Influence of Customer Experience Dimensions on Purchase Behavior in Kenyan Hotels

Customer experience has been found to be a competitive edge for many hospitality industries. The growth and survival of many hotel industries depend on its ability to manage and create memorable experience. Research on customer experience tends to focus more on managerial outcomes than on the theories underlying the antecedents and consequences of experiences. Whilst realizing the gap between traditional quality management practices and what customers desire from their experiences, firms are challenged to define experience, identify its determinants, make it operational and manage its implementation effectively. This study aimed at assessing customer experience and its relative effects on customer emotions and purchase behavior in the Kenyan hotel industry. The study adopted Berry and Carbone’s conceptualization of customer experience and Shen and Zhao (2005) indicators to measure purchase behavior. A mixed exploratory research design was adopted to conduct the research where selfadministered questionnaires were used to collect quantitative data. The study assessed luxury hotels within Nairobi (20), Kisumu (1) and Mombasa (10) since they had a clear and consistent organizational structure and can give more insight into experiences because of their experienced and demanding clientele. The study population was 5,800 guests staying in the hotels. A total of 361 guests were selected as the sample size using multi stage sampling procedure. Data was analyzed using descriptive statistics which involved use of means, percentages and tests for normality and inferential statistics which included the use of correlation, principal axis factor analysis and regression. The research findings indicate that the respondents agree with all the 35 dimensions as describing their perceptions about customer experience in the hotel given that all the means of the 35 customer dimensions was > 4. The results proved that customer experience is composed of three set of clues (humanic, functional and mechanic) which impact on customers perception of overall customer experience. Regression results also showed that of the three customer experience factors, only humanic clue factor had significant influence on purchase behavior (β = .17, t = 1.94, p = .05), with the rest of the two factors having no significant influence. The implication of this finding was that any efforts towards enhancing customer experiences in a hotel should focus primarily on aspects of a hotel operation that are equally important to the customer. While acknowledging the importance of all aspects of the hotel operation, managers should recognize the significance of each aspect in influencing purchase behavior.


Introduction 1.Background of the Study
Every company must find ways to keep and attract new customers and at the same time remain competitive and profitable. As consumers today have more information available, are more flexible in their decisions and have many more choices than before, it is even more important for service firms to win the loyalty of their customers. To stay competitive, many companies have adopted approaches like Customer Relationship Management (CRM). However, research revealed that implementing CRM did not bring the results that marketers have expected (Meyer & Schwager, 2007;Schmitt, 2003;Palmer, 2010). Given the formidable facts of rapid shifts in business environments and customers' demands pose the challenges to achieve sustainable competitive advantages in the long run (Gentile et al., 2007). Hospitality is essentially a service industry or, perhaps more accurately, an amalgam of service industries. Consequently, its management practices are typically concerned with such issues as quality and productivity as they fall within the field of services marketing. While these concerns are critical, they may only be telling part of the management story. The other side of the story is the 'psychological environment'; that is, the subjective personal reactions and feelings experienced by consumers when they consume a service. This phenomenon has been termed the customer experience and has recently been found to be an important part of consumer evaluation of and satisfaction with services (Orsingher & Marzocchi, 2003). Hospitality and tourism organizations are now placing the hope on the concept of "customer experience", a relatively new approach to become customer oriented. Customer experiences are extremely relevant to the tourism industry. Since tourism is an experience-intensive service industry, travelers are likely to pay much attention to their travel and visit experiences (Ali et al., 2014;Smith, 1994). A review of literature shows that several researchers have sought to sampling was used to identify hotels that gave the needed information. Two dimensions were used to select the hotels; amenities and bed capacity. The guests to participate in the study were determined using Cochran's formula which gave a sample size of 361 guests. Israel (1992) recommended the use of Cochran's formula in calculating the sample size when the population is huge and can change at any time of the study. The total number of guests to participate in the study in each hotel was selected using proportionate sampling. This implied that the number of rooms in each hotel was considered in relation to the total number of rooms in all the luxury hotels and total guests sample size. Guests who participated in the study were selected using systematic sampling procedure such that every guest staying in the nth room was involved in each hotel. Berry and Carbone's Model (2007) was used for measuring customer experience. This model posited that customer experience clues generally fall into three main categories: functional, mechanic and humanic. Four scale items, adopted from Shen and Zhao (2005) were used to measure purchase behavioral intentions. The items are "I am willing to visit the hotel again.", "I will resist the offers of other hotels.", "I will always recommend this hotel whenever anyone seeks my advice" and "I would say positive things about this hotel to others." All items were measured on a likert scale ranging from '1' Strongly Disagree to '5' Strongly Agree.

