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MEETING AND EXCEEDING GUEST EXPECTATIONS: THE INFLUENCING ROLE OF TECHNOLOGY IN BAHAMIAN HOTELS.

Introduction

Increased competition and globalization have provided the impetus for hotels to identify methods that will provide a competitive edge (Sirirak, Islam & Khang, 2011). The adoption of information and communication technology has been the preferred method by most hotels to manage the transformation of the hotel industry landscape (Shang, Hung, Lo & Wang, 2008). Information and Communication Technology (ICT) facilitates instantaneous access to hotels' products and services by the consumer irrespective of their geographical location. Furthermore, the capabilities which ICT applications possess has allowed hotel management to successfully target consumers worldwide, the rapid growth of mobile computers and web technologies have made this significantly easier (Bethapudi, 2013). Thus, hotel managers perceive ICT adoption as an essential component in improving hotel performance (Siguaw, Enz & Namasivayam, 2000; Sigala, 2003). The use of ICT to tailor the tourism product produces an increasing level of guest satisfaction. Therefore, improving customer satisfaction is viewed as imperative for prolonged success and survival (Jones, 1999). As such, it is postulated that ICT adoption within the hotel industry can increase operational productivity, reduce costs, facilitate efficient decision making, improve service quality, improve guest satisfaction and increase revenues (Gibson & Swift, 2011; Aziz, Bakhtiar, Syaquif, Kamaruddin & Ahmad, 2012).

While the adoption of ICT stands to improve the operational productivity of hotels, this demands substantial capital and investment in resources (Hoontrakul & Sunil, 2007). Therefore, small hotels which do not have the capital at their disposal to adopt ICTs will lag behind counterparts who have the financial prowess to invest in ICTs (Hoontrakul & Sunil, 2007). It is felt that the higher the star rating of a hotel the more likely it will have the latest ICT infrastructure (Athey, 2011). The 4-star and 5-star rated hotels are usually found in developed countries. Small island-developing states, such as the Bahamas, are inherently at a disadvantage, which is further compounded by their lack of financial reserves and human constraints (Fiestas, 2011). These limitations hinder the adoption of ICT in these hotels.

Within the hospitality and tourism literature a gap persists. Even though scholars have investigated and evaluated the benefits that are produced by ICT adoption most have focused on the direct benefits which ICT adoption facilitates; one such direct benefit is increased performance (Mihalic & Buhalis, 2013; Yousaf, 2011). Yet, the indirect implications of ICT adoption such as customer satisfaction have been neglected within the literature hence; this study seeks to close the gap by assessing the impact of ICT on customer satisfaction in Bahamian hotels.

Presently the Bahamian tourism industry accounts for approximately 53,500 jobs that represent 28.5% of the country's total employment. Furthermore, the industry contributes 46% to the national GDP; therefore, it can be deduced that the country is highly dependent on the tourism industry and its growth and development are pivotal (WTTC, 2014). Taking into consideration the island's position within the global tourism market, Bahamas must position itself to reap the economic rewards from the tourism industry.

In the Doing Business report, Bahamas is ranked 97th as it pertains to the country's ease of doing business. While the country's rank is not the best once compared to other Caribbean countries, it is relatively fair and business investors have the ability to access and utilize ICTs. ICTs can be viewed as a strategic developmental tool (Aziz et al., 2012), and there exists an ingrained perception that strong ICT infrastructure within a country aids in dismantling the barriers associated with conducting business. Thus, ICT facilitates a less cumbersome transaction between stakeholders. Therefore, the Bahamas is poised to exploit the benefits associated with ICTs due to the fact that the country's Internet users have seen tremendous growth and presently accounts for 76.9% of the population, similarly the country's mobile penetration is growing. Given that both the Internet and mobile phones are essential channels that facilitate global connectivity which is beneficial to prospective guests as well as hotel managers.

Within the hospitality and tourism literature there is insufficient investigation as it pertains to the impact of ICT adoption on hotel performance, specifically in developing countries (Mihalic & Buhalis, 2013). As a consequence, the study at hand seeks to ascertain the impact of ICT adoption on customer satisfaction in Bahamian hotels. The research model as shown in Figure 1, illustrates a research model which emphasizes the independent variables associated with the availability of ICT components, and the dependent variable - customer satisfaction as well as associated indicator variables. Both the independent and the dependent variables were adapted from Sirirak et al. (2011) study.

There has been a transformation in the way hotels market their products and utilize ICT to provide services to their customers (Ansah & Blankson, 2012). This shift is very important in the hospitality industry as the focus is more on the experience of guests rather than service (Zhang, Cole, Fan, & Cho, 2014). In addition, Travel Agents also play a major role in the utilization of ICT in the industry. Travel Agents with online capabilities play a very important role by contributing huge volume of transactions and sales (Pan, Zhang, & Smith, 2011). Based on these developments, hotel guests expect certain services and technological applications similar to those they possess at home which assist in improving the quality of their stay and experience. Moreover, these services can be categorized into four groups namely; reservation management, room management, telecommunication and guest accounting. Other scholars (Ham, Kim, & Jeong, 2005; Sigala, 2003) use the current services to classify ICT components.

