Service Value Assessment in Emerging Chain Restaurants in Nairobi Kenya

Traditionally, Kenya’s restaurants have in the past largely depended on international tourists for the main stay of their business. With the earlier steady growth of Tourism in the 1980s, these restaurants registered very good business, also supported by the fact that there were only a handful of restaurants that could be considered as ‘tourist class’. However, tourist arrivals in Kenya began to face serious challenges in the 1990s. Simultaneously, more serious restaurant ventures made market entry, especially within the capital city of Nairobi. It has been acclaimed that the prices charged for local hospitality services have not worked well to support it. As this takes place, questions have been asked as to whether these new investments have introduced product and service quality that is worth the price that they charge for the same. It was against the argument that is developing above that this study carried out a value assessment amongst the emerging chain restaurants in Nairobi city. The study sought to establish the part played by restaurants in building destination competitiveness through quality service offer and value pricing. A series of chain restaurants operating in Nairobi were identified all together with the specific unit and outlets that they operate. The customers in these restaurants were conveniently sampled and interviewed to inform this study of their perceptual judgment of service and value. The data was then be analyzed and interpreted to establish the extent to which these customers approve of service and value and how this can influence Kenya’s destination competitiveness, both for domestic and international tourists. The assessment of customer expectation and perception resulted in a four factor construct. An assessment of service quality led to the identification of the critical latent variables that leads to customer attraction and satisfaction in restaurants. An evaluation of prices charged indicated that price is a critical component in value assessment amongst customers.


INTRODUCTION
A number of well pointed restaurants have emerged in Nairobi within the past 10 years, all targeting the middle class as their customers.With heightening competition, a number of these restaurants have started experiencing business challenges largely attributed to turnover.According to Namkung & Jang (2008) [19] building an inclusive view of quality as applicable specifically to restaurants is a pressing concern because it will enable restaurant managers, within their limited resources, to prioritize decision-making that focuses on key quality attributes.However, while quality may be an important differentiating factor, customers in Nairobi may want to choose a restaurant on the basis of both satisfaction and value.Shoemaker et al. (2005) defined value as the price charged, while Zeithmal (1988) [30]defined values as the products quality reflecting the price paid.She further observed that consumers use extrinsic cues, such as price, in forming perceptions of value.Shoemaker et al. (2005) [26] adds that, if the price is too high relative to the other cues, then consumers will have poor perceptions of value and will have a decreased probability of purchase.Therefore value is the result of quality and price charged.Price or value for money is a factor that yields high customer loyalty and hotel revenue (Shifflet et al., 1997) [25].Traditionally, restaurant menu pricing has been done very haphazardly, reflecting very little systematic consideration of all operating cost; but rather laying more emphasis on the direct or variable costs of producing these items (Raab & Mayer, 2003[22]; Schmidgall, 1997 [24]; Chan & Au, 1998) [6].This practice has led restaurants to use a loose mark-up method, demand and supply or just mere rule of thumb as the major determinants of price.Failure to determine an acceptable reference price leads to customer dissatisfaction.The landscape of the Kenyan service sector is characterized by proliferation and internationalization of services resulting in business opportunities and at the same time posing competitive threats to existing service marketers.Service marketing researchers have suggested that a strategy for the survival and success of service firms is the delivery of quality services that satisfy customer needs and wants (Lee & Ulgado, 1997 [17]; Parasuraman et al., 1988;Thompson et al., 1985) [28].However, the design and implementation of such a strategy can never be successful unless service marketers first determining how the quality and value of their services are perceived by customers.Restaurants service providers are amongst the core travel and tourism firms that attract greater competition amongst destinations within the African region.In view of this, it was necessary to carry out a study that could contribute to management decisions on destination competitiveness as well as enhancing domestic tourism.It was therefore the purpose of this research to examine the value perception of customers who patronize emerging middle class restaurants in Nairobi, Kenya.The research answered a series of questions that were meant to build up conclusions and possible recommendations in order to attain the following objectives: Develop a profile of customers who patronize emerging chain restaurants in Nairobi, Measure customers" expectation of services in emerging chain restaurants in Nairobi, Measure customers" perception of services in emerging restaurant chains in Nairobi, Establish the parameters that define service quality and satisfaction in restaurants in Nairobi and Establish the customers" perception of price charged for the services offered in emerging restaurant chains in Nairobi.