Data Collection Methods
Self-administered questionnaires were used to collect data in the quantitative phase and interviews were used in the qualitative phase of the study. Self-administered questionnaires were considered because the respondents answered at their own convenient time. Questionnaires were chosen because administration of questionnaires to individuals helped to establish relationships with the respondents while introducing the survey (Satirenjit et. al., 2012). Questionnaires provided the clarifications sought by respondents and they may even be collected immediately after they are completed.

Data Collection Procedures
The data collection procedures involved getting the authority letter from the University to facilitate data collection process. Letter of introduction was sent to the selected hotels notifying the managers of the intention to conduct research in the hotels. This paved way for accessibility to the hotels. The questionnaires to be administered were then delivered to the receptionists in each of the selected hotels. The questionnaires were distributed to those guests checking in to the selected rooms by the receptionist during the four weeks data collection period. Guests were instructed to fill the first part of the questionnaire on check in and the other parts upon their departure.

Data Analysis
Data collected was analyzed using both descriptive and inferential statistics. Means, percentages and tests for normality was used to describe the data. Specifically factor analysis by principal axis approach was used to examine the specific items that define the primary structure of customer experience and analyze the significance of aspects of customer experience in shaping customer behavior. Correlation was also used to examine the relationship between customer experience and customer behavior variables.

Results and Findings
This chapter looks at questionnaire response, reliability and validity tests; respondents profile and results based on factor, regression and correlation analysis.

Questionnaire Response
The target respondents for this research were predominantly guests staying in the selected hotels within the four weeks data collection period. A total of 361 questionnaires were distributed in the selected hotels. The number of responses achieved was 321 providing a response rate of 88.92%. The reason for the low response rate was not only due to the timing of the survey distribution, which was a non-peak time of year for hotels, but also some of the respondents went with the questionnaires and it was difficult to follow up.

Validity and Reliability Tests of the Research Instruments
In order to conduct factor and regression analysis the variables in the research model were tested for their validity and reliability. Questionnaires were tested for content validity to establish quality of instrument. These procedures involved pilot testing conducted on 10% of the total sample which was then excluded from the study. There was no variation from the expected result and the instrument was considered to be valid. Piloting was also used to identify the length of time it will take to fill questionnaires, check understanding of the tool and correct simple mistakes like spelling and wording of sentences. The pilot study was done as if it was a normal survey and data generated was used to do a reliability test based on Cronbach's alpha of the items in the instruments. The reliability of the measures was established by testing for consistency and stability of the questionnaire results in the pre-test study and the main survey using Cronbach's alpha. Cronbach's alpha is a reliability coefficient that indicates how well the items in a set are positively correlated to one another. The Cronbach alpha coefficient was computed for all the construct measures in SPSS 21 to ascertain the reliability for all the sets of measures. Reliability tests were done for all the sets of measures i.e. customer experience and purchase behavior. George and Mallery (2003) rules of thumb was used to classify the Cronbach's alpha coefficients generated. These rules of thumb provide the following: "> .9 -Excellent, > .8 -Good, > .7 -Acceptable, > .6 -Questionable, > .5 -Poor, and < .5 -Unacceptable" (p. 231). The closer the Cronbach's alpha is to 1.0, the higher the internal consistency reliability. During the pre-test, dimensions of customer experience measures registered excellent reliability while customer emotions and purchase behavior measures registered acceptable reliability. Cronbach's alpha reliability coefficients registered in the main survey were as follows: Customer experience measures α = .95 and purchase behavior measures α = .74. This shows that the items were reliable in measuring their respective constructs given that all the Cronbach's alpha for the constructs in both the pre-test and main survey were >.7.

