Influence of social media management practices on hotel performance

Abstract

Purpose:

This paper aims to examine the influence of social media management practices on hotel performance.

Originality/value:

The hotel industry is undergoing organizational transformations due to the insertion of social media as a communication platform that engages customers. Given this, verifying whether social media can collaborate on internal resources and help the companies’ performance has been a potential source of studies.

Design/methodology/approach:

The study sample comprised 67 hotels. To this end, hotel managers conducted face-to-face interviews to collect data from their respective hotels. Data were collected using social media management practices and performance measures measured through RevPAR (a revenue division by total rooms available) and online review scores from Booking.com. Exploratory factor analysis and multiple regression analysis were applied to evaluate the study’s hypotheses from a quantitative approach.

Findings:

It was evidenced that social media management practices can be categorized into monitoring and comment responsing practices and the dimension of responsiveness and information dissemination practices. These practices positively influence hotel performance measured through online review scores and revenue measured through RevPAR. Given the results, it is expected that hotels will have competitive advantages by managing their resources with the help of social media and that studies in this sector will gain more visibility.

Keywords:
performance; management practices; social media; online assessment; hospitality industry

Resumo

Objetivo:

Este artigo tem como objetivo examinar a influência das práticas de gerenciamento de mídias sociais no desempenho dos hotéis.

Originalidade/valor:

O setor hoteleiro está passando por algumas transformações gerenciais por causa da inserção das mídias sociais como plataformas de comunicação que envolvem os clientes. Diante disso, verificar se as mídias sociais podem colaborar nos recursos internos e ajudar no desempenho das empresas tem sido uma fonte potencial de estudos.

Design/metodologia/abordagem:

A amostra do estudo apresentou 67 hotéis. Para isso, foram realizadas entrevistas presenciais com gestores hoteleiros a fim de coletar os dados de seus respectivos hotéis. Coletaram-se dados sobre a utilização de práticas de gerenciamento de mídias sociais e sobre medidas de desempenho mensuradas por meio do RevPAR (divisão das receitas pelo total de quartos disponíveis) e das notas de avaliação on-line do site Booking.com. A partir de uma abordagem quantitativa, aplicaram-se as técnicas de análise fatorial exploratória e análise de regressão múltipla para avaliar as hipóteses do estudo.

Resultados:

Evidenciaram-se que as práticas de gerenciamento de mídias sociais podem ser categorizadas na dimensão de práticas de monitoramento e de resposta aos comentários, e na dimensão de práticas de responsividade e disseminação de informações. A utilização dessas práticas influencia positivamente no desempenho hoteleiro medido por meio de notas de avaliação on-line e nas receitas medidas por meio do RevPAR. Diante dos resultados, espera-se que os hotéis tenham vantagens competitivas ao gerenciarem seus recursos com a ajuda das mídias sociais e que estudos nesse setor ganhem mais visibilidade.

Palavras-chave:
desempenho; práticas de gerenciamento; mídias sociais; avaliação on-line; setor hoteleiro

INTRODUCTION

For a long time, the nature of service-providing companies has resulted in difficulties for consumers when making their choices before consumption (Litvin et al., 2008). However, this scenario has changed through the evolution of online platforms (Liu et al., 2019). Studies show that through social media, it is possible to obtain information about services before purchasing them, which facilitates purchase decisions (Park & Nicolau, 2015; Leung et al., 2019).

Concerning this situation, the hotel industry has stood out with social media. People like to seek information about experiences already lived by guests to help them choose where to stay (Schuckert et al., 2015; Guillet et al., 2016). This information can range from complaints or compliments, and consequently, using these online platforms enables the evaluation of hotel service delivery (Litvin et al., 2008; Schuckert et al., 2015; Varkaris & Neuhofer, 2017; Liu et al., 2019).

For Kim et al. (2015), social media provide new ways to interact with and understand hotels’ old and new customers. In this context, the online information present in social media can positively or negatively impact hotels. Therefore, strategies related to managing these platforms should not be overlooked (Kim et al., 2015; Schuckert et al., 2019). According to Leung et al. (2019), this management of companies can be related to online reputation and overall performance.

