The Influence of Consumer Experience on Their Buying Behaviour

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In the last decade, the hotel industry has been performing well because of an increase in market destinations and a growing appetite for travel among young people. However, increased competition and a heightened level of uncertainty in the business environment have undermined this growth (Weerathunga et al., 2020). Consequently, to distinguish themselves from the competition many companies have adopted a customer-centric model of designing their operational plans to place the customer at the center of all marketing activities (Bravo, Martinez and Pina, 2019). Stemming from these measures, organizations aim to improve their bottom-line performance by predicting consumer behaviors through an analysis of customer experiences

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Consumer experience is a concept defining the impression that a person gets after consuming a good or service. Most consumers makes their purchasing decisions by balancing their emotional and functional characteristics in the decision-making plan (Bhatt, 2019). This statement is true for customers in the hotel industry because their experience starts before they arrive at a hotel and endures throughout their stay and after leaving the facility. Guest experiences that are derived from interactions with hotel staff as well as other patrons, also contribute to their overall experience.

Based on the above insights, customer experience refers to an intangible feeling defined by a broad set of emotions and attitudes that customers experience when they purchase a product or service. It can be influenced by favorable customer relationships, quality of services offered at a hotel facility and the environment it creates for its guests (Shahabudin, 2018; Roschk and Hosseinpour, 2020). The sensitivity of the hotel industry to customer views and attitudes make understanding customer experience an important part of managing hotel operations. At the same time, it is a key determinant of consumer purchasing behaviors in the industry.

Despite the presence of the expanding body of literature that defines customer experiences, there are growing calls for more investigations on this subject area because few researchers understand how unique experiences influence behavior. Particularly, there are incessant calls for a sectoral or contextual understanding of customer experience and its effects on behavior (Kumar, 2020; Robertson, Ferreira and Paschen, 2021; Fernández-Barcala, González-Díaz and López-Bayón, 2020; Nam and Kannan, 2020).

These issues have emerged from glaring gaps in the literature about the influence of consumer experience on buying behavior that have necessitated further inquiry into this subject area. Notably, among the deficiencies in this study is the link between experience and behavior in service-oriented industries like the tourism and hospitality sector (Park and Jeong, 2019). Central to these discussions is the nexus that perceptions about service value have played in understanding the relationship between consumer experiences and behaviors in the hotel industry.

Based on the above insights, the present research aims to explore the concept of customer experiences and its relationship with behavior. Customer experience design will be mentioned in the study to define the systems, processes, and procedures set up by companies to improve their overall user experiences. These experience designs have traditionally been linked with machine learning and the use of computing technologies to enhance the experiences of customers and improve the desirability and perceived usefulness of a product or service (Aluri, Price and McIntyre, 2019). Over time, the process has grown to include all aspects of a product or service that may affect people’s experiences when interacting with it.

Although experience designs are commonly associated with omni-channel experiences, the process is cross-disciplinary because a single design plan is inadequate to coverall all product and service categories that could impact customer experiences (Juaneda-Ayensa, Mosquera and Sierra, 2016; Harkison, 2017; Bèzes, 2019). To understand these issues, the Hilton hotel will be used as a case study to evaluate how clients’ experiences have shaped consumer behavior at the international hotel.

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Research Justification

Hilton is a global chain of hotels that spans across more than 100 markets around the world (Hilton Hotel and Resort, 2020). Established in 1919, the hotel has grown from a small franchise domiciled in McLean, Virginia United States, to a global conglomerate now operating more than 4,600 subsidiaries around the world (Hilton Hotel and Resort, 2020). Some of the firm’s key competitors include Marriott International, Hyatt Hotels, Four Seasons and Shangri- La International – all of which command about 27% of the global share of the hotel industry. In the US alone, Hilton commands about 9% of the total market share (Hilton Hotel and Resort, 2020).

The company’s business model is designed to attract luxury clients in major cities around the planet. Over the years, it has served millions of customers who are primarily attracted to the high quality services offered at the resorts. Due to its appreciation of customer experiences, Hilton has developed a service model that uniquely caters to it customer’s needs (Hilton Hotel and Resort, 2020).

Doing so has helped to lay a firm foundation for the development of competitive advantages that the multinational can use to differentiate itself from competitors. In line with this observation, marketers can exploit existing data to generate better customer experiences that could eventually increase loyalty to brands and boost their overall performance. Due to Hilton’s recognition of the importance of service experience to its overall corporate strategy, it emerges as the preferred case study for the present investigation.

Aims and objectives

The main aim of the current research is to explore the influence of customer experience on consumer behavior. The investigation will focus on understanding how consumer experience affects their purchasing decisions. The specific objectives of the research will be:

  1. To investigate the theories and models underpinning the concept of customer experience.
  2. To identify opportunities that exist in enhancing customer experience in the hotel industry.
  3. To identify barriers that prevent the development of better customer experience designs in the hotel industry.
  4. To discuss future trends and patterns in customer experience design.

Research Questions

  1. What are the major theories and models underpinning the concept of customer experience?
  2. Which opportunities exist for enhancing customer experience in the hotel industry?
  3. What barriers prevent the development of better customer experience designs in hotel industry?
  4. What are the projected future trends and patterns in customer experience design?

Outline of Chapters

This dissertation is categorized into five key chapters. The first one is the introduction section, which sets the stage for the investigation and provides a background of the research issue. The aim and objectives that will be met at the end of the investigation are also highlighted in this section of the paper. The second chapter is the literature review section, which contains an analysis of existing literature that is relevant to the research topic.

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In this chapter, relevant concepts and theories relating to customer experience and consumer behaviors will be highlighted with a gap in the literature highlighted at the end to justify the current study. The third chapter of this dissertation explains the methods used by the researcher to meet the objectives of the study. The justification for use of selected techniques will also be provided with key sections of this chapter being the research philosophy, approach, data collection methods, data analysis techniques, ethical implications of the study and techniques used by the researcher to safeguard the validity and reliability of the findings. The findings derived from the implementation of this technique are highlighted in the fourth chapter of this document and a discussion of how the evidence compares with existing data and body of evidence provided.

The last section of the dissertation will be the conclusion chapter and it will summarize key points mentioned in the investigation as well as outline the implications of the study on practice. Suggestions for improving the research will also be provided, including recommendations or future studies.

Literature Review

This chapter contains a review of existing studies that are relevant to the research topic. Attention is paid to explaining key concepts about customer experience and consumer behaviors that are relevant to the hotel sector. Key sections of this chapter also discuss existing theories relating to consumer behavior and customer experiences that are pertinent to the investigation. At the end of the chapter, the research gap, which justifies the current study, will be described.

Customer Experience

The concept of customer experience has been mentioned in business studies to describe the impression that consumers get after purchasing a product or service. Traditionally, the concept was appreciated for its entertainment value and it was commonly mentioned in research studies that explored research issues of similar nature (Kaur Sahi, Sehgal and Sharma, 2017). However, the current attention on customer experience stems from research investigations, which showed that consumers naturally, get an experience for buying a product or service. Therefore, it is up to companies to influence this experience, understand how it can work to their advantage, or leave customers to make their judgements without influence.

The latter is not a desired strategy because of the competitive nature of the hotel industry. This is why researchers, such as Klaus (2020), Jaiswal and Singh (2020) note that customer experience has the potential to influence industry outcomes in a sector dominated by a few large players.

