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The impact of social media input intensity on firm performance: Evidence from Sina Weibo
Physica A 536 (2019) 122556
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Physica A journal homepage: www.elsevier.com/locate/physa
The impact of social media input intensity on firm performance: Evidence from Sina Weibo Xu Zu, Xinyi Diao, Zhiyi Meng
∗
Business School, Sichuan Agricultural University, Chengdu 611830, PR China College of Economics, Sichuan Agricultural University, Chengdu 611130, PR China Business School, Sichuan University, Chengdu 611130, PR China
article
info
Article history: Received 17 June 2019 Received in revised form 12 August 2019 Available online 5 September 2019 Keywords: Social media Sina Weibo Input intensity Inverted U-shaped relationship Firm performance Private listed firms
a b s t r a c t The aim of the present paper is to determine whether launching social media accounts affects the performance of a firm, assess the impact of firms’ different social media input intensity on their performance, and identify whether there is a linear or nonlinear relationship between firm performance and social media input intensity. To this end, this paper takes panel data, matching data for private listed firms from Sina Weibo and the China Stock Market & Accounting Research Database between the years of 2010 and 2014 as an example to empirically investigate the abovementioned issues. The results show that: (1) launching Weibo accounts does indeed enhance the performance of firms; (2) greater Weibo input intensity leads to a greater improvement in performance; (3) Weibo input intensity has a nonlinear impact on firm performance, and, more specifically, there is an inverted U-shaped relationship between input intensity and performance; and (4) firm size has a significantly positive influence on the relationship between Weibo input intensity and firm performance, but the type of real controller of firm does not have a statistically significant impact on the relationship between the two. This paper innovatively investigates the nonlinear impact of social media input intensity on firm performance, while previous work investigated only their linear relationship. Another contribution of this work is that the existing customer-oriented literature mainly utilized questionnaire data, which may be subject to human manipulation, while this paper collected Weibo data through data mining, making the research more comprehensive and accurate. © 2019 Elsevier B.V. All rights reserved.
1. Introduction It is well-known that firm performance reflects a firm’s profitability and operation level, which is critical to the development and maintenance of a firm’s competitive advantage [1]. Currently, firms attempt to increase their performance by implementing different business models because of the increasingly fierce market. Mature firms advance by introducing new products, product upgrades or through research and development (R&D) [2]. Newcomers in the market, however, choose different approaches, such as enhancing firm reputation, promoting products and using innovative technologies to improve their competitiveness [3]. In general, all types of firms need to pay consistent attention to customers in the market and adapt promptly to change. ∗ Corresponding author. E-mail address: [email protected] (Z. Meng). https://doi.org/10.1016/j.physa.2019.122556 0378-4371/© 2019 Elsevier B.V. All rights reserved.
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For a long time, scholars have conducted in-depth discussions regarding firm performance. Most studies focus on the relationship between firms’ internal factors, such as their characteristics, R&D investment, absorptive capacity, human resource management, and firm performance [4]. Specifically, Huselid et al. [5] looked at 293 U.S. firms as a sample to verify the positive impact of human resource management capability on financial performance. Veugelers et al. [6] found that the industrial characteristics of firms have an important impact on the relationship between firm size and performance. Kostopoulos et al. [7] showed in their study that absorptive capacity will promote innovation and financial performance at different development stages of the firm. Additionally, others are studying the impact of external environmental factors on firm performance. For example, Dangelico et al. [8] examined the relationship between environmental governance and firm performance and found that the market performance of a firm is positively influenced by its environmental governance capabilities, especially in the fields of energy and pollution. Lee et al. [9] examined the period from 2011–2012 by using Korean firms as an example and verified the significantly positive relationship between firm environmental responsibility and their market performance. In addition, scholars have begun to focus on the linkages between consumers and firm performance. Frambach et al. [10] noted that customer orientation is the focus of many firms’ connection with the market and confirmed that performance of the customer-oriented firms is always better. With the rapid development of information technology, social media has become a major trend of the Internet [11]. Social media websites such as YouTube, Facebook, Twitter, Sina Weibo, etc. have experienced exponential growth [12]. Social media sites have attracted extensive attention from various fields, especially business [13]. With the increasingly mature understanding of social media platforms, a large amount of enterprise generated content (EGC) has entered people’s vision [14], giving firms a new channel of communication with consumers because of its interactive, accurate and real-time characteristics. The disclosure of relevant information by firms through social media platforms shortens the distance between firms and their customers in the market, which might have an impact on firm performance to an extent. Compared with the traditional firm propaganda methods, such as announcements, advertisements and news media, social media possesses the characteristics of timeliness, broader reach, high influence, low cost and minimal technology requirements, leading to an increasing number of firms launching social media accounts to directly contact consumers [15]. As firms frequently employ social media, substantial academic attention has been paid to social media intensity. In the majority of previous literature, social media intensity is defined from the viewpoint of users and is considered to be their use and engagement extent of social media [16], which is commonly measured by a series of questions in a questionnaire [17–19]. Additionally, there are also studies explaining social media intensity from the perspective of the organizations. For example, Schlagwein and Prasarnphanich [20] regarded the number of social media types used by organizations as social media intensity. Drawing on and distinguishing previous research, this paper puts forward social media input intensity to measure the extent firms input in social media and connects this input with firm performance. To the best of our knowledge, there are few prior studies concerning social media input intensity in firm performance. The most related literature is social media adoption and firm performance, which was demonstrated to be either positive or non-influential by scholars [21,22]. However, these studies only consider whether social media adoption or no adoption have an impact on performance but do not take social media input intensity and its possible nonlinear influence on performance into consideration. Therefore, in this paper, we attempt to answer the following questions: RQ1. Does launching social media accounts affect firm performance? RQ2. How do firms’ different social media input intensity influence their performance? RQ3. Is there a linear or nonlinear relationship between firm performance and social media input intensity? To achieve the aim, we conducted research based on Sina Weibo, which is China’s largest social media platform with the largest number of users. It is also increasingly favoured by firms because it is able to quickly disseminate and receive information. The significance of this study lies in the following aspects. First, this paper expands on the research investigating the relationship between Weibo input and firm performance. In the existing literature, there are few works concerning this topic, and these studies only focus on their linear relationship. However, this paper innovatively links the two and investigates the nonlinear impact of Weibo input intensity on firm performance. Second, this paper verifies the feasibility of Weibo as a data source on social group information. The existing customer-oriented literature mainly acquires data through questionnaire surveys, while this paper collects Weibo data through data mining, which makes the research data more comprehensive and accurate. Third, the research conclusion of this paper shows that Weibo inputs are valuable for the improvement of their performance, which is beneficial for firms to make correct decisions when adopting competitive strategies. The remainder of this paper is constructed as follows. The second part presents a short literature review of related studies. Section 3 puts forward the hypotheses of this study. Next, the research design of our research, including data sources, variable setting and the regression model used in the study are shown in the fourth part. Then, in Section 5, we offer results of the empirical research. The final part gives the conclusion and prospects for related issues. 2. Literature review The last decade has seen a great shift in the media landscape, which has attracted critical attention by scholars and practitioners [23]. Digital social media channels (such as microblogs, online BBS and social networking sites) have