When comparing research on consumer and hotel company perspectives on social media use, a higher percentage of research is conducted with consumers than with hotels (Leung et al., 2019). Limited research has highlighted how guests’ perceptions of physical aspects or hotel services could impact how hotels manage to increase their performance (Phillips et al., 2016). By analyzing different studies, Kwok et al. (2017) noticed that most address research topics related to online reviews’ quantitative and verbal characteristics. Given this, there is a gap in what managers do with online information, what strategic actions are taken (Kwok et al., 2017), and how this may influence industry performance.

It is known that implementing management practices can subject companies to variations in performance (Bloom & van Reenen, 2007; Bloom et al., 2012). Few studies have examined the influence of social media as a tool to improve organizations’ businesses (Guillet et al., 2016; Pereira & Freitas, 2018). Given the above, this study will examine the influence of social media management practices on hotel performance.

Monitor the external environment to integrate and coordinate resources, capabilities and actions are strategies that seek competitive advantages and superior performance (Rossetto et al., 2019). Thus, social media represent opportunities and challenges for organizations, as companies are still learning how to use them to enhance their performance (Araujo & Zilber, 2016; Muninger et al., 2019).

Therefore, this study brings a new approach that verifies whether there is a relationship between social media management practices and performance in the hotel industry. It intends to improve hotel management and, mainly, to make companies in general and the academic community aware of both the opportunities for studies and applications offered by social media management practices.

MANAGEMENT PRACTICES

The terms “practice” and “practices” are found in the literature but are differentiated poorly. According to Jarzabkowski et al. (2007), “practice” can be understood as an activity or process in which thought becomes an act, transforming itself into an experience. The term “practices” for the same authors refers to routines, habits, and the use of tools and technologies in organizations.

The importance of management practices has gained prominence since the studies of Bloom and van Reenen (2007). They conducted research that confirmed that management practices could influence firms’ productivity. Due to the importance of these resources for firms, research involving relationships between management practices and performance has become increasing (Davies & Kochhar, 2002; Bloom & van Reenen, 2012; Bloom et al., 2012; Bloom et al., 2013; Brito & Sauan, 2016; Bender et al., 2018; Oliveira & Honório, 2020).

Mizumoto et al. (2010) investigated the impact of the factors of human capital, social capital, and managerial practices executed by entrepreneurs at the beginning of opening their businesses. The results showed that none of the three factors could, in isolation, explain the chance of success. However, when analyzing the three factors together, the most significant explanatory power was precisely related to adopting managerial practices. Some authors explain that the synergy of management practices can bring more effects on business performance than the application of isolated techniques (Flynn & Flynn, 2005).

García et al. (2014) researched quality management practices in the hotel industry and concluded that quality planning and leadership are the practices that most influence results. Peixoto (2012) explains that the search for more efficient management practices can be seen as one of the most promising alternatives to improve the effectiveness of business processes in the hotel industry.

Bender et al. (2018) confirmed a positive relationship between management practices and firm performance by explaining that managerial procedures can result in higher productivity. In the findings, many variations among firms in productivity measures are caused by differences in management practices (Bender et al., 2018). Research shows that organizations differ in their use of management practices in reasonably simple and seemingly apparent ways and that these distinctions lead to differences in performance across firms (Bromiley & Rau, 2014). Bloom et al. (2012) explain that these performance variations reveal heterogeneous performance behavior.

SOCIAL MEDIA MANAGEMENT PRACTICES IN HOTELS

Given the growth in the use of social media, many hotels are using online information to increase visibility and build trust and credibility (Rosario et al., 2013). Schuckert et al. (2015) consider that online reviews on social media can be a strategic tool that plays a vital role in hotel management, especially in promotion, online sales, and reputation management. These reviews can be found on specialized websites for lodging facilities, such as Booking.com and Tripadvisor.

In this sense, when used as a management tool, social media enable better management of resources that can improve the positioning of hotels concerning their competitors (Anagnostopoulou et al., 2020). This management of available social media resources can be linked to the concept of management practices. For Barney (1991), the resource-based view (RBV) can be a strategic basis for achieving business advantage. Companies in the hospitality industry can use social media for value generation (Yadav et al., 2013) to improve their internal processes, increase their service quality, and achieve better competitive advantage.

