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Article

Face or Relational Benefits? Research on the Influencing Mechanism on Repurchase Intention for Agricultural Inputs

by
Chen Gao
,
Gang Li
,
Yaolin Du
* and
Yaru Wanyan
School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(20), 15137; https://doi.org/10.3390/su152015137
Submission received: 20 August 2023 / Revised: 17 October 2023 / Accepted: 18 October 2023 / Published: 22 October 2023
(This article belongs to the Special Issue Sustainable Marketing in China)
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Versions Notes

Abstract

:
Drawing insights from interpersonal relationship theory and relationship marketing theory, this study investigates the impacts of “face” and relational benefits on farmers’ repurchase intentions for agricultural inputs, and the moderating effect of relational benefits on the relationship between face and repurchase intention. A survey method was employed to test the hypotheses and data were collected from a sample of 578 farmers in rural China. The findings obtained through hierarchical regression analysis indicated that face and relational benefits (including social benefits and special-treatment benefits) exert positive effects on farmers’ repurchase intentions. However, relational benefits negatively moderate the relationship between face intentions and repurchase intention. This research sheds light on the dilemmas faced by farmers when choosing between maintaining face and seeking actual benefits while making repurchase decisions related to agricultural inputs. Moreover, the results contribute to the existing literature on the marketing of agricultural inputs and offer valuable practical implications for agricultural retailers.

1. Introduction

With the development of the economy and government support, the agricultural market in China has witnessed rapid growth in recent years. Consequently, numerous retailers have entered the agricultural market, and they are eager to reduce customer costs and enhance their competitive advantages. Previous studies have demonstrated that retaining existing customers is more cost-effective than acquiring new ones, and maintaining existing customers is less expensive than attracting new ones [1,2]. As a result, it has become crucial for agricultural retailers who seek to expand their market shares to focus on maintaining and strengthening farmers’ repurchase intentions.
Farmers’ repurchase intentions for agricultural inputs signify their inclinations and desires to sustain ongoing relationships with specific agricultural retailers. Once such a relationship is established, farmers repeatedly purchase agricultural inputs such as fertilizers, pesticides, and seeds from the same retailers.
The concept of “face,” deeply rooted in Chinese culture, plays a significant role in shaping farmers’ repurchase intentions. Face is defined as the recognition given by others to an individual’s social standing and position [3]. In China, face is a fundamental element of interpersonal dynamics, signifying social status and reputation earned through achievements in society [4]. From the perspective of interpersonal interactions, face influences farmers’ status in social networks, determining their choices of social relationships and shaping their interactions within society [5]. Additionally, from the standpoint of social resources, face holds the value of a “special currency” in Chinese society [6], influencing the resources that farmers can access through their social relationships [4]. As such, face emerges as a critical factor in farmers’ decision-making processes insofar as it affects the continuity of their relationships with particular agricultural retailers.
Relational benefits arising from interactions with agricultural retailers also exert a significant influence on farmers’ repurchase intentions for agricultural inputs. These benefits encompass social benefits and special-treatment benefits [7]. Within the domain of agricultural marketing, relational benefits refer to the emotional satisfaction that farmers experience during their interactions with agricultural retailers, including feelings of emotional support, recognition, care, and friendship. Additionally, special-treatment benefits encompass economic advantages and personalized benefits offered by agricultural retailers, such as price concessions and more convenient services [7,8]. As a result, relational benefits encompass the emotional contentment, economic advantages, and personalized perks that farmers receive throughout their transactions with agricultural retailers, thereby directly influencing their intentions to repeatedly purchase agricultural products from the same retailers. These relational benefits play crucial roles in fostering positive and enduring relationships between farmers and agricultural retailers, contributing to the likelihood of continuing business between the two parties.
Prior studies have primarily concentrated on examining the direct and indirect effects of face and relational benefits on consumer behavior and customers’ repurchase intention in the realm of online marketing [9,10]. However, in the domain of agricultural marketing, there is a growing interest among researchers in understanding the distinct characteristics of farmers’ repurchasing behavior [11]. Despite the increasing body of literature on this topic, certain aspects concerning the impact of face and relational benefits on farmers’ repurchase intentions remain unexplored.
First, prior studies have given little attention to examining the influence of face on farmers’ repurchase intentions. Face, as a fundamental element of Chinese rural society, significantly shapes farmers’ behavior. Thus, delving into the effects of face on farmers’ repurchase intentions can provide valuable insights into how retailers can effectively maintain existing customers in the rural Chinese context.
Second, the specific impacts of different aspects of relational benefits on farmers’ repurchase intentions have not been clearly elucidated. Existing research on repeated purchasing intentions has mostly focused on business-to-business marketing, consumer products retailing in urban areas, or online marketing, with minimal emphasis on rural settings. In this study, we aim to investigate how social benefits and special-treatment benefits individually affect farmers’ repurchase intentions in rural China.
Third, few studies have explored the combined effects of face and relational benefits on farmers’ repurchase intentions. Although both face and relational benefits are vital elements of relationship dynamics in Chinese culture, their joint effects have received limited attention. Investigating the joint impact of face and relational benefits is essential for obtaining a comprehensive understanding of the underlying mechanisms driving farmers’ repurchase intentions.
Drawing upon interpersonal relationship theory and relationship marketing theory, this study aims to fill the gaps in the existing literature by examining the impact of face, investigating the specific effects of different aspects of relational benefits, and exploring the joint influence of face and relational benefits on farmers’ repurchase intentions in the context of rural China. Such investigations are crucial for developing a deeper comprehension of the factors that influence farmers’ repurchasing decisions and can provide valuable insights for agricultural-marketing strategies.

