in Jieyang City and Suixi County in Zhanjiang City, both located in Guangdong Province. Guangdong is a province with a significant e-commerce sector. The two villages have extensive rural e-commerce operations. Junpu Village was designated as an e-commerce demonstration base in Guangdong Province in 2015 and had been touted as an effective conduit to support China’s transformation for the global economy. Junpu has excellent local infrastructure facilities, strong policy support, and visible development results [81], which have attracted some of those who have emigrated to Guangzhou’s big cities to return [82]. In 2017, Junpu processed 4 CNY billion (USD 612 million) in transactions, resulting in the direct and indirect employment of more than 150,000 workers [81]. Suixi County of Zhanjiang City is a comprehensive demonstration county for e-commerce in rural areas and ranks first among the provincial-level demonstration counties of e-commerce in Guangdong Province. Suixi has actively explored new modes of rural industrial development and has vigorously promoted the development of the rural e-commerce industry [83].

In China, there are many blockages and restrictions that have been brought by the spread of COVID-19, and it was difficult for us to carry out the survey by heading to the target area; thus, we had to implement the survey by distributing electronic questionnaires.

The research team used the following methods to collect the questionnaires. First, we used WeChat, China’s largest social networking software, to distribute electronic questionnaires to rural e-commerce entrepreneurs to fill out. Second, we commissioned local rural e-commerce associations, e-commerce industrial parks, and e-commerce service stations to send the questionnaires to the target group for completion. Third, as our team has been engaged in research on rural e-commerce in Guangdong for many years, we have rich experience. Therefore, we targeted people in charge of rural e-commerce businesses to invite them to take the questionnaire.

The survey lasted six months, from June to November 2021. The whole survey process is quite successful, and the questionnaire can be accurately delivered to the people who are engaged in rural e-commerce business or related work. The survey was not compensated with any money; it was a completely academic survey, but local organizations and people in charge were willing to cooperate with our research by sending electronic questionnaires to work or industry exchange groups, which greatly enhanced the validity of our survey questionnaire. In addition, inside the questionnaire, we also set criteria to identify respondents, such as whether they were in the surveyed area and whether they were engaged in rural e-commerce ventures. Finally, out of the 280 questionnaires sent, 175 were received back, and 151 were deemed complete and accepted, equivalent to an effective rate of 86.29%.

Table 3. Descriptive statistics of basic information of returning residents.

Categories	Items	Ratios
Gender	Male	64%
	Female	36%
Age	18~25	10%
	26~30	45%
	31~35	21%
	36~40	16%
	≥40	8%
Education level	≤Junior high school	5%
	High school	23%
	College	34%
	≥Bachelor’s degree	38%
Area	Suixi County, Zhanjiang City	52%
	Junpu Village, Jieyang City	48%
Had urban life experience	Yes	100%
	No	0%
Occupation before engaging in rural e-commerce business	Student	20%
	General employee	22%
	Entrepreneur	35%
	Business manager	5%
	Other	18%
Time spent in rural e-commerce business	≤0.5 year	31%
	0.5~1 year	20%
	1~1.5 year	24%
	≥1.5 year	25%

summarizes the results of the descriptive statistics.

As shown in Table 3, male respondents were the majority, accounting for 64% of the total respondents. The majority of the respondents were between 26 and 30 and had at least a college degree. There was no significant difference in the sample sizes between Suixi County and Junpu Village. All respondents had previously lived in the city, and the majority (65%) were non-entrepreneurs before engaging in rural e-commerce. The majority of the respondents had been involved in rural e-commerce for less than six months.

4.4. Control Variables

Control variables are the parameters that remain constant and are unrelated to the study’s aim. These parameters are controlled because they may affect the study’s results and are often employed to fix and improve flaws in the data-gathering process [84]. Based on the recommendation of Ye and Kankanhalli [77] and Huang et al. [52], the respondents’ demographic information (i.e., gender, age, education level, area, urban life experience, occupation, and time before engaging in rural e-commerce entrepreneurship) were used as control variables to eliminate the influence of extraneous factors and ensure the accuracy of the findings. The respondent’s occupation before starting a rural e-commerce business can be used to determine the respondent’s work experience, which could influence their readiness to engage in a rural e-commerce business.