By allocating resources and acting proactively, managers can surprise customers and reduce or avoid potential complaints on social media (Phillips et al., 2016). In addition, responding quickly to negative customer comments can make customers feel important to the company and increase customer satisfaction (Kim et al., 2015). Therefore, monitoring online comments and hotel ratings is essential for management activities and serve as an internal metric to improve performance (Kim et al., 2015).

Regarding the attitudes that can be taken from the information in social media, Park and Allen (2013) explain that companies can have quick attitudes to solve customer complaints and problems to manage the hotel’s good image. For Litvin et al. (2008), collecting opinions related to issues experienced by guests can be defined as a category of information management in which the goal is to solve the problems presented and improve the company’s reputation.

Thus, it is necessary to understand which attitudes and strategies are being implemented by managers on account of the use of social media (Xie et al., 2014; Kwok et al., 2017). In this sense, Table 1 presents a set of social media management practices proposed by Pereira and Freitas (2018) from a collection of approaches related to managerial procedures cited in the literature on the hospitality industry.

Table 1
Social media management practices

Practices	Authors
PG1: Monitor the company’s reputation through online reviews.	Litvin et al. (2008); O’Connor (2010); Levy et al. (2013); Xie et al. (2014); Kim et al. (2015).
PG2: Respond to online comments on social media.	Litvin et al. (2008); Levy et al. (2013); Xie et al. (2014).
PG3: Conduct training of employees to handle social media.	Chan and Guillet (2011); Guillet et al. (2016); Phillips et al. (2016).
PG4: Document response standards to be used in online reviews.	Park and Allen (2013); Kim et al. (2015); Guillet et al. (2016).
PG5: Develop standard internal procedures for handling social media information.	Litvin et al. (2008). O’Connor (2010); Guillet et al. (2016).
PG6: Communicate to internal areas the information extracted from online reviews to improve operations and services.	Litvin et al. (2008); Levy et al. (2013); Park and Allen (2013).
PG7: Develop strategies to promote the company’s services, considering the particular characteristics of each social media.	Chan and Guillet (2011); Kietzmann et al. (2011); Rosario et al. (2013); Guillet et al. (2016).

• Source:Pereira and Freitas (2018).

Leung et al. (2019) explain that social media platforms help companies in terms of reputation management, performance management, channel management, and human resource management. However, few studies address how to handle information from social media to improve their services.

Araujo and Zilber (2016) emphasize that the continuity and intensity of media use by companies are directly related to the degree of perception of the advantages and benefits of these online platforms and that they will depend on the companies’ organizational innovation capacity. In this regard, it is necessary to have the ability to recognize which is the best strategy to develop in social media, according to each industrial segment (Bruhn et al., 2012).

BUSINESS PERFORMANCE IN THE HOTEL INDUSTRY AND PROPOSITION OF THE HYPOTHESES

Performance measurement plays a crucial role in organizations, as it enables managers to monitor the company’s direction over time and thus evaluate performance to achieve organizational goals (Teeratansirikool et al., 2013).

The investigation of business performance impact from a strategic perspective is not so frequent in hotel industry studies because there is still difficulty collecting and comparing data from performance indicators in this sector (Phillips et al., 2016). Peixoto (2012) used the occupancy and average daily rates (ADR) to analyze hotel companies. Occupancy rate refers to the number of occupied rental units at a given time, compared to the total number of available rental units at that time. ADR measures the hotel’s daily revenue per occupied room. Other studies have used lodging revenue per available room, RevPAR, which involves multiplying the average daily room rate by the occupancy rate at the hotel (Kim et al., 2015). RevPAR indicates how much is earned per room in the hotel, including those occupied in a given period and those available.

In recent years, with the spread of social media, it has been shown that online reviews on virtual platforms can influence the financial performance of hotels. According to Anderson (2012), the scores present in online reviews affect hotel revenue performance, pricing power, and hotel demand. Given this, research on possible relationships between social media management practices and the financial performance of hotels should not be overlooked.

Ye et al. (2009) used hotel data collected through online reviews to analyze the impact of online reviews on hotel performance. They observed that a 10% improvement in hotel scores could increase the number of sales in hotels by 4.4%. In contrast, a 10% decrease in online review scores harms the number of sales, as it can cause sales to decrease by 2.8% (Ye et al., 2009).