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gradually surpassed traditional media channels (such as newspapers, television and magazines), becoming popular with the masses. With the popularity of social media, an increasing number of firms are aware of its potential profitability through the interaction with their customers whenever and wherever possible [24]. Therefore, a large number of firms use social media to promote product information in order to attract customers to use their products and brands and obtain benefit [25]. Social media has various definitions because of people’s different understanding and utilization. The most simple and comprehensive definition in terms of social media derives from Kaplan et al. [26]. Based on this definition, social media are ‘‘a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0 and that allow the creation and exchange of User Generated Content.’’ There are a wide range of types of social media, including microblogs, BBS, photographs, video sharing, etc. [27]. Since its emergence, people around the world quickly accepted and began to use social media, such as Facebook, YouTube, Twitter, Instagram, Sina Weibo, etc., to communicate, which not only strengthened information sharing among users but also helped firms to achieve their distinctive hierarchical goals, including marketing, advertising, branding and so forth [28]. Therefore, a large number of firms attempt to utilize this effective platform to interact with potential users to spread their business information [29]. Specifically, this paper investigated microblogs, one of the most popular social media formats, and used Sina Weibo as an example for the empirical study. It is common knowledge that Sina Weibo, a Twitter-like service, is a user-relationshipbased platform for information sharing [30]. The users on Weibo are free to publish various forms of information, including text (limit to 140 characters), images, audio, video, etc. Though the length of messages posted on Weibo is allowed in a limited way, this information may contain useful data. Therefore, since its emergence, it has been quickly accepted by the public. According to the research by Shen et al. [31], as of 2015, there are more than 500 million registered users posting 100 million messages on Weibo each day. The tremendous growth of Weibo attracts great interest from academic scholars, spanning several strands of literature. The first main avenues of research focused on Weibo itself and Weibo user-related topics, such as motivations, behaviours, satisfaction and other aspects. Since Weibo is much like Twitter, Chen et al. [32], for example, compared Weibo and Twitter, analysing their similarities and differences. In the study of Zhang et al. [33], they identified dominant Weibo user motivations and their effects on usage patterns. Additionally, in a study by Gao et al. [34], more than 40 million microblogging activities were analysed to compare different use behaviours between Weibo and Twitter. Guan and his colleagues [11] examined Weibo users’ behaviours in 21 widely discussed events in 2011. In addition, since WeChat popularizes these years, studies focusing on comparison of Weibo and WeChat are emerging. Gan [35], for example, researched how to examine users’ satisfaction of Weibo and WeChat. As research on this topic expanded, some scholars widened the scope to study the surrounding topics of Weibo. These studies cover a wide range of fields and are often intersected with other disciplines, such as psychology, computer science, sociology, etc. For example, Guan et al. [36] employed Weibo big data to identify users with a high likelihood to commit suicide. Mao et al. [37] applied machine learning methods on Weibo data, proposing the discovering marital distress (DMD) model to identify users with marital distress. Additionally, there is other literature that focuses on prediction. In the research by Zhao et al. [38], which was based on Weibo data, the influence of Weibo on the spreading of topics was analysed, and a topic spreading model of short-term trend prediction of issues was built. In addition, several studies connected Weibo and rumours. Mondal et al. [39] constructed a probabilistic model to identify tweets containing rumours at an early stage of post-disaster. More recently, scholars have payed more attention to the effect of Weibo, especially the aspect of information disclosure. It is well-known that information diffusion is critical to market efficiency [40]. Since the popularity of Weibo has increased, firms launch official accounts in order to announce firm-specific information to the public, considering it as an alternative approach to transfer information [31,41]. According to Blankespoor et al. [42], microblog was found to be more interactive than traditional announcements methods, such as newspaper or other traditional media. Firms can use microblogs to deliver timely information to more investors and thus reduce information asymmetry. Therefore, some scholars combine Weibo with stock market performance to conduct research. Dong et al. [43], for example, considered the Weibo Index as a proxy for investor attention and performed an analysis of the relationship between investor attention and stock market performance. Similarly, Hu et al. [44] studied the impact of specific information disclosure of Weibo on the pricing efficiency of listed firms’ stock. In addition, Wang et al. [45] collected Weibo data from firms’ employees to analyse whether their Weibo comments have an impact on their firms’ performance. However, though growing numbers of researchers are paying attention to Weibo and performance, the existing studies only consider social media adoption or not but do not take social media input intensity and its possible nonlinear influence on performance into consideration. Therefore, in this paper, we employed Weibo information from private listed firms from 2010 to 2014 to explore these issues in depth. 3. Hypothesis This section proposes the research hypotheses of this study. The main hypotheses include: first, launching Weibo accounts has significantly positive effects on firm performance; second, Weibo input intensity is positively correlated with performance, and an inverted U-shaped relationship between them exists; third, firm size and the type of real controller of firm play moderating roles on the relationship between Weibo input intensity and performance.
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3.1. Launching Weibo accounts and firm performance In recent years, the rapid rise of social media as the mainstream application on the Internet not only broadens the channels for firms to communicate with users and promote their products but also provides convenience for them to absorb external knowledge and promote a trend of community-based development of firms. It has been shown that social media would increase brand image and awareness [28], leading to electronic word-of-mouth (eWOM) advertising, which would then enhance users’ purchasing intention and ultimately provide firms better business performance [46,47]. With the rapid expansion of the number of users, firms are paying attention to Weibo as the most critical social media communication channel [48]. Weibo is a platform based on user relationships for information sharing and dissemination. For firms, Weibo has an enormous user base, provides low-cost channels of communication and utilizes an interactive way of communication, which can increase the mobility, real-time nature and socialization of firms’ communication of information [11]. Through Weibo, firms can not only promote new products or services but also increase attention through the interaction with users to improve their popularity and achieve rapid, comprehensive and extensive dissemination through real-time sharing of firm information. Jin et al. [49] found that firms could attract more users’ attention after launching Weibo accounts and trigger a large number of users’ forwards and comments in order to get more attention. Therefore, by building communication platforms and channels through Weibo, firms can present themselves and their products and services more comprehensively and extensively, thus improving their popularity, gaining more users’ attention, and achieving rapid and long-term growth of economic benefits by building a good corporate image. Based on this, this paper proposes the following hypothesis: H 1. Launching Weibo accounts has significantly positive effects on firm performance. 3.2. Weibo input intensity and firm performance Weibo input intensity measures the degree of firms’ operation level on Weibo after launching their accounts. The operation mode mainly includes the number of blog posts, the frequency of posting blogs within a certain period and the frequency of interaction with fans. In general, firms can obtain a certain positive influence in the initial stage of launching Weibo accounts, increasing users’ attention and brand awareness [50]. Therefore, by gaining a certain number of fans, if firms increase their input in Weibo and maintain continuous activity, this impact on firms will be decisive. This approach can not only update followers about recent developments within the firms but can also further increase the attention and memory of other non-concerned people. Generally, there is a positive correlation between media flow and its influence [51]. Firms can generate more information flow by strengthening Weibo input, which will increase the attention of followers and enhance brand awareness, leading to firms gaining advantages in the fierce market competition and thus improving profitability. However, on the other hand, if Weibo management is not continued in the later stage of operation, it may result in a large loss of attention and gradual decline in brand awareness, which would lead a brand to have difficulty achieving the desired effect of Weibo marketing [52]. Additionally, most people use Weibo mainly for entertainment purposes [53]. Accordingly, if firms input so much marketing information that does not match their perception, it might give users negative emotions, boredom or antagonism, which will then result in a negative performance. Therefore, Weibo input intensity might have a threshold; i.e., when Weibo input intensity exceeds such a threshold, the performance might decline. Based on this idea, this paper puts forward the following hypotheses: H 2a.
Weibo input intensity is positively related to the improvement of firm performance.
H 2b.
There is a nonlinear, i.e., inverted U-shaped, relationship between Weibo input intensity and firm performance.
