Study on Sustainable Development Strategy of Rural E-Commerce in the Northeast of China—A Case Study of 11 Villages, 11 Towns and 4 Counties

Abstract

Using field research data from 11 towns and 11 villages in 4 counties of Shenyang, data building, coding and analysis were conducted through Nvivo 11 to distill the influencing factors of rural e-commerce development in Shenyang into advantages, disadvantages, opportunities and threats. Combined with the SWOT-AHP model, the weights of each influencing factor on rural e-commerce development were obtained by scoring by experts from five aspects, including government, enterprises, farmers, etc. The results show that the weak infrastructure and high cost of express delivery are important factors affecting the development of rural e-commerce, confirming the folk experience of “to get rich, first build roads”. At the same time, the awakening of brand awareness and the strengthening of technology services are advantages and opportunities for the development of rural e-commerce. Finally, according to the different combinations of influencing factors, we proposed a breakthrough strategy for rural e-commerce development based on “external help + internal drive”, supplemented by “cooperation + demonstration leading” and “industrial upgrading + channel integration”.

1. Introduction

The development of rural e-commerce has great significance in promoting the transformation of the agricultural industry, activating the potential of the rural economy and enhancing farmers’ income. The Chinese government has made important deployments to rural e-commerce development for nine years in a row, and this year it has put forward the key conclusion of “Digital-Business to promote agriculture”, which shows that rural e-commerce has brought significant changes to China. With socio-economic development, Chinese farmers have basically crossed the “primary divide”, characterized by differences in digital devices, and are gradually diverging from the “secondary divide”, characterized by gaps in digital technology use, and are triggering a “tertiary divide”, characterized by gaps in digital income [1]. The emergence and development of rural e-commerce in China has a very important impact on the sustainable development of China’s rural economy, culture and society. According to the “2021 China County Digital Agriculture Rural E-Commerce Development Report”, China’s county online retail sales exceeded 3530.32 billion yuan, up 14.02% year-on-year, and county online sales of agricultural products were 350.76 billion yuan, up 29.0% year-on-year. In order to make the rural e-commerce “cake” bigger, Chinese governments at all levels have started to pay attention to rural e-commerce development and actively seek support space for rural e-commerce [2]. It can be seen that the rural e-commerce economy with Chinese characteristics has played a great role in the historical process of getting rid of poverty and will become an important step on the way to prosperity.

However, there is a huge gap between the south and north of China’s rural e-commerce. As of 2021, there are 5425 Taobao villages in China, and only 15 in the northeast (Heilongjiang, Jilin and Liaoning provinces), accounting for only 0.28% of the total. So, it is important to analyze the influencing factors of rural e-commerce development and choose the path of rural e-commerce development according to local conditions objectively and scientifically. Therefore, the research problem of this paper is to comprehensively analyze the economic, political, institutional and cultural factors affecting the development of rural e-commerce from the perspective of sustainable development through applicable and scientific research methods, and gradually explore the sustainable development strategies of rural e-commerce in Northeast China through the weighting analysis and different combinations of each influencing factor.

This paper has six parts: the second part is a literature review of rural e-commerce research; the third part is the field research situation, research design and model selection; the fourth part is the analysis of influencing factors of rural e-commerce development in Shenyang city; the fifth part is the weight calculation of influencing factors and alternative strategies; the last part is a discussion of breakout strategies for rural e-commerce development in Shenyang city based on the results of the model analysis.

2. Literature Review

To understand the influencing factors of rural e-commerce development objectively and comprehensively, then make path choices for rural e-commerce development, we need to grasp the changes brought by rural e-commerce development to agriculture, rural areas and farmers.

The impact of rural e-commerce development on agriculture is manifested in the provision of a new marketing channel for agricultural products [3], which has a “push-back” effect on agricultural production [4]. Due to the platform mechanism of this sales channel, operators pay more attention to transaction evaluation, and in order to pursue a positive transaction, evaluation will motivate farmers to adopt green production techniques when carrying out agricultural production, thus promoting the quality and efficiency of the agricultural industry and playing a positive role in the restructuring of the agricultural industry [5]. The impact of e-commerce development on rural areas is demonstrated by the fact that rural e-commerce has stimulated rural economic vitality, changed the face of rural life and contributed to the promotion of integrated urban and rural development [6]. In addition, rural e-commerce from the emergence to the mature stage also presents the characteristics of industrial clusters and distribution concentration [7], making some villages rise to fame due to the development of e-commerce, whereby the “Taobao village”, the “e-commerce village”, has become the new business card of the village. Some villages have successfully explored innovative models of rural e-commerce in the form of collective economy, which has led to further expansion of the collective village economy while improving rural habitat conditions and infrastructure [6]. Research between rural e-commerce development and farming subjects has been more extensive, and scholars have not only found that individual characteristics such as prior experience [8], social capital [9], perceived value [10], information literacy [11] and risk preference [12] have significant effects on farming households’ willingness to participate in e-commerce, participation behavior and participation level, but also there is a general consensus that participation in rural e-commerce can promote farming households’ income growth [13,14,15,16], increased employment opportunities [16,17,18] and increased entrepreneurship, and the sense of entrepreneurship [19,20] formed a general consensus, which was confirmed by cross-sectional or panel data from multiple provinces and regions. These studies show that rural e-commerce is not only an important force for promoting rural economic development, but also an important driving force for transforming traditional farmers into new farmers. This is the basis for China’s proposal of “promoting agriculture through digital business”.

Moreover, rural e-commerce is a systematic and organic whole, which is simultaneously influenced by both the internal characteristics of the subject and the external rural environment [21]. Concerning the influencing factors of rural e-commerce development, the above studies mainly focus on the internal characteristics of e-commerce operators while ignoring the influence of the rural external environment on rural e-commerce development. As far as the study area is concerned, most of the research areas selected for the current study are developed e-commerce regions, compared to the more urgent needs of the slow-developing rural e-commerce regions. The existing studies on rural e-commerce development strategies in a region are mostly based on qualitative analysis [22,23], and a combination of qualitative and quantitative methods is needed to deeply analyze rural e-commerce development issues.

