Free The rise of Artificial Intelligence in Hospitality industry and its effects on customer satisfaction. Dissertation Example
The Rise of Artificial Intelligence in Hospitality Industry and Its Effects on Customer Satisfaction
Table of Contents
TOC o “1-3” h z u 1.0 Introduction31.1 Research Purpose PAGEREF _Toc515786609 h 31.2 Research questions32.0 LITERATURE REVIEW42.1 The history of artificial intelligence42.1.1 What is artificial intelligence (AI)42.1.2 The evolution of artificial intelligence4 2.2 The need for artificial intelligence in the hospitality industry…………………………5
2.3 AI in the hospitality the millennial era compared to other generations………………….5
3.0 METHODOLOGY63.1 Research philosophy6 3.2 Data used…………………………………………………………………………………..6
3.3 Primary data collection techniques73.3 Data analysis74.0 Conclusion7 4.1 Limitations………………………………………………………………………………….9
In the millennial era, the use of high-end technology in various aspects of life has become a common phenomenon that has been embraced and adopted by almost every industrial sector in the world’s economy. In particular, the application of Artificial intelligence in various industrial and service delivery sectors has become a forthcoming issue in today’s world. The agricultural sector, healthcare, military, business, education, and transportation sectors have all experienced tremendous growth and development in the application of Artificial Intelligence (AI) in these particular sectors (Victorino et al., 2005). Indeed, the hospitality sector is a highly competitive and relatively service delivery sector that calls for effectiveness and efficiency in service delivery. Innovation and technology development has become a major boost for increased efficiency and improved customer satisfaction in this particular sector. Through the introduction of application of AI technology in the hospitality industry, the stakeholders in the industry have reported a significant improvement in the levels of customer satisfaction over the recent years. For instance, the development of digital assistance, concierge robots, travel experience enhancers, and automatic data processing in the hospitality sector has completely revolutionized the industry based on customer experience and satisfaction. Such innovations and artificial intelligence technologies have had a significant impact on the general customer experience in hotels and their overall satisfaction. When the recent hotel innovations are named which include, towel-ferrying assistants, augmented reality applications and voice-automated assistants (Henderson, 2018), it all sounds like science fiction, but these innovations present the reality of the increasing application of AI in the hospitality sector.
This paper studies the influence of artificial intelligence in the hospitality industry and its effects on the different generations, that is, the millennials and other generations.
As mentioned earlier, the paper will try to answer the following research question:
How has the increased application of artificial intelligence in the hospitality industry influenced customer satisfaction across the millennials and other generations?
Numerous previous studies have addressed the issue of the rise of artificial intelligence in the hospitality sector. However, none of these studies have illustrated the effects of the AI techniques on customer satisfaction across different generations. As such, this paper intends to bridge this information gap.
Research question/ hypothesis
What are the effects of the application of artificial intelligence in the hospitality industry on millennials versus the other generations?
What are the views of millennials on artificial intelligence application in the hospitality sector?
How and to what extent has AI application in the hospitality industry influence customer satisfaction?
The rise of artificial intelligence technology employment in the hospitality sector can be linked to the competitive nature of the industry and the desire to achieve higher standards of customer satisfaction. The adoption of this technological advancement sector has received varying results across different generations. The topics concerned with the effects of AI on customer satisfaction across various generations is better explained in the literature review.
In the modern-day hospitality industry, innovations are driven by the stiff competition together with the demand to provide the highest customer satisfaction standards by the key players in this industry. In this case, there has been no better way to achieve this rather than through the employment of artificial intelligence techniques such as the voice-automated assistants, augmented hotel reality apps, and towel-ferrying robots. According to Pierce (2015), robots are ready to take over the hotel industry, for instance, the Henna-na Hotel found in Japan is entirely staffed with robots which have taken over peoples’ roles in this hotel. In the literature review, the history of artificial intelligence will be discussed, followed by a discussion on the need for AI in the hospitality industry, and finally, the effects of AI on the millennials compared to other generations will be discussed.
The history of artificial intelligence
2.1.1 What is artificial intelligence (AI)
Negnevitsky (2005) identifies John McCarthy as the inventor of the word Artificial Intelligence (AI). Since then numerous definitions have been developed to explain what artificial intelligence means. According to Marr (1997), artificial intelligence is the “study of complex information processing problems that have their roots in some aspects of biological information processing.” AI can is the scientific development of intelligent machines that are able to perform the tasks that were previously carried out humans effectively (Fox, 1986). According to Shi (2011), AI “is a branch of computer science and a discipline in the study of machine intelligence, that is, developing intelligent machines or intelligent systems imitating, extending and augmenting human intelligence through artificial means and techniques to realize intelligent behavior.”
