HOTEL MANAGER's ATTITUDES TOWARD SOCIAL MEDIA by Colleen M. Iacianci December 2015

HOTEL MANAGER’S ATTITUDES TOWARD SOCIAL MEDIA

A thesis dissertation submitted to the Kent State University College of Education, Health, and Human Services in partial fulfillment of the requirements for the degree of Master of Science

Colleen M. Iacianci

December 2015

Thesis written by Colleen M. Iacianci B.S., Art Institute of Pittsburgh, 2008 M.S., Kent State University, 2015

Approved by

______, Director, Master’s Thesis Committee Ning-Kuang Chuang

______, Member, Master’s Thesis Committee Andrew Lepp

______, Member, Master’s Thesis Committee Christopher Groening

Accepted by

______, Director, School of Foundations Kimberly S. Schimmel Leadership and Administration

______, Interim Dean, College of Education Mark A. Kretovics Health, and Human Services

IACIANCI, COLLEEN, M., M.S., December 2015 Hospitality and Tourism Management

HOTEL MANAGER’S ATTITUDES TOWARD SOCIAL MEDIA (177 pp.)

Director of Thesis: Ning-Kuang Chuang, Ph.D.

The hotel industry is forever growing as is the diversity of the consumer base.

With that in mind, hotel managers need to make precise and confident decisions when it comes to hotel operations. Taking advantage of all the resources, tools, and tactics managers have at their disposal is important as they work to stay ahead of the competition. Understanding current manager perceptions and attitudes toward the use of social media in the hospitality industry can benefit individual properties and help brands to be better prepared to maintain their competitiveness. The research objectives of this study are to (1) investigate manager’s attitudes toward social media, (2) explore factor’s

(e.g., external, internal, perceived usefulness, perceived ease of use, and attitude) effects on actual social media use, and (3) examine what are the most influential factors that drive change as well as pressing challenge and returns on investment affecting actual social media use in hotels. A survey was developed and distributed via email to hotel managers. Cronbach alpha, exploratory factor analysis, a series of simple linear regressions, a one-way ANOVA, independent sample t-test, and frequencies were used to analyze survey data. Results indicated that TRI strongly influences ease of use and usefulness; usefulness strongly influences attitudes, and type of hotel is the strongest predictor of actual use. In addition, significant differences were found of perceived ease

of use and job titles, hotel type, tenure, and age. Significant differences were found in perceived usefulness and job titles. Implications and limitations are discussed and can be used as a basis for further studies.

ACKNOWLEGEMENTS

I would like to thank my committee members, Christopher Groening and Andrew Lepp for their support and advice during the process of accomplishing this study. They provided me with new insights of the study based on their industry experience and academic expertise.

I would like to extend my sincerest appreciation and gratitude to my thesis advisor, Ning-

Kuang Chuang. Were it not for her patience, guidance, and dedication, I would not have been able to complete this study. I greatly appreciate all of her support during the development of this thesis.

Lastly, I would like to thank my family and friends for their support and encouragement throughout this process. A special thanks to my husband and parents. Were it not for their love and reassurance during my time at Kent State University, I do not believe I would have been able to accomplish my Master of Science Degree.

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TABLE OF CONTENTS

ACKNOWLEDGMENTS...... iii

LIST OF FIGURES...... vi

LIST OF TABLES…...... vii

CHAPTER I. INTRODUCTION ...... 1 Factors Affecting Manager’s Perceptions and Attitudes toward Social Media ...... 3 External and Organizational Variables ...... 4 Demographical and Job Background Variables ...... 5 Internal variables ...... 7 Percevied Ease of Use and Usefulness ...... 9 Social media return on investment ...... 10 Pressing Challenges and Factors Affecting Actual Social Media Use ...... 11 Purpose of Study ...... 13

II. LITERATURE REVIEW ...... 17 Social Media in the Hotel Industry ...... 18 Impact of Social Media to Hotel Operations ...... 22 Factors Affecting the Implementation of Social Media in Hotel Operations ...... 26 Conceptual Underpinning – Technology Acceptance Model ...... 28 External Variables ...... 32 Internal Variables – Technology Readiness Index (TRI) ...... 41 Perceived Ease of Use ...... 44 Perceived Usefulness to Hotel Operations and Return on Investment ...... 46 Attitude toward Using ...... 53 Proposed Model ...... 55 Challenges and Factors Which Drive Change ...... 57

III. METHODOLOGY ...... 60 Human Subjects Review ...... 60 Sample and Procedure ...... 60 Instrument Design ...... 61 iv

Data Collection ...... 64 Data Analysis ...... 64

IV. RESULTS ...... 66 Demographic Characteristics and Descriptive Statistics ...... 66 Reliability of Scales ...... 69 Factor Analysis ...... 70 Internal and External Variables ...... 73 Independent Samples t-Test and One Way ANOVA ...... 75 Regression ...... 77 Frequencies ...... 79 Return on Investment ...... 80 Challenges ...... 80 Driving Forces ...... 82

V. DISCUSSION ...... 83 External Variables ...... 83 Internal Variables ...... 89 Factors Impacting Manager's Perceptions and Attitudes toward Social Media ...... 90 Return on Investment ...... 93 Pressing Challenges and Factors Which Drive Change ...... 95 Driving Changes ...... 97 Return on Investment ...... 99 Return on Impressions ...... 99 Return on Engagement ...... 101 Brand Promotion ...... 104 Managerial Implications ...... 107 Limitations ...... 112 Future Research ...... 113

APPENDICES ...... 116 APPENDIX A. CONSENT FORM FOR MANAGERS ...... 117 APPENDIX B. KSU INSTITUTIONAL REVIEW BOARD APPROVAL FORM ...... 119 APPENDIX C. RESEARCH STUDY SURVEY ...... 121

REFERENCES ...... 127 v

LIST OF FIGURES

Figure

1. Technology Acceptance Model ...... 28

2. Theoretical Extension of the Technology Acceptance Model ...... 31

3. Proposed Model ...... 57

LIST OF TABLES

Table

1. Demographic Characteristics of Respondents ...... 68

2. Summary Descriptive Statistics of Seven Variables among Hotel Managers ...... 70

3. Total Variance of Technology Readiness ...... 71

4. Return on Investment of Social Media ...... 72

5. Challenges Associated with Actual Social Media Use ...... 73

6. Technology Readiness Mean Ranking...... 74

7. Actual Use Frequency ...... 79

8. Return on Investment Mean Ranking ...... 80

9. Challenge Mean Ranking ...... 81

10. Driving Forces in Implementation of Social Media ...... 82

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CHAPTER I

INTRODUCTION

When discussing a modern strategic hotel marketing plan the conversation would be incomplete without considering the use and importance of social media (Andzulis,

Panagopoulos & Rapp, 2013). Social media refers to “online tools where content, opinions, perspectives, insights, and media can be shared…at its core social media is about relationships and connections between organizations and people” (Nair, 2011, p.

45). These online tools include social networks, blogs, and consumer review sites, just to name a few. Social media’s use by the consumer has increased exponentially with 1.4 billion Facebook users, 300 million Instagram users, 58 million tweets being sent out every day, 4.2 billion videos being watched daily on YouTube, and more than 200 million consumer reviews on TripAdvisor, the most widely used and accepted consumer travel review site (Schoenfeld, 2010; statisticbrain, 2014). Even with these astounding numbers, some hotels have not fully invested their resources to understand how and why they should leverage the power of social media.

Many researchers (Davis, Bagozzi, & Warshaw, 1992; Lin & Lu, 2011b;

Venkatesh, Thong, & Xu, 2012) have discovered that both internal and external motivations influenced behavioral intention of information technology. Furthermore, attitudes help to define how a person behaves toward a situation or object (Pickens,

2005). For the above reasons, it is critical to evaluate internal and external variables in

addition to attitude to fully understand the motivations behind actual social media use.

This research aims to explore manager’s reactions toward the use of social media.

Specifically, this study first explores which factors, both internal and external, affect hotel managers’ beliefs and perceptions of the usefulness, ease of use, and return on investment. Secondly, this study examines which variable affects attitudes and actual social media use the most. Lastly, to provide insight to hotel managers, the most pressing challenges affecting actual social media use, factors that drive changes in hotels, and social media return on investment will be investigated. According to the theory of reasoned action (Fishbein, 1979), mental beliefs such as perceived usefulness and perceived ease of use immediately affect attitudes toward using that object, intentions to use and ultimately, and actual use of that object. External variables (ones outside of a person’s cognitive beliefs) affect behavior only through their impact on perceived ease of use and perceived usefulness (Karahanna & Straub 1999).

Hotel general managers and directors of sales, operations, and marketing all contribute to important decision making when it comes to implementing new strategic measures within the property. If these individuals do not hold open attitudes toward social media and see it as an important or useful tool in the personal and professional lives, this could cloud their judgement on utilizing social media to gain a competitive edge for their hotel (Diga & Kelleher, 2009). Studying attitudes and perceptions is critical to this research as both lead to actual use of social media. Much research has been conducted on a variety of topics related to consumer behavior on social networking sites (e.g., Chu & Kim, 2011; DeAndrea, 2012; Hudson & Thal, 2013; Kwok & Yu, 2012;

Kwok & Yu, 2013; Lin & Lu, 2011) and the advantages of having an active role as a business on these networks (McCarthy, Stock & Verma, 2010; Anderson, 2012; Culnan,

McHugh, & Zubillaga, 2010) but few studies were found examining the role of the individual responsible for this online presence, or how the active online representation began within the property. In a 2011 analysis of existing hospitality marketing research,

Line and Runyan found that in spite of the explosion of the Web 2.0 phenomenon, research into its application in marketing has been largely ignored. Online reputation management helps to build trust and credibility of a business as well as help to manage any negative online presence while increasing the positive image (Zaglia, Waiguny,

Abfalter, & Müller, 2015). Proactive online reputation management has a direct impact on a hotel’s bottom line; a one-point increase in a hotel’s average user rating on a 5-point scale makes potential customers 13.5% more likely to book that hotel (Anderson, 2012).

Decision makers within a hotel are responsible for maintaining a competitive strategy that will aid in a hotel’s success (Buhalis & Mamalakis, 2015). Their exclusion of online reputation management in the current digital age could hinder the success of their hotel

(Cohen & Chapman, 2015).

Factors Affecting Manager’s Perceptions and Attitudes toward Social Media

Research has shown that the hospitality industry generally has difficulty carrying out innovation (Baum & Ingram, 1998) and managers in the hotel industry typically use an authoritative leadership style (Lamelas & Filipe, 2011; Tracey & Hinkin, 1994). If hotel managers or hoteliers lead with little participation or input from others, it is possible there is little change within their hotel.

External and Organizational Variables

Social media and online reputation management is a relatively new task for hospitality management companies and independent hotels. While many branded hotels are given guidelines by parent companies on how to successfully manage their online reputations, often times the final decision on if and how it is done, especially in a franchised property comes down to the general manager. If the general manager does not understand the importance of managing the hotel’s online reputation or the specific channels or methods of this management process, it could lead to concerns in implementing an online reputation management system. These concerns could not only be due to a personal misunderstanding or misperception; it could be due to budgetary constraints in hiring or training an employee to carry out this task (Law & Jogaratnam,

2005), or due to not knowing how to fit social media management in with other necessary parts of hotel operations such as marketing, revenue management, and sales. As for the future, 62% of the companies already using the social media believe in its increased use, however, an impressive 50% of them fear the potential legal issues (personal data protection, labor code or copyright issues) resulting from its use (Scholz, M., & Zajko,

2014). With the advanced use of technology and social media in most segments in the service industry, it is now imperative for hotels to actively manage their online reputation. Being able to reach their guests before, during, and after a hotel stay can assist with improved competitive edge, repeat business, and positive electronic word of mouth (Leung, van Hoof, & Buhalis, 2013).

Hotel operations tend to focus on efficiency (Assaf, Barros, & Josiassen, 2010).

Being efficient often requires standardization, repetitions, and mechanistic behaviors

(Ogaarda, Marnburga, & Larsena, 2007). The relatively new practice of social media and online reputation management does not fall into the standardized ways of efficient hotel operations but because of the change in the way travelers consume information, hotels must adapt and be flexible (Yohannes, 2015). Search engines and social media sites play a central role in building a company’s reputation online (Madden & Smith, 2010). The messages sent across social media and other online channels can be amplified very quickly and brand performance will be impacted (Woodcock & Green, 2010). An innovation is any idea, practice, or object that is perceived new by the adopter (Fichman,

1992). A 2005 survey (Ottenbacher & Gnoth) of German hoteliers found that innovation is far less important than the effectiveness of a hotel’s human resources management and employee training, empowerment, and commitment to the service. Ensuring that innovation is matched to the targeted market is important as is the customer service, but having innovative technology was not a significant factor in new-service development for these hoteliers. These external factors have added influence to manager’s perceptions which in turn affect their actual use of social media.

Demographical and Job Background Variables

Changing demographic patterns and cultural influences have led to an increasingly older workforce (Sharit & Czaja, 1994). Research suggests that age differences in information processing have an impact on workers’ performance on computer based systems or tools (Sharit & Czaja, 1994). Thus, it could be assumed that

6 an older manager may have difficulties adapting to innovation therefore, social media practices within a hotel than a younger manager as evidence suggests that as basic physiological processes decline with age, older workers are less able to process complex technology practices (e.g., Birren, Woods & Williams, 1980; Botwinick, 2011; Rodin,

2014). In addition, research suggests that older workers have more difficulty adapting to changes in the work environment and are likely to prefer practices that are familiar to them (e.g., Sharit & Czaja, 1994). In terms of years of hotel experience, general managers are more senior than line employees based on the typical workforce trend in the hospitality industry (Bharwani & Butt, 2012). Therefore, the longer an individual has been in the hotel industry, the older they are (Riley, 2014). Consequently, an individual who has been in the industry longer is hypothesized to have a lower perceived ease of use and usefulness of social media compared to a less experienced worker. In addition, millennials (those born between 1980-early 2000s) have grown up with technology in a very different way than previous generations and therefore may adapt more easily than their older counterparts (Kilian, Hennigs, & Langner, 2012). Digital natives are millennial students who have grown up using information communication technologies

(Prensky & Berry, 2001). The digital native concept describes the generational switchover where people are defined by the technological culture which they are familiar with. These individuals were exposed to technology and the internet at an early age and therefore familiar with the technology. Digital native immigrants (Joy, 2012) are those

(assumed older generation) who did not grow up with the technology and are slower to

7 grasp concepts and hi-tech progress. Especially in the U.S., there is a noticeable gap

(Bow & Wohn, 2015; Prensky & Berry, 2001).

With regard to the level of education, some technologies cannot be adopted as a

"black-box" solution, but rather, impose a substantial knowledge burden on would be adopters. While classical diffusion focuses on the determinants of a would-be adopter's willingness to adopt, in circumstances where knowledge barriers are high, the more telling issue can be an adopter's ability to adopt (Fichman, 1992). Research by Cohen and Levinthal (1990) developed the idea that an organization's innovative capability is determined by its absorptive capacity, where absorptive capacity is defined by the organization's ability to recognize the value of new information, assimilate it, and apply it to productive ends. Some potential technology adopters are more innovative than others and can be identified as such by their personal characteristics such as level of education

(Jackson, Mun, & Park, 2013; Lam & Shankar, 2014; Rogers, 1983). Those with higher levels of education may have had more opportunity to interact and engage with technology over those with less education (Bennett & Maton, 2010).

Internal variables. Favorable perceptions of innovation characteristics are positively related to adoption (Andreassen & Streukens, 2013; Arts, Frambach, &

Bijmolt, 2011; Davis, Bagozzi & Warshaw, 1989; Huff & Munro 1989). Amiel and

Sargent (2004) explored the relationship between personality and internet usage motives and found that individuals who scored high in neuroticism (low emotional stability) reported using the internet to feel a sense of “belonging” and to be informed, while extraverts made more instrumental and goal-oriented use of the internet. McElroy,

Hendrickson, Townsend, and DeMarie (2007) found personality to be a much better predictor of internet use than cognitive reasoning, while Devaraj, Easley, and Crant’s

(2008) results showed a moderating role for personality on the relationship between technology usefulness and intention to use. Technology may trigger both positive and negative feelings. Although positive and negative feelings about technology may coexist, the strength of the two types of feelings is likely to vary across individuals. Therefore, people can be arranged along a hypothetical technology beliefs continuum anchored by strongly positive at one end and strongly negative at the other. Furthermore, people’s positions on this scale can be assumed to correlate with their inclination to adapt a technology (i.e., their technology readiness) (Parasuraman, 2000). It is important to take into account both external and internal factors when measuring an individual’s attitude toward technology. The technology readiness index (TRI), developed by Parasuraman

(2000) takes into account a person’s individual traits (internal variables) and how they relate to a propensity toward technology. The measured traits in this model are optimism, innovativeness, discomfort and insecurity. Although the positive feelings (optimism and innovativeness) propel people toward new technologies, the negative feelings (discomfort and insecurity) may hold them back. According to TRI research, optimism is a positive view of technology with belief in increased control, flexibility, and efficiency in life due to technology. Innovativeness is a person’s tendency to be the first using a new technologies. Discomfort means having a need for control and a sense of being overwhelmed. Lastly, insecurity is a distrusting of technology for security and privacy reasons (Parasuraman & Colby, 2015; Walczuch, Lemmink, & Streukens, 2007). The

9 stronger a trait, the better the individual fits into one of the groups and the more significantly they are influenced in the use of high-technology products and services.

People with high TRI levels score high on optimism and innovativeness. They feel comfortable using technology and require little proof of its performance. People with lower TRI levels are more critical; they ask for help more often and feel uncomfortable with new technologies (Dutta & Mia, 2011; Walczuch, Lemmink, & Streukens, 2007;

Wook, Yusof & Nazri, 2014).

Perceived Ease of Use and Usefulness

The technology acceptance model suggests that perceived usefulness and perceived ease of use of information technology (IT) are major determinants of its usage

(Davis, 1993). Consistent with the theory of reasoned action, the technology acceptance model suggests that user’s beliefs determine the attitudes toward using the system.

Behavioral intentions to use, in turn, are determined by these attitudes toward using the system. Finally, behavioral intentions to use lead to actual system use (Moon & Kim,

2001). Perceived ease of use is defined as the degree to which a person believes that using the system will be free from effort (Davis, 1989; Hess, McNab & Basoglu, 2014).

Perceived ease of use has been shown to have a direct effect on intention to use and an indirect effect on intention to use via perceived usefulness (Davis, 1989; Martins,

Oliveira & Popovič, 2014).

Much evidence shows that the most critical belief in understanding an individual’s attitude toward adopting a new technology in the workplace is based on their perceptions of the technology’s perceived usefulness (Davis, 1989; Taylor & Todd, 1995). Szajana

(1996) found that when an individual becomes more experienced with the information technology, usefulness directly determines not only intention to use but actual usage behavior. Szajana (1996) suggests that unless the user perceives the technology to be useful, their perceived ease of use has no bearing on actual use. However, Moon and

Kim (2001) confirmed that perceived ease of use and perceived usefulness were shown to be important to user’s perceptions of internet based systems but found that perceived ease of use had a more significant effect on individual’s attitudes than perceived usefulness.

Jackson, Mun, and Park, (2013) explain that perceived ease of use, compatibility, and result demonstrability are not important in explaining how personal innovativeness in information technology (PIIT) exerts its influence on behavioral intention. However, perceived usefulness, image, subjective norm and perceived behavioral control are important (Jackson et al., 2013). Therefore, this study is in the hope to discover which variable, perceived ease of use or perceived usefulness, affects attitude toward actual social media the most.