ICT components as classified by Sigala (2003) are:

1. Rooms division

2. Food and beverage

3. General/Back office

4. In-room

The aforementioned services were used to formulate four hypotheses analogous to methods employed by (Sirirak et al., 2011) in their study. Thus, the four derived hypotheses associated with the experiences of guests in Bahamian hotels are:

H1: The availability of room division ICT components will positively impact customer satisfaction

H2: The availability of food and beverage ICT components will positively impact customer satisfaction

H3: The availability of back office ICT components will positively impact customer satisfaction

H4: The availability of in-room ICT components will positively impact customer satisfaction

The rationale for conducting the study is to provide additional information and methods that will serve as a guide for hotel administrators as it pertains to ICT components. By providing this information it is endeavored that the greatest beneficiaries will be the consumers, thereby improving hotel performance via improved customer satisfaction. The outcome is of grave importance given that countries, such as the Bahamas, are heavily dependent on the industry and it is suggested by the literature that growth in tourism can affect national economic growth (Jaforullah, 2015).

Literature review

Information communication technology (ICT) comprises the use of computer software, hardware and telecommunication devices to store, convert, manipulate, protect, receive and send data (Olifer & Olifer, 2006). The rapid emergence and commercialization of ICT within the tourism industry has propelled hotels to adopt these information and communication technology applications anticipating improved operational productivity and customer satisfaction levels. Notably, ICT is credited as the greatest singular factor impacting and effecting change within the hospitality industry (Connolly & Olson, 2000). This development can be attributed to the rapid growth in technology and increased customer demands for specialized, accessible, flexible and interactive products and communication with principals (Buhalis, 1998). Tourists' intention to use ICT is driven by social norms (Erawan, 2016). Moreover, products and processes that are ICT based aid hotels by enhancing their operation efficiency, service experience and provide the platform required to access global markets (Hoontrakul & Sahadev, 2004).

Historically, while ICTs were employed in the late 70s in the hotel industry in the form of Computerized Reservation Systems and Global Distribution Systems, it was not until the 90s that ICTs began to transform the hospitality sector (Cooper, Gilbert & Wanhill, 1998). As it pertains to the daily operation of hotels before the advent of ICTs, operations were carried out using a manual system in the front office. As such information on hotel occupancy, as well as guest expenditure and departure of guests were done manually. However, the utilization of ICTs in various domains of the hotel has facilitated an efficient and effective front office operation as well as improved overall hotel operation.

Ham et al. (2005) postulates that inventory, procurement and room reservation systems, hotel website, email and electronic transaction are some of the application which have been implemented extensively within the hotel industry. Moreover, numerous major hotels invest in a property management system (PMS) as well as cost and accounting systems which facilitates management of the front and back office operations as fundamental applications (Leung & Law, 2013). The use of ICTs in hotels, cultivates the expectation of increase revenues and profit margins by hotel managers (Law & Jogaratnam, 2005). Siguaw, Enz and Namasivayam (2000) note hotel managers believe ICT adoption as a vital component in enhancing hotel performance. Similarly, Jones (1999) states the capability to improve customer satisfaction and operational productivity is perceived as fundamental to a hotel's survival and success.

ICT adoption, use and acceptance

A hotel's propensity to adopt ICT is an indication of its inclination to be ground-breaking while simultaneously reflecting its capability to accept, use and assess new technologies. Hoontrakul and Sahadev (2004) postulate that hotels that have a high adoption propensity will inevitably be early adopters of technology; thereby being a risk taker in the industry. The perception that innovativeness facilitates and acts as a source of competitive advantage will influence a hotel's adoption propensity. This perception is predicated on factors that characterize the competitive landscape of the hotel. Therefore, a hotel's propensity to adopt is determined by its internal capabilities and requirements. Its adoption propensity is affected by numerous factors which are related to the hotel and its external environment. Nwakanma et al. (2014) note that the geographical location of a hotel significantly impacts its operations and profitability. Furthermore, the geographical location of a hotel foreshadows customer profile, market size and the competition level to which it is exposed.

The three aforementioned factors strongly influence a hotel's ICT adoption propensity. Given that a hotel ICT adoption propensity is intricately intertwined with its expectations, as it pertains to value addition that ICTs can offer to the consumer as well as the perception of market expansion through ICTs. Therefore, a hotel propensity to adopt ICT increases if its expectations of ICT based applications are to increase its competitive advantage over the competitors or to eliminate any advantage held by the competitors as it regards customer profile characteristics, market size and the intensity of competition encountered. Thus, a hotel's customer profile, size of its target market and competitive intensity influences their level of ICT adoption propensity. Wei, Ruys, Van Hooh and Combrink (2001) discovered that geographical location has a significant impact on the adoption and use of Internet among hotels.

Conversely hotels are slow to implement contemporary ICTs (Cho & Olsen, 1998; Sheldon, 1997); as such the hotel industry currently lags behind other industries in ICT adoption (Gamble, 1988). Hotel's slow adoption rate can be indicative of the lack of IT knowledge possessed by decision makers within the industry. Therefore, hotel managers are oftentimes reluctant to the implementation of modern technologies due to their lack of technical knowledge and understanding. Apprehension about the implementation of ICT among hotel managers exists because they often perceive that their jobs are threatened since ICT adoption and implementation eradicate personalized services to hotel guests. Connolly, Olsen and Moore (1998) assert that hotel managers are skeptical about the benefits of investing in ICTs due to their low IT prowess.