LITERATURE OVERVIEW
Restaurants can be categorized as either full service restaurants or fast food service restaurants (Mueller & Kleiner, 2004) [18].While fast food restaurants are generally defined by menu simplicity, service speed and limited seating, full service restaurants can either be characterized by buffet offer, family service offer or fine dining experience (Angelo & Vladmir, 2007).There are also casual and specialized independent or chain restaurants that serve different types of snacks and biting such as sandwich shops, pizza places, chicken grills, hamburger joints, fish and chips.(Ditmer, 2002[10]; Dipierto, Murphy, Reviera & Muller, 2007) [9].In practice price is a factor that is normally taken into consideration when choosing and defining restaurant category.Price has been defined by Zeithaml et al. (2006) [31] as the expense that must be incurred in the given purchase transaction and serves as a proxy for quality or value to customers.The price at which a service or a product is offered has been found to be a factor that can be strongly associated with high customer loyalty and thus sales revenue (Shifflet & Bhatia, 1997) [25].The price of the items on the menu also greatly influences customers because price has the capability of attracting or repelling customers especially since price functions as an indicator of quality (Andaleeb & Conway, 2006) [1].It is thus agreeable that establishing effective pricing strategies is critical to restaurant competitiveness.The pervasive influence of price is due, in part, to the fact that the price cue is present in all purchase situations, especially in services (Raab et al, 2009) [23].Price has also been identified as the only element in marketing that holds a direct influence on revenue while all the other elements of the marketing mix are cost based (Shoemaker et al., 2006[27]; Kotler et al. 2005[16]; O"Connor, 2003;) [20].Hospitality firms use various methods to set prices for their products.The most commonly employed methods of setting menu prices have been identified by Kotler et al., (2005) as including; cost based pricing, volume-based, going rates, time-of-purchase discounting and discriminatory pricing.In a more recent development, Raab et al. (2009) proposed the use of Activity Based Pricing (ABP) in the restaurant industry.They defined ABP as a pricing method that combines market research data with cost accounting information to establish prices for products and services that result in "designed" profit levels.They recommend this method because it can be used to establish a total cost picture for a restaurant (excluding taxes) and further accommodate price sensitivity measurement in identifying customer price perceptions.Measuring customer satisfaction in restaurants goes beyond just price.For this reason, Shoemaker et al., (2006) points out that prices need to be established with the concept of customer satisfaction and loyalty in mind and not just short-term profit maximization.Customer satisfaction is often defined in marketing literature as a customer"s overall evaluation of his or her purchase and consumption experience of a good or service (Cronin & Taylor, 1992[8]; Johnson et al., 1995) [15].Customer loyalty is another aspect that judges satisfaction and service popularity.Jang and Mattila (2005) [14] carried out an examination of restaurant loyalty programmes in the USA to establish that immediate monetary based rewards are most preferred by customers and this may be akin to price discounting or rebates.To understand how to manage and improve quality in service companies we must appreciate the unique characteristics of the service industry.Edvardsson (1995) [11] notes that as a result of service intangibility, it is difficult for the supplier to explain service quality and for the customer to accurately assess the quality of a service.The SERVQUAL model (Parasuraman et al., 1988) has been used widely as a framework for measuring service quality across the entire service business domains.This model revolves around a set of five important dimensions that were originally indicated in the SERVQUAL approach by Parasuraman et al. (1988), and they are: Tangibles (physical facilities, equipment, and appearance of personnel), Reliability (ability to perform the promised service dependably and accurately), Responsiveness (willingness to help customers and provide prompt service), Assurance (knowledge and courtesy of employees and their ability to inspire trust and confidence) and Empathy (caring, individualized attention the firm provides its customers).SERVQUAL is however a generic measure; researchers have found that the relative importance of the five dimensions varies across different service industries (Lee & Ulgado, 1997; Carman, 1990).For this reason, Stevens et al. (1995) created a service quality scale for restaurants and other food service outlets (DINESERV).In application the DINESERV model has been found to borrow heavily from the SERVQUAL model and its application is therefore widespread amongst restaurants.However, Namkung & Jang (2008) [19] pointed out that DINESERV model left out food quality which is considered a major element of restaurant experience.According to the SERVQUAL construct, tangibles are critical dimensions of service quality.In restaurants, tangible takes many forms, key amongst them, is food quality.A general description of food quality focuses on presentation, healthy options, taste, freshness, and temperature (Namkung & Jang, 2008) [19].It is also observed that these attributes serve as tangible cues of service quality in restaurants and thus a basis for measuring satisfaction.Presentation is defined as how attractively food is presented and decorated as a tangible cue for customer perception of quality and Kivela et al. (1999) pointed out that the presentation of food is a key food attribute in modeling dining satisfaction.The menu also provides tangible evidence and provides a reflection of the restaurant"s image.The design, colours, paper, illustrations and type should reinforce the image of the restaurant.The menu becomes an extension of the personality of the restaurant (Bowen & Morris, 1995) [3].