4.5. Data Analysis

SmartPLS 3.0 software was used to develop the structural equation model (SEM) to evaluate the paths of the latent variables and their associations. The SEM is the preferred method for analyzing path diagrams involving multiple latent variables and their relationships and evaluating how the sample data support the theoretical structure of the hypothesis [85]. Partial least squares structural equation modeling (PLS-SEM) can be implemented in SmartPLS 3.0 software for the hypothesis testing of difficult-to-measure latent variables [86]. In exploratory and explanatory research, PLS-SEM is a preferred approach [87], as it can better handle measurement errors associated with small samples and exhibit optimal predictive power [88]. Using the PLS-SEM method in the SmartPLS3.0 software, Lin et al. [89] investigated the influence of institutional pressure on the information security legitimization process and the link between information security legitimization and organizational performance. Huang et al. [52] utilized SmartPLS-SEM to divide the factors impacting workers’ involvement behavior. SmartPLS-SEM has been demonstrated to be useful in investigating the factors influencing rural e-commerce entrepreneurship by returning residents.

4.5.1. Reliability and Validity Test

The PLS-SEM model was created using the SmartPLS 3.0 software (see Figure A1 in Appendix A). The internal consistency test was used to assess the scale’s reliability, and the findings are summarized in

Table 4. Results of reliability and validity tests.

Latent Variables	CA	CR	AVE
REEI7	0.822	0.894	0.738
EO1	0.764	0.864	0.680
SoB2	0.829	0.898	0.746
ESA3	0.823	0.890	0.730
SC4	0.812	0.889	0.727
PS5	0.872	0.921	0.796
IN6	0.714	0.839	0.637

Note: EO¹, Employment obstacles; SoB², Sense of belonging to the city; ESA³, Entrepreneurial networking capabilities; SC⁴, Start-up costs; Ps⁵, Policy support; IN⁶, Infrastructure; REEI⁷, Rural e-commerce entrepreneurship intention.

. The Cronbach’s alpha (CA) and composite reliability (CR) values for each of the latent variables were higher than the benchmark 0.7 [90]. External loading values for each observed variable were greater than 0.7 (the lowest loading value was 0.733), and the average extracted variance values (AVE) for the latent variables were higher than 0.5 (the lowest AVE was 0.637), as shown in Figure A1 [91]. The findings suggest that the study’s scale and model are both reliable and valid. As shown in

Table 5. Mean square root of extracted variance and factor correlation coefficient.

Latent Variables	H	H1	H2	H3	H4	H5	H6
REEI	0.859
EO	0.853	0.824
SoB	0.096	0.070	0.864
ESA	0.201	0.188	0.009	0.854
SC	−0.675	−0.650	−0.176	−0.180	0.852
PS	0.558	0.502	0.092	0.181	−0.360	0.892
IN	0.770	0.711	−0.166	0.202	−0.572	0.516	0.798

Note: Diagonal elements are the square root of average variance extracted (AVE).

, the square root of the AVE for each latent variable is greater than the correlation coefficient with the other latent variables, showing that the model has excellent discriminant validity and no multicollinearity [92].

Common method bias (CMB) may arise during data collection and dramatically affect the validity and objectivity of the study [92]. In order to reduce the impacts of common method bias, procedural and statistical controls were applied [93]. To reduce the psychological burden, the respondents were informed in advance that the survey was anonymous and would be for academic purposes, and that participation in the survey would have no impact on their work or lives. Feedback from the pretest was used to improve the scale and questionnaire text, ensuring comprehensibility and readability of the survey. The Harman one-way test for exploratory factor analysis of all variables was also performed [93], and the results are shown in

Table 6. Total variance explained.

Component	Initial Eigen Values			Extraction Sum of Squared Loadings
	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	7.651	36.434	36.434	7.651	36.434	36.434
2	2.332	11.107	47.541	2.332	11.107	47.541
3	2.063	9.826	57.366	2.063	9.826	57.366
4	1.602	7.627	64.994	1.602	7.627	64.994
5	0.976	4.649	69.643

. The variance explained by the first factor was estimated at 36.43%. The value is less than the 40% determination criterion, indicating no serious common method bias in the sample data.

4.5.2. Hypothesis Testing

SmartPLS 3.0 software was used to perform operations on the built model (see Figure A1 of Appendix A), and the results are presented in

Table 7. Results of hypothesis testing.

Hypotheses	Path	Path Coefficient	t-Value	p-Value	Hypothesis Support?
H1	EO→REEI	0.508	6.139	0.000	Y
H2	SoB→REEI	−0.021	0.539	0.590	N
H3	ESA→REEI	0.004	0.103	0.918	N
H4	SC→REEI	−0.156	2.461	0.014	Y
H5	PS→REEI	0.113	2.544	0.011	Y
H6	IN→REEI	0.264	3.482	0.001	Y
H7	SC→PS→REEI	−0.040	2.375	0.018	Y

. The R² (R-squared) was calculated at 0.803, indicating an excellent explanatory power of the model [90]. H1, H4, H5, H6, and H7 passed the hypothesis testing (p-value ≤ 0.05 [90]), while H2 and H3 were rejected (p-value > 0.05 [90]). The model’s overall fit was also analyzed. The SRMR value was 0.067, suggesting that the model fits well with the data [94].