However, it is accepted that the utilization of ICTs within hotels can be classified into the following groups: room division (RD) ICTs, food and beverage (F&B) division ICTs, general and back office ICTs and in-room ICTs (Ham et al., 2005; Sigala, 2003). The level of ICT adoption in hotels can be measured by the availability of ICT components, integration of ICT components and the intensity of ICT usage (Sigala, 2003). The availability of ICT constituents in a hotel is denoted by the number of items it possesses (Ham et al., 2005; Siguaw et al., 2000). The incorporation of ICT components is characterized by the number of linkages which exist between an operational domain and any other domains or to the primary server systems (Sigala, 2003). The intensity of ICT usage is measured by the percentage of total operations completes using ICTs. For example, the percentage of transactions done via the hotel's website reservation systems denoted the intensity of ICT usage of the reservation procedure (Sahadev & Islam, 2005).

Performance and expectations

In a highly competitive operating environment hotel managers must understand the aspects of the business that are essential to their guests in an effort to meet and exceed expectations as it pertains to products and services offered. A hotel's performance is measured by its ability to ensure that customers are satisfied at a minimum and ideally that customers are delighted (expectations are not only met but exceeded). The relationship that exists between customer satisfaction and loyalty (Bowen & Shoemaker, 1998; Tepeci, 1999) has been a known and accepted assertion for managers for decades. Perceived customer satisfaction level as it pertains to hotel services offered and the customers' proclivity to re-book and/or endorse the hotel service to others reflects the satisfaction of the customer which influences the hotel performance (Choy & Chu, 2001; Johnston & Jones, 2004). A customer's overall satisfaction level with services offered is the composite of satisfaction levels with each of the hotel service categories. These are inclusive of room quality, general amenities, staff service, value, security and business service (Choy & Chu, 2001).

Research suggests that technology has a greater impact on back office functions of hotels than it does on front office or guest contact centers. This may mean that while there is impact on satisfaction based on the smooth running of the back office, this may not be as apparent to guests, if the areas with which they directly interface are not ICT friendly. This may be in part due to the fact that as Sirirak et al., (2011) point out, the propensity to adopt ICT in many hotel chains is driven by a desire to improve operations rather than an emphasis on customer satisfaction. Importantly, Zhu, Sarkis and Lai (2008) postulate that operational performance is denoted by a hotel performance in attaining fundamental objective/s; inclusive of quality, service delivery and productivity. Productivity is operationalized as the ratio of operational outputs to input over a time frame. Inputs within the operational productivity ratio refer to that of materials, staff costs and equipment. Meanwhile outputs are denoted by revenue, number of goods or services purchased and the number of customers processed (Johnston & Jones, 2004). Hence while operational productivity of a hotel mirrors the efficiency and effectiveness of the establishment business operations and management; high levels of customer satisfaction create the gateway to establishing and forging prolonged customer satisfaction and the integrity of the hotel (Sirirak et al., 2011).

Satisfaction as a performance indicator

Essentially ICT should be viewed as an amplifier to a hotel's operational structure and management. Thus, if implemented in a poorly managed hospitality establishment its ability to increase the hotel's performance is significantly lessened. On the other hand, the implementation and use of ICTs in properly managed hotels will result in the increase of its performance (Sigala, 2003). Guest satisfaction, while not being the only outcome is the ultimate indicator of whether key objectives are being met.

Kim and Ham (2006) established that the use of ICT applications in the front office significantly enhance service quality in high-end hotels. It was previously purported that ICT applications significantly impact front office productivity (David, Grabski, & Kasavana, 1996). However, the introduction of ICT applications to the back office does not yield the same results as the front office. The study undertaken by Siguaw et al. (2000) bolsters the findings by David et al. (1996) reiterating that ICT introduction to the back office had little effect on improving a hotel manager's strategic judgments. Even though there exist a positive relationship between hotel management and effective ICT adoption it must be noted that studies done in Hong Kong discovered that hotels adoption rate of modern ICTs are low (Law & Au, 1999; Law & Jogaratnam, 2005). Similarly, O'Connor (2008) noted that in spite of the rapid adoption of ICT within the hospitality industry, it still lags half a generation behind other industries.

While there has been a proliferation of studies, focused on identifying the relationship between ICT adoption and hotel performance in developed countries (David et al., 1996; Sigala, 2003), there is a need for contemporary research to unearth the relationship that exists between the impact of ICT and hotel performance in developing countries (Sirirak et al., 2011). This would bring into focus a slow ICT adopting industry in slow adoption countries.

ICT and customer satisfaction

The establishment of customer reservation systems, global distribution systems and the Internet, have transformed the hotel industry dramatically (Buhalis, 2003). The development of search engines, bandwidth and the speed of networks have influenced a large number of travelers around the world to use technologies for planning and experiencing their travels. ICTs facilitate potential travelers to access reliable and accurate information, then enable the processing of reservations in a fraction of time and cost in comparison to conventional methods (O'Connor, 2008). As a result, it assist in the improvement of service quality and contribute to higher satisfaction by hotel guest (O'Connor, 2008). In essence, ICTs and particularly the Internet, empower potential guests to become more knowledgeable in their quest to seek exceptional value for money and leisure time.