Therefore, this paper is innovative in the following ways: first, the research subject complements the current research cases in the slow-developing rural e-commerce regions, which has a “carbon in snow” effect on the rural e-commerce research in these regions. Second, the research perspective is to treat the county as a whole in the study of rural e-commerce and to explore the factors influencing the sustainable development of rural e-commerce, which is more in line with China’s national conditions. Third, the research methodology overcomes the subjectivity of qualitative analysis in the study of rural e-commerce development and uses a combination of qualitative and quantitative methods to standardize and demonstrate the influencing factors and strategic choices of rural e-commerce development in the region, providing a set of scientific and complete analysis methods for the development path selection of other regions.

3. Research Design and Model Selection

In 1971, Andrews first proposed the SWOT analysis method, which became a classic theory for systematically analyzing the internal capabilities and external environment of things [24]. The development of rural e-commerce in Shenyang is affected by both internal and external conditions, so the SWOT matrix is applicable here. The Analytic Hierarchy Process (AHP) is a common analytical measure in social science research which measures the relative strength of indicators [25]. This study organically combines SWOT-AHP. On the one hand, Nvivo 11 was used to analyze the text of the research materials and extract the internal and external influencing factors of rural e-commerce development in Shenyang city to obtain the SWOT matrix; on the other hand, Yaahp11 was used to measure the relative importance of the extracted influencing factors using the AHP model [26], and the question of “breakout strategy selection” was answered through the systematic construction of the main influencing factors.

3.1. Sample Selection

Based on the principle that the selected case fits the research problem and is typical and representative [27], from March to September 2021, research on the development of e-commerce was conducted in Damintun Town, Fangjinniu Village, Xinglongpu Town, Erlama Village and Xinnong Town, Kaoshantun Village in Xinmin County, Shenyang; in Zhangjiabao Village, Dengshibao Town, Lamahe Village, Yiniubao Town and Dasheshan Village, Dingjiafang Town in Faku County, as well as Jinshanbao Village, Lengzibao Town, Yangshibao Town, Yangqian Village and Panjiabao Town, Yujiatai Village in Liaozhong County, and Latahu Village, Huangjia Town and Shanjia Village, Xinglongtai Town in Shenbei County (

Table 1. Distribution of research subjects and research forms.

Levels	Time	Research Subjects	Forms
Village Research	March 2021–May 2021	Zhangjiabao Village, Lamahe Village, Jinshanbao Village, Yujiatai Village, Yangqian Village, Latahu Village, Shanjia Village, Fangjinniu Village, Erlama Village, Kaoshantun Village, Dasheshan Village	Field Research
Town Research	June 2021–July 2021	Dengshibao Town, Yiniupu Town, Dingjiafang Town, Lengzibao Town, Panjiabao Town, Yangshibao Town, Huangjia Town, Xinglongtai town, Damintun Town, Xinglongpu Town, Xinnong Town	In-depth Interview
County Research	August 2021–September 2021	Liaozhong County, Faku County, Xinmin County, Shenbei County	Field Research + In-depth interviews

Note: The research records, interview transcripts, audio recordings, pictures and videos were used to create a database through Nvivo 11 case analysis software, including 276 pictures, 14 audio recordings and 41 documents, totaling 193,453 words.

). These four counties cover different fields such as planting, farming and agricultural processing industry, which are good representatives of Liaoning Province and even Northeast China.

3.2. Data Collection

The scientific nature of the case study methodology lies in the organic combination of research data and secondary sources, forming an “evidence triangle” [27]. The validity and reliability of the study can be ensured by using suitable analytical methods within the theoretical framework and by combining the data for justification [28]. To this end, research was conducted in 11 villages in 4 agricultural counties and 11 towns through field observation and in-depth interviews (Table 1), resulting in 193,500 words of written research materials. In addition to the textual information, 276 pictures and 14 audio recordings were collected. To ensure the accuracy of the data, the data collection process strictly followed Eisenhardt’s “24-h principle” [29]. In addition, to enhance the confidence of the results, 19 additional relevant reports from Xinhua News Agency and Zhejiang Daily were collected as supplementary verification materials (The following supporting information can be downloaded at: Xinhua News Agency, “From “Li Ziqi” to “Zhang Classmate”: The nostalgia code behind China’s grassroots netizens”. http://www.news.cn/2021-12/25/c_1128200671.htm (accessed on 25 December 2021); Zhejiang Daily, “Upgrade anti-poverty fund Ali aimed at rural revitalization of this “hot land”. http://zjrb.zjol.com.cn/html/2021-05/18/node_18.html (accessed on 18 May 2021); China Youth Daily, “Pinduoduo set up “10 billion agricultural research special”, profits priority into the plan”. https://s.cyol.com/articles/2021-08/24/contentr5OeZlcM.html (accessed on 24 August 2021)), but not as the main argumentation materials.

3.3. Data Coding and Analysis

According to the rooting research methodology, the acquired data were open-coded and spindle-coded, and after coding, the established SWOT matrix was tested for saturation, and the data were updated and added until the model was saturated [27].

3.3.1. Open Codes

According to the principle of open coding, all the information was broken up and given concepts, reassembled according to the concept classification and multiple data were made to form an evidence chain by establishing a case study database [29], and the 193,500 words of textual information obtained from the research were decomposed and labeled and 378 concepts were extracted. Of these, 317 concepts were used for modeling, and the remaining 61 concepts were used for saturation testing of the model (see

Table 2. The process of refining the main concepts of influencing factors for rural e-commerce development in Shenyang (partial).