Demographic Characteristics of Respondents
This section presents the personal data of 321 customers who stayed in the hotels between November 9 th and December 22 nd , 2017. The results indicated that 172 respondents (53.60%) were males and that 149 respondents (46.40%) were females. The frequency and the percentage fallout of the demographic analysis depicted that the highest percentage (57.90%) of the people who stayed in the hotels were foreigners and 42.10% were Kenyans. The majority respondents declared their visit for vacation that was around 44.90% of the total respondents. The rest 23.10% were business, 21.80% conference and 6.50% honey moon. Other purposes of visit included cancelled flight, educational trips, humanitarian visit, just to relax and visiting an orphanage which contributed to 3.70% of the total respondents. The largest proportion of the respondents (41.70%) was within the age bracket of 20-35 years and the lowest proportions (6.90%) were below 20 years whereas 37.10% and 14% were within the age bracket of 36-50 years and over 50 years respectively. The results further indicated that most of the respondents (95.60%) had stayed in the hotels before whereas 4.40% of the respondents were staying in the respective hotels for the first time. Among those who had stayed before 33.60% had stayed in the hotel once, 23.40% twice, 20.20% thrice and 18.10% had stayed for more than three times. Most of the respondents 29.60% spend in the hotel for 3 days, 27.70% for 2 days, 20.60% for more than 4 days, 13.40 % for 4 days and 8.70% spend for just a day.

Dimensions of Customer Experience
In order to address specific objective one namely: To examine the specific items that defines the primary structure of customer experience in Kenyan hotel industry, mean ranking of the customer experience dimensions was done and subjected to factor analysis. In this case, respondents were required to indicate their level of agreement on a scale of 1-5 against 35 customer dimensions. To achieve this objective in the analysis stage, mean ranking of the 35 dimensions of experience were first done and the results are presented in Table 1. The 35 items were then subjected to principal axis factoring (PAF) in SPSS using varimax rotation. The factor analysis results, other than defining the primary structure of customer experience, were relevant for subsequent multiple regression analysis using Smart PLS 3.2.7. Table 1 shows that the highest ranked customer experience dimension is "The hotel is kept clean" (M = 4.60, SD = .57), followed by "The television in the guest room is in proper working condition" (M = 4.59, SD = .61) and then "The ambient conditions such as temperature, ventilation, noise and odour of the hotel are good" (M = 4.57, SD = .62). The least ranked customer experience dimension is "The hotel offers variety of recreational facilities" (M = 4.24, SD = .86). The results generally indicate that the respondents agree with all the 35 dimensions as describing their perceptions about customer experience in the hotel given that all the means of the 35 customer dimensions was > 4.
