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Article

Does Information Source Matter? Corporate Reputation Management during Negative Social Responsibility Events

by
Hongxia Peng
,
Qiang Zhang
* and
Zhiqiang Zhang
Business School, Hubei University, Wuhan 430062, China
*
Author to whom correspondence should be addressed.
J. Theor. Appl. Electron. Commer. Res. 2024, 19(4), 2747-2764; https://doi.org/10.3390/jtaer19040132
Submission received: 22 July 2024 / Revised: 5 September 2024 / Accepted: 1 October 2024 / Published: 9 October 2024
(This article belongs to the Topic Interactive Marketing in the Digital Era)
Browse Figures
Versions Notes

Abstract

:
In the era of digital marketing, where consumers and enterprises frequently interact with each other, consumers hold different attitudes toward the different sources of information, including corporate social responsibility information. Negative corporate social responsibility can have direct impacts on corporate reputation. Choosing appropriate channels to publish the negative social responsibility information of enterprises in order to reduce the impact of these negative social events on corporate reputation is imperative for corporate image management. This research examines the differences in the impact of enterprise-generated content and -co-generated content on consumer attitudes using second-hand data analysis and then investigates how different information sources influence corporate reputation through empirical experiments. The results indicate that co-generated content performs better than other sources of information on corporate reputation, while professional user-generated content has the most negative impact. We further identify the external attribution as a mediation mechanism in the relationship between information sources and corporate reputation. The theoretical contributions and managerial implications of the research findings are discussed.

1. Introduction

With the advancement of new technology and the wide use of social media platforms, interactive marketing has become the new normal [1]. Corporate strategies involve more consumer engagement in the value co-creation process through social activities, including social events and cause marketing [2,3]. Conversely, companies also face the challenge of value destruction due to negative corporate social events that hurt a corporation’s reputation [4]. Dong et al. [5] found that consumers feel happy after leaving negative evaluations of brands online, which can lead to the emergence of many negative evaluations and have adverse effects on the company’s reputation and various aspects of its operations. Therefore, how to release negative corporate social responsibility (CSR) information in a way that reduces its impact on companies’ corporate reputation has become a major topic of interest. To help companies improve their CSR communication, scholars have extensively explored the factors that influence CSR communication effectiveness [6]. An important influencing factor is the source of information on CSR. However, the extant research literature in this area has inconsistent findings. For example, Huang et al. [7] argued that companies should use third-party channels to publish CSR information, whereas Groza et al. [8] suggested that companies should use their own channels when publishing forward-looking CSR information. The emergence of this contradiction may be due to previous research mainly focusing on comparing corporate sources with third-party sources, while ignoring the differences in the impact of corporate social responsibility information dissemination on corporate reputation among third-party information sources.
In practice, consumer–brand relational communication has become an increasingly digital experience [9]. The fast development of social media has made it essentially interactive with built-in interactive tools [10]. When a company encounters negative social responsibility events, it will disclose negative information on its own, and, due to the interactivity of social media, consumers will also express their own evaluations [11,12]. Because of the virality of social media content [13], user-generated content will appear in large amounts. Previous research on corporate social responsibility has noticed the differences in the roles of Employee-Generated Content (EGC) vs. User-Generated Content (UGC) on social media platforms [14]. For example, Fennis et al. [15] argued that, when companies disclose negative corporate social responsibility events, their self-disclosure has a positive impact on consumer-choice behavior, perceived company reputation, and company evaluation compared to third-party reports [16,17]. In the digital era, the interactivity of social media has inevitably spread negative user evaluations more quickly, which has a significant negative impact on a company’s image and business performance [11,18], Even with a large number of positive reviews, this influence still exists. Therefore, companies should be cautious in using social media to disseminate corporate social responsibility information [19,20]. With the development of social media platforms, the status of professional users makes the impact of content generated by these users on their audience increasingly significant. It is also becoming increasingly common for enterprises, as sponsors, to jointly generate content with professional users. However, existing research lacks a differentiation and a comparison of third-party information sources on social media. In examining the communication of negative CSR events, studies have mainly used legitimacy theory to analyze consumers’ subjective feelings about negative corporate events, which are easily affected by the severity of the negative events themselves, leading to fluctuations in research conclusions.
Contributing to the extant CSR literature, this study systematically distinguishes and compares various sources of information on social media platforms by reviewing existing research and considering the actual situation of social media platforms [21] and explores the differential impact of different information sources on corporate reputation when disseminating negative social responsibility information. This article also introduces some relevant theories of consumer responsibility attribution to explore the impact mechanism of information sources on corporate reputation in a negative CSR context.