Customer experience should be viewed as a continuous process because engagements among different groups of people occur at different stages of the purchasing process. For instance, in chapter 1of this document, it was reported that consumers acquire their experiences pre-purchase, during the purchasing process, and post-purchase. Research investigations have pointed out that the point of interaction between a customer and a hotel brand is mostly characterized by psychological and social experiences (van Lierop et al., 2019). Some scholars highlight the growing awareness of the modern consumer about his or her needs and requirements as a significant driving force for hotels to improve their customers’ experiences (Chylinski et al., 2020).

Indeed, according to Forrester (2015), consumers are in search of a seamless experience from the time they make a purchase, check-in to a hotel and leave the facility. In light of these views, Alnawas and Hemsley-Brown (2019) conducted a study on 420 customers and pointed out that customer experiences were mostly pegged on their emotional states during purchase. Therefore, the process of engineering better outcomes depends on a company’s ability to configure its services to enhance experiences.

The emergence of the experience economy has drawn most of the current scholarly attention on consumer experience to the forefront of consumer behavior studies. Particularly, scholars have been attracted to the need to investigate consumer behaviors through an acknowledgement of the need to examine knowledge through experiential learning. Consequently, customer experience has been regarded as one of the major driving forces of experiential marketing (Chiew, Mathies and Patterson, 2019).

Researchers have used to it to understand the behavioral dispositions of their clients because their experiences is a manifestation of it. Others have described customer experience as the cornerstone of the activities of various players in the hotel industry including staff, professionals, and managers because they recognize the need to provide quality services (Klaus, 2020; Jaiswal and Singh (2020). In today’s uncertain economy, customer experience has also been highlighted as one of the main differentiating factors for competitors.

Like any other sector of the economy, the hospitality industry is characterized by many complexities, including the intangibility of services and the subjective nature of experiences that consumers derive from it (Walden, 2017). The move towards commoditization of the service industry has spurred the trend further as companies compete with one another to provide the best experiences for their customers. A broad overview of research studies that have focused on understanding customer experiences shows that this is a relatively underdeveloped area of research relative to others, which have mostly focused on addressing service quality issues and strategies for boosting loyalty (Mody and Hanks, 2020; Siebert et al., 2020).

Regardless of the type of context under analysis, most consumers go through an experience when buying a product or service, thereby creating an opportunity for emotional engagement with their audiences (So and Li, 2020). In this regard, the analysis of customer experience is relevant in as far as the need to understand future behavioral intentions of customers is concerned.

Customer Experience Designs in the Hotel Industry

The concept of customer experience is synonymous with the hotel industry because this sector accounts for most of the literature developed in this subject area. For example, the hotel industry was one of the first economic sectors to introduce the star rating system to quantify customer experiences. Similarly, the industry was among the first to advocate for the consistency of product features as an integral part of their service plans. Seen from the activities of some of the major hotel chains, such as Marriott Hotel and Intercontinental, one of the major objectives of the hotel industry is to maximize positive customer experiences. This is why they are popular destinations for people holding some of their most memorable life events, including birthdays, wedding, honeymoons, and even corporate meetings or seminars.

Recent research studies have mentioned the growth and increased penetration of the internet as some of the major forces of change influencing customer experiences in hotels. For example, a group of researchers looks at digital channels as one of the major drivers influencing customer experiences today (Kumar, 2020; Robertson, Ferreira and Paschen, 2021; Fernández-Barcala, González-Díaz and López-Bayón, 2020; Nam and Kannan, 2020). Others consider physical locations as the main influencers of consumers’ experiences, including planning events where employees interact with customers face-to-face and placing billboards on highways to increase the awareness of consumers regarding a product or service (Jasrotia, Mishra and Koul, 2019). Regardless of the medium used, customers have to undergo specific stages of experience as outlined blow.

Stages of Customer Experience

Owing to the importance of customer experiences in the hotel industry, researchers have conducted investigations that highlight different stages that a client goes through before forming an opinion about a company’s products or services (Lemon and Verhoef, 2016). They are classified as follows:

Inspiration

This is the pre-service stage characterized by an inquiry about a hotel and its respective services. At this phase of customer experience, the consumer has not made up their mind about where to visit. Consequently, they may send an email, make a phone call or directly message a hotel to seek information about its products or services. The manner a hotel’s staff responds to such inquiry forms the first basis of their clustered experience (Jang et al., 2018). The information they get from this process creates room for the implementation of the second phase of customer experience, which is an evaluation of options.

Evaluation of Options

An evaluation of options is the second stage of customer experience and it is predicated on a review of data obtained from the first stage of inquiry or from other supplementary platforms, such as online forums where other customers have shared their experiences about the preferred destination (Chen, Cong and Kang, 2009). This process increases the confidence that a potential customer needs to make a purchase decision, which emerges as the third stage of developing customer experiences.

Purchase

The purchasing stage is the third phase of customer experience and it involves completing a financial transaction that may be aimed at booking a hotel for a specific number of days. Several considerations go into this plan, including a selection of the best deal, identification of hidden costs, and an acknowledgement of the convenience of making payments (Lemon and Verhoef, 2016). This customer experience stage may also involve pre-planning preparations that often follow a confirmation of the booking process. Some hotels may even issue a welcome note anticipating the arrival of the guests, thereby boosting their morale to visit the facility.

Stay

After the purchasing process is complete and the guests have booked into a hotel, the consumer experience shifts to their stay at the facility. This stage of the experience starts at the point where customers check in and occupy the premise allocated. Their use of hotel services and assessment of arrangements made during departure also play a critical role in defining their overall experience at the facility. This stage of customer experience paves the way for the last stage, which is engagement.

Engagement

This last stage of a customer’s hotel encounter and it sums up the overall experience that a person as acquired after visiting a hotel. Two possible outcomes could arise from the process: termination or advocacy of the relationship they have with the hotel. Usually such views are shared through word-of-mouth communications, via social media sites and other online forums (Ye et al., 2020; Hamilton et al., 2021; Quach et al., 2020).

Theories and Models Pertinent to Consumer Experiences

Information relating to theories and models was mostly obtained from the document review process. Indeed, understanding the theories and models underpinning consumer behaviors was one of the major objectives of this study. The expectancy disconfirmation and cognitive dissonance theories emerged as the most relevant to this discussion. Notably, the expectation disconfirmation theory explains the perceptions of customers regarding a product or service and outlines factors that may influence their levels of satisfaction (Evangelidis and Van Osselaer, 2018). This theory is closely related with the cognitive dissonance theory, which explores the divide between customers’ cognition and reality (Mao and Oppewal, 2010). The expectation disconfirmation theory also plays a critical role in explaining how customer experiences are derived from this relationship because it regards it as a product between their expectations and reality.

This dichotomy for analyzing expectation and reality stems from the cognitive dissonance theory, which highlights the conflict between the two concepts. Explained by researchers, such as Hinojosa et al. (2017), the cognitive dissonance theory is relevant to the current discussion because it highlights a conflict in people’s beliefs, values and behaviors about the purchasing process that may be uncomfortable to a customer.

For example, a smoker may experience cognitive dissonance when he or she is addicted to smoking and understand the negative health implications of doing so. The origin of the theory stems from similar circumstances because Leon Festinger founded it after observing the behaviors of members of a cult, which believed that the world was going to end at a specific date and sold their belongings in preparation for the event (Lindeman, Durik and Dooley, 2019). The intensely committed ones suffered the strongest levels of cognitive dissonance when this outcome did not materialize.

