1 + 1 < 2! Effects of Social Media Engagement and Advertising on Firm Value of Tourism and Hospitality Companies

Abstract

Engaging customers via social media networking has become a rising trend of investments for tourism and hospitality firms. This new trend is termed “social media engagement.” However, whether social media engagement can actually lead to increased financial value for tourism and hospitality firms is doubted. This study theorizes and empirically examines the relationship between social media engagement and intangible value of tourism and hospitality firms, and the joint effects of social media engagement and advertising investments on firm value. Using a daily longitudinal data set from tourism and hospitality firms that have issued domestic A-shares in China, this study finds that social media engagement has a significant and positive relationship with the firm value of tourism and hospitality companies. However, the two types of investments interact as substitutes, such that increasing advertising investments attenuate the beneficial effect of social media engagement on firm value.

Keywords

social media engagement user-generated content advertising investments firm value customer-based brand equity

Introduction

The literature in tourism and hospitality has demonstrated that nowadays, consumers rely on Internet-based sources to make travel-related decisions (Mariani et al., 2018). One major source of information is social media platforms, which help consumers post their comments, share their opinions, and communicate about other brand-related content with the firm and other consumers (Xiang & Gretzel, 2010). Therefore, it has become a rising trend for tourism and hospitality firms to engage and co-create value with consumers on social media networks, through which consumers can interact more with firms and other consumers (S. Yang et al., 2016).

While the importance of social media engagement has been increasingly discussed in hospitality and tourism, prior studies in this domain have focused predominantly on the impacts of social media engagement on consumers (e.g., Dijkmans et al., 2015; Hudson et al., 2015), employees (e.g., Sigala & Chalkiti, 2015; F. Yang, 2020), or firm performance (e.g., Garrido-Moreno et al., 2018; B. Kim et al., 2016; S. Lin et al., 2018). However, researchers have not yet explored the effects of social media engagement in the tourism and hospitality industry on firm value. Most practitioners in this industry are skeptical about the effectiveness of social media engagement strategies. Specifically, tourism and hospitality practitioners are not sure whether social media indeed generates a return on investment (Aluri et al., 2015; Phelan et al., 2013). Thus, there is a gap between the current literature and practitioners in the tourism and hospitality industry. This study inquires: Does social media engagement affect hospitality and tourism firms’ value and if so, how?

Moreover, we attempt to examine the joint effect of social media engagement and advertising investments on firm value. More specifically, we explore the moderating impact of advertising investments on the effect of social media engagement on firm value. Advertising represents an effective value-appropriation strategy through increasing brand equity, which helps persuade potential customers, increase awareness, and provide relevant information (Chen et al., 2012). Hence, investigating whether social media engagement should be deployed in isolation, or in combination with advertising is needed.

These are the research questions we seek to answer. To do so, we obtained a longitudinal data set from tourism and hospitality firms that have issued domestic A-shares in China and empirically examine the relationships between social media engagement and firm value. The key contributions of this study are two-fold. First, we contribute to relevant literature on social media engagement by quantifying the financial value of social media engagement empirically for tourism and hospitality companies. Second, this study offers practical insights to assist tourism and hospitality firm managers in understanding their investments in social media engagement and advertising investments.

Theoretical Background and Hypotheses Development

Social Media Engagement

Social media are collaborative, dynamic, and interactive online applications, platforms, and media, which allows the creation and exchange of user-generated content on social media platforms (Kaplan & Haenlein, 2010). In recent years, social media has grown exponentially and been exploded as a category of online discourse where users create content, share, and have discussions in communication networks. Social media benefits the hospitality and tourism industry by attracting consumers to interact with their brands, building up friendly attention toward brands, and then simulating consumers’ desire for hotels and travels (Garrido-Moreno et al., 2018).

Following S. Yang et al. (2016), we define “social media engagement” as the extent to which brands utilize social media networks to engage consumers and encourage consumers to interact with their brands and other consumers. In particular, social media engagement in this study is measured by activities performed on the brands’ owned social media (OSM), such as Twitter accounts, Facebook fan pages, and official Sina Weibo brand page. The concept of social media engagement parallels a wide range of social media-related concepts and reflects the nascent development of research on social media. Studies in marketing find that the use of social media affects consumer attitude (Ki & Kim, 2019), consumer satisfaction (Agnihotri et al., 2016), consumer spending and purchase behaviour (Hajli, 2014; Kumar et al., 2016; Mayrhofer et al., 2020), electronic word-of-mouth behavior regarding the brand and its services or products (T. Kim et al., 2019), firm revenue (Yoon et al., 2018), firm value (Colicev et al., 2018; Nguyen et al., 2020), stock returns (Nam & Kannan, 2014; Van Dieijen et al., 2020), Tobin’s Q (Wang & Kim, 2017), and consumer–firm relationships (Chuang, 2020).

In the field of hospitality and tourism, fundamentally, research has studied the effects of social media from three aspects (see Table 1). First, an increasing number of studies have examined the effects of social media on consumers’ perceptions, attitudes, and behaviour. For example, Noone and McGuire (2013) find that review information and aggregate ratings play a significant role in consumers’ evaluations of quality. Leung et al. (2013) find that customers’ experience on a hotel’s social media page positively affect their attitudes toward a social media site, which in turn influences their attitudes toward a hotel brand, and then affects their hotel booking intentions. Dijkmans et al. (2015) indicate that the intensity of consumers’ use of social media is positively related to their engagement in social media activities and consumers’ perception of corporate reputation. Touni et al. (2020) show that customer engagement in social media is a significant indicator of a brand’s relationship quality.

Table 1

An Overview of Selected Empirical Research on Social Media in Hospitality and Tourism

Aspects	Authors	Independent Variable	Dependent Variable	Method
Consumers	So et al. (2012)	Customer engagement	Behavioural intention of loyalty	Survey
	Leung et al. (2013)	Social media experience	Attitude toward hotel brand	Survey
	Aluri et al. (2015)	Website with social media channels	Social satisfaction of perceived social interaction	Experiment
	Hudson et al. (2015)	Social media interaction	Word of mouth	Survey
	Book et al. (2015)	Online reviews	Purchase decisions	Survey
	Šerić and Praničević (2017)	Consumer-generated reviews on social media	Brand satisfaction, trust, commitment, loyalty	Survey
	Narangajavana, Luis, et al. (2017)	User-generated content in social media	Tourist satisfaction with the destination	Survey
	Narangajavana, Callarisa, et al. (2017)	The intensity of social media use	Tourist expectations	Survey
	Noone and McGuire (2013)	Review information, aggregate ratings information	Consumers’ prepurchase evaluations of variably priced services	Survey
	Ou et al. (2020)	Customer engagement	Attitudinal loyalty, behavioral loyalty	Survey
	Shin and Back (2020)	Customer–brand engagement	Brand loyalty and love	Survey
Firms	W. G. Kim et al. (2015)	Overall ratings, the response rate	Hotel performance (average daily rate and revenue per available room)	Secondary data
	B. Kim et al. (2016)	Social media reviews	Restaurant performance	Secondary data
	Xie et al. (2016)	The rating and volume of reviews on social media	Hotel performance	Secondary data
	W. G. Kim and Park (2017)	Traditional customer satisfaction, the rating of social media comments	Hotel performance (average daily rate, revenue per available room, total revenue per available room)	Secondary data
	Garrido-Moreno et al. (2018)	Social networking use and review sites use	Social customer relationship management performance	Survey
Employees	Sigala and Chalkiti (2015)	Social media use	Employee creativity	Survey
	F. Yang (2020)	The intensity of social media use	Workplace fun, workplace stress	Survey
	Xu and Wang (2020)	Customer interactivity	Employee innovation behavior	Survey