2. Information Sources

Depending on a study’s research objectives, the definition of information sources may vary slightly. Kim et al. [22] referred to different information sources as “sources”, Snoeijers et al. [23] analyzed them from the perspective of social information publishers, and Kang et al. [24] and Xiang et al. [25] pointed out that social media serves as a source of information. Considering the historical background of social media and the specific context of corporate social responsibility events, this study defines the source of social media information as the presenters and publishers of personal, social, organizational, and other information related to a company’s corporate social responsibility activities published on social media platforms.
In the context of CSR events, scholars have used different classifications of information sources. Most scholars have classified information sources as either internal channels or third-party channels (external channels) [8,15]. “Internal channels” refer to an enterprise’s official website or official self-media, while “third-party channels” refer to stakeholders or social organizations that are beyond the enterprise’s control. Although there are various forms of third-party communication channels, scholars have not explored their diversity, instead using a specific third-party channel to represent third-party channels as a whole. This study summarizes the specific third-party channels in previous research, including non-governmental organizations [26], UGC [20], system-generated content [20], media institutions [27], and professional evaluation institutions [15]. Additionally, scholars have discussed joint promotion between official enterprise channels and third-party organizations [28].
Based on a review of the literature and the consideration of the actual background of social media, this article takes user-generated content as one of the independent variables and explores the differences between professional-user-generated content and user-generated content. Professional user generated content is added as one of the independent variables. At the same time, co-generated content is becoming increasingly important in practice, but few scholars have studied joint CSR promotion. Therefore, this study takes enterprise-generated content, user-generated content, professional-user-generated content, and co-generated content as independent variables.
(1)
Enterprise-Generated Content
The information posted by enterprises on official social media pages is referred to as employee-generated content [29] or EGC [30]. Research has shown that increasing publicity through social networking pages [31] or advertisements [32] can improve brand awareness. Companies’ establishment of official social media accounts is conducive to the dissemination of product information, corporate culture promotion, and brand communication. The generation of content by companies has a positive and significant impact on customer behaviors such as customer spending and cross-purchasing [29]. Having their own official social media accounts brings opportunities for enterprises, as social media are changing the way that marketing communication is conducted and becoming tools on which brand marketers increasingly rely [33]. There are also successful corporate cases, such as the official account of Bilibili’s Honey Snow Ice City enterprise, which gained popularity throughout China with the song “Honey Snow Ice City Sweet Honey.” Drawing on the work of Liu et al. [30], this study refers to CSR information published by a company on its official social media account as EGC.
(2)
User-Generated Content
User generated content or UGC is defined as any kind of text, data, or action performed by the users of online digital systems that is published and disseminated by the same user through independent channels and that incurs an expressive or communicative effect, either individually or combined with other contributions from the same or other sources [34]. For example, UGC can take forms such as comments, posts, and blogs using text or video. UGC, especially negative UGC, has a significant impact on enterprise marketing [20].
The present study focuses on the effectiveness of brand-related UGC, an important third-party source of information, in the dissemination of CSR information. There are three reasons for this. First, the application of other third-party information sources in the commercial field has been relatively limited in previous studies. For example, the influence of non-governmental organizations on social media in China is weak, and media institutions generally only report on the negative social impact of enterprises. System-generated content, such as likes and comments, is highly correlated with the quality of the information itself. Second, UGC is vulnerable to all kinds of manipulation and abuse [14]. In recent years, UGC has been exposed to negative events, such as the “water army (A hired online writer who publishes specific information on specific content and disguises himself as an ordinary netizen or consumer, publishing, replying to, and disseminating blog posts that have an impact on normal users),” “control review,” and spreading rumors, which may have adversely affected the credibility of UGC. As such, its effectiveness needs to be further tested. Third, UGC is particularly effective in allowing users to create and publish media content and achieve considerable reach through dynamic social networks. UGC also remains the most widely used source of information on social media. For example, according to Bilibili’s 2021 Q3 financial report, the monthly average video submission volume of Bilibili reached over 10 million (a year-on-year increase of 80%) and the monthly active number of UP (uploader) owners reached 2.7 million (a year-on-year increase of 61%). Therefore, testing the effectiveness of UGC in spreading CSR has practical value.
(3)
Professional-Generated Content or Professional-User-Generated Content
With the development of social media, a new source of information is emerging: professional-generated content (PGC) or professional-user-generated content (PUGC). PUGC has evolved as a result of the development of UGC and professional-generated content (PGC). It has a greater narrative depth than UGC on short-form video platforms, and it is more interesting and entertaining than PGC on long-form video platforms [35]. Professionalism, regarded as the amount of knowledge that a person has in a particular field [36], is a characteristic of professional users. Therefore, PUGC has a higher level of professionalism than UGC, ensuring content quality while also providing users with an enjoyable experience, which facilitates content dissemination. The most prominent advantages of PUGC over UGC are its better content quality and higher fluency. From the perspective of industry segmentation, YouTube and Bilibili are social websites for video content with a relatively concentrated global PUGC. Bilibili is an outstanding PUGC video community in China, of which Li Ziqi is a representative member. She has both the grassroots characteristics of UGC and a professional video-editing team to oversee content, allowing her to become a globally renowned internet celebrity.
According to Bililbili’s third-quarter financial report in 2021, the number of video views created by professional users accounted for 93% of the total number of views on the platform. This indicates that PUGC is loved by a large audience and has become an important source of information on social media. However, the analysis of PUGC in the literature remains limited. Therefore, this study introduces PUGC as a research object.
(4)
Co-Generated Content
Little research has been conducted on joint promotion between third parties and enterprises. Only a few scholars have examined the joint promotion of CSR through enterprise channels and third-party channels, finding that, compared with individual enterprise channels and third-party channels, this method has better dissemination effects [28]. This provides new ideas for the current study.
On social media platforms, in addition to publishing their promotional content, corporate officials often act as sponsors and collaborate with bloggers to promote their products. For example, the official account of Mengya Jia on the Bilibili platform sponsors well-known video bloggers, such as the Huanong Brothers, to create video content. Bloggers use their creativity to embed products into video content. Bilibili netizens refer to this as “Qiafan,” which means earning corresponding fees by incorporating sponsor brands into video content. Unlike traditional advertisers, bloggers often craft their ads in a down-to-earth manner and are praised by many netizens. However, few studies have analyzed this type of promotional model.
Referring to the research of Tian et al. [28], this study combines PUGC and EGC, considering them together as a single information source (PUGC + EGC). This source of information is referred to as co-generated content, which is the content generated as a result of the cooperation between the official account of an enterprise and professional users in a certain field.
In summary, this study categorizes social media information sources as EGC, UGC, PUGC, and PUGC + EGC. A comparative analysis is presented in Table 1.