Two groups of people emerged from this process. The first one was made of people who did not believe that they were duped and reinterpreted the missed event as a sign of some higher power in play, such as God having mercy to destroy the earth because of their faithfulness and devotion to the cult (Marchetti et al., 2019). The second group of people is comprised of cult members who understood that they were duped and used the event as an “experience.” This cluster of faithfuls explain the relevance of the cognitive dissonance theory because it highlights the gap between expectation and reality. The wider the gap between these two elements of human expectation, the more impactful the experience will be. Therefore, people who are affected by the cognitive dissonance theory are likely to seek a reduction in discomfort by altering their behaviors.

Due to its relevance in predicting human behavior, the expectation disconfirmation theory has been successfully used by numerous researchers in different fields of science, including psychology and marketing (Olkkonen and Luoma-aho, 2019). Overall, the expectation disconfirmation theory assumes that consumers often have a set of expectation on how their product or service utility should be (Evangelidis and Van Osselaer, 2018). They also act as benchmarks for evaluating all other marketing processes. Therefore, customer experience is achieved when these two likelihoods suffice – a process that eventually leads to behavioral changes.

The above-mentioned characteristics of the cognitive dissonance theory shares similar properties with the expectation-confirmation model, which has been used by researchers to understand how consumer experiences affects satisfaction levels (Calvo-Porral, Ruiz-Vega and Lévy-Mangin, 2019). With its roots pinned in understanding how social media influences consumer behaviors, the expectation-confirmation model acknowledges that consumers have a right to make their own purchasing decisions based on their understanding of reasoning. However, expectations about service quality play a significant role in influencing this decision. Furthermore, the model suggests that the information received about a product or service is instrumental in influencing their purchasing decisions and behaviors.

The expectations that consumers acquire from purchasing various products and services depends on their expected levels of satisfaction. For example, customers who buy their goods online have a reasonable expectation that the quality of the product and the mode of delivery will be based on what is advertised on the platform. Such sentiments may influence the perception of consumers about the role and importance of technology in commerce (Mogaji, Soetan and Kieu, 2020).

Similarly, it affects the extent that this tool will influence purchasing behaviors. Most advertisers aim to improve customer satisfaction because a positive behavioral state would influence their shopping experiences in the same manner. Regardless of the communication medium used, if these expectations are met, consumers are likely to have a positive shopping experience and exhibit high levels of satisfaction (Ettinger et al., 2020). In this analysis, the expectation confirmation theory not only draws a link between customer experiences and their purchasing behaviors but also adds levels of satisfaction as an additional quality for predicting their response to the shopping experience.

Opportunities That Exist In Enhancing Customer Experience

The extant literature analyzed in this study have shown that customer experiences are mostly provided through two modes: physical and digital channels. Players in the hotel industry have mostly optimized the physical channels of enriching a customer’s experience and they involve an increase in accommodation options, revising of pricing plans, and linkage of service processes (Jocevski, 2020). However future opportunities that exist to harness the same experiences have most been observed in research studies that have advocated for the use of digital techniques as the new frontier of influencing customer’s experiences (Hsu and Chen, 2020).

Researchers, such as Xu (2019) and Stoldt et al. (2019), suggest that digital technologies, such as social media tools and online travel platforms, will play a bigger role in influencing future customer experiences. Stemming from this statement, the researchers encourage hotels to have a social media presence and use it as their main communication channel (Xu, 2019; Stoldt et al., 2019). Those that have such a platform are similarly encouraged to improve their social media marketing plans by integrating better computer graphics, providing more details and linkages to websites as well as engage with their customers in real-time to maximize their customer experiences.

The identification of digital marketing platforms as the new frontier for enhancing consumer experiences stems from studies, which have highlighted demographic shifts in the consumer base, which is increasingly being dominated by changing preferences for travel and accommodation (Stoldt et al., 2019). Particularly, these studies have mentioned changing attitudes and preferences of millennials, generation X and Ys will likely dictate the customer experience scores in the hotel industry (Liu, Wu and Li, 2019).

Of importance to this analysis is that this group of customers are technologically well informed and are likely to make their purchasing, stay and departure decisions online (Enam and Konduri, 2018). Furthermore, they have a higher probability of sharing their experiences online compared to any other group of travelers, thereby making their views more potent. Hotels stand a unique chance of controlling their experiences if they exploit digital marketing tools to increase customer preferences.

Barriers That Exist in Developing Better Customer Experience Designs

The process of improving customer experiences is often the talk in many hotels but few of them take effective actions in realizing this goal. This is because there are several obstacles associated with the process, including rigid organizational structures and a blatant refusal to change by some employees. Researchers have also mentioned this challenge by pointing out that many companies have management silos that can delay or hinder customer growth because they inhibit information flow and innovation (Smith and Besharov, 2019; Schwarz, Bouckenooghe and Vakola, 2021).

These barriers hinder the development of better customer experience designs and the problem has mostly been attributed to the tendency of people within certain departments to hold on to the information they have. Their common fear has always been that the systems, processes and procedures that they use may be disrupted by innovation or the development of new customer experience designs (Smith and Besharov, 2019). Others are also fearful of the fact that they could lose their status as a “golden child” when other people are allowed to participate in processes that influence customer experience.

Differences in operations, varied geographical locations of markets and dissimilarities in company sizes offer little hope that there is a common solution to all problems identified above. However, some researchers say positive changes could be realized if management engages all employees from the early stages of developing customer experience designs (Özcan and Elçi, 2020). Others claim that doing so is not enough as there needs to be constant communication among all parties involved throughout the product design process (Braun et al., 2019). Other researchers note that in the quest to improve the customer experience standards of a company, the actual quality of services offered may decline (Smith and Besharov, 2019).

This is because the ensuing changes may cause cracks in several areas of operational management. Similarly, there is likely to be inconsistencies in the manner departments communicate with each other during the process, thereby demanding patience from all parties concerned (Perrault, Hildenbrand and Rnoh, 2020). Therefore, it may be prudent for each department head to update their colleagues about their stand in the change management process and explain which aspects of the experience design process they are working on.

Another barrier that has been identified to hamper progress in the betterment of customer experience designs has been the lack of adequate resources to make changes. These resources may be in various forms including finances, time and skills. Relative to this discussion, Turner and Hesford (2019) say the resource shortage problem is not unique to the hotel industry because any business would have difficulty getting money to fiancé changes aimed at improving customer experiences. Therefore, the problem partly lies in the attitudes of management because some of them may be stuck to the old ways of doing things and fail to consider proposed changes as a priority. Regardless of the situation facing a company, it is still imperative for managers to look for the right resources to help in improving design plans.

The lack of a sufficient infrastructure for accommodating new technologies has also been cited as another impediment to the improvement of customer experience designs. This obstacle may cause different problems for an organization, including creating the inability to track feedback and performance (Smith and Besharov, 2019; Schwarz, Bouckenooghe and Vakola, 2021). The lack of proper technological resources also hampers the ability to connect different information points that are essential in the provision of quality customer experiences.

Fixing all these problems may come at a significant cost to an organization as some of them may require an overhaul of their entire design processes to accommodate proposed changes. However, some scholars are more optimistic of the situation by noting that most companies are not optimizing the capabilities of existing technologies (Perrault, Hildenbrand and Rnoh, 2020). Therefore, they propose that some of these new design changes be transferred to existing systems to save on time and costs.