Leisure time is increasingly being used for "edutainment". Edutainment is the desire to satisfy personal interests for both personal and professional development. As a result, the new tourists are less interested in following the crowd with packaged tours. They are more inclined to pursue their own preferences and schedules (O'Connor, 2008). ICTs provide a wide range of tools to facilitate the transactions of potential guests both before and during the hotel accommodation. Customers can search for travel information, make online airline bookings, online room reservations and other online related transactions by themselves instead of relying on travel agents (Morrison, Jing, O'Leary, & Lipping, 2001).

In addition, while in the hotel the guests can access ICT components like wireless Internet, dining table reservation system, electronic point of sale devices, automated teller machines, security systems and entertainment systems to their comfort. ICTs provide the opportunity to reduce uncertainty as well as enhance the quality of trips. These are achieved because customers are able to conduct deep research on each trip and the more information accessed the greater the likelihood to meet, serve and exceed customer's expectation.

Methodology

A quantitative approach in the form of a survey was taken to execute this study. Both an online and a self-administered survey method were utilized to collect the data. The unit of analysis was at the firm level and the targeted survey respondents were guests who had recently visited a Bahamian hotel. The approach of referrals was used to compile the list of respondents to participate in the online survey, whilst two research assistants were deployed to various hotels in an effort to conduct the self-administered survey. For the online survey a total of 134 emails were distributed, but only 45 were completed and analyzed. This gave a 33.6% response rate. In addition, the two research assistants were able to get 120 completed surveys during the period with four (4) being discarded due to incomplete data. So within this batch only 116 were analyzed. As a result, a total of 161 surveys were analyzed using descriptive and inferential statistics.

Statistical package for the social sciences (SPSS) was used to do the data analysis. SPSS was selected based on its popularity (Hair, Black, Babin & Anderson, 2010). The survey instrument had 32 questions which were anchored on a 5-point Likert scale, which ranged from 1 being strongly disagree to 5 being strongly agree (see Appendix A for the survey instrument). The independent and dependent variables were derived from Sirirak, Islam and Khang (2011) study in which they investigated the influence of ICT adoption on hotel performance in Thailand. ICT components were broken down into room division, food and beverage, back office and in-room, while five variables namely room quality, general amenities, business services, value-security and staff service quality were used to measure customer satisfaction.

Findings and discussion

The large majority of the respondents were Bahamian with 38.9% of the respondents being males and 61.1% being females. The majority of the respondents, approximately, 52% were 35 years of age and younger, followed by 17% being between the ages of 35-45 years, 16% between 46-55 years and finally 15% were 55 years and older. The majority of the guests (76.4%) stayed at Bahamian hotels for vacation, followed by 17.2% for business related reasons and 6.4% for business and vacation. In terms of hotel size, approximately 58%, 24% and 18% of the hotels had between 151-200 rooms, 100-150 rooms and less than 100 rooms respectively.

The reliability tests as shown in Table 1 outlines that both the ICT component and customer satisfaction constructs were internally reliable because the readings were above the 0.70 threshold (Chin, 2010). This means that the survey items are good measure for their respective constructs. Table 2.1's regression results revealed an F-test of 7.840 with an associated significance value of zero, which thereby shows significance at the 1, 5 and

10 percent level. Based on this result, it can be concluded that there is a significant linear relationship between the adoption of ICT components and total customer satisfaction at all levels of significance. The adjusted R squared value (2) in table 2.1 specifies that 66.7 percent of the variation in total customer satisfaction is explained by the variation in the availability of ICT component scales. In other words, approximately 67% of customer satisfaction can be explained by the different ICT components. As an extension to this research, one could find how other factors such as, the hotel ranking, the level of hotel maturity or culture could be considered and incorporated into the research in an effort to provide richer insights. In looking at the result of the multiple regression in Table 2 only two out of four independent variables were found to be statistically significant at the 1 percent level of significance. These were the availability of In-Room ICT components and General/ Back Office ICT components. It is not surprising that back office and in-room ICT components were found to be significant, although previous studies included the food and beverage component. These findings are in alignment with previous studies (Choy & Chu, 2001; Kim & Ham, 2006). The statistical insignificance of rooms division could be explained with the widely held view that ICT changes nothing in the hotel industry because hospitality requires the interaction of hotel staff and guests to drive guest satisfaction (Yousaf, 2011). This view is even more applicable in rooms division which deals with online check-in/out, online expenditure status reports and housekeeping management. There exist the possibilities of the lack of clarity regarding how ICT in these areas can impact guest satisfaction because the work in these areas is usually perceived to be highly human intensive.

In accordance with the research model, the researcher seeks to investigate how each ICT component affects Customer Satisfaction. These results are tabulated in table 3. Under hypothesis 1, the results show that the In-Room ICT Component does in fact explain customer satisfaction, with a 38.8% explanatory power. If the In-Room ICT Component was equal to zero, then the guests would be on average satisfied with a coefficient of 28.809 on a 70-point scale. If the component was not equal to zero, then for a 1-point increase in the In-Room ICT Component, customer satisfaction increases by 6.295 ceteris paribus.