Several studies have also investigated the effects of social media on firms’ performances. For example, B. Kim et al. (2016) indicate that the number of online reviews on social media sites positively affects restaurant performance. W. G. Kim and Park (2017) find that social media ratings have a significant and positive effect on hotel performance. Garrido-Moreno et al. (2018) suggest that both the use of social networking and review sites positively affect hotels’ social CRM performance. S. Lin et al. (2018) show that social media engagement is positively related to hotels’ display advertising performance. Also, a few studies have examined the effects of social media use with company employees. For instance, Sigala and Chalkiti (2015) find that the use of social media for knowledge management processes is positively related to employee creativity. F. Yang (2020) finds that social media use intensity with coworkers is positively related to workplace fun and workplace stress.

While the effects of social media engagement have been increasingly discussed in the field of hospitality and tourism, one key aspect that remains underexplored is whether social media engagement can increase firm value. Although social media is claimed to be effective in improving firm value, there has been limited empirical evidence to support these claims (Leung et al., 2013). More important, it remains unclear as to whether social media should be deployed in isolation, or in combination with traditional value-appropriation activities such as advertising.

Social Media Engagement and Firm Value

The firm’s value consists of the present value of a firm’s cash flows during its value growth period and the long-term value of its products at the end of the value growth period (Day & Fahey, 1988). It is determined by investor expectations of the firm’s future cash flows (Srivastava et al., 1998). In this study, firm value is measured by abnormal returns, which capture a firm’s stock return above and beyond the firm’s expected stock market return (Luo et al., 2013). Therefore, we expect that firms will attain higher value when they have a higher level of social media engagement for several reasons.

First, we employ the social capital theory, the social cognitive theory, and customer-based brand equity literature to explain the relationship between tourism and hospitality firms’ social media engagement and firm value. The rationale is that social media engagement helps firms establish customer-based customer equity, and such customer equity creates more value for the company. Firms now rely on a set of social media marketing activities to leverage opportunities for engaging consumers, allowing consumers and firms to express various facets of their relationships (Schmitt, 2012; Wright et al., 2010). The social capital theory suggests that social capital obtained from social relationship networks helps brands create customer equity, which is viewed as “the differential effect that brand knowledge has on customer response to the marketing of that brand” (Keller, 2013). Meanwhile, the social cognitive theory suggests that consumers can learn about a brand through brand-related content on social media platforms generated by the brand and other consumers, thereby strengthening their brand familiarity, brand associations, and quality perceptions (A. J. Kim & Ko, 2010; Laroche et al., 2012). When consumers are familiar with the brand and hold favorable and robust brand associations in their memory, customer-based brand equity occurs.

On the other hand, customer-based brand equity literature suggests that customer-based brand equity can broaden stock ownership (Frieder & Subrahmanyam, 2005). Customer equity is considered the key driver of shareholder value and the most determinant of long-term firm values (K. H. Kim et al., 2010). For example, Barth et al. (1998) posit that brand valuation positively increases stock returns. Similarly, Madden et al. (2006) point out that strong brands are associated with greater stock returns. Therefore, as a component of social capital, firms’ social media engagement might establish distinct customer-based brand equity and then create firm value.

Second, when information created in social media networks is continuously updated, social media is more advanced and ahead than firms’ other information sources (e.g., financial figures). Given that firm value reflects firms’ all available information (Fama, 1970), the information created and shared on social media should be reflected in the firm’s value. Social media characteristics such as brand-related content on social media can determine consumers’ evaluation of the brand. Some scholars argue that social media engagement represents consumer satisfaction and word-of-mouth advertising (Luo et al., 2013). In particular, social media engagement is an indicator of customers’ satisfaction and, thus, an indicator for firm performance, such as sales. Therefore, social media engagement reflects an information source of firm performance, which in turn could be used by investors as a tool for predicting firm value. Some studies support the notion that investors heed the information generated on firms’ social media platforms (Chen et al., 2012). Taken together, we argue that social media engagement is positively associated with firm value. Thus, we propose that

Hypothesis 1₀: Social media engagement does not relate to the firm value of tourism and hospitality companies.

Hypothesis 1_a: Social media engagement has a positive relationship with firm value of tourism and hospitality companies. Specifically, social media engagement increases tourism and hospitality firms’ abnormal stock returns.

Social Media Engagement, Advertising Investments, and Firm Value

We now consider how advertising expenditures influence the effect of social media engagement on the firm value of tourism and hospitality companies. Previous studies have noted that advertising helps firms increase their financial value. For example, Assaf et al. (2015) indicate that advertising investments have a positive effect on firm performance, and the effect will be more substantial for larger hotels and higher star rating hotels. Hsu and Jang (2008) suggest that advertising investments could help generate intangible value for restaurant firms. Similarly, J. Kim et al. (2019) find that incremental advertising spending improves stock value.

We further examine the joint effect of social media engagement and advertising on firm value. We postulate that the joint effect will be substitutive. In other words, advertising expenditures negatively moderate the positive effect of social media engagement on firm value. We explain this postulation from both firms and consumers’ perspectives.

On the one hand, Olson et al. (2005) suggest that when both the activities of the firm lead to the same outcome, they will exhibit redundancy and inefficiencies, mainly when the two activities are determined by different units of the firm. In a typical company, social media and traditional advertising are usually managed by different marketing groups. Increasing investments in both activities might lead to resource misallocation (Rothaermel & Hess, 2007), and thus results in coordination difficulties between the two groups. Such coordination difficulties can reduce stock returns and increase the variability of future cash flows. Thus, we propose that social media engagement and advertising interact as substitutes, which increases resource misallocation and inefficiencies and consequently reduce firm value.

On the other hand, previous studies on social media have found that advertising in the environment of brands’ OSM helps more in increasing consumers’ awareness and familiarity than reducing their uncertainty or perceived risk (Dost et al., 2019). Thus, with the increase of advertising exposure, the incremental effect of social media engagement on brands’ OSM on awareness would be lower. Similarly, Dost et al. (2016) indicate that word of mouth initiated by brands toward consumers who are already aware of the product leads to a weaker sales effect. Therefore, when consumers evaluate firms with high advertising expenditures, their high level of awareness and familiarity with the brands should attenuate their reliance on social media engagement, thus reducing its positive effect on firm value.

Formally, we propose that

Hypothesis 2₀: Tourism and hospitality firms’ advertising investments does not moderate the effect of social media engagement on firm value.

