The Impact of Customer Service through Information Systems for Lodging Industry

Transcription

1 The Impact of Customer Service through Information Systems for Lodging Industry Yi Wen Fan, Assoc. Professor of Information Management, National Central University, Taiwan Edward C.S. Ku, Doctoral Candidate of Information Management, National Central University ABSTRACT Information technologies offer companies alternative applications of improving customer relationships. Customer Relationship Management systems (CRM) are the most popular systems among these applications these days. Because of the timeliness and relevance of data provided by CRM, many hotels in lodging industry are using CRM to improve their service quality. However, it is rare in literature for researchers to document the processes and the value of CRM applications in lodging industry. This study proposes a CRM process model and aims to study the value of CRM applications for hotels systematically. First, a CRM process model was proposed to illustrate the impact of CRM performance by factors such as customer-oriented culture, system-aided service process, and system support. Then, a survey was conducted to mail questionnaires to 232 subjects. Result from the analysis of 129 returned valid samples show that CRM plays a different role within a hotel depending on CRM operational nature. Overall, the operational CRM provides more benefits to hotel than the analytic CRM at present time. As to the CRM benefits for various functional areas, front desk service perceives the most value of CRM. It is then suggested that room division for improvement for analytic CRM shall attract more academic and practice research for better CRM applications in lodging industry. Keywords: Operational CRM, Analytical CRM, lodging industry. INTRODUCTION As accessibility to information systems increases and cost of computer hardware declines, the use of information systems to improve customer relationships becomes an important issue in today s lodging industry (O Connor and Murphy, 2004; Piccoli et al., 2001; Jain and Singh, 2005). The information systems that aim at the reshaping of customer relationships are often referred as customer relationship management systems. As a matter of facts, CRM is one of the most discussed topics in E-Commerce era. CRM is more important than ever, for service industry such as lodging industry, it is an important component of the tourism industry, providing accommodation (and associated ancillary services) to travelers while away from home. Hotels need to invest a large amount of resource to build rooms and facilities before they can provide service to customers. If a room is not rented or sold out for one night, the room vacancy can not be stored as inventory to be sold next day as other products do. Therefore, the competition among the lodging industry emphasizes on retaining customers as much as possible. Hotels often eager to look for effective and efficient activities that can identify, select, acquire, develop, and keep increasing loyal and profitable customers. On the other hand, information technologies offer companies alternative applications of improving customer relationships. All these methodologies, software, and usually Internet capabilities that help hotels manage customer relationships in an organized way are basically CRM applications. Focus on customer will be a critical factor in the customer relationship (Kim et al., 2003). Despite of this trend of CRM application in lodging industry, there is little systematic research to document the processes and the value of CRM applications in lodging industry. Although all hotels declared a customer-centric approach to CRM implementation, small and large hotels significantly differ in some specific motives, the CRM in large hotels is greatly driven by a need streamline and integrate fragmented, disconnected processes and guest information for enabling, improvement process and reduction of error cost; Ham et al., (2005) argued the information technology significantly affect on the profitability of front-office application, back-office application, restaurant management office, however, only guest-related interface applications were not significant in affecting the profitability.

