Impact of Text and Image Information on Community Group Buying Performance: Empirical Evidence from Convenience Chain Stores

Abstract

Although the importance of the content of a webpage in retail business performance is widely recognized, there are few empirical studies on the importance of text and image information on the homepage in retailer performance. How will consumers sift through this information? Does text and image information affect consumers’ purchasing behavior? Using a data set of a Chinese convenience chain store, we attempt to clarify the influence of the brand in the title, the emotional atmosphere on the picture, and the product images of the homepage on the picture on retail business performance by employing a panel fixed-effects negative binomial regression model and a panel fixed-effect regression. Our results show that mentioning the product brand in the event title and presenting clear product images significantly enhance retailer performance in online community group buying. It is noteworthy that emotional descriptions have a greater impact on retailer performance compared to rational descriptions. In practice, this study provides a new perspective and reference for online community group buying platforms to better attract consumers and maintain sustainable development.

1. Introduction

Since the rise of mobile e-commerce, the field of mobile commerce has witnessed a steady increase in popularity. The continuous innovation of new retail models has led to the emergence of an innovative form known as community group buying, which was initially pioneered by Chinese retailers. Mainly aimed at community residents, community group buying regards fresh food as the breakthrough point and is primarily focused on food and agricultural products. Community group buying does not provide delivery services. Consumers need to pick up their goods at designated offline stores [1]. Nowadays, there are also many convenience stores that offer community group buying as a new marketing channel. By serving the pick-up points, convenience stores can better meet consumers’ shopping and pick-up needs at different times, with the advantage of operating 24 h a day. The goods the community group is buying are dispatched directly from the origin, and the intermediate links are reduced. It will greatly improve the efficiency of transportation. Particularly for perishable goods such as fruits and vegetables, faster transport speeds will further preserve their freshness, and people can enjoy fresher food material. The orders for community group buying are formulated according to actual needs, which will effectively avoid the long-term shelving of food, control the quality of fresh food to a certain extent, and decrease the loss rate. Relying on the advantages of low cost and high freshness, community group buying collects consumer demand through online platforms to form large-scale orders at a lower price. The sustainable development model of community group buying brings more possibilities for retailers. The shortening of the supply chain can not only bring high-quality products to consumers but also improve the efficiency of the supply chain, reduce losses in the process of commodity circulation, and reduce environmental pressure. The simplification and optimization of inventory management will effectively avoid the risk of overstocking and unsalable inventory, reduce inventory costs, and improve inventory turnover. The balance of supply and demand achieved by demand-oriented order counting will also reduce the food surplus, further decreasing the possibility of food waste. This unique model will facilitate the further sustainable development of community group buying. Both parties to the community group buying transaction and even the whole society will benefit from this sustainability.

The development situation for community group buying is rapid. In 2019, the market scale of China’s community group buying reached RMB 34 billion, and the market size increased by more than 100 percent in 2020. In 2021, the market scale reached RMB 120.51 billion with nearly 600 million users.

However, with the entry of numerous internet giants, the competition for community group buying services has become more and more fierce. It has had a profound impact on retailers ability to carry out community group buying. Studying how consumer behavior affects community group buying is essential to grasping rational and efficient management strategies and offering innovative marketing concepts for retailers. This will help them achieve sustainable development and restore their status in the field of community group buying.

The rise of online community group buying is closely related to the digital lifestyle. Nowadays, the increasingly rich content of webpages will attract the attention of consumers from different angles and affect consumers’ purchasing decisions, especially for the homepage, which can influence the first impression of what the next page contains and create an intuition for the browsing consumer. This attitude will further influence the consumer’s subsequent behavior, whether to continue browsing the content of the next page or lose interest in exiting the website [2]. Homepages serve as an advertising role in this process [3], which is a crucial part of the platform economy, and sustainable design for the platform economy promotes sustainable development [4]. Two indispensable parts of the homepage are the title and a picture. The visual information delivered by them can be divided into text information and image information. Both of them are unstructured and play an important role in consumers’ decisions as visual cues. Various types of text and image information are spread in large quantities. How will consumers screen this information? How will consumers refer to this information to make decisions? Empirical evidence is needed to support how different types of information affect retail business performance. However, few studies focus on this visual information to explore the impact of homepage information on consumers’ behavior and retail business performance in community group buying. Therefore, our research focuses more on these aspects to ensure that the platform economy can also provide a better shopping experience for consumers while driving sustainable development.