Hypothesis 2_a: Tourism and hospitality firms’ advertising investments attenuate the positive effect of social media engagement on firm value. Specifically, an increase in advertising decreases the positive effect of social media engagement on abnormal stock returns.

Methodology

Data

In this study, we selected firms in the tourism and hospitality industry that issued domestic A-shares in China. We checked all listed firms that had issued domestic A-shares in China by December 29, 2017, and found that 32 firms were in this industry. Among the 32 firms, 10 companies have not set up an active Sina Weibo account. We thus chose the other 22 firms as samples of tourism and hospitality firms in this study.

We collected the data set from two secondary sources. First, we obtained the 22 firms’ daily social media engagement data from Sina Weibo with the help of a consulting firm. Sina Weibo is the most popular social networking website for firms in China. Most Chinese firms set up their official Sina Weibo brand page to enable users to communicate with companies as well as other Sina Weibo users. We checked the Sina Weibo accounts of the firms and collected their daily engagement data from the date that the firms set up their Sina Weibo site to December 29, 2017. Following previous literature (Ge & Gretzel, 2018; Jung et al., 2019), we measure a firm’s social media engagement as the daily total number of likes, comments, and forwards of all posts on the firm’s official Sina Weibo brand page on each day. All likes, comments, and forwards are consumer actions toward the posts that are posted on the firm’s Sina Weibo account (see Supplement Figure 1, available online).

Second, we obtained firms’ financial information from the China Stock Market & Accounting Research Database (CSMAR), which is maintained by the University of Hong Kong and the Shenzhen GuoTaiAn Company. In essence, the CSMAR provides comprehensive data on Chinese stocks and is widely used for studying Chinese firms’ financial performance in finance and accounting (Huang & Song, 2006). We required the 22 firms to have available data on CSMAR during their Sina Weibo post period. However, 3 of the 22 firms did not report advertising investment data during this period. This leads to our final data set of 8,339 observations from 19 firms.¹ Finally, we collected daily data on the risk factors (i.e., market, size, value, profitability, and investment) from Kenneth French’s Data Library. We summarize variables, measures, and data sources in Supplement Table 1 available online.

Model Specifications

For the dependent variable, we followed previous literature (e.g., Fama & French, 2015; Q. Lin, 2017) and estimated the Fama–French five-factor model as follows:

\begin{matrix} R_{i t} - R_{f t} = β_{0 i} + β_{1 i} (R_{m t} - R_{f t}) \\ + β_{2 i} S M B_{t} + β_{3 i} H M L_{t} + β_{4 i} R M W_{t} \\ + β_{5 i} C M A_{t} + e_{i t} \end{matrix}

(1)

where R_it represents the stock returns for firm i on day t, R_ft represents the risk-free rate on day t, R_mt represents the market return on day t, SMB_t represents the Fama–French size effect on day t, HML_t represents the value effect on day t, RMW_t represents the profitability factor on day t, and CMA_t represents the investment factor on day t. We ran Model (1) for a rolling window of 90 trading days prior to the target day.

Abnormal returns. Abnormal returns capture a firm’s market performance beyond the firm’s expected stock market return (Luo et al., 2013; Wei et al., 2017), which are calculated as the difference between the actual return and the expected return.

A R_{i t} = (R_{i t} - R_{f t}) - (\begin{array}{l} {\hat{β}}_{0 i} + {\hat{β}}_{1 i} (R_{m t} - R_{f t}) \\ + {\hat{β}}_{2 i} S M B_{t} + {\hat{β}}_{3 i} H M L_{t} \\ + {\hat{β}}_{4 i} R M W_{t} + {\hat{β}}_{5 i} C M A_{t} \end{array})

(2)

where $\hat{β}$ represents the factor coefficients estimated from Equation 1.

To test our hypotheses, we regress firms’ abnormal returns against social media engagement, advertising investments, and their interactions in Model (3). Although we have included a comprehensive set of control variables in our models, there might be unobservable heterogeneity in our unbalanced panel data. To control for the possible unobservable heterogeneity, we also include the fixed effects of firms. For firm i at day t, we specify the models for abnormal returns as follows:

\begin{matrix} A R_{i t} = β_{0} + β_{1} S o c i a l_{i t} + β_{2} A d_{i t} + β_{3} S o c i a l_{i t} * A d_{i t} \\ + β_{4} T {obinQ}_{i t} + β_{5} A s s e t s_{i t} + β_{6} R O A_{i t} \\ + β_{7} S e l l i n g_{i t} + β_{8} M a n a g e m e n t_{i t} \\ + β_{9} F i n a n c i a l_{i t} + L e v e r a g e_{i t} \\ + β_{11} L i q u i d i t y_{i t} + β_{12} C o n c e n t r a t i o n_{i t} \\ + \sum^{} a_{t} W e e k d a y_{t} + \sum^{} α_{k} F i r m_{k} + e_{i t} \end{matrix}

(3)

where Social_it is the social media engagement for firm i on day t, Ad_it is the advertising expenditures for firm i on day t, Tobin Q_it represents the intangible value of firm i on day t, Assets_it represents the total assets of firm i on day t, ROA_it represents the return on assets of firm i on day t, Selling_it, Management_it, and Finance_it represents the selling investment, management investment, and financial investment of firm i on day t, Leverage_it represents the financial leverage of firm i on day t, Liquidity_it represents the liquidity of firm i on day t, Concentration_it represents the ownership concentration of firm i on day t, variable t represents the time trend, Firm_i represents the dummy variable for each firm, and e_it represents the error term.

Results

Table 2 presents the descriptive statistics and correlation matrix for key variables. Table 3 presents the results of the fixed-effect models specified in Equation 3. Column 1 contains only the main effects of social media engagement. In column 2, we include the main effects of both social media engagement and advertising investments. Finally, as specified in Equation 3, column 3 includes the interaction effects between social media engagement and advertising investments as well as their main effects. We test our hypotheses based on the results of column 3.

Table 2

Descriptive Statistics and Bivariate Correlation

	M	SD	1	2	3	4	5	6	7	8	9	10	11	12
1. AR	0.114	2.564	1
2. Social	2.601	2.113	0.014	1
3. Ad	10.944	1.542	0.007	0.143	1
4. TobinQ	2.136	0.896	0.144	−0.195	−0.287	1
5. Assets^a	38.3^a	78.9^a	−0.031	−0.084	0.420	−0.195	1
6. ROA	0.037	0.035	−0.081	−0.173	−0.228	0.319	−0.016	1
7. Selling	0.118	0.118	−0.028	−0.257	−0.170	0.062	−0.167	0.036	1
8. Management	0.194	0.124	0.012	−0.254	−0.407	−0.006	0.212	0.165	0.265	1
9. Financial	0.053	0.189	0.004	−0.119	0.255	−0.151	0.852	−0.064	−0.121	0.367	1
10. Leverage	2.082	13.424	−0.044	−0.068	−0.059	−0.032	−0.046	−0.070	0.094	0.182	−0.023	1
11. Liquidity	0.313	0.102	−0.039	0.012	−0.189	−0.010	−0.035	−0.057	0.407	−0.086	−0.092	−0.210	1
12. Concentraction	0.219	0.100	0.040	−0.013	0.270	0.102	−0.097	−0.154	−0.172	−0.186	0.103	−0.126	−0.029	1

Note: AR = abnormal return; Social = social media engagement; Ad = advertising investments; TobinQ = Tobin’s Q; Assets = total assets; ROA = return of assets; Selling = selling investment; Management = management investment; Financial = financial investment; Leverage = financial leverage; and Concentration = ownership concentration. Correlations in boldface are significant at p < .05.