Resistance to change has also been highlighted as another impediment affecting the development of improved customer experience design processes (Malhotra et al., 2020). This obstacle has been highlighted in several literatures, not only those that have focused on the hospitality industry( Oreg and Sverdlik, 2018; Malhotra et al., 2020). They suggest that it is common for everyone in an organization, including top-level managers, to be hesitant about change sometimes. Most employees harbor this fear because they are often comfortable doing things, as they know and are careful not to destabilize the status quo. Therefore, it comes as no surprise that even when managers are furnished with the resources to improve their customer experience designs, they may express some hesitation in doing so.

Summary

The evidence analyzed in this chapter shows the importance of understanding customer experience as a key tenet of organizational performance in the hotel industry. The literature examined so far suggests that consumer experience and behaviors have been analyzed as two independent concepts with a minimal understanding of their relationship outside their academic definitions and associations. The present study aims to contextualize the two concepts in the hotel industry to derive meaning on how consumer experience influence customer behavior.

Methodology

This chapter describes approaches employed by the researcher in conducting the study. The main areas addressed in this section include research philosophy, research approach, research design, target population definitions, data collection strategy, sampling techniques, data analysis methods, the risks and limitations of the study.

Research Philosophy

A research philosophy underscores a belief in the manner an investigation should be conducted and its findings interpreted. Three main research philosophies characterize academic investigations: positivism, interpretivism and realism (Ryan, 2018). Positivism is associated with the belief that research investigations should be conducted objectively as researchers play the role of social observers and keeping their views and opinions away from the overall analysis. Therefore, it stresses the need to minimize the influences of emotions and perceptive bias in interpreting findings. The interpretivism approach takes a different trajectory in its presentation of research processes because it suggests that research phenomenon can be viewed from multiple perspectives. In this regard, it proposes the need to accommodate subjective views of people’s reality because people have different interpretations of it (Hsiao et al., 2020).

Therefore, the multiplicity of views surrounding a research phenomenon is highlighted as a core tenet of the research philosophy. Comparatively, the realism philosophy highlights the need to recognize reality as being independent of the cognitive processes going on in the human mind. Relative to this reasoning it argues for the adherence to scientific approaches when addressing research issues.

Based on the above definitions of the three research philosophies, the interpretivism research philosophy was used in the present study because it accommodates diverse views in research, which are useful to the current investigation because consumer behavior is not static and varies from one person to another. Relative to this assertion the University of Delaware (2020), Pan and Gao (2009) say that consumer behavior is influenced by several factors, including a person’s culture, religion, and lifestyle. For example, some consumers often go on spending sprees every time they get surplus cash, while others choose not to even buy the most basic things when they have the same cash. The same behavior has been observed in the hospitality industry because some cultures are known for frequent travels, while others rarely indulge in the activity (Kim and Baker, 2019). Therefore, consumer behavior is subject to various psychosocial factors impacting behavior.

The justification for the use of the interpretivist research approach is informed by the complex nature of the research topic because it aims to examine the influence of consumer experiences on buying behaviors in the hotel industry. Relative to this statement, Stokes (2017) notes that researchers who recognize the complexity of the social world commonly use the interpretivism approach. The focus on experience is also important to this analysis because it cannot be understood from a monolithic perspective. Therefore, interpretivism emerged as the best approach to use in the investigation because of its recognition of multiple perspectives in research.

Research Approach

There are two main approaches used in research investigations: qualitative and quantitative techniques. Quantitative methods are associated with the collection of measurable variables, while the qualitative method is linked with studies that have subjective measures of assessment (Mohajan, 2018). This research investigation adopted both techniques in the collection and analysis of data within a broader framework of the mixed methods research approach. This research approach works by accommodating both qualitative and quantitative data in research investigations to have a broader understanding of a research topic (Lise and Elisabeth, 2019).

It was selected for use in the present study because it accommodates aspects of quantitative and quantitative reasoning (Brannen, 2017). For example, customer behaviors can be quantified using various measures, such as sales patterns and frequency of feedback, thereby necessitating the integration of quantitative data. Additionally, the present research investigation also contains aspects of qualitative reasoning because customer experiences are described in subjective terms and may vary from one person to another based on their expectations and culture. The social nature of this research investigation also justifies the use of the mixed methods approach because customer experience is multifaceted. The qualitative aspect of mixed method research was also adopted in this investigation because it allows researchers to collect in-depth data relating to consumer experiences (Conway, 2020).

This contribution of the qualitative research approach to the investigation is consistent with the views of Stacey (2019) who says that the research approach is appropriate to use when analyzing complex variables, such as people’s experiences and behaviors. Overall, the integration of qualitative and quantitative data in the research process justified the use of the mixed methods research approach.

Research Design

The case study research design was employed in this investigation to examine the influence of consumer experience on buying behaviors in the hotel industry. The case study was based on analyzing the customer experiences of Hilton hotel. This multinational was selected as the preferred case study because it has accumulated many data regarding customer experiences due to its rich history and experience in the hospitality industry. Furthermore, its business experience cuts across various markets and parts of the world, meaning that the researcher could gain access to a broader outlook of the research problem. Therefore, it is reasonably assumed that its managers would have a lot of information about consumer experience and are privy to the institutional knowledge that links them with consumer behaviors. Therefore, using the Hilton hotel as a case study helped the researcher to gain a critical and intricate understanding of the relationship between customer experiences and their behaviors.

Target Population

The target population for the current study was comprised of Hilton employees working in the US. Three hundred respondents were selected for the investigation to provide a reasonable sample of workers who understand the research problem and could give informed views about the research issues. The employees were all customer care staff and were selected to participate in the study because this position allowed them to have first-hand experiences interacting with customers (Troebs, Wagner and Herzog, 2020). Coupled with their understanding of the hotel’s service design, the respondents could help the researcher to understand how customer experiences vis-à-vis the Hilton’s service design affected consumer behaviors.

Data Collection

Several data collection techniques can be used in studies that employ the mixed methods approach. Sekaran and Bougie (2016) say that the choice for collecting data collection instruments to use in a study should depend on the resources available and objectives of the investigation. In line with this recommendation, this study will use a collection of both secondary and primary research sources.

Primary data will be obtained using questionnaires that were sent to the respondents virtually, while secondary data were structured to standardize the data obtained and to reduce the cognitive load that the informants had to bear while answering the research questions, as advised by Waring (2021) and Brothers (2020). Time constraints and resource limitations also justified the use of structured questionnaires because the inquiry simplified the data collection and analysis process. The large number of respondents who took part in the investigation made it difficult to use other time-consuming methods of data collection, such as interviews or focus group discussions.

The semi-structured questionnaires were divided into three main sections. The first one was aimed at collecting the demographic data of the participants. This section of the inquiry included the process of gathering data relating to their gender, age, education qualifications, and work experiences. They were included in the investigation because researchers have affirmed the role of personal factors in influencing consumer behavior. For example, researchers point out that age, gender and education qualifications influence consumer behavior and perceptions about service quality (Patten and Newhart, 2017; Morin, Olsson and Atikcan, 2021).

Similarly, associated research studies point to the effects of factors influencing a person’s social status, such as job positions and managerial experience, as being key drivers in the management of service quality issues (Žukauskas, Vveinhardt &Andriukaitienė, 2018). Therefore, it was integral to include these psychosocial aspects of the investigation in the data collection process through the integration of primary and secondary data.

The second part of the questionnaire gathered the respondents’ views regarding customer experiences, while the third part sampled their observations regarding customer behavior. To measure the intensity of their opinions and reactions to the questions, the questionnaires were structured to accommodate the 5-point Likert scale. This instrument categorizes respondents’ reactions into five categories: “strongly agree,” “agree,” “neither agree nor disagree,” “disagree,” and “strongly disagree” (see appendix 1). Comparatively, secondary data was included in the investigation to contextualize the information obtained from the primary data.