METHODOLOGY
The study adopted a multi-faceted cross sectional sample survey approach, where each level of sampling criterion was subject to the objective being pursued.Sampling was done at two levels, restaurants and restaurant-customers. Prior to sampling the restaurants, a pilot study was conducted to establish the number of the chain restaurants within the horizontal scope of Nairobi and the average number of customers they receive in a day.A proportionate randomized sampling methodology of the various chain restaurants was conducted based on the weighting.To avoid dominance of one demographic characteristics of a particular residential neighborhood, the sites for conducting the interview were judgmentally selected.Another level of sampling involved the restaurants-goers.From the pilot survey, an average number of customers was established for each restaurant.This helped in giving a proportionate figure that would be adopted after conveniently sampling the customers for interview.Gay, (1981) in Mugenda and Mugenda, (2003) suggest that a sample size of 10% of accessible population is enough.However a researcher, depending on the availability of resources, may study more than 10% of this population.In this study 25% of the accessible population was interviewed.19 restaurants were sampled against 357 customers translating to approximately 17 customers per restaurant as displayed in Table 1 below.Permission was sought from the restaurant operators regarding on-going study within their business premises.For the purpose of this study, structured questionnaires were distributed to restaurant customers.A structured questionnaire was preferred in the study due to its ease in administration and in collecting the required data.Before proceeding to the field, the questionnaire was administered to four restaurant managers and four customers to assure of its content validity.The question had three sections.Section one of the instrument assessed the socio-demographic characteristics of the restaurantsgoers so as to develop a profile of customers who patronize emerging chain restaurants in Nairobi.The second section of the instrument sought to establish the parameters that define service quality expectation amongst restaurant patrons.Section three of the instrument examined customer perception in emerging restaurant chains.Questions in section two were of a five point Likert scale form with 1 standing for very low and 5 standing for very high, while section three had a sevenpoint scale questions with 1 standing for very unimportant and 7 standing for very Important.

DATA ANALYSIS
A total of 357 questionnaires were administered, out of which 247 were returned and found usable resulting a sample size n = 247.This reflected a 70.0 percent response rate that was considered adequate for the study.
A normality tests the data was showed that the data was normally distributed, while a reliability test of the 66 item scale instrument revealed a Cronbach"s alpha value of 0.927 which was interpreted to mean the instrument was very reliable.

Sample Profile
The demographic profile of the respondents in table 2 shows gender parity between the male and female gender.
However there were slightly more male, 126 (51.0 percent) than females, 121 (49.0 percent).The difference was considered minimal and insignificant in explaining variations in behaviour of the sampled group.The study noted a significant difference in age (p < 0.05), where a majority of restaurant customers fell in the age bracket of 25-45 (61.8 percent), this group is considered to be economically empowered and hence their restaurant service purchase choice are less influenced by the prices.Coyeman (1998, p.40) described this age group as "Optimistic, energetic, technology driven, pragmatic, resilient, with high social awareness, and open to and eager for new experiences".They are therefore most likely to try new service offer in a restaurant menu.This observation confirmed by the variable employment status, which revealed that the customers were either employed 131 (53.0 percent) or were in business 64 (25.9 percent).
The study observed that a majority of the respondents had university education with Bachelor holders constituting 136 (55.1%) and Masters and higher level comprising 51 (20.6%).A cross tabulation of education level and job status showed that 78 of the restaurant customers had up to Bachelor education level and were employed, while 34 respondents who had above Bachelors education level were employed, both findings indicating that restaurant patrons are well educated individuals.The sampled population had 71 (28.7 percent) single individuals and 176 (71.3 percent) were married.The married couples were the most frequent restaurant patrons with 77 repotting that they visit the restaurant three times a week while only 12 of the singles visited the restaurant three times a week.