2 Despite of this trend of CRM application in lodging industry, there is little systematic research to document the processes and the value of CRM applications in lodging industry. Fan and Ku (2006) argued there is different functional CRM implementation from PMS; the purpose of the study addresses this gap in current research by investigating what roles CRM plays in lodging industry, and by studying the value of CRM applications. The results of this study will be of value to hotels engaging CRM activities or planning to adopt CRM systems since it systematically delineates the current roles CRM plays and the factors affecting CRM performance. It will also be of value to those that wish to supply CRM solutions to lodging industry since it will provide evidence to identify rooms for improvement for the future applications. This paper begins with the motivation of this study; section 2 describes the theoretical background of this study, followed by a review of previous researches in Section 3. The research design is then presented in Section 4. Finally, the research findings and conclusions are reported in Sections 5 and 6, respectively. THEORETICAL BACKGROUND AND LITERATURE REVIEW Customer Lifetime Value Perspective The concept of customer lifetime value (CLV), which was defined as the sum of the revenues gained from company s customers over the lifetime of transactions after the deduction of the total cost of attracting, selling, and servicing customers, taking into account the time value of money (Jain and Singh, 2002). Companies with a strategic focus on establishing long-term customer relationships build databases to identify their customers, track customer transactions, and predict changes in customer purchase patterns at an individual level (Ryals, 2005), they can also leverage the purchase information available in these databases in order to target and retain the right customers through customer base analysis, and predicting their lifetime and future level of transactions, considering their observed past purchase behavior (Schmittlein et al., 1987). Early research used CLV as a means to solve specific marketing decision problems pertaining to customer acquisition/retention decisions (e.g., Blattberg and Deighton, 1996). Determination or calculation of CLV was done mainly by considering specific numerical examples in particular business settings, evidence also suggested that successful companies gain a superior competitive advantage and deliver superior customer value as a result of exploiting the organization s assets like brand image, marketing abilities, and organizational innovation when applied to business processes (e.g., Berger et al., 2006; Nadeem, 2006). The benefits of retaining customers have led companies to search for means of profiling their customers individually and tracking their retention and defection behaviors. CLV and CRM CLV is rapidly gaining acceptance as a metric to acquire, grow, and retain the right customers in CRM. Marketing theory and practice has become more and more customer centered, and managers have increased their emphasis on long-term client relationships because the length of a customer s tenure is assumed to be related to long-run company revenues and profitability (Ahmad and Buttle, 2001; Gupta et al., 2004). CRM is organized according to the customer lifecycle because lifetime duration with a firm generally is not perpetual. Consumers may be dissatisfied and find better value elsewhere (Oliver, 1999) or change their lifecycle in a way that causes them to lose the need for the product. Effectively, marketers need to predict the future purchasing behavior of customers (Ryals, 2005) to arrive at their Customer Lifetime Value. There have been some studies relevant to the CRM literature that deal with customer level analyses. For example, Reinartz and Kumar (2003) explored the antecedents of profitable lifetime duration of a customer; Knott et al. (2002) formulated and evaluated the next-product-to-buy models for improving the effectiveness of cross-selling at the individual customer level; Fader et al. (2005) proposed a simpler alternative to Pareto/NBD model in the form of a beta-geometric/nbd model for predicting customer s future purchase contingent to past purchase behavior. While all of these studies discussed CLV looks at what the retained customer is worth to the organization now, based on the predicted future transactions and costs (Berger et al., 2006; Mulhern, 1999). Looking forward to the value of future sales and costs fits more comfortably with the development of CRM strategies than current period profits.

3 Customer Relationship in Lodging Industry Lodging industry participants face an increasingly competitive market. In addition, the basis of competition is changing. Location, a key driver of business, is fixed in the short and medium term and attracting and retaining customers based on facilities and amenities is becoming increasingly difficult as they have become increasingly standardized across competing brands. CRM has its roots in relationship marketing inaugurated by the influential work (Seiders., et al, 2000). Relationship's marketing rational is to enhance long-term profitability by moving from transaction-based marketing and its prominence in attracting new customers, to customer retention by means of effective management of customer relationships, successful CRM is applied technology for marketing, sales and service (Chan, 2005), for example, integrated call center, OLAP, data warehouse application for a firm. Piccoli et al., (2001) pointed customer established a need for the produce is the first stage of customer service life cycle; Piccoli et al., (2004) validated a descriptive taxonomy of customer needs amenable to online fulfillment. From reservation periods, much of customer s requests will happen from customers, customer requests are the collective outcome of the customer's perception, evaluation, and psychological reaction to the consumption experience with product or service (Fornell, 1992). From the Implementation of CRM in the lodging industry, there operational CRM implementation is significantly affect on the profitability in lodging industry (Fan and Ku, 2006). As to the CRM benefits for various functional areas, the front offices service perceives the most value of CRM. Figure 1: Conceptual Framework RESEARCH MODEL In CRM activities, a customer-oriented firm will integrate their service process to create their target and market strategy(skaates and Seppeanen, 2005), CRM profitability is probably one of the most fundamental and extensively studied topics in marketing and service management, from service provide view, profitability based on customer focus of a organization, and its service process fit, considering the conceptual CRM function perspective, CRM implementation are from different function, the research model of this study is depicted in Figure 2. Figure 2: Research Model