Social media return on investment. Financial and organizational concerns could be factors in manager’s attitudes toward social media. Furthermore, perceived ease of use and perceived usefulness could very well have an effect on attitude. However, to only examine those particular aspects of the hotel operational system would leave out other possibilities. What concerns a manager or hotel operator the most may be what they could gain the most from. Finding a viable formula for social networking return on investment is being examined by numerous researchers (e.g, Alston, 2009; Avectra, 2012;

Hoffman & Fodor, 2010), however for many hotel practitioners, the ability for hotels to

11 successfully connect with their existing or potential consumers would lead to a better consumer experience, which will in turn lead to improved financial performance of hotels

(McKay, 2010; Montague, 2006). Social media has changed the way that companies interact with their consumers and customers. In the hospitality industry, online review sites have created an electronic word of mouth that is considered to be extremely valuable by creating honest feedback, known as user generated content, for other potential customers to read (Chu & Kim, 2011). In a 2008 study, Cheong and Morrison found that the majority of internet users trust user generated content over brand advertisement. In a

2013 study, Neilsen found that 84% of consumers trust word of mouth recommendations from family and friends more than any other source. Furthermore, 68% of consumers trust online consumer opinions which is 7% more than just six years prior (Nielsen,

2013). This is why proper online reputation management can be important to hotel operations so they may ensure only correct and harmless information is online for their potential guests to read. There are many factors that go into social media ROI that so often the answer for “What’s the ROI of X, Y, and Z” morphs into “it depends” (Lee,

2014, p. 1). The idea that there are intangible benefits that extend beyond those that are measurable is especially true when it comes to content, which has become the way for marketers to reach their audience (Safran, 2014). Marketers know that theoretically, social media should be a powerful way to generate sustainable, positive word of mouth

(Kumar & Mirchandani, 2012).

Pressing Challenges and Factors Affecting Actual Social Media Use

In their 2011 study, Hanna, Rohm, and Crittenden found that companies and organizations are looking to online social marketing programs and campaigns in an attempt to reach consumers where they ‘live’ online. However, the challenge facing many companies is that although they recognize the need to be active in social media, they do not truly understand how to do it effectively, what performance indicators they should be measuring, and how they should measure them. Furthermore, as companies develop their own social media strategies, social platforms such as YouTube, Facebook, and Twitter are often treated as stand-alone elements rather than part of an integrated system. As identified by PhoCusWright’s “Social media in travel: Mayhem, myths, mobile & money” report, the top three social media concerns in the hotel industry are as follows: (1) measuring return on investment on organized social activity (52% of hoteliers); (2) measuring the impact/reach of branding and brand marketing through social media; and (3) keeping up with new social platforms (Hotel News Now, 2014).

With the emergence of the internet, information privacy arose as a salient issue. Concern for information privacy on social media platforms is increasingly gaining the interest of researchers, business leaders, and consumers (Osatuyi, 2015). Specifically, information privacy is defined as “the interest individuals have in controlling, or at least significantly influencing, the handling of data about themselves” (Clarke, 1999). Hoffman, Novak, and Peralta (1999) asserted that consumers’ expectations of privacy depend on the type of media. While consumers do not pay much attention to privacy in traditional media, they do want control and protection of privacy in electronic media (Hoffman et al., 1999). In the context of the internet, privacy is important because it builds a sense of trust in

13 consumers which can lead to increased use of social networking sites. Privacy is also a major concern for hoteliers and general managers as safety plays a large factor in a guest’s travel decisions (Feickert, 2006). As technology and innovation continue to evolve, hotels are often forced to make changes to stay competitive and keep the consumer’s travel dollars in their pocket. Hotels that survive and even thrive are usually the ones that most readily adapt to change. A variety of factors can cause a hotel to reevaluate its operational strategy. For these reasons, this study aims to discover what the most pressing challenges are affecting actual social media use in hotels.

Purpose of Study

Although it is important to investigate how the decision makers react and adapt to this new marketing effort, in order to tackle the fundamental issue and gain a comprehensive understanding of why online reputation management is vital to the success of a hotel. The success of a hotel in the quickly growing hospitality industry depends strongly upon their online reputation and without proper management the hotel can suffer (Conner, 2014). This can create a significant concern with general managers of hotels as to whether social media will affect their property’s reputation, and at the most basic, the hotel’s bottom line. Research ﬁndings thoroughly demonstrate the strategic importance of social media for tourism competitiveness (Leung et al., 2013). Recently, many hotels have begun using social media (e.g., Facebook fan pages) to enhance brand attractiveness and maintain customer relationship management. Radical shifts in business models are also occurring in other industries. For example, Pepsi bypassed a

Super Bowl advertisement for the first time in 20 years in order to shift those millions of

14 dollars into social media efforts. Ford Motor Company has adjusted their marketing budget so 25% of it is utilized in digital and social media strategies (Qualman, 2010).

Social network sites have evolved into social utility networks, thereby creating a number of promising business opportunities (Lin & Lu, 2011). This can create a positive or negative outcome for the hotel and its position in the industry. Social media management becomes more and more popular and expensive, both in terms of time and money.

Therefore, how effective social media is versus the resources needed to maintain the effort is important to keep in mind (Uitz, 2011). Not fully understanding the many facets and forms of social media (Kietzmann, Hermkens, McCarthy, & Silvestre, 2011) in addition to the use of social media in their own lives; and operational feasibility within the hotel (Bottles & Sherlock, 2011) can all be factors in a manager’s attitude toward social media.

The use of social media has changed the way that businesses interact with consumers. Travelers are using electronic word of mouth review sites such as

TripAdvisor and Yelp to aid in making traveling decisions (McCarthy, Stock, & Verma,

2010). Reaching these consumers before, during, and after a hotel stay requires active online interaction (Leung & Bai 2013). Some hotel executives still struggle to understand the importance of social media and the role it plays in modern marketing and online reputation management (Lin & Lu, 2011a). Others do not know that they should be concerned with online reputations (Conner, 2014). This misunderstanding may cause hotel managers to delay in implementing proactive online representation which can in fact damage the online reputation of a business (Conner, 2014) and limit reach of

15 message and loss of market share to competition (Starkov & Safer, 2014). To further understand these attitudes, this research will utilize the Technology Acceptance Model

(Davis, 1985), Technology Readiness Index (Parasuraman, 2000), and Social Media

Return on Investment (Buhalis & Mamalakis, 2015; Oana, Valentin, & Cosmin, 2014).

Implicit attitudes can cause behavior (Blair, Dasgupta, Glaser, 2015). By combining these models, we hope to discover what the current attitudes toward social media are by examining the following variables: external, internal, perceived ease of use, perceived usefulness, return on investment and which variable affects their attitude the most.

Lastly, this study intends to discern what the most frequently cited factor drives change or appears the most challenging in hotels.

In specific, this study aims to answer the following research questions (RQ):

RQ1 − Which internal or external factors are perceived to exercise the most

influence on manager’s attitudes to implement social media within their

organization?

RQ2 − Are there significant differences in managers’ perceptions, beliefs, and

attitudes toward social media based on their demographics and contextual

background (i.e., age, levels of education, work experiences, job titles, type of

hotels, and management ownership)?

RQ3 − Which of the predictor variables are most influential in predicting

managers beliefs and perceptions (i.e., ease of use, return on investment, and

usefulness) as well as their attitudes and actual use of social media?

RQ4 − What are the factors that drive changes, what are the pressing challenges,

and what are the most important returns on investments which affect social media

use within the organization?

By understanding how managers in the U.S hotel industry accept and use social media, it can provide beneficial information to hoteliers, other managers and department heads within the industry, and current or future hotel employees with an interest in online reputation management so they may better implement or improve the practice of social media management within their means of reason at each property. Creating a strategic plan in maintaining or bettering a hotel’s competitive edge is beneficial to hoteliers and stakeholders (Hehir, 1999; Enz 2011). While it may be difficult to sustain a competitive advantage, hotels can work to create advantages through the development of resources and capabilities. Social media and new technologies are playing a key role towards the growth in the hospitality industry (Deloitte, 2010). Therefore, social media and online reputation should be part of a hotel or management company’s strategic plan. The research findings of this study are expected to provide hotel management companies with useful information. First, by successfully utilizing all possible methods and means to successfully reach their target audience, hotels can increase their competitive edge.

Secondly, there is a possibility that there are hotels or hotel management companies that do not have a qualified or interested employee who would be willing and able to take on the task of social media management at their property. This research could spark interest with general managers at those properties and it could prompt them to prioritize training or group discussion within their hotel.

CHAPTER II

LITERATURE REVIEW

Advantages of proper online reputation management for a hotel are countless.

97% of consumers search for information about a business online (BIAKelsey, 2010) and

85% of consumers read online reviews to determine if a business is a good business

(Anderson, 2014). Online consumers spend at least 37 minutes per day on social networking sites which is more than they spend on email (Adler, 2014). 70% of consumers trust consumer opinions online (neilsen, 2013). Should a hotel receive a negative review, it is imperative the hotel respond publicly as responding hotels see an average increase of 0.1 stars in their TripAdvisor ratings after they start responding

(Proserpio & Zervas, 2014). In addition, if a property is able to increase its average user rating by one-star (for example, from 3.8 to 4.8 on a five-point scale), the hotel could increase the daily rate by 8% without seeing a negative impact on overall net bookings.

Online reputation management is defined as an attempt to shape the public perception of a person or business by influencing online information (Horster & Gottschalk, 2012).

This involves establishing, maintaining, monitoring, and sometimes repairing public information about the organization (Jones & Thevenot, 2010). With sites like

TripAdvisor, where guests can leave feedback for the hotel and recommendations (both positive and negative) for other potential guests, hotels can learn from the negative, and respond with appreciation to the positive. By actively managing their online reputation, a

hotel can show their current and potential guests that they care about the consumer’s comments and concerns. This not only gives the hotel the ability to reach guests before they make a booking decision, but also allows follow up for possible repeat business. By not properly managing their online reputation, it could have negative impacts on the hotel from losing out on potential room nights, to appearing as though they are ignoring, or do not care about consumer opinion, thus damaging their reputation (Conner, 2014). Hotel owners and general managers need all the tools they can use to maintain competitive edge in the growing market. By understanding current attitudes, perceptions, and pressing challenges, they can better learn how to implement successful social media tactics within their organization. In consideration of this, this chapter first contains background information of social media in the hotel industry. The paper will then explore manager’s attitudes and perceptions toward social media by examining external concerns via fear management, the technology acceptance model; and internal factors via the technology readiness index. Lastly, this chapter contains background information on current social media return on investment methods of measurement, specifically, return on impression, return on engagement, and opportunity for brand promotion which can affect an individual’s perceived usefulness of the technology.

Social Media in the Hotel Industry

Web 2.0 is a stage of development for the World Wide Web that changed the internet scene from one of static web pages to an increased amount of interactive pages and user generated content (Lo, McKercher, Lo, Cheung, & Law, 2011). Along with these changes come two phenomena, a new form of consumer known as the creative

consumer, and social media (Page & Pitt, 2011). Previously, consumers had been spoken at by businesses and marketers; however nowadays, their purchasing decisions are influenced largely by their social circles (Hinz et al., 2014; Ma et al., 2014; Palmer &

Ponsonby, 2002). Thus, the modern manager should not underestimate the power of a social circle because the people a hotel engage may be the ones who create or bring new sales leads to the hotels. Marketers previously believed that after a purchase of a product of service, the relationship between a brand and consumer relied solely on the continued use of the product or service (Hudson et al., 2013). With the innovation of Web 2.0, consumers began interacting and developing relationships with brands online before and after a purchase. In an industry round table discussion, Verma, Stock, and McCarthy

(2012) said “…the most powerful promotional tool is word of mouth from a friend, and social media are an extension of this network” (p.183). However, how managers realize the impact of the social media and how much they take an initiative to adjust or reform the organizational structure to support the online reputation management efforts are underexplored. For many individuals, the terms social media and social network can be used interchangeably. For this study, clarification is needed and industry experts agree that there are differences between the two. Social media include anything that one can upload including blogs, videos, and newsletters (Burke, 2013). It is mainly used for sharing ideas and while readers can respond and comment, the content is owned and produced by the host. Some may call social media a strategy and social networking sites tools. Social networking sites are all about the engagement and a multiple way conversation between brands and online users. As an example of how hotels can benefit

20 from social media management, Noone et al. (2011) found that hotel revenue management teams can utilize social media to (a) understand consumer’s willingness to pay, therefore optimizing pricing structure; (b) utilize user-generated content to manage add-ons like breakfast, and special package options; (c) create and target online messages to direct consumers to specific booking distribution channels; and (d) maintain beneficial search engine optimization strategies.

Social media provides a whole new platform for which it builds or destroys an industry. According to a 2014 Facebook shareholder meeting, there are currently 30 million Facebook business pages (Facebook, 2014). The rapid development of social media has challenged managers to rethink how this trend will shape traditional marketing practices (Lee et al., 2012) and perhaps the organizational structure and pattern of responsibility. Hotels can build their reputability through technology; they can also equally ruin them. The importance of access to the right type of experience is evident in the finding of survival-enhancing learning from the local experience of related others

(Baum & Ingram, 1998). The population’s experiences and associations can aid in consumers’ decision-making process. Law and Jogaratnam (2005) suggest that information technology can transform the nature of tourism and hospitality products, processes, businesses, and competition, and that tourism and hospitality organizations that have failed to master the right information technology systems would find it difficult to direct and manage their information-intensive business without damaging their competitiveness.

Referencing the current slow moving growth the hotel industry experienced in

2013-2014, Lodging Econometrics (2014) believes that in 2015, hotel growth will begin to stride ahead. In 2015 hotel occupancy in the United States is expected to reach 64.8%, the highest it has been in 20 years (PwC, 2014). According to a leading hotel predictor,

Mark Woodworth at PKF Hospitality Research, hotels are expected to increase rates by an average of 5.4% (Hobbes, 2015). Other research predicts the increase to be anywhere from 2.6% to 3.4% (Global Business Travel Association, 2014). Nonetheless, the travel demand and price increase will be a change for the consumer and will require travelers to even more carefully consider their vast options in hotel accommodations. Furthermore, with this growth in mind, consistent monitoring and analyzing competitive strategy and continuously distinguishing their business from others, become a crucial part of hotel marketing and management (Hehir, 1999).

The tendency of customers to stay with a certain business, store, brand, or product over another is based on how the consumer’s needs are met (Litvin, Goldsmith, & Pan

2008). From the 1990’s, the use of new technologies in the hotel sector started to be considered not only in terms of productivity, but also in terms of intangible benefits such as client service and satisfaction, and as an incentive to establish intra-company, inter- company, and customer relationships (Siguaw & Enz, 1999). An example of the hotel industry’s adaptation to this is the secret codes given over social channels by Kimpton

Hotels. Guests can use the secret codes at check-in and receive prizes like a free upgrade or bottle of wine (Bessette, 2014). Social media has enabled its users to become more acquainted with certain everyday aspects of fellow users’ lives (Murthy, 2012). This directly aids in the development of businesses’ social media strategy. Hotels may focus

22 on the idea of preparation for public interactions, private communication, public performance, and observation of public performance (Sas, Dix, Hart, & Su, 2009).

Kimpton Hotels has used their social media team to be a listening hub for people talking about the brand online. Through Twitter, they have connected with guests and after learning that a particular guest was feeling under the weather, they informed the team at the property level who delivered soup, warm tea, and a get well card to the guest’s room

(Bessette, 2014).

Impact of Social Media to Hotel Operations

Organizations may be seen as entities with their own perceptions and memories of the market and the customers. From this perspective, managers need to facilitate and support knowledge creation, rather than control and measure it directly (Gjelsvik, 2002).

The direct sustainability of this is that the hotel can build their image, instead of allowing their image to build them. Organizational development can be directly reflected through social media. Desktop users spend 55.4 minutes per day engaging in Facebook (Adler,

2014). Many web based services are used to book hotels and travel. The percentages of consumers consulting reviews at TripAdvisor prior to booking a hotel room has steadily increased over time, as has the number of reviews they are reading prior to making their hotel choice. Transactional data from Travelocity illustrate that if a hotel increases its review scores by one point on a 5-point scale (e.g., from 3.3 to 4.3), the hotel can increase its price by 11.2 percent and still maintain the same occupancy or market share

(Anderson, 2012). The ability to review their experience and share with the community is an important part of the success of TripAdvisor. The successful operation of an online

23 travel community depends on the understanding of member participation and active contribution to the online travel community (Wang & Fesenmaier, 2004). A proposed solution to the shortcomings of traditional media campaigns is the adoption of online mediums in which participatory social media plays a crucial role in health communication (De Andrea, 2012).

In a 2011 World Travel Market report, a survey found that 36% of travelers ended up changing hotels because of what they found on social media sites (Koumelis, 2011).

Consumers today are more sophisticated and have a greater demand for information when making a purchasing decision. Their demand along with the number of choices in accommodations growing at a predicted 1.6% in 2015 (Lodging Econometrics, 2013) means that hotels need to be able to reach customers and gain their attention before they even decide to go on a trip. This is where hotels need to have an integrated customer relationship management strategy that extends outside of their doors to compete effectively. Hospitality Sales and Marketing Association International published a 2006 survey on the customer relationship management strategies of resort properties and found that many resorts saw their customer relationship management only as on-site customer service and these same resort properties saw their marketing tools as separate. Hotels are able to connect with their guests on a personal level by utilizing customer relationship management tools and learning personal preferences. To do this efficiently however, every department within the operation must function cohesively to produce a meaningful strategy (Green, 2006).

Many other industries such as retail, technology, and financial services have moved from customer relationship management to customer experience management

(Green, 2006). The hospitality industry has yet to fully embrace this strategy. Superior performance is the result of satisfying the customer more efficiently and effectively than competitors (Osborne & Ballantyne, 2012). Many scholars contend that it is necessary for marketing efforts to continue to become more and more customer-centric (e.g.,

Osborne & Ballantyne, 2012; Shah, Rust, Parasuraman, Staelin, & Day, 2006). Through a content analysis of previous social media research articles, Leung et al. (2013) found that many researchers contend the ability for social networking sites to assist tourism and hospitality companies to engage potential guests, build online relationships with increased online presence, and therefore increase online revenue. The hospitality industry has been slow in gaining momentum in its use of technology (Law &

Jogaratnam, 2005; Sloan, Legrand, & Chen, 2012). Customer needs are changing constantly and many hospitality organizations have to adapt their service delivery processes to these changes. With the reputation of holding on to outdated practices and with the relatively new eruption of Web 2.0, this study will attempt to find out if hotels have begun to flex their ways of thinking and acting to adapt to this change with special attention paid to management’s attitudes toward social media. Front line employees are often in a unique position to observe changing customer needs and suggest new approaches for improving the service delivery process (Raub, 2008) but the feeling of empowerment in these front line employees to suggest an idea of change is not generally encouraged (Bolino, 1999). It has been found that the management of social media in the

25 hospitality industry is most often a junior position (if any position at all) (Lepp, 2013).

The general manager of a hotel is the key position in a hotel and in many properties; the general manager is an employee of a hotel management firm making them an agent of the operator and/or owner (Hodari & Sturman, 2014). With regard to responsibilities, general managers have relatively great authority in human resources, marketing, and strategy (Hodari & Sturman, 2014). Therefore most if not all decisions when it comes to these categories have influence by the general manager on whether or not new practices are put in place. When reviewing a property's digital assets, often a hotel has a Facebook brand page and they may have Twitter or Pinterest or some other social media community, but there is typically no social media strategy in place, or even regular activity in managing the communities (Virginia Phelan, Chen & Haney, 2013). Even larger brands have commissioned front line personnel to manage social communities, and even review sites such as TripAdvisor and Google reviews, which is even more concerning as these channels have an impact on the bottom line (Anderson, 2012). Social media channels have become the heartbeat of a brand, a direct channel for communication with the customer. In hospitality, there is no choice but to ensure social media is part of the marketing mix, and that it is managed and measured properly (Kim,

Lim & Brymer, 2015). Law and Jogaratnam (2005) further suggested that information technology can transform the nature of tourism and hospitality products, processes, businesses, and competition, and that tourism and hospitality organizations that have failed to master the right information technology systems would find it difficult to direct and manage their information-intensive business without damaging their competitiveness.