2. Theoretical Base

2.1. Interpersonal Relationships and Face

Interpersonal relationships refer to the cognitive and emotional connections formed through interactions [12]. The closeness of a relationship is influenced by the frequency of interactions and by emotional intimacy [13], which in turn shape individuals’ attitudes and behaviors in social interactions, based on their positions in a network of relationships [14]. Close relationships foster more trust and cooperation than distant relationships [12].
Face reflects an individual’s status in social interactions. Previous studies have emphasized the pivotal role face plays in the dynamics of interpersonal interactions in Chinese society. Liu identified face, personal relationships, and the instrumentality of relationships as key components in the interpersonal relationships in business-to-business marketing in China [14]. Huang classified interpersonal relationships in online marketing into the categories of face, reciprocal norms, and affections, viewing face as a social benefit derived from fulfilling social responsibilities [9]. In rural China, which is characterized as an acquaintance society, relationships are often based on kinship and geographic proximity [15]. Face serves as a signal to demonstrate one’s status and resources, influencing farmers’ decisions and their repurchase intention for agricultural inputs.
Researchers have described the nature of face from three perspectives. The first perspective considers face as an objective evaluation by other people. Face is gained from other peoples’ evaluations of an individual’s morality, social resources, achievements, as well as his/her social role [16]. Face indicates an individual’s status [14] and reputation [17] in a social network. The second perspective applies a self-perception lens to face research. It defines face as an individual’s perception of his/her self image in social life [18]. Like the first perspective, evaluations by significant others have a vital impact on one’s perception of self image [18]. In the third perspective, both objective and subjective views are considered in exploring the nature of face. From this perspective, other peoples’ evaluations provide an objective basis for an individual’s face, and this objective basis affects how the individual will be treated by others in interpersonal interactions. Meanwhile, an individual’s attitudes and behaviors are influenced by his/her perceived face that is gained from interpersonal interactions. In this study, we adopt the definition of face from Liu’s study and define face as an individual’s perception of his/her social status obtained in social interactions [14]. Within the context of Chinese rural society, where interpersonal relationships are significant, farmers are highly motivated to maintain and improve face. Therefore, a farmer’s face plays a substantial role in his/her purchasing behavior.
Previous studies have confirmed face’s impacts on consumers’ attitudes and behaviors. Such studies have found that face could facilitate the establishment of trusting relationships between businesses and their consumers. Through the information contained within face, consumers and businesses could have a better understanding of each other. To maintain or improve face, both businesses and consumers need to consider the other party’s interests and maintain a harmonious relationship [9]. Therefore, face promotes trust between consumers and businesses. Face could also help consumers identify the potential risks of certain products. When face is involved in purchasing behavior, consumers consider whether a product is acceptable to other members of the community. If a buying decision for certain products were to cause a customer to be alienated by the community, the stress and anxiety experienced by this customer would stop him/her from taking that risk [19]. Moreover, prior research has found that a business that respects a customer’s face is more likely to earn that customer’s loyalty to the business. If face is respected by a business, it gives customers pleasant purchasing experiences and makes them willing to build stable relationships with the business [20]. Finally, face reduces the likelihood of a customer withdrawing from a relationship with a business. To maintain one’s own face and avoid embarrassment, a customer will continue the transactional relationship with the business [9].

2.2. Relationship Marketing and Relational Benefits

Berry first introduced the term “relationship marketing” and defined it as a facet of customer relationship management that focuses on customer loyalty [21]. Relationship marketing focuses on establishing long-term brand–customer relationships. Relationship marketing places significant emphasis on the concept of mutual benefits between brands and customers, forming a crucial precondition for the establishment of enduring brand–customer relationships [22]. Prior research has demonstrated a positive correlation between relationship marketing and an increased market share and profitability for a brand [22]. Furthermore, customers derive various benefits, such as price discounts and high-quality services, by engaging in long-term relationships with a brand.
In the practice of relationship marketing, brands frequently employ two key tactics: active communication and the promotion of cooperation with customers [23]. Active communication serves as a means for brands and customers to build a profound understanding of each other. The exchange of information within this communication process contributes to the establishment of enduring relationships. Additionally, promoting cooperation between a brand and a customer facilitates the integration of resources from both parties, ultimately leading to mutually beneficial outcomes for the parties. These strategies play an instrumental role in enhancing the effectiveness of relationship-marketing initiatives, ultimately contributing to the growth and sustainability of brand–customer relationships. Through proactive relationship-marketing approaches, brands can create a loyal customer base, thereby achieving long-term success in the competitive-market landscape [24].
Relational benefits form the foundation of relationship marketing, encompassing the advantages that customers derive from engaging in long-term cooperative relationships with companies [7]. Extensive research has shown that relational benefits have positive impacts on businesses’ market shares, competitive advantages, and customer retention [25]. In this study, our focus is on exploring how farmers’ receipt of relational benefits from agricultural retailers influences their repurchase intention for agricultural inputs. Building on the research of Hennig-Thurau et al. [7], we define relational benefits as comprising social benefits and special-treatment benefits that farmers obtain through their relationships with agricultural retailers. Social benefits refer to the emotional satisfaction farmers experience during their interactions with agricultural retailers, while special-treatment benefits include the economic and customized advantages farmers gain from maintaining their relationships with retailers. Prior research has shown that these relational benefits play a pivotal role in shaping customer satisfaction, commitment, loyalty, and buying behaviors [25,26,27]. As customers experience the advantages of sustained cooperation with particular retailers, they are more likely to feel content with their overall experience, develop a deeper commitment to the brand, exhibit greater loyalty to the retailer, and display positive buying behaviors.
For agricultural retailers, cultivating enduring relationships with farmers can lead to increased market shares and heightened competitive advantages in the agricultural sector. Conversely, for farmers, the array of benefits stemming from a stable cooperative relationship with a retailer further strengthens their inclination to sustain such a connection. By examining the impact of relational benefits on farmers’ repurchase intentions, this study contributes to our understanding of the dynamic interplay between customers and agricultural retailers, shedding light on the factors that drive customer loyalty and foster mutually beneficial relationships in the agricultural market.
In conclusion, both face and relational benefits play significant roles in shaping customers’ attitudes and behaviors. In the context of agricultural marketing, this study specifically focuses on farmers’ repurchase intentions. When farmers contemplate whether to repeat their purchases of agricultural inputs, such as fertilizers, pesticides, and seeds, from particular retailers, they are likely to take into account face and relational benefits. Both face and relational benefits (which encompass social benefits and special-treatment benefits) act as the primary factors stimulating farmers’ repurchase intention. Moreover, relational benefits moderate the relationship between face and repurchase intention. As a result, this paper presents the proposed theoretical model illustrated in Figure 1.