Dimensions	Spindle Codes	Research Subjects
Strengths	Based on agricultural industries	Greenhouse vegetables are the leading industry in Fangjinniu village, with 1200 greenhouses covering 767 hectares and producing 100 million kilograms of greenhouse vegetables annually. Available for e-commerce sales are mainly cucumbers, tomatoes, peppers, kidney beans, cantaloupes, grapes and other conventional fruit and vegetables (FJN-DMT-XM).
	Brand awareness is increasing	Our village has registered the trademark of “Xingjiusheng” agricultural products, and we plan to package our agricultural products and sell them through the Internet to broaden the sales channels of agricultural products (ELM-XLB-XM).
Weaknesses	Shortage of rural e-commerce professionals	Our village lacks professionals in e-commerce and live streaming. Especially during COVID-19, it is more difficult to sell agricultural products (ELM-XLB-XM).
	The degree of integration of one, two, three industries is not high	We feel that the main constraint to the development of agricultural products e-commerce is the difficulty of transforming primary agricultural products to agricultural commodities suitable for online sales. Bulk millet cannot be retailed and requires packaging and machinery and equipment (LMH-YNB-FK).
Opportunities	School and government cooperation enhanced	We have participated in the e-commerce training organized by Xinmin City. At that time, it was an e-commerce training in cooperation with the government and some universities, and the school used it as an internship site (YJT-PJZ-LZ).
	Develop rural e-commerce development plan	The county government will make the development of rural electric business a key task and scientifically plan the construction of electric villages in conjunction with the development trend of agriculture and rural areas in the next decade or longer (Liaozhong County Government Seminar).
Threats	The high cost of express logistics	The development of the electric business industry in Kaoshantun is limited by the cost of express delivery. Strawberries want to be sent out only by express delivery, and the cost of express delivery is more expensive than strawberries (KST-XNX-XM).
	First secretary articulation issues	We are concerned about whether there will be a replacement for the first secretary when his term expires. First secretaries are generally expiring this year; will the next secretary come and still be able to take over? (DSSZ -DJFZ- FK)

Note: The source codes of the evidence examples are noted according to “Village–Town–County“, for example, “FJN-DMT-XM“ is “Fangjinniu Village–Damin Tun Town–Xinmin County“. For reasons of space, only some examples of evidence are taken from this table.

for the coding process).

3.3.2. Spindle Codes

The 317 concepts formed by the open coding were further summarized into 24 main concepts using the SWOT model framework (Table 2), which are the strengths, weaknesses, opportunities and threats of rural e-commerce development in Shenyang. For a clear visual representation, the area size of each main concept is visualized and outputted corresponding to its frequency of occurrence (as in Figure 1).

3.3.3. Coding Saturation Test

To check the saturation of the open coding and spindle coding, the 61 reserved open codes were compared with the spindle coding concept, and no new dimensional relationships were found. Therefore, the above coding extraction is saturated.

3.4. Model Selection

The SOWT analysis alone is inevitably challenged by the strong subjectivity, and the SWOT-AHP model, an accepted social science research method in academia, responds well to this challenge. Moreover, it has been applied in many famous case studies around the world, such as the analytical investigation of seafarer casualties in the Istanbul Strait [26], the selection of forest farm development strategies in Finland [30] and the exploration of possible strategies to increase the public acceptance of FCEV and hydrogen economic development in Korea [31]. This hybrid application approach improves the qualitative information base of the strategy selection process, and the two-by-two comparison required by the hierarchical analysis method (AHP) enables the experts involved in scoring to think critically and thus analyze the situation more accurately. The SWOT-AHP model can determine the priority of internal and external influencing factors of rural e-commerce development in Shenyang and make them metric, which excludes personal subjective preferences and overcomes the drawbacks of qualitative analysis. Therefore, applying this model to analyze the influencing factors and development path options of rural e-commerce development in Shenyang is possible to meet the research objectives and obtain scientific answers.

4. Analysis of Factors Affecting the Sustainable Development of Rural E-Commerce in Shenyang Area

After extracting the main concepts, the number of reference nodes of the main concepts under each dimension is arranged in descending order and the first four main concepts are taken as the main influencing factors under this dimension, whereby the SWOT matrix is applied to analyze the influencing factors of rural e-commerce development in Shenyang.

4.1. Strengths of Rural E-Commerce Development in Shenyang (S)

4.1.1. Based on Agricultural Industries (S1)

The agricultural industry is the foundation and support for rural e-commerce development [32], and a good industrial base provides a rich labor force and products for the sustainable development of rural e-commerce. Shenyang City is located in the Liaohe Plain, and the land is concentrated and contiguous, which is conducive to mechanized operation, so the development of agricultural industry has certain advantages compared with other regions. Field research shows that rural agricultural products in Shenyang are rich in categories. Take the village of Fangjinniu in Xinmin County as an example, with 450 hectares of greenhouse vegetable facilities, where the annual gross vegetable product reaches 220 million. The village of Fangjinniu alone produces as many as a dozen types of vegetables that can be sold by electricity suppliers (material source XM-DMT-FJN).

4.1.2. Brand Awareness Is Increasing (S2)

Branding as an intangible asset has a significant contribution to rural e-commerce development [33]. From the current stage of the major e-commerce platform requirements for online sales of agricultural products, brand awareness can be seen to enhance the development of rural e-commerce and is already a necessary condition. Tmall, Jingdong and other e-commerce platforms require online sales of agricultural products to have a trademark registration certificate, and there are certain supportive policies and traffic rewards for national geographical indication products or agricultural products from advantageous areas. Through the statistics of the research materials, we found that the word “brand” appeared as many as 150 times, which shows that the rural areas are currently experiencing a “brand awakening” of agricultural products. For example: “You have to have a “brand” to go online. Our village apples have registered the trademark “Wangguoshi”, passed the green food certification, and are now sold online” (source: XM-XLB-ELM).

4.1.3. Growing Collective Cooperative Economy (S3)

E-commerce is new to rural areas, and farmers are inevitably afraid to “touch the e-commerce” because of the perceived risks [34]. The collective cooperative economy can effectively disperse the business risks of the rural electricity business, so many village collectives began to explore the rural electricity business. By the end of 2021, Liaoning Province had 12,000 villages complete the reform of the rural collective property rights system, with a completion rate of more than 98%, which has grown the collective economy and revitalized collective idle resources. The reform also provides a favorable opportunity for the development of rural e-commerce. Farmers can participate in the business by taking shares and working part-time, not only selling villagers’ agricultural and sideline products, but also solving the problem of surplus rural labor and promoting the return of young farmers by absorbing farmers to work in e-commerce sites. For example, “Dasheshan Village in Faku County sells millet through the village’s e-commerce sales platform. It has solved the employment of more than 50 laborers in the village, increased the collective income of the village by more than 500,000 yuan, and distributed more than 340,000 yuan in dividends to shareholders” (source: FK-DJF-DSS).