In a 2011 white paper by Oracle, they examined the tie between social networking and customer loyalty. They stated that when ignored, social networks will not go away but customers may. With so many options for lodging, if consumers cannot find out information to questions they may have quickly enough, they will move onto the next lodging option (Oracle, 2011). While traditional media keeps customers informed, social media goes a step further by keeping the customers stimulated and involved. When a company engages with their customers, it can lead to lasting relationships (van Doorn, et al., 2010). A reduction of stress among staff in a people-oriented industry such as tourism and hospitality will be perceived quickly and positively by the customers of that organization (Cheng & Wong, 2015; Ross, 1991), therefore, the employee’s behavior and performance is a direct reflection of the business (Korschun, Bhattacharya, & Swain,

2014). In the hospitality industry, specifically, within hotels, there are typical hierarchies.

Within those hierarchies, general managers or owners oversee department heads who oversee front line employees (Torres & Kline, 2013). This hierarchy is in place for organizational structure and creates a decision making chain of command (Subramanian

& Ramanathan, 2012). Without examining the top decision makers, this study would have little implication for hotels and their ownership.

Factors Affecting the Implementation of Social Media in Hotel Operations

The sustainability of the hotel industry depends heavily upon the economy and environment for which they are built. Organizations that set forth defined positions for each employee may be necessary for the organizational structure but those definitions may not be enough to guarantee the organization’s success. Tracey and Nathan (2002)

27 stated that many views and policies in the hospitality industry are archaic and inflexible.

Specifically in the hospitality industry, Raub (2008) found that a centralized organizational structure, where one individual was responsible for all decision making, lead to negative impacts on organizational citizenship behavior which is said to be essential for service delivery. While hotel employees are empowered with frontline service practices, some decision-making process regarding staffing or handling critical marketing strategies may still be centralized (especially when it deals with a complex ownership situation). Effective implementation of a marketing strategy can prove difficult, as it requires coordinated and appropriate efforts of individuals throughout an organization. Accordingly, a critical task for senior managers is to define the key success activities for their organization's strategy and develop an organizational system that promotes those same activities (Olson et al, 2005). In their 2005 study, Law and

Jogaratnam found that many hotel managers did not understand the importance of information technology in the purpose of making decisions so it is safe to assume that many of these decision makers do not actively empower their employees to use information technology for business purposes. The main finding in Raub’s (2008) study was a suggestion that hotels de-centralize their organizational structure and replace with a more employee empowerment practice. This idea is useful in the current study to examine whether or not the lodging industry has taken this recommendation with their social media management practices by assigning social media management to an employee within the organization who may be a part of a successful strategic planning model.

Conceptual Underpinnings - Technology Acceptance Model

Fred Davis proposed the Technology Acceptance Model in 1985. His model said that technology use can be explained or predicted by user motivation. Davis proposed that user motivation could be clarified by three factors: (a) perceived ease of use; (b) perceived usefulness; and (c) attitude toward using (see Figure 1). Davis (1985) found that perceived usefulness has a strong influence on intention to use technology. He also found that perceived usefulness will be influenced by perceived ease of use because the easier something is to do, the more useful it seems (Adams, Nelson, & Todd, 1992).

Figure 1: Technology Acceptance Model (Davis et al., 1989)

The technology acceptance model (TAM) has been applied in different contexts to investigate a wide range of information technologies and has been researched and validated across many industries. Lai and Lei (2005) confirmed this model by testing it on a different respondent subgroup to ensure age, gender, and information technology competence did not negatively affect research findings thereby validating TAM further.

Because of its simplicity and understandability, TAM is widely employed in various

29 studies to predict users’ behavior intentions. However, in the model application stage, the

TAM model may lack the ability to explain other potentially important factors that can influence a users’ acceptance process (Lee et al., 2012). Law and Jogaratnam (2005) confirmed that hotels have widely adopted technologies to improve operational efficiency, enhance service quality, and lessen costs. Nevertheless, despite the increase in the use of technology in the hospitality industry, few studies have been steered to investigate the relationship between the external variables and the technology acceptance model framework to explain actual use of technology in tourism and hospitality organizations (e.g., Lam et al., 2007; Lee et al., 2006; Wober & Gretzel, 2000). Kim, Lee and Law (2008) utilized the technology acceptance model in an attempt to investigate the relationship between experiences and users’ acceptance of hotel front office systems.

Schrier (2009) attempted to determine and quantify factors which impact a hotel guests’ intentions to seek and utilize guest empowerment technologies. His study found that factors of individual characteristics, technology characteristics, task characteristics, fit, perceived ease of use, and perceived usefulness have a significant impact on intention to use. Hsu and Lu (2004) ascertain that an extension of the TAM model may provide more explanation than the TAM model alone. In an attempt to strengthen TAM, some researchers have attempted to incorporate prior factors that could impact perceived ease of use and perceived usefulness to increase the prediction power of TAM (King & He,

2006). For example, Saadé and Kira (2006) contended that emotional factors such as anxiety, general beliefs, efficacy, and affect are all potential causes of perceived ease of use. Moon and Kim (2001) interjected perceived playfulness into the model and argued

30 that it is the basic motivation that can affect individuals’ acceptance of the internet. It is believed that a better understanding of these factors can shed light on how to cultivate positive perceived ease of use and perceived usefulness from the technology (Venkatesh,

2000). Built upon the successful use of the technology acceptance model in information science and information technology, this research extends the knowledge of the model into social media, where the argument becomes, of course, that both a users’ external and internal variables are the key factors in determining perceived ease of use and perceive usefulness and therefore attitude and ultimate use. In this study since the author believes that hotel managers are unlikely to assign importance to the playfulness of a work related activity in its significance to a hotel’s overall competitive strategy, the first argument is employed – external factors related to the knowledge and experience of a manager are related to perceived ease of use and perceived usefulness of social media. Venkatesh and

Davis (2000) contend that emotional factors can affect perceived ease of use and therefore perceived usefulness. Besides emotion, there are other possible factors that can be incorporated into TAM. Among them, both intrinsic and extrinsic motivations are commonly recognized as important determinants which affect users’ attitudes and behavior intentions (Davis et al., 1992; Wu & Li, 2007; Zhang et al., 2008). Intrinsic motivations refer to the perceptions of pleasure and satisfaction that come from performing the behavior (i.e. perceived ease of use), whereas extrinsic motivations relate to the drive to perform a behavior to attain specific goals and rewards (i.e. perceived usefulness) (Vallerand, 1997). As seen in the technology acceptance model (Figure 1), external variables affect perceived usefulness and perceived ease of use. External

31 variables in the technology acceptance model II (3) as defined by Venkatesh and Davis in

2000 in the theoretical extension of the model are subjective norm, image, job relevance, output quality and result demonstrability.

Figure 2: Theoretical Extension of the Technology Acceptance Model (Venkatesh & Davis, 2000)

Subjective norm is defined as a “person’s perceptions that most people who are important to him think he should or should not perform the behavior in question”

(Fishbein & Ajzen, 1975). Venkatesh and Davis (2000) added this variable because it is possible an individual performs an action or adopts a behavior even if they are unfavorable towards that action or behavior if they believe one of more influential people is favorable towards it. Job relevance, was also added as an external variable and is defined as an individual’s perception regarding the degree in which the technology in

32 question is applicable to their job (Venkatesh & Davis, 2000). In addition to these influences, other variables have been identified for the purposes of this particular study, types of ownership, the manager’s age, hotel experience, and level of education. The external variables that are utilized in this study from the extension of the technology acceptance model are job relevancy and result demonstrability as they both contribute to perceived usefulness.

External Variables

There are many types of hotel management and ownership and they are not necessarily mutually exclusive. For example, a hotel can either be in an independent property, one not associated with a parent brand; or the property can be a franchise of a chain hotel in which a management company maintains day to day operations, earns profit, and pays franchise fees (Contractor & Kundu, 1998; Felstead, 1991; O’Neill &

Carlbäck, 2011). An owner or owning company maintains financial and legal responsibility for the property while a management company maintains daily operations and earns money based on a set fee or success of the property (Freed, 2014). Hotel News

Now (2015) defines a hotel franchise as an individual or company buying or leasing a franchise, typically of a branded hotel. According to the same article, a manchised hotel is one that is franchised and managed by the same company. Remaining profits go to the ownership with which they pay for insurance, debt, etc. Many branded hotels in the

United States are franchised or manchised. For example, InterContinental Hotel Group has 75% of the rooms in its system, franchised; compared with 39% of Starwood’s as of

2009 (The Economist, 2009). The high statistic for InterContinental was attributed to the

33 recession and the impact of the recession was absorbed by the hotel owners rather than the chains that franchise them (The Economist, 2009). In some cases, ownership includes multiple individuals in which they may have a varying degree of decision making.

Franchising involves three major stakeholders: the franchisor, the franchisee and the customer (Zhang et al., 2015). Given their large stake in a company's equity, large stockholders have an obvious incentive to monitor top management's decisions closely in order to promote the positive long-term performance and growth (Alchian & Demsetz,

1972). Franchising's pervasiveness is partially due to its ability to incentivize independent local representatives while affiliating them with a widely recognized brand.

In this relationship, franchisees rely on the franchisor's brand to attract customers to their local location. In exchange for the right to assume the brand in delivering service to customers, the franchisee pays the franchisor royalties, typically calculated as a portion of total revenue (Argyres & Bercovitz, 2013). Customers interact with the local franchisee who is the actual service provider but associate their experience with the franchisor who owns the brand (Zhang et al., 2015). Independent properties have flexibility when it comes to marketing autonomy, and adaptations while flagged, or franchise chain properties while they may have some flexibility; they have to abide by certain standards to remain branded (Texas Education Agency, 2011).

Ownership and hotel experience can have much influence on a manager depending on daily involvement with operations, experience at other properties in portfolio, or with other hotel brands/management companies, etc. Hotel owners sometimes work off-property and complete much of their business through e-mail,

34 conference calls, etc. Not being on property leaves the responsibility of overseeing day to day operations to the general manager. It is then up to the general manager to inform the owner if they are missing out on any crucial activities or strategies that could add to the success of the property. Furthermore, most national brands such as Hilton, Starwood, and Marriot have required social media activities individual hotels must participate in

(Stokes, 2012). If a hotel is unbranded, this may affect any influence being received to being involved with online reputation management. For example, without being given strict guidelines and requirements, online reputation management for an independent property is seen as a voluntary activity. By focusing on operations, new technology, competition, and customer feedback that is learned at the property level, a general manager may learn of the importance of online reputation management (Litvin, 2008). If implementing an online reputation management strategy affects budget or personal, it is then either up to the hotel owner(s) or based on a mutual decision with the owner(s) to investigate how social media management can be worked into the daily operations of the hotel. If an owner disagrees or does not understand its importance, the general manager would have their hands tied. This is just one example of how hotel ownership and management can affect the implementation of new positions, training, or marketing strategies. Industry practitioners have long argued that hotel owners play critical roles in the hotel industry, and they implement different strategies to improve the performance of their hotels (Xiao et al., 2012). To date, little has been studied with regard to the effects of hotel owner corporate-level strategies on property-level performance. There are a variety of hotel ownership situations: corporate owned and managed, franchisor with

35 management contract, contracted management company, independent property, etc. Each hotel ownership type is unique in that there could be one owner, multiple owners, multiple investors, vocal or silent, corporate regulations, the list goes on. With this in mind, each situation is unique in how a policy or procedure becomes implemented at the property (Lee, 1985; Qu and Ennew, 2005; Zhou, 2014).

Hotel operations often focus on efficiency in their daily procedures, efficiency to clean guest room, check in guests, reset banquet space, etc. (Anderson et al., 2000; Wang et al., 2006). Being efficient requires policies, standardized ways, and repetition and often times, these practices can feel mechanistic to employees (Øgaarda, Marnburga, &

Larsena, 2007). Due to the changes in consumer communication channels, the organizational design has to be changed accordingly. With these types of standardized practices in place, innovation and change may still be required to keep up with the changing market and increased competition. These changes can be an intimidation factor for general managers which can create concern in their implementation of new practices like social media management. When hotels in the modern market try to emphasize a personal experience to each of their guests, sometimes the mechanical emphasis can get in the way of employees who need to be empowered to create these customized experiences for their guests. It is based on the employee’s ability to maintain efficiency while creating customization that will be an important factor for the success of hotel operations. The internal and external monitoring of social media mandates the company to ensure their presence is positive. The politics and culture behind a hotel is clearly presented through various social media outlets. An employee can spend their entire day

36 maintaining the sanctioned company presence on various social network sites, acting as a company's 'voice'. Such roles are arguably not that different from methods employed by more traditional marketing and sales operatives (Wilson, 2009).

In various studies (Gjelsvik, 2002; Karatepe, 2013; Ross, 1991; Zacarelli, 1985), it has been shown that hotel employees in the United States are very motivated about their work and have a positive outlook on the industry but Gjelsvik (2002) found that high motivation dissipates after an employee has been at one hotel for a long time due to decreased learning opportunities. Social media can be utilized in revenue management, sales, marketing, and even human resources. With this in mind, it can create a new learning opportunity for the employees in those departments thus increasing their motivation.

Organizational development thinking was more oriented towards structures, roles, and power positions rather than knowledge and knowledge creation (Hall, 1980).

However, as social networking and media has shown, there are far more factors to consider in organizational development than what was once believed. Today, the hotel industry is highly flooded with information (Law et al., 2013; Siguaw & Enz, 1999).

Because of that, hotel managers have been utilizing a variety of technologies to manage hospitality information to improve operational efficiency and enhance guest service. In their 2005 study, Law and Jogaratnam indicated that technologies are useful when they make hotel employees more productive and better able to serve their customers. By utilizing technology to benefit hotel operations, efficiency, and service to customers could provide a beneficial competitive edge in the ever growing hospitality industry (Siguaw &

Enz, 1999). The hotel industry extensively relies on information technology to improve employees’ productivity and efﬁciency which in turn, also improves customer satisfaction. Technology is not limited to social media when it comes to the hotel industry as many web based services are used to book hotels and travel.

Previous research into the hospitality industry has shown that specifically within hotels, there is difficulty in carrying out innovations (Baum & Ingram, 1998; Mattsson &

Orfila‐Sintes, 2014). There are also speculations about the traditional dictatorial management style within the industry (Pittaway et al., 1998; Solnet et al., 2013; Tracey &

Hinkin, 1994). These two ideas combined with research showing that the industry rarely takes advantage of its highly motivated, high quality workforce (Fossum et al., 2004;

Gjelsvik, 2002; Knox et al., 2014; Ross, 1991, 1994; Zacarelli, 1985), which could affect how the relatively new idea of social media management within the industry develops at the individual property level. Employees are able to feel empowered when there is a systematic organization form; however, with lower levels of mechanistic ways, employees could be at a loss as to what to do in certain situations. Therefore, for an employee to be beneficial to the organizational form, they need rules and regulations along with managerial expectations (or openness to changes), operational freedoms, and management support to perform their jobs effectively.

In Worsfold’s 1989 research, he found that the hospitality industry may have a problem with how effectively managers make the most of an employee’s resources or specifically, how managers react, adopt, or adapt to innovation. It is not to be assumed that an overly mechanistic organization will benefit the company, more so, it is

38 questioned how much is needed for hotel management to be successful. Øgaard et al.

(2007) states that more research into the understanding of manager’s roles in the hospitality industry is needed. These studies cannot be considered conclusive about the hospitality industry but they do speak to the idea that employees within the industry only want for its success. Nieves and Segarra-Ciprés (2015) found that both resources, internal and external, are factors that explain the introduction of new management practices and processes. Specifically, their results show that employees with high levels of knowledge, abilities and skills play a relevant role in the introduction of management innovations.

Level of education and age of the manager may have influence on their perceived ease of use and perceived usefulness due to exposure to the technology, social media training and education, daily use of social media in their personal lives and online connections (Porter & Donthu, 2006). Knowing that technology can benefit a hotel’s competitive edge (Siguaw & Enz, 1999) and social media can aid employees to better serve their guests (Law & Jogaratnam, 2005), one may deduce that hotel managers or hoteliers who have not already implemented social media in their operational strategy could be inhibiting hotel growth and innovation at their hotel. Many of these practices and innovative application in a hotel is left up to the hotel owner to decide on. It is important for opinion leaders within an organization to cultivate positive reactions about new technologies thereby increasing the likelihood of widespread acceptable across the organization (Venkatesh et al., 2003). If a hotelier is not on board with the new practice of social media and the hotel manager does not have strong enough feelings on the topic,

39 there is little chance it will be implemented (Kotey & Meredith 1997). The actions of trusted colleagues, or in this case, managers, can accelerate innovation adoption in potential adopters such as hoteliers (Rogers, 1983).

There is significant evidence (e.g., Davis, 1989; Davis et al., 1989; Mathieson,

1991) that suggests that the most critical belief underlying an individual’s attitude toward the behavior of adopting a new technology in the workplace is their perceptions about the usefulness of the technology. Specifically, whether or not the individual believes that using the technology will enhance a person’s job performance (Davis, 1989). Therefore, in determining usage, it is important to understand differences between younger and older workers in the importance each group attaches to factors relating to the usage of the technology (Venkatesh et al., 2003). Evidence shows that younger workers focus on job related outcomes and task achievement thus it is predicted that age will have a negative relationship to perceived ease of use and perceived usefulness. Increased age has been shown to be associated with difficulty processing complex stimuli (Plude & Hoyer, 1985) such as new technology. Venkatesh et al., (2003) found younger workers’ attitude toward using a new technology to be more salient than older workers. The researchers associated this finding with the idea that younger workers, ones in their twenties or thirties, were much more likely to be exposed to technology at a relatively early age. When their study was completed in 2003, it was likely that the older study participants were not exposed to technology until after completing high school or college, before a personal computer was common. Therefore, the opportunity to interact and understand technology before entering the workforce was limited. It is reasonable to assume that the older workers of

40 that particular study were more comfortable in utilizing non-technical methods to achieve a work-related task which is hoped to be confirmed by the survey question on how strongly one feels that they “do not feel confident doing business with a place that can only be found online.” Furthermore, younger workers were thought to be more comfortable making independent judgments about technology at the workplace and care less about what others around them believed (Stewart, 2014; Venkatesh et al., 2003).

Results from Hsu et al., (2015) revealed that entertainment has stronger influence on continuance of social media use for educated users, while self-presentation has stronger influence on continuance intention for users with lower level of education. However, links between information seeking and socialization to continuance intention do not display significant differences in either subgroups of high and low education. Beyond the mentioned study, very little existing research was found investigating level of education and social media use for the benefit of a business. Furthermore, no information was found on the relationship between industry experience and technology or social media use. One question in the survey asks how strongly the respondent feels that they are able to “figure out new social media products and services without help from others” as older workers were thought to be less confident in their ability to apply independent judgements on various new technologies and were more likely to seek out and consider other opinions offered by friends of coworkers (Venkatesh et al., 2003). As older workers appear to rely more heavily on training they receive on new technology and they weight issues of ease of use more heavily than younger workers, (Venkatesh et al., 2003), the survey for this research asks respondents about confidence in understanding and

41 accessing training support and manuals. In their study of the Technology Acceptance

Model, Portu, and Donthu (2006) concluded that older, less educated individuals have lower technology usage rates than those of younger, highly educated individuals. They also discovered that those factors affected their belief or attitude toward technology and ultimately, actual use. Lastly, they found that while certain barriers such as an understanding of the technology affected attitude, their perceived ease of use and perceived usefulness was affected even greater. Therefore, it is hypothesized that individuals with higher levels of education will have an increased perceived ease of use and perceived usefulness of social media.

H1.1: Hotel ownership has effect on perceived ease of use and perceived

usefulness of social media.

H1.2: Age has effect on perceived ease of use and perceived usefulness of social

media.

H1.3: Years of hotel experience has effect on perceived ease of use and perceived

usefulness of social media.

H1.4: Level of education has effect on perceived ease of use and perceived

usefulness of social media.

Internal Variables − Technology Readiness Index (TRI)

Some researchers have concluded that new information technology would not be accepted fully if there are human factor barriers that are being overlooked (e.g. Hasan,

2003; Ross et al., 1996). Examples of these barriers may include employee job relevance and result demonstrability (or return on investment) (Venkatesh & Davis, 2000).