2.1.2 The evolution of Artificial Intelligence (AI)
The history AI can be traced back to the classical philosophers’ era who termed ‘human thinking’ as a figurative system (Russell & Norvig, 2016). However, it was in 1956 at the Dartmouth College conference where the first actual issues regarding artificial intelligence were proposed. In the conference, one of MIT scientist identified as Marvin Minsky stated that “within a generation, the problem of creating artificial intelligence will be substantially solved” (Crevier, 1993). It is in this conference that the idea of artificial intelligence was born. From 1956 to the 70’s, the period represented the ‘golden years’ of computer technology and AI advancement as sophisticated machine languages and technologies were being developed every day. On May 12th, 1997, the artificial intelligence development was put into test when a programmed computer system (Deep Blue 2) was able to defeat the world’s best chess player, Gary Kasparov, to a six-game chess match (Turing, 2005). In the late 70’s and early 90’s, the period was characterized as the AI winters whereby the government from various countries and organization had slashed all the investments and funding on the AI research activities. However, since the beginning of the 21st century, the AI research and technological advancement have developed exponentially to all sectors of the global economy including the hospitality industry.
2.2 The need for artificial intelligence in the hospitality industry
In the hospitality industry, customer loyalty and customer relationship are the essential aspects that focus on effective service delivery through customers satisfaction. As such, there is a need to ensure consistent long-term customer relationship in the industry to achieve this. In the hospitality circles, robots, artificial intelligence tools, and automation will keep the labor costs in the industry down; it will assist the employees to become more efficient in the hospitality service delivery. Also, it will be vital in improving guest experience across all the generations (Carlino, 2017). For instance, the use of artificial intelligence tools is vital for data mining in this particular sector. The stakeholders in this sector need to understand customers’ choices; preferences tastes through the employment of artificial intelligence tools. Weaver (2016), describes the continued development and application of AI in the hospitality sector as a forthcoming renaissance that is imminent in this particular industry. Based on the competitive nature of this industry, hotels and other businesses will are forced to be innovative through to gain a significant competitive advantage in the market.
Therefore, detailed systematic information should be developed using artificial intelligence or data mining to acquire customer’s needs, behavior, and expectations. Four areas of customer management through data mining are as follows:
Customer Identification: Also known as customer acquisition that targets the population or market that could be potential customers or clients and increase the company’s profit
Customer attraction: After customer identification, the company makes efforts to attract the target customers. This is done by marketing through different forms, for example, digital adverting campaigns.
Customer retention: This represents the most crucial element of data mining and business growth. This has to do with customer profiling, including loyalty programs, complaints management, and one-to-one marketing (understanding customers’ needs and bringing positive change in their behavior).
Customer development: From customer retention, the available data can be used for customer development through the development of AI tools that suit the customer’s preferences (Azzalini, Walton, & Scarpa, 2012).
2.3 Artificial Intelligence in the millennial era compared to other generations
The millennials popularly identified as Generation Y comprises of individuals who are born between (1980-1994). Besides other economic, social and political factors, the millennial generation is marked by the great innovations, application and development of media technologies, digital technologies, and communications. The generation Y individuals have been born and raised in the digital era, as such, the effect of artificial intelligence application in the hospitality industry has been robust in this generation compared to their prior generation and other generations (Baiyun et al., 2018). These include the baby boomers, the silent generation, generation X, and the generation Z. Fromm & Garton (2013) illustrate generation Y as the largest and the most dominant generation of consumers ever. This translates to the hospitality sector, the recent boom in the application of AI sector has been widely felt by the millennials based on their familiarity with the technological environment.
Other generations, for instance, generation Z are too young to have an impact on the hospitality sector. For the individuals in the silent generation, generation X, and the baby boomers, the technological advancement, and application of AI has a minimal effect based on their little understanding of the digital era (Gustavo, 2013). Having experienced the whole digital era involvement, the millennials have witnessed a greater extent of the impact of AI technology in the hospitality sector. The millennials are a dynamic generation characterized by regular eating and outgoing activities which are all encompassed in the hospitality sector. In this case, AI has been integrated into most hospitality business to improve millennials guest experiences and customer satisfaction as the form the largest consumer market for these services compared to other generations.
After conducting the literature review, it is evident that there is a lot of literature concerning the application of AI in the hospitality industry. However, the is no literature available on the effects of the AI tools on the millennials compared to other generations. This dissertation could, therefore, offer to bridge the information gap that exists in this area.