For readability, values are multiplied by 10⁻⁸.

Table 3

Estimates Results of Equation 3

Variable	(1)	(2)	(3)
Social	0.046** (0.01)	0.039** (0.01)	0.308** (0.10)
Ad		0.279*** (0.05)	0.339*** (0.06)
Social × Ad			−0.025** (0.01)
TobinQ	1.831*** (0.06)	1.836*** (0.06)	1.833*** (0.06)
Assets^a	−0.393 (0.30)	−0.616* (0.30)	−0.569 (0.30)
ROA	−7.326*** (1.25)	−9.432*** (1.31)	−9.437*** (1.31)
Selling	−12.652*** (1.29)	−12.641*** (1.28)	−12.761*** (1.28)
Management	5.335*** (0.71)	4.961*** (0.71)	5.012*** (0.71)
Financial	−2.519*** (0.67)	−2.432*** (0.67)	−2.431*** (0.67)
Leverage	−0.008** (0.002)	−0.008*** (0.002)	−0.008 (0.002)
Liquidity	−4.172*** (0.47)	−4.302*** (0.47)	−4.275*** (0.47)
Concentration	1.704* (0.73)	1.708* (0.72)	1.529* (0.73)
Fixed effects of firms	Yes	Yes	Yes
Fixed effects of day of week	Yes	Yes	Yes
Intercept	−1.999*** (0.36)	−4.771*** (0.62)	−5.381*** (0.66)
AIC	38014.37	37986.39	37980.26
BIC	38112.77	38091.82	38092.72

Note: Ad = advertising investments; TobinQ = Tobin’s Q; Assets = total assets; ROA = return of assets; AIC = Akaike’s information criteria; BIC = Bayesian information criteria. Dependent variable is abnormal return. Robust standard errors. Standard errors are in parentheses.

For readability, coefficients for Assets are multiplied by 10¹⁰.

p < .05. ^**p < .01. ^***p < .001.

Hypothesis Testing

The main effect of social media engagement (Hypothesis 1). As shown in column 3, the effect of social media engagement on abnormal returns is positive and significant (β₁ = 0.308, p < .01). It suggests that social media helps increase the financial value of tourism and hospitality firms. Thus, Hypothesis 1_a is supported. Additionally, column 3 shows that advertising has a positive and significant association with abnormal returns of tourism and hospitality firms (β₂ = 0.339, p < .001). This finding is consistent with prior research (e.g., Frennea et al., 2019).

The joint effect of social media engagement and advertising on abnormal returns (Hypothesis 2). Hypothesis 2_a predicts that the joint effect of social media engagement and advertising on firms’ abnormal returns will be negative. As shown in column 3 in Table 3, the interaction of social media engagement and advertising has a negative and significant effect on firm value (β₃ = −0.025, p < .01). This implies that firms’ advertising expenditures attenuate the positive effect of social media engagement on firms’ abnormal returns, although social media engagement and advertising may separately increase abnormal returns. Thus, Hypothesis 2_a is supported.

To obtain more insights into the interaction effect, we follow Aiken and West (1991) and plot the interaction between social media engagement and advertising for abnormal returns in Figure 1. Specifically, the points in the diamond shape represent a low level of advertising investments, and the points in the square shape represent a high level of advertising investments. The values of social media engagement and advertising in the plot are chosen to be 1 standard deviation below the mean and above the mean. The pattern in Figure 1 is consistent with Hypothesis 2_a.

Figure 1

Interaction Between Social Media Engagement and Advertising for Abnormal Returns

Robustness Checks

In this subsection, we conduct several additional analyses to examine whether the results are robust to different econometric models, alternative measures of key constructs, and a different estimation process to account for potential endogeneity (see Supplement Table 2, available online).

Random-effect model. To check the robustness of our results, we first reestimate our hypotheses using the random-effect model. As expected, the results presented in column 1 of Supplement Table 2 are similar to that of the fixed-effect models. This provides evidence for the robustness of our results.

Fama–French three-factor model. Though Q. Lin (2017) finds that the five-factor model outperforms the three-factor model in the Chinese market, some researchers argue that the five-factor model might not better describe equity returns in this region (e.g., Foye, 2018). Thus, we reestimate our hypotheses using the Fama–French three-factor model. As expected, the results presented in column 2 of Supplement Table 2 are similar to those of the Fama–French five-factor model. This provides evidence for the robustness of our results.

Firm-quarter observations for calculating the abnormal returns. Observations in the main analysis are based on a firm-day level. To check whether the results are robust to different levels of observations, we use firm-quarter observations to test the hypotheses. We measure the company’s quarterly social media engagement as the sum of the number of likes, comments, and forwards of all posts of a firm in a given quarter (i.e., the sum of daily social engagement data in the quarter). To account for periodic variation, we adopt an X-12-ARIMA seasonal-adjustment method to eliminate the impact of seasonal fluctuations on the engagement data (Findley et al., 1998; Shinji, 2003). The results in column 3 of Supplement Table 2 remained unchanged.

Advertising investment measurement. Advertising investments in the main analysis are measured in monetary terms. To check whether the results are robust to different measurements of advertising investments, we use the ratio of firms’ advertising expenses to sales revenues as another measurement of advertising investments to test our hypotheses. The results in column 4 of Supplement Table 2 remained unchanged.

Addressing endogeneity. Prior research suggests that firms react to past stock returns through adjusting their resource allocations to different activities (Frennea et al., 2019). This might raise a potential endogeneity concern for our estimation. Therefore, we need to examine whether social media engagement and advertising investments are endogenous in abnormal returns. Following Tavassoli et al. (2014), we use lags (i.e., Social_t_-1 and Ad_t_-1) as instruments for the two investments. The reason is that lags of social media engagement, and advertising investments would be correlated with current investments due to the persistence of marketing investments, whereas they are unlikely to be correlated with the error term (Hirschey & Weygandt, 1985; Winer & Neslin, 2014). Thus, the lags of social media engagement and advertising investments should be appropriate instruments. The Durbin–Wu–Hausman test indicates that social media engagement and advertising investments are not endogenous in abnormal returns (i.e., Equation 3; p > .1).

Discussion and Conclusions

Discussion

Social media has changed the way individuals interact with each other and is redefining the way firms connect with their customers in the hospitality and tourism industry. Companies are increasingly investing in the creation of social media platforms and strategies to augment customer–firm interactions. However, from the perspective of a firm that is contemplating social media investments, it is imperative to know whether such investments help increase their firm’s value.