Therefore, manager’s perceptions of information technology affect adoption and application of information technology in hotels (Lam, Cho & Qu, 2007). The Technology

Readiness Index, or TRI, was developed by Parasuraman (2000) and is used to measure someone’s inclination to use a new technology to achieve a work related, or personal goal. The Technology Readiness Index uses four concepts to measure a person’s readiness of the technology, drivers, optimism and innovativeness; and inhibitors, insecurity and discomfort (Aboelmaged, 2014). Optimism and innovativeness are both positive constructs that show an increase in control, flexibility, and efficiency. Insecurity and discomfort represent negative responses to technology and a feeling of loss of control or being overwhelmed. The stronger a trait, the better the individual fits into one of the groups and the more significantly they will be influenced in the use of new technology

(Walczuch, Lemmink & Streukens, 2007). Parsasuraman (2000) found that individuals who sustain optimism and innovativeness over discomfort and insecurity are more open to using a new technology. Kleijnen et al. (2004) adapted the Technology Readiness

Index into a more specific “Mobile Technology Readiness” scale to examine the intention to use mobile technology to manage their finances. Saade and Kira (2006) stated that emotional factors like anxiety and efficacy are potential determinants of perceived effectiveness of use. In 2011, Moon and Kim added perceived playfulness to the theory and said that the intrinsic motive can affect user’s acceptance of social media. Venkatesh

(2000) argued that the better we understand these factors, the better we can create positive perceived ease of use and perceived usefulness of technology.

Personality has been found to be a leading factor in understanding why people behave the way they do on the internet (Amichai-Hamburger, 2002; Hamburger & Ben-

Artzi, 2000). In their study on the big five personality characteristics (openness, extroversion, conscientiousness, agreeableness, and neuroticism), Devaraj, Easley, and

Crant (2008) found a direct impact on perceived usefulness. It is important to study the use of social networking sites, an information and communications innovation, in the context of how individuals respond to innovations. Hirschman (1980) defined innovativeness as “the desire to seek out the new and different”. Innovativeness has been treated as a personality trait because it is possessed to some degree by all individuals

(Midgley & Dowling, 1993). Innovativeness can be socially influenced and different throughout a person’s life cycle (Hirschman, 1980). Hamburger and Ben-Artzi (2000) concluded that the extraversion and neuroticism (emotional stability) were related to use of different internet services. McElroy et al. (2007) controlled for computer anxiety and self-efficacy in their study which removed the effect of extraversion on internet use.

However, like other studies, Svensdon et al., (2013) implemented no such controls and utilized a web based questionnaire in their study of personality trait’s influence on internet use which may have created a bias towards low computer anxiety and high computer self-efficacy.

Some researchers have suggested that the role of Technology Readiness may be minor in explaining their intention to use (e.g., Liljander et al., 2006) compared to the

Technology Acceptance Model but it is nonetheless just as important for this research.

For the purposes of this study, TRI variables, optimism, innovativeness, discomfort and

44 insecurity will be used as internal variables. We contend that the technology readiness index is a better model for the present study to predict individual’s attitudes and perceptions toward social media than alternate models such as the big five personality dimensions (Barrick & Mount, 1991) because this study focuses on social media use in a work environment. The big five personality dimensions focus on a person’s innermost feelings and traits whereas the technology readiness index allows for a complete overview of a person’s traits without becoming too complicated. Furthermore, the majority of current research on related topics has utilized the technology readiness index and the technology acceptance model over any other (e.g. Aboelmaged, 2014; Adams,

Nelson, & Todd, 1992; Godoe and Johansen, 2012; Lee, Xiong, & Hu, 2012; Moon &

Kim, 2001; Morris & Venkatesh, 2000).

Perceived Ease of Use

Perceived ease of use can be attributed to confidence (i.e., self-efficacy) in using technology. Self-efficacy has been shown to associate with a person’s technology acceptance (Compeau & Higgins, 1995). Computer self-efficacy refers to how an individual perceives their ability to use a computer to complete a task successfully

(Bandura, 1986). The concept of computer self-efficacy has been shown across a large number of studies to be strongly related to subsequent technology-specific performance

(e.g., Chung, Lee, & Kim, 2014; Huffman, Whetten, & Huffman, 2013; Marakas, Yi, &

Johnson 1998). When an individual has positive social media self-efficacy, it will create a positive disposition which will affect their attitudes toward social media (Bradley &

McDonald, 2012). Alternately, when an individual is uncomfortable or insecure of their use of social media, this creates a negative attitude.

Older individuals tend to perceive a reduction in their own cognitive capabilities to learn (Hertzog & Hultsch, 2000) and have lower perceptions of self-efficacy with regard to cognitive functioning (Bandura, 1997). Thus, since many older individuals have limited experience using computers and social media, it is likely that they have self- efficacy concerns related to learning how to use social media. Marakas, Yi, and Johnson

(1998) argued that computer self-efficacy not only affects an individual’s perceptions of their ability to use information technology but also of their intention towards future use of the technology. Therefore, by examining manager’s technology self-efficacy, otherwise known as perceived ease of use, this research will be able to better predict their intention to use or even actual implement social media in their property. Both the number and the diversity (age, gender, etc.) of people utilizing social media are increasing every day.

Pew Research Center (Duggan et al., 2015) points out, the use of Facebook and LinkedIn by adults aged 50+ grew by 14 percent between 2013 and 2014. Similarly, 71% of internet using American adults use Facebook and while usage among seniors continues to increase, 56% of internet users ages 65 and older, now use Facebook; up from 45% who did so in late 2013 (Duggan et al., 2015). The growing diversity of people signing up with social media suggests that it should be relatively easy to create an account and begin using. If perceived ease of use is the degree to which the social media site is free of effort, perceived usefulness maintains the ability in which the user may accomplish their social-media-related needs (Rauniar et al., 2014). Most studies about TAM assume also

46 that perceived ease of use is directly linked to perceived usefulness (Davis, 1989; Godoe

& Johansen, 2012; Nysveen et al., 2005a, b).

H2.1 Technology readiness is related to manager’s perceived return on investment

of social media.

H2.2 Technology readiness is related to manager’s perceived usefulness of social

media.

H2.3 Technology readiness is related to manager’s perceived ease of use of social

media.

Perceived Usefulness to Hotel Operations and Return on Investment

In a study on bloggers and their intentions to use, “Social Media Release”, an online public relations tool, (Steyn et al., 2010) exchanged the word usefulness with effectiveness to measure a blogger’s perception of success with the tool. Absorption of information was found to play an important role as a precursor to perceived usefulness in a study on on-line learning (Saadé & Bahli, 2005). Performance improvement can also be considered an important part of the usefulness perception. As the users perceive that the system improves their performance, they accordingly may intend to use the system.

Further, the significant effect of perceived usefulness on behavioral intention to use is confirmed by many studies (Lee et al., 2009; Li, Duan, Fu, & Alford, 2011; Saade et al.,

2007). Results from a survey of over 540 blue-collar workers and their intention to use a web-based learning system show that behavioral intention to use that system is directly explained by perceived usefulness (Caliser et al, 2014). It was thought that for that particular demographic, workers may be more willing to use the web-based learning

47 system if they expect that the information and the services provided by the system will improve their job performance. Roca and Gagne (2008) have found that perceived usefulness is the strongest predictor of intention to continue e-learning among workers of four international agencies of the United Nations. Social media has changed how businesses interact with their customers; they can join in on conversations and interact with the virtual community at any time. With social media’s exponential growth, businesses are now able to speak with their customers, as opposed to earlier marketing efforts where businesses talked at their customers (Mills, 2012).

The travel and tourism industry has not ignored the importance of Web 2.0 as most businesses have now become part of the conversation; setting up their own social networking site profiles and acknowledging the importance of online reviews to help better their company and services. However, with budget restrictions and organizational structure in place, general managers may have difficulty justifying the need for online reputation management unless a clear ROI can be defined. There have been many proposed methods of measuring ROI in social media in the past but many have been quickly dismissed as unworkable (Fisher, 2009). While traditional ROI has been well defined in the hospitality industry for many years, social media ROI is relatively new.

This matters not only to a hotel’s financial bottom line and operational and marketing efforts, but also to general managers and hoteliers who have only been recently introduced to online reputation management (Fisher, 2009).

In an industry where the consumer is not given an opportunity to test drive a product, hotels have one shot to please their guests and because travel can often be a

48 luxury no matter the nightly room rate, consumers are making an effort to make a more informed decision that best suits their needs and consumers are turning to online review and social networking sites to aid in their decision making process (Anderson, 2012;

Hudson & Thal, 2013; Leung & Bai, 2013; McCarthy, Stock, & Verma, 2010). Over the past decade, social media has exploded with its spreadability, variability, and content; social networking sites have become a part of our everyday lives. This has come to be known as Web 2.0, a shift from static web pages to an increased amount of user generated content and social networking. Social media is used to not only reach existing customers but to build new relationships (Mills, 2012). The question that many hotels still ask is how can they get an average person who is on social networks to choose to stay at their hotel, and how can their hotel maintain a positive online relationship with that customer

(McKay, 2010)? Attention to the little things can be the difference between a customer’s intention to make a recommendation and he/she actually making one (McKay, 2010).

The issue of finding a viable formula for social networking return on investment is being examined by numerous studies (e.g., Gunelius, 2012) but for many hotels, they may not only wish to have a monetary return on investment, rather, they want to be able to show their consumers a better experience (McKay, 2010). There are several traditional ways for businesses to define return on investment (ROI). One is simply dividing net profit by net worth (Entrepreneur, 2015). Return on investment in a hotel is a standardized way for hotels to justify whether an investment in anything reaps a valuable enough financial result. The idea that general managers can focus solely on their return on investment is no longer existent. Together, return on impression, return on

49 engagement, return on opportunity, and return on objectives give the customers a clearer picture of how the firm’s marketing initiatives are performing than return on investment offers alone (Avectra, 2012; Alston, 2009). Today, focusing on traditional return on investment is not enough (Gunelius, 2012). With the transparency of the industry, return on investment is based on many other factors. According to Noone, McGuire, and Rohlfs

(2011), hotel operators are concerned with showing returns on investment on social media programs. This is not an easy task; for example, showing the impact of sentiment on average daily rates. It requires each organization to develop its own methodology.

Morgan (2009) stated that the reason why it is difficult for companies to calculate their social media return on investment actually has nothing to do with social media. It has to do with companies and top managers not knowing the exact value of their customers. Social media is not about sales, market share, or profit margins and it is not company or brand-centric (Fisher, 2009). Peppers and Roger’s (2005) research into mass marketing questioned the role of the consumer. They found that in the modern digital age, consumers are more like agents who actively engage with an organization about their needs and desires. The traditional role of mass marketing was to increase a business’ market share and to sell more products (Peppers & Roger, 1993). However, if this is the sole end goal or a business, the homogeneous message of mass marketing becomes lost on consumers with differing tastes. Social media is an important shift as it summarizes the importance of interaction between the customer and the community (Universal,

2008). As such, the idea shows a collective impact on the media platform. A newer, more modern goal of marketing is to respond to an existing consumer’s needs and

50 desires, but also, to expand the horizons of the consumer base (Peppers & Roger, 1993).

Social networking is about creating relationships, communicating with readers, building a following, and connecting with an online audience (Castells, 2013; Jenkins, Ford, &

Green, 2013; Seraj, 2012). If a business treats social networking like social media, they could come off as someone using a bullhorn. It is important to listen as much as talk with social networking (Burke, 2013). This means the input provided needs to be used for business development, just as much as building a name. Studies have found that smartphones can mediate both the behavioral and psychological dimensions of the touristic experience by facilitating information search, information processing, and information sharing, by enabling a traveler to learn about new travel opportunities and get to know better a destination, and by sharing photos and other ‘social’ activities at any time during the trip (Tussyadiah & Fasenmaier, 2009). This is a means for developing a name for a hotel as well.

This study aims to provide a meaningful discussion and to better re-examine what return on investment means to hotel companies from a marketing perspective. Specific to this study, returns on investments are return on impression, return on engagement, and brand supporting behavior. Impression, engagement, and brand supporting behavior all contribute to creating loyal guests, or brand advocates. Loyal guests are incredibly important as studies have shown they can spend 50% more nights at the hotel(s) or with the brand(s) they support (Voorhees, McCall & Carroll, 2014). This loyalty also influences other consumers as the majority of internet users trust electronic word of mouth and user generated content more than brand advertisements (Cheong & Morrison,

2008). In the past, ROI has been defined for online advertising, but experts wonder if those same parameters can be applied to social media. Older ROI definitions include unique visitors (or number of visitors), page views, and cost per click where social media tends to focus on a more qualitative interaction with the consumer (Fisher, 2009).

Attempting to assign a financial return on social media efforts means trying to assign a numerical quantity to human interaction (Uitz, 2012), which may not encompass all the social media ROI is. Modern marketers are not looking at the traditional form of return on investment; they are looking at their efforts for return on impressions, return on engagement and opportunity to promote their brand (Gunelius, 2012). For example, the flow of customer opinions and reviews on social media sites about a product or service represents a stream of knowledge that can be extremely influential (Heuer, 2012). Return on impressions typically can be defined as how many people see the ad or post, or how many times it appears on a screen (Uitz, 2012). By appearing on more screens, a hotel can reach a bigger and broader audience thus creating more brand awareness. This in turn can encourage more users to comment, like, share, and engage (Fisher, 2011).

Return on engagement is critical to examine as the electronic word of mouth continues online by a company’s followers and can make or break a marketing strategy. How individuals respond and interact, or engage with a marketing initiative is a viable method at evaluating social networking postings. Lastly, treating brand awareness as a modern day return on investment measurement can be considered invaluable. Brand awareness and brand support may not lead to one individual committing to a purchasing decision but it could lead to them discussing that business on and offline (Gunelius, 2012). Positive

52 word of mouth and electronic word of mouth from a peer is more trustworthy to consumers than brand advertising (Cox et.al, 2009). Return on impression, return on engagement, and brand awareness can assist social media professionals gain a clearer picture of their efforts. Focusing on only traditional return on investment is not enough with Web 2.0. It is because when businesses fail to engage their followers, they fail to take advantage of all of the capabilities social media has to offer. Customers are likely to do more to help a company succeed if they know that a company is committed through words and actions to increasing the “value” for the customer, the company, and the market (Kanter, 2011). These values are supported by online engagement that provides efficient and consistent communication. By valuing these types of online interactions, a hotel could win the support, positive word of mouth or electronic word of mouth, and wallets of customers (Heuer, 2012).

Perceived usefulness is seen as the impact a technology has on achievement of a work related task or goal (Karahanna & Straub, 1999). A few goals of a typical hotel manager, among others are to increase customer satisfaction and increase brand awareness (Skogland & Siguaw, 2004; Tepeci, 1999). Should a technology make those goals more attainable, it is seen as providing a type of return on investment (Roberts et al., 2005). Managers prefer projects that yield measurable short term returns (Baysinger

& Hoskisson, 1989). Therefore, if social media is observed as being able to assist a manager reach his or her goals, financial or otherwise, its return on investment would be seen as valuable.

H3: Perceived ease of use of social media is related to perceived usefulness and

perceived return on investment.

Attitude toward Using

The attitude of using the system was hypothesized to be the most important determinant of whether the user will use technology (Morris & Venkatesh, 2000; Taylor

& Todd, 1995). Attitude toward behavior refers to “the degree to which a person has a favorable or unfavorable evaluation or appraisal of the behavior in question” (Ajzen,

1991, p. 188). In a technology or social media context, attitude toward the behavior is an individual’s assessment of the pros and cons of using the new technology. Over the years, other researchers have proposed additions to the technology acceptance model and it is considered one of the most cited theories when it comes to research that deals with the user acceptance of technology. The technology acceptance model is based on the theory of reasoned action (Ajzen, 1985). This suggests that actual behavior intention is based on the attitude toward the system. Businesses adopt and implement new technologies in order to improve efficiency and effectiveness of the organization’s efforts.

Senior hotel executives are aware of the importance of information technology in improving customer service and enhancing operational effectiveness (Kim et al., 2015;

Lamelas & Filipe, 2011; Law & Jogaratnam, 2005) as well as improving guest satisfaction (Mayock, 2012; Proserpio & Zervas, 2014; Van Hoof et al., 1996). Typically within a hotel, a general manager is the decision maker when it comes to adopting and implementing these new technologies. Should a decision maker not believe or understand the value or importance of the technology, there is little chance this

54 technology will be utilized within the hotel (Godoe & Johansen, 2012; HSMAI

Foundation, 2014; van Riel & Fombrun, 2007). Consequently, hotel managers with positive perspectives about the operational benefits information technology has on their hotel can create (unseen) pressures on operational employees to utilize information technology successfully (Karatepe, 2013; Lam, Cho, & Qu, 2007).

Sas, Dix, Hart, and Su (2009) found that people’s most memorable experiences with Facebook are all about positive emotion, particularly when interacting and connecting with people and enjoying themselves. This theory could potentially be extended to other social media which is why the model will be examined in this study.

Lee, Xiong, and Hu (2011) also found that perceived enjoyment had a direct correlation with perceived ease of use. While in the past, these theories have been used to research how consumers (or guests, in the hospitality industry) interact with social media, these ideas could be applied to an executive management team at a hotel and how their perceived ease of use and perceived usefulness affects if and how their hotel participates in social media. While most studies focus on the positive emotions (e.g., enjoyment) of the users, little attention has been paid to their negative emotions. This study will examine both the positive and negative dispositions of hotel managers which will create a more thorough understanding of their attitudes, which may or may not hinder them from implementing social media.

Attitude toward an object refers to a person’s affective evaluation of a specific object and attitude toward behavior refers to a person’s evaluation of a specified behavior involving the object (Davis, 1993; Fazio & Olson, 2014). Any change in beliefs or

55 attitudes will likely have a corresponding impact on, and may even reverse users' continued intention to use an object or behave (Bhattacherjee & Premkumar, 2004;

Krasnova, 2015). Yang and Yoo (2004) closely examined both the affective and the cognitive dimensions of attitude on information systems use utilizing the technology acceptance model. While many of the earlier findings in the model’s research were confirmed, the role of affective (emotional) attitude between cognitive (thoughts and beliefs) attitude with information system use was not supported. Yang and Yoo (2004) elaborate that while cognitive attitude was found to be an important variable when examining information system use, affective attitude was not, which coordinates with

Riff, Lacy, & Fico’s 2014 findings. Riff et al. (2014) suggest attitude deserves more attention in information system research for its considerable influence on the individual and organizational usage of information systems.

H4.1: Perceived usefulness of social media is related to attitude toward using

social media.

H4.2: Perceived return on investment is related to attitude toward using social

media.

H4.3: Perceived ease of use is related to attitude toward using social media.

Proposed Model

Social media can directly influence social behavior. Biocca et al. (2003) proposed that a detailed theory and measure of social presence could contribute to our understanding and explanation of social behavior in mediated environments. It could also allow researchers to predict and measure differences among media interfaces, and

56 guide the design of new social environments and interfaces. This sets the stage to determine how far technology influences the hotel industry, and how concerned a general manager should really be. Social media is about the instant ability to communicate with others on a platform that holds no limitations (Tardanico, 2012). Social media networking is an electronic word-of-mouth which allows for policy makers to develop promising regulations that help consumers and brands interact in a reciprocal manner and establish a long-term relationship (Chu & Kim, 2011). Social media is perceived by consumers as a more trustworthy source of information regarding products and services than corporate-sponsored communications transmitted via the traditional elements of the promotion mix (Mangold & Faulds, 2009). What really matters are the opinions, voices, and experiences that people are sharing (Owyang, 2007).

While many studies have incorporated the technology acceptance model to examine user intentions (King & He, 2006; Lai & Li, 2005; Lee, Xiong & Hu, 2012;

Saade, Nebebe & Tan, 2007), very few have considered actual use. The current study is also unique in utilizing the technology acceptance model to look at both hotels, and the new technology of social media. With a direct link to business success (Mohanty, 2012) this research is intended to benefit the hotel industry as a whole. As shown in Figure 2, the proposed model for this study includes external variables and internal variables which have an effect on perceived ease of use, perceived usefulness, return on investment, attitudes, and actual use.

Figure 3: Proposed Model

H5.1: External variables are related to actual social media use.

H5.2: Internal variables are related to actual social media use.

H5.3: Perceived usefulness is related to actual social media use.