There are two reasons for the lack of research on it.

First, it is difficult for researchers to obtain sufficient retail data to study the impact of the visual information on the homepage on retailer performance. Especially for text and image data, the webpage is time-sensitive, so it is difficult to obtain this information. In addition, the visual information is unstructured. Processing this unstructured information on the webpage is not simple. Second, heterogeneity among stores is difficult to control. Due to the limitations of store-related data, it is hard to match the webpage data of the activity with store sales data. With that confounding factor in such studies, it is difficult to exclude the interference of designated offline stores on consumers’ purchasing behaviors and make a correct judgment.

We have overcome the difficulties mentioned above by different means.

First, in terms of data, our data set comes from real-order data from seven convenience stores in a convenience chain in Beijing, China. It provides a unique data set for our empirical research, effectively avoiding the impact of retail brands. Secondly, for the heterogeneity of self-picking stores, our data set is panel data. The panel fixed-effects models can control the heterogeneity of different convenience stores and improve the accuracy of our empirical analysis. Our unique dataset and analytical methods allow us to effectively uncover the relationship between unstructured text, image information on the homepage, and store performance.

Our results demonstrate that showing the brand in the title, shaping the emotional atmosphere on the picture, and showing product images on the picture have a significantly positive effect on retail business performance. Therefore, enterprises can take corresponding measures, such as optimizing the layout of the homepage and improving picture quality, in a timely manner to accurately convey group buying information and meet consumers’ needs.

The rest of this paper is organized as follows: Section 2 reviews the relevant literature. Section 3 presents the hypotheses on how unstructured text and image information affect retail business performance. We then discuss our data and research design in Section 4. Section 5 presents the empirical results, and we test the robustness of our results in Section 6. The paper concludes with a discussion of our findings and managerial implications in Section 7.

2. Literature Review

Our research builds on earlier work on online community group buying, image information, text information, and the S-O-R theory.

2.1. Online Community Group Buying

Online community group buying is an innovative way of shopping, similar to “online ordering” and “community pickup” [5], which cleverly combines traditional community structures with modern online technology. In this model, community leaders (such as nearby businesses or service providers) play a crucial coordinating role in gathering and meeting the shopping needs of community residents through online platforms such as WeChat groups and applications [6]. Consumers can enjoy products and services at below-market prices through online payments, while sellers can expand their customer base and improve their performance [6]. As a derivative form of online group buying, online community group buying uniquely emphasizes the operation of the physical community. This model brings many advantages to consumers, such as interactivity, closeness, convenience, and affordability [7].

In recent years, the influencing factors of group buying intention in online communities have become a hot topic among scholars, who have conducted in-depth discussions from multiple perspectives. Song et al. [8] pointed out that perceived usefulness, ease of use, service quality, trust, expectation confirmation, and subjective norm are all important factors affecting users’ intention to continue to use. In addition, Zhang [9] paid special attention to the changes in consumers’ purchase intentions on online community group buying platforms under the background of the epidemic and deeply analyzed the core elements affecting consumers’ decision-making. At the same time, Chang [10] combined the theory of electronic word-of-mouth with the technology acceptance model and discussed the influence mechanism of online group buying from the perspective of virtual community trust. He highlights the central role of trust in the group buying process in online communities and reveals how this trust further influences consumer purchasing choices. In addition, based on the role theory and trust transfer theory, Wu et al. [11] found that the interactive behavior of group buying leaders can enhance interpersonal trust, thus enhancing the overall trust of community group buying and ultimately promoting consumers’ lock-in purchase intention. On the other hand, Chou [12] conducted in-depth research on repurchase behavior under the C2B e-commerce model and analyzed in detail the influencing factors of customer satisfaction and repurchase intention in online group buying. He not only deeply dissects the multiple dimensions of customer satisfaction but also reveals how these dimensions act on consumers’ repurchase intentions. In addition to the above studies, Wang and Song [13] explored the impact of the community group buying model driven by e-commerce from the perspective of supply chain efficiency, while Shu et al. [14] focused on the optimization of agricultural product logistics networks under the community group buying model. These studies provide us with rich perspectives and in-depth insights for a more comprehensive understanding of group buying in online communities.