By collecting data of firms in the tourism and hospitality industry that issued domestic A-shares in China, this research is the first to empirically examine the effect of social media engagement on the firm value of tourism and hospitality companies. The results show that social media engagement increases tourism and hospitality firms’ abnormal returns. This finding agrees with that in the marketing literature. For example, Nguyen et al. (2020) find that emotional word of mouth on social media affects firm value through the mediating effect of institutional investors’ stock holdings. Colicev et al. (2018) show that both owned and earned social media engagement influences firm value. Consistent with these studies in marketing, this current research verifies the relationship between social media engagement and firm value in the industry of tourism and hospitality. The results suggest that interactive and passionate social media engagement would influence investors’ expectations on tourism and hospitality firms’ future cash flows who are looking for information about the firms continuously.

Besides, this research finds that firms’ advertising expenditures decrease the positive effect of social media engagement on firm value. Social media and traditional advertising are two kinds of value-appropriation strategies, both of which require substantial resources. Our findings suggest that increasing investments in both activities would cause resource misallocation or overlap, leading to lower firm value. Hence, when investing in the two activities, firms need to consider how to use their existing resources effectively.

Moreover, previous literature indicates that there are two types of social media activities on brands’ OSM—consumer actions and brand actions (Park et al., 2016). While brand actions social media engagement refers to the content created by the firm on its social media pages, consumer actions social media engagement represents the content generated by consumers on the company’s social media pages. Social media engagement in this research is measured by the daily total number of consumers’ likes, comments, and forwards of all posts on the firm’s official Sina Weibo brand page on each day (Ge & Gretzel, 2018; Jung et al., 2019). All likes, comments, and forwards are consumer actions toward the posts that are posted on the firm’s Sina Weibo account. This raises one question: How does brand actions social media engagement affect firm value? To answer this question, we specify the model as follows.

\begin{matrix} A R_{i t} = β_{0} + β_{1} S o c i a l_{i t} + β_{2} B r a n d_{i t} \\ + β_{3} A d_{i t} + β_{4} S o c i a l_{i t} * A d_{i t} + β_{5} B r a n d_{i t} * A d_{i t} \\ + β_{6} T {obinQ}_{i t} + β_{7} A s s e t s_{i t} + β_{8} R O A_{i t} \\ + β_{9} S e l l i n g_{i t} + β_{10} M a n a g e m e n t_{i t} + β_{11} F i n a n c i a l_{i t} \\ + β_{12} L e v e r a g e_{i t} + β_{13} L i q u i d i t y_{i t} + β_{14} C o n c e n t r a t i o n_{i t} \\ + \sum^{} a_{t} W e e k d a y_{t} + \sum^{} α_{k} F i r m_{k} + e_{i t} \end{matrix}

(4)

where Brand_it is the brand actions for firm i on day t.

Table 4 shows the results for the effects of consumer actions and brand actions social media engagement on firm value. These findings show that the effect of brand actions engagement on a firm’s value is similar to that of consumer actions engagement on firm value. Specifically, both types of social media activities have a significant positive impact on firm value, while firms’ advertising investments attenuate both the positive effects of consumer actions and brand actions engagement on firm value. Overall, our results indicate that it is necessary for tourism and hospitality firms to recognize that the importance of social media engagements are influential in improving firm value, and companies should effectively manage their existing resources between social media and traditional advertising.

Table 4

Results for the Effects of Consumer Actions and Brand Actions Engagement on Firm Value

Variable	Firm Value
Social	0.129** (0.05)
Brand	0.067* (0.03)
Ad^a	1.22*** (0.21)
Social ×Ad^a	−0.274* (0.13)
Brand ×Ad^a	−0.509* (0.20)
TobinQ	1.818*** (0.06)
Assets^a	−1.31*** (0.33)
ROA	−7.628*** (1.25)
Selling	−13.332*** (1.28)
Management	5.511*** (0.71)
Financial	−2.232** (0.68)
Leverage	−0.008** (0.002)
Liquidity	−4.003*** (0.47)
Concentration	1.381 (0.72)
Fixed effects of firms	Yes
Fixed effects of day of week	Yes
Intercept	−1.678*** (0.34)

Note: Ad = advertising investments; TobinQ = Tobin’s Q; Assets = total assets; ROA = return of assets; Social = consumer-actions engagement; Brand = brand-actions engagement. Dependent variable is abnormal return; Robust standard errors. Standard errors are in parentheses.

For readability, coefficients for Assets are multiplied by 10¹⁰, coefficients for Ad, Social × Ad and Post × Ad are multiplied by 10⁶.

p < .05. ^**p < .01. ^***p < .001.

Theoretical Implications

Our study makes several significant contributions to the literature. First, our research contributes to the growing literature on social media in the hospitality and tourism industry. Research on social media in the field of hospitality and tourism has focused on the effects of social media on consumers’ perceptions, attitudes, and behaviors (e.g., Dijkmans et al., 2015; Hudson et al., 2015; Leung et al., 2013; Narangajavana, Callarisa, et al., 2017), on firm performance (e.g., Garrido-Moreno et al., 2018; B. Kim et al., 2016; S. Lin et al., 2018) and their employees (e.g., Sigala & Chalkiti, 2015; F. Yang, 2020). Still, an important question that needs to be addressed is whether social media increases/decreases intangible firm value. To our knowledge, our research is the first to examine the effects of social media on hospitality and tourism firm’s value.

Second, our research further explores the relationship between social media engagement and advertising. By investigating the two activities together, this research provides a framework to help better understand whether social media and advertising act as complements or substitutes. Our results find that firms’ advertising expenditures attenuate the positive effect of social media engagement on a firm’s value. Thus, social media engagement and advertising act as substitutes. While researchers in hospitality and tourism have noted the positive relationship between advertising expenditures and firm value (Assaf et al., 2015; Hsu & Jang, 2008; J. Kim et al., 2019), they have not taken into account the interaction between advertising and social media activities. Therefore, this research calls attention to the judicious allocation of resources to a variety of marketing activities.

Last, we contribute to research on the marketing–finance interface. A growing body of studies (Luo, 2008; Morgan & Rego, 2009; Srivastava et al., 1998) has examined the impacts of marketing-based assets on financial performance, which enlarges the scope of both marketing and finance research. This article also brings together the two streams of studies by investigating how hospitality and tourism firms’ social media and advertising investments in the domain of marketing can affect firm value in the domain of finance.

Practical Implications

The findings of this study provide several managerial implications for tourism and hospitality companies. First, this study helps tourism and hospitality managers create proxy measures of social media engagement activities from the perspective of firm value. Although tourism and hospitality firms are often highly recommended to engage with customers through online cocreation activities, managers often find it difficult to measure such activities and feel uncertain about the effectiveness of social media (Phelan et al., 2013). Therefore, tourism and hospitality firms hesitate to embrace social media and struggle with successful social media strategies (Aluri et al., 2015). The significant effects of social media engagement on firm value provide implications that can serve as a basis to measure firm value.