H5.4: Return on investment is related to actual social media use

H5.5: Perceived ease of use is related to actual social media use

H5.6: Attitude is related to actual social media use.

Challenges and Factors Which Drive Change

If a hotel is not engaging in any type of social media, they could be missing out on a large digital marketing opportunity. According to Wilson (2009), there are five main fears management has in regard to the use of social networking: (a) perceived loss in staff productivity; (b) data leakage from staff gossiping freely in an open environment; (c)

58 malware and phishing scams by cyber crooks; (d) open access potentially offered to the company servers by lax and outdated attitudes towards passwords; and (e) damage to a company’s reputation. While social media engagement is necessary to a business for branding and communication, it can also work against a business if used inappropriately

(Coombs & Holladay, 2012; Kietzmann et al., 2012). However, a social media policy can be produced to educate and provide better understanding for their employees to keep within certain parameters and implications of their participation. In an industry where success can rely solely on recommendations from others, maintaining a positive hotel reputation is vital. In the event of an unfortunate situation, social media can serve as a catalyst to turn the situation into an opportunity for a business to extend their services and go the extra mile to reverse any negative feelings. Reputation management has become an important aspect of online activity for businesses (González-Herrero & Smith, 2008).

In the crisis phase, Gonzalez-Herrero and Smith (2008) suggested using the internet as a third-party information site such as a blog; creating interactive tools such as mini-surveys to understand stakeholders' perceptions; using chat tools to foster dialogues; and having

CEOs personally address the stakeholders. This requires social media to allow communication and gather the information. Experiences with programming and computer graphics applications, which are difficult and unfamiliar task experiences, have the strongest effects on computer science and engineering beliefs (Hasan, 2003).

Managers of hotels can fear their inexperience and lack of exposure with technology and social media. While this inexperience can be a source of hindrance, this can serve as a motivation to keep up with such factors that affect their hotel

RQ4.1: What are the most pressing challenges affecting actual social media use in

hotels?

RQ4.2: What are the factors that drive changes within the organization in the

utilization of social media?

According to McCarthy et al. (2010), on one hand social media has created a new distribution channel and opened a deep well for marketing research. On the other, however, social media has changed the way travelers will determine where they will stay

– particularly leisure travelers (McCarthy et al., 2010). The representation of the social media phenomenon will significantly impact a company’s sales, survival, and reputation yet many executives ignore this form of media because they do not understand what it is, the various forms it can take, and how to engage with it and learn (Kietzmann et al.,

2011). General Managers fear the reputation that social media can affect their hotel, based on the fact that they do not know the true expansion of the outlet. Social media and its various tools have dramatically shifted the way consumers experience and interact with brands online,” said Randall Rothenberg, President and CEO of the Interactive

Advertising Bureau (IAB, 2009). This is especially true in the mobile world. Consumers can leave a review about their experience with a few quick taps on their smartphone.

Social media usage is now standard practice in our daily lives—almost half (47%) of smartphone owners visit social networks every day Nielsen (2014).

CHAPTER III

RESEARCH METHODOLOGY

This chapter will provide research objectives, Kent State University Internal

Review Board approval, a description of the sample used, and survey design development. It will also include information on survey procedure, data collection, and finally data analysis.

Human Subjects Review

The researcher in this study has completed the human subjects training and is certified by the Internal Review Board (IRB) of Kent State University. The KSU

Committee on the Use of Human Subjects in Research approved the proposal application for this study on June 17, 2015. The research contained minimal risk to human subjects which will be qualified under Level one of Human subject.

Sample and Procedure

The sample surveyed in this study was a convenience sample. All surveyed individuals have the role of managing daily operations in a branded or independent hotel as defined by STR Global, a trusted hotel resource (STR Global). The data was collected during summer 2015 through an email web-based survey. The survey was administered to individuals who may have different job titles from general manager to director of marketing, revenue manager, director of sales, or others (e.g., front office managers, catering and sales). Depending on the organizational structure, there were a variety of

respondent positions. This study looked at both independent and branded hotels as well as franchised properties. The original hotels to be examined in this study were in Ohio

only but due to difficulty in obtaining survey responses, the survey was opened up via snowball sampling to the entire United States.

Participants were contacted ahead of time and informed of the research purposes of the current study. They were asked for their consent in this voluntary study. A minimum of one manager per hotel was asked to complete the survey. Participants were emailed a link to an online survey via Qualtrics. A follow up email was sent out three weeks later after distributing the survey and one week before the deadline to remind participants to complete the survey.

Instrument Design

The survey was comprised of three sections; section one contained three scales.

First, attitude was assessed by question items developed by Harvard Business Review

(2010). All nine items were measured on a seven-point Likert scale ranging from 1

(strongly disagree) to 7 (strongly agree). The scale measured the manager’s current attitude toward social media and asks for the participant to rate the extent to which they agree with the nine statements about social media within their organization. Sample items included: “the use of social media by our organization will grow significantly over the next five years;” “until we are able to clearly measure the impact of social media, it will not be taken seriously in our organization;” and “using social media is an important component of our overall marketing strategy.”

The second question items surveyed their technology readiness index

(Parasuraman & Colby, 2015), which measures their optimism, innovativeness, discomfort, and insecurity with four questions for each factor creating a total of 16 questions related to TRI. These were used for their internal variables. Technology readiness was assessed based on a seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree).

In 2000 Venkatesh and Davis took their original TAM design and trimmed it down to only focus on the most important and relevant aspects of technology acceptance.

Known as TAM2, most of these items were used with a slight fine tuning of wording to adjust to the present study; the phrase “the system” was changed to “social media”. The question pertaining to the technology acceptance of the manager was based on survey question in Venkatesh and Davis’ 2000 theoretical extension of the technology acceptance model. Specifically, eight questions were used from Venkatesh and Davis’ study pertaining to perceived ease of use (four questions) and perceived usefulness (four questions) of social media. These questions were each ranked on a seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree).

Section two contained questions about actual use, return on investment, challenges, and factors that drive changes. First, two questions pertaining to actual use were adapted from Harvard Business Review (2010). The first question inquired as to if the hotel has someone who monitors and responds to online reviews and if the hotel actively engages on social networks. These items had yes or no response options. Next, the survey asks about participation on eight specific social networks. These specific

channels were chosen because of their current popularity in the hospitality industry for customer interaction and online reviews (Benea, 2014; Nadda, Dadwal, Mulindwa, &

Vieira, 2015). This aids in discovering how extensive respondent’s online efforts are.

The third section contains a 12-item question pertaining to return on investment which was adapted from Harvard Business Review (2010). Items were ranked on a six-point

Likert scale ranging from 1 (not at all important) to 6 (very important). The question pertaining to challenges contained 14 items to be ranked on a five-point Likert scale ranging from 1 (not at all challenging) to 5 (extremely challenging). The questions were adopting from Harvard Business Review (2010) and Wilson’s 2009 work on the five main fears managers associate with social networking. Sample items include: damage to company’s reputation; perceived loss in staff productivity; operational integration; and linking social media activities to an impact on company financials or ROI. Lastly, managers would ask which of seven factor(s) would drive change within their organization in terms of social media usage. Respondents were asked to choose up to three. Factors were utilized from previous research (Alston, 2009; Anderson, 2012;

Benea, 2012; Fisher, 2009; Hotel News Now, 2014; Kaplan & Haenlein, 2010).

Examples of the items were: increased budget; knowledgeable employee; management acceptance; customer encouragement; and available training. Results from this question help back up research objective three and provide managerial implication.

Section three contained seven questions about demographics, hotel information, and managers’ career background information (Gregory, 2006 & Kimes, 2010).

Background information inquired as to years of work experience in the industry, age,

level of education. The organizational structure of the hotel was asked to find out if it was owned, managed, franchised, or otherwise operated. The survey also asked if they manage a branded or unbranded property. Lastly, the respondent’s current title (e.g.

General Manager, Director of Sales) was asked as a purely demographical question.

Participants took approximately 15 minutes to complete the survey.

Data Collection

A web based survey was sent in an email to participants. Web survey is used for the fast response time, high response rate, and low cost (Cobanoglu, Warde, & Moreo

2001).

Data Analysis

The collected data was analyzed using the following methods. First, a description analysis was used to summarize the participants’ demographic and job background profiles. Second, Cronbach alpha coefficient was computed for the internal consistency reliability of scales. Third, an exploratory factor analysis was conducted to examine the number of dimensions within the main variables (i.e., ROI, pressing challenges, driving factors). Forth, an independent samples t test and a series of one-way analysis of variance (ANOVA) were performed to examine whether the variables differ based on demographic and hotel background information (e.g., age, level of education, years of hotel experience, branded and independently owned hotel, and type of hotel ownership).

Fifth, a series of simple linear regressions and a logistic regression were conducted to determine if the constructs (perceived ease of use, perceived usefulness, internal or

external variables, or attitude) predict a manager’s implementation of social media use in the hotel.

CHAPTER IV

RESULTS

This study was designed to investigate hotel manager’s attitudes toward social media and how internal and external variables, perceived usefulness, perceived ease of use, social media return on investment, and attitude affect actual social media use. All of the variables and actual use were surveyed through online Qualtrics surveys (Appendix

B). Approximately 450 e-mails were sent out by the researcher. An additional 20 surveys were sent out via snowball sampling. A total of 97 surveys were returned which represents a response rate of 20%.

Demographic Characteristics and Descriptive Statistics

Descriptive statistics and frequency distributions were employed for analysis of the participants’ characteristics. Results are shown in Table 1. Of the respondents that answered the age question, most respondents were 31-35 (n = 10) and 41 to 45 (n = 10).

Of the respondents that answered how many years they have been working in the hotel industry, 26% had been working for only 1-5 years. Of the 63 respondents who answered, 60% (n = 38) achieved a Bachelor’s Degree as their highest level of education and only seven completed a Master’s Degree. In terms of job title, the general manager

(n = 27) accounts for the majority of the respondents and eleven (41%) of those general managers oversee the daily management duties of (at least) three properties. In total,

67% of all respondents oversee one single property, 26% oversee two properties, and

17% oversee three. These hotels added up to a total of 92 and of those hotels, 78% were

branded and 22% were independent. The most frequent ownership style was a franchised property (n = 47, 51%), followed closely by franchisor with management contract (n =

31, 34%).

Table 1. Demographic Characteristics of Respondents

Characteristic Frequency Percentage Age range 20-25 8 13.6 26-30 9 15.3 31-35 10 16.9 36-40 6 10.2 41-45 10 16.9 46-50 3 5.1 51-55 6 10.2 56 and up 7 11.9 Job Title General Manager/DOP 27 42.9 Owner/Operator 3 4.8 Asst. GM/FOM 5 7.9 Revenue Mgr/Dir. Brand Sprt/Regional Mgr 5 7.9 Sales/Marketing Manager 10 15.9 Social Media Manager 10 15.9 Other 3 4.8 Highest level of education High School 4 6.3 Some College 9 14.3 Business College 1 1.6 Associate’s Degree 4 6.3 Bachelor’s Degree 38 60.3 Master’s Degree 7 11.1 Years working in industry 1-5 16 26.2 6-10 11 18.0 11-15 8 13.1 16-20 5 8.2 21-25 7 11.5 26-30 5 8.2 31 and up 9 14.8 Type of Hotel Branded 72 78.3 Independent 20 21.7 Note. Other = administrative assistant (n = 1), buffet assistant manager (n = 1), reservations (n = 1); Social Media Manager = social media manager (n = 4), concierge and social media champion (n = 1), online community & brand manager (n = 1), online marketing manager (n = 1), public relation, advertising, graphic design, social media (n = 1), sales & catering coordinator/social media champion (n = 1)

Reliability of Scales

Cronbach alpha reliability coefficient (α) was acquired to measure the internal consistent reliability of each scale used. The value of coefficient alpha for the scale of technology readiness index (TRI) was 0.731 and the Cronbach’s Alpha for its subscales of optimism, innovative, insecurity, discomfort were 0.845, 0.866, 0.708, and 0.714 respectfully. The value coefficient alpha for return on investment (ROI) scale measured at 0.902 and the Cronbach’s Alpha for its subscales of engagement, brand promotion, and impression were 0.873, 0.823, and 0.741 respectfully. The proposed research partially tested the technology acceptant model (TAM) with two variables were included for analysis. Value coefficient for the subscales of TAM measuring perceived usefulness and ease of use were 0.945 and 0.812 respectfully. The value coefficient alpha for scale of pressing challenges was 0.938. It’s subscales of organizational, operational, and financial had Cronbach’s Alpha of 0.913, 0.857, and 0.805 respectfully. The value coefficient for the scale measuring actual use is 0.797. The value coefficient for the overall attitudes was 0.69 which is slightly below the acceptable value specified by Cortina, 1993. This could be due to the wording of some items that were not perceived consistently among participants or the number of items in the scale. Apart from the attitudes scale, the remaineder of the scales used in this research can be regarded as reliable since values above the cut-off value (α ≥ .70) are generally considered sufficient for research purposes

(Cortina, 1993).

Table 2. Summary Descriptive Statistics of Seven Variables among Hotel Managers

Measurement Reliability Mean SD coefficient (α) Attitude .697 5.580 .839 Technology readiness .731 4.191 .715 Return on investment .902 6.137 .725 Usefulness .945 4.475 1.588 Ease of use .812 4.924 .1.224 Challenges .938 2.484 .884 Actual use .797 2.913 1.405

Factor Analysis

Factor analysis identified the underlying dimensions in the data by condensing the specified variables. The Kaiser-Meyer-Olkin Measure of sampling adequacy was done to confirm the adequateness for factor analysis (Lee & Sparks, 2007, pg 509). The Kaiser-

Meyer-Olkin Measure for technology readiness index (TRI) was 0.705 which exceeds the recommended value of 0.6 to complete a successful factor analysis (Lee & Sparks, 2007).

Bartlett’s Test of Sphericity reached a statistical significance of (p = 0.000) supporting the factorability of the rotated component matrix as well as producing a chi-square of

503.312 and (df =120). The 16 items for technology readiness were used in a factor analysis using principal component analysis with varimax rotation to reduce the variables to a smaller number of underlying factors. All items were fit for evaluation with 0.4 loading or higher (Lee & Sparks, 2007). These factors were tested for reliability using

Cronbach’s alpha. Four factors were extracted from technology readiness (Table 3).

Table 3. Total Variance of Technology Readiness Explained

Initial Eigenvalues Extraction Sums of Squared Loadings Component Total % of Variance Cumulative % Total % of Variance Cumulative % 1 4.20 25.75 25.751 4.120 25.751 25.751 2 3.213 20.083 45.834 3.213 20.083 45.834 3 2.020 12.625 58.459 2.020 12.625 58.459 4 1.096 6.851 65.310 1.096 6.851 65.310 5 .949 5.928 71.238 6 .792 4.948 76.186 7 .725 4.530 80.717 8 .640 3.999 84.716 9 .538 3.361 88.077 10 .460 2.873 90.950 11 .384 2.399 93.349 12 .327 2.044 95.393 13 .234 1.465 96.859 14 .194 1.219 98.077 15 .173 1.082 99.159 16 .135 .841 100.000

The Kaiser-Meyer-Olkin Measure for return on investment was 0.826 which exceeds the recommended value of 0.6 to complete a successful factor analysis (Lee &

Sparks, 2007). Bartlett’s Test of Sphericity reached a statistical significance of (p =

0.000) supporting the factorability of the rotated component matrix as well as producing a

Chi-square of 479.492 and (df =66). The 12 items for the return on investment were used in a factor analysis using principal component analysis with varimax rotation to reduce the variables to a smaller number of underlying factors. All items were fit for evaluation with 0.4 loading or higher (Lee & Sparks, 2007). These factors were tested for reliability using Cronbach’s alpha. Three factors were extracted from return on investment and were named 1) engagement, 2) brand promotion, and 3) impression (Table 3).

Table 4. Return on Investment of Social Media

Component Scale Variables in Component Factor Loading Reliability 1 Engagement Build brand/property loyalty .799 .873 Create new customers .793 Create brand/property awareness .775 Share brand/ property information .667 Advertise on social networks .617 Gain customer feedback and insight .586 2 Brand Promotion Have a page on social networking site .833 .823 Provide ways for customer to interact .812 Collect and track reviews .669 Promote brand .586 3 Impression Monitor trends among customers .877 .741 Research new product ideas .730

The Kaiser-Meyer-Olkin Measure for attitudes was 0.719 which exceeds the recommended value of 0.6 to complete a successful factor analysis (Lee & Sparks, 2007).

Bartlett’s Test of Sphericity reached a statistical significance of (p = 0.000) supporting the factorability of the rotated component matrix as well as producing a Chi-square of

281.675 and (df =36). The nine items for attitude were used in a factor analysis using principal component analysis with varimax rotation to reduce the variables to a smaller number of underlying factors. All items were fit for evaluation with 0.4 loading or higher

(Lee & Sparks, 2007). These factors were tested for reliability using Cronbach’s alpha.

Two factors were extracted from attitudes

Lastly, the Kaiser-Meyer-Olkin Measure for pressing challenges was 0.806 which exceeds the recommended value of 0.6 to complete a successful factor analysis (Lee &

Sparks, 2007). Bartlett’s Test of Sphericity reached a statistical significance of (p =

0.000) supporting the factorability of the rotated component matrix as well as producing a

Chi-square of 327.855 and (df =105). The 15 items for challenges were used in a factor analysis using principal component analysis with varimax rotation to reduce the variables

73 to a smaller number of underlying factors. All items were fit for evaluation with 0.4 loading or higher (Lee & Sparks, 2007). These factors were tested for reliability using

Cronbach’s alpha. Three factors were extracted from challenges and were named 1) organizational, 2) operational, and 3) financial (Table 5).

Table 5. Challenges Associated with Actual Social Media Use

Component Scale Variables in Component Factor Loading Reliability 1 Organizational Data leakage from staff gossiping .842 .913 Perceived loss in staff productivity .812 Damage to company’s reputation .795 Other .735 Malware and phishing scams by cyber crooks .712 Open access to company servers by .623 lax attitudes toward passwords Ownership .565

2 Operational Linking social media activities to .827 .857 impact on financials or ROI Getting people in organization to .804 see value of activities Educations staff on how to use .771 Capturing and analyzing online .713 conversation about brand/service Quickly resolving issues raised by .659 social media 3 Financial Cost of social media management .869 .805 Operational integration .837 Finding qualified social media manager .618

Internal and External Variables

Research question one explored how internal and external variables affect managers’ comfort level with social media. A manager’s personal belief, propensity, perception, business mindset/concern toward social media, have direct or indirect influence on their attitudes toward the actual implementation of social media. In specific, technology readiness, technology acceptance, and social media return on investment are included for their effect on actual use. An individual's personality influences the potential

74 acceptance of technology, which is known as the Technology Readiness Index (Godoe &

Johansen, 2012). The overall mean score for TRI is 4.19 (SD = .716).

Table 6. Technology Readiness Mean Ranking

Technology Readiness Mean STD Cronbach’s Alpha 4.19 .716 .731 Factors Mean Ranking Cronbach’s Alpha Discomfort (D) 5.13 1 .714 Innovative (INO) 4.26 2 .866 Optimism (O) 4.11 3 .845 Insecurity (INS) 3.63 4 .708 Highest items Lowest items Items (O and INO) Mean Ranking Mean Ranking TRI7-I keep up with the latest social media developments in 4.83 1 my areas of interest (INO) TRI2-Social media gives me more freedom of mobility (O) 4.53 2 TRI5-Other people come to me for advice on new social 4.20 3 media (INO)

TRI16- In general I am among the first in my circle of friends to acquire new social media when it appears (INO) 3.96 1

TRI4-Social media makes me more productive in my 3.81 2 personal life (O) TRI6-I can usually figure out the new high-tech products 3.20 3 and services without help from others (INO)

Highest items Lowest items Item (D and INS) Mean Ranking Mean Ranking TRI15-I do not feel confident doing business with a place 5.29 1 that can only be reached online (D) TRI14- Social media lowers the quality of relationships by 5.14 2 reducing personal interaction (D) TRI13- Too much social media distracts people to a point 4.96 3 that is harmful (D) TRI9- Social media support lines are not helpful because 3.20 1 they don’t explain things in terms I understand (INS) TRI10- Sometimes, I think that social media systems are not 3.39 2 designed by ordinary people. (D) TRI11-There is no such thing as a manual for a social media 3.57 3 product or service that is written in plain language. (D)

Factors in the table were divided in between optimism and insecurity (as the positive

75 influencers) and discomfort and insecurity (the negative influencers) of TRI. The item with the highest mean of technology readiness was “I do not feel confident doing business with a place that can only be reached online.” This item is a negatively influencing item belonging to the discomfort factor.

