TECHNOLOGY-ENABLED GUEST EXPERIENCE, SMART HOTEL MANAGEMENT, AND SERVICE PERSONALIZATION

TOPIC: TECHNOLOGY-ENABLED GUEST EXPERIENCE, SMART HOTEL MANAGEMENT, AND SERVICE PERSONALIZATION

TOPIC IS SUITABLE FOR:
1-Department of Hospitality and Tourism Management
2-Department of Business Administration
This research material contains:
1-Chapter One to Five
2-Recent References/citations
3-Tables in Chapter Four
4-Accurate Data Analysis
5-Table of Contents
6-Questionnare

ABSTRACT
This study was carried out to examine Technology-Enabled Guest Experience, Smart Hotel Management, and Service Personalization in Hotels using Eko Hotels and Suites, Lagos State, Nigeria as a case study. The study was specifically carried out to determine the relationship between automated check-in/check-out systems and service quality in hotels, assess the relationship between smart room technologies and comfort and convenience in hotels, examine the relationship between digital payment systems and repeat purchase in hotels, and determine the relationship between energy management systems and positive reviews in hotels. The study employed the descriptive survey research design. Hence, the questionnaire was used for data collection, while the data collected were analyzed using mean and standard deviation for descriptive statistics and Simple Linear Regression for hypothesis testing using SPSS version 27. A total population of 1,250 respondents was used while a sample size of 303 respondents was selected using stratified and purposive sampling techniques, with 288 valid responses retrieved for analysis. The participants consisted of both employees and guests of Eko Hotels and Suites, Lagos State. From the responses obtained and analyzed, the findings revealed that automated check-in/check-out systems significantly influence service quality at β = 0.721, R² = 0.520, P = .000. The study also showed that smart room technologies have a significant relationship with comfort and convenience at β = 0.694, R² = 0.482, P = .000. Likewise, digital payment systems significantly influence repeat purchase behavior at β = 0.708, R² = 0.501, P = .000, while energy management systems significantly affect positive reviews at β = 0.701, R² = 0.491, P = .000. The study therefore recommends that hotel management should invest in advanced automation systems, expand smart room technologies, enhance secure digital payment platforms, and strengthen energy-efficient systems to improve guest experience, customer loyalty, and overall hotel performance.
Keywords: Technology-Enabled Guest Experience, Smart Hotel Management, Service Personalization, Hotel Service Quality, Customer Satisfaction.

CHAPTER ONE
INTRODUCTION (Preview)
1.1 Background to the Study
Digital innovation has been changing the very definition of structures and processes for delivering service in the hospitality sector. In today's digital era, technology has become a significant part of the hotel business as it supports the seamless interaction between guests and service providers by using a range of technology-enabled guest experience systems, including mobile check-in, self-service kiosks, artificial intelligence-powered chat interfaces and IoT-enabled room controls. The hospitality industry is becoming a more connected digital environment where guests' interactions are controlled by smart technology to make them more responsive and convenient (Buhalis and Moldavska 2021). Chen, Tzeng, Tham, and Chu, (2021) also elucidate that the introduction of smart technologies into the hospitality service has transformed the concept of “service encounter” and introduced automation and responsiveness to the core service processes. Wilson (2025) stated that these technical advancements have raised guests' expectations, including for speed, personalisation, and accessibility of services. Moreover, Singh, Raheja, and Sharma (2023) highlight that while digital transformation in the hospitality industry involves enhancing operations, it also requires a new approach to value creation and delivery to customers. In this way, Hiezl and Gyurácz-Németh (2025) point out the fusion of smart systems and user-centered design has led to more adaptive and immersive experiences for guests in a hotel setting. These developments together represent a move towards a more technologically-enabled hospitality system where the guest experience is increasingly influenced by the use of technology and intelligent service platforms (Buhalis and Moldavska, 2021; Chen, Tzeng, Tham, and Chu, 2021).
Moreover, the development of smart hotel management systems and service personalization approaches has also extended the operational and strategic potential of smart hotels in today's hospitality services world. Ali, Şener, Petkovic, Cavusoglu, and Alotaibi (2026) define smart hotel management as the integration of various digital technologies that enable automated decision-making, optimization, and real-time coordination of hotel services. Agina, Okocha, Umeokwuaka and Esonu (2026) opined that these systems allow the hotel to effectively manage guest data, which helps them provide personalized services to guests based on their preferences and behaviour. Youssofi, Jeannot, Jongmans, and Dampérat (2023) also note the shift of personalization practice in the hospitality sector toward a more data-driven approach, as service providers leverage AI to predict customers' needs and improve their service. Wilson (2025) also validates that personalization technologies are essential for hotel customer relationship and enhancing customer valued services. Concretely, these innovations can be seen in the increasing use of smart infrastructure in the hotel industry in urban areas like Lagos, Nigeria, where technology is increasingly being incorporated into service delivery systems. This evolution highlights the shift towards intelligent hospitality ecosystems, where technology can enhance guest experiences and optimize hotel operations, and both factors contribute to service personalization (Ali, Şener, Petkovic, Cavusoglu, and Alotaibi, 2026; Agina, Okocha, Umeokwuaka, and Esonu, 2026).