On subjecting the 35 customer experience dimensions to PAF, three factors accounting for 57.06% of the total variance explained resulted. All factor loadings were > .60 with six items (Employees have the knowledge to answer questions, The hotel lighting is pleasant, The background music is pleasing, The additional wi-fi services provided by the hotel are valuable to you, The food and drink offered in the restaurant are delicious and The hotel offers variety of food and beverage) not loading because of low factor loadings < .06 (see Table 2). The factors were named Humanic Clues Factor with 13 items accounting for 25.18%, Functional Clues Factor with 7 items accounting for 16.99% and Mechanic Clues Factor with 8 items accounting for 14.89% of the total variance explained (see Table 5). This supports a number of research findings on dimensions of customer experience (Carbone & Haeckel, 1994;Pullman & Gross, 2004;Hemmington, 2007;Brunner-Sperdin & Peters, 2009;Wells et al, 2011b) who share a common believe that customer experience is developed by various components within the physical and social environments, that is, interaction with staff, other customers and service provider. The results proved that customer experience is composed of three set of clues (humanic, functional and mechanic) which impact on customers perception of overall customer experience. This suggests that consumers' evaluation  Vol.11, No.21, 2019 of experience goes beyond the direct service encounter, and includes direct and indirect encounters with all touchpoints, Payne et al. (2008). Investigating the influence of each individual dimension on the outcomes, the study further revealed that humanic clue played a significant role in the customer's service experience evaluation process. Functional clues on the other hand were the second important dimension while mechanic clues were the third important dimension. The factors generated under each study construct are discussed in the sub-sections that follow.  (5), Agree (4), Neutral (3), Disagree (2), Strongly Disagree (1) Table 1 indicate that of the thirteen items, employee expertise as a dimension of customer experience had the highest mean ranking (M = 4.45, SD = .68) followed by employee personal grooming and employee behaviour with (M = 4.40, SD = .62) and (M = 4.40, SD = .67) respectively. Table 2 indicates that the thirteen items that loaded on humanic clue factor (HCF) account for 25.18% of the total variance explained in customer experience. The main sub-dimensions that determined humanic clues were employee friendliness, guest respect, understanding guest needs, guests' problem solving, grooming, courteousness, caring about customers, guests interest at heart, behavior, willingness to help, prompt service delivery, individual attention and employee assurance of safety. The findings of this study suggest that all thirteen sub-dimensions are important to hotel industry. The percentage explained by the factors implies that all the thirteen factors were important in evaluation of customer experience as perceived by guests. Of the thirteen factors extracted, employee friendliness, guest respect and understanding of guests' needs explained for the greatest percentage of the total variance 83 %. This higher percentage explained by these factors could be attributed to the unique characteristic "inseparability" of service industries. Since in hotels you cannot separate the consumer and the service provider there is a lot of interactions between the employee and the customer in the service delivery process. The delivery of service occurs during the interaction between service employees and customers, and, together with the attitudes and behavior of service employees, influences customer perceptions and evaluation of service experience (Iglesias and Guillen, 2004).