3. Hypotheses Development

3.1. Face and Repurchase Intention

We propose a positive relationship between face and farmers’ repurchase intentions for several reasons. First, when farmers and agricultural retailers mutually respect each other’s face [9], this fosters the development of good relationships between them. These positive relationships facilitate effective communication, allowing retailers to better understand farmers’ requirements for agricultural inputs. The smooth interactions and pleasant consumption experiences make farmers more inclined to choose the same retailers for their subsequent purchases of agricultural inputs.
Second, the experience of being respected by a retailer fulfills a farmer’s need to maintain face, enhancing the famer’s willingness to make repeated purchases from the same retailer. In rural society, where face holds significant importance, farmers are highly motivated to preserve and elevate their social status. When an agricultural retailer shows respect for a farmer’s face, the farmer perceives recognition of his or her standing by the retailer [28]. This fosters a norm of reciprocity, prompting the farmer to reciprocate the respect and to be more inclined to establish a long-term exchange relationship with the retailer [29].
Finally, farmers are more likely to continue purchasing products from agricultural retailers who are recommended by their relatives or friends, as an act of respect toward their face. Recommendations from close friends or relatives help alleviate anxiety during the purchasing process, instilling a sense of security in buying agricultural inputs from a recommended retailer. Additionally, accepting the recommendation reflects the farmer’s recognition of and respect for their relatives’ and friends’ face, which fosters a positive outlook for being respected in return. This positive gesture reinforces the farmer’s repurchase intention with the recommended retailer. Based on these insights, we propose the following hypothesis:
H1: 
Face has a positive effect on farmers’ repurchase intentions for agricultural inputs.

3.2. Relational Benefits and Repurchase Intention

Regarding relational benefits, we propose that the social benefits farmers receive from their interactions with agricultural retailers will have a positive impact on the farmers’ repurchase intentions for agricultural products. The receipt of social benefits leads to an increased sense of familiarity with the agricultural retailer, subsequently reducing the perceived risks during the purchasing process. This heightened familiarity instills a feeling of security, motivating farmers to repeatedly purchase agricultural inputs from the same retailer.
Moreover, social benefits signify that the customer–retailer relationship contains emotional aspects, indicating that both parties have positive intentions toward each other and care about each other’s interests [30]. These emotional connections foster a sense of closeness and trust between farmers and agricultural retailers. Consequently, farmers become more inclined to demonstrate loyalty to such retailers.
Finally, providing farmers with social benefits demonstrates that agricultural retailers value their relationships with the farmers and that they are committed to cultivating long-term, mutually beneficial connections. Through active consumer-relationship-management practices, retailers can encourage farmers to purchase products from them and to maintain stable business relationships. Based on these arguments, we propose the following hypothesis:
H2a: 
Social benefits positively impact farmers’ repurchase intentions for agricultural inputs.
We further argue that the special-treatment benefits that farmers receive from agricultural retailers have a positive influence on their repurchase intentions. Special--treatment benefits encompass economic advantages, such as price breaks and exclusive deals, that customers obtain through their long-term relationships with retailers [31]. The cost savings realized through these special treatments act as a compelling incentive for farmers to maintain stable relationships with particular retailers and to make repeated purchases from them.
Moreover, special-treatment benefits also encompass faster or customized services, which significantly impact farmers’ repurchase intention. Timely service provides farmers with quick responses to their needs, saving their time and minimizing any feelings of inconvenience during waiting periods [32]. In addition, customized services cater to the individual needs of customers. When farmers receive personalized service from agricultural retailers, they perceive that their unique requirements are understood and considered, fostering trust in a particular retailer and reinforcing their inclination to repeatedly purchase agricultural inputs from that retailer.
The combination of actual economic benefits and high-quality services offered through special-treatment benefits serves as a powerful motivator for farmers to make repeated purchases from a retailer who provides such benefits. This positive impact on repurchase intention reinforces the importance of special-treatment benefits in cultivating enduring customer relationships and driving sustained business growth for agricultural retailers. Therefore, we propose the following hypothesis:
H2b: 
Special-treatment benefits positively impact farmers’ repurchase intentions for agricultural inputs.