4 Customer Relationship Management Profitability CRM is a technology-enabled business strategy whereby companies leverage increased customer knowledge to build profitable relationships, based on optimizing value delivered to and realized from their customers, and by automating and improving the businesses processes in the areas of sales, marketing, customer service, and support. With the ever-increasing competition for marketing dominance, many firms have utilized CRM systems to improve their business intelligence, decision making, customer relations, and quality of services and product offerings. The concept of customer-oriented management is underpinned by the identification and satisfaction of customer needs leading to improved customer retention, which is based on corporate profitability (Day, 2006). The rapid advances in information and communication technology provide greater opportunities for today s firms to establish, nurture, and sustain long-term relationships with their customers than ever before, and CRM requires perfect alignment with the ever-changing needs of customers based on integrated and reliable customer information (Sigala, 2005). Previous research has indicated that CRM provides analytical, operational, and direction capabilities: the analytical capabilities aid profitability maximization from the customer relationship (Ryals, 2005), the operational capabilities influence the customer value process, and the direction capabilities depend on strategic skills and reflect the efficacy of long-term cooperation and organizational values. Operational CRM consists of specifying a suitable and replicable business, and analytical CRM refers to the firm-level processes involved in analyzing customers and the market. From the CLV perspective, CRM has the potential to deliver substantial benefits to firms in terms of long-term profitability (Ahmad and Buttle, 2001; Gupta et al., 2004). The economic benefit is easily justified in terms of enhancing lifetime value; firms also enjoy noneconomic benefits such as enhanced customer trust, commitment, and cooperation. Moreover, a competitive advantage is obtained by the inability of competitors to copy successful customer relationships, in contrast to product attributes, sales promotions, and advertisement campaigns. Customer Focus The lodging industry was a customer orientation organization, hotels espousing a certain strategy type do better than other, but there are trade-offs (Phillip, 1996). For example, hotels consider competitive strategy or service strategy. A service organization aspiring for leadership position creates an organization wide customer orientation (Jain and Jain, 2005); customer should feel that the organization genuinely cares about them and take planned efforts to reflect into its practices. Customer oriented hotels provide service as promised and continue to put customers request and interests ahead of his or her own (Han et al., 1998; Kim and Cha, 2002), when employees of customer oriented hotel provide superior service as a representative of the hotel, the service image of the hotel will improve, customer focus appears to have direct relationship with process fit after system implementation. Moreover, customer requests are critical for establishing long-term customer relationships (McKinney et al., 2002; Patterson et al., 1997). A guest select the hotel that he/she will stay, and make request to the hotel which he/she book; and the staff will record the guest special need to information systems during staying period, after the guest check out, the record about the guest will transfer to guest information systems; a customer focus hotel will analysis their customer request and the staff record the guest s request in reservation systems, and develop marketing and service strategy; On the next service process, that is, when the guest return to the hotel, the hotel will provide personalized service to their guest, we develop H1 that is stated as follows. Hypothesis 1:Customer focus is positively associated with process fit. Process Fit Beyond environmental and organizational factors, the success of CRM depends on a customer-focused strategy that is often implemented by reengineering current customer interaction processes and sometimes designing entirely new processes (Hansotia, 2002). Process fit to the corporate operations is necessary in making CRM activities become familiar with the customer-oriented work process. In the customer information centric characteristic of CRM, companies should analyze customers experiences and problems, then respond and support their needs. CRM requires the perfect alignment with ever-changing customers needs based on the integrated and reliable customer information.