Humanic Clues
This support Berry and Carbone (2007) who emphasise that humanic clue is a significant dimension of customer experience. Humanic clues are concerned with the actions and appearance of employees and the service providers. The findings generally suggest that employees' behaviour and performance during the service are powerful clues that influence the customers' perceptions of the total customer experience. This support the arguments of Berry et al. (2006) and Bitner et al. (2008) that an organisation needs to pay particular attention to humanic clue set in terms of orcherstrating the total customer experience. Having competent, knowledgeable and professional employees leads to provision of quality service as employees dominate the service delivery process. This is attributed to the argument that employees conduct, friendliness, courtesy, commitment, trust, effective solving of customer complaints and other staff personalities Caro and García, 2007;Wu et al., 2011) influence the overall service delivery process. Employees who are well trained on customer service and able to handle guests' requests and complain promptly are equally an important asset to the hotel as it enhances customer experience. Good service training equips service staff with the competence to deliver a high-quality service. Moreover, training and development experience enhances the ability of employees to deliver a highquality service and to meet the needs of customers more effectively and in a more friendly way. This is because such employees' traits contribute to guests' overall evaluation of customer experience. Humanic clue dimension reflects the emotional benefits customers experience based on the perceived expertise of the service provider and guidance throughout the process leading to the notion of building 'a relationship' with a service provider. This suggests that employees' behaviour and performance during the service are powerful clues that influence the customers' perceptions and evaluation of the total customer experience. Management should understand that the vital process of selection, promotion, motivation, training, empowerment, and retention contribute to satisfactory service delivery. In other words, hotel managers should focus on enhancing the knowledge, skills and commitment of their employees by providing regular trainings and incentives (Ali et al., 2014). In short, in determining positive customer experience, relevant competencies and efficient staff are core issues that should be worked on.   Table 1 indicate that of the eight items, hotel cleanliness as a dimension of customer experience had the highest mean ranking (M = 4.60, SD = .57) followed by Television working in guestroom with (M = 4.59, SD = .61). Hotel layout though registered a higher loading (.81) (see Table 2), ranked the least (M = 4.41, SD = .65) with respect to customer experience. Table 2 indicate that the eight items that loaded on mechanic (MCF) factor account for 14.89% of the total variance explained in customer experience dimension, an indication that all the eight service factors are critical measurement of customer experience. The main sub-dimensions that determined mechanic clues were hotel layout, appealing exterior appearance, proper functioning television, proper arrangement of furnishings, comfortable physical layout of furniture and furnishings, good ambient conditions, cleanliness of the hotel and appealing overall hotel facility. This is in line with Wall & Berry (2007) findings that hotel industries could improve customers' perception towards a hotel's services by orchestrating mechanical clues. This further supports Berry and Carbone (2007) findings that mechanic clues are important in creating memorable customer experience dimension. Mechanic clues come from inanimate objects and offer a physical representation of the intangible service. Berry & Carbone (2006) also emphasized that customers usually experience mechanic clues to some degree before experiencing the other types of clues and even before making a purchase decision, such as selecting a restaurant after peering in the windows and seeing tablecloths on the tables. Facility design, equipment, furnishings, displays, signs, colors, textures, sounds and lighting among other sensory clues, paint a visual picture of the service experience, communicating to customers without a single word being spoken. Part of the first impressions role that mechanic clues play is their influence on customers' service expectations. Customers' perceptions of service quality are subjective evaluations of a service experience compared to their expectations for the service. Mechanic clues provide customers with information about what they can expect during a service performance. These findings imply that the design of mechanic clues should fit and support the company's market strategy. It clearly is not a good idea to create a physical environment for the service that implicitly promises a quality level that cannot be consistently delivered. On the other hand, this suggests that the right kind of mechanic clues help a company attract the type of customer it seeks. Hotel industries should therefore pay attention to the sensory presentation of the product as they are often an important part of product design as it influences how customers feel about an experience. Table 1 indicate that of the eleven items, additional wifi services as a dimension of customer experience had the highest mean ranking (M = 4.49, SD = .60) followed by delicious food and drink offered with (M = 4.47, SD = .67). Table 2 indicate that only seven items loaded onto functional clues factor (FCF) accounting for 16.99% of the total variance explained in customer experience dimension, an indication that all the seven service factors are critical measurement of customer experience. The main sub-dimensions that determined functional clues were great lobby facilities, prompt response to queries, excellent guest rooms, real time service delivery, attractive food presentation, standardized product delivery process and variety of recreational facilities. Functional clues concern the technical quality of the offering. These are the "what" of the service experience, revealing the reliability and competence of the service. Anything that indicates or suggests the technical quality of the service (its presence or absence) is a functional clue. This supports Berry & Carbone (2006) discussion that functional clues are usually important in meeting customers' service expectations because functionality offers the core solution customers buy. Functional clues support the core of any service because they address the problem that brings the customer to the market. This finding also coincides with the viewpoint that the outcome of the service encounter and physical surroundings significantly affects customer perceptions of overall customer experience. This is because the physical surroundings represented by objects are thought to create a positive consumer experience which according to Leong (2008) plays a pivotal role in sustaining business growth. The findings imply that managers of hotels need to focus more on those factors perceived to create positive experience. To achieve high quality of service, hotels need to concentrate or dedicate most of their time in improving the hotel facilities and service environment.