3.3. Face, Relational Benefits, and Repurchase Intention

Previous studies have demonstrated the existence of two distinct interaction patterns in the relationships between farmers and agricultural retailers, both of which significantly impact farmers’ purchasing decisions [33]. The first pattern is characterized by a face-oriented interaction, driven by the motive to maintain and enhance one’s face. Farmers engaged in face-oriented interactions are highly attuned to information that is related to gaining or losing face [34]. They willingly invest efforts to enhance their face status [35]. The second pattern is a benefits-oriented interaction, propelled by the pursuit of individual interests. In this scenario, farmers evaluate the quality of their relationships with retailers based on the gains and losses associated with such interactions, seeking tangible or intangible benefits from retailers at a low cost [36].
In the context of agricultural marketing, face and relational benefits emerge as two major factors that influence farmers’ purchasing decisions. We argue that relational benefits moderate the relationship between face and farmers’ repurchase intentions. With the economic growth in rural China, farmers’ purchasing decisions for agricultural products are influenced by both face, which captures the interpersonal dynamics in rural society, and the actual benefits obtained from retailers [37]. Consequently, when making purchasing decisions for agricultural inputs, farmers carefully weigh both face and benefits, aiming to strike a balance and to maximize their own profits [38].
For farmers exhibiting a face-oriented interaction pattern, their purchasing and repurchasing decisions are primarily shaped by the desire to maintain and enhance their own face. Nevertheless, they also prioritize obtaining additional benefits from retailers. Agricultural retailers who offer social benefits and special-treatment benefits can fulfill farmers’ emotional and economic needs, leading to positive consumption experiences. Therefore, social benefits and special-treatment benefits strengthen face-oriented farmers’ repurchasing decisions for agricultural inputs.
On the other hand, for farmers characterized by benefits-oriented interaction patterns, their repurchasing decisions are predominantly influenced by benefits obtained from retailers. However, they also seek to safeguard and improve their face. Agricultural retailers who demonstrate respect for their customers effectively fulfill the farmers’ face-related needs, thus facilitating the establishment of stable relationships with farmers. Moreover, social benefits and special-treatment benefits fulfill famers’ needs for actual benefits from retailers. Therefore, for benefits-oriented famers, social benefits and special-treatment benefits also strengthen the relationship between face and repurchase intention.
Based on the above analysis, we propose the following hypothesis:
H3a: 
Social benefits positively moderate the relationship between face and farmers’ repurchase intentions.
H3b: 
Special-treatment benefits positively moderate the relationship between face and farmers’ repurchase intentions.

4. Methods

4.1. Participants and Procedures

The study utilized a stratified sampling method to create representative samples of farmers from three hierarchical levels: provinces, cities, and counties. Agriculturally developed provinces were randomly selected from the eastern, central, and western regions of China, resulting in Hebei Province representing the eastern region, Henan Province representing the central region, and Guizhou Province and Ningxia Autonomous Region representing the western region. Subsequently, 11 cities were randomly chosen from the aforementioned provinces, and 11 counties were selected from each of the 11 cities, forming a final list of 121 counties covering eastern, central, and western China, ensuring comprehensive representation.
The survey was conducted by visiting 605 rural households in the 121 counties and selecting one member who was primarily engaged in agricultural production from each household as the respondent. Well-trained surveyors initially provided a brief introduction to the households about the research and proceeded with the formal survey after obtaining their informed consent. The questionnaires were distributed in a one-on-one, face-to-face manner. This approach was chosen to encourage careful completion of the questionnaires by the households. It also allowed for timely adjustments in the questionnaire-completion strategy based on the cultural literacy of the households and provided the opportunity to promptly address any questions raised by them, ensuring the smooth and effective completion of the questionnaires.
Among the 605 collected questionnaires, 27 were removed due to missing data exceeding 10%, resulting in a final sample of 578 questionnaires, with a response rate of 95%. In accordance with the statistical methodology employed in Sghaier et al.’s study [39], we determined the requisite sample size using G*Power 3.1.9.4 software, yielding a minimum sample size of 91 participants. The distribution of respondents across different regions was as follows: 17% from eastern China, 59% from central China, and 24% from western China, indicating wide geographic coverage and diversity in the sample.
Regarding the sample profile, the majority of farmers were male, constituting 66.78% of the final sample. In terms of age, participants were predominantly middle-aged and elderly, with ages mainly distributed between 37 and 65 years old, comprising 77.67% of the final sample. In terms of education, most farmers had low levels of education, with the majority having received primary, secondary, or middle school education, accounting for 77.33% of the final sample. Overall, the sample demonstrated relatively even distribution and strong representativeness.
Through statistical analysis of the respondents’ demographic characteristics, several notable findings were revealed (see Table 1). In terms of sociological characteristics, the majority of the respondents primarily planted food crops, accounting for 70.24% of the valid sample. Furthermore, most respondents had arable land of less than 15 acres, accounting for 90.83% of the valid sample, with farmers having less than 5 acres of arable land making up 57.61% of the valid sample, suggesting that rural land planting in China is relatively small-scale and farmers’ agricultural purchases are more dispersed. Regarding farming experience, the majority of the respondents had been farming for more than 11 years, making up 76.1% of the valid sample, indicating that farmers possess substantial experience and knowledge about farming products. As for family farming income, the majority fell within the range of CNY 10,000 to 60,000, accounting for 67.13% of the valid sample, indicating that farming income comprises a relatively small proportion of total family income, indirectly suggesting farmers’ relatively diminished interest in farming. These findings provide insights into the potential reasons for the decline of farmers’ intervention in agricultural cultivation.
In conclusion, the sample exhibited wide coverage across different regions, an even distribution across various demographic characteristics, and robust representativeness, rendering it well-suited for analyzing farmers’ repurchase intentions for agricultural inputs within the context of agricultural marketing.