1.2 Statement of  the Problem    
Digital transformation in the hospitality sector is becoming more of a strategic tool for gaining better business efficiencies and creating a better experience for customers. In the context of Modern Hotel Operations, Guest Experience, Smart Hotel Management and Service Personalisation are key aspects of modern hotel management that allows hospitality businesses to keep up with the changing demands of their customers and stay relevant in the modern era. Digital technologies provide a better way of engaging with customers and delivering better services, while technology-driven hospitality services enable better, seamless, and efficient guest experiences. Intelligent management systems have also become important for enhancing hotel operations, while service personalization has gained increasing attention as a means of strengthening customer satisfaction and loyalty. Such developments are clear indications of the role of technological innovations in the hospitality industry as it affects the world today, particularly Nigeria.
While there is an increasing use of digital technology in the hotel industry, it is yet unclear how the three dimensions of technology-enabled guest experience, smart hotel management, and service personalization would impact service outcomes individually and collectively in Nigerian hotels. The ultimate goal for the implementation of intelligent technologies should be to create seamless guest interactions, efficient hotel operations, and highly personalized service experiences that enhance customer satisfaction and improve organizational performance. However, the adoption and impact of these technological innovations appear to vary across hospitality establishments. Digital innovations are increasingly being adopted in Nigerian hotels, yet the effectiveness of smart technologies largely depends on how well they are integrated into hotel operations. This disparity between the expected benefits of technology adoption and actual operational outcomes underscores the need for further empirical investigation within the Nigerian hospitality sector.
Another important concern that requires attention is the manner in which technology-enabled guest experience, smart hotel management, and service personalization interact within the Nigerian hospitality environment. Existing studies have largely examined these concepts independently or within broader international contexts, thereby providing limited insight into their combined influence on hospitality service delivery in Nigeria. Research has explored technology-facilitated guest interactions and service personalization as mechanisms for enhancing customer engagement, yet little attention has been given to understanding how these variables collectively shape operational effectiveness and guest satisfaction in Nigerian hotels. Consequently, a contextual and empirical gap remains regarding the integrated influence of these technological dimensions on hospitality performance. This study seeks to address that gap by examining the relationship among technology-enabled guest experience, smart hotel management, and service personalization in Nigeria, with a particular focus on generating evidence that can contribute to both academic discourse and hospitality management practice.
1.3 Objective of the Study
The main purpose of this study is to investigate technology-enabled guest experience, smart hotel management, and service personalization case study of Eko Hotel Lagos State. The specific objectives of the study seek to measure the following:
1.Automated check-in/check-out systems and service quality.
2.Smart room technologies and comfort and convenience.
3.Digital payment systems and repeat purchase.
4.Energy management systems and positive reviews.
OTHER PARTS OF CHAPTER ONE INCLUDE:
1.4 Research Questions
1.5 Research Hypotheses
1.6 Significance of the Study
1.7. Scope of the Study
1.8 Operational Definition of Terms