To sum up, scholars have conducted in-depth studies from different perspectives on the influencing factors of online community group buying intention, the impact of community group buying mode on supply chain efficiency, and the optimization of agricultural product logistics networks. However, we were surprised to find that very few studies have focused on the consumer information environment.

2.2. Image Information and Text Information

In the environment of consumer information decision-making, image and text are undoubtedly two extremely key information carriers that have an impact on the consumer’s choice process that cannot be ignored. Images, as an intuitive and vivid visual medium, can help consumers better understand and identify intangible goods on the internet, effectively convey the core information of goods, and then guide consumers’ purchase behavior [15,16]. In addition, image plays an important role in the communication of electronic word-of-mouth. High-quality product pictures can significantly enhance consumers’ trust in word-of-mouth information, interest in products, and purchase intention [15,16]. This is because product pictures can often shape consumers’ initial impressions of products for the first time and provide detailed product displays by simulating real items, helping consumers to have a more comprehensive understanding of all the details of products, thus improving consumers’ interaction efficiency and having a profound impact on their purchase decisions [17,18,19,20].

On the other hand, words, as a precise and detailed way of expression, can capture the essential features of things while excluding those insignificant details. Studies have shown that when product pictures are combined with relevant text descriptions, consumers tend to remember more details and understand and remember product information in a more profound way [19]. In addition, the study of Necula et al. [20] also revealed an important correlation: consumers’ interest in additional verbal descriptions of product functions, the importance of product functions, and consumer satisfaction are closely linked. They found that the level of this interest not only depends on the importance of product features but is also closely related to the consumer’s perception of product satisfaction. At the same time, images and text information in advertisements will also affect people’s emotions and cognitive processes to a certain extent. However, it is worth noting that only text information can obviously stimulate consumers’ purchase desires [21]. Therefore, in the consumer’s information environment, images and words are complementary to each other, and together they affect the consumer’s purchase decision.

In the context of community group buying, consumers can easily obtain product information through online platforms [5], which not only provides them with more choices and comparison opportunities but also improves the efficiency of their search and decision-making, thus optimizing the quality of decision-making [22]. No matter what kind of product type, the purchase decision is a process involving the trade-off of multiple pieces of information [23]. In the current technical environment, although multimedia content such as video and dynamic images is gradually increasing, text and still images are still the main information forms for online product display [24].

In conclusion, in the consumer information environment, images and words complement each other and act together in the consumer’s purchase decision-making process. Therefore, it is of great theoretical and practical significance to deeply study the relationship between product information (especially image information and text information) and consumers’ reactions to purchase decisions in the context of community group buying.

2.3. The S-O-R Theory

The S-O-R (stimulus-organism-response) theory points out that cues in the environment will affect individuals’ emotions, thus driving their behavioral responses [25]. Robert and John [26] introduced the S-O-R theory into the environment of community group buying because consumers’ shopping behaviors are often stimulated by various factors, such as store atmosphere. According to this theory, store atmosphere, as a stimulus, can stimulate consumers’ emotional reactions and then affect their shopping decisions and behaviors [27]. For example, a warm and comfortable shopping environment may make consumers feel relaxed and happy, so they are more willing to explore and buy goods. A crowded and noisy environment may make them feel uncomfortable and lead to a decline in the shopping experience. In the online retail environment, this stimulus is translated into the network atmosphere, that is, the various cues transmitted by the online store. These cues may include visual elements such as website layout, color, images, and links, which together constitute the atmosphere of online stores. In the process of online shopping, consumers will be affected by these atmospheric cues and have corresponding emotional reactions, thus further affecting their shopping decisions and behaviors [28]. In order to explore the impact of online atmospheres more deeply on consumer emotions and how these emotions translate into actual shopping intentions, some scholars have conducted in-depth studies using the S-O-R framework. For example, the empirical study of Eroglu et al. [29] verified the impact of online store atmosphere cues on shoppers’ emotions and cognitive states and further pointed out that these emotions would directly affect consumers’ shopping results. The results show that website atmosphere has a significant impact on shoppers’ attitude, satisfaction, and approach or avoidance behaviors, and that behind these effects are the emotions that consumers experience during the shopping process. In addition, Chang et al. [30], from the perspective of network aesthetics, took aesthetic forms and aesthetic appeals as stimulus factors and analyzed their influence on purchase behavior through emotional models. They found that these aesthetic factors not only affect the behavioral control of consumers but also have a significant impact on their cognitive control and decision control. This provides a new perspective and enlightenment for us to understand the impact of the online atmosphere more comprehensively on consumer behavior.