4.6. Research Results

4.6.1. Significant Hypotheses

• Urban employment obstacles to rural migrants engaging in rural e-commerce entrepreneurship have a significant positive influence, which is consistent with the results of Chen and Cao [95]. When obstacles in urban employment develop (e.g., job market fragmentation by the urban labor force and the rejection of low-quality workers by upgrading industrial structures), the obstacles to urban employment will rise [96]. As a result, returning migrants may opt to return home to establish a rural e-commerce business for exploring new employment prospects.
• Policy support was found to have a strong positive impact on returning migrants engaging in rural e-commerce entrepreneurship. This finding is similar to the conclusions of Zhu et al. [71], Darnihamedani et al. [69], and Zhang et al. [97]. Returning residents who establish their own business may face initial challenges, such as a lack of funds, projects, and entrepreneurial abilities. The government can adopt policies, provide guidance and incentives, and take other steps to address these issues and support entrepreneurship among returning migrants [98].
• Start-up costs have a considerable negative impact on returning migrants engaging in rural e-commerce entrepreneurship. Previous studies by Bao et al. [73], Kuang [99], and Zhang et al. (2018) [100] also came to similar conclusions. For rural populations, the cost of entrepreneurship includes the cost of living, the cost of operation, the cost of financing, the cost of failure, and other factors, all of which impact their willingness to start a business [73]. If start-up expenses decrease, rural residents may be more motivated to engage in rural e-commerce entrepreneurship.
• Infrastructure has a substantial beneficial effect on rural residents returning to their hometowns to engage in rural e-commerce entrepreneurship, supporting the findings of previous (e.g., Zhu et al. [71], Zheng and Ruan. [72]). Rural residents are encouraged to return to their hometowns by well-developed infrastructures, such as the living environment, fast and accessible transportation system, and interconnection network [24]. The better the infrastructure is, the higher the likelihood is to return and start a business [70]. The development and utilization of existing resources, the introduction of external resources, the increase in production efficiency, and the promotion of economic interchange may be better facilitated by better infrastructure.
• Policy support mediates the cost of entrepreneurship and rural e-commerce entrepreneurship among returning migrants, similar to the conclusions of Autio et al. [101], Darnihamedani et al. [69], Zheng and Liu et al. [72], and Bao et al. (2020) [73]. The more government-sponsored entrepreneurial policies are implemented, the lower the cost of start-ups is for entrepreneurs. With lower returning start-up costs from government assistance, the start-up finance will become accessible and quicken the process of rural migrants engaging in rural e-commerce entrepreneurship. Our results also confirm this view, showing that policy support can effectively reduce start-up costs and promote entrepreneurship.

4.6.2. Non-Significant Hypotheses

• The sense of belonging to a city did not significantly affect returning migrants engaging in rural e-commerce entrepreneurship. This contradicts Li’s findings [102]. One possible explanation is that rural residents living in cities have relatively homogeneous lifestyles, low levels of material requirements, and mainly subsistence consumption [103], and consequently choose to stay in cities despite a low sense of urban belonging. Another reason may be that the sense of belonging is changing as the world becomes more connected and social media becomes more prevalent. Even though rural residents still feel nostalgic for their hometowns, people’s sense of what constitutes home is becoming less dependent on geography. A sense of belonging will then have less and less impact on returning entrepreneurship.
• Entrepreneurial network capability was found to have no significant positive effect on rural e-commerce entrepreneurship among returning migrants, contradictory to the conclusions of Liu and Chen [59]. One possible reason is that while entrepreneurial network capability can alleviate some of the problems (e.g., lack of entrepreneurial resources) [104], increased government policy support may provide rural residents sufficient support and guidance to solve some entrepreneurial problems. In addition, due to the small scale and low threshold of entrepreneurship and the low operational difficulty in rural e-commerce, having entrepreneurial network capabilities can have little impact on rural residents.

5. Discussions

In our study, five of the seven hypotheses were verified. These hypotheses are assumptions about the effects of variables on returning residents who want to start a rural e-commerce business. Return migrant e-commerce entrepreneurship is favorably associated with urban employment obstacles, policy support, and infrastructure and is inversely connected with start-up costs. The lower the start-up costs, the more likely rural residents are to engage in rural e-commerce. Government support through policies and incentives was also found to mediate the cost of entrepreneurship and rural e-commerce entrepreneurship. We offer the following theoretical and practical consequences based on our findings.