3. Research Hypotheses and Model

3.1. Research Hypotheses

3.1.1. Impact of Information Sources on Corporate Reputation in Negative CSR Events

Social media supports the interaction between consumers and brands, so social media platforms provide a high number of response opportunities [37]. When a company experiences negative social responsibility events, the relevant negative information will be quickly known to consumers and spread. Deng et al. [38] found through a review of the existing literature that there is a close relationship between CSR and corporate reputation, and negative CSR information can damage corporate reputation [39]. Negative CSR information may be exaggerated during the transmission process, thereby amplifying the negative effects of the CSR event itself. The source of information plays a crucial role in influencing the dissemination of negative CSR based on previous studies. For instance, scholars have observed that the disclosure of negative company information through third-party channels has a more detrimental effect on the company than its disclosure through other channels [26]. Therefore, this study suggests that different sources of information have varying effects on corporate reputation when it comes to the spread of negative CSR information.
(1)
Role of EGC
Enterprises’ self-reporting of negative information may have unforeseen effects. When product-related information includes negative details, it is more effective in enhancing credibility than information without such negative details. The presence of negative information can lead consumers to believe that the advertiser is being truthful [40]. In contrast, the corporate self-disclosure of negative CSR information does not influence decision-makers’ stock price estimation and investment decisions, unlike disclosing such information through third-party channels [26]. Therefore, before disclosing negative information through third-party channels, self-disclosure significantly enhances the credibility of information, a phenomenon some scholars have referred to as “grabbing the limelight” [41].
(2)
Role of UGC
The detrimental impact of negative UGC on businesses can be significant. Negative UGC is more readily believed and exerts a greater influence on audiences than positive UGC, thereby affecting consumers’ perceptions of a company’s legitimacy [20]. The adverse effects of user feedback on corporate reputation outweigh its positive effects [19]. In the context of online shopping, consumers tend to prioritize reading various types of UGC, particularly negative comments, which can significantly affect a company’s reputation. Consequently, this study posits that UGC has a more pronounced detrimental effect on corporate reputation than EGC.
(3)
Role of PUGC
The content generated by enterprises has a greater impact on customers who are more experienced and inclined to use social media [29]. Therefore, when enterprises post information related to negative social responsibility events, it is more likely to trigger comments and reposts from professional users. Compared with UGC, PUGC often garners a larger following on social media platforms, leading to greater information dissemination. Additionally, due to the perceived credibility of PUGC in terms of information quality, it may have a more substantial negative impact on corporate reputation than UGC.
(4)
Role of Co-Generated Content
The joint influence of PUGC and EGC in promoting negative CSR information may better mitigate the negative effects of CSR than either PUGC or EGC alone. Enterprises’ provision of negative information can demonstrate a responsible attitude, while PUGC, as a trusted source of information, can reduce consumer skepticism regarding EGC. Research has indicated that, when third-party channels and a company’s channels collaboratively promote negative CSR, the impact on consumer brand identity is more significant [28]. Therefore, this study suggests that co-generated content has the least detrimental effect on corporate reputation.
The following hypotheses are thus presented:
Hypothesis 1 (H1): 
In the dissemination of negative CSR information, different sources of information have different effects on a company’s reputation.
Hypothesis 1a (H1a): 
In the communication of negative CSR information, UGC has greater power to damage corporate reputation than EGC.
Hypothesis 1b (H1b): 
In the communication of negative CSR information, PUGC has greater power to damage corporate reputation than UGC.
Hypothesis 1c (H1c): 
In the communication of negative CSR information, co-generated content has a greater positive impact on corporate reputation than other sources of information.

3.1.2. Mediating Role of the Attribution of Responsibility in Negative CSR Events

There are two main perspectives on attribution theory among scholars. One perspective focuses on attributing behavioral processes, known as motivational attribution theory, and the other perspective involves attributing the outcomes of events that have already occurred, known as success or failure attribution theory. The latter refers to people’s tendency to interpret the outcomes of others’ success or failure [42]. Scholars tend to analyze negative events from the perspective of what has caused these events, as perceived by the audience, which is responsibility attribution [39,43]. Based on Weiner’s [42] attribution theory and related research on responsibility attribution in product crisis [43], this study divides the responsibility attribution of consumers in negative CSR into internal and external attributions. “Internal attribution” refers to consumers attributing negative outcomes to the company itself, including its ability and effort level, whereas “external attribution” refers to consumers attributing negative outcomes to external factors that are unrelated to the enterprise, such as environmental and social factors. According to the theory of attribution of responsibility, when a negative corporate social responsibility event occurs, consumers may interpret this negative outcome as the result of the company’s own fault or other factors, that is, internal attribution or external attribution.
The consumer sharing of negativity online has both destructive and constructive aims [5]. When a company discloses negative CSR information, consumers may perceive companies as having a responsible attitude and actively solving problems by following their advice, consumers may perceive the company as more trustworthy [41]. Consumers’ positive attitude towards a company may lead them to attribute negative corporate social responsibility outcomes to external factors, indicating that consumers believe the cause of negative events in the company is external rather than internal. Additionally, due to the more personalized and grounded nature of UGC compared with EGC alone, it may play a greater role in mitigating the impact of negative CSR. Considering that consumers may attribute negative outcomes to factors both internal and external to a company, this study posits that external attribution by consumers plays a more significant role than internal attribution in their evaluation of the company’s reputation. The following hypothesis is proposed based on these considerations.
Hypothesis 2 (H2): 
In the context of negative CSR information, consumer external attribution plays a mediating role in the impact of information source on corporate reputation.