Anderson (2012) pointed out that if a hotel increases its rating score by 1 point on online review sites, it can increase its price by 11.2% without affecting its occupancy rate. Furthermore, the author revealed that a 1% improvement in a hotel’s online satisfaction score raises the occupancy rate by 0.54% and RevPAR by 1.42%.

Phillips et al. (2016) observed a considerable impact on performance measured through the occupancy rate and RevPAR of hotels by checking positive user comments in online reviews compared to negative comments. Moreover, due to the dynamic environment in which hotel companies are embedded, the results showed that one should manage online reviews to bring strategic advantages and increase managers’ dynamic capabilities and competencies (Phillips et al., 2016).

Regarding these different performance metrics, Peixoto (2012) explains that the impact of management practices on companies varies according to the indicators chosen to measure performance. Consequently, depending on how performance will be measured, it can be impacted by management practices in different ways.

Given the above, hypothesis 1 is posited as follows:

• H1: The use of social media management practices influences hotel RevPAR.

Still, regarding hotel performance, it is observed that the scores of online reviews in social media can serve as performance measures (Anderson, 2012) because consumers evaluate hotels through the scores (Anagnostopoulou et al., 2020). Given this, a new way of assessing performance exclusively by people outside the companies is perceived.

Online comments generated on social media can be important for business performance in the hotel industry. As hotels provide more resources to reduce or avoid potential complaints on social media, one can improve consumers’ online review scores (Phillips et al., 2016).

In researching the importance of social media for hotels, Wang et al. (2015) demonstrated that online comments, in some instances, can influence consumers’ decision-making power more than conventional hotel choice characteristics, such as the price of the stay.

Kim et al. (2015) noted that the online score social media provides is a strong performance indicator, as the higher the hotel’s score, the better its performance. In this way, Xie et al. (2014) clarified that managers’ responses to online hotel reviews could positively or negatively impact online ratings depending on the issue being questioned. Thus, managing hotels’ online reputation effectively improves guest satisfaction, sales rates, and hotel performance (De Pelsmacker et al., 2018).

Given the above, it is evident that the management of internal resources obtained from the information on social media can result in better hotel performance (Kim et al., 2015). This management can be accomplished by using social media management practices, such as collecting information online, passing on information to the responsible areas, and monitoring the reputation of companies (Guillet et al., 2016; Park & Allen, 2013).

From the studies presented, hypothesis 2 is as follows:

• H2: Social media management practices influence online hotel review scores.

From the stated hypotheses, Figure 1 presents the design of the conceptual model to measure the effects of social media management practices on each performance indicator chosen for the research.

Figure 1
Conceptual model

METHODOLOGY

According to the proposed objective of examining the influence of social media management practices on hotel performance, this research is classified as exploratory because the research corpus will serve as the basis for further research (Vergara, 2016). In addition, the study has a quantitative nature, according to Malhotra (2006), due to the quantification of the data.

Next, the methodological procedures for the construction of the research instrument, the data collection procedure, the characteristics of the sample collected, and the data analysis procedures used will be explained.

Research instrument

A data collection script was used as a research instrument and divided into four parts. The first part was composed of the scale of social media management practices. The second part included the items that involved the performance indicators. The third part was reserved for filling in the companies’ characteristics. Finally, the last part was related to the respondents’ sociodemographic questions.

The social media management practices used the scale proposed by Pereira and Freitas (2018) composed of seven indicators as presented in this literature review. The scale for measuring the degree of use of the practices is categorical of the numeric scalar type, which ranges from 1 to 5 points, divided into “Does not use (1 point)”, “Uses rarely (2 points)”, “Uses eventually (3 points)”, “Frequently uses (4 points)”, and “Always uses (5 points)”.

As for performance measurement, the following indicators were used: RevPAR and online review scores from the Booking.com website. The RevPAR indicator, already used in other studies (Anderson, 2012; Peixoto, 2012; Phillips et al., 2016), is a financial variable, and its value was annual, of the numeric-proportional type.