Under hypothesis 2, the results show that the Room Division ICT Component does in fact explain customer satisfaction, with a 17.6% explanatory power. If the Room Division ICT Component was equal to zero, then the guests would be on average satisfied with a coefficient of 43.260 on a 70-point scale. Customer satisfaction is therefore less dependent on Room Division ICT Component, compared to the In-Room ICT Component. If the component was not equal to zero, then for a 1-unit increase in the Room Division ICT Component, customer satisfaction increases by 2.826 ceteris paribus.

Under Hypotheses 3 and 4 can be interpreted similar to that of hypotheses 1 and 2. The hypotheses show that 26.9% and 36.9% of the variation in Customer Satisfaction can be explained by the Food and Beverage ICT Component and the General/Back Office ICT component respectively.

All hypotheses in table 3 showed statistical significance for the parameters included in the model. The F-test generally checks for a relationship between the dependent and independent variables. For all the hypotheses, the F-tests were generally large and statistically significant. Further analysis was done to ascertain which of the twelve ICT components had the greatest influence on customer satisfaction. Tables 4 and 5 outline the results, which shows that automated wake-up system and in-room television/entertainment systems, two determinants of the in-room ICT component classification, are the major determinants of customer satisfaction. Based on the results in Table 3, in-room ICT components were found significant at the 1 percent level of significance. Apparently, although the out-door amenities in Bahamian hotels are attractive it would seem like guests place a high value on the in-room entertainment.

Given the F-test of 7.840 with the associated significance value of zero that is significant at the 1, 5 and 10 percent level of significance, it can be concluded that there is a significant linear relationship between ICT components and customer satisfaction at the 1 percent level of significance. The model also specifies that all twelve ICT components explain 66.7% of the variance in customer satisfaction as shown in Table 4. Most of the ICT components did not add much value when examined in the model because most proved to be insignificant based on their associated t-test and significant value.

Only two out of the twelve ICT components were statistically significant in relation to customer satisfaction. These are:

1. Automated wake-up system--An in-room ICT component

2. In-room television--An in-room ICT component Deeper analysis was conducted to investigate the impact of demographic data like gender and size of hotel on customer satisfaction. Given the F-test result in Table 5 of 6.627 with an associated significance value of 0.000 that is significant at the 1, 5 and 10 percent level of significance, it can be concluded that there is a statistically significant linear relationship between the predictor variables (gender and hotel size) and being satisfied with the hotel accommodation. This is shown in Table 6.

Levene's test for equality of variance and a t-test for equality of means were conducted to assess if gender difference impacted customer satisfaction. The mean values for male and female were 4.25 and 4.48 respectively. In addition, the F-statistic and significance values for the Levene's test were 0.918 and 0.339 respectively. Also, the t-statistic and significance values in the t-test were -1.566 and 0.119 respectively. Based on these results, it was concluded that customer satisfaction does not differ across gender.

Based on the [R.sup.2] value in Table 6, the model specifies that 10.1 percent of the variance in satisfaction with hotel accommodation is explained by gender and size of hotel. Further studies could incorporate other demographic factors like purpose of visit and age of respondents in an effort to increase the value of the [R.sup.2]. To conclude our findings, the scatter plot in Figure 2 shows that there is a moderate positive correlation between the availability of ICT component and customer satisfaction. This means that as ICT components increase then customer satisfaction also increases. The graph shows a few noticeable outliers. Further studies could explore the reasons for these outliers.

Conclusion

The findings of this research are consistent with previous studies, which found a positive relationship between ICT components and customer satisfaction in hotels. This study is particularly important as it fills a gap in terms of the context of the Bahamas, which contributes to the discourse on developing country technology adoption levels. While the study is only generalizable to the extent that a destination bears similar characteristics to the Commonwealth of the Bahamas, it provides a platform for exploration into the readiness of businesses in these destinations to meet and exceed guest expectations and generate repeat business.

While the supply side of the discussion is very instructive, the findings of this study also extend to provide insights for destinations that attract similar types of tourists from similar generating countries. The moderate positive correlation between the availability of ICT component and customer satisfaction found in this study relates most significantly to in-room entertainment. This finding is intuitive to the extent that guests value the ability to be constantly entertained, but it is counter-intuitive to the extent that one component of in-room entertainment which was statistically insignificant was wireless Internet in the room. Such a finding is even more incongruent with the fact that more than 50% of the sample were below the age of 35. In exploring this phenomenon, the researchers concluded that in-room wireless Internet is such a normal part of existence for this demographic, that its presence does not create a high level of satisfaction, none-the-less, its absence would result in dissatisfaction.

The details of each component provide useful decision-making data, however a more holistic analysis of the creative use of ICTs to increase overall hotel performance and ultimately meet or exceed guest expectations should be the focus of hotel managers. Although guests may not come in direct contact with operational back office functions, they are aware that the smooth running of the back enhances their own experience, as evidenced by this dimension, along with in-room and food and beverage being significant factors in the study. Future research should seek to compare other developing destinations such as Dominica or Guyana, which attract a completely different type of tourist seeking for less automation and greater interaction with locals and nature.

The authors recognize that the research scope in this project is limited in two ways. Firstly, the Commonwealth of the Bahamas has some peculiarities, which limit the possibility for generalization of these results to destinations with similar characteristics to a Small Island Developing State, which is an archipelago and heavily tourism dependent (45% GDP contribution). Secondly, there is a limitation with the sample-size. It must be noted that while the 161 respondents captured to examine relationships between nine variables is sufficiently robust to inform decision makers, further validation of these results could be achieved with a larger sample size for future research.