Influence of Customer Experience on Purchase Behavior
In order to establish the influence of customer experience dimensions on purchase behavior, PLS-SEM was conducted using Smart PLS 3.2.7. Latent variables were created for customer experience, customer emotions and purchase behaviour. For customer experience, the factors identified in principal axis factoring (PAF) were used as latent variables. The measurement models were first assessed for internal consistency, convergent validity, discriminant validity and collinearity. Internal consistency was assessed using Cronbach's alpha (α), composite reliability coefficients (Pc) and rho_A coefficient as defined in Dijkstra and Henseler (2015). Values above .70 indicate higher levels of internal consistency (Hair et al., 2014;Dijkstra &Henseler, 2015;Hair et al., 2017). The results indicate that the measures are robust in terms of their internal consistency reliability. Table 3 for instance, show that composite reliabilities (Pc) ranged from .80 (Purchase behaviour) to .96 (Humanic clues factor), an indication of internal consistency. Convergent validity was assessed using Fornell and Larcker criterion, average variance extracted (AVE) > .5. Table 3 shows that all the AVE were > .5, an indication that almost all the constructs explained more than 50% of their indicator's variance. The table indicate that AVEs for this study ranged from .51 (Mechanic clues factor) to .68 (Humanic clues factor), implying that, on average, the construct explains more than half of the variance of its indicators.   does not give rise to discriminant validity concern as all the values are < .85.  (Hair et al., 2011;Hair et al., 2013;Hair et al., 2014;Petter, Straub & Rai, 2007). Table 5 shows the result of collinearity assessment among the study constructs as indexed by the variance inflation factor (VIF) values. All the VIF were < 5, suggesting that multicollinearity was not an issue. The highest VIF value (2.11) is registered between Mechanical clues factor (MCF) and Purchase behaviour (PB). The lowest VIF value of 1.43 is recorded between Customer emotions (CE) and Purchase behaviour (PB). 0.11 0.12 0.10 1.14 0.25 NS 2.11 0.01 Small To assess the extent to which customer experience dimensions influence purchase behaviour, the significance of path coefficients, coefficient of determination (R 2 ) and the effect size measure (f 2 ) were used. Table 5 shows that of the three customer experience factors, only Humanic clue factor had significant influence on purchase behaviour (β = .17, t = 1.94, p = .05), with the rest of the two factors having no significant influence. Table 6 shows that the R 2 value for the endogenous constructs are above the 25% accepted level set as the threshold in this study. The R 2 values (R 2 = .44) indicate that the three customer experience factors (Functional clue factor, Humanic clue factor and Mechanic clue factor) together with customer emotions account for 44% of the total variance explained in purchase behaviour (see Table 6). However, Table 5 show that the exogenous constructs Customer emotions (CE), Functional clues factor (FCF), Humanic clues factor (HCF) and Mechanic clues factor (MCF) for explaining the endogenous latent variable Purchase behaviour (PB) have large effect size (f2 = .34), small effect size (f2 = .00), small effect size (f2 = .03) and small effect size (f2 = .01) respectively. This imply that of the 44% of variance in purchase behaviour (PB), the three-customer experience factors had smaller influence on purchase behaviour with humanic clue factor having a higher influence and functional clues factor having a smaller influence of the three.