As for the second indicator, the Booking.com website was selected since all the hotels in the sample are registered there. The online evaluation scores for Booking.com range from 0 to 10 and can only be evaluated by people who have made reservations through the website and who stayed there. It should be noted that this indicator is of the non-numeric ordinal type.

Data collection procedure and sample characteristics

Data collection was conducted from January to March 2018. Personal and face-to-face interviews were conducted with the hotel managers to help verify the appropriateness of the interviewees’ answers during the questionnaire. All interviews were conducted face-to-face and with the same interviewer to ensure standardization in data collection. The sample selection followed the non-probabilistic criterion by accessibility because the population elements to compose the sample were selected according to ease of access.

A total of 67 managers were interviewed, each linked to a hotel. The sample was 55.22% micro and small hotels and 44.78% medium and large hotels. All companies are located in Ceará, Brazil, and are associated with the Ministry of Tourism.

Regarding the respondents’ sociodemographic details, the sample showed a higher representation of female respondents, with 56.9%, compared to 43.1% for males. The majority were between 21 and 30 years old and between 41 and 50 years old, respectively, 53.7% and 22.4% of the sample. The roles of the interviewees in the companies were as follows: director (6%), manager (33%), reservations coordinator/supervisor (28%), reception supervisor (28%), and commercial assistant (4%). It is essential to clarify that all respondents agreed with the statement they were competent to answer the questionnaire about social media practices in the companies.

Data analysis procedure

Initially, exploratory factor analysis was chosen for the data analysis because, according to Corrar et al. (2014), this modality is used when there is no prior knowledge of the dependency relationship between the variables. The factor analysis technique summarizes the information contained in a group of different variables in a smaller set of factors without significant data loss (Hair Jr. et al., 2009).

Then, multiple regression analyses were conducted to examine the influence of social media management practices on hotel performance.

Endogeneity is still a murky issue for empirical marketing strategy research, and there is potentially no perfect solution to endogeneity when working with non-experimental data (Rutz & Watson, 2019). Thus, this study determined that the utilization of social media management practices is the cause, and performance is the effect.

Before starting the application, the assumptions for the data analysis were performed and validated. In order to assist in the data analysis, SPSS software was used.

The sample did not present missing values, and it was decided not to remove the atypical observations found. The variables under study did not present multicollinearity since the variance inflation factor (VIF) value was less than 10. A Kolmogorov-Smirnov normality test was performed, in which, to be validated, the significance value must be greater than 0.05. Thus, it was verified that the distribution was normal. A Durbin-Watson test demonstrated no evidence of serial autocorrelation in the residuals. The graphs of the residuals were analyzed to identify a homogeneous variance, and a Levine test was performed. The test showed that the sign was more significant than 0.05, thus confirming the existence of homoscedasticity among the variables. Finally, the linearity diagnosis was examined by observing scatter plots, concluding that this assumption was not violated.

RESULTS AND DISCUSSIONS

The analyses of the results comprised two parts. First, the exploratory factor analysis (EFA) was addressed. Then, the multiple regression techniques were addressed to analyze the relationships between social media management practices and performance. The discussion presents the verification of the hypotheses formulated in this study.

Exploratory factor analysis application

In applying EFA, we sought to identify common structural characteristics among the variables and to obtain fewer factors representing the original set of variables. Before starting the EFA, all the necessary assumptions were verified as presented in the study’s methodology.

For the first test of the application, all seven variables represented via the following managerial practices were used in the analysis technique: monitor the company’s reputation through online reviews (PG1); respond to online comments on social media (PG2); conduct employee training to manipulate social media (PG3); document response patterns to be used in online reviews (PG4); develop standard internal procedures for manipulating social media information (PG5); communicate to internal areas the information extracted from online reviews to improve operations and services (PG6); and develop strategies for promoting the company’s services, considering the particular characteristics of each social media (PG7).

When starting, the Kaiser-Meyer-Olkin – KMO value was adequate (0.722 > 0.05), as was the significance (less than 0.05) and the anti-image matrix. However, the results related to commonalities were not satisfactory due to some values being lower than 0.4. Because of this, a second factorial analysis was run but with one less indicator. Hair Jr. et al. (2009) advise removing one variable at a time. Thus, variable PG3, referring to “train employees to handle social media,” was extracted because it indicated the lowest communality value in the model.