Independent Samples t-Test and One Way ANOVA

The second research question proposed in this study was to examine if there is any group differences based on manager’s demographics and background information.

An independent samples t test and a series of one way ANOVAs were conducted to test whether these variables varied among attitude, perceived usefulness, perceived ease of use, challenges, and actual use.

An independent t-test was performed to determine if differences existed between type of hotel (branded or independent) on the seven variables: ease of use, usefulness,

TRI, ROI, challenges, attitude, and actual use. Levene’s test for equality of variances was examined and the assumption of equal variances was satisfied (p > .05) for each variable. The results of Levene’s test found there is a relationship between branded and independent and their perceived ease of use (branded M = 4.91; independent M = 5.05) with a significance of 0.025 (p <.05) and their technology readiness (branded M = 4.17; independent M = 4.12) with a significance of .010 (p <.05). However, perceived ease of use has a t-test value of -0.397 based on 61 degrees of freedom with a two-tailed significance of 0.693 and technology readiness (TRI) had a t-test value of 0.255 based on

61 degrees of freedom with a two-tailed significance of 0.800. Therefore, we fail to reject the null hypothesis that there is no difference between branded and independent

76 hotels and their perceived ease of use and technology readiness.

One-way analysis of variance (ANOVA) was performed to examine the variances among different job titles. Levene’s test of equality of error variances was utilized to generate statistics to test the assumption of homogeneity of variance for the individual variables. This study met the assumptions for homogeneity of variance. There was a statistically significant difference on manager’s perception of usefulness as determined by one-way ANOVA (F (6,56) = 4.35, p = .001) based on managers’ job titles. An LSD post-hoc test was conducted and revealed the different perception of usefulness was found between (1) front office and assistant managers and general manager/director operations (p = .002), owner/operator (p = .023), and director of marketing, sales and sales coordinator (p = .002) and those categorized as social media manager’s (p =.000).

Those social media managers were also found significant different from general manager/director of operations (p = .001), revenue manager/regional manager, director of brand support (p =.006), other administrative key personnel (p = .024). The results suggest that an employee’s position at a hotel could influence their perceived usefulness of social media.

There was a statistically significant difference between on manager’s perception of ease of use as determined by one-way ANOVA (F (6, 54) = 2.98, p = .014) based on managers’ work experiences. The LSD post hoc test was followed up and revealed the differences were found among the following groups: managers who worked 21 to 25 years were different from those worked one to five years (p =.004), six to ten years (p =

.004), and 11 to 15 years (p = .030). In addition, managers who worked 31 years and

77 more were found different from those who worked one to five years (p = .013) and six to ten years (p = .013).

There was a statistically significant difference between on manager’s perception of ease of use, F (7, 51) = 2.55, p = .025 as well as external challenges, F (7, 51) = 2.34, p = .038, based on managers’ age. In terms of age, the LSD post hoc test revealed the differences were found between managers age between 20 to 25 years old with other groups: 36 to 40 (p =.005), 46 to 50 (p = .010), 51 to 55 (p = .007), and 56 and up (p =

.003). In addition, manager with age between 56 and up were found different from those age between 20 to 25 (p = .003) and 26 to 30 (p = .044). In terms of external challenges, managers whose age between 41 to 45 years old were found different from other groups:

36 to 40 (p =.007), 46 to 50 (p = .012), 51 to 55 (p = .030), and 56 and up (p = .033). In addition, manager with age between 26 and 30 were found different from those age between 36 to 40 (p = .017).

There was not significant differences found among managers with different levels of education (p > .05) and worked in different management ownership (p >.05).

Regression

The second research objective in this study was to discover which independent variables had a relationship with the dependent variables, and ultimately, which variable is the most predictive of actual social media use. A series of simple linear regression

(SLR) analyses were computed to determine the predictive power between the variables.

There are four principal assumptions, which rationalize the use of linear regression models for prediction purposes: (a) linear relationship between the independent and

78 dependent variables, (b) independence, (c) homoscedasticity, and (d) normal distribution of the variables which were met by the data.

The first pair of regression with ease of use as the dependent variable and internal and external variables as well as managers’ background and demographic variables as independent variables, it was found that 36.3% of the variability is predicted by the predictors. The identified equation for this relationship is as follows: Y (ease of use) =

5.005 + 0.514 (technology readiness)-.302(external challenges)+.291(type of hotel)-

.064(current position)-.029(age)-.023 (education)-.014(years of working).

The variables explain 24.2% of the variability of ROI. The identified equation for this relationship is: Y (ROI) = 4.563 + -3.27 (type of hotel)+.159(TRI)-

.205(challenge)+.031(job title)+.119 (highest level of education) -.039(years of experience)+.048(age).

The variables explain 37.4% of the variability of usefulness. It was found that

TRI is the strongest predictor of usefulness. The ANOVA tests support the statistical significance of the results (p<.05). The identified equation for this relationship is as follows: Y (usefulness) = -2.194+.517 (TRI)+.011(job title)+.097(highest level of education)-.079(years of experience)+.081(age).

The variables explain 23.1% of the variability of attitude. Perceived usefulness is the only significant predictor of attitude (RQ4, RQ5). The ANOVA tests support the statistical significance of the results (p<.05). The identified equation for this relationship is as follows: Y (attitudes) = 3.356 +.182 (usefulness)+.165(ROI)+.035(ease of use).

Attitude was found to be the most significant predictor of actual use. The

ANOVA tests supports the statistical significance (p=.05) and the identified equation for this relationship is: Y (actual use) = 1.279 + .325 (attitude).

The rest contextual variables explain 53.6% of the variability of actual use. It was found that type of hotel is the strongest predictor of actual use of social media. The

ANOVA tests support the statistical significance of the results (p<.001). The identified equation for this relationship is as follows: Y (actual use) = .060-.597(type of hotel)+.254(age)+.226(highest level of education)+.204(ease of use) -.186

(TRI)+.146(usefulness)+.129(job title)-.122(years of experience)+.111(ROI)+.109(management ownership)-.083(external variables).

Frequencies

Actual channel use data was calculated using frequencies examining specific social networking channels and online review sites.

Table 7. Actual Use Frequency

Channel Use Ranking Never Rarely Sometimes Often All of the Time Most to Least Used Facebook 1 4 5 16 38 1 TripAdvisor 1 1 1 7 55 2 Twitter 10 8 10 7 26 3 Yelp 7 10 14 13 18 4 Instagram 12 11 11 10 16 5 Google+ 14 11 13 11 13 6 YouTube 21 12 18 6 3 7 Pinterest 20 12 19 5 3 8 Other 10 4 5 3 1 9 Note: Other = Periscope (n = 3) online travel agent (OTAs) (n = 3), Vine (n = 1) Tumblr (n = 1) Foursquare (n = 1) LinkedIn (n = 1) other (n = 3)

By combining frequent use (often and all of the time) measures, it was found that those surveyed utilized Facebook more than any other social media.

Return on Investment

Return on investment has an overall mean score of 6.14 (SD = .121).

Table 8. Return on Investment Mean Ranking

Return on investment Mean STD Cronbach’s Alpha 6.14 .121 .902 Factors Mean Ranking Cronbach’s Alpha Brand promotion (B) 6.32 1 .823 Engagement (E) 6.19 2 .873 Impression (I) 5.63 3 .805

Highest items Lowest items Items Mean Ranking Mean Ranking ROI -Monitor trends among customers (I) 8.77 1 ROI - Have a page on social networking 8.12 2 Site (BP) 7.99 3 ROI - Build brand/property loyalty (E)

ROI - Advertise on social networks (E) 6.17 1 ROI -Promote Brand (BP) 5.86 2 ROI - Gain customer feedback and insight (E) 5.86 3

Items considered return on investments of social media were grouped into three factors, brand promotion, engagement, and impression. Table 8 shows the three factors return on investments were categorized into as well as the highest and lowest ranking

ROI items.

Challenges

Pressing challenges has an overall mean score of 2.80 (Std. = .176).

Table 9. Challenge Mean Ranking

Challenges Mean STD Cronbach’s Alpha 2.80 .176 .938 Factors Mean Ranking Cronbach’s Alpha Organizational (OG) 2.84 1 .913 Operational (OP) 2.70 2 .857 Financial (F) 2.26 3 .805

Highest items Lowest items Items Mean Ranking Mean Ranking challenging5-Linking social media activities to an 3.33 1 impact on company financials or ROI (OP) challenging12-Malware and phishing scams by cyber 3.00 2 crooks (OG) challenging7-Educating your staff on how to use 3.00 3 social media (OG) challenging3-Cost of social media management 2.63 1 systems (F) challenging8-Responding to findings from social 2.52 2 media (i.e., quickly resolving/ addressing an issue raised by social media) (OP) challenging1-Finding a qualified social media 2.48 3 manager (F)

The third research objective examined the most pressing challenges managers have in actual social media use in their hotel. Challenges were grouped together into three categories, organizational, operational, and financial with organizational having the highest mean.

Driving Forces

Table 10. Driving Forces in Implementation of Social Media

Item Frequency Percentage Increased budget 33 24% Knowledgeable employee 30 22% Customer encouragement 26 19% Brand support (if applicable) 23 17% Ownership approval 13 9% Management acceptance 10 7%

Respondents were able to choose up to three factors that would drive change the most within the organization in the implementation of social media for managerial implications. Data was summarized using frequencies and the results (Table 10) indicated budget was the top driving force for respondents.

CHAPTER V

DISCUSSION

The main objective of this study was to investigate hotel manager’s current attitudes on social media. The study also sought out to determine which variable affects actual social media attitudes and use in the hotel industry the most as well as what the most pressing challenges and driving force are affecting that use. Manager’s attitudes could be affected by various factors (e.g., internal or external variables). Specifically, some noteworthy discoveries have been made about determinants of hotel manager’s attitudes toward social media.

External Variables

External variables were examined in the survey to see if they offered a significant effect on managers’ perception, propensity, and attitudes towards social media. In response to research question two, hotel type (branded vs. independently own), education, and management ownership were found to have no impact on aforementioned variables.

However, managers’ job titles, work experiences, and age made significant impacts.

First, variable differences among job titles revealed interesting results. Among the survey questions, respondents were asked their job title for demographic reasons. Job titles that were combined were based on daily job responsibility and reporting hierarchy.

For example, social media manager, concierge and social media champion, pr, advertising, graphic design, and social media were grouped together because while the respondents in this segment may have had different responsibilities or titles, they were still responsible for the social media management of their property. This study will use 83 84

social media managers to represent all related positions grouped under this category. In addition, front office and assistant general managers (FOMs) were combined because while they oversee the front of house in a hotel, and supervise employees, they still both directly report to a general manager or director of operations. Lastly, general managers and directors of operations (GMs) were combined as they oversee all daily operations within and hotel and only answer to an owner or management company.

Significance was found between social media managers and GMs, “revenue manager/regional manager,” and “other administrative personnel.” GMs and revenue or regional managers’ main goal for a hotel is to succeed financially, stay in operation, stay competitive, and stay successful. People with these job titles may demand a clear and precise ROI for social media management that warrants the need for dedicated social media management. In addition revenue managers utilize social media to optimize pricing structure on OTAs, and increase or maintain bookings (Noone et al., 2011). As is their job to do so, social media managers find social media to be useful in the workplace and the reasons behind this could be non-monetary ROI based thus creating a significant difference in perceptions of usefulness. In addition, while only limited number of respondents were categorized under other administrative personnel, these individuals do not have an operational management duty and may not feel that their job or guests they are serving are affected by social media efforts thereby not perceiving usefulness of social media.

Significant differences were found in percevied usefulness between front office manager and assistant general manager (FOM) and “general manager/director

operations,” “ owner/operator,” “director of marketing, sales and sales coordinator,”

(sales personnel) and “social media managers”. It is not surprising that social media managers find the practice of social media management to be useful, as the very essence of their job is based on social media acceptance and use. However, reasons for this significance could be based on job duties. FOMs are face to face with hotel guests every day (Riley, 2014). Their responsibility is based on operations within the hotel as well as taking care of the day to day responsibilities hotel guests brings (Karatepe, 2014). With these duties on the forefront of the minds of front office and assistant general managers, social media may not only not be part of their job description, but they may not see any immediate effect of it during their days therefor not on the forefronts of their minds. In addition, the traditional ways of sales and marketing have been drastically affected social media’s creation of two way communication between brand and customer. Door to door sales, mailed brochures, and in some cases, even telephone calls have been put by the wayside due to emailing, Facebooking, Tweeting, and online booking. With these changes, every department within a hotel has been affected and while sales personnel have had to adapt quickly to stay competitive and successful in their position, these changes take time to trickle down the workforce and affect front of house personnel thereby creating significant differences in perceptions of usefulness by sales personnel and FOM. Lastly, owner/operators and GMs are responsible for final decision making in a variety of departments and manners in hotel operations. While FOMs work directly under GMs who work with and for owner/operators, they are typically not privy to full details regarding a hotel’s competitive strategy in the planning stages. With this said,

GMs and owner/operators could see potential for a social media management strategy that would aid in the success of a business. Having full details about this strategy could create a perceived usefulness of social media that front office managers do not have.

Second, managers with different years of work experiences perceived ease of use differently. In specific, differences were found between managers who worked 21 to 25 years and those who worked one to five, six to ten, and 11 to 15 years. Many hotel employees and young managers are either in college or college interns. These employees may be in a FOM, social media manager, or sales personnel position in less than five years depending on available opportunities and would be considered Millennials and today’s younger workforce (Aluri, 2011). In addition, those who have committed 21 to

25 years to the hotel industry may be around 40 years old in. Individuals of this age are known as Generation X and are documented to live completely different lives than

Millennials when it comes to technology use, specifically, social media use. Erickson,

Alsop, Nicholson, and Miller (2009) state that Millennials consider their jobs to be an additional wing in their lives, whereas Generation X believes “you are what you do”.

Millennials are usually perceived as “fast-paced, communication saturated, friend-rich and changed-filled” (Aluri, 2011) with progressively tech-savvy multitude.

Understanding these confirmed generational differences, it only makes sense that it would carry over into their perceived ease of use of a new technology like social media.

Third, managers who worked 31 years and more were found different from those who worked one to five years (p = .013) and six to ten years (p = .013) on their perceived ease of use. An employee of long tenure in the hospitality industry tends to be resistant to

change (Cheng & Wong, 2015; Chung-Herrera, Enz, & Lankau, 2003) and may therefore have less experience with social media then a college intern thereby finding the technology more difficult to use.

In addition, differences were found in ease of use and external challenges based on managers’ age. In terms of ease of use, the differences were found between managers between 20 to 25 years old and other groups: 36 to 40, 46 to 50, 51 to 55, and 56 and up.

In addition, managers aged 56 and up were found different from those aged between 20 to 25 and 26 to 30 years old. Separately, these variable findings are inconsistent with other researchers. Lai and Li’s (2005) study did not find bias with age in their respondent’s perceived ease of use and perceived usefulness of internet banking. Other researchers (Argarwal & Prasad, Burton-Jones & Hubona, 1999; Dishaw & Strong, 1999;

Taylor & Todd, 1995) have suggested that perceived ease of use and perceived usefulness cannot be significantly predicted by age, level or education, or other work variables; however these researchers conclude that a strong relationship between attitude and system use is based on individual experience with the system. Therefore, even if an employee is older and “out of touch” with social media, they very well may have had more experience with the system for business purposes than a younger employee. The hospitality workforce is becoming increasingly age diverse and in an industry where customer service can make or break a company, there is increasing interest in how to most effectively succeed with a multigenerational workforce in a competitive industry

(Gursoy, Chi, & Karadag, 2013).

In terms of external challenges, this study found managers whose age was

between 41 to 45 years old were found different from other groups: 36 to 40 (p =.007), 46 to 50 (p = .012), 51 to 55 (p = .030), and 56 and up (p = .033). In addition, managers aged between 26 and 30 were found different from those aged between 36 and 40 (p =

.017). Challenge options in the survey ranged from being based on hotel operations, education of staff, developing a meaningful ROI, and the five main fears as identified by

Wilson (2009). Each person, no matter the age perceives challenges differently. This is especially true when it does or does not directly affect a person’s job duties and goals.

For example, an owner/operator may perceive many of the challenge selections in this survey particularly challenging due to feasibility with budget or operations. However, a

FOM may perceive the challenge of developing a meaningful ROI as less challenging as they can see some immediate effects of online reputation management by the word of mouth response they receive from guests they interact with on a daily basis. This gap in perception of challenges with age could be based on how 41 to 45 year olds cope with challenges in their lives. When someone is 40 they have most likely been in the workforce for 20 years and still have 20 years before retirement. Their work experiences and vision of the future could help them cope better with any challenges brought on by social media.

There was no significance found to show that level of education affects perceived ease of use or perceived usefulness. In their 2006 study on email based systems, Burton-

Jones and Hubona, found that level of education does not directly affect ease of use or usefulness and suggest this variable depends on the nature of the technology. In their study of older adults and their technology acceptance, Peek, Wouters, van Hoof, Luijkx,

Boeije, and Vrijhoef (2014) found level of education to only be a factor in some technologies in their research but not others, even though all fell under the category

“aging in place technologies.” With this in mind, perhaps no significance was found as the entire scope of the present study was the broad category of social media and not specific channels or methods.

Internal Variables

Internal variables were made up of the four constructs of the technology acceptance index (TRI) model, optimism, innovativeness, discomfort, and insecurity. By utilizing mean ranking (Table 5) with survey responses, factors from highest to lowest mean are: discomfort (M = 5.13); innovativeness (M = 4.26); optimism (M = 4.11); and insecurity (M = 3.63). The construct with the highest mean was discomfort. Specifically looking closer, two questions in the discomfort category scored the highest means out of all 16 TRI questions and they are the following “I do not feel confident doing business with a place that can only be reached online” (M = 5.29) and “social media lowers the quality of relationships by reducing personal interaction”. (M = 5.14). One thing these two questions have in common is the people factor. The respondents in this study were all members of the hospitality industry, a people facing, and guest serving industry

(Wang & Hung, 2015). The success of hotels is built upon guest interaction and although there have been many technological advances in the past few years that eliminate some opportunity for guest interaction such as e-check in and front desk kiosks, the essential element that still remained in the industry is personal interaction (Chen, Yen, Dunk, &

Widjaja, 2015). Because of this, perhaps respondents have a difficult time relying so

heavily on a technology that still involves guest interactions, but eliminates the face to face nature of hospitality (Neuhofer, Buhalis, & Ladkin, 2015).

Out of the two positive related constructs, optimism and innovativeness, the survey respondents had a higher innovativeness mean score. Two of the top three positive emotion related questions were related to the innovativeness construct: “I keep up with the latest social media developments in my areas of interest” (M = 4.83) and

“other people come to me for advice on new social media” (M = 4.20). This suggests that hotel managers keep up to date with trends associated with new technology.

Factors Impacting Manager’s Perceptions and Attitudes toward Social Media

In response to the research question three, a few aforementioned variables were included to determine which had the most impact on managers’ perception, belief, as well as their attitudes towards social media. First, as supported by other researchers (Boon-itt,

2015; Godoe & Johansen, 2012; Lin et al., 2007; Tsourela & Roumeliotis, 2015;

Walczuch et al., 2007; Wook et al, 2014), technology readiness index variables were found to be the strongest predictor of perceived ease of use. Perceived ease of use and perceived usefulness were examined as to their effect on attitude and actual use of social media. External and internal variables and TRI explain 37% of the variability of ease of use. Among these variables, TRI is the strongest predictor of ease of use. Previous research on technology acceptance (TAM) suggests that individual differences, including personality traits like those that make up TRI, generalized beliefs, and demographics, may affect the acceptance (Im, Bayus, & Mason, 2003; Meuter et al., 2005; Parasuraman,

2000). For example, a persistent insecure feeling about technology may influence a

person’s acceptance of a variety of technology-based products and services (Lam, S. Y.,

Chiang, J., & Parasuraman, 2008). Many studies have confirmed the positive effect TRI has on the technology acceptance constructs (e.g., Lin et al., 2007; Parasuraman, 2000).