5.1. Theoretical Implications

To analyze the influencing factor of returning migrants engaging in rural e-commerce entrepreneurship, we constructed an influence factor model based on the PPM theory. There are three significant theoretical contributions of this paper. First, this study adds to the body of knowledge on rural e-commerce entrepreneurship. Previous studies (e.g., Zhang et al. [97], Kuang [99], Wang and He [66], and Zhu et al. (2010) [71]) have focused mainly on rural e-commerce entrepreneurship as a bridge for the urban–rural divide and as a means to solving rural employment problems. However, few have focused on the mechanisms affecting rural e-commerce entrepreneurship. This study addresses this research void, providing a novel perspective for decision-makers when developing policies and strategies on rural e-commerce.

Second, based on the push–pull–mooring theoretical model, we conducted an empirical study on the factors that influence rural e-commerce entrepreneurship among returning residents. This differs from other research that examines influencing factors through literature reviews (e.g., Wang and He [66], Li and Xie [105]) and case studies (e.g., Tang and Zhu [40], Han and Li [106]). We also found the mediating effect of policy support between start-up costs and rural e-commerce entrepreneurial intents.

Finally, this study demonstrates that PPM theory provides a scientifically sound framework for identifying and investigating factors affecting rural individuals’ inclination to return to their hometowns and engage in rural e-commerce. This theoretical framework can supplement studies on returning to rural entrepreneurship.

5.2. Practical Implications

This study can help decision-makers identify and address the disconnect between urban–rural communities and promote a more pragmatic and sustainable approach for rural economic development. The findings of this study could be used to develop realistic and more effective strategies to support and motivate returning rural inhabitants to actively participate in the economic development and construction of rural areas. Therefore, we make the following recommendations based on the findings of this study.

First, governments and businesses should pay attention to the challenges rural residents face in finding work in cities. Our findings demonstrate a strong link between urban employment obstacles and rural e-commerce entrepreneurship among returning migrants. Employment obstacles were a major reason for migrants to return to their hometowns [53]. Government and enterprises should boost improvements in employment and entrepreneurship in rural areas, measures should be developed to alleviate the employment obstacles faced by rural residents in cities and to guarantee their working and living conditions in cities. For rural managers and enterprises, the relative lack of manpower in rural areas should motivate and attract rural workers who encounter obstacles to participate in rural economic development.

Second, the government should assist entrepreneurs in lowering the cost of business start-ups and entrepreneurship. According to our findings, the cost of starting a business has a significant negative link with rural e-commerce among returning migrants. When starting a business, returning migrants may encounter high initial costs, operating expenses, relocation and living expenses, failure costs, and other expenditures, affecting their motivation for entrepreneurship—living costs and operating costs having the most impact [73]. To reduce exorbitant rural start-up costs and promote entrepreneurial motivations, the government should provide greater assistance in terms of living costs (e.g., living consumption levels, living conditions) and business operation costs (e.g., human resource services, training services, and operation consulting).

Third, the government should focus on rural e-commerce infrastructure construction. Based on our research findings, infrastructure has a significant correlation with rural e-commerce entrepreneurship among returning migrants. E-commerce infrastructure, such as logistics and storage facilities, could directly impact the development of e-commerce in rural communities and motivate the returning population towards entrepreneurship. The government should concentrate on enhancing the efficiency of logistics transportation and strengthening road traffic infrastructure. Rural e-commerce industrial parks and rural transportation logistics distribution centers should also be established if the conditions are favorable, so as to build a good ecology for the development of rural e-commerce.

Finally, the government should adequately guide and macro-control to formulate effective policies, strengthen support and optimize the environment for rural e-commerce development. Our results show a significant positive correlation between policy support and rural e-commerce entrepreneurship and that policy can have a mediating effect on start-up expenses and entrepreneurship in rural areas. By adopting business-friendly rules, the government can, directly and indirectly, lower the operational and financing expenses and increase participation in entrepreneurship, particularly for returning migrants [73]. The government could provide monetary support to new entrepreneurs by providing special loan rates and grants, offering tax benefits to start-ups, lowering land costs for new businesses, and providing free guidance on e-commerce operations. Entrepreneurial training and the education system can be further improved by establishing a special training fund to give entrepreneurs a certain amount of training subsidies, thereby reducing the cost of all aspects of entrepreneurship for rural residents and greatly increasing the incentive to start a business.

