Introduction
The hospitality industry is gradually embracing artificial intelligence as a measure to boost operations and to minimize costs. This technology can potentially change the industry entirely. Dirican (2015) maintains that the introduction of artificial intelligence into the hotel business has led to a paradigm shift. The technology has come at a time when hotels are increasingly being required to automate the majority of their processes in order to enhance service delivery and meet customer satisfaction. Indeed, automation has helped to drive revenue up, enhance the reputation of many facilities, and to improve overall customer experience.
Like most industrial systems, “the world of hotels revolve around a handful of solutions, all driven by intelligent chatbots and voice-enabled services” (Dirican, 2015, p. 568). Artificial intelligence has enabled hotels throughout the world to improve their services and operational systems to cope with changing consumer expectations. Today, hotels can utilize intelligence-based analytics to enhance the consumer experience. The introduction of artificial intelligence into the hospitality industry will help to reduce costs attributed to service delivery.
It will also assist in addressing the challenges attributed to operational dynamics of the sector. The motivation for this study is to assist hotels to profit from the functionalities of artificial intelligence. As many hotels begin to embrace the technology, this study is vital as it will serve as an eye-opener to its numerous benefits. It will not only be of significance to the hospitality industry but also to other business sectors.
Literature Review
The growth of the hospitality industry is founded on effective service delivery. According to Dirican (2015), artificial intelligence can allow hotels to automate customer care practices and internal processes, therefore minimizing service costs and optimizing operational expenses. The technology comprises of machine language capabilities that are valuable to customers and hoteliers. One of the factors that contribute to increased costs in the hospitality industry is the inability of management to cope with changing consumer demands. At times, hotels incur losses due to procuring services and products that are in little demand.
Ivanov, Webster, and Berezina (2017) argue that the incorporation of chatbot software into marketing and sales systems enables hotels to gather information regarding consumer tastes and preferences, existing offers, and client behavioral patterns. Machine learning in artificial intelligence uses information regarding past operations, as well as current changes in trends, to come up with precise responses, tailored propositions, and customer offers that suit the needs of clients and travel planners. In other words, the technology does not only improve customer services but also facilitates effective decision-making, thus minimizing possible losses.
The provision of personalized recommendations to hotel guests enhances their experience and minimizes operations costs. Artificial intelligence enables hotels to gather information that is helpful in anticipating the preferences of different customers. It goes a long way towards making sure that a hotel does not offer unnecessary services. Ivanov et al. (2017) posit that reduction of hospitality operation costs depends on the ability of a facility to predict future trends in consumer preferences and service offerings.
Artificial intelligence equips hotels with analytical capacities that are essential in determining the character of future clients or traveler’s, thus ensuring that they are offered the correct packages. The application of artificial intelligence at the Red Roof Inn, for example, has proved to be effective in cost reduction. The hotel chain uses the technology to anticipate changes that it can exploit to its advantage. In 2014, the facility used predictive analytics to gather weather and flight data (Ivanov et al., 2017). It used the information to anticipate flight cancellations and to target affected customers.
In the past, the provision of room services required hotels to hire many employees to cater to the needs of different customers. It contributed to the increase in operation costs of hospitality businesses. Artificial intelligence has enabled hotels to offer voice-enabled virtual assistance services, which are more cost-effective (Kisilevich, Keim, & Rokach, 2013).
Today, hotels do not need to hire many employees to provide in-room services to customers. Artificial intelligence supports voice technology, which allows hotels to offer excellent services to clients at low cost. Wynn Las Vegas is one of the hotels that have successfully reduced their operation costs through voice-enabled virtual assistance technology. It offers virtual assistance, which enables clients to order different services from the comfort of their rooms.
Theoretical Framework
The hospitality industry requires involving customers in decision-making to boost service delivery and minimize cost. Artificial intelligence allows hotels to interact with clients, gather feedback, and anticipate future changes in consumer demands (Xiang, Schwartz, Gerdes, & Uysal, 2015). This study will use the customer-integrated theoretical framework to discuss the significance of artificial intelligence in cost reduction in the hotel industry. Technology has facilitated the creation of open-source communities that allow organizations to involve consumers in the design, manufacture, and supply of products.
The growth of artificial intelligence has helped organizations to create business models that assist them in capitalizing on consumer integration. According to Xiang et al. (2015), many hospitality companies are focusing on enhancing service delivery to clients. The businesses do not only view clients as revenue generators but also vital assets that can aid in cost reduction. In the past, hospitality companies and their clients were loosely coupled.
Dirican (2015) claims, “A system is considered to be loosely coupled when its components do not have the same goals, react to the identical variables, and share similar temporality or culture” (p. 569). Hospitality companies are using artificial intelligence to align their goals with those of customers. It helps in ensuring that hotels provide products and services that meet consumer preferences, thus boosting profitability and minimizing operational costs.
Conceptual Framework
The proposal will use a resource-based conceptual framework to evaluate the role of artificial intelligence in cost reduction in the hospitality industry. The resource-based theory cites organizational assets and capabilities as the primary source of competitive advantage. In the hospitality industry, resources can either be tangible or intangible. The substantial resources comprise the physical and monetary assets. On the other hand, intangible assets are hard to quantify because they are not reflected in a company’s balance sheet (Dirican, 2015).
Literature regards a firm’s intellectual, human resource practices, employee skills, and organizational culture as the significant intangible assets of hospitality businesses. Technology, especially artificial intelligence, has proved to be an essential intangible resource that is revolutionalizing the hotel industry. The capabilities and brand images of the hotel companies change with time. Customer perceptions are critical to the reinforcement of brand image.