3.2. Research Model

Various information sources can exert distinct effects on consumer attitudes, potentially stemming from the consumers’ attribution of responsibility to corporate conduct. This study’s research model is depicted in Figure 1.

4. Study 1: Impact of EGC and Co-Generated Content on Consumer Attitudes

To intuitively reflect the differences in the effects of information dissemination between EGC and co-generated content on social media, Study 1 used Python to capture relevant data on information sources and consumer attitudes on social media to provide second-hand data support for this study.

4.1. Data Collection

To measure information sources and consumer attitudes, Bilibili was selected as the data source for this study, as it is the most active virtual community in terms of PUGC. Bilibili’s current commercial media platform, Observer Network, was chosen as the research object for two main reasons. First, the network had very successfully launched the community’s EGC operations. By February 2022, it had gained more than 7.2 million fans and had published more than 12,000 videos. Second, it often publishes videos jointly with other bloggers, making the research of co-generated content more convenient. To prevent the stability of the data from decreasing due to the use of too long a period, February 2022 was taken as the time node and Python software was used to capture the data of all Observer Network videos in the 3 months before February 2022 (i.e., from December 2021 to February 2022), including the title, release time, publisher, video playbacks, video likes, video coins, video barrage, and video collection for each video. The above consumer behavior indicators were used as alternative variables to measure consumer attitudes.

4.2. Data Analysis

During the 3 months examined, the Observer Network released 698 videos in total, including 610 videos released alone and 88 videos jointly released with others. Descriptive analysis and inter-group differences are shown in Table 2. Some data were automatically filtered due to missing values. The analysis found that the separate release of EGC and the joint release of EGC + PUGC demonstrated no significant differences in terms of playback and like-count volume (MEGC = 479,859, Mco-generated = 390,061, t = 1.929, p = 0.054). However, considering that the audience might not have known the publisher before clicking on the video, the playback volume may not directly reflect consumer attitudes. As such, this study used like-count volume divided by playback volume to generate a new variable, the like rate (i.e., likes/plays), to measure video popularity. To facilitate comparative analysis, the value of the like rate was magnified by 10,000. The analysis of the differences between groups demonstrated that the joint release of EGC + PUGC scored significantly higher than the single release of EGC for indicators such as bullet count (MEGC = 1245 < Mco-generated = 3787; t = −4.181, p = 0.000), coin count (MEGC = 589 < Mco-generated = 2231; t = −5.970, p = 0.000), collection count (MEGC = 1414 < Mco-generated = 2428; t = −4.321, p = 0.000), and like rate (MEGC = 707 < Mco-generated = 863; t = −5.800, p = 0.000). To some extent, the results indicate that, in the information dissemination on social media, PUGC + EGC has a more positive impact on consumer attitudes than EGC.

4.3. Research Results of Study 1

The analysis of data from the Observer Network revealed that information source had a significant impact on consumer attitudes. As an information source, EGC + PUGC scored higher for consumer behavior indicators such as bullet count, coin count, collection count, and like rate than EGC alone. This demonstrates the value of the joint content generation style that is characteristic of EGC + PUGC in information dissemination on social media.
Two limitations of Study 1 must be acknowledged. First, as a form of commercial media, the Observer Network mainly focuses on current affairs content and has nothing to do with the company (i.e., Bilibili) itself. Second, political media are greatly influenced by hot topics.
Overall, Study 1 still identified differences in the impact of EGC and EGC + PUGC on consumer behavior in information dissemination, preliminarily verifying that information sources can play an important role in information dissemination. To overcome research noise, experimental methods were used to further examine the role of information sources in CSR communication contexts and explore the mechanisms underlying this role to enhance the persuasiveness of this study.

5. Study 2: The Impact of Information Sources on Corporate Reputation in Negative CSR Contexts

5.1. Experimental Design

Of the 143 Chinese university students recruited to participate in Study 2, 50.35% were female and 49.65% were male, and all reported having attained education at the undergraduate level or above. The experiment used a randomized controlled trial method to randomly assign the participants to one of four experimental groups (32 for EGC, 38 for UGC, 34 for PUGC, and 39 for PUGC + EGC).

5.2. Manipulation and Testing of Variables

5.2.1. Manipulation of Negative CSR Events

Negative CSR events were selected as the stimulus materials for this experiment based on three criteria. First, the CSR events had to be common in daily life to avoid errors due to contingency. Second, the CSR events could not have obvious real brand connotations, but they had to be based on real scenarios to manipulate the source of information. Third, to avoid bias caused by consumers’ lack of participation, the CSR events had to have moderate consumer participation and be related to consumer interests or overall societal interests.
The negative CSR events selected are listed in Table 3. The control materials for this study were adapted from real cases. To avoid interference from consumers’ stereotypes of real brands, the fictional company ACE Technology was used as the company involved in the negative CSR event.
The manipulation of CSR type was divided into two parts: virtual background materials and virtual publishing content. The detailed control method is shown in Table 4. To more accurately reflect the tone of different information sources, the third person (“the company”) in third-party sources was replaced by the first person (“we”) in EGC, but the other content remained completely the same. To better distinguish the information sources, they were further manipulated.
To evaluate whether the participants had correctly identified the type of CSR event, this study followed Dou’s [44] method and used multiple-choice questions to test them. Details are presented in Table 5.