In summary, S-O-R theory provides strong theoretical support for understanding consumer behavior in retail environments. By applying it to the field of online retail, we can more clearly see the influence of the online atmosphere on consumers’ emotions and shopping decisions, which provides a valuable theoretical framework for us to further explore the influence of information display on consumers’ purchasing behavior in the online group buying environment.

3. Theory and Hypothesis Development

The information conveyed by the website has a significant impact on consumers, and many scholars have conducted research on the impact of information on consumer purchases [31,32]. Various webpage information and commodity information are increasingly complex, which increases the difficulty for consumers to find effective information, especially for the homepage. The text information presented has an obvious influence on consumers [33]. The image information is the same. Scholars began to further focus on the impact of image information and text information on consumers [19,33,34]. However, little attention in previous studies was paid to the homepage to explore the impact of visual webpage information on consumer behavior and business performance in community group buying, particularly in the context of community group buying. Therefore, we focus on the effect of text and image information on retail store performance in community group buying. Our hypotheses are built on the marketing literature on consumer behavior, particularly information-searching behavior when making purchase decisions. Figure 1 illustrates the conceptual framework of our research.

The consumer of online community group buying cannot see the physical object in advance. The unpredictability of the outcome of shopping behavior may lead to the emergence of perceived risks [22,35]. If the homepage of online community group buying is not attractive, consumers may not buy with confidence, and the transaction may only stay in the demand stage. Consumers require quantity and quality of information in order to make their decisions without regret after making a purchase.

The commodity not only has tangible attributes but also depends on intangible factors such as brand and packaging. Analyzing the relationship between self-concept and products, Levy et al. [23] find that commodity sales are symbol sales at the same time, and brand is the focus of consumers as one kind of symbol. Brand positioning strategy, through its unique points, changes people’s awareness of the product and adds additional memories. Consumers’ cognition of a brand is the result of consistent meaning formed on the basis of their brand experience [36].

Brands create emotional connections in consumers’ minds through symbols [37]. Consumers have emotional dependence on the brand and regard the brand as a symbol related to their personal emotions. It reinforces the consumer’s loyalty to the brand. In addition, brand loyalty can strengthen the emotional bond between consumers and target brands through the product of the target brand, and the effect of brands on consumers will continue to strengthen and increase their purchase intention [38]. The quality of the product links to its brand [39]. Merchant brands can greatly influence consumers’ perceptions of product quality, which can reduce consumers’ perceived risks and save on decision-making costs [40]. In the scenario of the retail industry, brands play an important role in influencing consumers’ choices [41].

The activity title with brand identity on the webpage will be highlighted by the consumer. By identifying the brand included in the activity, the consumer will be aware that branded goods are contained in the activity. Associated with the previous consumption experience of brand goods, consumers will pay more attention to that activity, consider the quality of the products of this group buying activity as better than others, and click the link for purchase.

Therefore, we propose the following hypothesis:

Hypothesis 1 (H1). 

Activity titles containing product brands have a positive effect on retailer performance.

Emotion is one of the five major consumption values that affect consumers’ shopping behavior, which also contains functional value, social value, epistemic value, and conditional value [42]. Environmental cues influence people’s cognitive or emotional responses, which in turn influence their consumption behavior [25]. The electronic environment is an important factor for online shopping, which influences consumers’ feelings. As one of the components of the electronic environment, pictures are often used to guide consumers visually through the links of community group buying. Mehta [43] demonstrated the effectiveness of visual merchandising and its positive impact on consumers.