The study on the effects of AI application on the hospitality sector on the millennials and other generations aims at exploring and comparing the effects of artificial intelligence used in the hospitality industry between the millennials and other generations.
As mentioned earlier, no previous academic research has sort to cover this topic. Therefore, this research will be exploratory to try and investigate the effects of the AI application in the hospitality sector.
3.1 Research Philosophy
The research in this paper will apply an inductive approach which will be based on two essential elements, that is, a case study of a specific sample in the hospitality industry concerned with the application of AI in the hospitality industry. In this case, the case study will review the Henna-na Hotel found Japan that is fully staffed with robots. Secondly, it will employ a quantitative approach to investigate the effects of AI application in the hospitality sectors for the millennials and other generations. The data collection will involve the use of questionnaires which will be provided to the hospitality industry customers from the millennials and other generations.
3.1 Data used
The research will rely on both the primary data and secondary data collected through questionnaires and other sources for theoretical development and formulation of the research conclusions. For the primary data, the researcher will provide questionnaires to the sample population of the hospitality industry customers. Through the questionnaires, the research will be able to source for data from a large group of participants within a short period. The secondary data from the research will include magazines, web pages, media images, and newspapers. The questionnaires will test the respondents’ knowledge of AI application in the hospitality industry, their opinion on the effectiveness of AI tools towards customer satisfaction, and present real-life case scenarios to the respondents. The data will be derived from millennials, who are people within (15-35 years) age bracket and individuals from generation X that is (40-50 years). The data will be from both male and female participants.
3.2 Primary data collection techniques
In this paper, the chosen primary data collection techniques will be through the use of questionnaires. Saunders (2011) defines a questionnaire as a system of data collection technique whereby a respondent is expected to answer similar questions in a predetermined sequence. For this case, this method will be relatively effective for this study based on the big sample data that will be required. Also, it will be able to incorporate respondents with tight or busy schedules. However, besides the strengths associated with the use of this method, it also has demerits which can affect the reliability of the data collected. These include lack of proper understanding of the questions presented in the questionnaire. These issues can be solved through implementation of alternative forms and internal consistency during the study to uphold the reliability of the primary data collected through the questionnaires.
The sample group of the questionnaires will be comprised of two groups, that is, the customers (both the millennials and individuals from other generations). The other group will be comprised of hotel managers in the hospitality sector. The customers (millennials and people from other generations) will be questioned about the effects of the rise of AI on guest experience and customer satisfaction. On the other hand, the managers will provide information on the effects of rising AI activities on the overall hotel industry ratings based on customer satisfaction.
3.3 Data analysis techniques
Once the data relevant to this study has been collected, it will be analyzed through the use of both the quantitative and qualitative data analysis tools. This will involve the application of statistical data analysis tools which include both the regression and correlation data analysis. In this case, these statistical tools will be able to determine the relationship between the increasing use of AI in the hospitality sector and the effects on the millennials and other generations. Secondly, the hypothesis relating to these variables will be tested through an F-test, Z-test and the analysis of Variance (ANOVA) to establish the significance of the variables present in this study.
The world is changing every day. Innovations have transpired in every sector in today’s economies. The hospitality industry has not been left behind as more innovations have been implemented to improve customers experience and satisfaction. Such innovations have had different effects across various generations. Several studies have touched on the growth and development of AI activities in the hospitality sector. However, there exists a wide information gap on the effect of the rise of AI activities in this sector across several generations, particularly, the millennials.
This study is challenged by the inexistence of previous literature on this topic that would provide more insights on the issues discussed. Secondly, the lack of geographical boundaries also limits the success of the study as it lacks specificity in its discussion.
Azzalini, A., Walton, G., & Scarpa, B. (2012). Data Analysis and Data Mining: An Introduction. Oxford: Oxford University Press.
Baiyun, G., Ramkissoon, A., Greenwood, R. A., & Hoyte, D. S. (2018). The Generation for Change: Millennials, Their Career Orientation, and Role Innovation. Journal of Managerial Issues, 30(1), 82-96.
Carlino, N. (2017). Automation, robots and artificial intelligence: How will they shape the industry?. Hotel Business, 10A-14A.
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Negnevitsky, M. (2005). Artificial intelligence: A guide to intelligent systems. Pearson Education.
Pierce, A. (2015). A Hotel Staffed by Robots. Tech Directions, 75(2), 8-9.
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Saunders, M. N. (2011). Research methods for business students, 5/e. Pearson Education India.
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Weaver, T. (2016). Artificial intelligence: The forthcoming hospitality renaissance. Publican’s Morning Advertiser, (8), 57.
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