4.2. Measures

To align with the research setting, items on each scale employed in our study were modified to fit the context of agricultural marking in rural China and the language was crafted to ensure clarity and comprehension for the surveyed farmers.
Face is a prominent cultural characteristic that has strong implications for interpersonal dynamics in China [3]. Face was assessed using a four-item scale developed by Liu [14]. The responses were evaluated using a 7-point Likert scale. The scale included the following anchors and their corresponding numerical codes: Strongly Disagree (1), Disagree (2), Somewhat Disagree (3), Neutral (4), Somewhat Agree (5), Agree (6), and Strongly Agree (7). This coding scheme was consistently applied in subsequent 7-point scales.
Relational benefits include social benefits and special-treatment benefits [7]. Drawing from Gwinner et al.’s study [7], we adopted three items to measure social benefits and six items to measure special-treatment benefits. The responses were scored on a 7-point Likert scale.
Three items developed by Guenzi and Georges [40] were used to measure farmers’ repurchase intentions for agricultural inputs from certain agricultural retailers. The responses were scored on a 7-point Likert scale.
Age, gender, education, and the irreplaceability of a specific agricultural retailer were controlled in our study, as prior studies suggested that they could influence farmers’ purchasing behavior [41,42]. Age was measured using four continuous categories (≤36 = 1; 37~46 = 2; 47~65 = 3; ≥66 = 4). A dummy variable was used to control for gender (female = 0; male = 1). Education was controlled by five continuous categories (less literacy = 1; elementary school = 2; junior high school = 3; high school/technical school = 4; diploma and above = 5). Three items developed by Yilmaz and his colleagues [41] were used to measure irreplaceability.

5. Results

5.1. Data-Analysis Method

This study employed reliability analysis, validity analysis, and correlation analysis to assess the quality of the data. Additionally, a hierarchical linear-regression analysis was used to validate the conceptual model and the hypotheses. Reliability reflects the stability and repeatability of the measures, with Cronbach’s α coefficient used as an indicator to measure the internal consistency of the scale. Validity refers to the degree of closeness between the observed results of variable measurement items and their actual characteristics. This study examined the structural validity of the scales, which includes convergent validity and discriminant validity. Correlation analysis measures the degree of closeness between two variables and is quantified using Pearson’s coefficient. While correlation analysis provides a general understanding of the relationship between variables, it does not establish causality. Therefore, a hierarchical regression analysis was conducted on the sample data. Regression analysis uses an approximate estimated mathematical model to represent the linear quantitative relationship between variables. Typically, there can be one or more independent variables, while the dependent variable is often singular. Prior to use, it is necessary to verify whether the data meet the underlying assumptions for conducting linear-regression analysis.
The statistical analysis utilized the average scores from the face, relational benefits, repurchase intention, and irreplaceability scales. Missing data were imputed with the mean of the observed values.

5.2. Common Method Variance

Harman’s single factor test was used to examine the common method variance of the data. All the items in the questionnaire were put together for unrotated factor analysis and released a total of five principal component factors, with the first factor having a variance explanatory power of 26.88%, which was lower than the threshold standard of 40%. Thus, the common method variance was not significant and did not affect the research conclusions of this study.

5.3. Reliability and Validity

This study used internal consistency as the reliability measurement index and measured the structural reliability of the questionnaire by Cronbach’s α coefficient. The reliability coefficient of the five scales used in our study all reached above 0.6, showing good internal consistency (see Table 2). In order to further assess the internal consistency of the scale, the combined reliability (CR) value of each variable was analyzed. The results showed that the CR value of each variable was greater than the standard threshold of 0.7 (see Table 2). Cronbach’s α and CR values showed that the questionnaires had fairly good reliability and consistency, and the stability was also very good.
In the structural validity test, the factor analysis results of the four variables of face, social benefits, special-treatment benefits, repurchase intention, and irreplaceability of agricultural retailers are shown in Table 2. The factor loadings of each variable were greater than 0.7 and much larger than the standard of 0.4. The average variance extraction value (AVE) of all factors exceeded the threshold value of 0.5, indicating that the scale had good convergence validity. In addition, the results of confirmatory factor analysis for the proposed five-factor structure (face, social benefits, special-treatment benefits, repurchase intention, and irreplaceability) demonstrated good fits with the data (χ2 = 149.73, df = 142; RMSEA = 0.07, CFI = 0.95), indicating good discriminant validity. Therefore, the questionnaires had good structural validity.

5.4. Descriptive Statistics

Means, standard deviations, and correlations for the variables are displayed in Table 3. The bivariate results indicated that repurchase intention had positive relationships with face (r = 0.322, p < 0.01), social benefits (r = 0.175, p < 0.01), and special-treatment benefits (r = 0.322, p < 0.01).