Second, our findings demonstrate the importance of coordination between different marketing activities. Prior research (e.g., S. Yang et al., 2016) has indicated that social media is part of marketing communications that need to coordinate with other forms of marketing communications. The finding of the substitutive effects of social media and advertising in this study can be ameliorated with better coordination among different marketing communication programs. In this regard, this study provides evidence that tourism and hospitality managers should reasonably allocate resources for social media and advertising, and adjust integrated marketing communications strategies in a timely and consistent manner.

Limitations and Future Research

The limitations of this study provide future research opportunities. First, this study did not consider the sentiment (e.g., positive, negative, or neutral sentiment) of social media engagement, which could have a significant effect on firm value. Future research might focus on the effects of the sentiment of social media engagement on firm value. Second, future research could examine whether other types of value-appropriation activities, such as sales promotions, act as substitutes for social media engagement. Third, we rely on the data of hospitality and tourism firms in China to test our hypotheses, which limits our ability to apply these results to other cultures and countries. Future research could check the generalization of our results by utilizing data from other cultures and countries.

Summary

In summary, using a daily longitudinal data set from tourism and hospitality firms that have issued domestic A-shares in China, this study investigates the effect of social media engagement on tourism and hospitality firms’ value, as well as the joint effect of social media engagement and advertising investments on firm value. Our findings suggest that social media engagement significantly increases the firm value of tourism and hospitality companies. However, advertising investments attenuate the beneficial effect of social media engagement on firm value. This study contributes to the literature on tourism and hospitality as it is the first to empirically examine the effects of social media on hospitality and tourism firms’ value. Moreover, this study provides managerial implications for hospitality and tourism firms in managing their social media and advertising investments strategically.

Supplemental Material

sj-pdf-1-jht-10.1177_10963480211015361 – Supplemental material for 1 + 1 < 2! Effects of Social Media Engagement and Advertising on Firm Value of Tourism and Hospitality Companies

Supplemental material, sj-pdf-1-jht-10.1177_10963480211015361 for 1 + 1 < 2! Effects of Social Media Engagement and Advertising on Firm Value of Tourism and Hospitality Companies by Shuai Yang, Yahui Liu and Xiaojun Wu in Journal of Hospitality & Tourism Research

Footnotes

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: We acknowledge the financial supports from the National Natural Science Foundation of China (No. 71972035, 71774029, 71602026), the Fundamental Research Funds for the Central Universities, and DHU Distinguished Young Professor Program.

ORCID iD

Xiaojun Wu

Supplemental Material

Supplemental material for this article is available online.

Notes

Shuai Yang, PhD (e-mail: shuai.yang@dhu.edu.cn), is an associate professor at the Glorious Sun School of Business and Management, Donghua University, China. Yahui Liu (e-mail: yahui56@163.com) is a graduate student at the Glorious Sun School of Business and Management, Donghua University, China. Xiaojun Wu, PhD (corresponding author; e-mail: xjunwu@dhu.edu.cn), is an associate professor at the Glorious Sun School of Business and Management, Donghua University, China.

References

Agnihotri

Dingus

M. Y.

Krush

M. T.

(2016). Social media: Influencing customer satisfaction in B2B sales. Industrial Marketing Management, 53(February), 172-180. https://doi.org/10.1016/j.indmarman.2015.09.003

Aiken

L. S.

West

S. G.

(1991). Multiple regression: Testing and interpreting interactions. Sage.

Aluri

Slevitch

Larzelere

(2015). The effectiveness of embedded social media on hotel websites and the importance of social interactions and return on engagement. International Journal of Contemporary Hospitality Management, 27(4), 670-689. https://doi.org/10.1108/IJCHM-09-2013-0415

Assaf

A. G.

Josiassen

Mattila

A. S.

Cvelbar

L. K.

(2015). Does advertising spending improve sales performance? International Journal of Hospitality Management, 48(July), 161-166. https://doi.org/10.1016/j.ijhm.2015.04.014

Barth

M. E.

Clement

M. B.

Foster

Kasznik

(1998). Brand values and capital market valuation. Review of Accounting Studies, 3(1-2), 41-68. https://doi.org/10.1023/a:1009620132177

Book

L. A.

Tanford

Montgomery

Love

(2015). Online traveler reviews as social influence: price is no longer king. Journal of Hospitality & Tourism Research, 42(3), 445-475. doi:10.1177/1096348015597029

Chen

Liu

Zhang

(2012). When do third-party product reviews affect firm value and what can firms do? The case of media critics and professional movie reviews. Journal of Marketing, 76(2), 116-134. https://doi.org/10.2307/41406852

Chuang

(2020). Co-creating social media agility to build strong customer-firm relationships. Industrial Marketing Management, 84(January), 202-211. https://doi.org/10.1016/j.indmarman.2019.06.012

Colicev

Kumar

O’Connor

(2018). Modeling the relationship between firm and user generated content and the stages of the marketing funnel. International Journal of Research in Marketing, 36(1), 100-116. https://doi.org/10.1016/j.ijresmar.2018.09.005

10.

Day

G. S.

Fahey

(1988). Valuing market strategies. Journal of Marketing, 52(3), 45-57. https://doi.org/10.1177/002224298805200305

11.

Dijkmans

Kerkhof

Beukeboom

C. J.

(2015). A stage to engage: Social media use and corporate reputation. Tourism Management, 47(April), 58-67. https://doi.org/10.1016/j.tourman.2014.09.005

12.

Dost

Phieler

Haenlein

Libai

(2019). Seeding as part of the marketing mix: Word-of-mouth program interactions for fast-moving consumer goods. Journal of Marketing, 83(2), 62-81. https://doi.org/10.1177/0022242918817000

13.

Dost

Sievert

Kassim

(2016). Revisiting firm-created word of mouth: High-value versus low-value seed selection. International Journal of Research in Marketing, 33(1), 236-239. https://doi.org/10.1016/j.ijresmar.2016.01.002

14.

Fama

E. F.

(1970). Efficient capital markets: A review of theory and empirical work. Journal of Finance, 25(2), 383-417. https://doi.org/10.2307/2325486

15.

Fama

E. F.

French

K. R.

(2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22. https://doi.org/10.1016/j.jfineco.2014.10.010

16.

Findley

D. F.

Monsell

B. C.

Bell

W. R.

Otto

M. C.

Chen

(1998). New capabilities and methods of the X-12-ARIMA seasonal-adjustment program. Journal of Business & Economic Statistics, 16(2), 127-152. https://doi.org/10.1080/07350015.1998.10524743

17.

Foye

(2018). A comprehensive test of the Fama-French five-factor model in emerging markets. Emerging Markets Review, 37(December), 199-222. https://doi.org/10.1016/j.ememar.2018.09.002

18.

Frennea

Han

Mittal

(2019). Value appropriation and firm shareholder value: Role of advertising and receivables management. Journal of Marketing Research, 56(2), 291-309. https://doi.org/10.1177/0022243718822506

19.

Frieder

Subrahmanyam

(2005). Brand perceptions and the market for common stock. Journal of Financial and Quantitative Analysis, 40(1), 57-85. https://doi.org/10.2139/ssrn.299522

20.

Garrido-Moreno

García-Morales

V. J.

Lockett

King

(2018). The missing link: Creating value with social media use in hotels. International Journal of Hospitality Management, 75(September), 94-104. https://doi.org/10.1016/j.ijhm.2018.03.008

21.