Customers' Expectation of a Satisfying Dining Experience
Using exploratory factor analysis (EFA) the critical factors that define customer expectations of service quality amongst restaurants were decomposed.A pretest of factor analysis was undertaken using Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) and a Bartlett's Test.The KMO statistics of 0.935 was arrived at and the sample was subsequently considered adequate for the study to proceed with factor analysis.Bartlett"s Test of Sphericity was used to test the null hypothesis that the variables in the population correlation matrix are uncorrelated (Owino, et al, 2014) [21].The Bartlett"s Test showed a 0.000 significance level.This implied that a strong relationship existed among the variables, and hence the study could proceed with factor analysis.
The study sought to examine the factors that defined restaurant customer expectation of services.A twenty nine item scaled instrument was developed to address the construct of restaurant customer expectation.Using EFA and in particular Principle Component Analysis and Varimax Rotation, the study identified the critical parameters in restaurant customer expectations.Following an initial PCA, 29 components were revealed out of which seven (7) components had Eigenvalues ≥1.The seven components explained 61.719 percent of the variations in service quality from customer expectation perspective, while the other twenty three components explained the 38.281 percent of the total variance explained.A scree plot confirmed that the seven components were very important in defining expectation of restaurant customers.The unrotated solution captured in the component matrix revealed 7 (seven) components, of which variations in component one (1) were explained by twenty nine (29) variables, while variations in component two were explained by three variable.Variation in component three was explained by only one (1) variable and variations in component four till seven, remained unexplained.Using PCA extraction method and Varimax with Kaiser Normalization rotation method, the first attempt at factor extraction resulted in seven (7) components.An attempt was made to repeat the rotation with a specification of a fixed number of factors (5) instead of Eigenvalues; however it resulted in non convergence after 25 iterations.The study proceeded with rotated solution reflecting seven (7) components and twenty five (25) variables as shown by Table 3. Variations in component one (1) are now explained by four (four) variables.The variables with the highest factor loading and which explained variation in component one (1) to a great extent were; employees strive to satisfy customers needs, with a factor loading of 0.700, preparedness to help the customer (0.699), preparedness to help the customer (0.676) and "one stop shop" dealing with matter (0.674).The four variables were interpretated as the factor reliability.The variables that loaded on component two were; accessibility and clarity of information needed (0.724), general ambience of the restaurant (0.660), restaurant serves tasty food (0.608), employees individually intercede for customer (0.549) and the physical facilities are visually appealing (0.515).The five items were interpreted as the factor physical evidence of the restaurant.Variations in component three (3) were explained by four (4) variables.The four were; sufficient waiting time for delivery of the meal (0.733), followed by speed of service and promptness with a factor loading of 0.713, when the restaurant promises to do something by a certain time it does so (0.597) and employees raise trust at customers (0.538).A closer examination of the four variables revealed convergence on the factor responsiveness of the restaurant service employees.Variations in component four (4) were explained by four (4) variables, with the following variables presenting the highest factor loading; service delivery in line with promises (0.789), expertise of employees who deliver the services (0.744), the service staff are well dressed and appear neat (0.529) and food is served at the appropriate temperature (0.500).The four variables were interpreted as the factor assurance provided by the restaurant service staff.Variations on the fourth component were explained by three (3) variables; arrangement of premises, equipment and environment (0.798), the overall arrangement of the restaurant creates ease of movement (0.792) and warm, welcoming and honest staff (0.672).These three variables were identified as the factor physical evidence of the restaurant.Variations in the fifth component were explained by four (4) variables.The four variables and their associated factor loading were; service delivery is in line with promise (0.782), expertise of employees who deliver the service (0.734), food is served at the appropriate temperature (0.517) and the restaurant performs the services right the first time (0.516).The four variables were interpretated as the factor reliability of the restaurant service staff.The three variables that loaded on component six were; the restaurant has the customer"s best interest at heart (0.766) the restaurant has operating hours convenient to the customers (0.659) and customers get individual attention (0.524).The predictors of component five were subsequently interpreted as the factor empathy of the employees of the restaurant.Only one variable loaded on component seven and this was; the restaurant has up to date equipment for ease of service provision, this was inferred as the factor physical evidence.Using EFA the study demonstrated that there are four critical parameters that define expectation of customers in emerging chain restaurants in Nairobi.The four were; responsiveness, physical evidence, reliability and empathy.These findings were found to be consistent with past studies (Buttle, 1996[4]; Parasuraman et al., 1988 and Berry et al., 1985) [2].The main difference noted was that the factor assurance was dropped from the key parameters that defined customer expectation of restaurant services.The study sought to examine the internal validity of the four constructs.The factor loadings against each factor were arranged inorder of their sizes.They were then scaled in SPSS and subjected to a Cronbach"s alpha test of reliability.Eight items (8) loaded onto the first construct (reliability) and the overall Cronbach"s alpha for factor 1(reliability) was α = 0.867.The overall Cronbach"s alpha for factor 2 (physical evidence) was α = 0.835 with nine (9) items loading on it.The overall Cronbach"s alpha for factor 3(responsiveness) was α = 0.765 with four (4) items loading on it.The overall Cronbach"s alpha for factor 4 (empathy) was α = 0.675 with three (3) items loading on it.The findings against factor four (empathy) led the study to consider it unreliable in explaining service quality expectation in the restaurant sector in Nairobi.Using the internal validity test results, the study does conclude that there are only four critical factors that were reliable in guiding customer"s expectation in restaurants sector in Nairobi.Amongst them, reliability is considered very important, followed by physical evidence, responsiveness and assurance respectively.