5 In a customer oriented hotel, process fit was conducted employees worksheet (Roh et al., 2005); In lodging industry, when a guest check in, employee used guest history information to understand guest behavior, and after guest check out, they recorded guest requestment, the process fit was made employee prepared worksheet for guest. With the personal service delivery, guest wills feedback their need to the hotel, and employee can analysis their request, or develop marketing strategy. Implementation of hotel information system helps manage all hotel activities interactions. Computerized guest-history systems for hotels are a technological alternative to the cumbersome, hand-kept method of maintaining rolodex files for personalized service (Bieber, 1989; Sparks, 1993), and it is contributed to enhanced performance in reservation, marketing and control areas. From the role change of information technology in lodging industry, one of PMS Key functions is reduced hotel operational cost (Phillips, 1999). Revenue system and yield management system will helps managers of hotel to segment their customer (Griffin, 1995), and develop pricing strategy. Every interaction between the guest and the customer is an opportunity to refine knowledge about her or him and to further build a relationship. Thus, we develop H2 that is stated as follows. Hypothesis 2:Process fit after system implementation of lodging industry is positively associated with customer relationship management Profitability. Operational and Analytical CRM Profitability Sigala (2005) argued although all hotels declared a customer-centric approach to CRM implementation, small and large hotels significantly differ in some specific motives, which clearly indicate hotel different operational problem and managerial situation; significantly, the CRM in large hotels is greatly driven by a need streamline and integrate fragmented, disconnected processes and guest information for enabling, improvement process and reduction of error cost. There are two type of CRM, and they will provide analytical and operational capability (Xu and Walton, 2005; Fan and Ku, 2006), valuable customer insights can be derived from operational information obtained from various channels and customer touch points, such insights created by analytic processes can greatly improve future operations(chan, 2005). Ham et al., (2005) argued the information technology significantly affect on the profitability of front-office application, back-office application, and restaurant management office. Conspicuous, functional of sub-business unit (SBU) play a motivated role among customer relationship management. We develop H3 that is stated as follows: Hypothesis 3:The greater the application CRM functions of SBU, the great customer relationship management Profitability in lodging industry. RESEARCH METHODOLOGY Sample and Data Collection There are 2,629 hotels identification from Tourism Bureau of Transportation and communication, 58 of 4 and 5 stars hotel were selected to be our samples, which those hotels use information systems to be as a CRM system. The other hands, we concerned the one of the success factors was the firm is used the centralized customer database (Roberts et al., 2005), that is, each division of the firm can share and use the information of database to server their guest, the service procedure will influence CRM performance. Thus, we mailed total 4 survey questionnaires to each hotel(included Reservation, Front Office, Sales and Marketing, and Housekeeping Department for each hotel), the total 232 questionnaires was mailed. There are 129 survey questionnaires were collected from hotels in Taiwan, which have implemented and are operating the Property Management systems, Reservation Systems, or Guest History Systems. The systems include the functions of response, reservation center management, guest history Systems, business intelligence, personalization, sales force automation, customer profiling/segmentation and so on. By CRM functional perspective, there is different functional CRM implementation from PMS; thus, the full survey was administered to persons who work in the divisions of Reservation, Front Office, Sales and Marketing, and Housekeeping. The returned rate is 55.6%, sample description sees Table 1:

6 Table 1: Sample Description Item Management Total Analytical Sales /Marketing % % Reservation % Operational Front Office % % Housekeeping % Total % % Measures Expert for the functional implementation, the other three construct were measured with a multi-item scale, as shown in Table 2. Customer Focus Successful lodging industries know that they must make every decision with the customer in mind. In few other industries do customers provide the significant amount of information hotel guests divulge when making a reservation and during their hotel or restaurant (Kim et al., 2003; Piccoli et al., 2003). Every interaction between the guest and the customer is an opportunity to refine knowledge about her or him and to further build a relationship. The measure was developed by modifying the scale of Kim et al., (2003) to suit the customer focus context of lodging industry and contains three items. Process Fit after System Implementation Process fit after system implementation will help service providers become more effective in their service profitability. From service delivery perspective, lodging industry provided their efficient service in order to set the highly service standard to their customer (Danaher and Mattsson, 1998), the measure is modified from the scale of the process fit (Roh et al., 2005), to suit the process fit after system implementation context of lodging industry, and contains five items for process fit. Functional implementation Functional of sub-business unit (SBU) play a motivated role among customer relationship management. In the study, we are separated SBU into two functional: operational and analytical function, operational function including front office, reservation, and housekeeping department, and analytical function including sale and marketing department. CRM Profitability Based on the conceptualization of CRM function, The study focuses on lodging industry applied information systems in CRM activities, the construct is adapted with Roh., Ahn., and Han s CRM Profitability (Roh et al., 2005) and to suit the process fit after system implementation context of lodging industry, and contains four items for CRM profitability. Table 2: Items in Survey Factors Item Description Customer Focus CF1 Hotel forced on guest service. CF2 Hotel forced on customer information. CF3 Employee understood the guest service concept of hotel.) Process Fit PF1 The customer interaction process built in system are will equipped PF2 The linking between other service departments is well control. PF3 The personalized service support processes are well constructed. PF4 The system provided guest information in my service process. PF5 Service process is controlled through information system. CRM Profitability CRMP1 Developed new market by systems. CRMP2 Increased occupancy by systems. CRMP3 Increased customer satifactation by systems. CRMP4 Increased revenue by systems.