5.2.2. Manipulation and Verification of Information Sources

The manipulation of information sources in this study was divided into two parts. First, after the publication of the virtual background material and before the publication of the virtual communication content, different words were used to remind the participants of different information sources. Second, to more closely resemble the real-life browsing experience of users on social media, the Bilibili page was simulated using a dynamic graph that further indicated the source using system information. The detailed manipulation method is shown in Table 6. Finally, the source of information was incorporated into the background of the respective content as a watermark.
After combining the information sources with the communication content, the final dynamic diagram (replaced by screenshots here) is shown in Figure 2. Because the sample group is Chinese, it uses Chinese for manipulation demonstration, and relevant information has appeared in Table 4 and Table 6.
To assess whether the participants had correctly identified the information sources, the manipulated variable was tested following Dou’s [44] method for testing information sources. After viewing the material, the participants were required to select the source of the CSR content from four given information source options. The detailed options are presented in Table 7.

5.3. Experimental Procedure

The experiment was conducted in four steps. First, the participants were informed that they would be participating in a study on the consumer evaluations of CSR. They were also advised that they would be reading background materials about the abnormal heating of a mobile phone manufactured by ACE Technology (a negative CSR event). Second, this part reminded participants of the different sources of social media content. Text reminders were provided, and then participants saw Bilibili information dynamic graphs from different sources of information. Third, the subjects’ true feelings were then tested, including their opinions on the CSR information publishers, their attribution of responsibility for the negative CSR events, and their evaluation of corporate reputation. The subjects were required to select relevant options and rate scale items based on their real opinions. The measurement items for the attribution of responsibility and corporate reputation are shown in Table 8 and Table 9, respectively. All of the items measured in this study were scored using a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Finally, the subjects’ basic demographic information was collected, including information on their gender, education, and commonly used social media platforms. The questionnaire was generated with the help of Questionnaire Online and it was distributed online.

5.4. Research Results

5.4.1. Questionnaire Reliability and Validity Testing

SPSS was used for the analysis. The Cronbach’s alpha coefficient of each variable in the questionnaire exceeded 0.7, indicating that the item settings of the scale are reasonable and reliable.
Confirmatory factor analysis was conducted directly on the scales of the three variables in this study. The results are shown in Table 10. The average variance extracted (AVE) of each variable was greater than 0.5 and the composite reliability (CR) was greater than 0.8, indicating that the questionnaire had good validity.

5.4.2. Manipulation Check

To assess whether the participants had correctly identified the information sources, they were required to determine the publisher of the information from four given options. A chi-square test using SPSS software in the contingency analysis found significant differences among the options (χ2(9) = 262.3, p = 0.000). Further analysis found that 96.8% of the subjects had correctly identified the publisher of the information under the EGC condition, 84.2% had correctly identified the publisher under the UGC condition, 79.4% had correctly identified the publisher under the PUGC condition, and 74.3% had correctly identified the publisher under the PUGC + EGC condition. The subjects’ detailed selections are shown in Table 11. They indicate that the manipulation of information source in this experiment was successful. As such, it can be analyzed further.

5.4.3. Hypothesis Testing

(1)
Impact of Information Sources on Corporate Reputation
A one-way analysis of variance was used to verify the role of information sources in negative CSR communication, to compare and analyze the different impacts of different information sources on corporate reputation. The results of the analysis are reported in Table 12. The F-value was 17.714 (p < 0.05), indicating significant differences in the impact of different information sources on corporate reputation. Therefore, H1 was supported.
Co-generated content (PUGC + EGC) as an information source demonstrated a greater positive impact on corporate reputation than EGC (Mco-generated − MEGC = 0.73, p < 0.05), PUGC (Mco-generated − MPUGC = 1.46, p < 0.05), and UGC (Mco-generated − MUGC = 1.06, p < 0.05), as shown in Table 13. Therefore, H1c was supported.
However, no significant difference was observed between EGC and UGC in terms of their impact on corporate reputation (MEGC − MUGC = 0.33, p > 0.10). Therefore, H1a was not supported. A significant difference was observed between PUGC and UGC in terms of their impact on corporate reputation (MPUGC − MUGC = −0.40, p = 0.061). Further analysis revealed a significant difference between PUGC and EGC in terms of their impact on corporate reputation (MPUGC − MEGC = −0.73, p < 0.05). It follows that PUGC has stronger power to damage corporate reputation in negative CSR events than UGC. Therefore, H1b was supported. A detailed comparative analysis is shown in Table 14.
(2)
Mediating Role of External Attribution in the Attribution of Responsibility
Stepwise regression was used to verify the mediating role of external attribution in responsibility attribution. This study virtualized different types of information sources (EGC, UGC, PUGC, and PUGC + EGC) and used PUGC as the reference group. There were four main models (see Table 15). First, EGC, UGC, and PUGC + EGC were regressed on corporate reputation (Model 1). EGC (β = 0.292, p < 0.01) and PUGC + EGC (β = 0.627, p < 0.001) were significantly related. Second, EGC, UGC, and PUGC + EGC were regressed on internal attribution (Model 2). EGC (β = −0.398, p < 0.001), UGC (β = −0.293, p < 0.01), and PUGC + EGC (β = −0.536, p < 0.001) were all significantly related. Third, EGC, UGC, and PUGC + EGC were regressed on external attribution (Model 3). EGC (β = 0.280, p < 0.01) and PUGC + EGC (β = 0.527, p < 0.001) were significantly related. Finally, UGC, PUGC, PUGC + EGC, internal attribution, and external attribution were regressed on corporate reputation (Model 4). Internal attribution had no significant impact on corporate reputation (β = −0.126, p > 0.05), whereas external attribution had a significant impact on corporate reputation (β = 0.184, p < 0.05). Therefore, H2 was supported.