Customers' Perception of Service Quality in These Restaurants
The third section of the instrument sought to establish customer judgement of the service after service encounter.
Using EFA in terms of PCA followed by Varimax Rotation of the variables, the study established the dimensions of service quality from customer perception after the service encounter as shown in Table 4.The PCA identified five components that accounted for 64.586 percent of the total variance explained and had Eigenvalues ≥ 1.The remaining 34.414 percent of the variation were unexplained.The study sought to examine if there were additional variables that had not been unveiled and employed Varimax with Kaiser Normalization rotation method.Following the rotation, 21 items loaded onto the five components.The seven (7) variables loaded on the first component were: sufficient waiting time for the delivery of meals (0.770), speed of service promptness (0.737), employees strive to satisfy customer needs (0.722), preparedness to help the customer (0.720), proper speed of dealing with matters (0.600), "one stop shop" dealing with matters (0.595) and the restaurant has up to date equipment for ease of service.The seven items were interpreted as the factor reliability.The five ( 5) variables that loaded on component two were; the restaurant serves tasty food (0.752), the restaurant offers a variety of menu (0.744), the security and safety of the restaurant (0.643), accessibility and clarity of information needed (0.604) and the restaurant insist on error free records (0.546).It was noted that the five converged on the factor responsiveness.
The third component had the following four variables loading on it; arrangement of premises, equipment and environment (0.787), arrangement of restaurant creates ease of movement (0.757), warm, welcoming and honest staff (0.613), general ambience is comforting (0.525).The commonality of these four was interpreted as the factor physical evidence.The fourth component had four associated variables including; customers get individual attention (0.686), the restaurant has the customers best interest at heart (0.667), the restaurant has operating hours convenient to the customers (0.656) and employees individually intercede for customers (0.589).The fourth component was interpreted as the factor empathy.
Component five was dropped when it was noted that the variables that loaded onto it had factor loading less with a value ≤ 0.5, hence were not significant in explaining the variations.
The test of internal validity of the resulting construct from restaurant customer"s service perception indicated that; seven items loaded on the first construct and that the overall Cronbach"s alpha for factor 1 (reliability) was α = 0.930.Seven items loaded on the second factor (responsiveness) and its resulting overall Cronbach"s alpha was α = 0.883.The overall Cronbach"s alpha for factor 3 (physical evidence) was α = 0.845 with four items loading on it.The last factor (empathy) had four items loading on it and its overall Cronbach"s alpha was α = 0.744.These findings were inferred to mean the four constructs were reliable in explaining the perception of restaurant customers.This further meant that the restaurant customers strongly agreed that the main determinants of service quality experience in restaurants were; reliability, responsiveness, physical evidence and empathy respectively.