4.1.4. Strong Cultural Atmosphere (S4)

The distinctive rural culture of the northeast can be a favorable vehicle to fuel the sustainable development of rural e-commerce. The brisk and hospitable character of the northeast people is known nationwide, and the dialect of the northeast is highly infectious and spreadable. Therefore, the head anchor of the major e-commerce live platform also has a lot of northeastern, for example, “Zhang students” in Liaoning, relying on the sharing of daily life in the northeast to attract 19,154,000 fans. The soft power output of e-commerce culture represented by the unique northeast rural theme output has more advantages in the northeast. E-commerce not only includes the sale of products, but also requires the output of “nostalgia”. Take Yangqian Village in Liaozhong Country as an example: “The 26.67 hectares of water in the village are rippling and present a harmonious appearance of a northern water village, where many people have live broadcasts in summer, attracting many fans to visit and shop here” (source: LZ-YSB-YQ).

4.2. Weaknesses of Rural E-Commerce Development in Shenyang (W)

4.2.1. Lack of Rural E-Commerce Professionals (W1)

The lack of professional talent has seriously hampered the development and growth of rural e-commerce [35]. The lack of rural e-commerce professionals in Shenyang is manifested in three aspects: first, the lack of managers who have e-commerce knowledge, especially grassroots government personnel, whose lack of understanding of rural e-commerce has stifled the idea of e-commerce development. Second, the lack of rural electric business to get rich guides, agricultural traditional enterprises and breeding farmers are mostly focused on expanding the scale of production and broadening the traditional channels. Third, the lack of localized rural e-commerce talent who understand the technology and can operate, as the many rules of the e-commerce platform still have a high threshold for farmers, foreign talent does not adapt and local talent cannot be retained, which are the internal disadvantages of rural e-commerce development. For example, “E-commerce and live streaming are good things, but unfortunately we don’t have such capable people in our village” (source: XM-XLP-ELM).

4.2.2. The Degree of Integration of One, Two, Three Industries Is Not High (W2)

If industry, agriculture and services cannot be integrated, then the sustainable development of rural e-commerce will be hindered, as well as the promotion of the organic linkage of the agriculture and industry and service industry. From the research, poor articulation with industry and the service industry is an important issue that restricts the development of rural e-commerce. The sale of primary agricultural products alone not only has to overcome transportation difficulties, bear high freight costs and the risk of breakage, but also makes the business and consumers face food safety problems. Moreover, the low threshold for primary agricultural products is easily imitated by other regions, resulting in farmers not only not enjoying the benefits of rural e-commerce, but also becoming “runners” due to the increasingly high costs of product promotion and advertising. For example, “In order to solve the problem that bulk millet does not meet the standards of e-commerce sales, our village plans to invest 1.25 million yuan to build a millet processing plant” (source: FK-YNB-LMH).

4.2.3. Weak Rural Infrastructure Development (W3)

Infrastructure such as roads, logistics and communications are prerequisites for the sustainable development of rural e-commerce [36]. Although, as early as 2009, all the main roads in Shenyang’s countryside were hardened, the research found that, in some areas, due to age and the lack of maintenance, coupled with the increase in rural motor vehicles, the roads were severely damaged, affecting the passage of logistics and express vehicles and increasing the breakage ratio and transportation costs of agricultural products. Moreover, the construction of express sites lags behind the development of rural e-commerce, as most villages do not have express outlets, and the county, township and village three-tier e-commerce service system structure has not been built to perfection. Due to the lack of necessary rural e-commerce infrastructure, the e-commerce needs of farmers cannot be effectively met. For example, “The roads in the village are too muddy to walk on in the rain. All couriers have to go to the town to pick them up and the village does not deliver them” (source: XM-XLB-ELM).

4.2.4. Inefficient Use of Dedicated Funds (W4)

The development of e-commerce requires a certain amount of capital investment. In recent years, the government has also increased its financial support for rural e-commerce. However, the research found that the efficiency of the use of project funds is not high, on the one hand, due to the different leading industries in each village, the project unified with the electric business equipment because it does not meet the needs of the village industry and idles; on the other hand, due to the financial constraints at the grassroots level and the weak awareness of electric business, electric business support funds are very prone to misappropriation, making special funds ineffective and seriously hindering the development of rural electric business. For example, “Subsidy funds or special funds for rural e-commerce cannot simply be issued to enterprises or cooperatives, let alone do something else because of a momentary emergency” (source: information from the symposium in Liaozhong county).

4.3. Weaknesses of Rural E-Commerce Development in Shenyang (W)

4.3.1. University–Local Cooperation Enhanced (O1)

Science and technology services, represented by e-commerce training, have a positive and significant impact on farmers’ e-commerce participation behavior [12]. The results of the research show that local governments regularly organize training for agricultural enterprises or breeders in rural e-commerce, usually 1–3 times a year. At the same time, the local university also regularly conducts voluntary training, which covers the relevant content of rural e-commerce. The training has increased the farmers’ understanding of e-commerce, effectively reduced their risk perception and enhanced their access to information, thus promoting the development of local rural e-commerce. Therefore, the strengthening of school–local cooperation is an important opportunity for the development of local rural e-commerce. For example, “In the first half of this year, participated in e-commerce training, they taught us the technology, and we provided internship sites for students to promote each other” (source: XM-DMT-FJN).

4.3.2. Governments at All Levels Introduced Protection Initiatives (O2)

The sustainable development of rural e-commerce cannot be achieved without the support and assistance of the government. The government actively introduced relevant initiatives to help clear the policy barriers to the development of rural e-commerce. Shenyang municipal government attaches great importance to the development of rural electric business, and will support the development of rural electric business in agriculture-related counties, the demonstration village of electric business, electric business industrial park, as well as the main body of electric business cultivation, personnel training subsidies, etc., into the “Shenyang City to implement the Central Document No. 1 to promote the development of modern agriculture a number of policies”. The introduction of this series of favorable initiatives has created a favorable environmental atmosphere for the development of rural electric business. For example, “On 12 March, the secretary of Shenyang Municipal Party Committee went to Faku County to research rural electric business” (source: Faku County Research Symposium Meeting Minutes).