3.3. The moderating effect of firm size and type of real controller Extant literature has verified that firm performance is affected by many factors. Amongst these, firm size plays an important role. The larger the size of the firm, the more it is able to reduce its production cost and thus improve its performance by virtue of its advantages via the scale effect [54]. Therefore, it could be said that firms of different sizes might have different operational behaviours. Therefore, firms of different sizes might have different attitudes towards Weibo input. Specifically, the larger the size of a firm, the more significant impact Weibo input will be on firm performance. Based on this, this paper puts forward the following hypothesis: H 3a.
Firm size has a positive moderating effect on the relationship between Weibo input intensity and firm performance.
In addition, the type of real controller of the firms will also have an impact on the performance. The type of real controller in this paper is divided into individual and non-individual (state-owned, foreign-owned, etc.). According to the existing literature, different real controller types can affect a firm’s market value orientation, so firms with different types of real controller may have different responses to Weibo input [55]. When the type of real controller is non-individual, Weibo input may have a more significant impact on firm performance; i.e., such firms can better improve performance. Based on this, this paper puts forward the following hypothesis:
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Fig. 1. Research framework of the present study.
H 3b. Type of real controller has a negative moderating effect on the relationship between Weibo input intensity and firm performance. Research framework of this paper is presented in Fig. 1. 4. Data and methods 4.1. Data sources This paper selected private listed firms in China and from the China Stock Market & Accounting Research Database during the period of 2010 and 2014 as the research objects. The specific steps of sample data cleaning are presented as follows: first, we deleted any abnormal values; if firms’ age was listed as negative and the number of employees is zero, related records were dropped. Second, we obtained data on firms’ Weibo accounts from the Sina Weibo website, including whether firms had Weibo accounts or not and the number of Weibo posts in each year. Here, we got balanced panel data from 732 firms and 3660 records to conduct analysis for the relationship between launching Weibo account and firm performance. Third, to further analyse the relationship between Weibo input intensity and firm performance, we deleted firm records that launched Weibo accounts but did not post any Weibo information. According to this process, unbalanced panel data from 185 firms and 585 records were obtained. 4.2. Variable settings This paper explores whether firms launching Weibo accounts or not can improve performance, and how input intensity affects firm performance. Accordingly, here we describe the dependent variable, independent variables and control variables that influence firm performance. The specific variables are set as follows: Dependent variable: firm performance. Relevant literature point out that the main indicators to measure firm performance include financial and market indicators [56]. However, financial indicators, such as the return on assets (ROA), are easily affected by accounting data and be subject to human manipulation [57]. Thus, they cannot truly reflect the situation of listed firms. Therefore, this paper uses Tobin’s Q as an index of firm performance. The main reason for this is that this index takes the market value of listed firms into consideration, which can avoid the influence of human manipulation to a certain extent and, thus, can reflect the performance of listed firms more accurately. For the calculation of Tobin’s Q, this paper refers to the method of O’Brien et al. [58], which provides the following formula: Tobin′ sQ =
MVE + PS + DEAT
(1) TA where MVE denotes firms’ circulatable stock market value, PS is the liquidation value of the preferred shares, DEAT is the book value of the debts, and TA is the book value of the total assets at the end of the period. Independent variables: Launching Weibo accounts and Weibo input intensity. First, this paper employs a dummy variable to measure whether firms launch official Weibo accounts or not. A value of 1 indicates that a firm has launched the official Weibo account (with blue and V marks in Sina Weibo), while 0 denotes that a firm has not opened an official Weibo account. Second, if a firm has launched its official Weibo account, this paper proposes an index to measure Weibo input intensity in order to judge the degree of a firm’s input in Weibo after launching its account. Specifically, the Weibo input intensity of a firm is calculated by the following formula. CWP (2) LAW where WII refers to Weibo input intensity, CWP means the cumulative number of Weibo posts issued by each firm during the observation period, LAW denotes the difference between the year of firms’ launching Weibo accounts and the observation year. WII =
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Table 1 Description of variables used in the present study. Variables
Abbreviations and related definitions
Dependent variable
firm performance
FP: Tobin’s Q
Independent variables
launching Weibo Weibo input intensity
LW: 0 = Not launching, 1 = Launching WII: Cumulative number of Weibo posts per year/ Weibo launching age
Control variable
firm age
FA: the logarithmic value of a difference between observation year and the year of listing FZ: the logarithmic value of major business income of a firm TRC: 0 = non-individual (state-owned, foreign-owned, etc.), 1 = individual IDN: the number of independent directors in each year
firm size type of real controllers the number of independent directors
Control variables. According to existing studies, firm performance will be affected by many other factors, such as firm size, firm age, etc. [59]. To control the influence of these factors, this paper selects firm age, firm size (logarithmic value of major business income used), type of real controller and the number of independent directors as the control variables. In addition, in order to test whether there are moderating effects between firm size and type of real controller on the relationship of Weibo input intensity and firm performance, this paper also tests these interaction items. It is worth noting that the interaction items are standardized prior to analysis in order to avoid multiple collinearities [60]. Note that industries and years are both controlled in regression models. The description of variables is shown in Table 1. 4.3. Methods This paper uses panel data from the period between 2010 and 2014. Currently, there are three common panel data models: mixed least square model, fixed effect model, and random effect model. Considering the possible heterogeneity among industries in this study, a fixed-effect or random-effect model is used. The regression equation is set as follows: FP = α + β1 LWit + β3 FAit + β4 FZit
+ β5 TRCit + β6 IDNit + αi + εit
(3)
FP = α + β1 WIIit + β3 FAit + β4 FZit
+ β5 TRCit + β6 IDNit + αi + εit
(4)
where i represents the industry and t denotes year. αi means other unobservable factors, and εit indicates the residual term. To judge whether to use fixed effect or random effect models, the Hausman test is employed. It should be noted that time effect is also considered in the model. 5. Findings This subsection consists of two parts. First, a descriptive analysis of variables is performed. Then, a regression analysis is performed to test the hypotheses. 5.1. Descriptive analysis Table 2 presents the descriptive analysis of the variables in this study. Each variable fluctuated stably according to variables’ mean value and standard deviation in the table. The Spearman correlation coefficient is shown in the table since nominal variables are included. Specifically, it can be seen that both launching Weibo accounts (0.013) and Weibo input intensity (0.025) are positively correlated with firm performance, which can be preliminarily interpreted as showing that launching Weibo accounts can improve firms’ performance. The greater a firm’s input in Weibo is, the greater the improvement of firm performance. In addition, when observing each control variable, it was found that firm age, firm size and the number of independent directors have a significantly positive relationship with firm performance. These coefficients are 0.432, 0.453 and 0.099, respectively, all of which are statistically significant at the significance level of 0.01. However, the type of real controllers has a significant negative connection (−0.169) with firm performance, which is also statistically significant. 5.2. Regression analysis To test the hypotheses proposed above, this paper conducted a regression analysis and used a hierarchical regression method to gradually bring control variables, independent variables, and moderators into the model. The specific results are shown in Tables 3 and 4. First, we analysed whether launching Weibo accounts can improve firms’ performance. Table 3 shows the regression results of the connection between these variables. Model 1 only includes the control variables and the dependent variable.
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Table 2 Descriptive analysis and correlation coefficient matrix of variables. 1. 2. 3. 4. 5. 6. 7.