Parameters That Define Service Quality and Satisfaction in Emerging Chain Restaurants
The results of service expectations and service perception were compared to determine the restaurant customer"s evaluation of the key determinants of service quality and satisfaction.The service expectation analysis using EFA had revealed the following four parameters as most significant in their choice of a service provider; reliability, physical evidence, responsiveness and assurance.The service perception analysis using EFA indicated that restaurant customer"s perceived the following four parameters as most significant in their value judgment of a service provider; reliability, responsiveness, physical evidence and empathy.In a conceptualization by Parasuraman et al. (1988, p.5), the authors coined the definition; "service quality is the degree of discrepancy between customers" normative expectations for the service and their perceptions of the service performance".The preceding factor analysis has established that what restaurant customers expected of services varied from what they perceived after the service encounter.This observation led the study to adopt a paired sample t-test analysis to examine this variation further and identify the specific latent variables that defined service quality and satisfaction.A paired sample t-test was conducted to compare the mean scores for the customer expectation and customer perception of restaurant services and the results displayed in paired sample test in Table 5 below.All the variables posted a significant (p < 0.05) accept one variable; employees satisfy customer needs under the factor assurance.The p < 0.05 values meant that there was a significant difference between customer expectation and perception scores.
Having established that a significant difference existed, the study proceeded to examine the variables with the highest scores under expectation and perception.The disconfirmation paradigm proposed by Parasuraman et al. (1988) guided the paired sample t-test analysis.The expectation minus perception (E-P) analysis of the factor physical evidence showed that the expectation scores were higher than the perception scores and the difference were statistically significant.The most significant latent variable under this construct was "general ambience is comforting".There was a statistically significant decrease in general ambience scores in terms of expectation (M = 4.62, SD = 0.507) compared to perception (M = 4.15, SD = 0.738), t (246) = 9.190 and p = 0.000 (two tailed).The paired difference reflected a mean decrease in general ambience scores as 0.445, with an SD = 0.049 at a 95 % confidence interval ranging from 0.350 to 0.541.The eta squared statistics of general ambience was 0.255 and the study concluded that there was a large effect, with a substantial difference noted in reference to general ambience score obtained at the customer expectation stage and customer perception stage.From Table 5, the other important variables that service managers must pay attention to under physical evidence are; the visual appearance of food presentation (mean difference = 0.486) and the appearance of the physical facility should be visually appealing (mean difference = 0.381).
From Table 5, the E-P analysis of the factor reliability reflected that all expectation scores were higher than the perception scores and the difference were statistically significant.The most significant variable under this construct was "proper speed of dealing with matters".There was a statistically significant decrease in scores of "proper speed of dealing with matters" in terms of expectation (M = 4.56) compared to perception (M = 4.09), with t (246) = 9.944 and p = 0.000 (two tailed).The paired difference shows that the mean decrease in "proper speed of dealing with matters" scores was 0.470, with an SD = 0.742 at a 95 % confidence interval ranging from 0.377 to 0.563.The eta squared statistics of proper speed of dealing with matters was 0.287 and the study concluded that there was a large effect, with a substantial difference noted in reference to the difference between expected and perceived proper speed of dealing with matters.The other important latent variables that define the reliability of a restaurant service facility are; provision of error free records (mean difference = 0.470) and serving food at the right temperature (mean difference = 0.421).
The factor responsiveness showed a statistically significant difference between customer expectation and perception of restaurant services.The most significant variable was the "ability of employees to satisfy customer needs".The expectation score for this variable was (M = 4.76), while the perception score was (M = 4.17) with t (246) = 11.981 and p = 0.000 (two tailed).The paired difference reflects mean decrease in "ability of employees to satisfy customer needs" scores as 0.587, with an SD = 0.770 at a 95 % confidence interval ranging from 0.491 to 0.684.The eta squared statistics of general ambience was 0.368 which indicates a large effect, with a substantial difference noted in reference to the difference between expected and perceived "ability of employees to satisfy customer needs".The other important latent variable that define the responsiveness of restaurant service staff was employees" preparedness to help customers (mean difference = 0.518).
The scores under the factor assurance illustrated a statistically significant difference between customer expectation and perception of restaurant services, with the most significant variable being, "the restaurant serves tasty food".The expectation score for this variable was (M = 4.65), while the perception score was (M=4.22) with t (246) = 9.405 and p = 0.000 (two tailed).The paired difference reflects mean decrease in variable "the restaurant serves tasty food" scores as 0.429, with an SD = 0.771 at a 95 % confidence interval ranging from 0.339 to 0.519.The eta squared statistics of general ambience was 0.264 which indicates a large effect, with a substantial difference noted in reference to the difference between customers expected and perceived opinion of the variable "the restaurant serves tasty food".
Comparison of importance and actual performance of the factor empathy reflected a similar experience showing statistically significant difference in all four areas assessed.The most significant variable under this factor was "employees have the customer"s best interest at heart".There was a statistically significant decrease in scores of the variable "employees have the customer"s best interest at heart" in terms of expectation (M = 4.69) compared to perception (M = 4.28), with t (246) = 8.217 and p = 0.005 (two tailed).The paired difference shows that the mean decrease in "employees have the customer"s best interest at heart" scores was 0.405, with an SD = 0.774 at a 95 % confidence interval ranging from 0.308 to 0.502.The eta squared statistics of the variable "employees have the customer"s best interest at heart" was 0.215 and the study considered this a large effect, with a substantial difference noted in reference to the difference between what customers expected and perceived of employees having the customer"s best interest at heart.