The new model with six indicators presented entirely satisfactory results. The KMO value was 0.667 (greater than 0.05), and its significance was also satisfactory. When comparing the models with seven and six indicators, it was observed that there was a change from 52.85% of explanatory variance to 57.05%. Therefore, this positive increase showed that removing the variable from the model was an appropriate measure, as Corrar et al. (2014) proposed. Thus, it is believed to have reached a degree of relationship and explanation of the variables.

The scree plot presented the eigenvalues of each factor and allowed visualization that the model generated two factors with eigenvalues above 1. According to Hair Jr. et al. (2009), the scree test analysis indicates the number of factors that should be maintained in the model. Costa (2011) explains that factor loadings above 0.4 are considered significant. A varimax rotation matrix was applied, shown in Table 2, in which all the values of the scores of the loadings were above 0.62. When identifying the composition of the factors, variables PG1, PG2, and PG7 were classified in the first factor, and variables PG4, PG5, and PG6 fitted the second.

Table 2
Factorial loading values after varimax rotation

Indicators	Factor 1	Factor 2
PG1	0.754	-
PG2	0.720	-
PG4	-	0.652
PG5	-	0.655
PG6	-	0.845
PG7	0.620	-

• Source: Elaborated by the authors.

The first factor accounted for 30.01% of the explained variance. The practices involved were PG1 – monitoring the company’s reputation through online reviews, PG2 – responding to online comments on social media, and PG7 – developing strategies to promote the company’s services, considering the particular characteristics of each type of social media. These practices were named monitoring and responding to comments.

The second factor was responsible for 27.04% of the explained variance. It has in its composition the practices PG4 – document response standards to be used in online reviews, PG5 – develop standard internal procedures for handling information on social media, and PG6 – communicate to internal areas the information extracted from online reviews to improve operations and services. Thus, these practices were called responsiveness and information dissemination.

After the exploratory factor analysis, reliability analysis was performed to observe whether the items fit the expectations defined for the measurement. Internal consistency analysis was performed by calculating Cronbach’s alpha coefficient, and a value of 0.88 was observed. According to Costa (2011), this value suggests that the set of items presents an excellent internal consistency.

Multiple regression application and analysis

In order to perform the multiple regressions, the necessary assumptions established in the literature (Hair Jr. et al., 2009) were checked, as presented in the methodology of this study.

The factors found in the factor analysis created two independent variables from the average practices in each factor. Studies have shown that this procedure is appropriate for treating management practices with an independent variable (Bloom & van Reenen, 2007; Brito & Sauan, 2016). The simple average of the indicators, rather than the weighted average, is justified by the lack of absolute ex ante support for assuming which practices are more important than others for performance (Fleury et al., 2018).

Two regression models were run for each performance variable. In addition, the following control variables were added to the models: hotel size, respondent’s gender, respondent’s age group, and the hierarchy of the position held in the company.

The first analysis used the performance indicator RevPAR as the dependent variable and social media management practices as the independent variables. It was found that the correlation coefficient (R) between the variables indicated a positive degree of association with R = 0.334. Next, the coefficient of determination (R²) was used to determine how much of the dependent variable was explained by the independent variable (Hair Jr. et al., 2009). R² indicated that variations in management practices could explain 11.2% of RevPAR variations.

When analyzing the linear regression of the dependent variable measured through Booking.com’s review scores, a degree of association was found between the dependent and independent variables with R = 0.302. In sequence, the R² showed that 9.1% of the variation in the dependent variable could be explained by the variations occurring in the independent variable average scores of managerial practices.

When analyzing the results of the F-ANOVA test, we observed a significant level of 0.022 and 0.046 for the RevPAR and Booking.com models, respectively. Therefore, as the sign was less than 0.05, the hypothesis that R² is equal to zero was rejected. Therefore, it is possible to state that social media management practices influence RevPAR and Booking.com’s online review scores. Therefore, the models are significant.

By inserting the control variables in the model with RevPAR, the R² increased from 11.2% to 34.4% and proved significant. The results of the second model with Booking.com scores, despite the increase of the R² from 9.1% to 12%, showed that the insertion of the control variables did not bring about significant relationships; thus, they were removed from the model.

