Analyzing Customer Behavior and Decisions in Saudi Arabia Hotel Industry

Transcription

1 International Journal of Engineering & Technology IJET-IJENS Vol:10 No:05 8 Analyzing Customer Behavior and Decisions in Saudi Arabia Hotel Industry Rami H. Alamoudi Department of Industrial Engineering King Abdulaziz University, Jeddah, Saudi Arabia Abstract Businesses and top management must understand what differentiates their companies from others and be obliged to appreciate the need of customers in their sector. The hotel business in Saudi Arabia is expanding rapidly with increasing international arrivals and domestic tourist. The primary objective of this paper is study the customer behaviors of toward the hotels sector and their behavior in shifting between hotels due to certain reasons. The focus was on the hotels located in Jeddah, Saudi Arabia such as Hilton, Weston, Sheraton and others. Most of the customers go through different hotels due to service provided, variety of offers, low prices and proportions. There has been no systematic study on customer behavior and its analysis in Saudi Arabia. Therefore, this paper reports the results of a steady conducted to assess the behavior of customers toward the hotels sector in Saudi Arabia. This was obtained by carrying out a survey with a sample size of 184 customers. The survey contains 9 questions and the analysis of each question is presented in this paper. This was implemented by applying the concept of Markov analysis which deals with the probabilities of future occurrence by analyzing presently know probabilities.. The results of this paper can be used as a guideline for all hotels in Saudi Arabia to understand the customer behaviors and for the management to meet and satisfy these behaviors. Index Term Markov analysis; customer behavior; decisions, vector of states; transition probabilities. I. INTRODUCTION SAUDI Arabia has a significant potential for tourism development. Top executives must understand what differentiates their companies from others and must understand the need of the customers in their markets [1]. If these two ingredients are understood, a business can develop a strategic plan to create a market niche and develop their customer base to be successful. Development of this information along with the development of the internal business processes can lead to some form of a competitive advantage in the market. The businesses and their representatives are directly responsible for the patterns of purchases (in the long run) of each of their customers. How the customer will react within certain R. Alamoudi is an Assistant Professor in Industrial Engineering Department at King Abdulaziz University, Jeddah, Saudi Arabia. He received his Ph.D. degree in Industrial Engineering from the University of Miami in May His research interests include, engineering management, complexity analysis of manufacturing systems and supply chain systems, and discrete event simulation ( rhalamoudi@kau.edu.sa). situations is largely due to the education and supplying the customer with enough data and tools to proficiently inform them of what is to be completed and within what context and timeframe [1]. Understanding the customer and their reactions to the environment will prolong the life of the relationship between businesses and their customers. Understanding the customer can be a starting point for most businesses and a re-evaluation point for most others [2]. There are at times where a gap occurs between what customers expect and what management / businesses presume they expect. This often happens because companies overlook or do not fully understand customer s perceptions and expectations. Market share is the portion or percentage of sales of a particular product or service in a given region that are controlled by a company. Market share is used by businesses to determine their competitive strength in a sector as compared to other companies in the same sector. It also allows you to accurately assess your performance from year to year. Regardless of considerable efforts by many researchers [2, 3, 4] to improve the productivity in the hotels sector, a key limitation of their researches is not considering customers behaviors toward the hotels sector. In this paper, we conducted a questionnaire to search for the people that go to different Hotels and the factors affecting on their decisions such as promotions, low prices, and other information related to their decisions as it will be shown in the survey. There are about 9 different questions to see the customer behavior toward different Hotels in Saudi Arabia in the survey. The surveys have been distributed in different locations in Jeddah, as well as we have uploaded it on the internet with the help of the Survey Monkey Corporation. This survey is beneficial in our study because the questions mentioned in the survey has been directed toward a certain goal, and that is, it will be helpful in thee Markov analysis discussed in this paper. The structure of this paper proceeds as follows: Section 2 explains the structure and the analysis of the questionnaire. Section 3 discusses the technique used to predict the customer s behaviors and decisions toward the hotels sector. Market share for a long run using equilibrium condition are presented in Section 4. Finally, Section 5 presents a summary of results and directions for future research. II. ANALYSIS OF THE SURVEY The survey has been performed through the distribution of a questionnaire to 184 customers in Jeddah, Saudi Arabia,