In fact, online consumers can experience shopping in advance through the images presented in the links. These sensory experience clues enhance the visual appeal to consumers, attract consumers to browse, and stimulate subsequent purchasing behaviors [44]. As an essential marketing tool, atmosphere can effectively increase its appeal to consumers [26]. Eroglu et al. [45] extend the influence of atmosphere on consumers to the online retail environment and find that atmosphere still enhances the shopping experience in the online environment. Such an atmosphere contains emotional factors, which will have an impact on consumers’ shopping outcomes [46]. This process will lead to users’ approach-avoidance behavior through the intervening internal processes of users’ arousal, pleasure, trust, etc. Consumers may go to the next page to buy, or they may exit the page directly [29]. It is because specific emotions will increase expectations for events with matching emotional cues [47]. The emotional response of consumers in the emotional atmosphere of warm colors will be enhanced, making them feel more pleasant and enjoyable [48]. This kind of enjoyment and pleasure is an important factor affecting the attitude and behavior of online shopping [44], and they have a positive impact on consumer satisfaction and form a better shopping experience [49].

We distinguish the sentimental atmosphere of pictures displayed by different group buying links by displaying emotional atmosphere and rational atmosphere.

Therefore, we propose the following hypothesis:

Hypothesis 2 (H2). 

Compared with the rational atmosphere, shaping the emotional atmosphere in the picture has a positive effect on retailer performance.

Biswas [50] points out that consumers will greatly consider perceived risk when shopping online compared to in-store shopping conditions. Fu et al. [51] state that the risk of online group buying has a negative impact on the purchase intention of online group buying. Group buying risks will bring additional financial expenses and effort. To avoid risk, consumers will choose the link with more perceived usefulness to purchase. A detailed description of the product can alleviate customer concerns about product uncertainty [52]. Laroche et al. [53] propose that images will trigger emotions that contain happy, positive, and other emotions, change cognition and attitude towards the links, and ultimately influence consumers’ purchase intentions. The content variables in the picture will affect the effect of the picture [54]. For the product images in the linked pictures, they can reflect the product information contained in the group purchase to a certain extent. Enhancing the interpretation of the product information will further change the effect of the pictures on the purchase intentions of consumers. Therefore, the product image in the linked picture is the information with more perceived benefits for consumers. We thus propose the following hypothesis:

Hypothesis 3 (H3). 

The product images in the picture have a positive impact on retailer performance.

4. Research Design

The data for our study comes from a Chinese retailer that specializes in convenience store chains. This company focuses on developing a specialized local convenience store chain with distinctive city characteristics. In the convenience store chain industry in Beijing, it is in a leading position in both the number of stores and brand awareness. We collected activity data on the online community group buying from this leading platform, covering the period from September 2019 to November 2020. For each online community group buying activity, we obtain information regarding the dynamic commercial data, activity characteristics information, and housing price data. The housing price data comes from the real estate rental and sales service platform at beijing.anjuke.com. For unstructured activity data, we manually label the category of sentiment atmosphere and the content variables in the image after data preprocessing.

Table 1. Descriptive statistics of variables.

Variable	Obs	Mean	Std. Dev.	Min	Max
OrderQuantities	238	16.529	14.894	1	81
SalesVolume	238	940.654	1120.565	1.8	7006
HousePrice	238	100,195.11	22,175.72	62,277	137,566
TitleSentiment	238	0.353	0.479	0	1
If_TitleEmoji	238	0.5	0.501	0	1
If_ProductPicture	238	0.176	0.382	0	1
If_TitleBrand	238	0.618	0.487	0	1
PictureSentiment	238	0.853	0.355	0	1
If_PicturBrand	238	0.118	0.323	0	1
TitleLength	238	52.382	6.207	39	65
If_Daytime	238	0.366	0.483	0	1
If_TitleLocation	238	0.529	0.5	0	1
Ave_Sale_Price	238	32.749	11.888	14.35	63.32
If_Titilefresh	238	0.294	0.457	0	1

shows the descriptive statistics of business data, activity characteristics, and housing price data in our sample. We noticed that in our sample, the average activity sales of stores were 940.654 yuan, and the average number of activity orders sold was 16.529. There is a big difference between the minimum value and the maximum value of the store’s activity sales and the number of activity orders sold. In addition, 61.8% of all titles on the webpage of our activity sample contain brand names. Among all the pictures on the webpage of our activity sample, 85.3% are pictures expressing the emotional atmosphere, and 17.6% of the activities choose to put the product image into the picture on the webpage of the activity.