Lam et al., (2008) and Olsen & Andreassen (2014) both examined the specific TRI factors’ effect on TAM constructs and found that high mean scores in innovation and optimism had a stronger effect on perceived ease of use.

Second, type of hotel (branded vs. independently own) was found to be the strongest predictor of social media return on investment (branded M = 6.18; independent

M = 6.01), followed by external challenges and concerns. Franchised hotel properties are provided brand support, training and resources for social media efforts so it is no surprise that this has a strong effect on return on investment as the investment seems small.

Additionally, an independent property may value ROIs more because they must research and acquire the resources themselves. In both cases, this creates a strong influencing property on return on investment.

Third, return on investment was found to be the strongest predictor of perceived usefulness. Return on investment is a direct correlation to usefulness in a business setting. Hotels set forth policies and practices that are based on efficiency to ensure a low labor cost and high profit. Should a system be deemed useless, it is either manipulated or destroyed. As social media creates more ROI, monetary or non-monetary, it is deemed more useful to a hotel’s bottom line.

Forth, return on investment was again found to be the strongest predictor of managers’ attitudes toward social media, followed closely by usefulness. As stated

earlier, hotels are based on a balance of pros and cons, gains and losses. Hotel managers need to weigh every decision carefully to make the highest profit, be the most successful in town, create the most brand loyalty, etc. A recognizable return on investment deems social media more valuable to managers thus improving their attitudes.

Fifth, external and internal variables, perceived usefulness, perceived ease of use, and attitude were all tested to see which variable was the strongest predictor of actual social media use. While both attitudes and type of hotel are robust predictors of actual use of social media, type of hotel appears to be the strongest predictor of actual use of social media. Whether franchised or not, branded hotel properties are typically provided rules and requirements in maintaining or at the very least, monitoring social media channels or online review sites. For a hotel to comply with brand standards, they must abide by the guidelines creating a strong influence to actual use. Actual social media use was expanded by examine which channels the manager’s reported as having their hotel currently utilize. Based on responses, it appears that the most frequently used social media channel is TripAdvisor followed by Facebook, Twitter, and Instagram, respectively. This is not surprising as TripAdvisor is the world’s largest online review site with over 250 million reviews and 950,000 hotels, bed and breakfasts and specialty lodging properties listed (TripAdvisor, 2015). Facebook is the most widely used, demographically diverse social networking channel with over 1.4 billion (statisticsbrain,

2015). As of mid-2015, there are 288 million monthly active Twitter users sending out

500 million tweets every day. In politics, social media sites such as Facebook and

Twitter are used to track sentiment (i.e. positive or negative) in real-time during election

campaigns, analyzing major speeches, political debates, and policy announcements as they happen; the ability to take the word of others based on their freedom to share

(Feldmanm, 2013). With many hotel brands specifically using Twitter as a listening hub for customer complaints and feedback (Mathur & Mathur, 2015), it is not surprising that it is the second most used social networking site by the survey respondents. Instagram is the second (closely behind Snapchat) fastest growing social network (but as it is a mobile based app, this could present a challenge to the person managing a hotel’s online reputation if they aren’t provided a company phone or do not wish to use their own.

Return on Investment

Returns on investments fell into three categories from the results. In mean ranking order they are: brand promotion (M = 6.32), engagement (M = 6.19), and impression (M = 5.63). The goal of social media marketing is to gain brand awareness and interaction with the customers to talk about a specific business (Csutoras, 2008;

Erdoğmuşa & Çiçekb, 2012). Every organization today has a brand; from producers to distributors to services, and commodities (Kapferer, 2012). Most companies rely on consumer support for their financial stability and this support by created by earning consumer trust and developing those consumers into brand advocates. The three individuals returns on investment that are the most important to the survey respondents are to monitor trends among customers (impression; M=8.77), have a page on social networking site (brand promotion; M = 8.12), and build brand or property loyalty

(engagement; M=7.99). By monitoring trends, Hyatt Hotels saw a need from their customers for 24 hour customer service monitoring on Twitter. In response, they created

their corporate Twitter account in July 2009. Hyatt Hotels’ global head of marketing,

John Wallis said that the Twitter initiative is to provide the extra mile for service

(Mackenzie, 2009). Hyatt Hotels then encouraged their guests to voice their opinions via

Twitter which boosts two way communication and relationship building. In another example of how monitoring trends became a priority for Pink Shell Resorts, they saw the exponential growth of photo based social network, Flickr, and teamed with an internet marketing team to leverage the sight to increase brand awareness and traffic on the resort website in 2010. After one month of the campaign, Pink Shell Resorts saw a 1,000% increase of photo views on their website, an increase in reservation bookings and created an additional $5,000 in revenue (HSMAI).

Having a social presence on the top ranking social media networks is the second most important return on investment for hotel managers. Having a social presence allows for action, interaction and reaction to customer questions, reviews, and engagements

(Biocca et al., 2003; Sparks, So, & Bradley, 2016). Research shows that as a property’s social reputation improves, its overall performance also improves (Anderson, 2012; Zhu,

Sun, & Leung, 2014). A stronger online reputation increases a hotel’s pricing power, which allows the property to increase pricing while maintaining consistent occupancy levels. This price increase results in higher revenue and improved performance. The opposite is also true, properties with weaker social reputations perform worse overall because they have to reduce prices to maintain occupancy levels (Anderson, 2012).

Social media tools have given consumers the ability to easily express themselves online,

without filters. Consumers are actively talking about the brands they love and hate, and why (Alston, 2009; Wallace, Buil, & de Chernatony, 2014).

Building brand or property loyalty should be an important part of any organizational strategy (Kandampully, Zhang, & Bilgihan, 2015) so it is no surprise that this is a top return on investment for hotel managers. A willingness to buy one brand over another gives a financial advantage to one company. What creates this preference for one brand over another, even when paying more? This brand loyalty is created through marketing efforts of the brand to produce a particular bond or belief in the consumer’s mind (Kapferer, 2012). The benefit of having brand loyal consumers not only creates a financial advantage for one brand against their competition, but it also creates brand ambassadors. The end goal for any business is to create brand ambassadors and examples of the benefits companies have received from the attempt in creating brand ambassadors is substantial (Kandampully et al., 2015; Mangold & Faulds, 2009;

Michaelidou et al., 2011).

Pressing Challenges and Factors Which Drive Change

So as to contribute valuable insight to the hotel industry, the most pressing issues in actual social media implementation were examined. These pressing challenges are grouped into three components based on statistical significance and in mean ranking they are: operational (M = 2.84), organizational (M = 2.70), and financial (M = 2.26). Of the three individual most pressing challenges, the following had the highest means: linking social media activities to an impact on company financials or ROI (operational)

(M=3.33); malware and phishing scams by cyber crooks (organizational) (M=3.00); and

educating your staff on how to use social media (organizational) (M=3.00). In regard to the third challenge, with social media being one of the most researched, talked about, and blogged about subjects, there are many free tools and resources that provide step by step tutorials, and provide best practices for social media management. In addition, there is a lot to be learned from how hotel brands are engaging with soon-to-be guests (and current ones) on social media. The top hotel chains have some of the savviest digital presences in the world (Hitz, 2014) and franchised properties often have required, and cost included, training systems for social media management. Malware and phishing scams by cybercrooks can be controlled with proper information technology management and routine virus scans on hotel computers. In an industry where customers are not able to test-drive the product, the hospitality industry is heavily relied on positive word of mouth

(Mathur & Mathur, 2015). Social media has the power to take word of mouth recommendations to a whole new, viral capacity (Majumdar, 2015). The effect of online reviews has caused the U.S. hotel industry to invest close to $6.4 billion to improve and upgrade their properties in 2015 alone (Martin, 2015). Not only has the industry spent dollars on property renovations, guest services and offerings have had to adapt and innovate to stay up to date. This innovation includes keyless guest room entry, mobile apps that allow e-check in, and self-serve kiosks (Kaushik, Agrawal, & Rahman, 2015).

These expenditures represent a 7% increase (Martin, 2015) over 2014 improvements showing the industry is willing to adapt to make their guests satisfied. The 1987

Brundtland Report defined what is called sustainable development which aims to meet the needs of the current and future generations (Brundtland Commission, 1987). In the

business sense, this involves implementing sustainable practices that assist in guaranteeing success which means support from management leaders, human resources, communication, and legal departments (Alvarado-Herrera et al., 2015). Based on a 2009

Mzinga and Babson Executive Education study, it was found that at least 80% of industry professionals do not take into account the return on investment for their social media efforts (Dash, 2010). The metrics can be measured quantitatively and qualitatively, so as to collect both the concrete numbers and subjective evidence (feedbacks, comments, pictures, etc.) to give a whole and accurate perspective to social media strategy (Brown,

2010) that can provide a response to the highest ranked challenge of linking social media activities to an impact on company financials or ROI. By providing an examination to the three returns on investment categories as defined by this research, hotel managers may better understand and appreciate the impact of online reputation management to their property’s overall competitive strategy.

Driving Changes

In response to the research question four regarding the factors that drive change, respondents were surveyed on which items they believed would drive change within their hotel in the utilization of social media. These results provide managerial implications that enable hotel managers to have a realistic comparison for their individual property as to what they may need to overcome stay competitive with regard to online reputation management. The three items the most frequently selected by respondents as driving forces were: increased budget (n = 33); knowledgeable employee (n = 30); and customer encouragement (n = 26). While this study does not examine revenue or budgetary

constraints of individual properties, many tools and resources available for proper online reputation management are free or come at a very small cost to businesses. The most popular social networking sites and hotel review sites are free to maintain profiles on and respond to customer reviews. Increased budget may have been selected the most as managers feel they do not have the employee resources available to manage proper online reputation management. However for many properties, focusing on the top three used social media sites as ranked in this survey, Facebook, TripAdvisor, and Twitter, this task does not necessarily need to be a full-time management position. Giving the duty to a front line employee, perhaps who already is familiar with the property and brand will just add to their responsibility but not necessarily require a significant increase in budget. In fact, having an existing employee manage the social media and online reputation of the hotel is already being done at many properties as brands like Hilton and Starwood are encouraging individual hotels to do so (Lanz, Fischhof, & Lee, 2010). Secondly, having the right person manage a hotel’s online reputation is no doubt an important factor.

However, one of the advantages of social media is that not only are tools free but it is an incredibly analyzed and discussed topic. So much so, the leg work on what works for hotels and what doesn’t has already been done. This information is available, free to read, and free to take advantage of on many social media devoted websites, blogs, and case studies. Furthermore, large hotel brands like Hilton and Starwood provide online social media specific training to their properties. Even if a hotel is not branded, YouTube users have created countless platform and social networking channel tutorials that can walk a hotel employee step by step through the details of setting up a profile on any

desired channel or network, creating or posting content, and more. Lastly, as explained in previous chapters on how many travelers and potential hotel guests utilize social networking channels and online review sites and taking into account how a hotel manager’s response to a poor online review can affect the impression of a potential traveler, it is an unavoidable fact that hotel customers are already talking online about a hotel, whether they are listening or not. Survey respondents may have selected customer encouragement as a driving factor in regard to utilization of newer platforms. As monitoring customer trends was the highest mean ranking return on investment for survey respondents, by being present on social media, and monitoring trends, it can in turn create a listening post for customer encouragement.

Return on Investment

As the success of any business is dependent on balancing costs and benefits, or costs to incomes, it is no surprise that attempting to find an impact on company financials or ROI is the top challenge for hotel managers. With tight budgets, growing competitive sets, and personnel changes, maintaining a competitive strategy and growing profits is key (Hwang & Lockwood, 2006). In addition, nonmonetary return on investments have been provided as implications to hotel managers as for many hotel practitioners, the ability for hotels to successfully connect with their existing or potential consumers lead to a better consumer experience, which will in turn lead to improved financial performance of hotels (Assaf et al., 2015; Grissemann, Plank, & Brunner-Sperdin, 2013; McKay,

2010; Montague, 2006).

Return on Impressions

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The way that individuals control the impressions others form of them is regarded as impression management (Dedeoğlu & Demirer, 2015; Leary & Kowalski, 1990;

Radojevic, Stanisic, & Stanic, 2015). This plays an important role in interpersonal behavior. The impressions that hotel guests and potential guests form about a hotel can be built and maintained through social media. Due to travel review sites, it is undisputable how important a hotel’s reputation is. To build a strong brand, a marketer should therefore preferably look for attributes that rate highly on both differentiation and on relevance (Aufreiter et al, 2003; Kostyra et al., 2015). Transparency, truthfulness, and honesty are valued by the online consumer. The current dominant trend is moving away from the assumption that advertising effectiveness equals the simple media exposure and is inquiring about the role of media integration and media engagement (Buhalis &

Mamalakis, 2015; Calder & Malthouse, 2005; Sigala, Christou, & Gretzel, 2012).

Social media is developing as is the ability for consumers to utilize technology on a regular basis. The human agency is a great form of advertising. Reaching customers can be a form of advertising without an intention of consumer engagement. Kwok and

Yu (2013) found that restaurants mainly used Facebook as a tool for advertising and seldom to actively engage customers. Knowing the vast usages of social media will allow businesses and managers to take a stronger role in their position. Building a reputation in the hospitality industry depends strongly on the quality of services provided.

To stay competitive, a hotel must be involved with their audience by participating in online discussions while building brand awareness, building new relationships and fostering existing ones (Ribarsky, Wang, & Dou, 2014). This user-generated information

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has become part of trip planning, influencing consumers in the decision making process because people tend to trust this information more when it comes directly from other consumers (Wilson et al., 2012). It also dictates the price that a hotel can charge their consumers. Hotel revenue management has evolved over the past two decades and is built on the basis of manipulating price so that demand matches supply. What were simple demand pricing practices have become more complex with the use of technology

(Christensen, 2013; Gregory & Beck, 2006). Positioning themselves in a competitive manner with similar industries allows hotels to capitalize on their potential revenue.

Disneyland Resort utilizes Instagram to show their history. This creates a story with the customer about where they came from and where they are now (Wardell, 2014).

CitizenM Hotels uses their Instagram to show the people behind the brand (Wardell,

2014). Whether the staff member works in the kitchen or behind the reservations counter, this puts names and faces behind the brand creating transparency and identity. How a hotel presents itself is no longer limited to paper advertisements. Social media tells stories based on reality versus how the industry wants to be perceived.

Return on Engagement

Customers want to engage with businesses across many different channels and methods and the customers want to be recognized and remembered through every step

(Adler, 2014; Avectra, 2012; Green, 2006). This is not to say that hotels do not want to engage is this form of customer relationship management but with reservation systems, customer satisfaction surveys and many other obstacles, Green (2006) suggests that hotels may not have the needed infrastructure or focus to achieve the success of

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integration that other industries have seen. The modern day consumer wants access to information and be able to ask questions at any time of the day. They not only use a desktop pc but also tablets and mobile devices; customization is everything to them.

They need to be able to find and purchase a product or service that suits them and their needs immediately. With a declining brand and property loyalty (Singh & Chekitan,

2014) and an increased amount of competition, hotels are beginning to lose their relationships with their guests (Green, 2006; Torres & Kline, 2013). There are many interpretations of a customer service relationship lifecycle but generally, the touch points hotels have an opportunity with are: need, planning, purchase, preparation, stay, satisfaction, loyalty, and advocacy (Øgaarda et al., 2007; Thompson, 2014).

A consumer decision process has four stages: consider, evaluate, buy, and advocate. Tourists go through these stages when making travel purchases, but social media has made the evaluating and advocating stages increasingly relevant (Hudson &

Thal, 2013). Social media is simply any online tool or site that allows interaction with the users and visitors. If one can comment on a post, vote on content, or even just re- arrange the design of a site, then that is social media (Csutoras, 2008; Lipkowsky &

Konert, 2015). The interaction is what sets the stage for an industry to build their reputation. Inspired by the power of social media to engage users in virtual relationships, organizations began seeking ways to immerse into “people’s internet “and learn to leverage the “likes,” “shares and “comments” for profit making (Culnan et al., 2010;

Gard & Whetstone, 2012). By positioning a business well in the center of this community, they can set themselves up for future successes. However, there is no

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challenging the building of a reputation through social media. Nonetheless, social media is still altering the travel plans of more than half the people who use it (Koumelis, 2011).

Storytelling is a common marketing term that defines how companies talk about their brand. This encompasses both on and offline advertising. After the development of social media and two way communications between brands and their consumers, companies had to create a better strategy that created loyal brand advocates in the modern marketing world. What was created was storydoing; when brands convey the message of their company in an organized, efficient manner while engaging with fans and consumers. In storydoing, customers engage and react to the story by using it to promote their own story (Montague, 2013). Social media storydoing created opportunity to build strong relationships with consumers by making them brand advocates and telling your story for you in their own personal communication (HSMAI, 2014). TOMS shoes, Walt

Disney, American Express, Starbucks, Apple and Target are all companies that have implemented successful storydoing strategies (Montague, 2013). Ty Montague of co:collective, an advertising agency, conducted research in 2013 to find out if storydoing really affected a company’s financial bottom line. The study looked at 42 publicly traded companies so they were able to have access to their financial statements. The study found that storydoing created more discussion on social media that was of mostly positive sentiment, the companies spent less on the campaign, the growth of social media mentions steadily increased, and their annualized revenue growth, and share rate increased. Psychologists Melanie Green and Tim Brock (2000) conducted studies that showed that the more immersed the reader is in a story, the more the story changes them.

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With this in mind, brands like Burberry and Dove have moved away from traditional campaign marketing tactics to more brand storytelling to evoke the emotion and passion in their customers. This storytelling may help the customer feel a more emotional connection to the brand thus creating a brand advocate (Kandampully, Zhang, &

Bilgihan, 2015). These brand advocates will speak on behalf of and recommend the brand to others. Advocacy done right drives consumer influence which impacts behavior in others (Park, Lee, & Han, 2007).

Brand Promotion

A successful marketing mix effort in today’s modern world is widely understood to result in customer value creation (Osborne & Ballantyne, 2012). This thought still gives marketing control to the firm, or business, and assumes the consumer is acting as a passive recipient. In the service industry, a new concept within the service-dominant logic is one of value cocreation, where the value is not solely being created for the consumer by the provider of a service, but where value is created that benefits both the consumer and the provider (Neghina et al., 2014). In today’s digital world, it is simpler to turn a cocreator into brand ambassadors. Cocreators feel valued and appreciated when their opinions and needs are responded to online, thus creating a more willing participant in creating positive electronic word of mouth.

For the Roger Smith Hotel in Manhattan, NY, their leap into social media began in 2006. They quickly realized that by being present on social networking sites, they not only were able to join the conversation but to listen to their own online brand ambassadors vouch for their property without any direct hotel encouragement (McKay,

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2010). When people are looking to their social networks for influence on their purchasing decisions, these brand ambassadors are priceless (van Doorn, et al., 2010). A

2010 report by Deloitte titled “Hospitality 2015” states that social media and new technology trends will play a key role in the growth in the hospitality industry.

Millennials—those between 21 and 35—are now beginning to enter their prime earning years. The Millennial generation will represent up to three quarters of the global workforce within ten years (Deloitte, 2014). Millennials love to travel, even more so than previous generations but to win the Millennial’s travel dollar, a hotel must understand the needs and desires of this critical consumer demographic (Langford, 2015).

The adoption of social media practices has opened up a variety of opportunities to listen to the hotel guest. This can be beneficial in learning of their guest’s preferences and needs. The hotel industry highly relies on information technology to improve employees’ productivity and efficiency, accordingly to improve customer satisfaction (Lam, Cho, &

Qu, 2007; Lee, Verma, & Roth, 2015). Lurpak, a Danish butter brand created a website called Bake Club. It allowed baking enthusiasts to connect with other each other. It also allowed Lurpak to connect with them therefore creating direct multi-way communication.

