Development of the hospitality quality consciousness

The Business Review, Cambridge * Vol. 12 * Num. 1 * Summer * 2009 73 Development of the Hospitality Quality Consciousness Scale: A Pilot Study Wei-Jaw Deng, Ph.D. and Lei Pei, Chung Hua University, Hsinchu, Taiwan, R.O.C. ABSTRACT This research describes the development and validation of a 19-item instrument (hospitality quality consciousness scale, HQCS) for assessing employees’ quality consciousness in hospitality organizations. Two studies were conducted to develop the final scale items, and to evaluate the scale’s reliability and validity. Two core dimensions of quality consciousness are identified, namely, service management and total quality management. The HQSC has a variety of potential applications and can serve as a framework for further empirical research in service management or human resource management field. INTRODUCTION The more special difference between service industry and others industry is the compact intricate relationship between employee and customer. Employee completes service delivering that is part of service product. Customers consume such service product and finally assess the service quality and consuming values. Some time customers even are participators of service production. In such circumstance, there is no chance that employee can correct service failures without customer’s awareness. Therefore, by source management viewpoint, every service enterprise really needs to make endeavor of employee management in service system to pursue the competitive advantage of excellent service quality and customer satisfaction. The performances of front-line employee dramatically affect service quality and customer satisfaction (Mohr and Bitner, 1995). Many researchers emphasized the importance of customer-contact employees in creating and providing good service quality (Bitner et al. 1990; Hartline & Ferrell, 1996; Kelley & Hoffman, 1997). Tsaur and Lin (2004) indicated service quality depends on the performance of interactive result between employees and customer. Heskett et al. (1994) presented a Service-Profit Chain theory that had emphasized the critical role of employee’s performance in pursuing customer satisfaction. The good performances of front-line employee deeply depend on their service attitudes and service behaviors. Constanti and Gibbs (2005) attribute a critical role to the perceived attitude and behavior of front-line staff in service delivery. Ahearne et al. (2007) indicated that salesperson service behaviors are important in building trust and customer satisfaction. Taner (2001) indicated not only employee’s service behaviors are affected by their attitudes but also employee’s service attitudes are affected by their quality consciousness. Moreover, he also addressed that an employee with high positive quality consciousness is likely to be willing to participate in quality improvement efforts and to take on more responsibility for service quality. Therefore, when manager try to make endeavor of service quality and customer satisfaction improvement, employees’ quality consciousness definitely is the critical management topic in present human resource management and service management. Tourism appears as the world’s most important service industry, both by number of employees and by the effects it has on the social and economic development of regions and countries (Holjevac, 2003). Balaguer and Cantavella–Jorda (2002) indicated proceeds that generated from tourism expansion can represent a significant income source for a national economy. Therefore lots of nations had developed tourism industry hardly. The hospitality industry plays an important role in tourism industry (Claver-Cortés et al., 2006). Today, hospitality industry which includes the restaurant, accommodation, entertainment and transportation businesses (Brotherton, 1999; King, 1995) faces increasing competition in global marketplace environment. Therefore, every managers of hospitality industry work hard for achieving competitive advantage of excellent service quality and customer satisfaction. In the improvement task of service quality and customer satisfaction, improving quality consciousness of front-line employee definitely is an effective approach since consciousness affects people’s attitude and behavior obviously. But there are very few researches had discussed about quality consciousness issue or developed a quality consciousness scale. To address the need for a quality consciousness scale that is tailored to measure hospitality employees’ quality consciousness presentation, this research develops an instrument called the hospitality quality consciousness The Business Review, Cambridge * Vol. 12 * Num. 1 * Summer * 2009 74 scale (HQCS). The research scope limits in restaurant only since this is a pilot study. The respondents for validating quality consciousness scale are the front-line employees in restaurant. Consequently, The HQCS proposed by this research can be used in understanding the present employee’s quality consciousness performance and in pinpointing employee’s improvement areas that required more managerial attention and action to pursuit competitive advantage of excellent service quality and customer satisfaction in restaurant enterprise. Moreover, researchers can use this pilot scale result under other hospitality industry scopes to build up a complete hospitality quality consciousness scale. QUALITY CONSCIOUSNESS COMPONENTS Taner (2001) gave the definition of quality consciousness as the employees’ awareness concerning the quality of the service they produce; or attaching high priority to quality in the service they produce. In terms of measuring the quality consciousness of service employee, he also presented an index of quality consciousness to assessment both manager and front-line employee’s quality consciousness in Turkey’s twenty hotel. About related research for addressing the importance of quality consciousness, Daniel et al. (1995) examined the impact of quality strategy and management control