Customers' Judgment of Price Charged For Services Restaurants
Using Pearson correlation coefficient (r), the study sought to examine whether there existed any significant relationship between the respondents profile and prices charged in restaurants.A significant relation with r = 0.002 was observed between level of education and perception of price charged.There were no significant relation between perception of price charged and age, gender, marital status and employment status.A majority (109) of the respondents (44.1 percent) reported that the prices charged in the restaurant were expensive, 94 respondents (38.1 percent) reporting the prices were affordable, 31 respondents (12.6 percent) suggested that the prices were extremely expensive and only 13 respondents (5.3 percent) thought the prices were cheap.A majority of the respondents (63) with Bachelors education perceived the prices were expensive.The relationship between price and consumer expectation and perception was examined.The 29 items that defined customer expectation were transformed into a variable named service expectation.The 29 items that defined customer perception were computed into a variable named service perception.Using Pearson correlation coefficient the correlation between the construct service expectation and price showed an insignificant relationship between the variables.While the correlation between the construct service perception and price was significant (p = 0.000) with an r = -0.505.

CONCLUSION
The restaurant services in Nairobi are characterized by intense competition for customers, a fact that calls for adoption of quality service provision for restaurant competitiveness.The study concludes that there exist a significant difference between what restaurant customers expect and their perception of services in restaurants.The findings are in line with other similar studies that identified the parameters of evaluating service quality in restaurants to encompass; reliability, responsiveness, physical evidence, empathy and assurance (Andaleeb & Conway, 2006[1]; Wei, 1999) [29].The key latent variables that managers in the restaurant business must pay attention to, to optimize customer satisfaction were identified as including; the general ambience of the facility, proper speed of dealing with matters, ability of employees to satisfy customer needs, ability of the restaurant to serve tasty food, and employees who have the customer"s best interest at heart.The demographic analysis demonstrated that the main patrons of restaurants in Nairobi are youthful in age, have financial resources and are highly educated.Whereas price did not have a significant influence on customer expectation, the restaurant customers were keen on evaluating the value of the service after the service encounter.The significant relationship between price and perception of services meant that restaurant customers in Nairobi were not price sensitive and that manager of restaurant facility need to build value in their service offer to justify the referenced price.

Table 1
Sample Size

Table 2
Demographic Profile of the Sample

Table 3
Rotated Component Matrix of Restaurant Customer Service Expectation Varimax with Kaiser Normalization.Rotation converged in 25 iterations This necessitated a rotation of the component matrix to reveal the variables behind the unexplained components.

Table 4
Rotated Component Matrix of Restaurant Customer Service Perception Extraction method: Principle Component Analysis, Rotation method: Varimax with Kaiser Normalization.Rotation converged in 19 iterations

Table 6
Correlations between price, service expectation and service perception