The low R2 values are justified because social media management practices represent only one of the several areas that make up the organizations and that impact performance. All the results presented can be seen in Table 3, in which model 1 shows only the dependent and independent variables, and model 2 includes the control variables.

Table 3
Linear regression results

Model 1
RevPAR		Non-standardized coefficients	t
		B
Management practices	(Constant)	72.139	5.14
	Factor 1	13.953	1.905
	Factor 2	-2.802	-0.421
	R2 (%)	11.2%
	Sig	0.022
Booking.com
Management practices	(Constant)	7.282	38.64
	Factor 1	-0.27	-0.271
	Factor 2	0.145	1.624
	R2 (%)	9.1%
	Sig	0.046

Model 2
RevPAR		Non-standardized coefficients	t
		B
Management practices	(Constant)	140.637	5.079
	Factor 1	7.702	1.087
	Factor 2	-2.795	-0.462
	R2 (%)	34.4%
	Sig	0.000
Booking.com
Management practices	(Constant)	7.168	16.835
	Factor 1	-0.043	-0.395
	Factor 2	0.155	1.668
	R2 (%)	12%
	Sig	0.243

• Source: Elaborated by the authors.

DISCUSSION OF THE RESULTS

Observing the results made it possible to confirm the hypotheses proposed in the research. Table 4 presents a summary of the multiple regressions.

Table 4
Results of the relationships between the independent and dependent variables

Dependent variable	Independent variable	Sig	Result
RevPAR	Management practices	0.000	Significant
Online Booking.com review rating	Management practices	0.046	Significant

• Source: Elaborated by the authors.

Hypothesis H1 was proposed to verify whether social media management practices influence the RevPAR of hotels. The tests presented significant results and showed that managerial practices positively influence the financial performance of hotels. It can thus be stated that the hypothesis was accepted.

The result of H1 showed similar results to those of studies conducted in other industries, which also resulted in positive relationships between management practices and performance (Davies & Kochhar, 2002; Bloom & van Reenen, 2007; Brito & Sauan, 2016; Bender et al., 2018; Fleury et al., 2018).

In addition, the result was in line with the findings of Phillips et al. (2016), who state that managing online information significantly impacts hotel demand and revenue. Furthermore, it can be noted that social media management practices can affect hotels’ average daily rate and occupancy rates, as the RevPAR calculation involves these two rates.

Hypothesis H2 was posited to verify whether social media management practices influence hotels’ online reviews on the Booking.com website. The results were significant and showed the positive influence of using social media management practices on the company’s performance, measured through online reviews. Given this, H2 was confirmed.

Studies by Xie et al. (2014) concluded that online consumer reviews and management responses impact hotel performance. Furthermore, the authors found that the overall rating score of the hotel is significantly associated with its performance. In the research of Kim et al. (2015), it was observed that social media management could affect the online rating score of hotels because managing resources from the information collected on social media can improve consumer reviews.

The confirmation of H1 and H2 is in line with the literature. It demonstrates that the results found to advance the results of previous studies, which have analyzed social media management practices in isolation concerning influencing performance (Kim et al., 2015; Wang et al., 2015; Phillips et al., 2016; De Pelsmacker et al., 2018). Using a set of management practices for analytics with performance is appropriate and has already been implemented in other areas (Bloom & van Reenen, 2007; Brito & Sauan, 2016). Therefore, the importance of this study was the evidence and use of two factors consisting of a set of management practices specific to the field of social media.

Combining practices helps in new implementations for superior performance because their union tends to reinforce and promote more synergy (Flynn & Flynn, 2005; Fleury et al., 2018). As Barney (1991) emphasizes, specific resources, or even competencies, are valuable because they are difficult to imitate and consequently can generate competitive advantages. Therefore, these combinations of practices can generate unique competencies for organizations.

Finally, regarding the control variables that did not bring significant results for online evaluation scores, Araujo and Zilber (2016) explain that the organization’s size may even influence the adoption of social media. Still, the organizational innovation capacity will influence the continuity and intensity of use, that is, the ability to realize the advantages and benefits of online platforms.