FP LW WII FA FZ IDN TRC
Mean
St. D
1
2
3
4
5
6
0.411 0.158 0.760 7.716 20.806 3.121 0.905
0.555 0.365 1.938 6.086 1.340 0.514 0.293
1 0.013 0.025 0.432*** 0.453*** 0.099*** −0.169***
1 0.974*** 0.029* 0.122*** 0.048*** 0.033**
1 0.029* 0.131*** 0.048*** 0.024
1 0.169*** 0.014 −0.310***
1 0.176*** −0.077***
−0.051***
1
Table 3 Regression results of launching Weibo account and firm performance. Variable
Model 1
Model 2
FA
0.248*** (0.021) 0.085** (0.028) 0.005*** (0.001) 0.048** (0.016)
0.248*** (0.021) 0.086** (0.028) 0.006*** (0.001) 0.049** (0.016) 0.062*** (0.011) 2.146** (0.612) 0.496 0.365 248.180 0.000
FZ IDN TRC: non-individual LW Constant term 2
R Adjusted R2 F value P value Hausman test Industry effect Year effect
2.127** (0.621) 0.495 0.364 134.010 0.000 P = 0.000 Yes Yes
Yes Yes
Note: Numbers in brackets are robust standard errors; *** p < 0.01, ** p
< 0.05, * p < 0.1.
Overall, firm age, firm size, the number of independent directors and type of real controllers are all positive determinants of firm performance, which is consistent with the finding of previous studies [61,62]. Model 2 introduces launching Weibo accounts on the basis of Model 1. Specifically, by comparing these two models with other factors unchanged, it can be seen that firm performance was significantly enhanced by 0.062 units after firms launch Weibo accounts, denoting that firms can indeed improve their performance by launching Weibo accounts. Therefore, H 1 is confirmed. This result might indicate that Weibo is a new channel connecting firms and users [48]. When firms launch Weibo accounts, they can directly talk with customers and get timely feedback, which allows the firms to launch new products or optimize existing products thus seizing market opportunities, gaining competitive advantages and improving firm performance [49]. In addition, this paper also considered the different effects of Weibo input intensity on firm performance, and the results are shown in Table 4. Model 1 still consists of only control variables, which are proved to be significantly positive factors affecting firm performance. Model 2 adds Weibo input intensity on the basis of Model 1. When other factors remain unchanged, greater input in Weibo leads to improvement of firm performance. Specifically, after firms launch Weibo accounts, the firm performance is improved by 0.014 units for each unit of increase in Weibo input intensity, and this result is significant at the α = 0.05 level. Therefore, Hypothesis 2a is confirmed. Further, we checked if there is a nonlinear relationship between Weibo input intensity and firm performance. To this end, we standardized the quadratic term of Weibo input intensity to avoid a multicollinearity problem, and the result is shown by Model 3. This shows that the coefficient of WII2 is −0.001 while WII is 0.013, both of which are significant. This result verifies H 2b that there is an inverted U-shaped relationship between Weibo input intensity and firm performance, indicating that firms first obtain benefits from the launching of Weibo accounts but sustain losses when the input in Weibo is too high. The reason for this finding might have two distinct aspects. Initially, firms inputting more into Weibo could attract more attention from followers and enhance brand awareness, thus leading to a more beneficial result [51]. However, when the critical point is exceeded, information bombing would annoy customers and thus obtain lower revenue. This paper also studied the moderating effect of firm size and type of real controllers in the regression model of Weibo input intensity on firm performance to verify the consistency of results. Firm size was found to have a significantly positive effect on performance (β = 0.009; α = 0.1). Thus, Hypothesis 3a is verified, indicating that bigger firms may see an increase in performance due to input in Weibo, which is intuitively reflected in Fig. 2. However, the type of real controller plays a negative moderating role, but this result was not statistically significant. Hypothesis 3b is therefore partially verified.
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Model 1
Model 2
Model 3
Model 4
Model 5
FA
0.119** (0.041) 0.032*** (0.005) 0.022** (0.006) 0.058*** (0.007)
0.127* (0.047) 0.030*** (0.005) 0.020** (0.006) 0.053*** (0.006) 0.014** (0.004)
0.118*** (0.008) 0.062*** (0.015) 0.006 (0.007) 0.052* (0.031) 0.013** (0.005) −0.001*** (0.000)
0.135** (0.040) 0.026*** (0.004) 0.020** (0.006) 0.056*** (0.005) 0.013* (0.005)
0.121* (0.046) 0.030*** (0.006) 0.020** (0.007) 0.165* (0.077) 0.014** (0.004)
FZ IDN TRC: non-individual WII WII2 FZ * WII
0.009* (0.004)
TRC * WII Constant term R2 Adjusted R2 F value P value Hausman test Industry effect Year effect
−0.011 0.141*** (0.025) 0.664 0.477 32.000 0.002
0.148*** (0.021) 0.668 0.481 33.620 0.002
Yes Yes
Yes Yes
0.253*** (0.071) 0.687 0.511 86.24 0.000 P = 0.000 Yes Yes
0.136*** (0.023) 0.668 0.481 43.810 0.001
(0.007) 0.129*** (0.021) 0.668 0.481 45.360 0.002
Yes Yes
Yes Yes
Note: Brackets are robust standard errors. *** p < 0.01, ** p < 0.05, * p < 0.1.
Fig. 2. Moderating effect graph of firm size.
In addition, by observing the control variables, we found that the results presented in Tables 3 and 4 are generally consistent; that is, firm age, firm size, the number of independent directors and type of real controllers all significantly increase firm performance, indicating that these factors are effectively controlled. 6. Conclusions In the era of the Internet, there are a growing number of firms that publicize their products through Weibo. As such, numerous studies focus on Weibo related issues. However, few studies have explored the impact of firms launching Weibo accounts and input intensity on their performance. Therefore, this paper empirically tests this relationship using panel data matched with Sina Weibo data and data from private listed firms in China from 2010 to 2014. The results show that launching Weibo accounts can increase firm performance, and the greater a firm’s input intensity in Weibo is, the more obvious the improvement of performance. However, this relationship is not always linear and is actually an inverted U-shaped relationship. In addition, firm size has a significantly positive moderating effect, indicating that bigger firms’
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input in Weibo might increase more performance. However, type of real controllers does not have a statistically significant moderate effect on the relationship between Weibo input intensity and firm performance. Our results have some theoretical and practical implications. First, previous studies have investigated firm performance and examined the role of social media in it. However, these studies focus more on social media adoption and firm performance. The study of Weibo input intensity has been limited. Therefore, this study extends our understanding on Weibo input intensity and firm performance. Second, this study also extends the extant stream of social media studies by analysing the non-linear relationship between Weibo input intensity and firm performance, which may expand current research findings. Finally, the non-linear relationship between Weibo input intensity and firm performance indicates that firms do not need to blindly increase Weibo input intensity; they should instead increase appropriately and moderately to achieve optimal firm performance. However, although some progress has been made, there are some limitations in this study. For example, many factors affect firm performance, but based on the principle of data availability, only some of the variables affecting firm performance are controlled in this paper. Therefore, in future research, more relevant factors can be included to build a more comprehensive analysis framework. In addition, this paper analyses data only from the perspective of firms. As Weibo connects firms and customers, customer feedback is crucial for firms to understand market trends and develop relevant strategies to improve performance. Therefore, in future research, we can conduct a study from the perspective of customers to study the impact of consumer feedback on firm performance, which would enrich existing research. Acknowledgements This research was supported by the National Natural Science Foundation of China (Grant No. 71903139) and the Humanities and Social Sciences Foundation of the Ministry of Education of China (Grant No. 16YJC630089). It was also support by the Soft Science Program of Sichuan Province (Grant No. 2019JDR0155) and Basic Scientific Research Service Fee Project of Central Universities of Sichuan University (Grant No. 2019 Self Research-BusinessC03). References [1] S. Yang, M. Ishtiaq, M. Anwar, Enterprise risk management practices and firm performance, the mediating role of competitive advantage and the moderating role of financial literacy, J. Risk Financial Manag. 11 (2018) 35–51. [2] B.J. Zirger, M.A. Maidique, A model of new product development: An empirical test, Manage. 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Physica A journal homepage: www.elsevier.com/locate/physa
The impact of social media input intensity on firm performance: Evidence from Sina Weibo Xu Zu, Xinyi Diao, Zhiyi Meng
∗
Business School, Sichuan Agricultural University, Chengdu 611830, PR China College of Economics, Sichuan Agricultural University, Chengdu 611130, PR China Business School, Sichuan University, Chengdu 611130, PR China
article
info
Article history: Received 17 June 2019 Received in revised form 12 August 2019 Available online 5 September 2019 Keywords: Social media Sina Weibo Input intensity Inverted U-shaped relationship Firm performance Private listed firms
a b s t r a c t The aim of the present paper is to determine whether launching social media accounts affects the performance of a firm, assess the impact of firms’ different social media input intensity on their performance, and identify whether there is a linear or nonlinear relationship between firm performance and social media input intensity. To this end, this paper takes panel data, matching data for private listed firms from Sina Weibo and the China Stock Market & Accounting Research Database between the years of 2010 and 2014 as an example to empirically investigate the abovementioned issues. The results show that: (1) launching Weibo accounts does indeed enhance the performance of firms; (2) greater Weibo input intensity leads to a greater improvement in performance; (3) Weibo input intensity has a nonlinear impact on firm performance, and, more specifically, there is an inverted U-shaped relationship between input intensity and performance; and (4) firm size has a significantly positive influence on the relationship between Weibo input intensity and firm performance, but the type of real controller of firm does not have a statistically significant impact on the relationship between the two. This paper innovatively investigates the nonlinear impact of social media input intensity on firm performance, while previous work investigated only their linear relationship. Another contribution of this work is that the existing customer-oriented literature mainly utilized questionnaire data, which may be subject to human manipulation, while this paper collected Weibo data through data mining, making the research more comprehensive and accurate. © 2019 Elsevier B.V. All rights reserved.