We choose the store’s whole OrderQuantities within the online community group buying at an activity as the performance indicator of the retail store. As the OrderQuantities is a countable entity and can only take non-negative integers, the appropriate econometric model is a negative binomial regression method [55]. We chose the panel fixed-effects negative binomial regression model to study the effect of text and image homepages. For information on retailer performance in community group buying, we took Equation (1) as our main regression model.

$$\begin{gathered} {\mathrm{O}\mathrm{r}\mathrm{d}\mathrm{e}\mathrm{r}\mathrm{Q}\mathrm{u}\mathrm{a}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{t}\mathrm{i}\mathrm{e}\mathrm{s}}_{it}={\beta }_1{\mathrm{I}\mathrm{f}\_\mathrm{T}\mathrm{i}\mathrm{t}\mathrm{l}\mathrm{e}\mathrm{B}\mathrm{r}\mathrm{a}\mathrm{n}\mathrm{d}}_t+{\beta }_2{\mathrm{P}\mathrm{i}\mathrm{c}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{e}\mathrm{S}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}}_t \\ +{\beta }_3{\mathrm{I}\mathrm{f}\_\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{t}\mathrm{P}\mathrm{i}\mathrm{c}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{e}}_t+\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}\mathrm{s}+{\mathsf{\mu }}_i+{\mathsf{\nu }}_{it} \end{gathered}$$

(1)

where OrderQuantities_it denotes the number of sales orders of store i in the community group purchase activity t.

If_TitleBrand_t and If_ProductPicture_t are two binary variables that, respectively, represent whether the activity title contains the brand name and whether the picture content contains product images. PictureSentiment_t is the binary variable that represents the sentiment atmosphere of the picture. Moreover, 1 represents the emotional atmosphere, and 0 represents the rational atmosphere. Relatedly, ${\mathsf{\mu }}_i$ is the time-invariant unobserved project heterogeneity. ${\mathsf{\nu }}_{it}$ is a random error.

Our model includes multiple control variables. HousePrice_it indicates the house price level around store i at the time of activity t. If_Daytime_t Indicates whether the activity only allows pickups during the weekday. If_PicturBrand_t indicates whether the brand name is displayed in the picture. TitleSentiment_t indicates the sentiment atmosphere of the activity title. Moreover, 1 represents the emotional atmosphere, and 0 represents the rational atmosphere. TitleLength_t indicates the length of the activity title. If_TitleEmoji_t indicates whether an additional emoji has been added to the activity title. If_TitleLocation_t indicates whether the title of the activity adds the country of origin name. If_Titilefresh_t indicates whether the title of the activity conveys the freshness of the food. Ave_Sale_Price_t indicates the average selling price in activity t. All of the above control variables may affect consumers’ interest in continuing to browse group-buying platforms and purchase products.

In this paper, Equation (1) is tested by regression four times, and the first regression is regression without any control variables. The second regression includes the first set of control variables, which contains the dummy variable of whether pick-up was allowed only for the weekday. The third regression includes the second set of control variables, which contains the dummy variable of whether pick-up was allowed only for weekdays and the house price level around store i at the time of activity t. The fourth regression includes the third set of control variables, which contains the dummy variable of whether the title of the activity conveys the freshness of the food and the average selling price in activity t on the basis of the second set of control variables.

One of the important factors affecting the housing price is the per capita disposable income of the region [56,57]. Adding the regional housing price at the activity time into the equation will control regional differences in consumption power.

To prevent endogenous problems caused by unobserved variables, the following measures were taken in this study: First, our empirical model includes a fixed effect at the convenience store level to illustrate unobserved convenience stores that do not change over time. Second, different sets of control variables are used for regression verification. Third, after the robustness test of the replacement variables and model, our results are still robust.

5. Results

Table 2. The effect of text and image information on order quantities.

	(1)	(2)	(3)	(4)
Variables	OrderQuantities	OrderQuantities	OrderQuantities	OrderQuantities
If_TitleBrand	0.177 ***	0.204 ***	0.203 ***	0.189 ***
	(3.654)	(4.017)	(3.765)	(2.838)
PictureSentiment	0.246 **	0.320 ***	0.307 ***	0.422 ***
	(2.329)	(3.268)	(3.567)	(3.928)
If_ProductPicture	0.459 ***	0.549 ***	0.536 ***	0.544 ***
	(3.744)	(4.384)	(3.987)	(4.048)
If_Daytime		0.184 ***	0.186 ***	0.232 ***
		(3.202)	(2.955)	(5.175)
HousePrice			−0.000	−0.000
			(−0.261)	(−0.178)
Ave_Sale_Price				0.008 *
				(1.898)
If_Titilefresh				−0.090
				(−1.122)
Constant	1.984 ***	1.896 ***	2.314	2.045
	(13.526)	(11.849)	(1.274)	(0.711)
Controls	No	Yes (Group 1)	Yes (Group 2)	Yes (Group 3)
Observations	238	238	238	238
Number of shops	7	7	7	7

Note: Standard errors are in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01.

presents the estimates of the regression when the dependent variable is the store order quantities of each community group buying event.