5.5. Conclusions

The main findings of this study were as follows:
(1)
In the context of negative CSR events, different information sources on social media have different effects on corporate reputation. Specifically, the joint generation of content (PUGC + EGC) alleviated the negative impact of negative information on corporate reputation to the greatest extent, followed by EGC. This means that actively posting negative information may not necessarily have a negative impact on companies’ reputation. PUGC had the greatest negative impact on corporate reputation. Surprisingly, no significant difference was observed between UGC and EGC. This can be explained as follows. When an enterprise publishes negative social responsibility information through an official account, according to the research conclusion, consumers may think that the negative event is caused by factors unrelated to the enterprise, which has less negative impact on the reputation of the enterprise. And, with the development of the internet, the explosion of negative information makes the audience remain rational when dealing with negative information. Only when third-party information sources have a certain level of credibility, such as users with certain professional backgrounds, are audiences more willing to attach importance to negative CSR, thereby damaging corporate reputation. Therefore, there is no significant difference between EGC and UGC in terms of negative CSR information.
(2)
This study reveals the internal mechanism underlying the effect of information sources on corporate reputation in the context of negative CSR events. The empirical results suggest that external attribution in consumer responsibility attribution mediates the effect of information sources on corporate reputation in negative CSR scenarios. Specifically, the differential impact of different information sources on corporate reputation on social media is achieved through consumers’ subjective belief that an enterprise’s negative CSR outcomes are caused by uncontrollable external factors.

6. Discussion

6.1. Significance of the Study

6.1.1. Theoretical Significance

The field of interactive marketing is a relatively new field that requires new theoretical progress and knowledge development [21]. The theoretical contributions made in this article are as follows.
First, this study systematically distinguishes information sources and proposes a new information source that involves enterprises and professional users jointly generating content. As part of this information source, enterprises act as sponsors or content producers, explicitly indicating that the content is commercial in nature. From a practical perspective, this model shows great commercial potential due to the high-quality content of professional users. Furthermore, the exposure of many brands has been greatly improved. However, relevant research on this information source remains scarce. Based on the actual situation of Bilibili, this study innovatively introduces professional users and enterprises jointly generating content as a combined information source and analyzes the role of this emerging information source in CSR communication.
Second, the study reveals a new mechanism of the impact of information sources on corporate reputation in negative CSR communication. In the communication of negative CSR events, previous studies have mainly used legitimacy theory to analyze consumers’ subjective feelings toward negative events, which is easily influenced by the severity of the negative event itself, leading to fluctuations in research conclusions. This study innovatively analyzes consumers’ evaluations of corporate reputation under different information sources in the context of negative CSR events from the perspective of responsibility attribution, to explain the impact of information sources on consumer attitudes in negative CSR situations and to complement related research on attribution theory.

6.1.2. Managerial Insights

When negative corporate social responsibility events occur, key enterprises should pay attention to the dynamics of professional users in public opinion monitoring. Especially in the digital age, by analyzing customer behavior, feedback, and interaction data, companies can identify areas that need improvement and innovation [45]. According to the conclusions of this study, compared to other sources of information, PUGC has the greatest negative impact on companies in negative CSR events. Therefore, when conducting their public opinion monitoring of negative events, enterprises should focus on the dynamics of PUGC and, if necessary, respond to PUGC because, when negative CSR information comes from PUGC, consumers are more likely to negatively attribute responsibility to the enterprise itself. Enterprises can pay less attention to the negative dynamics of UGC. Second, when promoting important corporate information, companies should actively collaborate with professional users. According to the conclusion of this study, the positive impact of co-generated content (PUGC + EGC) is always the greatest, and there is no significant difference in the impact of enterprise-generated content and user-generated content on corporate reputation. This provides new ideas for companies on how to address their negative CSR events. On the one hand, companies should actively release negative social responsibility information and demonstrate their attitude towards resolving negative events; on the other hand, by strengthening cooperation with professional users, companies can release negative CSR information jointly with professional social media users. The presence of companies in the information source demonstrates their official recognition of their mistakes and a responsible attitude, while the presence of professional users further reduces the severity of the information, increases consumer confidence in the company, and, thus, reduces consumers’ internal responsibility attribution (i.e., responsibility attribution to the company). Considering the actual situation on social media, jointly generated content currently has a short history, demonstrates a low usage rate, and largely belongs to the field of advertising (its usage in the field of CSR communication is low). In the future, companies may be able to overcome their CSR communication challenges by actively collaborating with PUGC.