CONCLUSIONS

This study makes significant contributions to organizations of various sectors in general by showing the impact of employing social media as a new alternative to gather information and manage internal resources to a company’s benefit. Given this, practical and theoretical implications were found.

Practical implications

The objective of this study was to examine the influence of social media management practices on hotel performance. It can be gauged that this objective was achieved, and it was confirmed that there is a positive influence on hotel performance with the adoption of social media management practices.

These results show that managing information in an online environment generates a fundamental capability for companies aiming at superior performance and competitive advantages.

The choice of performance variables was beneficial. The RevPAR variable is financial and was acquired through a perception of the companies themselves, i.e., through the hotels’ internal information. It is the result of good internal management that allows the adjustment of daily rates according to occupancy rates.

On the other hand, the online evaluation scores showed the perception of companies to customers, i.e., an external view. The content exposed in online reviews on social media is an essential source of information consumers offer. Therefore, online review scores represent a summary of the guest experience and serve as an aid in new consumers’ purchase decisions. This form of performance measurement is relatively new and innovative for hotels. Therefore, this research contributes to two different views of hotel performance measurement.

It can be concluded that the importance of the research lies in the fact that it shows that online platforms can represent opportunities and challenges since their use as management tools is still growing in companies. Thus, concerning management, besides contributing to the improvement of companies’ internal processes, this research encourages the use of social media management practices in organizations, in general, to achieve superior performance and generate a competitive advantage.

Theoretical implications

A significant theoretical contribution of this study shows that social media management practices in the hospitality context are executed through two separate dimensions since all previous literature only addresses practices in isolated ways and without a holistic view of their influence on performance.

The dimensions refer to the two factors found in the divisions of managerial procedures developed in the study. The first dimension, called monitoring practices, and response to comments involved monitoring the company’s reputation through online opinions, responding to online comments on social media, and developing strategies to promote the company’s services, considering the particular characteristics of each social media. These are practices related to the direct interface of social media with companies. Thus, they can be characterized as external practices that aim to manage the reputation and promotion of hotels.

One notices that this dimension resembles and complements the problem-solving approach proposed by Park and Allen (2013) on how managers use online information since the content exposed in online reviews serves as a fast and efficient mechanism for solving customer complaints and problems. Social media monitoring entails managing the company’s reputation by tracking online comments and acting as internal metrics to improve performance. In this first dimension, the concern for performance, in which long-term engagement with customers could be created (Kim et al., 2015), may be superficial and momentary rather than strategic.

The second dimension, called responsiveness and information dissemination practices, has in its composition the practices of documenting response standards to be used in online reviews, developing standard internal procedures for handling information in social media and communicating to internal areas about the information extracted from online reviews to improve operations and services. By conceptualizing these practices, it can be inferred that they are linked to the companies’ internal processes and have no direct contact with social media.

The characteristics found in this dimension are compatible with the strategic approach found in previous studies on how managers use online information (e.g., Park & Allen, 2013). This second dimension offers hotels a connection between the managerial and the operational sides, which is long-term and future-oriented for the company.

The expansion of existing knowledge from the meeting of the two dimensions has shown that the theoretical context surrounding social media management practices is still new and needs further study from the perspective of these two or more dimensions.

Limitations and future studies

As for the study’s limitations, it can be observed that the sample belonged to a specific state in Brazil; therefore, expanding the sample will provide better results. Another obstacle encountered was the face-to-face data collection, which limited the sample size.

Finally, this research studied the causality bias of using a set of social media management practices on the effect on performance. This direction was chosen in line with previous studies, but analyzing the issue of endogeneity in the opposite direction of cause and effect is suggested for future research.

The study also has limitations as to the use of variables due to their different measurement forms. Using other performance indicators to evaluate the similarity in the results is thus recommended. Another suggestion is to analyze whether the quality of managers’ answers on social media influences the companies’ performance. In addition, verifying the influence of social media management practices on performance according to other contextual variables of the hotels and sociodemographic variables of the respondents different from those used in this study is advised.

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Publication Dates

• Publication in this collection
  17 Apr 2023
• Date of issue
  2023

History

• Received
  13 Aug 2020
• Accepted
  16 Mar 2022