7 ANALYSIS In the study, PLS-Graph Version 3.01 was used to verify the measurement and test hypotheses. Structured equation modeling (SEM) with partial least squares (PLS) analysis allows empirical assessment of the measurement model used in this study. Accordingly, partial least squares via PLS-Graph 3.00 Build 1058 (Chin 1994) was used to analyses the data. The stability of the estimates was tested via a bootstrap re-sampling procedure. A PLS model is analyzed and interpreted in two stages: first, the assessment of the reliability and validity of the measurement model and second, the assessment of the structural model. This sequence ensures that the constructs' measures are valid and reliable before attempting to draw conclusions regarding relationships among constructs. Measurement Model By observing the factor loading of each item, individual item reliability can be examined, a factor loading higher than 0.6 can be viewed as high reliability and a factor loading less than 0.5 should be dropped. Item reliability, convergent validity, and discriminant validity serve to test the measurement model in PLS. In Table 3, the loadings of all indicators are larger than 0.5. Table 3: Factor Loadings and Correlation Factors Item Loading Item construct correlation t-statistic SC CF CF CF PF PF PF PF PF PF CRMP CRMP CRMP CRMP CRMP Convergent validity should be assured when multiple indicators measure one construct. Convergent validity can be examined by reliability of constructs, composite reliability of constructs, and average variance extracted (AVE) by constructs. Construct reliability can be assessed with Cronbach s alpha. To obtain composite reliability of constructs, the sum of loadings should be squared and then divided by the combination of the sum of squared loading and the sum of the error terms. AVE reflects the variance captured by indicators. If the AVE is less than 0.5, it means that the variance captured by the construct is less than the measurement error and the validity of a single indicator and construct is questionable. The composite reliability, AVE, and Cronbach s alpha values in Table 4 indicate high internal consistency. Table 4: Reliabilities and Variance Extracted Construct Composite Variance Cronbach s reliability Extracted Alpha CF PF CRMP Discriminant validity focuses on testing whether the measures of constructs are different from each other. Discriminant validity can be assessed by verifying the factor loading of indicators. To have discriminant validity, indicators should have higher loading to the defined construct than to other constructs. Because PLS-Graph only provides factor loadings on one construct, procedures were used to generate cross-loading values. Tables 5, and 6 show these conditions hold.

8 Table 5: Cross-Factor Loading Scale Items CF PF CRMP CF CF CF PF PF PF PF PF CRMP CRMP CRMP CRMP Table 6: Descriptive Statistics: Mean Standard deviation CF PF CF PF CRMP Structural Model Direct Model The test of the structural model includes estimating the path coefficients, which indicate the strengths of the relationships between the dependent and independent variables, and the R-square value, which indicates the amount of variance explained by the independent variables. R-square represents the predictive power of the model and interprets the same as in multiple regressions. A bootstrap resampling procedure was used to generate t-statistics and standard errors. The bootstrap procedure utilizes a confidence estimation procedure other than the normal approximation. Table 7 shows the coefficient of path analysis. Based on the results, H1, H2 were supported as seen in Table 7. Table 7: Hypotheses Testing Dependent variable: CRM Profitability Independent variable Model 1 Model 2 CF->PF (H1) 0.552* 0.552* PF->CRMP (H2) PF*FI (H3) (13.702) 0.742* (24.294) (12.377) 0.731* (21.014) 0.074* (1.985) R Differenced R f Test of differenced R * P<0.05* Moderating Effect Moderating effects can be assured by comparing the difference between the main effect and the moderating effect models. We first obtained the R-square (R 1 2 ) of dependent variable only. Then, the R-square (R 2 2 ) of the moderating effect model was obtained by including the independent variable, moderator, interaction term, and dependent variable in the model. Interaction terms used in the study were obtained for those variables that contain first-order only, the interaction terms are calculated by adding the product of each indicator in the independent variable and each indicator in the moderator.