Consequently, hospitality businesses ought to understand consumer preferences to influence their opinions. Artificial intelligence supports predictive analytics, which enables hotels to anticipate the future consumer needs and address them on time. This matching of needs and services goes a long way towards influencing a client’s perception of a facility. Positive impressions drive the profitability of a hotel up and reduces operational costs. This proposal will utilize a resource-based view as the basis for evaluating how artificial intelligence reduces costs in the hospitality sector.
Research Objectives
The study seeks to determine the significance of artificial intelligence in the hospitality industry. The primary objective of the research is to establish if the technology helps to reduce operation costs. It intends to answer the question of whether the application of artificial intelligence minimizes the cost of offering services in the hospitality sector.
Hypotheses
The study will test two hypotheses. First, it will examine the conjecture that artificial intelligence saves the hotel industry the costs associated with employee salaries. Second, it will test the theory that the technology eliminates unnecessary processes, thus saving hotels the costs attributed to offering unnecessary services.
Study Design
The study will use descriptive research design to analyze the effectiveness of artificial intelligence in reducing costs in the hospitality industry. Descriptive research design responds to the questions about how, what, where, and when, which are related to a specific study problem. It enables researchers to understand the current nature of a phenomenon. The primary objective of this study is to determine the role of artificial intelligence in reducing costs in the hotel industry.
The study aims at understanding how the technology enables hospitality facilities to cut down on expenses attributed to service delivery. Thus, the descriptive research design is the most appropriate for this research. The study requires a combination of quantitative and qualitative data to test the hypotheses. Descriptive research facilitates the collection of both quantitative and qualitative information; hence it is suitable for this study.
Setting for the Study
Researchers must prepare thoroughly before embarking on any study. Preparation entails identifying the research question, the method of data collection, the duration of the study, and the participants, among other things. For this study, the researcher will use the survey to gather both quantitative and qualitative data. Hence, preparations will entail setting questionnaires to be used in the data collection. It is not possible to research many hospitality facilities due to time constraints and limited resources.
Hence, they will need to identify the hotels that will be used for the study. The researcher will contact the management of the hotels to seek authorization to conduct their investigation. Moreover, research participants will be selected and notified regarding the study in advance to enable them to prepare.
Research Instruments
Research instruments refer to the tools that researchers use to gather data. They may include surveys, questionnaires, and tests. In the current study, the researcher will require both quantitative and qualitative data to analyze the research hypotheses. Therefore, the study will use questionnaires as the primary instrument of data collection. One needs detailed information to understand how artificial intelligence helps to reduce costs in the hospitality industry. Consequently, the questionnaires will comprise open-ended questions to allow the participants to elaborate on their responses. The questionnaire that will be used for the study is as follows:
- What do you understand by the term artificial intelligence?
- Has your company invested in artificial intelligence?
- How did employees respond to the introduction of the technology?
- Can you describe the type of artificial intelligence used in your company?
- Does your company benefit from the technology?
- How has investment in artificial intelligence affected service delivery?
- Has the technology facilitated cost reduction? If yes, describe how?
Sampling Design and Sample Size
The study will use a non-probability sampling technique. The researcher will apply a convenience sampling method to select the participants. Etikan, Musa, and Alkassim (2016) argue that the sampling technique depends on, “the convenience of the researcher in accessing the respondents and the expediency of the participants in providing the required information” (p. 2). Hotels will be selected based on the duration that they have used artificial intelligence. Facilities that have implemented the technology recently will not be considered because they cannot provide comprehensive and accurate information regarding the impact of artificial intelligence. The researcher will gather information from the management of five different hotels. It will be difficult to investigate more facilities due to time constraints.
Ethical Issues
The study will gather critical information about hotels, which might compromise the performance if leaked to rival facilities. Thus, the researcher will need to guarantee that all data remains confidential. Only authorized persons will have access to the data. Additionally, information regarding the name of the hospitality facility will not be disclosed to guarantee privacy.
Data Processing
A descriptive research design yields both qualitative and quantitative data. Hence, this study will use descriptive statistical techniques and thematic network analysis to process the collected data. The analytical approach will help to process quantitative information. The method will use measures like mean, mode, and median to describe the correlation between different variables. Conversely, the thematic analysis will help to code qualitative data from various hotels and establish common themes.
Proposed Chapters
The report will comprise four chapters. Chapter One will encompass the introduction to the study. Chapter Two will constitute a literature review of artificial intelligence and its role in cost reduction. Chapter Three will describe the research methodology. Chapter Four will represent the data analysis, findings, and conclusion of the study.
Problems and Limitations
One of the major issues facing this study is the unavailability of literature that discusses the application of artificial intelligence in the hospitality industry. The researcher will rely on information about other sectors and relate it to the hotel industry. Limited resources and time constraints are the primary limitations of this research. The researcher will use a small sample size, which might not give adequate data to produce a comprehensive report.
References
Dirican, C. (2015). The impacts of robotics, artificial intelligence on business and economics. Procedia – Social and Behavioral Sciences, 195(1), 564-573.
Etikan, I., Musa, S., & Alkassim, R. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1-4.
Ivanov, S., Webster, C., & Berezina, K. (2017). Adoption of robots and service automation by tourism and hospitality companies. Revista Turismo & Desenvolvimento, 27(1), 1501-1517.
Kisilevich, S., Keim, D., & Rokach, L. (2013). A GIS-based decision support system for hotel room rate estimation and temporal price prediction: The hotel brokers’ context. Decision Support System, 54(2), 1119-1133.
Xiang, Z., Schwartz, Z., Gerdes, J., & Uysal, M. (2015). What can big data and text analytics tell us about hotel guest experience and satisfaction? International Journal of Hospitality Management, 44(1), 120-130.