Gretzel

(2018). A taxonomy of value co-creation on Weibo: A communication perspective. International Journal of Contemporary Hospitality Management, 30(4), 2075-2092. https://doi.org/10.1108/IJCHM-09-2016-0557

22.

Hajli

M. N.

(2014). A study of the impact of social media on consumers. International Journal of Market Research, 56(3), 387-404. https://doi.org/10.2501/IJMR-2014-025

23.

Hirschey

Weygandt

J. J.

(1985). Amortization policy for advertising and research and development expenditures. Journal of Accounting Research, 23(1), 326-335. https://doi.org/10.2307/2490921

24.

Hsu

L. T.

Jang

S. C.

(2008). Advertising expenditure, intangible value and risk: A study of restaurant companies. International Journal of Hospitality Management, 27(2), 259-267. https://doi.org/10.1016/j.ijhm.2007.07.012

25.

Huang

Song

F. M.

(2006). The determinants of capital structure: Evidence from China. China Economic Review, 17(1), 14-36. https://doi.org/10.1016/j.chieco.2005.02.007

26.

Hudson

Roth

M. S.

Madden

T. J.

Hudson

(2015). The effects of social media on emotions, brand relationship quality, and word of mouth: An empirical study of music festival attendees. Tourism Management, 47(April), 68-76. https://doi.org/10.1016/j.tourman.2014.09.001

27.

Jung

W. J.

Yang

Kim

(2019). Design of sweepstakes-based social media marketing for online customer engagement. Electronic Commerce Research, 20(1), 119-146. https://doi.org/10.1007/s10660-018-09329-0

28.

Kaplan

A. M.

Haenlein

(2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59-68. https://doi.org/10.1016/j.bushor.2009.09.003

29.

Keller

K. L.

(2013). Strategic brand management: Building, measuring, and managing brand equity. Pearson Education.

30.

Kim

(2019). The mechanism by which social media influencers persuade consumers: The role of consumers’ desire to mimic. Psychology & Marketing, 36(10), 905-922. https://doi.org/10.1002/mar.21244

31.

Kim

A. J.

(2010). Impacts of luxury fashion brand’s social media marketing on customer relationship and purchase intention. Journal of Global Fashion Marketing, 1(3), 164-171. https://doi.org/10.1080/20932685.2010.10593068

32.

Kim

Heo

C. Y.

(2016). Analysis of satisfiers and dissatisfiers in online hotel reviews on social media. International Journal of Contemporary Hospitality Management, 28(9), 1915-1936. https://doi.org/10.1108/IJCHM-04-2015-0177

33.

Kim

Jun

Tang

(2019). How well does advertising work on restaurant performance? A dynamic and quadratic approach. International Journal of Hospitality Management, 81(August), 11-20. https://doi.org/10.1016/j.ijhm.2019.02.010

34.

Kim

K. H.

Park

S. Y.

Lee

Knight

D. K.

Jeon

B. J.

Moon

H. I.

(2010). Examining the relationships among attitude toward luxury brands, customer equity, and customer lifetime value in a Korean context. Journal of Global Academy of Marketing Science, 20(1), 27-34. https://doi.org/10.1080/12297119.2010.9707341

35.

Kim

(2019). How do brands’ Facebook posts induce consumers e-word-of-mouth behavior? Informational versus emotional message strategy: A computational analysis. Journal of Advertising Research, 59(4), 402-413. https://doi.org/10.2501/JAR-2019-027

36.

Kim

W. G.

Lim

Brymer

R. A.

(2015). The effectiveness of managing social media on hotel performance. International Journal of Hospitality Management, 44(January), 165-171. https://doi.org/10.1016/j.ijhm.2014.10.014

37.

Kim

W. G.

Park

S. A.

(2017). Social media review rating versus traditional customer satisfaction. International Journal of Contemporary Hospitality Management, 29(2), 784-802. https://doi.org/10.1108/IJCHM-11-2015-0627

38.

Kumar

Bezawada

Rishika

Janakiraman

Kannan

P. K.

(2016). From social to sale: The effects of firm-generated content in social media on customer behavior. Journal of Marketing, 80(1), 7-25. https://doi.org/10.1509/jm.14.0249

39.

Laroche

Habibi

M. R.

Richard

M. O.

Sankaranarayanan

(2012). The effects of social media based brand communities on brand community markers, value creation practices, brand trust and brand loyalty. Computers in Human Behavior, 28(5), 1755-1767. https://doi.org/10.1016/j.chb.2012.04.016

40.

Leung

X. Y.

Bai

Stahura

K. A.

(2013). The marketing effectiveness of social media in the hotel industry: A comparison of Facebook and Twitter. Journal of Hospitality & Tourism Research, 39(2), 147-169. https://doi.org/10.1177/1096348012471381

41.

Lin

(2017). Noisy prices and the Fama–French five-factor asset pricing model in China. Emerging Markets Review, 31(June), 141-163. https://doi.org/10.1016/j.ememar.2017.04.002

42.

Lin

Yang

Huang

(2018). Value co-creation on social media: Examining the relationship between brand engagement and display advertising effectiveness for Chinese hotels. International Journal of Contemporary Hospitality Management, 30(4), 2153-2174. https://doi.org/10.1108/IJCHM-08-2016-0484

43.

Luo

(2008). When marketing strategy first meets wall street: Marketing spendings and firms’ initial public offerings. Journal of Marketing, 72(5), 98-109. https://doi.org/10.1509/jmkg.72.5.98

44.

Luo

Zhang

Duan

(2013). Social media and firm equity value. Information Systems Research, 24(1), 146-163. https://doi.org/10.1287/isre.1120.0462

45.

Madden

T. J.

Fehle

Fournier

(2006). Brands matter: An empirical demonstration of the creation of shareholder value through branding. Journal of the Academy of Marketing Science, 34(2), 224-235. https://doi.org/10.1177/0092070305283356

46.

Mariani

Styven

M. E.

Ayeh

J. K.

(2018). Using Facebook for travel decision-making: An international study of antecedents. International Journal of Contemporary Hospitality Management, 31(2), 1021-1044. https://doi.org/10.1108/IJCHM-02-2018-0158

47.

Mayrhofer

Matthes

Einwiller

Naderer

(2020). User generated content presenting brands on social media increases young adults’ purchase intention. International Journal of Advertising, 39(1), 166-186. https://doi.org/10.1080/02650487.2019.1596447

48.

Morgan

N. A.

Rego

L. L.

(2009). Brand portfolio strategy and firm performance. Journal of Marketing, 73(1), 59-74. https://doi.org/10.1509/jmkg.73.1.059

49.

Nam

Kannan

P. K.

(2014). The informational value of social tagging networks. Journal of Marketing, 78(4), 21-40. https://doi.org/10.1509/jm.12.0151

50.

Narangajavana

Callarisa

Luis

Moliner

Miguel

Rodríguez

Rosa

Sánchez

G. J.

(2017). The influence of social media in creating expectations: An empirical study for a tourist destination. Annals of Tourism Research, 65(July), 60-70. https://doi.org/10.1016/j.annals.2017.05.002

51.