9 We then derived an estimated effect size of f 2 from (R 2 2 R 1 2 ) / (1 R 2 2) and then obtained a pseudo F-value by multiplying f 2 with (n k 1), where n is the sample size and k is the number of independent variables in the regression equation. Finally, we compared the pseudo F-value with F1, n k 1. The above four steps can test the change of variance extracted by adding a new variable (the interaction term) into the model (Carte and Russell, 2003). Based on the result, H3 was supported DISCUSSION Implications for Practice and Research From the competition among the lodging industry emphasizes on retaining customers as much as possible, hotels eager to look for effective and efficient activities that can identify, select, acquire, develop, and keep increasing loyal and profitable customers. Despite of this trend of CRM application in lodging industry, the study addresses the roles CRM plays in lodging industry, and by studying the value of CRM applications. This result will be of value to hotels engaging CRM activities or planning to adopt CRM systems since it systematically delineates the current roles CRM plays and the factors affecting CRM profitability. Our results provide empirical evidence to explain how customer focus and process fit influent CRM profitability. And our result indicate PMS will provide analytical and operational CRM capabilities under functional implementation in lodging industry; Customer oriented hotels provide service as promised and continue to focus customers request and analysis their behavior, Every interaction between the customers are opportunity to refine knowledge about guest to further build a relationship. Computerized guest-history systems for hotels are a technological alternative to maintain and analysis valuable operational data form guest, and hotel information system helps manage all guest service activities interactions. A manager will create a customer-oriented culture of organization, train their employee to collect and analysis guest information from reservation channel, and provide personal service via information system. And, customer-oriented employees, those who consider the customer value to be their primary work goal. Analytical capabilities are important to lodging industry, compared with Sigala (2005) and Ham et al., (2005) research finding, our result point important practice implications: It is quite obvious that guest information plays operational and analytical function, and it is significantly affected on the profitability of CRM. But the analytical function is not significantly affected operational CRM profitability; noteworthiness, hotel will enhance analytical function CRM investment, for example, hotel will integrate web function and PMS function, that is, the guest reservation information can be collected from web-site, and integrate them to hotel information system; and, hotel will enhance the analytical function of PMS by investing and bonding analytical tool. For future, analytical CRM implementation enhance profitability maximization from long-term customer relationship, and operational CRM implementation enhance profitability from saving service cost; Moreover, analytical CRM profitability significantly affected on the profitability of operational CRM; by guest service process perspective, hotel managers will concentrate guest behavior analysis.. Unfortunately, there is little investment to analytical CRM, for example, few lodging property linked PMS to web-site, and integrate PMS information from web-site, and few hotel do after sales service. It is different that interactive between operational and analytical CRM, as compare with finance-oriented industry, they put emphasis on analytical function CRM rather than on operational function CRM, and under conceptual of 80/20 rules, firm will segment the grade of customer in advance, and put more attention to the important or valuable customer, and then, to create customer profiles by analytical function. Contrary to finance-oriented firms, customer-oriented hotels view each customer relationship is very important, that is, lodging industry force each guest request by operational function will be the premier point, analyze customer behavior and segmentation for marketing strategy will be applied during customer service process, the result is also important for future study. Limitations This study has a number of limitations. Although cases in Taiwan provide a good opportunity for testing the implications of adopting a large-scale business application developed in a different culture, the generalizability of our findings is limited accordingly.

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