From a Managerial perspective the findings are instructive in terms of highlighting the role of specific technologies in driving customer satisfaction. This is particularly crucial in the tourism industry where memorable occurrences and experiences can generate repeat business. Hotel Managers will now have a study that justifies future technological investments in alignment with guest needs and will therefore be able to integrate empirical approaches to decision making.

REFERENCES

Ansah, A.K., and Blankson, V.S. (2012). The use of information and communication technologies (ICT) in front office operations of Chain Hotels in Ghana. International Journal of Advanced Computer Science and Applications, 3(3), 72-77.

Athey, S. (2011). Use of the World Wide Web by the Portuguese accommodation industry. Information Technology & Tourism, 13(3), 191-204.

Aziz, A.A., Bakhtiar, M., Syaquif, M., Kamaruddin, Y., and Ahmad, N. (2012). Information and communication technology application's usage in hotel industry. Journal of Tourism, Hospitality, and Culinary Arts, 4(2), 34-48.

Bethapudi, A. (2013). The role of ICT in Tourism Industry. Journal of Applied Economics and Business, 1(4), 67-79.

Bowen, J. T., & Shoemaker, S. (1998). Loyalty: A strategic commitment. Cornell Hotel and Restaurant Administration Quarterly, 39(1), 12-25.

Brynjolfsson, E. (1993). The productivity paradox of information technology. Communications of the ACM, 36(12), 67-77.

Buhalis, D. (1998). Strategic use of information technologies in the tourism industry. Tourism Management, 19(5), 409-421.

Buhalis, D. (2003). e-Tourism information technology for strategic tourism management. Englewood Cliffs, NJ: Prentice-Hall.

Chin, W.W. (2010). How to write-up and report PLS analysis. Berlin-Heidelberg: Springer Verlag.

Cho, W., and Olsen, M. D. (1998). A case study approach to understand the impact of information technology on competitive advantage in the lodging industry. Journal of Hospitality & Tourism Research, 22(4), 376-394.

Choy, T.Y., and Chu, R. (2001). Determinants of hotel guests' satisfaction and repeat patronage in the Hong Kong hotel industry. International Journal OF Hospitality Management, 20, 277-297.

Connolly, D., Olsen, M., and Moore, R. (1998). The Internet as a distribution channel. Cornell Hotel & Restaurant Administration Quarterly, 39(4), 42-45.

Cooper, C., Gilbert, D., and Wanhill, S. (1998). John Fletcher a Rebecca Shepherd. Tourism: principles and practice, 2.

David, J.S., Grabski, S., and Kasavana, M. (1996). The productivity paradox of hotel-industry technology. Cornell Hotel & Restaurant Administration Quarterly, 37(2), 64-70.

DiPietro, R.B.,and Wang, Y. (2010). Key issues for ICT applications: Impacts and implications for hospitality operations. Worldwide Hospitality and Tourism Themes, 2(1), 49-67.

Dwivedi, M., Yadav, A., and Venkatesh, U. (2012). Use of social media by national tourism organizations: A preliminary analysis. Information Technology & Tourism, 13, 1-10.

Erawan, T. (2016). Tourists' intention to give permission via mobile technology in Thailand. Journal of Hospitality and Tourism Technology, 7(4), 330-346.

Fiestas, I. (2011). Constraints to private investment in the poorest developing countries - A review of the literature. Nathan, 1-34.

Gamble, P.R. (1988). Attitudes to computers of managers in the hospitality industry. Behaviour & Information Technology, 7(3), 303-321.

Gibson, P., and Swift, J. (2011). e2c: Maximising Electronic Resources for Cruise Recruitment. Journal of Hospitality and Tourism Management, 8(1), 61-69.

Goode, S. & Stevens, K. (2000). An analysis of the business characteristics of adopters and non-adopters of world wide web technology. Information Technology and Management, 1, 129-154.

Hair, J., Black, W.C., Babin, B.J., and Anderson, R.E. (2010). Multivariate analysis. New Jersey ,NJ: Pearson Educational International.

Ham, S., Kim, W., and Jeong, S. (2005). Effect of information technology on performance in upscale hotels. International Journal of Hospitality Management, 24(2), 281-294.

Hoontrakul, P., and Sahadev, S. (2004). ICT Adoption Propensity in the Hotel Industry: An Empirical Study. Available at SSRN 635942.

Hoontrakul, P., and Sunil, S. (2007). ICT adoption propensity in the hotel industry: An empirical study. Paper presented at the International Marketing Conference on Marketing & Society, Indian Institute of Management Kozhikode.

Ip, C., Leung, R., and Law, R. (2011). Progress and development of information and communication technologies in hospitality. International Journal of Contemporary Hospitality Management, 23(4), 533-551.

Jaforullah, M. (2015). International tourism and economic growth in New Zealand. Tourism Analysis, 20(4), 413-418.

Johnston, R., and Jones, P. (2004). Service productivity: Towards understanding the relationship between operational and customer productivity. International Journal of Productivity and Performance Measurement, 53(3), 201-213.

Jones, P. (1999). Operational issues and trends in the hospitality industry. International Journal of Hospitality Management, 18(4), 427-442.