Discussions
Customer experience dimensions play different roles in influencing customer's purchase intentions. This agrees with Berry & Carbone (2006) findings that humanic clues created by employees are most salient for labor-intensive, interactive services. The more important, personal, and enduring the customer-provider interaction, the more pronounced and emotional humanic effects are likely to be. Human interaction in the service experience offers the chance to cultivate emotional connectivity that can extend respect and esteem to customers and, in so doing, exceed their expectations, strengthen their trust, and deepen their loyalty. A potentially important role of mechanic clues is to make a positive first impression that will influence customers' choice of service supplier. Customers usually experience mechanic clues to some degree before experiencing the other types of clues and even before making a purchase decision, such as selecting a restaurant after peering in the windows and seeing tablecloths on the tables. The idea of mechanic clues painting a service picture or representation of one thing in terms of another is fundamental in influencing purchase behavior. Mechanic clues can be a powerful source of sensory images helping customers visualizes the service (Berry & Carbone, 2006). Part of the first impressions role that mechanic clues play is their influence on purchase intentions. The study findings further suggest that functional clues are usually most important in meeting customers' service expectations because functionality offers the core solution customers buy. Functional clues on the other hand support the core of any service because they address the problem that brings the customer to the market. Customers buy solutions that depend on functionality.

Contributions and Recommendations 5.1. Contribution to Theory
This present research provides a number of theoretical and empirical contributions to customer experience management research and its relative effects on purchase behaviour particularly in the hotel industry. This study investigates the relationship between dimensions of customer experience and purchase behaviour in luxury hotels in Kenya. In developing countries particularly Kenya, there is limited literature on customer experience dimensions, the extent to which these dimensions influence purchase behaviour and the relationship between customer experience and purchase behaviour variables. This study adds to previous work in various ways. Firstly, the results of this study provide a better understanding on the specific items that define the primary structure of customer experience in Kenyan hotels. The findings of the study identifies that customer experience is composed of three set of clues (humanic, functional and mechanic) which impact on customers perception of overall customer experience in luxury hotels in Kenya. The study further revealed that humanic clue played a significant role in the customer's service experience evaluation process, functional clues on the other hand were the second important dimension while mechanic clues were the third important dimension. The findings might be used in improving marketing strategies, to create, manage, and control guest experiences in hotel industry. It contributes to research which focuses to consider these dimensions as antecedents that determine managerial practices hoteliers take into consideration to enhance customer experience in hotels. The results of this study support previous studies (Payne et al., 2008;Wall & Berry, 2007;Ali et al., 2014;Leong, 2008;Wu et al., 2011;Iglesias & Guillen , 2004) which have made numerous efforts to understand the dimensions and sub-dimensions of customer experience. Secondly, the study identifies the extent to which customer experience dimensions influence purchase behaviour in luxury hotels. The results of this study provide a better understanding on the extent of influence of customer experience dimensions on customers purchase behaviour. The study revealed that humanic clue factor had significant influence on purchase behaviour while functional clue and mechanic clue factor had no significant influence. The three customer experience factors combined had smaller influence on purchase behaviour with humanic clue factor having a higher influence and functional clues factor having a smaller influence of the three. The understanding of the influence of these customer experience dimensions can be helpful to managers in crafting and executing strategies that have the most positive effect on consumers' purchase behaviour. Consequently, this will allow organizations to manage customer experience properly that ultimately results into customer satisfaction, repeat purchase and positive word-of-mouth. Furthermore, this study establishes a direct linkage between firms marketing inputs and their consumer behavioural outcomes. The results of this study support previous studies (Cronin et al., 2000;Liu & Jang, 2007;Kivela et al., 2000;Mohr & Bitner, 1995;Ha & Jang's, 2010;Namkung & Jang, 2004) which have made numerous efforts to prove the effect of customers' evaluations of service performance on customer's behavioral outcomes This previous studies have reported a positive relationship between customers' perceptions of the quality of performance and customers' behavioral intentions. Implicit in this belief is that higher quality performance is likely to produce increased loyalty, future visitation, and other behavioral intentions (Baker & Crompton, 2000).
Thirdly, the study also identifies the relationship that exists between customer experience and purchase behaviour variables in Kenyan hotels. The results of this study provide a better understanding on the relationship between customer experience dimensions and purchase behaviour. The study revealed that the three customer experience factors had smaller influence on purchase behaviour with humanic clue factor having a higher influence and functional clues factor having a smaller influence of the three. The findings confirm that all the three dimensions of customer experience have a positive and significant impact on purchase behaviour, validating the notion that the customer experience evaluation goes beyond the direct service encounter, and includes direct and indirect encounters with all organisational functions of the organisation and possible channels and touchpoints. The empirical findings support a number of studies (Payne et al. 2008;Voss et al. 2008;Kim, 2010;Ali et al., 2014) who have pointed out that understanding how clients evaluate service experience is crucially important for a company success and determines relationship quality from the customer's perspective. This provide a guide for the development of the service offer by taking into account the variables the customers use to evaluate service experience and provides the firm with a sustainable competitive advantage.