Additionally, certain aspects of the research objectives, such as discussions of relevant theories and models underpinning customer experiences and behaviors, were best addressed using secondary research. This type of information was obtained from reputable data sources, including books, journals and credible websites. Journal articles were sourced from known databases, including Sage Journals, Emerald Insight and Google Scholar. These outlets were used to obtain materials published within the last five years (2016-2020) that were integrated in the research process to provide context to the primary research data highlighted above. It was important to establish this exclusion criterion to obtain the most updated information about the research process. Keywords used in the search process, included “consumer experiences,” “consumer behavior,” and “Hilton Hotel.”

Sampling Strategy

The purposeful sampling method was used to recruit the research respondents who took part in the investigation. According to Kingsley and Robertson (2020), this sampling technique is heavily reliant on a researchers’ subjective opinions about who should participate in a study and who should not. Most of the researchers who use this technique rely on their sound judgement to make such decisions with little accountability to anyone else (Kingsley and Robertson, 2020).

This sampling technique was adopted in the present study because the researcher intended to get the views of employees who worked in a specific job category – customer service. Therefore, the objective of the study was the primary motivator for the use of the purposeful sampling method. Additionally, the sampling method was selected for use in the current study because of time and resource constraints. Drisko and Maschi (2016) support this reasoning by saying that the sampling method is one of the most cost and time effective techniques to use in recruiting informants. The sampling strategy was also selected for use because it accommodated intuitive reasoning in the research process, which was critical in interpreting the data.

Data Analysis

The Statistical Packages for the Social Sciences (SPSS) technique (version 23) was used to analyze information collected from the respondents. It was employed to understand correlations between variables relating to customer experience and consumer behavior. The SPSS method was also used in the study because other researchers have successfully used it to analyze data in various social science studies, as alluded by researchers, such as De Mooij (2019). The data analysis method was also used in the study because of its vast array of statistical analysis tools that were instrumental to the research investigation. The aim was to describe the profiles of the informants as well as estimate the significance of their demographic characteristics on their views about consumer experiences. Additionally, the SPSS method was integrated in the investigation because it helped to establish the relationship between customer experiences and consumer behavior.

Research Risks and Limitations

Research risks and limitations refer to variable aspects of the investigation that may affect the interpretation of the findings. Based on this definition, the researcher assumed that the respondents were giving their honest views and that their memory of customer experiences and buying behaviors was as depicted in the questionnaires. Respondent bias could also affect the credibility of the information obtained. It refers to the tendency of respondents to give inaccurate or false views about a research phenomenon based on their idea of what they think should be said, as opposed to what they believe is the case. Researchers have linked this type of bias to investigations where informants have to report findings by themselves (Shin, 2020; Rothman et al., 2020). Another limitation of the study is its relevance to the US hospitality industry.

It is crucial to recognize this limitation because Hilton operates in several countries around the world. Therefore, the findings of the study are only relevant to the US hotel industry. Researchers who have cited differences in consumer behaviors across regions and countries also allude to limitations on the generalizability of the findings of this report. For example, Sinha and Verma (2019) suggest that urban consumers have different buying behaviors from rural consumers and those from rich nations may have different purchasing trends from those in developing nations. Therefore, it is important to recognize such limitations when interpreting the findings.

Reliability and Validity of the Findings

The reliability and validity of a study’s findings refers to the ability to attain the same results if the experiment is repeated. To safeguard against these issues, the reliability of the findings was protected using the member-check technique. It works by sharing the results of the investigation with the informants to make sure that they are consistent with their original views (Birt et al., 2016). Researchers have successfully used this technique to safeguard the integrity of the findings they generate because it allows them to identify gaps or discrepancies in opinions between the respondents’ original views and those presented in the report (Brear, 2019; Caretta and Pérez, 2019). However, because the informants approved the findings through the member-check technique, it can be assumed that they are reliable.

Comparatively, the validity of a study is premised on the need to make sure that the research instrument used in the investigation collects the desired data. To safeguard this principle of the research process, the questions posed to the respondents were derived from a thorough review of the existing body of evidence regarding buying behaviors and consumer experiences. Therefore, issues relating to customer loyalty, satisfaction, turnovers and experiences were mentioned in the questionnaires because they were the most commonly cited concepts in the extant literature (KhajehNobar and Rostamzadeh, 2018; Kim and Baker, 2020; Mulki and Wilkinson, 2017). Therefore, it can be assumed that the questions posed to the respondents were valid.

Ethics of the Study

The use of human subjects in research investigations attracts several ethical issues aimed at protecting their interests (Woodfield, 2017). In this regard, this investigation was undertaken with strict adherence to the university’s ethical code of conduct involving the use of primary and secondary data. At the same time, the researcher observed several ethical rules outlined by Saxena (2019), including the protection of the respondents’ privacy, safeguarding their confidentiality, especially concerning their work positions, and the safe storage of data obtained from them. The participants were also not coerced to participate in the study because they did so voluntarily.

Furthermore, they were not given financial incentives to take part in it and were allowed to exit the investigation without any repercussions. The use of secondary research data in the present study also brought attention to the need to attribute the sources of information used to their original authors. This measure was taken to avid plagiarism and the misrepresentation of facts in the study.

Summary

This chapter shows that the research process was largely influenced by the interpretivism research approach because it accommodates diverse views about consumer experiences. The mixed methods approach was also employed to accommodate this diversity, as it allows for the collection of both primary and secondary data. Data was collected using surveys and interpreted using SPSS to provide primary data, while secondary information was included in the analysis to provide context of the original data. The ethical implications of adopting this research approaches were safeguarded and the reliability of findings protected using the member-check technique.

Findings and Discussions

This chapter highlights the results of the findings obtained from implementing the research techniques highlighted in chapter three above. To recap, the overarching aim of this study was to understand how consumer experiences affected buying behaviors in the hotel industry. Four specific objectives guided the investigation and they centered on investigating the theories and models underpinning the concept of customer experience, identifying opportunities that exist in enhancing this experience, identifying barriers that exist for developing better system designs and discussing future trends and patterns in developing experience designs. The findings of the primary research investigations are highlighted below.

Demographic Findings

As highlighted in chapter three of this document, the collection of demographic data comprised the first part of the inquiry process. This area of inquiry sought to find out the respondents’ personal characteristics, including their gender, age, work experience and educational qualifications. According to table 4.1 below, most of the employees who took part in the investigation were male (54.7%), while females accounted for 45.3% of the total sample. This distribution of respondents implies that there was a balanced view of the research issues from a gender standpoint. Stated differently, no one gender was overly represented in the sample.

Table 4.1 Gender Findings (Source: Developed by Author).

What is your gender
Frequency Percent Valid Percent Cumulative Percent
Valid Male 164 54.7 54.7 54.7
Female 136 45.3 45.3 100.0
Total 300 100.0 100.0

Comparatively, able 4.2 below highlights the characteristics of the employees according to their ages. Those who were aged between 18 and 30 years formed the largest group of participants (48.3%), while those who were aged above 60 years comprised the smallest group of informants because they only made up 1% of the total sample.

Table 4.2 Age Group Findings (Source: Developed by Author).