5.5. Hypotheses Testing

This study employed hierarchical linear-regression (HLR) analysis using SPSS 20.0 software to assess the data and to evaluate the hypotheses. Following the methodology outlined in Danqual et al.’s research [43], we initially examined the essential statistical assumptions for conducting HLR. Exploratory analyses yielded skewness and kurtosis values of −0.26 and −0.18, respectively, which were well within the acceptable range of −2 to 2. Stem-and-leaf plots further confirmed the absence of outliers. Nevertheless, the Kolmogorov–Smirnov test indicated non-normality of the data (p < 0.001; statistic = 0.22). We then plotted standardized residuals against standardized predicted values of the dependent variable in all the HLR models through which the primary relationships were tested. These plots demonstrated non-random patterns, affirming that the relationships were adequately described by linear models. Additionally, the plots revealed a distribution of dots without a discernible (funnel-shaped) pattern and, thus, evidenced homoskedasticity. Finally, the independence of errors and multicollinearity assumptions were respectively met with Durbin Watson statistics that were approximately 2 and tolerance ≥ 0.2.
The hierarchical regression analysis of this study included eight models, as shown in Table 4. Model 1 represented the regression between control variables and repeated purchase intention. Models 2 to 5 showed the main effects of face, social benefit, and special-treatment benefit on repurchase intention. Models 6 and 7 tested two moderating effects of social benefits and special-treatment benefits on relationship between face and repurchase intention, respectively. To assess the moderating role of interest, we first mean-centered face, social, and special-treatment benefits, which constituted the interaction terms. We then used the mean-centered variables to calculate interaction terms for face × social benefits and face×special-treatment benefits.
As we can see from Model 5, face (β = 0.197, p < 0.01), social benefits (β = 0.265, p < 0.01), and special-treatment benefits (β = 0.057, p < 0.05) each demonstrated significant positive effects on repurchase intention. This indicated that face, social benefits, and special-treatment benefits each promoted farmers’ intention to repurchase agricultural inputs from a particular retailer. Therefore, Hypothesis 1, 2a, and 2b were supported.
Model 6 showed that the moderating effect of social benefit was negative and significant (β = −0.085, p < 0.01) However, the pattern of the moderating effect was opposite to the pattern presumed in Hypothesis 3a. In Hypothesis 3a, we predicted that the social benefits would demonstrate a positive moderating effect. The result in Model 6 presented a negative moderating effect. Model 7 showed that the moderating effect of special-treatment benefit was also negative and significant (β = −0.059, p < 0.01), which was opposite to the effect pattern (a positive effect) predicted in Hypothesis 3b. Possible explanations for these findings are discussed in the following section.

6. Discussion

6.1. Theoretical Contributions

Previous studies showed that face is closely related to customers’ repurchase intention in both business-to-business marketing and online marketing. Liu’s empirical study demonstrated that face can promote companies’ repurchase intention in the context of business-to-business marketing [14]. Similarly, Huang confirmed that face can reduce customers’ withdrawal behavior and increase customers’ repetitive purchase intention in the context of online marketing [9]. In our study, we explored the mechanism of face on farmers’ repurchase intentions in agricultural marketing, advancing prior research by extending the research context and providing a theoretical framework to explain how face impacts farmers’ repurchase intention for agricultural inputs in rural China.
Previous research also highlighted the significance of relational benefits in influencing customers’ repurchase intention, particularly with regard to two dimensions: social benefits and special-treatment benefits [44,45]. The positive effects of social benefits on repurchase intention were verified in the context of online marketing and the traditional service industry [10,46]. Building on this, our study extended prior research to the agricultural-marketing context and confirmed the positive effect of social benefits on farmers’ repurchase intentions.
However, in terms of special-treatment benefits, competing theoretical approaches were observed in prior research. One stream of research argued that special-treatment benefits fulfill customers’ emotional and economic needs and, therefore, enhanced customers’ repurchase intention [47]. Conversely, the other stream viewed special-treatment benefits as short-term economic stimulations that may not be conducive to establishing long-term cooperative relationships between companies and customers, potentially weakening customers’ repurchase intention [48,49]. In our study, we found that special-treatment benefits had a positive effect on farmers repurchase intention, providing empirical support for the positive-effect view of special-treatment benefits on customers’ repurchase intention.
Previous research gave little attention to the joint effects of face and relational benefits (including social benefits and special-treatment benefits) on repurchase intention. The results of this study indicated that social benefits and special-treatment benefits negatively moderate the relationship between face and farmers’ repurchase intentions for agricultural inputs, which contradicted our initial prediction. These unexpected findings suggested that the effects of face and relational benefits may not be simply supplementary to each other.
Face represents other peoples’ respect for a farmer, while relational benefits represent the farmer’s own interests. In interpersonal interactions, maintaining face sometimes requires a farmer to sacrifice his or her own interests to preserve harmony with relationship partners. Zhang found that, in mixed relationships where farmers and retailers are both friends and trading partners, farmers often feel conflicted between maintaining face and maximizing their own interests and this negative feeling can reduce farmers’ buying behavior [13]. Moreover, farmers can be classified into two distinct interaction patterns (face-oriented and benefit-oriented) when dealing with agricultural retailers. Face-oriented farmers base their repurchasing decisions on whether the behavior helps maintain and improve their face, while benefit-oriented farmers base their repurchasing decisions on whether continuing a business relationship with a retailer brings them more profits [50]. These two distinct interaction patterns might be incompatible, as farmers who emphasize gaining face may have to give up some their own interests and farmers seeking to maximize profits may not be able to maintain face at the same time. Our study provides empirical support for this intriguing phenomenon, in which face and relational benefits conflict with each other when they are jointly influencing farmers’ repurchase intentions.