Practical Implications
The findings of this study shed light on several unresolved issues and concerns in hospitality industry management particularly in Kenya. Given the changes in customer prefences and demands and the desire to manage and create memorable experiences for their customers, hoteliers need to develop strategies that will keep them at par with their competitors. While most hotels have considered customer experience management as a strategic tool for enhancing their performance (Carbone & Haeckel, 1994;Pullman & Gross, 2004;Bate & Robert 2007;Laderia, Costa & Santini, 2012;Walls et al., 2011;Kim & Brown, 2012;Cetin & Dincer, 2014), firms are challenged to define experience, identify its determinants, make it operational and manage its implementation effectively. This study points to the continued importance of customer experience management in enhancing hotel performance. The study makes several contributions for hotel practitioners; Firstly, the study allows managers to understand the primary structure of customer experience. The findings provide an understanding of how their customers evaluate the different dimensions and attributes of their customer experience by linking them to customers' journey. Understanding the customer can be a starting point for most hospitality industries. There are at times where a gap occurs between what customers expect and what management or businesses presume they expect. This often happens because companies overlook or do not fully understand customer's perceptions and expectations. The results suggest that managers need to put great efforts into understanding the process of customer experiences and the various interactions involved.
Secondly, the study identifies the extent to which customer experience dimensions influence purchase behaviour. The understanding of these experience dimensions can be helpful to managers in crafting and executing strategies that have the most positive effect on purchase behaviour. Consequently, this will allow organizations to manage customer experience properly that ultimately results into repeat purchase, referrals, resistance to competitors' offerings and positive word-of-mouth. Using these findings, practitioners can orchestrate an integrated series of "experience clues" that collectively meet or exceed people's emotional needs and expectations.
Thirdly, the study identifies the relationship that exists between customer experience and purchase behaviour variables in Kenyan hotels. Understanding how clients evaluate service experience is crucially important for a company success and determines relationship quality from the customer's perspective. The findings confirm that all the three dimensions of customer experience have a positive and significant impact on purchase behavior. The results enable managers to understand the factors which help enhance customer experience. In an attempt to help managers in need of looking for ways to create customer experience the current study suggests several antecedents of customer experience and their influence on purchase behavior. The research findings provide some advices for the industry players in drafting various managerial strategies to increase the purchase intention, by emphasizing the different perspectives of customer experience. In addition, the research findings provide certain approaches to the industry players how to modify the customer experience in the strategy planning because there are integrated relationships among humanic clue factor, functional clue factor, mechanic clue factor and purchase behavior.

Recommendations to Hospitality Practitioners
Based on the preceding of the survey results, the following recommendations regarding hotel customer experience and customer behaviour are suggested: a) Any efforts towards customer experience improvement in a hotel should focus primarily on aspects of a hotel operation that are equally important to the customer. While acknowledging the importance of all aspects of the hotel operation, managers should recognize the significance of each aspect in enhancing overall customer experience. Thus it is imperative that management channel their resources into updating guest services in accordance with the requirements of their clientele. b) Management of customer experience dimensions should become an important issue for hotel industry in order to enhance customer satisfaction and influence purchase decisions. Hotel managers should be aware of the direct link between service evaluations and behavioural intentions through the construct of customer experience. The study advocates customer experience as an alternative, and possibly even better, validated predictor of consumer behavior. Customer experience measures a more holistic consumer construct by taking into account the sum of all direct and indirect interactions with a service provider providing both better explanatory power and identification of priority areas for managerial attention. c) A key success strategy for hospitality facilities is to focus on creating memorable experiences as customer experience has a positive effect on purchase intentions. This philosophy must become part of the company culture and must be instilled in all employees by the management.

Recommendations for Future Research
For future research it is recommended that data should be collected over different time periods of the year to understand the changing patterns of hotel service attributes in enhancing customer experiences. More geographical regions within Kenya could also be considered to investigate the variations of evaluation of customer experience across cultures. The study further recommends the need to investigate the difference on how individuals of different genders, age groups and with different purpose of visit evaluate service experience. Further research should consider the cross-cultural challenges inherent in translating a customer experience from country to country when applying these principles.