1. Introduction It is well-known that firm performance reflects a firm’s profitability and operation level, which is critical to the development and maintenance of a firm’s competitive advantage [1]. Currently, firms attempt to increase their performance by implementing different business models because of the increasingly fierce market. Mature firms advance by introducing new products, product upgrades or through research and development (R&D) [2]. Newcomers in the market, however, choose different approaches, such as enhancing firm reputation, promoting products and using innovative technologies to improve their competitiveness [3]. In general, all types of firms need to pay consistent attention to customers in the market and adapt promptly to change. ∗ Corresponding author. E-mail address: [email protected] (Z. Meng). https://doi.org/10.1016/j.physa.2019.122556 0378-4371/© 2019 Elsevier B.V. All rights reserved.
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For a long time, scholars have conducted in-depth discussions regarding firm performance. Most studies focus on the relationship between firms’ internal factors, such as their characteristics, R&D investment, absorptive capacity, human resource management, and firm performance [4]. Specifically, Huselid et al. [5] looked at 293 U.S. firms as a sample to verify the positive impact of human resource management capability on financial performance. Veugelers et al. [6] found that the industrial characteristics of firms have an important impact on the relationship between firm size and performance. Kostopoulos et al. [7] showed in their study that absorptive capacity will promote innovation and financial performance at different development stages of the firm. Additionally, others are studying the impact of external environmental factors on firm performance. For example, Dangelico et al. [8] examined the relationship between environmental governance and firm performance and found that the market performance of a firm is positively influenced by its environmental governance capabilities, especially in the fields of energy and pollution. Lee et al. [9] examined the period from 2011–2012 by using Korean firms as an example and verified the significantly positive relationship between firm environmental responsibility and their market performance. In addition, scholars have begun to focus on the linkages between consumers and firm performance. Frambach et al. [10] noted that customer orientation is the focus of many firms’ connection with the market and confirmed that performance of the customer-oriented firms is always better. With the rapid development of information technology, social media has become a major trend of the Internet [11]. Social media websites such as YouTube, Facebook, Twitter, Sina Weibo, etc. have experienced exponential growth [12]. Social media sites have attracted extensive attention from various fields, especially business [13]. With the increasingly mature understanding of social media platforms, a large amount of enterprise generated content (EGC) has entered people’s vision [14], giving firms a new channel of communication with consumers because of its interactive, accurate and real-time characteristics. The disclosure of relevant information by firms through social media platforms shortens the distance between firms and their customers in the market, which might have an impact on firm performance to an extent. Compared with the traditional firm propaganda methods, such as announcements, advertisements and news media, social media possesses the characteristics of timeliness, broader reach, high influence, low cost and minimal technology requirements, leading to an increasing number of firms launching social media accounts to directly contact consumers [15]. As firms frequently employ social media, substantial academic attention has been paid to social media intensity. In the majority of previous literature, social media intensity is defined from the viewpoint of users and is considered to be their use and engagement extent of social media [16], which is commonly measured by a series of questions in a questionnaire [17–19]. Additionally, there are also studies explaining social media intensity from the perspective of the organizations. For example, Schlagwein and Prasarnphanich [20] regarded the number of social media types used by organizations as social media intensity. Drawing on and distinguishing previous research, this paper puts forward social media input intensity to measure the extent firms input in social media and connects this input with firm performance. To the best of our knowledge, there are few prior studies concerning social media input intensity in firm performance. The most related literature is social media adoption and firm performance, which was demonstrated to be either positive or non-influential by scholars [21,22]. However, these studies only consider whether social media adoption or no adoption have an impact on performance but do not take social media input intensity and its possible nonlinear influence on performance into consideration. Therefore, in this paper, we attempt to answer the following questions: RQ1. Does launching social media accounts affect firm performance? RQ2. How do firms’ different social media input intensity influence their performance? RQ3. Is there a linear or nonlinear relationship between firm performance and social media input intensity? To achieve the aim, we conducted research based on Sina Weibo, which is China’s largest social media platform with the largest number of users. It is also increasingly favoured by firms because it is able to quickly disseminate and receive information. The significance of this study lies in the following aspects. First, this paper expands on the research investigating the relationship between Weibo input and firm performance. In the existing literature, there are few works concerning this topic, and these studies only focus on their linear relationship. However, this paper innovatively links the two and investigates the nonlinear impact of Weibo input intensity on firm performance. Second, this paper verifies the feasibility of Weibo as a data source on social group information. The existing customer-oriented literature mainly acquires data through questionnaire surveys, while this paper collects Weibo data through data mining, which makes the research data more comprehensive and accurate. Third, the research conclusion of this paper shows that Weibo inputs are valuable for the improvement of their performance, which is beneficial for firms to make correct decisions when adopting competitive strategies. The remainder of this paper is constructed as follows. The second part presents a short literature review of related studies. Section 3 puts forward the hypotheses of this study. Next, the research design of our research, including data sources, variable setting and the regression model used in the study are shown in the fourth part. Then, in Section 5, we offer results of the empirical research. The final part gives the conclusion and prospects for related issues. 2. Literature review The last decade has seen a great shift in the media landscape, which has attracted critical attention by scholars and practitioners [23]. Digital social media channels (such as microblogs, online BBS and social networking sites) have
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gradually surpassed traditional media channels (such as newspapers, television and magazines), becoming popular with the masses. With the popularity of social media, an increasing number of firms are aware of its potential profitability through the interaction with their customers whenever and wherever possible [24]. Therefore, a large number of firms use social media to promote product information in order to attract customers to use their products and brands and obtain benefit [25]. Social media has various definitions because of people’s different understanding and utilization. The most simple and comprehensive definition in terms of social media derives from Kaplan et al. [26]. Based on this definition, social media are ‘‘a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0 and that allow the creation and exchange of User Generated Content.’’ There are a wide range of types of social media, including microblogs, BBS, photographs, video sharing, etc. [27]. Since its emergence, people around the world quickly accepted and began to use social media, such as Facebook, YouTube, Twitter, Instagram, Sina Weibo, etc., to communicate, which not only strengthened information sharing among users but also helped firms to achieve their distinctive hierarchical goals, including marketing, advertising, branding and so forth [28]. Therefore, a large number of firms attempt to utilize this effective platform to interact with potential users to spread their business information [29]. Specifically, this paper investigated microblogs, one of the most popular social media formats, and used Sina Weibo as an example for the empirical study. It is common knowledge that Sina Weibo, a Twitter-like service, is a user-relationshipbased platform for information sharing [30]. The users on Weibo are free to publish various forms of information, including text (limit to 140 characters), images, audio, video, etc. Though the length of messages posted on Weibo is allowed in a limited way, this information may contain useful data. Therefore, since its emergence, it has been quickly accepted by the public. According to the research by Shen et al. [31], as of 2015, there are more than 500 million registered users posting 100 million messages on Weibo each day. The tremendous growth of Weibo attracts great interest from academic scholars, spanning several strands of literature. The first main avenues of research focused on Weibo itself and Weibo user-related topics, such as motivations, behaviours, satisfaction and other aspects. Since Weibo is much like Twitter, Chen et al. [32], for example, compared Weibo and Twitter, analysing their similarities and differences. In the study of Zhang et al. [33], they identified dominant Weibo user motivations and their effects on usage patterns. Additionally, in a study by Gao et al. [34], more than 40 million microblogging activities were analysed to compare different use behaviours between Weibo and Twitter. Guan and his colleagues [11] examined Weibo users’ behaviours in 21 widely discussed events in 2011. In addition, since WeChat popularizes these years, studies focusing on comparison of Weibo and WeChat are emerging. Gan [35], for example, researched how to examine users’ satisfaction of Weibo and WeChat. As research on this topic expanded, some scholars widened the scope to study the surrounding topics of Weibo. These studies cover a wide range of fields and are often intersected with other disciplines, such as psychology, computer science, sociology, etc. For example, Guan et al. [36] employed Weibo big data to identify users with a high likelihood to commit suicide. Mao et al. [37] applied machine learning methods on Weibo data, proposing the discovering marital distress (DMD) model to identify users with marital distress. Additionally, there is other literature that focuses on prediction. In the research by Zhao et al. [38], which was based on Weibo data, the influence of Weibo on the spreading of topics was analysed, and a topic spreading model of short-term trend prediction of issues was built. In addition, several studies connected Weibo and rumours. Mondal et al. [39] constructed a probabilistic model to identify tweets containing rumours at an early stage of post-disaster. More recently, scholars have payed more attention to the effect of Weibo, especially the aspect of information disclosure. It is well-known that information diffusion is critical to market efficiency [40]. Since the popularity of Weibo has increased, firms launch official accounts in order to announce firm-specific information to the public, considering it as an alternative approach to transfer information [31,41]. According to Blankespoor et al. [42], microblog was found to be more interactive than traditional announcements methods, such as newspaper or other traditional media. Firms can use microblogs to deliver timely information to more investors and thus reduce information asymmetry. Therefore, some scholars combine Weibo with stock market performance to conduct research. Dong et al. [43], for example, considered the Weibo Index as a proxy for investor attention and performed an analysis of the relationship between investor attention and stock market performance. Similarly, Hu et al. [44] studied the impact of specific information disclosure of Weibo on the pricing efficiency of listed firms’ stock. In addition, Wang et al. [45] collected Weibo data from firms’ employees to analyse whether their Weibo comments have an impact on their firms’ performance. However, though growing numbers of researchers are paying attention to Weibo and performance, the existing studies only consider social media adoption or not but do not take social media input intensity and its possible nonlinear influence on performance into consideration. Therefore, in this paper, we employed Weibo information from private listed firms from 2010 to 2014 to explore these issues in depth. 3. Hypothesis This section proposes the research hypotheses of this study. The main hypotheses include: first, launching Weibo accounts has significantly positive effects on firm performance; second, Weibo input intensity is positively correlated with performance, and an inverted U-shaped relationship between them exists; third, firm size and the type of real controller of firm play moderating roles on the relationship between Weibo input intensity and performance.
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3.1. Launching Weibo accounts and firm performance In recent years, the rapid rise of social media as the mainstream application on the Internet not only broadens the channels for firms to communicate with users and promote their products but also provides convenience for them to absorb external knowledge and promote a trend of community-based development of firms. It has been shown that social media would increase brand image and awareness [28], leading to electronic word-of-mouth (eWOM) advertising, which would then enhance users’ purchasing intention and ultimately provide firms better business performance [46,47]. With the rapid expansion of the number of users, firms are paying attention to Weibo as the most critical social media communication channel [48]. Weibo is a platform based on user relationships for information sharing and dissemination. For firms, Weibo has an enormous user base, provides low-cost channels of communication and utilizes an interactive way of communication, which can increase the mobility, real-time nature and socialization of firms’ communication of information [11]. Through Weibo, firms can not only promote new products or services but also increase attention through the interaction with users to improve their popularity and achieve rapid, comprehensive and extensive dissemination through real-time sharing of firm information. Jin et al. [49] found that firms could attract more users’ attention after launching Weibo accounts and trigger a large number of users’ forwards and comments in order to get more attention. Therefore, by building communication platforms and channels through Weibo, firms can present themselves and their products and services more comprehensively and extensively, thus improving their popularity, gaining more users’ attention, and achieving rapid and long-term growth of economic benefits by building a good corporate image. Based on this, this paper proposes the following hypothesis: H 1. Launching Weibo accounts has significantly positive effects on firm performance. 3.2. Weibo input intensity and firm performance Weibo input intensity measures the degree of firms’ operation level on Weibo after launching their accounts. The operation mode mainly includes the number of blog posts, the frequency of posting blogs within a certain period and the frequency of interaction with fans. In general, firms can obtain a certain positive influence in the initial stage of launching Weibo accounts, increasing users’ attention and brand awareness [50]. Therefore, by gaining a certain number of fans, if firms increase their input in Weibo and maintain continuous activity, this impact on firms will be decisive. This approach can not only update followers about recent developments within the firms but can also further increase the attention and memory of other non-concerned people. Generally, there is a positive correlation between media flow and its influence [51]. Firms can generate more information flow by strengthening Weibo input, which will increase the attention of followers and enhance brand awareness, leading to firms gaining advantages in the fierce market competition and thus improving profitability. However, on the other hand, if Weibo management is not continued in the later stage of operation, it may result in a large loss of attention and gradual decline in brand awareness, which would lead a brand to have difficulty achieving the desired effect of Weibo marketing [52]. Additionally, most people use Weibo mainly for entertainment purposes [53]. Accordingly, if firms input so much marketing information that does not match their perception, it might give users negative emotions, boredom or antagonism, which will then result in a negative performance. Therefore, Weibo input intensity might have a threshold; i.e., when Weibo input intensity exceeds such a threshold, the performance might decline. Based on this idea, this paper puts forward the following hypotheses: H 2a.
Weibo input intensity is positively related to the improvement of firm performance.
H 2b.
There is a nonlinear, i.e., inverted U-shaped, relationship between Weibo input intensity and firm performance.
3.3. The moderating effect of firm size and type of real controller Extant literature has verified that firm performance is affected by many factors. Amongst these, firm size plays an important role. The larger the size of the firm, the more it is able to reduce its production cost and thus improve its performance by virtue of its advantages via the scale effect [54]. Therefore, it could be said that firms of different sizes might have different operational behaviours. Therefore, firms of different sizes might have different attitudes towards Weibo input. Specifically, the larger the size of a firm, the more significant impact Weibo input will be on firm performance. Based on this, this paper puts forward the following hypothesis: H 3a.