2 International Journal of Engineering & Technology IJET-IJENS Vol:10 No:05 9 who has visited many hotels in Saudi Arabia for the last 3 years. Four different hotels have been involved in the questionnaire. These hotels are as follow: Hilton, Weston, Sheraton, and other hotels located in Jeddah. A structured questionnaire was given to each customer asking him / her if he /she has visited any of the above mentioned hotels. If not a thanks letter will has been given to the participant. We attempted to enhance our response rate by undertaking a number of steps. First, participants were assured that all responses were top secret and that only comprehensive results would be presented. Second, each participant was offered an executive abstract of the study. In this questionnaire the Principles of Questionnaire Construction devolved by Presser et al. [5] has been considered. The survey questionnaire requests data about the customer s behaviors toward the hotels sector and what factors affect their decisions in shifting from one hotel to another. In conducting the survey, a sample size of 184 has been considered and the analysis on each question has been investigated, to show the answers in percentages as follows: for the first question in the survey which is; which hotel do you often go to? (45.1%) of the customers prefer to go to Hilton, (8.7%) of the customers prefer to go to Sheraton, 32 % prefer to go to Weston and 16 % prefer to go to other as shown in figure 1. For the second question in the survey, which was; from which hotel you usually receive the advertisement? (51.1%) of the customers stated that they have received the advertisement from Hilton, (27%) of the customers stated that they have received the advertisement the other hotels and (8.2%) of the customers stated that they have received the advertisement from Sheraton as shown in figure 2. For the third question in the survey which was; how many times do you often go to the (12%) of the customers go to their particular hotel due to promotions and (11.4%) of the customers go to their particular Fig. 2. Percentages of advertisement of hotel using brochures. Fig. 3. Customers distribution-visiting Hotels (yearly). hotel due to the clean look of the rooms as shown in figure 4. For the fifth question in the survey, which was; do you usually shift from one hotel to another? (52.2%) of the customers shift from one hotel to another while (47.8%) of the customers don t shift to other hotel and remain in their particular hotel as shown in figure 5. For the sixth question in the survey which was; if yes, which hotel do you go to? (if no go to question 8) (36.5%) of the customers like to shift to Hilton, (25%) of the customers like to shift to Weston, Fig. 1. Customer s distribution in the hotel. hotels annually? (.5%) of the customers go twice a year to the hotels, (19.6%) of the customers go more than four time a year, (19%) of the customers go three times a year, (15.8%) of the customers go once a year and (14.1%) of the customers go four times a year to the hotel as shown in figure 3. For the fourth question in the survey which was; what are the reasons for going to this particular hotel? (28.8%) of the customers go to their particular hotel due to service provided, (26.1%) of the customers go to their particular hotel due to variety of offers, (21.7%) of the customers go to their particular hotel due to low prices at some time of the season, Fig. 4. Distribution of choices going to different hotels. (19.8%) of the customers like to shift to Sheraton and (18.8%)