Column (1) of Table 2 presents the estimates of the first regression of Equation (1), which does not contain control variables. The results show that showing the brand in the title has a significantly positive effect on the order quantities of the convenience shop (β = 0.177, p < 0.01), supporting Hypothesis 1. The results also show that, compared with the picture of activity shaping the rational atmosphere, the picture of activity shaping the emotional atmosphere has a significantly positive effect on the order quantities of the convenience shop (β = 0.246, p < 0.05), which supports Hypothesis 2. In addition, showing product images on the picture has a significantly positive effect on the order quantities of the convenience shop (β = 0.459, p < 0.01), which supports Hypothesis 3.

Column (2) of Table 2 shows the estimates of the second regression of Equation (1), which, on the basis of the first regression, adds the extra control variable of whether it is only allowed to pick up on a weekday. Moreover, Column (3) of Table 2 reveals the estimates of the third regression of Equation (1), which, on the basis of the first regression, adds extra control variables of whether it is only allowed to pick up on a weekday and the house price level around store i at the time of activity t. Column (4) of Table 2 reveals the estimates of the fourth regression of Equation (1), which, on the basis of the third regression, adds extra control variables of whether the title of the activity conveys the freshness of the food and the average selling price in activity t.

The results show that across these three regressions, the brand in the homepage title, shaping the emotional atmosphere of the homepage picture of activity, and showing product images on the picture have a significantly positive effect on the order quantities of the convenience store. That adds additional validation to the hypothesis.

We verify our assumptions of robustness in Section 6.

6. Robustness Checks

Thus far, we have been using order quantities as the dependent variable. We now use another alternative variable, the sales volume. It is the performance indicator of the retail store. Then, we estimate Equation (2) using a panel fixed-effect regression analysis for robustness testing.

$$\begin{gathered} {\mathrm{S}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{s}\mathrm{V}\mathrm{o}\mathrm{l}\mathrm{u}\mathrm{m}\mathrm{e}\mathrm{s}}_{it}={\beta }_1{\mathrm{I}\mathrm{f}\_\mathrm{T}\mathrm{i}\mathrm{t}\mathrm{l}\mathrm{e}\mathrm{B}\mathrm{r}\mathrm{a}\mathrm{n}\mathrm{d}}_t+{\beta }_2{\mathrm{P}\mathrm{i}\mathrm{c}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{e}\mathrm{S}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}}_t \\ +{\beta }_3{\mathrm{I}\mathrm{f}\_\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{t}\mathrm{P}\mathrm{i}\mathrm{c}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{e}}_t+\mathrm{C}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}\mathrm{s}+{\mathsf{\mu }}_i+{\mathsf{\nu }}_{it} \end{gathered}$$

(2)

where ${\mathrm{S}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{s}\mathrm{V}\mathrm{o}\mathrm{l}\mathrm{u}\mathrm{m}\mathrm{e}\mathrm{s}}_{it}$ represents the sales quantity of store i in the group buying activity of the t community, and control represents the control variable, as shown in

Table 3. The effect of text and image information on sales volumes.

	(1)	(2)
Variables	SalesVolume	SalesVolume
If_TitleBrand	218.532 **	204.751 **
	(2.576)	(2.705)
PictureSentiment	389.274 **	496.742 **
	(2.820)	(2.458)
If_ProductPicture	459.231 **	543.051 **
	(2.740)	(2.488)
TitleSentiment	−291.297 **	−325.169 **
	(−2.514)	(−2.474)
HousePrice	−0.053	−0.053
	(−1.315)	(−1.295)
If_PicturBrand	821.515 **	930.113 *
	(2.508)	(2.416)
TitleLength	−7.063
	(−1.154)
If_TitleLocation	−50.371	−48.018
	(−1.838)	(−1.815)
If_TitleEmoji	113.417	107.559
	(1.359)	(1.298)
If_Holiday	229.430	238.299
	(1.445)	(1.451)
Constant	5875.931	5472.113
	(1.464)	(1.414)
Observations	238	238
R-squared	0.181	0.179
Number of shops	7	7

Robust t-statistics are in parentheses. ** p < 0.05, * p < 0.1.