4.3.3. Develop Rural E-Commerce Development Plan (O3)

In 2021, the Shenyang Municipal Bureau of Agriculture and Rural Development and Reform Commission jointly issued the “Five-Years Plan for the Development of Rural Industries in Shenyang City (2021–2025)”, which explicitly calls for accelerating the development of rural e-commerce in Shenyang, cultivating rural e-commerce subjects, building rural e-commerce platforms and optimizing the rural e-commerce environment. The “Five-Years Plan” provides a target for the development of rural e-commerce development in each county and district, and the main responsible persons in each county and district have started to formulate local rural e-commerce development plans according to the content of the higher-level planning. For example, “Fangjinniu Village plans to build a rural e-commerce model with market-oriented operation as the platform, cooperatives and enterprises as the main body, and the fruit and vegetable industry as the basis” (source: XM-DMT-FJN).

4.3.4. Rich and Selective E-Commerce Platform (O4)

Domestic e-commerce companies are taking rural e-commerce as the last “blue ocean”, and the fierce competition for the rural e-commerce market also provides opportunities for rural e-commerce development. To gain an advantage in the rural market competition, major platforms have increased their investment in rural e-commerce. The Alibaba Group’s “Rural Revitalization Fund” is dedicated to practicing common prosperity and helping to revitalize the countryside through rural e-commerce, with a cumulative investment of more than 100 billion yuan to strengthen rural digital infrastructure. The initiatives of the major e-commerce platforms also give agricultural operators more choices when facing e-commerce platforms, and, with each platform focusing on different aspects, they also provide good development opportunities for operators. For example, “We plan to vigorously develop the e-commerce industry, train e-commerce talents, and extensively carry out online sales of agricultural products by relying on the Jindo platform” (source: LZ-PJB-YJT).

4.4. Threats to the Development of Rural E-Commerce in Shenyang(T)

4.4.1. High Logistics Costs of Rural Express (T1)

Rural express costs remain high and the biggest threat to the development of rural e-commerce. Express costs are high for two reasons: first, rural areas are often inconvenient, remote and courier companies coincidentally engage in a “strategic abandonment” of the countryside; second, even if there are courier companies willing to carry out rural business, the main body of e-commerce cannot guarantee the number of couriers shipments and need to bear the higher transport costs. Therefore, to carry out rural e-commerce, enterprises will have to face the courier dilemma, which is to endure the high cost of rural courier logistics. These costs are passed on to consumers and eventually reflected in the selling price of agricultural products, making local agricultural products lose market competitiveness compared to developed areas of e-commerce. For example, “The development of the e-commerce industry in Kaoshantun Village is limited by logistics, and sometimes the courier fee is worth more than this agricultural product” (source: XM-XN-KST).

4.4.2. Over-Reliance on Leading Agricultural Enterprises (T2)

Sustainable rural e-commerce development is the development that takes into account the needs of agribusiness and farmers. The development of rural electric business should be wary of the problem of “strong enterprises and weak farmers”. Rural revitalization should adhere to the principle of “rise for farmers and build for farmers”. If we rely excessively on leading agricultural enterprises, it is often easy to cause the consequences of “rich enterprises” and “poor farmers”. The fundamental goal of enterprises is to create wealth and pursue profits, so when facing rural e-commerce, they are unwilling and will not take out time and resources to drive the surrounding farmers. Moreover, some regions subsidize e-commerce support funds directly to enterprises for convenience, making it even more difficult for farmers to engage in e-commerce for agricultural products after the enterprises that already have a competitive advantage receive the subsidy funds. For example, “there is a rice company in Faku County whose network sales are among the top three in the country, and the company prefers to buy farmers’ rice rather than to have farmers engage in e-commerce activities” (source: Faku County research and discussion meeting minutes).

4.4.3. Serious Homogenization of Rural Agricultural Products (T3)

The problem of homogenization of agricultural products directly affects the growth and long-term development of rural e-commerce. Product homogenization means that they are substitutes for each other. In many cases, the leading industries in a village or township are the same and can offer the same e-commerce products. Product homogenization intensifies competition among farmers, as the low threshold for rural e-commerce allows it to be quickly replicated by other farmers. Therefore, the homogenization of products will eventually be transformed into endless price competition, making the agricultural products’ electric business profits gradually reduce, resulting in the rural electric business “come fast, go fast” disorderly situation. For example: “New Xinnong town and Zhoutuozi town have nearly 4500 hectares of cold rich apples, almost every household has apples, the price is very transparent, there is no profit margin, no one wants to do e-commerce” (source: Xinmin County research talks meeting minutes).

4.4.4. Weak Role of the First Secretary Articulation (T4)

The first secretary plays an irreplaceable role in promoting the sustainable development of rural e-commerce and product incubation and in promoting rural e-commerce development and product incubation. In 2018, the Organization Department of the Shenyang Municipal Committee selected 1818 cadres to serve as grassroots first secretaries in villages, leading the masses out of poverty and helping rural revitalization together with local cadres. However, the first secretary has a general term of three years, and the first batch of the first secretaries expired in 2021; therefore, there is a general problem of retaining the first secretaries. Their departure may cause a lack of rural electricity business, or even a fault line and “abortion” phenomenon. For example, “The first secretary sent down by the province trained us in short videos, live streaming and other content. If the first secretary leaves, I’m afraid there will be no follow-up help” (source: XM-XLB-ELM).

In summary, based on the analysis of the strengths, weaknesses, opportunities and threats of rural e-commerce development in Shenyang, the analysis model of influencing factors of rural e-commerce development in Shenyang in the context of rural revitalization is constructed (as shown in Figure 2).

5. SWOT-AHP Analysis of Rural E-Commerce Development in Shenyang

The influencing factors of rural e-commerce development in Shenyang were obtained above after the SWOT analysis; subsequently, each influencing factor was analyzed and calculated according to the AHP and Fuzzy Comprehensive Evaluation(FCE) using Yaahp 11, and alternative strategies were formulated according to the quantitative analysis results. Meanwhile, a strategic radar map was drawn to provide a decision-making basis for the choice of breakout strategies for rural e-commerce development.