3 International Journal of Engineering & Technology IJET-IJENS Vol:10 No:05 10 of the customers like to shift to other hotels as shown in figure 6. For the seventh question in the survey whish was; what are the reasons of shifting to this particular hotel? (26%) of the customers like to shift to other hotels due to low prices on some seasons, (25%) of the customers like to shift to other hotels due to the service provided, (25%) of the customers like to shift to other hotels due to variety of offers, (28%) of the customers like to shift to other hotels due to promotions, and customers rate the service in Sheraton as very good, (14.7%) rate the services in Sheraton as excellent and (7.1%) rate the services in Sheraton as not acceptable. (38%) of the customers rate the service in Weston as very good, (34%) of the customers rate the service in Weston as excellent, (28.8%) of the customers rate the service in Weston as average and (2.7%) of the customers rate the services in Weston as not acceptable. (41.8%) of the customers rate the services in Hilton as very good, (32.6%) of the customers rate the services in Hilton as excellent, (21.7%) of the customers rate the services in Hilton as average and (3.8%) rate the services as not acceptable as shown in figure 9. III. STATUS OF RESOURCE USE AND MANAGEMENT IN SAUDI ARABIA HOTEL INDUSTRY Statistical technique used in forecasting the future behavior of a variable or system whose current state or behavior does not depend on its state or behavior at any time in the past in other words, it is random [6]. For example, in the flipping of a coin, the probability of a flip coming up heads Fig. 5. Distribution of customers prefer shift. Fig. 8. Customer satisfaction distributions. Fig. 6. Percentages of customers that like to shift between hotels. (3.1%) of the customers like to shift to other hotels due to the clean look of the room as shown in figure 7. For the eighth question in the survey, which was; are you happy with the customer service of the hotel you usually go to? (87%) of the customers are satisfied with the customer service of the hotels they go to, while others (13%) are not satisfied with the customer service of the hotel they go to, as shown in figure 8. For the ninth question in the survey which was; how do you rate the service in the hotel? (46.2%) of the customers rate the service in Sheraton as average, (32.1%) of the Fig. 9. Services quality assessment made by customer. Fig. 7. Distribution of customers shifting. is the same regardless of whether the previous result was heads or tails. In accounting, Markov analysis is used in estimating bad dept or uncollectible accounts receivable. In marketing, it is used in modeling future brand loyalty of consumers based on their current rate of purchases and repurchases. In quality control, Markov analysis is applicable to common-cause problems and other sequence dependent events, and can

4 International Journal of Engineering & Technology IJET-IJENS Vol:10 No:05 11 handle system degradation. Named after its inventor, the Russian mathematician and a probability theory pioneer [6]. The Markov model assumes that the future is independent of the past given the present. When using Markov the random variable is indexed in time, which can be either discrete or continuous. The number of first-order differential equations will equal the number of states of the model [7]. Markov methods offer significant advantages over other reliability modeling techniques, some of these advantages are [8]: 1- Simplistic modeling approach: The models are simple to generate although they do require a more complicated mathematical approach. 2- Redundancy management techniques: System reconfiguration required by failures is easily incorporated in the model. 3- Coverage: Covered and uncovered failures of components are mutually exclusive events. These are not easily modeled using classical techniques, but are readily handled by the Markov mathematical. 4- Complex systems: Many simplifying techniques exist which allow the modeling of complex systems. The most important features and benefits for Markov analysis are [8]: State transition diagrams, Powerful Markov engine, Sequence dependent events, Operational, degraded, and failed states, Steady state and transient results, Common cause s failures, Induced failures, System degradation, and Multioperational state components. In the following section, future states or conditions using Markov analysis has been determined. The long-term or steady-state conditions using only the matrix of transition probabilities has been computed. A. The Vector of State probabilities for Four Hotels Let s look at the vector of states for people in Jeddah with the hotels with 5 stars category. There are a total of 184 people filled up the survey that visited the hotels during the last year 3 years. Eighty three people stayed at Hilton, which will be called state 1. Sixty seven people stayed at Weston, which will be called state 2. Sixteen people stayed at Sheraton, which will be called state 3, and eighteen people stayed at different hotels with 5 stars category in Jeddah, which will be called state 4. The probability that person will be stayed at one of these four hotels is as follows: State 1- Hilton: 83/184= 45= 45.11% State 2- Weston: 67/184= 36= 36.41% State 3- Sheraton: 16/184= 09= 8.70% State 4- others: 18/184= 10= 9.78% The probabilities can be placed in the vector of state probabilities shown as follow: π (0) = (45, 36, 09, 10) Where: π (0) = vector of state probabilities for the four hotels for period 0 Recall that the Hilton hotel represents state 1, Weston hotel represents state 2, Sheraton hotel represents state 3, and other 5 stars hotels represent state 4. The meaning of these probabilities can be expressed in terms of the various states, as follows: Row 1 π 1 = 45 = probability that a person will stay at the Hilton hotel, state 1 π 2 = 36 = probability that a person will stay at the Weston hotel, state 2 π 3 = 09 = probability that a person will stay at the Sheraton hotel, state 3 π 4 = 10 = probability that a person will stay at other hotels, state 4 Figure 10 provides a tree diagram to illustrate this situation. Notice that of the 40% market share for the Hilton hotel in this period, 23 % (23 = 45(π 1)*51(P11)) will return, 10% will stay at Weston, 8% will stay at Sheraton, and 5% will stay at different hotels. Although a tree diagram and the calculations just illustrated could be used to find the state probabilities for the next period and the period after that, the tree would soon get very large. Rather than use a tree diagram, it is easier to use a matrix of transition probabilities that will be discussed in section 3.2. This matrix is used along with the current state probabilities to predict the future conditions [9]. B. Transition Probabilities for the Four Hotels We used historical data (from the survey) with the four hotels to determine what percentage of the customers would switch each year. After analyzing the surveys, the number of customers that remains in each hotel or switch to other hotels have been counted, as shown in Table I. Table I Number of customers that remains in each hotels or switch to other To From Hilton Weston Sheraton Others Total Hilton Weston Sheraton Others Total 184 Transitional probabilities have been found by dividing each cell of the hotels with the sum of each of it. We placed these probabilities into the matrix of transitional probabilities: P = P11 = probability of being in state 1 after being in state 1 the preceding period 22 = P12 = probability of being in state 2 after being in state 1 the preceding period = P13 = probability of being in state 3 after being in state 1 the preceding period