What is your Age?
Frequency Percent Valid Percent Cumulative Percent
Valid 18-30 145 48.3 48.3 48.3
31-40 70 23.3 23.3 71.7
41-50 49 16.3 16.3 88.0
Above 60 3 1.0 1.0 89.0
51-60 33 11.0 11.0 100.0
Total 300 100.0 100.0

The respondents’ education qualification was the third demographic variable investigated in the study. Table 4.3 below shows that the group of employees, which completed high school, formed the largest percentage of employees who gave their views in the study. This is because they comprised 56.7% of the total sample. Comparatively, those who had a diploma certificate formed the smallest group of respondents because they only made up 6% of the total number of employees who participated in the research.

Table 4.1 Education Qualification Findings (Source: Developed by Author).

What is your education qualification
Frequency Percent Valid Percent Cumulative Percent
Valid High School 170 56.7 56.7 56.7
Diploma 18 6.0 6.0 62.7
Undergraduate 51 17.0 17.0 79.7
Masters 61 20.3 20.3 100.0
Total 300 100.0 100.0

The last demographic variable that was investigated in this research related to the employees’ work experience. According to table 4.4 below, most of the respondents who took part in the study had worked in the organization for between two and seven years. This group of respondents made up 71.6% of the total sample of participants who took part in the study. Comparatively, the smallest number of employees who participated in the research either worked for less than two years (7%) or one year (8%).

Table 4.4 Work Experience Findings (Source: Developed by Author).

How long have you worked in your organization?
Frequency Percent Valid Percent Cumulative Percent
Valid Less than one year 24 8.0 8.0 8.0
Less than two years 21 7.0 7.0 15.0
2-5 years 103 34.3 34.3 49.3
5-7 years 112 37.3 37.3 86.7
More than seven years 40 13.3 13.3 100.0
Total 300 100.0 100.0

Impact of Gender on Employee Perceptions

As highlighted in table 4.5 below, age did not affect the respondents’ views regarding customer experiences and buying behaviors because none of the items on the questionnaire relating to these two variables had a significance value of less than P>0.05 which would imply that the age of the respondents did not affect their views on consumer experiences and behaviors.

Table 4.5 Impact of Gender on Employee Perceptions (Source: Developed by Author).

ANOVA
Sum of Squares df Mean Square F Sig.
Consumer Experiences Between Groups .574 1 .574 .899 .344
Within Groups 190.343 298 .639
Total 190.917 299
Consumer Experiences Between Groups .642 1 .642 .905 .342
Within Groups 211.345 298 .709
Total 211.987 299
Consumer Experiences Between Groups .006 1 .006 .012 .912
Within Groups 157.630 298 .529
Total 157.637 299
Consumer Experiences Between Groups .177 1 .177 .214 .644
Within Groups 246.610 298 .828
Total 246.787 299
Consumer Experiences Between Groups .708 1 .708 1.061 .304
Within Groups 198.689 298 .667
Total 199.397 299
Consumer Experiences Between Groups .054 1 .054 .285 .594
Within Groups 56.196 298 .189
Total 56.250 299
Consumer Experiences Between Groups .326 1 .326 .526 .469
Within Groups 184.404 298 .619
Total 184.730 299
Consumer Behavior Between Groups .169 1 .169 .500 .480
Within Groups 100.827 298 .338
Total 100.997 299
Consumer Behavior Between Groups .133 1 .133 .093 .760
Within Groups 424.813 298 1.426
Total 424.947 299
Consumer Behavior Between Groups .218 1 .218 .212 .645
Within Groups 306.169 298 1.027
Total 306.387 299
Consumer Behavior Between Groups 1.195 1 1.195 .766 .382
Within Groups 464.791 298 1.560
Total 465.987 299
Consumer Behavior Between Groups .003 1 .003 .003 .960
Within Groups 326.994 298 1.097
Total 326.997 299
Consumer Behavior Between Groups .072 1 .072 .120 .730
Within Groups 178.315 298 .598
Total 178.387 299
Consumer Behavior Between Groups .576 1 .576 1.173 .280
Within Groups 146.420 298 .491
Total 146.997 299

Impact of Age on Employee Perceptions

Similar to the findings highlighted above, according to table 4.6 below the respondents’ age had an insignificant effect on the views of the respondents because out of the 14 items posed to the respondents, only four had a significance value of less than P>0.05.

Table 4.5 Impact of Age on Employee Perceptions (Source: Developed by Author).

ANOVA
Sum of Squares df Mean Square F Sig.
Consumer Experiences Between Groups 2.470 4 .617 .967 .426
Within Groups 188.447 295 .639
Total 190.917 299
Consumer Experiences Between Groups 4.934 4 1.233 1.757 .137
Within Groups 207.053 295 .702
Total 211.987 299
Consumer Experiences Between Groups 13.969 4 3.492 7.171 .000
Within Groups 143.668 295 .487
Total 157.637 299
Consumer Experiences Between Groups 11.384 4 2.846 3.567 .007
Within Groups 235.403 295 .798
Total 246.787 299
Consumer Experiences Between Groups 3.915 4 .979 1.477 .209
Within Groups 195.482 295 .663
Total 199.397 299
Consumer Experiences Between Groups .788 4 .197 1.048 .383
Within Groups 55.462 295 .188
Total 56.250 299
Consumer Experiences Between Groups 2.943 4 .736 1.194 .313
Within Groups 181.787 295 .616
Total 184.730 299
Consumer Behavior Between Groups .898 4 .224 .661 .619
Within Groups 100.099 295 .339
Total 100.997 299
Consumer Behavior Between Groups 8.131 4 2.033 1.439 .221
Within Groups 416.816 295 1.413
Total 424.947 299
Consumer Behavior Between Groups 17.145 4 4.286 4.372 .002
Within Groups 289.241 295 .980
Total 306.387 299
Consumer Behavior Between Groups 30.533 4 7.633 5.171 .000
Within Groups 435.454 295 1.476
Total 465.987 299
Consumer Behavior Between Groups 7.657 4 1.914 1.768 .135
Within Groups 319.340 295 1.083
Total 326.997 299
Consumer Behavior Between Groups 2.619 4 .655 1.099 .357
Within Groups 175.767 295 .596
Total 178.387 299
Consumer Behavior Between Groups 1.725 4 .431 .876 .479
Within Groups 145.272 295 .492
Total 146.997 299

Impact of Education Qualifications on Employee Perceptions

According to table 4.7 below, the education levels of the employees sampled did not have an effect on their responses because out of the 14 questions posed to the hotel staff regarding consumer experiences and buying behaviors, only three had a significance value of less than P>0.05. This means that their education qualifications had little or no impact on their perceptions of these two variables.

Table 4.7 Impact of Education Qualifications on Employee Perceptions (Source: Developed by Author).