Narangajavana

Luis

Miguel

Rosa

Sánchez

G. J.

(2017). User-generated content sources in social media: A new approach to explore tourist satisfaction. Journal of Travel Research, 58(2), 253-265. https://doi.org/10.1177%2F0047287517746014

52.

Nguyen

H. T.

Calantone

R. J.

Krishnan

(2020). Influence of social media emotional word of mouth on institutional investors’ decisions and firm value. Management Science, 66(2), 887-910. https://doi.org/10.1287/mnsc.2018.3226

53.

Noone

B. M.

McGuire

K. A.

(2013). Effects of price and user-generated content on consumers’ prepurchase evaluations of variably priced services. Journal of Hospitality & Tourism Research, 38(4), 562-581. doi:10.1177/1096348012461551

54.

Olson

E. M.

Slater

S. F.

Hult

G. T. M.

(2005). The performance implications of fit among business strategy, marketing organization structure, and strategic behaviour. Journal of Marketing, 69(3), 49-65. https://doi.org/10.1509/jmkg.69.3.49.66362

55.

Wong

I. A.

Prentice

Liu

M. T.

(2020). Customer engagement and its outcomes: The cross-level effect of service environment and brand equity. Journal of Hospitality & Tourism Research, 44(2), 377-402. https://doi.org/10.1177/1096348019897360

56.

Park

S. O.

H. J.

Kwon

(2016). Comparative effect of company-driven SNS activity vs. Consumer-driven SNS activity on firm value: Evidence from Facebook. Computers in Industry, 82(October), 186-195. https://doi.org/10.1016/j.compind.2016.07.008

57.

Pauwels

Silva-Risso

Srinivasan

Hanssens

D. M.

(2004). New products, sales promotions, and firm value: The case of the automobile industry. Journal of Marketing, 68(4), 142-156. doi:10.1509/jmkg.68.4.142.42724

58.

Phelan

K. V.

Chen

H. T.

Haney

(2013). “Like” and “check-in”: How hotels utilize Facebook as an effective marketing tool. Journal of Hospitality and Tourism Technology, 4(2), 134-154. https://doi.org/10.1108/JHTT-Jul-2012-0020

59.

Rothaermel

F. T.

Hess

(2007). Building dynamic capabilities: Innovation driven by individual, firm, and network level effects. Organization Science, 18(6), 898-921. https://doi.org/10.1287/orsc.1070.0291

60.

Schmitt

(2012). The consumer psychology of brands. Journal of Consumer Psychology, 22(1), 7-17. https://doi.org/10.1016/j.jcps.2011.09.005

61.

Shin

Back

(2020). Effect of cognitive engagement on the development of brand love in a hotel context. Journal of Hospitality & Tourism Research, 44(2), 328-350. https://doi.org/10.1177/1096348019890055

62.

Shinji

(2003). The decomposition structures in two seasonal adjustment programs X-12-ARIMA and TRAMO-SEATS—with some empirical tests to compare both programs—(in Japanese). ESRI Discussion Paper, 14(8), 768-776. https://ideas.repec.org/p/esj/esridp/063.html

63.

Sigala

Chalkiti

(2015). Knowledge management, social media and employee creativity. International Journal of Hospitality Management, 45(February), 44-58. https://doi.org/10.1016/j.ijhm.2014.11.003

64.

K. K. F.

King

Sparks

(2012). Customer engagement with tourism brands: Scale development and validation. Journal of Hospitality & Tourism Research, 38(3), 304-329. https://doi.org/10.1177/1096348012451456

65.

Srivastava

R. K.

Shervani

T. A.

Fahey

(1998). Market-based assets and shareholder value: A framework for analysis. Journal of Marketing, 62(1), 2-18. https://doi.org/10.1177/002224299806200102

66.

Tavassoli

N. T.

Sorescu

Chandy

(2014). Employee-based brand equity: Why firms with strong brands pay their executives less. Journal of Marketing Research, 51(6), 676-690. https://doi.org/10.1509/jmr.13.0435

67.

Touni

Kim

W. G.

Choi

Ali

M. K.

(2020). Antecedents and an outcome of customer engagement with hotel brand community on Facebook. Journal of Hospitality & Tourism Research, 44(2), 278-299. https://doi.org/10.1177/1096348019895555

68.

Van Dieijen

Borah

Tellis

G. J.

Franses

P. H.

(2020). Big data analysis of volatility spillovers of brands across social media and stock markets. Industrial Marketing Management, 88(July), 465-484. https://doi.org/10.1016/j.indmarman.2018.12.006

69.

Wang

Kim

H. G.

(2017). Can social media marketing improve customer relationship capabilities and firm performance? Dynamic capability perspective. Journal of Interactive Marketing, 39(August), 15-26. https://doi.org/10.1016/j.intmar.2017.02.004

70.

Wei

Ouyang

Chen

H. A.

(2017). Well known or well liked? The effects of corporate reputation on firm value at the onset of a corporate crisis. Strategic Management Journal, 38(10), 2103-2120. https://doi.org/10.1002/smj.2639

71.

Winer

R. S.

Neslin

S. A.

(2014). The history of marketing science (World Scientific Books Publishers series, Vol. 3). World Scientific. https://doi.org/10.1142/9128

72.

Wright

Khanfar

N. M.

Harrington

Kizer

L. E.

(2010). The lasting effects of social media trends on advertising. Journal of Business & Economics Research, 8(11), 73-80. https://doi.org/10.19030/jber.v14i3.9747

73.

Xiang

Gretzel

(2010). Role of social media in online travel information search. Tourism Management, 31(2), 179-188. https://doi.org/10.1016/j.tourman.2009.02.016

74.

Xie

K. L.

Zhang

Singh

Lee

S. K.

(2016). Effects of managerial response on consumer e-WOM and hotel performance: Evidence from TripAdvisor. International Journal of Contemporary Hospitality Management, 28(9), 2013-2034. https://doi.org/10.1108/IJCHM-06-2015-0290

75.

F. Z.

Wang

(2020). Enhancing employee innovation through customer engagement: The role of customer interactivity, employee affect, and motivations. Journal of Hospitality & Tourism Research, 44(2), 351-376. https://doi.org/10.1177/1096348019893043

76.

Yang

F. X.

(2020). Social media friending in building co-worker guanxi: A study in the hotel industry. International Journal of Hospitality Management. 84(January), Article 102183. https://doi.org/10.1016/j.ijhm.2018.10.020

77.

Yang

Lin

Carlson

J. R.

Ross

W. T.

(2016). Brand engagement on social media: Will firms’ social media efforts influence search engine advertising effectiveness? Journal of Marketing Management, 32(5-6), 526-557. https://doi.org/10.1080/0267257X.2016.1143863

78.

Yoon

Y. G.

North

Hong

Liu

(2018). Attracting comments: Digital engagement metrics on Facebook and financial performance. Journal of Advertising, 47(1), 24-37. https://doi.org/10.1080/00913367.2017.1405753

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