6.2. Research Limitations and Prospects

First, this study did not match the areas of expertise of PUGC with the nature of the enterprise. PUGC is often specialized within a certain field, and the impact of different types of PUGC and enterprise collaboration on enterprise reputation may vary. PUGC related to the products of an enterprise may have a greater impact on consumers than other types of PUGC due to users’ recognition of the quality of the enterprise’s products. For example, users who specialize in mobile phone reviews may have different impacts on consumer attitudes when collaborating with mobile phone companies than other professional users. Future research could distinguish between types of PUGC to provide more accurate guidance for enterprises on selecting potential social media partners.
Second, this study did not distinguish between types of negative CSR. The negative CSR events selected in this study were unintentional negative events in the business activities of enterprises; intentional negative CSR events, which may be more harmful, were not discussed. Enterprises’ intentional negative CSR behavior may have different effects. Future research could compare the severity of negative CSR events, depending on whether they reflect intentional or unintentional behaviors and explore the role of information sources in this context.
Third, due to time and resource constraints, this article selected the Bilibili platform and a sample of Chinese university students for research, which has a certain impact on the generalizability of the research results. In future research, more diverse platforms and samples can be selected to increase the generalizability of research results.
Finally, this study did not explore the role of system-generated content on social media platforms. The source of information is only one of multiple important external characteristics of information; system-generated content (such as likes, comments, and views) may also be an important factors that affect consumers’ judgments. This study lacks a discussion of this feature. Future research could use more comprehensive system-generated information to analyze the impact of this feature on the effectiveness of information dissemination.