ANOVA
Sum of Squares df Mean Square F Sig.
Consumer Experiences Between Groups 6.472 3 2.157 3.462 .017
Within Groups 184.445 296 .623
Total 190.917 299
Consumer Experiences Between Groups 5.016 3 1.672 2.391 .069
Within Groups 206.971 296 .699
Total 211.987 299
Consumer Experiences Between Groups 7.551 3 2.517 4.964 .002
Within Groups 150.085 296 .507
Total 157.637 299
Consumer Experiences Between Groups 19.693 3 6.564 8.556 .000
Within Groups 227.093 296 .767
Total 246.787 299
Consumer Experiences Between Groups 1.980 3 .660 .990 .398
Within Groups 197.416 296 .667
Total 199.397 299
Consumer Experiences Between Groups 1.037 3 .346 1.854 .138
Within Groups 55.213 296 .187
Total 56.250 299
Consumer Experiences Between Groups 1.248 3 .416 .671 .570
Within Groups 183.482 296 .620
Total 184.730 299
Consumer Behavior Between Groups .365 3 .122 .358 .783
Within Groups 100.631 296 .340
Total 100.997 299
Consumer Behavior Between Groups 6.088 3 2.029 1.434 .233
Within Groups 418.859 296 1.415
Total 424.947 299
Consumer Behavior Between Groups 7.183 3 2.394 2.369 .071
Within Groups 299.204 296 1.011
Total 306.387 299
Consumer Behavior Between Groups 10.411 3 3.470 2.255 .082
Within Groups 455.576 296 1.539
Total 465.987 299
Consumer Behavior Between Groups 3.802 3 1.267 1.161 .325
Within Groups 323.194 296 1.092
Total 326.997 299
Consumer Behavior Between Groups .399 3 .133 .221 .882
Within Groups 177.988 296 .601
Total 178.387 299
Consumer Behavior Between Groups .493 3 .164 .332 .802
Within Groups 146.503 296 .495
Total 146.997 299

Impact of Work Experience on Employee Perceptions

The findings presented n table 4.8 below demonstrate that employee work experience had an effect on their perceptions of consumer experience and behaviors. This statement is supported by the fact that only one out of 14 items analyzed in the questionnaire had a significance value above P>0.05. This statement means that work experience was an important influencer of their views. This finding is consistent with research studies that have highlighted the impact of employee experience on work performance, attitude, perceptions and service quality (Kim and Qu, 2019).

Table 4.8 Impact of Work Experience on Employee Perceptions (Source: Developed by Author).

ANOVA
Sum of Squares df Mean Square F Sig.
Consumer Experiences Between Groups 10.785 4 2.696 4.415 .002
Within Groups 180.132 295 .611
Total 190.917 299
Consumer Experiences Between Groups 15.024 4 3.756 5.626 .000
Within Groups 196.963 295 .668
Total 211.987 299
Consumer Experiences Between Groups .534 4 .133 .251 .909
Within Groups 157.103 295 .533
Total 157.637 299
Consumer Experiences Between Groups 12.186 4 3.046 3.831 .005
Within Groups 234.601 295 .795
Total 246.787 299
Consumer Experiences Between Groups 26.506 4 6.627 11.307 .000
Within Groups 172.891 295 .586
Total 199.397 299
Consumer Experiences Between Groups 1.803 4 .451 2.442 .047
Within Groups 54.447 295 .185
Total 56.250 299
Consumer Experiences Between Groups 26.682 4 6.671 12.451 .000
Within Groups 158.048 295 .536
Total 184.730 299
Consumer Behavior Between Groups 3.830 4 .958 2.907 .022
Within Groups 97.166 295 .329
Total 100.997 299
Consumer Behavior Between Groups 105.665 4 26.416 24.407 .000
Within Groups 319.282 295 1.082
Total 424.947 299
Consumer Behavior Between Groups 82.761 4 20.690 27.294 .000
Within Groups 223.626 295 .758
Total 306.387 299
Consumer Behavior Between Groups 57.858 4 14.465 10.455 .000
Within Groups 408.128 295 1.383
Total 465.987 299
Consumer Behavior Between Groups 36.508 4 9.127 9.269 .000
Within Groups 290.489 295 .985
Total 326.997 299
Consumer Behavior Between Groups 8.759 4 2.190 3.808 .005
Within Groups 169.627 295 .575
Total 178.387 299
Consumer Behavior Between Groups 9.069 4 2.267 4.849 .001
Within Groups 137.927 295 .468
Total 146.997 299

Correlation between Employee Experience and Behaviors

The paired sample t-test was used in this review because the researcher sought to examine the influence of consumer experience on buying behavior. This goal created two sets of data, which were analyzed or purposes of understanding their relationship and the findings are highlighted in table 4.9 below.

Table 4.9 Correlation between Employee Experience and Behaviors (Source: Developed by Author).

Paired Samples Test
Paired Differences t df Sig. (2-tailed)
Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference
Lower Upper
Pair 1 Consumer Experiences – Consumer Behavior .280 .962 .056 .171 .389 5.043 299 .000
Pair 2 Consumer Experiences – Consumer Behavior -.147 1.248 .072 -.288 -.005 -2.036 299 .043
Pair 3 Consumer Experiences – Consumer Behavior -.270 1.250 .072 -.412 -.128 -3.741 299 .000
Pair 4 Consumer Experiences – Consumer Behavior -.200 1.682 .097 -.391 -.009 -2.059 299 .040
Pair 5 Consumer Experiences – Consumer Behavior 1.200 1.417 .082 1.039 1.361 14.672 299 .000
Pair 6 Consumer Experiences – Consumer Behavior -.157 .805 .046 -.248 -.065 -3.372 299 .001
Pair 7 Consumer Experiences – Consumer Behavior .473 1.055 .061 .353 .593 7.771 299 .000

According to the findings highlighted above, consumer experience had a significant impact on buying behavior because the significance value of all the paired data was less than P>0.05. This outcome means that the experiences that the patrons acquired influenced their behaviors. This view is consistent with existing studies that have also examined the same relationship (Yilmaz, 2017).

Discussions

The objectives of this study were centered on investigating theories and models underpinning the concept of customer experience, identifying opportunities that exist in enhancing it, pinpointing barriers that exist for developing better customer experience designs and discussing future trends and patterns that could be explored to improve it. The overarching aim was to understand how consumer experiences affect buying behaviors in the hotel industry. Relative to this goal, the findings depicted in this chapter have shown that customer experiences have a significant impact on consumer behavior in the hotel industry.

This positive relationship between the two variables is consistent with the findings of previous researchers, who have shown that positive experiences increase the utilitarian and hedonic values influencing the behavioral intentions of hotel guests (Giuntoli et al., 2017; Li et al., 2020). The expectancy disconfirmation and cognitive dissonance theories, which were highlighted in the second chapter of this document, suggest that consumer expectations and perceptions play an important role in influencing their experiences because they highlight the cognitive processes that occur at each stage of the purchasing process. The insights mentioned in chapter two about the customer experience process suggest that the two theories play an important role in the inspiration, evaluation of options, purchase, stay, and engagement phases of the customer experience process.

Key findings highlighted in this paper have also shown that potential exists in using digital technology means to improve user experience. This proposal is aligned with changing customer tastes and preferences that have been occasioned by shifting demographics in the customer base where younger hotel users are increasingly shaping service expectations in the industry (Hong and McArthur, 2019). However, such changes cannot be effected without overcoming the structural barriers to change that exist in most hotels. Therefore, there is need to adopt organization-specific strategies that would minimize such issues before a full-scale change adoption process is instituted. While the findings of this instigation relate to Hilton Hotel, there is need to undertake individual corporate assessments to identify unique challenges affecting a specific organization.

Summary

The insights gathered in this chapter show a positive relationship between customer experiences and buying behaviors. This finding relates to the Hilton case study but it shares similarities with previous research investigations that have explored the same issue. Therefore, the views presented in this report are consistent with those of other researchers in the field.

Conclusion

To recap, the overarching aim of this study was to understand how consumer experiences affected the buying behaviors of hotel clients. Four specific objectives guided the investigation and they centered on investigating theories and models underpinning the concept of customer experience, identifying opportunities that exist in enhancing it, pinpointing barriers that prevent the improvement of customer experience designs and discussing future trends and patterns that could be explored to improve it. Overall, the views presented in this document revealed that customer experiences significantly affected consumer buying behaviors. Additionally, it is affirmed that improvements that could emerge from this area of experience economy could likely come from the use of digital technology.