5.1. Building a Hierarchical Analysis Model

A complete hierarchical analysis model is constructed that includes a goal level (decision solution objectives), an indicator level (different factors affecting the decision) and a solution level (feasibility solution selection) which are combined in an iterative manner [25]. In this paper, “the choice of breakout strategy for rural e-commerce development in Shenyang” is taken as the target layer; the four influencing factors of strengths, weaknesses, opportunities and threats are taken as the indicator layer; the components of influencing factors are taken as the third layer; finally, the strengths–opportunities (SOs) strategy, weaknesses–opportunities (WOs) strategy, strengths–threats (STs) strategy and weaknesses–threats (WTs) strategy are taken as the option layer. The constructed model was tested for legitimacy, and the hierarchical structure analysis model was obtained after the test was passed (Figure 3).

5.2. Construction of Judgment Matrix

Based on the hierarchical analysis model, a judgment matrix was constructed and distributed to five experts: representatives of county governments, village secretaries, representatives of production entities, representatives of university experts and representatives of e-commerce enterprises (government is the policy maker, the village head is an important bridge connecting the government and farmers, the representatives of production entities engaged in e-commerce have the deepest experience of rural e-commerce, the university experts are the researchers of rural e-commerce and the enterprises have the most systematic and comprehensive understanding of rural e-commerce). Based on their own knowledge and experience, the experts made judgments and prioritized the factors influencing the development of rural e-commerce at the present stage through two-by-two comparisons, thus obtaining the comparison matrix. The specific basis for quantifying the values between the comparative indicators is shown in

Table 3. Table of quantitative values between comparative indicators.

Factor i Over Factor j	Quantified Values
Equally important	1
Slightly more important	3
Stronger and more important	5
Strongly Important	7
Extremely important	9
Intermediate value of two adjacent judgments	2, 4, 6, 8
Countdown	aij = 1/aji

, and the values are assigned to each influencing factor according to 1 (equally important) to 9 (extremely important) [25].

Taking the scoring of university expert representatives as an example, the judgment matrix will be compared n(n − 1)/2 times according to the principle of two-by-two comparison (n is the number of elements involved in the comparison, here n = 4) and finally the judgment matrix A is obtained (as in

Table 4. Judgment matrix after scoring by university expert representatives.

A	Strengths	Weaknesses	Opportunities	Threats
Strengths	1	3	1/2	1/5
Weaknesses	1/3	1	1/2	1/6
Opportunities	2	5	1	1
Threats	2	6	1	1

).

First, the matrix A is normalized by column to obtain the matrix Z (as in

Table 5. Normalized results of the judgment matrix after scoring the university expert representatives.

A	Strengths	Weaknesses	Opportunities	Threats	ωi	Aωi
Strengths	0.188	0.200	0.167	0.085	0.160	0.142
Weaknesses	0.063	0.067	0.167	0.070	0.092	0.104
Opportunities	0.375	0.333	0.333	0.423	0.366	0.374
Threats	0.375	0.400	0.333	0.423	0.383	0.380

). After that, the eigenvectors ω_i of the matrix Z are calculated according to the arithmetic mean method. Subsequently, the principal eigenvectors Aω_i of the matrix Z are solved, then the maximum eigenvalue λ_max of the normalized matrix is solved and finally the consistency test is performed.

Since:

$$A{\omega }_i={\lambda }_{\max }{\omega }_i$$

(1)

So, calculate the maximum eigenvalue of the normalized matrix:

$${\lambda }_{\max }={\displaystyle \sum _{i=1}^n\frac{(A{\omega }_i)}{n\ast {\omega }_i}}=4.002$$

(2)

Then, the consistency test of the judgment matrix is performed as follows:

• First, the consistency calculation CI:

  $$CI=\frac{({\lambda }_{\max }-n)}{(n-1)}=\frac{(4.0042-4)}{(4-1)}=0.0014$$

  (3)
• Second, the stochastic consistency index RI:
• When n = 4, RI = 0.9 (the reference values are taken from Table 6 below)

  Table 6. Table of random consistency index (RI) values.

  Dimension	1	2	3	4	5	6	7	8	9
  RI	0	0	0.58	0.90	1.12	1.26	1.32	1.41	1.46

  Table 6. Table of random consistency index (RI) values.

  Dimension	1	2	3	4	5	6	7	8	9
  RI	0	0	0.58	0.90	1.12	1.26	1.32	1.41	1.46

• Finally, calculate the CR:

  $$CR=\frac{CI}{RI}=\frac{0.0014}{0.90}=0.0016$$

  (4)

If the CR exceeds 0.1, the consistency test fails, the expert scoring is not credible and a review is usually required [27]. Here, CR = 0.0016 < 0.1, which shows that the judgment matrix has good consistency and the expert scoring results are credible.

In the same way, the consistency test is continued for the judgment matrix of strengths (in

Table 7. Judgment matrix after scoring of strengths influencing factors by university expert representatives.

B	S1	S2	S3	S4
S1	1	1/2	3	1/2
S2	2	1	5	1
S3	1/3	1/2	1	1/4
S4	2	1	4	1

):

The eigenvector ω_i after normalizing the judgment matrix B by columns is:

$${\omega }_i=[0.1962,0.3734,0.3546,0.0758]$$

(5)

$${\lambda }_{\max }={\displaystyle \sum _{i=1}^n\frac{(B{\omega }_i)}{n\ast {\omega }_i}}=4.0155$$

(6)

$$CI=\frac{({\lambda }_{\max }-n)}{(n-1)}=\frac{(4.0155-4)}{(4-1)}=0.0051$$

(7)

See Table 6.

$$CR=\frac{CI}{RI}=\frac{0.0051}{0.90}=0.0058$$

(8)

Here, CR = 0.0058 < 0.1, indicating that the judgment matrix of strengths has good consistency.

Next, the judgment matrix of weaknesses is tested for consistency (in

Table 8. Judgment matrix after scoring weaknesses impact factors by university expert representatives.

C	W1	W2	W3	W4
W1	1	1/3	2	1/5
W2	3	1	4	1/2
W3	1/2	1/4	1	1/9
W4	5	2	9	1

).