Joukes, V., and Gerry, C. (2010). Website Effectiveness in Wellness Promotion by Portuguese Spas. Journal of Hospitality and Tourism Management, 17(1), 136-143.

Kim, H., Xiang, Z., and Fesenmaier, D.R. (2015). Use of the Internet for trip planning: A generational analysis. Journal of Travel & Tourism Marketing, 32(3), 276-289.

Kim, W., G., and Ham, S. (2006). The impact of information technology implementation on service quality in the hotel industry. Information Technology in Hospitality, 4(4), 143-151.

Kumar, P. (2001). Information and communication technology. New Delhi, India: University Science Press.

Law, R., and Au, N. (1999). A neural network model to forecast Japanese demand for travel to Hong Kong. Tourism Management, 20(1), 89-97.

Law, R., and Jogaratnam, G. (2005). A study of hotel information technology applications. International Journal of Contemporary Hospitality Management, 17(2), 170-180.

Leung, R., and Law, R. (2013). Evaluation of hotel information technologies and EDI adoption: The perspective of hotel IT managers in Hong Kong. Cornell Hospitality Quarterly, 54(1), 25-37.

Ma, J.X., Buhalis, D., and Song, H. (2003). ICTs & Internet adoption in China's tourism industry. Journal of Information Management, 23(6), 451-467.

Maswera, T., Edwards, J., and Dawson, R. (2009). Recommendations for e-commerce systems in the tourism industry of sub-Saharan Africa. Telematics and Informatics, 26(1), 12-19.

Mihalic, T., and Buhalis, D. (2013). ICT as a new competitive advantage factor - Case of small transitional hotel sector. Economic and Business Review, 15(1), 33-56.

Minghetti, V., and Buhalis, D. (2010). Digital divide in tourism. Journal of Travel Research, 49(3), 267-281.

Monterubbianesi, P.D., and Brida, J.G. (2010). Causality between economic growth and tourism expansion: Empirical evidence from some Colombian regions. Journal of Tourism Challenges and Trends, 3(1), 153-164.

Morrison, A.M., Jing, S., O'Leary, J.T., and Lipping, A.C. (2001). Predicting usage of the Internet for travel bookings: An exploratory study. Information Technology & Tourism, 4(1), 15-30.

Nyheim, P., McFadden, F. & Connolly, D. (2004). Technology strategies for the hospitality industry. Upper Saddle River, NJ: Pearson Prentice-Hall.

O'Connor, P. (2008). Managing hospitality information technology in Europe: Issues, challenges and priorities. Journal of Hospitality Marketing & Management, 17(1), 59-77.

Olifer, N., and Olifer, V. (2006). Computer networks, principles, technologies and protocol for network design. London, England: John Wiley and Sons.

Pan, B., Zhang, L., and Smith, K. (2011). A mixed-method study of user behaviour and usability on an online travel agency. Information Technology & Tourism, 13(4), 353-364.

Sahadev, S., and Islam, N. (2005). Why hotels adopt ICTs: A study on the ICT adoption propensity of hotels in Thailand. International Journal of Contemporary Hospitality Management, 17(5), 391-401.

Shang, J.K., Hung, W.T., Lo, C.F., and Wang, F.C. (2008). Ecommerce and hotel performance: three-stage DEA analysis. The Service Industries Journal, 28(4), 529-540.

Sheldon, P. (1997). Tourism information technology. New York, NY: Cab International.

Sigala, M. (2003). The information and communication technologies productivity impact on the UK hotel sector. International Journal of Operations & Production Management, 23(10), 1224-1245.

Siguaw, A., Enz, A., and Namasivayam, K. (2000). Adoption of information technology in US hotels: Strategically driven objectives. Journal of Travel Research, 39(2), 192-201.

Sirirak, S., Islam, N., and Ba Khang, D. (2011). Does ICT adoption enhance hotel performance?. Journal of Hospitality and Tourism Technology, 2(1), 34-49.

Tepeci, M. (1999). Increasing brand loyalty in the hospitality industry. International Journal of Contemporary Hospitality Management, 11(5), 223-230.

Tesone, D. (2006). Hospitality information systems and e-Commerce. Hoboken, NJ: Wiley.

Thompson, M., Cassidy, L., Prideaux, B., Pabel, A., and Anderson, A. (2017). Friends and relatives as a destination information source. Advances in Hospitality and Leisure, 13, 111-126.

Vitterso, J., Prebensen, N.K., Hetland, A., and Dahl, T. (2017). The emotional traveller: Happiness and engagement as predictors of behavioral intentions among tourists in Northern Norway. Advances in Hospitality and Leisure, 13, 3-16.

Wang, Y.C., and Qualls, W. (2007). Technology adoption by hospitality organizations: Towards a theoretical framework. International Journal OF Hospitality Management, 26(3), 560-573.

Wang, Y. C. (2008). Collaborative destination marketing: Roles and strategies of convention and visitor's bureau. Journal of Vacation Marketing, 13(3), 187-203.

Wei, S., Ruys, H.F., Van Hoof, H.B., and Combrink, T.E. (2001). Uses of the Internet in the global hotel industry. Journal of Business Research, 54(3), 235-241.

World Travel and Tourism Council. (2014). The WTTC report: Travel & Tourism. Nassau, Bahamas: World Travel & Tourism Council.