systems in management rewards pursuing. They indicated that quality consciousness is a most importance element in quality strategy and management control systems. Peterson (2006) indicated that quality consciousness definitely is a beneficial training topic for assisting employee development and company operation. In the research of Taner (2001), question that measure quality consciousness has “importance of service quality”, “definition of quality service”, “willingness to assume responsibility”, “list of factors that lower service quality” and “contribution to increasing service quality”(point weight are 25%, 25%, 5%, 40% and 5%, respectively) five areas. But these attributes are ambiguous and hard to convince users that scale has validity. Therefore, it is necessary for researcher to develop a more suitable quality consciousness scale. In quality management field, no matter in which industry type, Total Quality Management (TQM) is a fundamental quality management frame system (Byrne, 1992; Luthans, 1995; Saylor, 1992). Chandler and Mcevoy (2000) indicated that the TQM system effectively be executed will improve company’s competitive advantage. Therefore, in every employee’s quality consciousness, TQM is definitely an important knowledge component. For service industry specially, service quality is a critical factor of company’s competitive advantage and continuous business (Palmer, 1998; Parasuraman et al., 1985; Zeithaml et al., 1990). Parasuraman et al. (1988) proposed SERVQUAL scale that has twenty-two attributes for assessing the service quality of general service industry companies. SERVQUAL has five dimensions those are tangible, reliability, responsiveness, assurance and empathy. Moreover, Hartline and Ferrell (1996) indicated the attitudinal and behavioral responses of customer- contact employees can influence customers’ perceptions of service quality. Consequently, if employee can totally know the requirements of good service quality in advance then he will show good positive service attitude and behavior more possible. By above description, service quality also definitely is an important knowledge component in every employee’s quality consciousness. In service industry, operation management of product production is named as service management. The characteristics of service product are intangibility, inseparability, heterogeneity and perishable (Zeithaml and Bitner, 2000). The production management jobs of service industry are much different and difficult for managing than manufacturing industry. Beside, bad service management can cause service failures, bad service quality and low customer satisfaction. Therefore, the concepts of service management also must include into the component of employee’s quality consciousness. In summary, there are three components need to integrate into the component of employee’s quality consciousness and are TQM, service quality and service management. THE SCALE DEVELOPMENT PROCESS The first step in the development of any scale is to construct a sound conceptual specification of the construct being scaled (Churchill, 1979). Based on the above paragraph, the conceptual framework for the HQCS has three necessary components those are TQM, service quality and service management. The five basic elements to a basic understanding of TQM are (1) communication, (2) cultural transformation, (3) participative management, (4) customer focus, and (5) continuous improvement (Richardson, 1997). These five basic elements are treated as first part of design dimensions. The five dimensions of SERVQUAL scale (tangible, reliability, responsiveness, The Business Review, Cambridge * Vol. 12 * Num. 1 * Summer * 2009 75 assurance and empathy) are treated as second part of design dimensions. The characteristic of service management is treated as final part of design dimensions. Therefore, there are eleven design dimensions for developing quality consciousness scale item. The steps employed in constructing the HQCS closely parallel the scale development guidelines provided by DeVellis (1991) and Hinkin, Tracey, and Enz (1997). There are seven steps for constructing scale: 1. Item Generation; 2. Content Adequacy Assessment; 3. Questionnaire Administration; 4. Factor Analysis; 5. Internal Consistency Assessment; 6. Construct Validity; 7. Replication. In first three steps, this research based on above eleven design dimensions and generated an initial pool of twenty-two scale items capturing employee’s quality consciousness. To help identify and capture more specific facets of employee’s quality consciousness, focus group with 8 experts is conducted. The initial pool of twenty-two scale items capturing employee’s quality consciousness is discussed and reworded by focus group to fit the context of the hospitality industry. Additional eighteen scale items are generated in the focus group. Finally, initial forty scale items those tapped the entire spectrum of TQM, service quality and service management are finished. Most of statements are phrased positively and are scored on a five-point Likert scale, ranging from “Strongly disagree (1)” to ‘‘Strongly agree (5)”. The questionnaire comprised two parts. The first part contained 40 statements reflecting agreement degree of quality consciousness. The respondents are asked to rate their levels of agreement in relation to the 40 statements. The second part of the questionnaire included the demographic information of respondent. In step 4 to step 6, the major jobs are scale purification, scale reliability and scale validity. Step 7 is a job content that researcher repeats the scale-testing with a new data set to validate the scale again. Therefore, this research planned two studies for developing HQCS. The first study focused on: (1) examining the reliability of the scale and refining the pool of items, and (2) primarily identifying the underlying dimensions of the scale and refining the pool of items. The second study sought to confirm the validity of the refined scale by analyzing a new data set obtained from another