. IF_Holiday indicates whether the pick-up time of community group buying activities includes weekends or not. Other variables are defined in the research design section.

The estimated results are shown in column (1) of Table 3. As expected, when SalesVolume was used as the dependent variable, the results showed that displaying the brand in the title had a significant positive effect on the quantity of orders for convenience stores (β = 218.532, p < 0.01), supporting Hypothesis 1. The results also showed that, compared with the activity picture that shaped the rational atmosphere, the activity picture that shaped the emotional atmosphere had a significant positive effect on the order quantity of convenience stores (β = 389.274, p < 0.01). In addition, displaying product images on pictures had a significant positive effect on the number of orders in convenience stores (β = 459.231, p < 0.01). Column (2) of Table 3 adds an additional control variable for whether pick-up is allowed only on weekends. The results are consistent with those presented in the main model, providing further support for the findings presented in Section 5.

7. Implications and Conclusions

Online community group buying provides consumers with high-quality products and services at prices lower than the market average [6], and this advantage is not only reflected in price and quality but also in its efficient operation mode. Merchants ship products directly from the source, greatly simplifying the supply chain and improving transportation efficiency. Behind this efficient operation mode, online community group buying websites attract consumers’ attention and emotions through carefully crafted page elements, especially the home page design, making consumers more easily attracted to the browsing process, thus increasing the possibility of continuing browsing and purchasing [2]. Our research indicates that skillfully integrating product branding into event titles and showcasing clear and compelling product images can significantly enhance a retailer’s performance. It is worth noting that the emotional atmosphere and emotional connection conveyed in the picture often touch the heartstrings of consumers more than the rational atmosphere. When consumers browse the web, their brains quickly filter and categorize presented information based on personal interests, needs, and past experiences. Therefore, an appealing title and attractive product image can often capture consumers’ attention immediately. These visual elements not only convey the basic product information but also improve the self-efficacy of consumers from the perspective of focusing on user experience and establish an intangible emotional connection with consumers, thus enhancing their sustainable purchase impulse [58].

In order to fully tap the potential value of visual elements in the retail industry, businesses can adopt a series of strategies, with special emphasis on interface design, especially homepage design. For example, when designing the activity title, it is necessary to focus on the core value of the product and the characteristics of the brand so as to strengthen the relationship between the brand identity and the activity and further deepen the consumer’s cognition and memory of the brand. In addition, merchants also need to carefully create an emotional atmosphere on the web page according to the market positioning of the product and the target consumer group, so that consumers can deeply experience the emotional temperature and unique charm of the brand during the browsing process. At the same time, the quality of the picture is also a key factor that cannot be ignored. High-quality pictures can intuitively show the appearance, characteristics, and actual quality of products, thus effectively stimulating consumers’ desire to buy. Therefore, in the selection of product pictures, merchants need to ensure that the selected image can truly reflect the characteristics of the product, not only in terms of beauty but also in terms of texture and performance. Through the above measures, merchants can use visual elements in a more academic way to inject new vitality into brand building and consumer experience improvement.

In conclusion, visual elements such as titles, emotional atmosphere, and product images play a key role in influencing consumer purchasing decisions. By continuously carefully designing and effectively managing these elements on the home page to achieve sustainable design for the platform economy [4], retailers can significantly improve performance and market share, stand out in the highly competitive market, and achieve long-term stable brand sustainability.

However, there are some limitations to our study, which also provide new directions for future exploration. First, our data came from only one single platform, so further research needs to be extended to more platforms to gather a broader range of information. More visual design elements and the interaction between image and text elements can also be studied. Secondly, future studies can further analyze the internal mechanism of how text and image information affect group buying performance from the perspective of psychology. Finally, our experiment was conducted in the context of Chinese culture. The items may be influenced by project deviations caused by cultural differences. Future research can further explore group buying behaviors across different cultural backgrounds.