The eigenvector ω_i after normalizing the judgment matrix C by columns is:

$${\omega }_i=[0.1083,0.2806,0.5496,0.0615]$$

(9)

$${\lambda }_{\max }={\displaystyle \sum _{i=1}^n\frac{(C{\omega }_i)}{n\ast {\omega }_i}}=4.0140$$

(10)

$$CI=\frac{({\lambda }_{\max }-n)}{(n-1)}=\frac{(4.0140-4)}{(4-1)}=0.0046$$

(11)

See Table 6.

$$CR=\frac{CI}{RI}=\frac{0.0046}{0.90}=0.0052$$

(12)

Here, CR = 0.0052 < 0.1, indicating that the judgment matrix of strengths has good consistency.

Subsequently, the judgment matrix of opportunities is tested for consistency (in

Table 9. Judgment matrix after scoring of opportunities impact factors by university expert representatives.

D	O1	O2	O3	O4
O1	1	4	2	3
O2	1/4	1	1/2	1/2
O3	1/2	2	1	2
O4	1/3	2	1/2	1

).

The eigenvector ω_i after normalizing the judgment matrix D by columns is:

$${\omega }_i=[0.4717,0.1078,0.1644,0.2562]$$

(13)

$${\lambda }_{\max }={\displaystyle \sum _{i=1}^n\frac{(D{\omega }_i)}{n\ast {\omega }_i}}=4.0458$$

(14)

$$CI=\frac{({\lambda }_{\max }-n)}{(n-1)}=\frac{(4.0458-4)}{(4-1)}=0.0152$$

(15)

See Table 6.

$$CR=\frac{CI}{RI}=\frac{0.0152}{0.90}=0.0169$$

(16)

Here, CR = 0.0169 < 0.1, indicating that the judgment matrix of strengths has good consistency.

Finally, the consistency test is performed on the judgment matrix of threats (in

Table 10. Judgment matrix after scoring of threats impact factors by university expert representatives.

E	T1	T2	T3	T4
T1	1	3	4	5
T2	1/3	1	2	3
T3	1/4	1/2	1	2
T4	1/5	1/3	1/2	1

):

The eigenvector ω_i after normalizing the judgment matrix E by columns is:

$${\omega }_i=[0.5462,0.2323,0.0838,0.1377]$$

(17)

$${\lambda }_{\max }={\displaystyle \sum _{i=1}^n\frac{(E{\omega }_i)}{n\ast {\omega }_i}}=4.0511$$

(18)

$$CI=\frac{({\lambda }_{\max }-n)}{(n-1)}=\frac{(4.0511-4)}{(4-1)}=0.0170$$

(19)

See Table 6.

$$CR=\frac{CI}{RI}=\frac{0.0170}{0.90}=0.0189$$

(20)

Here, CR = 0.0189 < 0.1, indicating that the judgment matrix of strengths has good consistency.

Therefore, the judgment matrices of the university expert representatives on the factors influencing the choice of rural e-commerce breakout strategies all passed the consistency test. Due to the reason of space, the specific process of the consistency test for the judgment matrix of other four experts is not listed. The judgment matrices of the five experts were input into Yaapp11, and the results of calculating the weights of the influencing factors of the rural e-commerce strategy selection were obtained (see

Table 11. Calculation results of each weight of factors influencing the choice of rural e-commerce strategy in Shenyang.

Objectives	Guidelines	Guideline Weights	Indicators	Indicator Weights	Combined Weights
Shenyang rural e-commerce development breakout strategy options	Strengths	0.158	S1	0.196	0.031
			S2	0.373	0.059
			S3	0.355	0.056
			S4	0.076	0.012
	Weaknesses	0.356	W1	0.108	0.039
			W2	0.280	0.099
			W3	0.549	0.196
			W4	0.062	0.022
	Opportunities	0.140	O1	0.472	0.066
			O2	0.108	0.015
			O3	0.164	0.023
			O4	0.256	0.036
	Threats	0.346	T1	0.546	0.189
			T2	0.232	0.080
			T3	0.084	0.029
			T4	0.138	0.048

Note: Results are retained to three decimal places.

).

5.3. Strategic Radar Chart Based on the Results of AHP Analysis

Referring to Arslan’s mapping method [26], the radar diagram of the breakout strategy selection for rural e-commerce development in Shenyang was constructed using the influencing factor with the highest weight among the four dimensions as the representative of that dimension (Figure 4).

From the figure, the weak rural e-commerce infrastructure has become the biggest factor limiting the development of rural e-commerce in Shenyang. The study confirms the folk proverb “to get rich, first build a road”, and the “road” here includes not only roads, but also networks, e-commerce service centers, logistics sites and other agricultural products out of the village into the city “access road“. Second, the high cost of rural express logistics is also an important factor affecting the development of rural e-commerce, which shows that there is a close link between infrastructure construction and logistics costs. Then, the brand awareness of rural agricultural operators is obviously improved, and they are potential rural e-commerce business subjects, thus their “brand awakening” will boost the development of rural e-commerce. Finally, with the strengthening of science and technology services and school–local cooperation, the services will gradually explore a rural area to provide students with internship opportunities, allowing the school in rural areas to carry out e-commerce training on a “win-win” road.

5.4. Reliability of Test Results

The judgments of the experts in the five aspects are ranked in terms of alternatives using the method of group decision expert data aggregation. First, the same weights are matched to the five experts, and the output results are shown in the average weights of experts in

Table 12. Calculation results of the weights of rural e-commerce strategy options in Shenyang.

Alternatives	Average Weight of Experts	Expert Assigned Weights
WTs Strategy	0.434	0.431
STs Strategy	0.234	0.256
WOs Strategy	0.193	0.186
SOs Strategy	0.139	0.127

Note: Results are retained to three decimal places.

. Secondly, considering the reality that e-commerce operation enterprises and production and operation subjects have more contact with rural e-commerce, a weight of 0.3 is assigned. The village secretary plays a top–down role in rural e-commerce and is assigned a weight of 0.2. University experts with theoretical research on rural e-commerce and representatives of district and county governments with in-depth knowledge of policies were assigned a weight of 0.1. After assigning weights to each of them, the group decision calculation was carried out and the output results are shown in Table 12.

According to the above table, the ranking of breakout strategies for rural e-commerce in Shenyang is consistent, both in terms of average and specified weights, and the ranking is the WTs strategy, WOs strategy, STs strategy and SOs strategy according to the degree of importance. This also indicates that the expert scoring and calculation process is scientific and ensures a good reliability.