World Bank. (2014). Doing business 2015: Going beyond efficiency. The World Bank Group, 1-60.

Yousaf, A. (2011). The impact of ICT in the eyes of hotel managers (Cyprus). Sodertorn University.

Zhang, H., Cole, S., Fan, X., and Cho, M. (2014). Do customers' intrinsic characteristics matter in their evaluations of a restaurant service? Advances in Hospitality and Leisure, 10, 173-197.

Zhu, Q., Sarkis, J., and Lai, K. H. (2008). Confirmation of a measurement model for green supply chain management practices implementation. International Journal of Production Economics, 111(4), 261-273.

Andrew J. SPENCER (*), Delroy A. CHEVERS (**)

(*) University of the West Indies, Mona P.O., Jamaica, andrew.spencer80@gmail.com.

(**) University of the West Indies, Mona P.O., Jamaica, delroy.chevers@uwimona.edu.jm.

Received on October 25, 2017.

Accepted on March 9, 2018.
Table 1 Reliability results

Element                         Cronbach's Alpha  Number of Items

Availability of ICT components  0.931             12
Customer Satisfaction           0.935             14

Table 2 Regression Results with ICT components and customer
satisfaction

Number of sample points  Adjusted R Square  F-Statistics  Significance

161                      0.667              7.840         0.000

(*) The Independent variables are ICT Components and the Dependent
variable is Customer Satisfaction.

Customer Satisfaction = 1.623 + 0.305 [X.sub.1] + 0.037 [X.sub.2] +
0.095 [X.sub.3] + 0.220 [X.sub.4]

(Standard
Errors)        (0.154)        (0.042)        (0.029)  (0.038)  (0.046)

[T-statistic]  10.522] (***)  [7.326] (***)  [1.282]  [2.532]  [4.844]
                                                               (***)

(*) Note: (***) p [less than or equal to] 0.001 (*) Independent
Variables: [X.sub.1]: In-Room ICT Component
[X.sub.2]: Room Division ICT Component
[X.sub.3]: Food and Beverage ICT Component
[X.sub.4]: General/Back Office ICT Component

Table 3 Hypotheses results

Hypothesis 1
Customer Satisfaction
= 28.809 +
6.295 In-Room
ICT
Component
(Standard Errors)      (2.357)         (0.625)
[T-statistic]          [12.222] (***)  [10.073] (***)
                                       [R.sup.2]= 0.388
                                       F-Test= 101.457(***)
Hypothesis 2
Customer
Satisfaction = 43.326                  + 2.826 Room Division ICT
Component
(Standard Errors)      (1.163)         (0.483)
[T-statistic]          [26.497] (*)     (**) [5.853] (***)
                                       [R.sup.2]= 0.176
                                       F-Test= 34.260 (***)
Hypothesis 3
Customer
Satisfaction = 36.526                  + 4.251 Food & Beverage ICT
Component
(Standard Errors)      (2.097)         (0.554)
[T-statistic]          [17.416] (**)   (*) [7.673] (***)
                                       [R.sup.2]= 0.269
                                       F-Test= 58.880 (***)
Hypothesis 4
Customer
Satisfaction = 37.                     297 + 5.740 General/Back Office
ICT Component (Stand   ard Errors)     (1.656) (0.593)
[T-statistic]          [22.52          3] (***) [9.672] (***)
                                       [R.sup.2]= 0.36.9
                                       F-Test= 93.553 (***)

Note: (***) p [less than or equal to] 0.001

Table 4 Regression Results with ICT Components and Customer
Satisfaction

Number of sample points  Adjusted R Square  F-Statistics

161                      0.667              7.840(***)

(*) The Independent variables are ICT Components and the Dependent
variable is Customer Satisfaction
Note: (***) p [less than or equal to] 0.001

Table 5 Results of the ICT component variables on customer satisfaction

Variable                           Operational  Coeff.  T-Stats.
                                   Domain       (P)
Wireless Internet service          IR            1.841   1.417
Telephone service                  IR           -1.822  -1.312
Online check-in system             RD            0.547   0.431
Dining table reservation           F&B           1.565   1.021
Electronic point of sale           F&B          -0.136  -0.085
ATM in the hotel                   BO            0.689   0.501
Check daily expenditure online     BO           -0.510  -0.370
Security system in room            BO           -1.834  -1.275
Automated wake-up system           IR            3.531   2.143 (**)
In-room television                 IR            5.307   2.782 (**)
Business Center for printing       BO           -1.308  -1.031
Teleconferencing/Skyping facility  BO            1.573   1.177

Note: (**) p [less than or equal to] 0.05
Key: IR = In-room; RD = Room division; F&B = Food and Beverage; BO =
Back office

Table 6 Regression results with demographic data and customer
satisfaction

Number of sample  Adjusted R Square  F-Statistics  Significance
points
161               0.101              6.627         0.000

Table 7 Coefficient results with demographic data and customer
satisfaction

Variable              Coefficient ([beta])  T-Statistics  Significance

Gender of respondent  0.311                 2.168         0.032
Size of hotel         0.345                 3.827         0.000

Note: (**) p < 0.05; (***) p < 0.001
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Author:Spencer, Andrew J.; Chevers, Delroy A.
Publication:Journal of Tourism Challenges and Trends
Geographic Code:0DEVE
Date:Dec 1, 2018
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