Therefore, it not only created brand knowledge but brand supporting behaviors by sharing and discussing recipes and tips that included the use or Lurpak products

(Labbrand Consulting, 2010). Hilton Hotels & Resorts employs staff to ensure every guest feels cared for, valued, and respected on their social channels by closely monitoring guest feedback. This dedicated staff listens, responds, and resolves guest feedback. To make an even greater impact with their guests, Hilton created a Twitter handle,

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@HiltonHelp for the sole purpose of allowing their guest assistance team to respond to guest comments and concerns. Andrew Flack, Vice President of global brand marketing for Hilton Hotels & Resorts said that by nurturing their online relationships with their guests, they are able to foster a sense of loyalty from them. This effort has helped the brand’s Facebook following increase by 185% in 2012 and guest engagement on

Facebook and Twitter has grown substantially (Wharton, 2012). This is an example of how Hilton has been able to create a return on investment based on their brand promotion which has created loyalty within their guests. That loyalty could be considered invaluable as the competing brands flood the marketplace. According to Woods (1995), one Delta Airlines' lifetime customer generates $1.5 billion in revenue. Brand loyalty is important because keeping and serving current customers requires less money than acquiring new customers (Grissemann et al., 2013; Tanford, Raab, & Kim, 2012; Tepeci,

1999). While Marriot Hotels & Resorts only just began their global social media efforts in late 2012, they have created a unique voice across the brand in an effort to connect and become more relevant with Generation X (those born between 1966-1976) and

Generation Y (those born between 1977-1994) travelers (Wharton, 2012). Gen X and

Gen Y both have advantages when it comes to technology use and adaptation compared to the baby boomer generation (those born between 1946-1965) (Anderson, Reitsma,

Sorensen, & Munsell, 2010). This tactical marketing decision allows Marriot Hotels &

Resorts to strategically connect with an audience that is familiar and most likely active on those social media networks and channels. Focusing on return on impression, engagement and opportunity for brand promotion can give a hotel a clearer picture of

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how their marketing initiatives are performing than traditional return on investment offers alone (Buhalis & Mamalakis, 2015; Gunulies, 2012).

Managerial Implications

The significant findings of this study contribute to a better understanding of the hotel manager’s attitudes toward social media. Particularly by incorporating a variety of departmental views, the results can aid both hotel managers and owners in terms of their future strategies. Furthermore, this study provides managers valuable information on how to overcome concerns and engage driving forces to maintain competitive strategy with online reputation management implementation.

Managers were found to have a high level of discomfort when it comes to their technology readiness levels. Discomfort is defined as having a need for control and a sense of being overwhelmed (Parasuraman & Colby, 2015; Walczuch, Lemmink, &

Streukens, 2007). This could be due to specific social networking channels, it could be linked to surveyed challenges, or it could just be due to an overall discomfort of technology and social media as a whole. In addition, top ranked challenges were found to be financially based. While many social media networks and tools come at a minimum to no cost, they are also not complicated to use or adapt to changes once a basic understanding is created. This finding calls attention to a need for managerial training as discomfort and financial challenge could be lessened by a more knowledgeable staff. By understanding how a technology works, the user will become more comfortable with it.

Furthermore, by understanding the non-monetary ROIs of social media and visualizing them in the manager’s own property, the comfort with including social media

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management in their competitive strategy will increase. This training can be completed in a branded or independent property by either a brand team or by utilizing a hotel’s local tools and resources of marketing or social media firms.

A successful competitive strategy for a hotel requires input and effort from all departments to work as a cohesive team with a unified goal. This research revealed a significant gap in perceived usefulness of social media between FOMs and social media managers and other job title groups. Social media can be incorporated into every department of a hotel. This perceptual gap can be minimized by sharing how social media and its ROIs affect every department of a hotel. For example, if a FOM understands how return on engagement creates online conversation which can potentially answer guest questions before check-in, the front office may receive less phone calls from future guests which tie up front office employees and prevent them from focusing on the guests currently within the hotel. In addition, by sharing knowledge of the capabilities of social media with a revenue manager or marketing manager, these departments can work together to take full advantage of the tools by promoting certain overnight packages, researching competition, and creating exciting online content that draws the attention of the consumer, thereby creating a usefulness of the tool to these specified departments. Furthermore, FOMs may have an opportunity to be promoted to revenue manager or even the general manager position. By having the knowledge and understanding of social media, this could provide an advantage to FOMs should a promotion opportunity arise.

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This research found a gap in perceived ease of use of social media within multiple tenure brackets, specifically, those who worked in the hotel industry 21 to 25 years differed from multiple group and those who worked 30 or more years, perceived ease of use differently than those working under 10 years. In addition, differences in perceived ease of use were found among age brackets. In specific, those aged 20 to 25 scored differently in their ease of use than other groups and those aged 56 and older ranked differently in their perceived ease of use. As an employee gets older, it is assumed they have worked in the same industry for an extended period of time due to opportunity for advancement and comfort level with the industry. Therefore in theory, those respondents who are 56 and older, may have worked in the industry 30 or more years. With an increasingly diverse workforce demographic, it is important to consider how a gap in an ease of use can affect hotel operations, particularly within an ever changing technological environment. By encouraging conversation on the topic of social media, it can level the playing field of knowledge as managers share with one another. With increased conversation and an opportunity for training, TRI discomfort levels will reduce and ease of use of the technology will increase thereby minimizing the gap.

External challenges of managers aged 41 to 45 were perceived differently from other groups. According to U.S. News (2013), in a person’s 40’s, they’ve entered a professional quandary. This is the peak of their career where enthusiasm coexists with expertise but often these individuals are weighed down with school-aged children, aging parents, and other responsibilities such as a marriage and mortgage. This creates an employee who likes to weigh pros and cons heavily before entering into a decision.

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However, this doesn’t have to be the case. With a better understanding of the resources available with social media management, best practices, and IT management, many of the existing perceived challenges can be broken down into actionable plans and manageable items. This better understanding can come from knowledgeable coworkers, and training initiatives.

TRI and ROI were found to be the key factors in ease of use, usefulness, and attitudes toward social media. This is important to take into account as a hotel owner or

GM implements a competitive strategy involving a variety of department managers. By examining meaningful ROIs which would have the most impact on each individual property, a plan can be put together more cohesively. Furthermore, by placing the right employee in the social media management position, who is equipped with the training efforts suggested above, the employee is more likely to identify meaningful specified or categorical ROIs to offer executive leadership which will in turn influence leadership’s optimism and attitude toward the system. Return on impression, engagement, and opportunity to promote the brand are the three key measurements for a modern social media ROI that were found in this study. Brand promotion had the highest mean among respondents finding that it is perceived to be the most important ROI for hotel managers.

While brand promotion is important to any business, brand loyalty cannot be created without the other two ROIs. Engagement and impression are similar terms when it comes to social media management and both can be valuable separately. Impression creates a broader reach while engagement can lead to brand loyalty and brand advocacy

(Erdoğmuşa & Çiçekb, 2012; Wirtz et al., 2013). Modern ROI affords hotels the

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opportunity to market to their consumer in a way that can not only get guests in the door of the hotel, but in a way that encourages individuals to be brand advocates which creates positive word of mouth.

The top three driving forces which would drive change within the organization were found to be increased budget, customer encouragement, and knowledgeable employee. Managers, especially human resource managers are responsible to ensure all needed training is properly provided to employees. Furthermore, having a knowledgeable employee can be achieved by providing access to needed training. With training, this knowledgeable employee will be able to attain and present meaningful ROIs to executive leadership. This research found that the top rated ROIs by the survey respondents are to monitor trends among customers, have a page on social networking, and build brand/property loyalty. While the third ROI may be more difficult to prove initially, with continued efforts by a hotel and social media strategy, this ROI can come to fruition. Lastly, in an effort to drive change, it is suggested that managers not concern themselves too much with brand support (if applicable), ownership approval, or management acceptance as driving forces as most hotel brands have an online presence, and ownership approval and management acceptance can be increased after a social media strategy has been put in place and meaningful ROIs develop. Approximately one- fifth of leisure travelers worldwide turn to social media platforms for inspiration within different categories of their travel planning including (Olenski, 2014) so it is important for hotel managers and owners to take full advantage of the tools and resources available to reach those travelers online in a meaningful and strategic way.

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Limitations

This study surveyed hotel managers in the United States on their attitudes toward social media. Although this study shed some light on factors that affect actual use as well as existing challenges on implementing social media in hotel operations, several limitations of this study must be acknowledged. Firstly, due to the lack of prior research studies on the topic social media use in hotel operations, it is difficult to compare the significance and possible explanations of the results with others. In addition, the model used in this study did not have a proven scientific design. Secondly, as age and experience in the industry naturally overlapped in the results, this caused an unspecified significance for usefulness and return on investment. Thirdly, the sample size for the consisted of 97 valid responses and as this is a small sample size, results may be limited in their generalizability. Fourthly, the online survey provides advantages of reaching a wide population and participants were able to complete the survey at their own pace; however, the low response rates and many incomplete responses could possibly affect the quality of survey results. Even though significant relationships from data were possible to discover, to ensure representative data of U.S. hotels, a larger sample size is recommend as it allows for greater generalizability. Although it is more cost effective to send out online surveys over mailing paper surveys, some of the limitations of online surveys include the difficulty of tracking non-response rates, participants either ignoring the emails, perceiving those as junk or deciding not to continue after looking at the instructions and/or length (Lefever, Dal, & Matthiasdottir, 2007). Furthermore, a low reliability alpha for the scale of attitudes makes it necessary to re-examine or re-design

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should a similar study be pursued. Lastly, more literature and research is needed to re- design survey questions pertaining to actual social media use behavior.

Despite these limitations, this study yields many tangible and distinctive results that are not found in other studies such as the predictive power of social media return on investment on manager’s attitudes, the effects of technology readiness on ease of use, as well as the impacts of job position on managers’ perception toward social media. This study found unique findings that contribute to a better understanding of hotel manager’s attitudes toward social media. Unique to this study was the finding that hotel type was the strongest predictor of actual use and that perceived usefulness among hotel managers was significantly different depending on job title.

Future Research

Research has been conducted on the role of social media on a traveler’s decision as well as in tourism and operations management (e.g., Akehurst, 2009; Anderson, 2012;

Arola, 2010; Buhalis & Law, 2008; Buhalis & Mamalakis, 2015; Cox et al., 2009;

Hudson & Thal, 2013). Leung, Law, van Hoof, and Buhalis (2013) suggest that industry professionals can use academic research on this topic to maintain competitiveness. Some business reports have shown that restaurants can increase sales with use of Facebook or

Twitter (Maines, 2009; Young, 2010) but whether a restaurant, retail outlet, or hotel, consumers have already shared their opinion and experience online. As this research explored manager’s attitudes toward social media, the relatively small sample size made it difficult to draw any substantial or generalizable conclusions. As continued research is vital to the hospitality industry in growth and competitiveness, it is recommended that the

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study be replicate and shared with a wider population in hopes of obtaining a higher response rate.

To better understand actual social media use within hotels, it is proposed that actual use not only be measured by channel but by activity and frequency of activity. For example, how often Facebook posting are made, how quickly customer reviews are responded to, and how many hours per week are spent on the online reputation management of the hotel.

Hotels in Ohio, Pennsylvania, and Michigan only were contacted to acquire general manager’s email addresses. Any remaining surveys completed outside of these states were completed by utilizing snowball sampling of existing professional contacts.

By individually contacting hotels outside of these three states, it is more likely general managers will receive the survey directly and complete it. In addition, comparing different service types with these questions could find interesting results, for example, a casino versus a resort. Furthermore, comparing results between major destination areas like Napa and New York City or Cleveland and Miami could prove interesting.

To better understand current manager’s attitudes toward social media, it is suggested to include interviews when expanding the present study. Gauging attitude may be better analyzed if a person were conducting interviews on a technology based subject as some managers may have negative attitudes toward social media and thus unable or unwilling to complete a web based survey. The findings of this study show a significant difference among job titles and their perceived usefulness of social media. To better understand these findings it is suggested to delve deeper into the reasoning behind this,

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perhaps by investigating if and how the person believes social media affects their daily duties and responsibilities. In addition, by asking if and how they utilize any social media or online review sites for any part of their job.

APPENDICES

APPENDIX A

CONSENT FORM FOR MANAGERS

APPENDIX A Online Consent Form for Managers

Dear Hotel Manager,

The purpose is to develop an understanding of the current stance on social media from a hotel management stand point. Risks of participation in this study are minimal. This online survey is brief and will take approximately 10-15 minutes to complete. Participation is voluntary and all participants will remain anonymous. If at any time you do not wish to participate, you are free to stop and have no obligation to continue. Additionally, participants should be aware that the survey is being run from a secure server.

Please complete this survey by August 30, 2015.

If you have questions or comments about the nature of the survey or are curious about the results, please contact Colleen Iacianci ([email protected]) or Ning-Kuang Chuang ([email protected]) in KSU’s Tourism and Hospitality program. This project has been approved by the Kent State University Institutional Review Board. If you have any questions about your rights as a research participant or complaints about the research, you may call the IRB at (330) 672-2704.

If you are 18 years of age or older, understand the statements above, and freely consent to participate in the study, click “I Agree” to begin. (You may print a copy of this consent form to keep at this time)

Thank you for you participating!

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APPENDIX B

KSU INSTUTUTIONAL REVIEW BOARD APPROVAL FORM

APPENDIX B

KSU Institutional Review Board Approval Form

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APPENDIX C

RESEARCH STUDY SURVEY

APPENDIX C

Research Survey Study Section 1 Q1 Please indicate the extent to which you agree with each of the following statements about social media in your organization using the following indicators: (1) Strongly Disagree (2) Moderately Disagree (3) Somewhat Disagree (4) Neither Disagree nor Agree (5) Somewhat Agree (6) Moderately Agree (7) Strongly Agreea) The use of social media by our organization will grow significantly over the next few years. b) Our organization has a significant learning curve to overcome before we can utilize social media. c) Interest in utilizing social media is growing rapidly within our organization. d) Until we are able to clearly measure the impact of social media it will not be taken seriously in our organization. e) Social media is an important component of our overall marketing strategy. f) Using social media is integral to our overall company goals and strategy. g) Social media has been designated as a high priority by our organization's executives. h) The use of social media for business purposes is a passing fad. i) Social media tools are not very relevant for our business.

Q2 Please indicate how strongly you agree or disagree with each of the following statements. 1) Strongly Disagree (2) Moderately Disagree (3) Somewhat Disagree (4) Neither Disagree nor Agree (5) Somewhat Agree (6) Moderately Agree (7) Strongly Agree a) New social media contributes to a better quality of life. b) Social media gives me more freedom of mobility. c) Social media gives people more control over their daily lives. d) Social media makes me more productive in my personal life. e) Other people come to me for advice on new social media. f) In general, I am among the first in my circle of friends to acquire new social media when it appears. g) I can usually figure out new social media products and services without help from others. h) I keep up with the latest social media developments in my areas of interest. i) When I get technical support from a provider of a social media product or service, I sometimes feel as if I am being taken advantage of by someone who knows more than I

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do. j) Social media support lines are not helpful because they don't explain things in terms I understand. k) Sometimes, I think that social media systems are not designed by ordinary people. l) There is no such thing as a manual for a social media product or service that is written in plain language. m) People are too dependent on social media to do things for them. n) Too much social media distracts people to a point that is harmful. o) Social media lowers the quality of relationships by reducing personal interaction. p) I do not feel confident doing business with a place that can only be reached online.

Q3 For the section below, please indicate how strongly you agree or disagree with each statement. 1) Strongly Disagree (2) Moderately Disagree (3) Somewhat Disagree (4) Neither Disagree nor Agree (5) Somewhat Agree (6) Moderately Agree (7) Strongly Agree a) Using social media improves my performance in my job. b) Using social media in my job increases my productivity. c) Using social media enhances my effectiveness in my job. d) I find social media to be useful in my job. e) My interaction with social media is clear and understandable. f) Interacting with social media does not require a lot of my mental effort. g) I find social media to be easy to use. h) I find it easy to get social media to do what I want it to do.

Section 2

Q4 Do you currently have someone who... (Yes or No) a) monitors and responds on and/or offline to online hotel reviews b) actively engages on social networks c) Other, please specify d) I am not sure

Q5 Please indicate to what extent your property (properties) is(are) actively utilizing the following channels? (1) Never (2) Rarely (3) Sometimes (4) Often (5) All of the Time (0) N/A a) Facebook b) Google+ c) Instagram d) YouTube e) Pinterest f) TripAdvisor g) Twitter h) Yelp i) Other, please specify

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Q6 Rate the importance of the following goals in your organization's social media efforts. (1) Not at all Important (2) Very Unimportant (3) Somewhat Unimportant (4) Neither Important nor Unimportant (5) Somewhat Important (6) Very Important (7) Extremely Important a) Promote your brand, and/or services via social media b) Have a page on social networking site c) Provide ways for customers to interact with your company using social media d) Use social media to monitor trends among your customers e) Research new product ideas via social networking/social media f) Collect and track customer reviews on your website and/or other sites g) Advertise on social networks h) Create brand or property awareness i) Build brand or property loyalty j) Create new customers k) Share brand or property information l) Gain customer feedback and insight

Q7 Please indicate how challenging you believe that your organization currently is facing with regard to social media. (1) Not at all Challenging (2) Slightly Challenging (3) Moderately Challenging (4) Very Challenging (5) Extremely Challenging a) Finding a qualified social media manager b) Ownership c) Cost of social media management systems d) Operational integration e) Linking social media activities to an impact on company financials or ROI f) Getting people across the organization to see the value of social media activities g) Educating your staff on how to use social media h) Responding to findings from social media (i.e., quickly resolving/ addressing an issue raised by social media) i) Capturing/ analyzing online conversations about your brand products/ services j) Perceived loss in staff productivity k) Data leakage from staff gossiping freely in an open environment l) Malware and phishing scams by cyber crooks m) Open access potentially offered to the company servers by lax and outdated attitudes towards passwords n) Damage to a company's reputation o) Other, please explain

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Q8 What factors would drive change within your organization in the utilization of social media? Please select up to three.  Increased budget (1)  Knowledgeable employee (2)  Ownership approval (3)  Management acceptance (4)  Brand support (if applicable) (5)  Customer encouragement (6)  Available training (7)  Other, please explain (8) ______

Section 3

Q9 What is your current position title?  General Manager (1)  Revenue Manager (2)  Director of Operations (3)  Assistant General Manager (4)  Owner/Operator (5)  Front Office Manager (6)  Social Media Manager (7)  Director of Marketing (8)  Director of Sales (9)  Other, please specify (10) ______

Q10 Please indicate the type of hotel you represent (branded or independent) for up to three hotels. Property 1 ______Property 2______Property 3______

Q11 Please tell us about your first hotel property. Check all that apply.  Corporate owned and managed (1)  Franchisor with management contract (2)  Franchised property (3)  Contracted management company (4)  Member of referral group (5)  Asset management company (6)  Independent property (7)

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Q12 Please tell us about your second hotel property. Check all that apply.  Corporate owned and managed (1)  Franchisor with management contract (2)  Franchised property (3)  Contracted management company (4)  Member of referral group (5)  Asset management company (6)  Independent property (7)  N/A (0)

Q13 Please tell us about your third hotel property. Check all that apply.  Corporate owned and managed (1)  Franchisor with management contract (2)  Franchised property (3)  Contracted management company (4)  Member of referral group (5)  Asset management company (6)  Independent property (7)  N/A (0)

Q14 How many years have you been working in the hotel industry? (1) ______What is your age? (4) ______

Q15 What is the highest level of education you've received?  High School (1)  Some College (2)  Associate's Degree (3)  Bachelor's Degree (4)  Master's Degree (5)  Doctorate (6)  Other, please specify (7) ______

Q16 Thank you very much for participation. Would you like to be entered to win one of ten $25 Starbucks gift cards?  Yes (1) Please enter your email address in the box below.  No (0)

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