6. Strategic Choice of Rural E-Commerce Breakthrough in Shenyang under the Background of Rural Revitalization

After the above analysis and calculation, the rural e-commerce development strategy in Shenyang should be based on the WTs strategy of “external help + internal drive”, supplemented by the WOs strategy of “cooperation + demonstration leading” and the STs strategy of “industrial upgrading + channel integration”. The STs strategy of “industry upgrading + channel integration” is complementary. At the same time, the SOs strategy of “courageous experimentation + reform and innovation” should be considered.

6.1. Prioritize the Development of “External Help + Internal Drive” WTs Strategy

The lack of a rural e-commerce infrastructure that can function effectively restricts access to a portion of the online market channels and hinders the online circulation of agricultural products. This prevents rural areas in Shenyang from accessing a fair-trading environment, equal market demand and reasonable trading results as in other regions. As a result, the transaction costs of rural e-commerce in the northeast, represented by the rural areas around Shenyang, are much higher than those in the south, and the higher transaction costs reduce the economic value and transformation efficiency of rural e-commerce. So, how to crack the current dilemma? They should “rely on external support, to achieve endogenous drive” to inclusive innovation to make up for the weak rural infrastructure and the lack of e-commerce talent brought about by internal disadvantages, to reduce the high cost of logistics, enterprise strong farmers weak to rural e-commerce development brought about by the threat of external environment and gradually realize the self-empowerment of rural e-commerce business entities.

Since, rural infrastructure is a public good, positive externalities and public goods are its basic attributes. Therefore, the government should be the main body to strengthen the construction of rural e-commerce infrastructure and should continue to increase the investment in rural e-commerce infrastructure through both policy and market means to continuously improve rural infrastructure. For the market economy, this means building the county, township, and village three e-commerce service system and the agricultural logistics system, which are dedicated to reducing logistics costs and transaction costs. At the same time, promoting the establishment of rural e-commerce associations and other public welfare organizations, accelerating the pace of endogenous drive, creating a strong e-commerce atmosphere, strengthening the guidance and support for enterprises or farmers willing to engage in rural e-commerce and focusing on training and incubating local e-commerce talent. In addition, the development of rural e-commerce should also be endogenously driven to push the boundaries, encourage mutual exchanges and learning among rural e-commerce operators and constantly promoting the reform and innovation of rural e-commerce business models.

Finally, the WTs strategy is summarized as the “external help + internal drive” model of “government investment + enterprise construction + association support + farmer innovation”.

6.2. Auxiliary Development of WOs and STs Strategies

6.2.1. WOs Strategy of “Collaboration + Demonstration Leadership”

The calculation results in the Section 5 show that science and technology services and school–local cooperation are the biggest opportunities facing the development of rural e-commerce in Shenyang, while the lack of rural e-commerce talents is a serious disadvantage limiting the development of rural e-commerce. Therefore, it is necessary to actively use external opportunities and try to make up for internal disadvantages. First, we need to continue to establish and strengthen school–site cooperation, take advantage of favorable opportunities to carry out rural e-commerce training, encourage research institutes to offer rural e-commerce courses for agricultural business entities and provide learning opportunities for farmers in need. Second, the need to strengthen school–enterprise cooperation, promoting the establishment of school-related majors in rural areas to establish e-commerce internship base through the school to deliver rural e-commerce talent for enterprises. Third, give full play to the positive role of role model demonstration and social learning for farmers to accept new things and adopt new technologies, increase the investment in help, cultivate and establish rural e-commerce and form a good atmosphere for e-commerce business in rural areas.

6.2.2. STs Strategy of “Industrial Upgrading + Channel Integration”

The core idea of the STs strategy is to “use own advantages to mitigate external threats”. Industrial advantage is an important advantage of northeast rural e-commerce development, but the high cost of logistics has cut off the “access” of northeast agricultural products from rural to urban areas. Moreover, primary agricultural products are not easy to preserve or transport, have low added value, serious homogenization and many other problems; thus, simple primary agricultural products are not the future of rural e-commerce. Therefore, to mitigate external threats, we should encourage the upgrading and industrial integration of agricultural industries in Northeast China, improve the processing capacity of agricultural products and increase the added value of agricultural products. Although not all farmers are likely to engage in rural e-commerce, as a new industrial model and form of economic development, we should encourage qualified business entities to actively try rural e-commerce and support farmers to participate in some aspect of rural e-commerce through village collective cooperative organizations. Through the development of rural e-commerce, farmers can be provided with a new sales channel for agricultural products to promote and “can grow”, while the traditional farmers “can operate” the transformation of modern farmers.

6.3. The SOs Strategy of “Courageous Experimentation + Reform and Innovation” Is Also Considered

Social innovation based on internal strengths and external opportunities is an important way out for the development of rural e-commerce in the northeast. Social innovation includes government innovation, organizational innovation and individual innovation. The government should break the traditional thinking of conformity, increase the reform of rural e-commerce, introduce policies favorable to the development of rural e-commerce and focus on the excavation and cultivation of new models. Organizations and enterprises should take advantage of the industry, with the power of research institutes to accelerate investment in the research and development of e-commerce agricultural products to speed up the renewal of products and push the new. Individuals should take advantage of the favorable opportunities provided by the government and associations to conduct useful explorations of rural e-commerce development models. The rapid changes in Internet information technology, represented by rural e-commerce, also offer the possibility of “overtaking” the northeast’s rural e-commerce development. The sustainable development of rural e-commerce can only be promoted through the collaborative innovation of government, organizations and individuals, combining the characteristics of the region and overcoming the traditional path dependence.

7. Conclusions

Rural e-commerce development is conducive to driving China’s countryside toward affluence, and sustainable rural e-commerce development should consider the interplay of strengths, weaknesses, opportunities and threats. Moreover, the basic conditions of each region in China are very different, and the choice of sustainable rural e-commerce development strategies may change as a result. Although this paper provides a methodological reference for rural e-commerce development strategy selection, it should not be dogmatic and rigid in choosing e-commerce development strategies. While promoting rural e-commerce development according to local conditions, we should also be wary of social problems such as the widening income gap among farmers, the disorderly expansion of industries tending to profit and the pollution of rural living environment arising from rural e-commerce development.