6.2. Management Implications

The results of this study have important implications for practice. First, face plays a significant role in farmers’ purchasing decisions for agricultural inputs. Face influences these decisions by affecting interpersonal harmony between two parties and fulfilling farmers’ needs to maintain face. From an interpersonal relationship perspective, face reflects the level of interpersonal acceptance between farmers and retailers. When both parties respect each other’s face, it becomes easier to form stable and trusting relationships, treating each other as in-group members. Farmers are more likely to trust and develop long-term relationships with agricultural retailers who treat them as in-group members. Therefore, in order to expand market shares, agricultural retailers should prioritize efforts to protect farmers’ face. Interactions with farmers should create a harmonious climate where their face is respected and their need for esteem is met. Following the norm of reciprocity, farmers are likely to strengthen their relationships with retailers who show them respect, leading to repeated purchases of agricultural inputs from the same retailers.
Second, relational benefits have significant impacts on farmers’ repurchase intentions. Social benefits enhance farmers’ familiarity with retailers and fulfill their emotional needs, which, in turn, increases their intention to repurchase. Special-treatment benefits help farmers save money and receive high-quality services, creating a positive outlook for future cooperation. Agricultural retailers should engage in various practices to increase social benefits and special-treatment benefits for farmers. These practices may include addressing farmers by name, maintaining good relationships, offering special deals and customized services, and providing price breaks. Such initiatives will help agricultural retailers maintain stable and cooperative business relationships with farmers.
Finally, agricultural retailers should adjust their sales tactics to suit farmers’ interaction patterns. In traditional rural societies, face is usually the most influential factor in determining farmers’ repurchasing decisions [51]. However, as agricultural marketing matures, benefits emerge as another critical factor in farmers’ repurchasing decisions [50]. Our study revealed that the interactions between face and relational benefits can have negative impacts on farmers’ repurchase intentions, meaning that the effect of one factor could undermine the effect of the other factor. Therefore, when interacting with farmers, agricultural retailers should first identify their interaction patterns and choose the right strategy for smooth communication. Two distinct interaction patterns, face-oriented interaction and benefits-oriented interaction, exist in farmers’ interactions with retailers [35,36]. For face-oriented farmers, retailers should leverage their sensitivity to face-related information and employ interpersonal skills to fulfill farmers’ needs for face. Retailers should carefully protect farmers’ face, show respect in interpersonal interactions, and avoid situations that might cause farmers to lose face. Efforts to protect farmers’ face will increase their personal recognition and emotional connections with retailers, thus facilitating the establishment of harmonious interpersonal relationships. In return, farmers will be inclined to make repeated purchases from these retailers and to build stable and cooperative relationships with them. For benefits-oriented farmers, retailers should address their needs for tangible and intangible benefits. Providing price breaks, special deals, and faster or customized services can attract farmers who prioritize their own interests and encourage them to build stable business relationships with the retailer. By adapting sales tactics to match farmers’ interaction patterns, agricultural retailers can effectively address the varying factors that influence farmers’ repurchase intentions in the agricultural-marketing context.

6.3. Limitations and Further Research Direction

The findings of this study were specifically tested in the context of agricultural marketing, focusing on farmers’ purchasing behavior and exploring the influence of face and relational benefits (social benefits and special-treatment benefits) on farmers’ repurchase intentions for agricultural inputs. Agricultural marketing is characterized by unique factors, including the closed interpersonal environment of rural society and the high risk and expertise associated with agricultural products. As such, the generalizability of this study’s findings to other research settings remains uncertain. Future research should aim to replicate and validate these findings in diverse contexts, such as online marketing and business-to-business marketing, to ascertain their broader applicability.
The data used in this study were subject to certain regional and quantitative limitations. The study collected data from four provinces in eastern, central, and western China, leading to potential regional restrictions on the findings. To enhance the generalizability and robustness of the results, future studies should collect data from a wider range of regions and obtain larger sample sizes. This would allow a more comprehensive examination and verification of the implications of this study.
Moreover, this study did not assess variations in farmers based on factors such as geographical location, income, gender, and other relevant variables. To gain a comprehensive understanding of farmers’ purchasing behaviors for agricultural supplies, future research should include comparative analyses across different regions, income levels, genders, farming experiences, crop types, and other influential factors. Additionally, it is imperative to consider the economic awareness of farmers in relation to the true value of their transactions, as well as the ethical risks associated with advocating for farmers as consumers and citizens. These aspects represent critical facets of farmers’ purchasing behaviors that warrant careful examination in future studies, in order to provide a more nuanced understanding.

Author Contributions

Conceptualization, C.G. and G.L.; data curation, C.G. and G.L.; formal analysis, C.G. and Y.W.; writing—original draft, C.G.; writing—review & editing, Y.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Henan University Philosophy and Social Sciences Outstanding Scholar Funding Project (2019-YXXZ-14), Henan Philosophy and Social Science Planning Project (2021BJJ063), Henan New Liberal Arts Research and Reform Practice Project (2021JGLX068; 2021JGLX070), and by the High-Level Talent Research Project of the North China University of Water Resources and Electric Power (202210007).