5 International Journal of Engineering & Technology IJET-IJENS Vol:10 No: = P14 = probability of being in state 4 after being in state 1 the preceding period Row 2 37 = P21 = probability of being in state 1 after being in state 2 the preceding period 48 = P22 = probability of being in state 2 after being in state 2 the preceding period = P23 = probability of being in state 3 after being in state 2 the preceding period 09 = P24 = probability of being in state 4 after being in state 2 the preceding period Row 3 = P = probability of being in state 1 after being in state 3 the preceding period 19 = P32 = probability of being in state 2 after being in state 3 the preceding period = P33 = probability of being in state 3 after being in state 3 the preceding period 19 = P34 = probability of being in state 4 after being in state 3 the preceding period Row 4 28 = P41 = probability of being in state 1 after being in state 4 the preceding period = P42 = probability of being in state 2 after being in state 4 the preceding period = P43 = probability of being in state 3 after being in state 4 the preceding period 50 = P44 = probability of being in state 4 after being in state 4 the preceding period. Fig. 1 Tree diagram for the four hotels for π (1). C. Predicting Future Market Shares If we are in any period n, we can compute the state probabilities for period n+1 as follows: After solving by MATLAB, we found the following results: π (1) = π (0) P π (n+1) = π (n) P (1)

6 International Journal of Engineering & Technology IJET-IJENS Vol:10 No: ( 45, 36, 09, 10 ) ) π (1) = ( 4186, 3059, 1320, 1490 ) (shown by figure 11) π (2) = π (1) P π (2) = ( 4093, 2893, 1394, 32 ) (shown by figure 12) π (3) = π (2) P π (3) = ( 4075, 2848, 1405, 1841 ) (shown by figure 13) Fig. 13. Percentages of being in each hotel in period π (3) π (5) = π (4) P π (5) = ( 4102, 2853, 1415, 1919 ) (shown by figure 15) Fig. 11. Percentages of being in each hotel in period π (1) π (4) = π (3) P π (4) = ( 4083, 2844, 1410, 1892 ) (shown by figure Fig. 14. Percentages of being in each hotel in period π (4) of periods. It is possible to see if the future values are Fig. 12. Percentages of being in each hotel in period π (2) IV. STATUS OF RESOURCE USE AND MANAGEMENT IN SAUDI ARABIA HOTEL INDUSTRY Equilibrium share of the market values or probabilities are normally encountered. One way to compute the equilibrium share of the market, or equilibrium state probabilities, is to use Markov analysis for a large number Fig. 15. Percentages of being in each hotel in period π (5) approaching a stable value. For example, it is possible to repeat Markov analysis for a long time of periods for the hotels. This is not too difficult to do by hand. As we saw previously the probabilities are changing from a period to