Firm size has a positive moderating effect on the relationship between Weibo input intensity and firm performance.
In addition, the type of real controller of the firms will also have an impact on the performance. The type of real controller in this paper is divided into individual and non-individual (state-owned, foreign-owned, etc.). According to the existing literature, different real controller types can affect a firm’s market value orientation, so firms with different types of real controller may have different responses to Weibo input [55]. When the type of real controller is non-individual, Weibo input may have a more significant impact on firm performance; i.e., such firms can better improve performance. Based on this, this paper puts forward the following hypothesis:
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Fig. 1. Research framework of the present study.
H 3b. Type of real controller has a negative moderating effect on the relationship between Weibo input intensity and firm performance. Research framework of this paper is presented in Fig. 1. 4. Data and methods 4.1. Data sources This paper selected private listed firms in China and from the China Stock Market & Accounting Research Database during the period of 2010 and 2014 as the research objects. The specific steps of sample data cleaning are presented as follows: first, we deleted any abnormal values; if firms’ age was listed as negative and the number of employees is zero, related records were dropped. Second, we obtained data on firms’ Weibo accounts from the Sina Weibo website, including whether firms had Weibo accounts or not and the number of Weibo posts in each year. Here, we got balanced panel data from 732 firms and 3660 records to conduct analysis for the relationship between launching Weibo account and firm performance. Third, to further analyse the relationship between Weibo input intensity and firm performance, we deleted firm records that launched Weibo accounts but did not post any Weibo information. According to this process, unbalanced panel data from 185 firms and 585 records were obtained. 4.2. Variable settings This paper explores whether firms launching Weibo accounts or not can improve performance, and how input intensity affects firm performance. Accordingly, here we describe the dependent variable, independent variables and control variables that influence firm performance. The specific variables are set as follows: Dependent variable: firm performance. Relevant literature point out that the main indicators to measure firm performance include financial and market indicators [56]. However, financial indicators, such as the return on assets (ROA), are easily affected by accounting data and be subject to human manipulation [57]. Thus, they cannot truly reflect the situation of listed firms. Therefore, this paper uses Tobin’s Q as an index of firm performance. The main reason for this is that this index takes the market value of listed firms into consideration, which can avoid the influence of human manipulation to a certain extent and, thus, can reflect the performance of listed firms more accurately. For the calculation of Tobin’s Q, this paper refers to the method of O’Brien et al. [58], which provides the following formula: Tobin′ sQ =
MVE + PS + DEAT
(1) TA where MVE denotes firms’ circulatable stock market value, PS is the liquidation value of the preferred shares, DEAT is the book value of the debts, and TA is the book value of the total assets at the end of the period. Independent variables: Launching Weibo accounts and Weibo input intensity. First, this paper employs a dummy variable to measure whether firms launch official Weibo accounts or not. A value of 1 indicates that a firm has launched the official Weibo account (with blue and V marks in Sina Weibo), while 0 denotes that a firm has not opened an official Weibo account. Second, if a firm has launched its official Weibo account, this paper proposes an index to measure Weibo input intensity in order to judge the degree of a firm’s input in Weibo after launching its account. Specifically, the Weibo input intensity of a firm is calculated by the following formula. CWP (2) LAW where WII refers to Weibo input intensity, CWP means the cumulative number of Weibo posts issued by each firm during the observation period, LAW denotes the difference between the year of firms’ launching Weibo accounts and the observation year. WII =
6
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Table 1 Description of variables used in the present study. Variables
Abbreviations and related definitions
Dependent variable
firm performance
FP: Tobin’s Q
Independent variables
launching Weibo Weibo input intensity
LW: 0 = Not launching, 1 = Launching WII: Cumulative number of Weibo posts per year/ Weibo launching age
Control variable
firm age
FA: the logarithmic value of a difference between observation year and the year of listing FZ: the logarithmic value of major business income of a firm TRC: 0 = non-individual (state-owned, foreign-owned, etc.), 1 = individual IDN: the number of independent directors in each year
firm size type of real controllers the number of independent directors
Control variables. According to existing studies, firm performance will be affected by many other factors, such as firm size, firm age, etc. [59]. To control the influence of these factors, this paper selects firm age, firm size (logarithmic value of major business income used), type of real controller and the number of independent directors as the control variables. In addition, in order to test whether there are moderating effects between firm size and type of real controller on the relationship of Weibo input intensity and firm performance, this paper also tests these interaction items. It is worth noting that the interaction items are standardized prior to analysis in order to avoid multiple collinearities [60]. Note that industries and years are both controlled in regression models. The description of variables is shown in Table 1. 4.3. Methods This paper uses panel data from the period between 2010 and 2014. Currently, there are three common panel data models: mixed least square model, fixed effect model, and random effect model. Considering the possible heterogeneity among industries in this study, a fixed-effect or random-effect model is used. The regression equation is set as follows: FP = α + β1 LWit + β3 FAit + β4 FZit
+ β5 TRCit + β6 IDNit + αi + εit
(3)
FP = α + β1 WIIit + β3 FAit + β4 FZit
+ β5 TRCit + β6 IDNit + αi + εit
(4)
where i represents the industry and t denotes year. αi means other unobservable factors, and εit indicates the residual term. To judge whether to use fixed effect or random effect models, the Hausman test is employed. It should be noted that time effect is also considered in the model. 5. Findings This subsection consists of two parts. First, a descriptive analysis of variables is performed. Then, a regression analysis is performed to test the hypotheses. 5.1. Descriptive analysis Table 2 presents the descriptive analysis of the variables in this study. Each variable fluctuated stably according to variables’ mean value and standard deviation in the table. The Spearman correlation coefficient is shown in the table since nominal variables are included. Specifically, it can be seen that both launching Weibo accounts (0.013) and Weibo input intensity (0.025) are positively correlated with firm performance, which can be preliminarily interpreted as showing that launching Weibo accounts can improve firms’ performance. The greater a firm’s input in Weibo is, the greater the improvement of firm performance. In addition, when observing each control variable, it was found that firm age, firm size and the number of independent directors have a significantly positive relationship with firm performance. These coefficients are 0.432, 0.453 and 0.099, respectively, all of which are statistically significant at the significance level of 0.01. However, the type of real controllers has a significant negative connection (−0.169) with firm performance, which is also statistically significant. 5.2. Regression analysis To test the hypotheses proposed above, this paper conducted a regression analysis and used a hierarchical regression method to gradually bring control variables, independent variables, and moderators into the model. The specific results are shown in Tables 3 and 4. First, we analysed whether launching Weibo accounts can improve firms’ performance. Table 3 shows the regression results of the connection between these variables. Model 1 only includes the control variables and the dependent variable.
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Table 2 Descriptive analysis and correlation coefficient matrix of variables. 1. 2. 3. 4. 5. 6. 7.
FP LW WII FA FZ IDN TRC
Mean
St. D
1
2
3
4
5
6
0.411 0.158 0.760 7.716 20.806 3.121 0.905
0.555 0.365 1.938 6.086 1.340 0.514 0.293
1 0.013 0.025 0.432*** 0.453*** 0.099*** −0.169***
1 0.974*** 0.029* 0.122*** 0.048*** 0.033**
1 0.029* 0.131*** 0.048*** 0.024
1 0.169*** 0.014 −0.310***
1 0.176*** −0.077***
−0.051***
1
Table 3 Regression results of launching Weibo account and firm performance. Variable
Model 1
Model 2
FA
0.248*** (0.021) 0.085** (0.028) 0.005*** (0.001) 0.048** (0.016)
0.248*** (0.021) 0.086** (0.028) 0.006*** (0.001) 0.049** (0.016) 0.062*** (0.011) 2.146** (0.612) 0.496 0.365 248.180 0.000
FZ IDN TRC: non-individual LW Constant term 2
R Adjusted R2 F value P value Hausman test Industry effect Year effect
2.127** (0.621) 0.495 0.364 134.010 0.000 P = 0.000 Yes Yes
Yes Yes
Note: Numbers in brackets are robust standard errors; *** p < 0.01, ** p
< 0.05, * p < 0.1.