CHAPTER TWO
REVIEW OF LITERATURE (Preview)
This chapter critically examines relevant literature that would assist in explaining the research problem and, furthermore, recognizes the efforts of scholars who had previously contributed immensely to similar research. The chapter intends to deepen the understanding of the study and close the perceived gaps. This chapter, therefore, focuses on the concept of technology-enabled guest experience, the concept of smart hotel management, types of digital technologies used in hotel operations, the role of technology in service delivery, service personalization, benefits and challenges of technology adoption in hotel management, and the relationship between technology-enabled guest experience, smart hotel management and service personalization etc. The chapter is sub-grouped into the following major headings:
2.1 Conceptual Framework
2.2 Theoretical Framework
2.3 Empirical Review
2.4 Summary of Literature Review

CHAPTER THREE
RESEARCH METHODOLOGY (Preview)
Presented below is a snapshot of key areas of the study methodology, the full and detail chapter three methodology is contained in the instant download document.

Research Design: The study adopted a descriptive survey research design.
Population of the Study: The population of the study comprises employees and guests of Eko Hotels and Suites, Lagos State, Nigeria.
Sample Size Determination: The study adopted the Taro Yamane formula to determine a sample size of 303 respondents.
Sampling Technique: The study employed stratified and purposive sampling techniques to select the individual respondents.
Research Instrument: The study utilized a structured questionnaire titled “Technology-Enabled Guest Experience, Smart Hotel Management and Service Personalization Questionnaire (TEGESM-SPQ)” as the instrument for data collection.
Methods of Data Analysis: The collected data were analyzed using frequencies, percentages, means, and standard deviations to summarize and present the demographic characteristics of the respondents and their responses. Inferential statistics, particularly Simple Linear Regression, were used to test the hypotheses.
Full outline for chapter three;
3.0 Introduction
3.1 Research Design
3.2 Population of the Study
3.3 Sample Size
3.4 Sampling Technique
3.5 Instrument for Data Collection
3.6 Sources of Data
3.7 Validity of Instrument
3.8 Reliability of Instrument
3.9 Method of Data Collection
3.10 Method of Data Analysis
3.11 Ethical Consideration

CHAPTER FOUR: DATA PRESENTATION AND ANALYSIS
MAJOR FINDINGS (Preview)
The analysis results were presented in tables and charts. Based on the results obtained from the analysis, the following major findings were made:

i. The study found that automated check-in/check-out systems have a positive relationship with service quality in hotels, as evidenced by a grand mean of 3.64, which is above the acceptance benchmark of 3.00. The corresponding hypothesis test further showed a correlation coefficient (R) of 0.721, F-value of 310.845, and p-value of 0.000 (p < 0.05), leading to the rejection of the null hypothesis.

ii. The study found that smart room technologies have a positive relationship with comfort and convenience in hotels, as evidenced by a grand mean of 3.62, which is above the acceptance benchmark of 3.00. The corresponding hypothesis test further showed a correlation coefficient (R) of 0.694, F-value of 266.792, and p-value of 0.000 (p < 0.05), leading to the rejection of the null hypothesis.

iii. The study found that digital payment systems have a positive relationship with repeat purchase in hotels, as evidenced by a grand mean of 3.65, which is above the acceptance benchmark of 3.00. The corresponding hypothesis test further showed a correlation coefficient (R) of 0.708, F-value of 288.673, and p-value of 0.000 (p < 0.05), leading to the rejection of the null hypothesis.

iv. The study found that energy management systems have a positive relationship with positive reviews in hotels, as evidenced by a grand mean of 3.64, which is above the acceptance benchmark of 3.00. The corresponding hypothesis test further showed a correlation coefficient (R) of 0.701, F-value of 273.842, and p-value of 0.000 (p < 0.05), leading to the rejection of the null hypothesis.

CHAPTER FIVE: SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
This chapter covers the following outline:
5.1 Introduction
5.2 Summary 
5.3 Conclusion
5.4 Limitations of the Study
5.5 Contributions to Knowledge
5.6 Recommendations
5.7 Suggestions for Further Studies
Reference
Appendix

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