6. Conclusions

The development of rural e-commerce can help secure the long-term growth of rural communities. Rural e-commerce offers a novel approach to economic growth in rural regions and has been one of the most economically productive approaches. Understanding how to effectively promote and sustain the growth of rural e-commerce is therefore extremely important.

In China, the main obstacle to rural e-commerce development is the lack of human resources. Most rural residents prefer to leave their hometowns to seek opportunities in the city. If this issue is not addressed, the rural economy may lose its driving force, causing development to stagnate and further widening the economic disparities between urban and rural communities.

This study used a new approach based on the push–pull–mooring theory to better understand the factors influencing rural e-commerce entrepreneurship among returning migrants. The empirical results show that urban employment obstacles, policy support, and infrastructure have significant positive correlations with return migrant entrepreneurship, while start-up costs have a significant negative relationship. Furthermore, we found that policy support has a mediating effect between start-up costs and rural e-commerce among returning migrants. The findings of this study add to the body of knowledge on rural e-commerce entrepreneurship.

To promote sustained rural economic development, the government should implement rural e-commerce policies that incentivize entrepreneurship and support returning migrants in setting up their businesses. Rural communities should continue investing in infrastructure development and improving the business and living conditions to increase their human capital and obtain long-term sustainable growth of their communities.

This study has several limitations. First, the survey respondents were from developed rural districts, Jieyang and Zhanjiang in Guangdong Province, China. Among less economically developed rural areas, the results may have considerable differences. Other factors could have a significant effect in resource-poor and poorer rural communities, which may impact the results. Future studies should explore the elements that influence rural e-commerce entrepreneurship in other communities (e.g., less developed areas, geographically smaller communities) and compare the results. Second, the impact of family characteristics was not considered in this study. Rural residents may have varying motivations for choosing to stay or migrate, and many of those motivations are related to family (e.g., elderly parents, small children). When migrants return to their hometown, their decision may be driven more by other motivations (e.g., family-related) rather than the desire to establish a business. Future research can then look into whether family variables play a role in their decision-making and up to what degree. Finally, the questionnaire approach chosen for this study has inherent limitations that may have affected the results. The theme of this research paper is rural e-commerce entrepreneurship among returning migrant workers. Presently, rural e-commerce entrepreneurship is mainly established as e-commerce enterprises selling agricultural products. The reason for this result is that China’s rural land is mainly planted, and with the increasing popularity of the Internet in rural areas, it has broadened the sales channels of agricultural products planted by farmers, which has undoubtedly attracted many farmers to start selling agricultural products online.

However, we believe that simply starting an e-commerce business to sell agricultural products cannot ensure the sustainable development of rural e-commerce and the rural economy, which is one of the purposes of this study. We hope that the form of rural e-commerce entrepreneurship should be pluralistic, which can promote development. Therefore, in order to achieve this goal, we think the first thing to do should be to get more people to start their own businesses, which may lead to the creation of pluralism. Our study of the factors affecting rural e-commerce entrepreneurship was carried out with a broad mindset. However, rural e-commerce entrepreneurship consists of many segments, and in the future, we can carry out further research in these areas. It is known that a new phenomenon has started to emerge in the field of rural e-commerce, where some people show their agricultural products or goods to the external world through live streaming on the Internet, a novel form that allows customers to visualize the characteristics of the goods and improve the credibility of the transaction. For example, in China, from 2019 to 2020, just one live streaming platform company helped poor villages sell goods amounting to CNY 1.999 billion (USD 29.22 million) [107]. In addition, the amount of self-media is starting to rise in rural areas, similarly, and people are using the Internet to propagate and share a rural lifestyle, thus attracting many followers. Moreover, some people make use of resources unique to rural areas and present them on Internet platforms in the form of videos, for example, making traditional rural food and handicrafts. We consider all of the above as examples of rural e-commerce entrepreneurship. These forms of entrepreneurship are very low-barrier and low-tech. Entrepreneurs can even use a smartphone to start a business. By producing interesting and beautiful content to attract the attention of strangers, the entrepreneurs will generate huge business value when they have many fans, which brings more channels for farmers to increase their income, and farmers have gradually changed from mere producers to production operators. In our imagination, self-media and Internet live e-commerce may become a new research direction. We believe they can create great value if integrated into the rural economy. How they are integrated is the key to the study. Big data technologies can be used in subsequent studies to collect more targeted data samples and analyze more factors. Focusing on the social issues generated by the urban–rural divide is extremely important, and promoting the growth of rural e-commerce is an efficient means to address this issue. More studies should explore the various facets of rural e-commerce and develop more diverse rural e-commerce entrepreneurship models to support the expansion and development of the rural economy.