Author Contributions

Conceptualization, H.P., Z.Z. and Q.Z.; investigation, Z.Z.; funding acquisition, H.P.; writing—original draft preparation, Z.Z. and Q.Z.; writing—review and editing, H.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by grant from National Social Science Foundation of China (15BGL205).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available on request to the authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Jtaer 19 00132 g001
Figure 1. Research model.
Figure 1. Research model.
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Figure 2. Display materials in negative CSR.
Figure 2. Display materials in negative CSR.
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Table 1. Segmentation of information sources.
Table 1. Segmentation of information sources.
Information SourceFull NameConceptCharacteristics
EGCEnterprise-Generated ContentInformation posted by enterprises on official social media accounts.Official content;
Low interest
UGCUser-Generated ContentBlogs, comments, etc. posted by users on social media.High arbitrariness;
Low entry threshold
PUGCProfessional-User-Generated ContentProfessional content from the perspective of ordinary users.Entertaining;
High quality
PUGC + EGCProfessional-User-Generated Content + Enterprise-Generated ContentCollaboration between professional users and official corporate accounts.Third-party endorsement of enterprise information;
High credibility
Table 2. Differences between the observer network video data group.
Table 2. Differences between the observer network video data group.
Publisher TypeNumber of
Samples		Mean
Value		Standard
Deviation		Independent
Sample t-Test
t sig (Both Sides)
Total PlaybackEGC610479,859.6421,658.91.9290.054
EGC + PUGC88390,061.9296,872.4
Bullet CountEGC6101245.482161.462−4.1810.000
EGC + PUGC883787.675643.806
Like CountEGC61029,946.5722,939.88−1.0380.300
EGC + PUGC8832,771.7829,553.39
Coin CountEGC591589.941358.909−5.9700.000
EGC + PUGC732231.182299.748
Collection CountEGC6021414.531631.697−4.3210.000
EGC + PUGC852428.982076.063
Like RateEGC610707.985240.5058−5.8000.000
EGC + PUGC88863.739196.8597
Table 3. Selection of negative CSR events.
Table 3. Selection of negative CSR events.
Event SelectionReasonsPractical Cases
Enterprise Product Crisis“Product crisis” refers to the occurrence of quality defects in products produced by enterprises, which reduce consumer interest and have a relatively high probability of negative corporate social responsibility (CSR) events in the operation of enterprises.Xiaomi’s new mobile phone, Xiaomi 11, experienced an abnormal heating event.
Table 4. Manipulation of negative CSR event types.
Table 4. Manipulation of negative CSR event types.
Virtual Background MaterialSocial Media Virtual Publishing Content
ACE Technology is a high-tech enterprise, whose business covers laptops, smartphones, smart tablets, and other electronic products. Recently, at a new product launch event, ACE Technology unveiled the highly anticipated FAST8 flagship phone equipped with the Snapdragon 888 super processor. However, the phone experienced abnormal heating during gaming or video calls, which greatly reduced the actual user experience, and some consumers even claimed to have been deceived.“The recently released FAST 8 flagship phone by ACE Technology experienced abnormal heating during use, which affected users’ video and game playing. The current repair patch is still being tested. In response, we (the company) will reflect deeply, review, accept criticism, and apologize.”
Table 5. Verification of CSR event types.
Table 5. Verification of CSR event types.
Manipulation InspectionItemOptions
CSR Event TypeThe event types described in the above dynamic diagram are…Positive events.
Negative events.
Uncertain.
Table 6. Manipulation methods for information sources.
Table 6. Manipulation methods for information sources.
Information
Sources		Text Manipulation of Information Sources in Negative CSRSystem Information Manipulation in the Image
EGCAfter gaining a preliminary understanding of consumer feedback, ACE Technology released the following content on the official account of BilibiliBilibili official certification;
280,000 fans;
background watermark
UGCAfter learning that the actual usage experience of the FAST8 flagship phone had been “overturned,” a regular user on Bilibili posted the following content1,876,238 Bilibili users;
36 fans;
background watermark
PUGCAfter learning that the actual use experience of the FAST8 flagship phone had been “turned upside down,” a well-known video uploader on Bilibili posted the following contentPersonal authentication on Bilibili;
renowned UP owner;
868,000 followers;
background watermark
EGC + PUGCAfter gaining a preliminary understanding of consumer feedback, ACE Technology and Bilibili’s well-known Uplinkers have released the following contentCreative team;
personal authentication on Bilibili;
Bilibili official certification;
background watermark
Table 7. Inspection of manipulated variables.
Table 7. Inspection of manipulated variables.
Manipulation InspectionItemOptions
Information SourcesThe publisher of the above dynamic is…A renowned individual user authentication account.
An official enterprise account.
An ordinary user account.
Jointly released by the enterprise and an individual.
Table 8. Responsibility attribution measurement items.
Table 8. Responsibility attribution measurement items.
DimensionItemsReferences
Internal
Attribution		The abnormal heating problem this time was caused by a lack of corporate responsibility.Chen et al. [43]
The company could have avoided this product quality issue.
The product issue this time was caused by the insufficient strength of the enterprise.
External
Attribution		Abnormal heating of mobile phones is caused by high performance and high power consumption.
The product issue this time was caused by accidental and unexpected factors.
The product issue this time was caused by improper use by consumers.
Table 9. Corporate reputation measurement items.
Table 9. Corporate reputation measurement items.
ItemsReferences
Corporate ReputationThis enterprise is responsible.Eberle [19]
This enterprise has a sense of responsibility.
This enterprise is worthy of respect.
This enterprise is trustworthy.
Table 10. Confirmatory factor analysis results.
Table 10. Confirmatory factor analysis results.
FactorVariableStandardized Load FactorAVECR
Internal Attributionint10.9070.7480.899
int20.891
int30.798
External Attributionext10.8530.7520.900
ext20.947
ext30.803
Corporate Reputationreputation10.8170.6800.894
reputation20.894
reputation30.840
reputation40.746
Table 11. Manipulation and verification of information sources.
Table 11. Manipulation and verification of information sources.
Source
Manipulation		Actual Perception of the ParticipantsTotal
EGCPUGCUGCPUGC + EGC
EGC31 (96.8%)00132
PUGC327 (79.4%)2234
UGC2332 (84.2%)138
PUGC + EGC53229 (74.3%)39
Table 12. Impact of information sources on corporate reputation.
Table 12. Impact of information sources on corporate reputation.
Variable NameInformation
Sources		Sample CapacityMeanSDf-Valuep-Value
Corporate
Reputation		EGC324.1250.80117.7140.000
PUGC343.3971.231
UGC383.7960.771
PUGC + EGC394.8590.718
Table 13. Impact of co-generated content on corporate reputation.
Table 13. Impact of co-generated content on corporate reputation.
GroupingMean Value
Difference		Standard
Error		Significance95% Confidence Interval
Lower LimitUpper Limit
PUGC + EGCEGC0.733970.21360.0010.31171.1563
UGC1.062920.204120.0000.65931.4665
PUGC1.461920.210120.0001.04651.8774
Table 14. Differences in the effects of EGC, UGC, and PUGC on corporate reputation in negative CSR.
Table 14. Differences in the effects of EGC, UGC, and PUGC on corporate reputation in negative CSR.
GroupingMean Value
Difference		Standard ErrorSignificance95% Confidence Interval
Lowe LimitUpper Limit
EGCUGC0.328950.214860.128−0.09590.7538
PUGCUGC−0.398990.21140.061−0.8170.019
PUGCEGC−0.727940.220650.001−1.164−0.2919
Table 15. Mediating role of external attribution.
Table 15. Mediating role of external attribution.
VariableModel 1
Corporate Reputation		Model 2
Internal Attribution		Model 3
External Attribution		Model 4
Corporate Reputation
βtβtβtβt
EGC0.292 **3.300−0.398 ***−4.2690.280 **3.0790.191 *2.034
UGC0.171.887−0.293 **−3.1000.0370.3970.1261.388
PUGC + EGC0.627 ***6.958−0.536 ***−5.6560.527 ***5.6990.463 ***4.433
Internal
Attribution		 −0.126−1.585
External
Attribution		 0.184 *2.252
Adjusted R20.2610.1830.2230.295
Note: * p < 0.05, ** p < 0.01, *** p < 0.001.
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MDPI and ACS Style

Peng, H.; Zhang, Q.; Zhang, Z. Does Information Source Matter? Corporate Reputation Management during Negative Social Responsibility Events. J. Theor. Appl. Electron. Commer. Res. 2024, 19, 2747-2764. https://doi.org/10.3390/jtaer19040132

AMA Style

Peng H, Zhang Q, Zhang Z. Does Information Source Matter? Corporate Reputation Management during Negative Social Responsibility Events. Journal of Theoretical and Applied Electronic Commerce Research. 2024; 19(4):2747-2764. https://doi.org/10.3390/jtaer19040132

Chicago/Turabian Style

Peng, Hongxia, Qiang Zhang, and Zhiqiang Zhang. 2024. "Does Information Source Matter? Corporate Reputation Management during Negative Social Responsibility Events" Journal of Theoretical and Applied Electronic Commerce Research 19, no. 4: 2747-2764. https://doi.org/10.3390/jtaer19040132

APA Style

Peng, H., Zhang, Q., & Zhang, Z. (2024). Does Information Source Matter? Corporate Reputation Management during Negative Social Responsibility Events. Journal of Theoretical and Applied Electronic Commerce Research, 19(4), 2747-2764. https://doi.org/10.3390/jtaer19040132

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