7 International Journal of Engineering & Technology IJET-IJENS Vol:10 No:05 14 another. So what would expect in the long run? By definition, an equilibrium condition exists if the state probabilities or market shares do not change after a large number of periods. Thus, at equilibrium, the state probabilities for a future period must be the same as the state probabilities for the current period. This fact is the key for solving for the equilibrium state probabilities. The equation for finding the long period for customers going to each hotel is as follow: π = π P (2) V. DISCUSSIONS AND CONCLUSION In this paper, customer s behaviors and decisions toward the hotel sectors in Saudi Arabia have been studied through surveys and assessment by questionnaire. Markov Analysis technique has been applied to the data of the conducted questionnaire. In this paper, the results of Markov analysis through period 1 to 5 have been calculated and we found the results of each has a slight changing in their values and after finding the forecasting for the long period we found that the forecasting is stable. Based on the ( 1, 2, 3, 4 ) ( 1, 2, 3, 4 ) Using matrix multiplication: (π1, π2, π3, π4) = [(π1) (5100) + (π2) (3700) + (π3) (00) + (π4) (2800), (π1) (2200) + (π2) (4800) + (π3) (1900) + (π4) (00), (π1) (00) + (π2) (00) + (π3) (00) + (π4) (00), (π1) (1100) + (π2) (0900) + (π3) (1900) + (π4) (5000)] Fig. 16. Percentages of being in each hotel in period π(n). π1 = 5100 π π2 +00 π π4 (3) π2 = 2200 π π π π4 (4) π3 = 00 π π2 +00 π π4 (5) π4 = 1100 π π π π4 (6) By adding another equation: π1 + π2 + π3 + π4 (7) Since the number of variables is four and the number of equations is five, we have to do drop one of the above equations so that the number of variables is equal to the number of equations. We will drop equation (4). After solving the equations by MathCAD program, we found the following results: (π1, π2, π3, π4) = (402, 28, 139, 18) These results are results for the hotels for the long period (πn). If we want to compare the main hotels such as Hilton, Weston and Sheraton without looking to other hotels, we will see that the percentage of going to Hilton hotel is 48.96%, the percentage of going to Weston hotel is 34.10% and the percentage of going to Sheraton hotel is 16.93% as shown in figure. Fig.. Percentages of being in the main hotels in period π(n). study of the survey data and after applying the Markov Analysis on the four hotels with 5 stars category, we found that most of the customers will go to the Hilton hotel, then Weston and finally to Sheraton hotel as they were shown on the above figures. For the long period, Hilton hotel is the number one hotel for the customers due to the best services which they give to the customers. It appears that the majority of customers prefer to go to Hilton hotel due to many reasons such the service provided, better customer service, variety of offers, clean look of the room and reasonable prices on many seasons. One promising avenue for future research is to provide customers behavior for each region in the country. Another avenue is to include the concepts of Total Productivity Gainsharing (TPG) in the Total Productivity management analysis to satisfy customers need.

8 International Journal of Engineering & Technology IJET-IJENS Vol:10 No:05 15 REFERENCES [1] Pershing, J. L. (2002). Using document analysis in analyzing and evaluating performance. Performance Improvement, 41(1), [2] Baker, M., and Riley, M. (1994). New perspectives on productivity in hotels: some advances and new directions. International journal of hospitality management, 13, [3] Brown, J., and Dev, C. (2000). Improving productivity in a service business: evidence from the hotel industry. Journal of service research, 2, [4] Alamoudi, R. (2009). Resource Use, Waste, and Total Productivity Management in Saudi Arabia Hotel Industry. International Journal of Basic and Applied Science, 9(10), [5] Presser, S., Rothgeb, J., Couper, M., Lessler, J., Martin, E., and Singer, E. (2004). Methods for Testing and Evaluating Survey Questionnaires. New York: Wiley. [6] Rabiner, L. R. (1989), A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition, Proceedings of the IEEE, 77 (2), [7] Ephraim Y, Merhav N (2002). "Hidden Markov processes". IEEE Trans. Inform. Theory 48: [8] Satish L, Gururaj BI 92003). Use of hidden Markov models for partial discharge pattern classification. IEEE Transactions on Dielectrics and Electrical Insulation. [9] Altinok Y., Kolcak D. (1999). An Application of the Semi-Markov Model for Earthquake Occurrences in North Anatolia, Turkey, Journal of the Balkan Geophysical Society, 2 (4).