Overall, firm age, firm size, the number of independent directors and type of real controllers are all positive determinants of firm performance, which is consistent with the finding of previous studies [61,62]. Model 2 introduces launching Weibo accounts on the basis of Model 1. Specifically, by comparing these two models with other factors unchanged, it can be seen that firm performance was significantly enhanced by 0.062 units after firms launch Weibo accounts, denoting that firms can indeed improve their performance by launching Weibo accounts. Therefore, H 1 is confirmed. This result might indicate that Weibo is a new channel connecting firms and users [48]. When firms launch Weibo accounts, they can directly talk with customers and get timely feedback, which allows the firms to launch new products or optimize existing products thus seizing market opportunities, gaining competitive advantages and improving firm performance [49]. In addition, this paper also considered the different effects of Weibo input intensity on firm performance, and the results are shown in Table 4. Model 1 still consists of only control variables, which are proved to be significantly positive factors affecting firm performance. Model 2 adds Weibo input intensity on the basis of Model 1. When other factors remain unchanged, greater input in Weibo leads to improvement of firm performance. Specifically, after firms launch Weibo accounts, the firm performance is improved by 0.014 units for each unit of increase in Weibo input intensity, and this result is significant at the α = 0.05 level. Therefore, Hypothesis 2a is confirmed. Further, we checked if there is a nonlinear relationship between Weibo input intensity and firm performance. To this end, we standardized the quadratic term of Weibo input intensity to avoid a multicollinearity problem, and the result is shown by Model 3. This shows that the coefficient of WII2 is −0.001 while WII is 0.013, both of which are significant. This result verifies H 2b that there is an inverted U-shaped relationship between Weibo input intensity and firm performance, indicating that firms first obtain benefits from the launching of Weibo accounts but sustain losses when the input in Weibo is too high. The reason for this finding might have two distinct aspects. Initially, firms inputting more into Weibo could attract more attention from followers and enhance brand awareness, thus leading to a more beneficial result [51]. However, when the critical point is exceeded, information bombing would annoy customers and thus obtain lower revenue. This paper also studied the moderating effect of firm size and type of real controllers in the regression model of Weibo input intensity on firm performance to verify the consistency of results. Firm size was found to have a significantly positive effect on performance (β = 0.009; α = 0.1). Thus, Hypothesis 3a is verified, indicating that bigger firms may see an increase in performance due to input in Weibo, which is intuitively reflected in Fig. 2. However, the type of real controller plays a negative moderating role, but this result was not statistically significant. Hypothesis 3b is therefore partially verified.
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X. Zu, X. Diao and Z. Meng / Physica A 536 (2019) 122556 Table 4 Regression results of Weibo input intensity and firm performance. Variable
Model 1
Model 2
Model 3
Model 4
Model 5
FA
0.119** (0.041) 0.032*** (0.005) 0.022** (0.006) 0.058*** (0.007)
0.127* (0.047) 0.030*** (0.005) 0.020** (0.006) 0.053*** (0.006) 0.014** (0.004)
0.118*** (0.008) 0.062*** (0.015) 0.006 (0.007) 0.052* (0.031) 0.013** (0.005) −0.001*** (0.000)
0.135** (0.040) 0.026*** (0.004) 0.020** (0.006) 0.056*** (0.005) 0.013* (0.005)
0.121* (0.046) 0.030*** (0.006) 0.020** (0.007) 0.165* (0.077) 0.014** (0.004)
FZ IDN TRC: non-individual WII WII2 FZ * WII
0.009* (0.004)
TRC * WII Constant term R2 Adjusted R2 F value P value Hausman test Industry effect Year effect
−0.011 0.141*** (0.025) 0.664 0.477 32.000 0.002
0.148*** (0.021) 0.668 0.481 33.620 0.002
Yes Yes
Yes Yes
0.253*** (0.071) 0.687 0.511 86.24 0.000 P = 0.000 Yes Yes
0.136*** (0.023) 0.668 0.481 43.810 0.001
(0.007) 0.129*** (0.021) 0.668 0.481 45.360 0.002
Yes Yes
Yes Yes
Note: Brackets are robust standard errors. *** p < 0.01, ** p < 0.05, * p < 0.1.
Fig. 2. Moderating effect graph of firm size.
In addition, by observing the control variables, we found that the results presented in Tables 3 and 4 are generally consistent; that is, firm age, firm size, the number of independent directors and type of real controllers all significantly increase firm performance, indicating that these factors are effectively controlled. 6. Conclusions In the era of the Internet, there are a growing number of firms that publicize their products through Weibo. As such, numerous studies focus on Weibo related issues. However, few studies have explored the impact of firms launching Weibo accounts and input intensity on their performance. Therefore, this paper empirically tests this relationship using panel data matched with Sina Weibo data and data from private listed firms in China from 2010 to 2014. The results show that launching Weibo accounts can increase firm performance, and the greater a firm’s input intensity in Weibo is, the more obvious the improvement of performance. However, this relationship is not always linear and is actually an inverted U-shaped relationship. In addition, firm size has a significantly positive moderating effect, indicating that bigger firms’
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input in Weibo might increase more performance. However, type of real controllers does not have a statistically significant moderate effect on the relationship between Weibo input intensity and firm performance. Our results have some theoretical and practical implications. First, previous studies have investigated firm performance and examined the role of social media in it. However, these studies focus more on social media adoption and firm performance. The study of Weibo input intensity has been limited. Therefore, this study extends our understanding on Weibo input intensity and firm performance. Second, this study also extends the extant stream of social media studies by analysing the non-linear relationship between Weibo input intensity and firm performance, which may expand current research findings. Finally, the non-linear relationship between Weibo input intensity and firm performance indicates that firms do not need to blindly increase Weibo input intensity; they should instead increase appropriately and moderately to achieve optimal firm performance. However, although some progress has been made, there are some limitations in this study. For example, many factors affect firm performance, but based on the principle of data availability, only some of the variables affecting firm performance are controlled in this paper. Therefore, in future research, more relevant factors can be included to build a more comprehensive analysis framework. In addition, this paper analyses data only from the perspective of firms. As Weibo connects firms and customers, customer feedback is crucial for firms to understand market trends and develop relevant strategies to improve performance. Therefore, in future research, we can conduct a study from the perspective of customers to study the impact of consumer feedback on firm performance, which would enrich existing research. Acknowledgements This research was supported by the National Natural Science Foundation of China (Grant No. 71903139) and the Humanities and Social Sciences Foundation of the Ministry of Education of China (Grant No. 16YJC630089). It was also support by the Soft Science Program of Sichuan Province (Grant No. 2019JDR0155) and Basic Scientific Research Service Fee Project of Central Universities of Sichuan University (Grant No. 2019 Self Research-BusinessC03). References [1] S. Yang, M. Ishtiaq, M. Anwar, Enterprise risk management practices and firm performance, the mediating role of competitive advantage and the moderating role of financial literacy, J. Risk Financial Manag. 11 (2018) 35–51. [2] B.J. Zirger, M.A. Maidique, A model of new product development: An empirical test, Manage. 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