Informed Consent Statement

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

Data Availability Statement

The data is unavailable due to privacy restrictions.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 15 15137 g001
Figure 1. The proposed theoretical model.
Figure 1. The proposed theoretical model.
Sustainability 15 15137 g001
Table 1. Sample profile.
Table 1. Sample profile.
FeaturesFrequencyPercentageFeaturesFrequencyPercentage
GenderMale38666.78Crop typeFood crops40670.24
Female19233.22Cash crops17229.76
Age≤366010.38Farming Experience≤10 years13823.9
37~4615126.1211~30 years22038.06
47~6529851.55≥31 years22038.06
≥666911.94Agricultural acreage (Acres)≤533357.61
EducationLess literacy6010.386–1519233.22
Elementary school18331.66>15539.17
Junior high school26445.67Average annual household income
(CNY)		<10,00014925.78
High school/technical school6411.0710,000–60,00038867.13
Diploma and above71.21>60,000417.09
Table 2. Variables and measures.
Table 2. Variables and measures.
VariablesScalesFactor Loadingsα
Face
AVE = 0.660
CR = 0.886		When local farmers interact with agricultural retailers, they take into account the face and self-esteem of both sides0.7610.824
When local farmers interact with agricultural retailers, the more the other party respects us, the more I feel dignified0.859
The more local farmers give each other face when dealing with agricultural retailers, the more they will also maintain our face0.836
In general, if an agricultural retailer is introduced by a friend/relative, I will give full face to the friend/relative0.789
Social benefits
AVE = 0.610
CR = 0.824		I have developed a friendship with the agricultural retailer I frequent0.7400.673
I am familiar with the agricultural retailers who provide services to me0.824
The agricultural retailer that I often visit knows my name0.777
Special treatment benefits
AVE = 0.714
CR = 0.926		At the agricultural retailer I frequent, I get a better price than most customers0.798
At the agricultural retailer I frequent, I get faster service than most customers0.8140.899
When customers are in line, I am often given priority service0.881
The agricultural retailer I frequent provides me with services that other customers do not enjoy0.873
The retailer I frequent will offer me discounts on agricultural products (pesticides, fertilizers, seeds) or special agricultural products that other customers do not receive.0.855
Repurchase intention
AVE = 0.686
CR = 0.867		Local farmers will have more business with agricultural retail stores in the future0.7630.789
Local farmers will buy new agricultural products (pesticides, fertilizers, seeds) or new services offered by their regular agricultural retail stores0.881
Local farmers will buy more agricultural products (pesticides, fertilizers, seeds) or services from their regular agricultural retail stores0.873
Irreplaceability
AVE = 0.686
CR = 0.867		Local farmers can easily make up for lost income if they stop going to the same agri-retailer they frequent and switch to another one0.7480.767
For local farmers, a clear alternative agricultural retailer can easily be found0.900
Local farmers can fairly easily switch to another agribusiness retailer if they want0.829
Table 3. Results of Descriptive Statistics.
Table 3. Results of Descriptive Statistics.
VariablesMeansS.D.12345678
1 Face5.5401.132
2 SI5.6921.0840.296 **
3 STI4.4071.5560.0450.256 **
4 RPI5.6410.9960.332 **0.175 **0.332 **
5 Gender0.3300.220−0.096 *−0.041−0.096 *−0.087 *
6 Age3.0001.3850.070−0.0580.070−0.061−0.175 **
7 Education2.6100.729−0.102 *0.062−0.102 *−0.020−0.021−0.194 **
8 Irreplaceability3.3642.362−0.134 **−0.001−0.134 **−0.123 **−0.099 *−0.100 *0.066(0.767)
Note: SI: social benefits; STI: special-treatment benefits; RPI: repurchase intention. N = 578, * p < 0.05, ** p < 0.01.
Table 4. Hierarchical regression.
Table 4. Hierarchical regression.
Independent VariablesRepurchase Intention
Model 1Model 2Model 3Model 4Model 5Model 6Model 7Model 8
Gender−0.202 **−0.130−0.247 ***−0.183 **−0.175 **−0.211 ***−0.183 **−0.208 **
Age0.0250.020−0.0050.0340.003−0.001−0.002−0.004
Education−0.0090.025−0.039−0.020−0.013−0.009−0.007−0.006
Irreplaceability−0.084 ***−0.056 **−0.064 **−0.082 ***−0.048 *−0.046 *−0.039−0.041 *
Face 0.278 *** 0.197 ***0.189 ***0.184 ***0.182 ***
SI 0.348 *** 0.265 ***0.240 ***0.254 ***0.238 ***
STI 0.112 ***0.057 **0.051 **0.060 **0.054 **
Face × SI −0.085 *** −0.066 **
Face × STI −0.059 ***−0.039 *
R0.1620.3490.4080.2380.4650.4180.4770.485
R20.0260.1220.1660.0570.2160.2310.2270.235
ΔR20.0190.1140.1590.0480.2070.2200.2170.223
F3.858 ***15.873 ***22.817 ***6.863 ***22.474 ***21.368 ***20.941 ***19.396 ***
Note: SI: social benefits; STI: special-treatment benefits; RPI: repurchase intention. *** p < 0.01, ** p < 0.05, * p < 0.1.
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Gao, C.; Li, G.; Du, Y.; Wanyan, Y. Face or Relational Benefits? Research on the Influencing Mechanism on Repurchase Intention for Agricultural Inputs. Sustainability 2023, 15, 15137. https://doi.org/10.3390/su152015137

AMA Style

Gao C, Li G, Du Y, Wanyan Y. Face or Relational Benefits? Research on the Influencing Mechanism on Repurchase Intention for Agricultural Inputs. Sustainability. 2023; 15(20):15137. https://doi.org/10.3390/su152015137

Chicago/Turabian Style

Gao, Chen, Gang Li, Yaolin Du, and Yaru Wanyan. 2023. "Face or Relational Benefits? Research on the Influencing Mechanism on Repurchase Intention for Agricultural Inputs" Sustainability 15, no. 20: 15137. https://doi.org/10.3390/su152015137

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