The presence of resistance to change among some employees and the lack of resources are some impediments highlighted in this study that could hamper efforts by hotels to improve their customer design processes. Similarly, strict and rigid organizational structures have made it difficult to realize efficient information flow across various departments to support the seamless delivery of services because some employees are protective of their tasks and are unwilling to relearn.

While these impediments are not true for all hotels, it is important for managers to plan on how to overcome them by adopting some of the recommendations outlined in this chapter, such as planning focused changes. Additionally, the increased use of technology to predict buying behavior could help them to overcome some of these challenges because technology is not bounded by common rationality and geographical limitations.

The findings of this study also suggest that hotels should play close attention to their customers’ experiences because they will likely determine the behaviors of their clients and, by extension, their profitability and bottom-line performance.

The insights highlighted in this document are relevant to today’s increasingly competitive hospitality industry, which is suffering under the weight of global uncertainties regarding the future of the sector due to travel restrictions imposed around the world to protect global health goals (Kaur and Kaur, 2020). Therefore, the findings highlighted in this investigation are instrumental in helping companies to distinguish themselves from their competitors and create a strong brand loyalty that would safeguard business growth even in times of uncertainty. Additionally, hotels could exploit the growing influence of a new crop of customers in the hotel industry, which is made up of millennials and generations X, Y, and Z, by developing products and services that would meet their unique needs.

Recommendations

Given this investigation has proven that customer experiences influence consumer behaviour, barriers to change have been highlighted as some of the obstacles hindering companies from developing more effective customer experience deigns. To overcome them, there is a need to adopt focused campaigns for changing customer experience designs, as opposed to taking a broad-based view of the same. Doing so will minimize the resistance to change because only one or a few departments may be affected during the initial stages of change. When this first phase has been completed, it may be prudent to integrate other departments in the process as well.

Doing so will minimize resistance to change. Some researchers also highlight the importance of rewarding employees for improved customer experiences as a strategy of securing their support to change existing experience designs (Rosemberg and Li, 2018). Those who propose this strategy believe it would motivate employees to improve their customer experiences and adopt the core values that support the process in the first place (Mai Chi, Paramita and Ha Minh Quan, 2021). Additionally, companies should realign their employee training processes to enhance core values that promote consumer experiences.

Implications of Study

The focus on customer experience is one of the most important pillars of operational success in the hospitality sector because of the importance of quality services to customer experiences. Owing to the need to provide clients with top-notch services, hotels cannot afford to have dissatisfied customers because they will affect the company’s bottom line. Indeed, today’s volatile business word, which is characterized by increased competition and widespread business uncertainties, may make it difficult for a business that does not understand the importance of consumer experiences to survive. Based on a recognition of these facts, the findings of this study have implications on various marketing operations in the hotel industry. First, they address the peculiarities of the hotel industry by explaining how they may influence customer experiences and behaviors in the long run.

This statement infers the importance of addressing service quality issues in the industry. The findings of this study also offer clarity to the role of consumer experiences in affecting behavior from a theoretical perspective because traditional research studies have been marred by generalizations and assumptions about their clients’ needs that may not reflect the peculiarities of the industry. The findings of this study are also instrumental in advancing knowledge within the areas affected by the research gap highlighted. The use of the mixed methods approach and the integration of primary and secondary research findings in this investigation have also helped to augment existing and historical literature with fresh empirical insights that are crucial to the overall management of the hotel industry.

Areas of Future Research

The current study has used a series of questions to measure the responses of the informants using the five-point Likert scale. Future research studies should use a different measurement or assessment technique to sample the views of the respondents regarding customer experiences and buying behaviours. For example, most research investigations that have examined user experiences have opposed the net promoter score as an alternative scale for measuring and assessing data (Raassens and Haans, 2017; Mecredy, Wright and Feetham, 2018).

This scale has been traditionally used to predict how often customers are likely to recommend a company’s products or services to their colleagues, friends or family members (Diéguez-Soto, Fernández-Gámez and Sánchez-Marín, 2017). Such a scale should be used in future studies to estimate customer experiences by giving an account of different factors influencing their overall experience.

Limitations of Study

Although this investigation focused on analysing customer experiences and behaviours, the views collected are those of Hilton’s employees and not of its customers. In other words, assumptions about customer experiences and behaviours are made from an employee’s perspective and not from a customer’s perspective. Therefore, feelings about satisfaction and product use are inferred from the employees of the company and not from the customers themselves. This is a limitation of the study because the views of the customers were not collected from the customers but from those who interacted with them.

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Appendix

Questionnaire

Dear Participant,

Thank you for choosing to participate in this study. Its central focus is to understand how consumer experiences in the hotel industry affect their behaviors. Four specific objectives will guide the investigation and they are centered on investigating theories and models underpinning the concept of customer experience, identifying opportunities that exist for enhancing customer experiences, identifying barriers that exist for developing better customer experience designs and discussing future trends and patterns in customer experience design.

Part 1: Demographic Data

Please, tick on the appropriate boxes.

  • What is your gender?
    • Male;
    • Female.
  • What is your age?
    • Under 18;
    • 19-25;
    • 26-30;
    • 31-35;
    • Over 35 years old.
  • Which is your highest education qualification?
    • Diploma;
    • Undergraduate;
    • Masters;
    • PHD;
    • Honorary Degree.
  • How long have you worked for your organization?
    • Less than 1 year;
    • Less than 2 years;
    • 2-5 years;
    • 5-7 years;
    • More than 7 years.

Part 2: Customer Experience

  • Our customers are largely satisfied with the quality of services offered at the hotel:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • Customers are likely to recommended our hotel to other people:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • I am satisfied that customers are contented with the services offered by the business purchasing and interactive functions:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • Our customers appreciate seamless, remarkable and effortless services during their stay at our facility:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • Our patrons value the experience they get from visiting our hotel:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • All our customers get the same quality of service every time they visit our facility:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • I believe that our patrons create memorable experiences while staying with us:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.

Part 3: Customer Behavior

  • Individual customer experiences when staying with us are likely to be exhibited in group behaviors:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • Individual customer experiences often influence changes in consumer behavior:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • The experiences accrued by a customer during the inquiry stage are likely to influence when they are most likely to make payments for booking:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • Past customer experiences play a significant role in raising questions or objections about present buying decisions:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • Out first-time patrons usually come back again:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • Our customers are loyal because of the experiences they get while staying with us:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.
  • Improving customer experience could unlock untapped consumer behavior potential that would lead to improved sales:
    • Strongly Agree;
    • Agree;
    • Neither Agree nor Disagree;
    • Disagree;
    • Strongly Disagree.

Thank you for participating in the study.

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Premium Papers. 2022. "The Influence of Consumer Experience on Their Buying Behaviour." August 25, 2022. https://premium-papers.com/the-influence-of-consumer-experience-on-their-buying-behaviour/.

1. Premium Papers. "The Influence of Consumer Experience on Their Buying Behaviour." August 25, 2022. https://premium-papers.com/the-influence-of-consumer-experience-on-their-buying-behaviour/.


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Premium Papers. "The Influence of Consumer Experience on Their Buying Behaviour." August 25, 2022. https://premium-papers.com/the-influence-of-consumer-experience-on-their-buying-behaviour/.