survey. The respondent restaurant is a chain restaurant in Taiwan. This chain restaurant operates two cuisine kinds restaurant. One is steak restaurant and the other is Japanese restaurant. There are total sixteen branch stores of Tasty steak restaurant in Taiwan. There are total seventeen branch stores of Taoban Japanese restaurant in Taiwan. The service quality management system in this chain restaurant is well executed. Therefore, front-line employees are capable to understand statements in research questionnaire and are suitable respondents for this research. In first study, the respondents are front-line employees in Tasty steak restaurants. The respondents of second study are front-line employees in Taoban Japanese restaurants. FIRST STUDY In first study, the respondents are front-line employees in Tasty steak restaurants. One hundred front-line employees participated in this study. The survey method used in this study is mail questionnaire survey. Ten branches of Tasty steak restaurant in Northern Taiwan were picked and mailed questionnaire to its branch manager for helping the execution of survey. After excluding questionnaires with missing values, a total of 76 valid and usable questionnaires were retained for analysis. The demographic profiles of the front-line employees are as follows. The sample included 16 (21%) males and 60 (79%) females among the respondents. The main age group was 21-30 and represented 69% of the respondents. Most of the respondents (75.6%) had a college or university level education. Most of the respondents (67%) had 1-3 years of work experience, with an average length of 1.6 years. In the beginning of scale refinement, Churchill (1979) suggested that the purification of a measurement instrument should begin with the computation of the coefficient α. Items with corrected item-to-total correlation lower than 0.35 were discarded (Parasuraman et al., 1988). Moreover, if item is deleted will increase the whole scale’s Cronbach’s α value then it should delete from scale. As individual items were deleted, each Cronbach’s α value was recomputed for the remaining items and the new corrected correlations were evaluated for further deletion of items. Item number 5, 22, 25 and 32 were deleted from the analysis in first round (Table 1). Item number 21, 23 The Business Review, Cambridge * Vol. 12 * Num. 1 * Summer * 2009 76 and 29 were deleted from the analysis in second round (α value of whole scale is 0.9726). No item was deleted from the analysis in thirdly round (α value of whole scale is 0.9737). Therefore, total seven items were deleted. Table 1 Refinement results of reliability analysis in first round Item number Corrected item-to-total correlation Cronbach’s Αlpha value If item deleted 5 .5340 .9749 22 .4968 .9750 25 .4791 .9750 32 .5130 .9749 Cronbach’s Αlpha value of whole scale .9748 A total of 33 items were retained for further unidimensionality examination. Exploratory factor analysis (EFA) was performed to identify and confirm the underlying structure of the items and to further reduce their number. The Kaiser–Meyer–Olkin (KMO) measure and Bartlett’s test of sphericity were used to ensure that the data had inherent sufficient correlations to perform EFA. In EFA analysis of this study, the principal component analysis with varimax rotation, eigenvalue exceeding 1 and factor loadings exceeding 0.5 are used and set. The KMO index of EFA analysis under 33 items was 0.808, and Bartlett’s test of sphericity was significant at a level of 0.00, which justified the use of EFA. Table 2 Refinement results of factor analysis in first round Factor loading Item number 1 2 3 4 5 8 .823 27 .791 30 .745 15 .711 13 .704 6 .703 2 .643 28 .625 3 b .624 .609 31 .605 19 .593 1 b .551 .539 11 .718 39 .673 12 .642 33 .640 17 .612 36 .599 9 .577 37 .555 20 b .553 .502 4 .551 10 a .468 26 .789 34 b .519 .717 35 .638 38 b .579 .508 7 b .558 .573 24 a .515 16 .735 18 .709 14 .681 40 a .486 Variance explained (%) 23.58 19.94 13.90 13.57 3.26 Note: a Indicate that the item was deleted because its low factor loading b Indicate that the item was deleted because its multiple loading The first round of factor analysis was resulted in a five factors solution, which explained 74.25% of variance. To achieve a more meaningful solution, items were deleted if they loaded equally heavily into more than one factor, and their loadings were smaller than 0.55, in consideration of the small sample size (Hair et al., 1998). Each time items were deleted from the analysis, the factor analysis was re-run and coefficient α was re-computed until a satisfactory result was achieved. In first round, Item number 10, 24 and 40 were deleted because their factor The Business Review, Cambridge * Vol. 12 * Num. 1 * Summer * 2009 77 loading were smaller than 0.55. Item number 1, 3, 7, 20, 34 and 38 were deleted because these items loaded equally heavily into more than one factor (Table 2). No item was deleted in second round. Therefore, total nine items were deleted in the EFA analysis. The process of scale purification in this initial stage reduced the number of items from 40 to 24 items. Among these 24 items, the factor analysis extracted four factors which explained 73.23% of variance with item loadings exceeding 0.55 (Table 3). Cronbach’s α value for each dimension ranged from 0.7518 to 0.9419. This demonstrates that the scales had considerable reliability (Cronbach’s α value for each dimension greater than 0.7) (Hair et al., 1998; Nunnally, 1978). Table 3 Refinement results of factor analysis in second round Factor loading Item number 1 2 3 4 Variance explained (%) Cronbach’s α value 8 .841 27 .772 30 .750 6 .695 15 .692 13 .685 2 .683 28 .667 31 .625 25.63 0.942 11 .745 39 .676 36 .656 12 .654 9 .645 33 .633 4 .632 37 .603 17 .587 22.73 0.942 14 .754 16 .709 19 .610 18 .607 15.71 0.843 26 .789 35 .644 9.16 0.752 SECOND STUDY In second study, researcher sought to confirm the validity of the refined scale by analyzing a new data set obtained from another survey. Using the 24-item HQCS, data were collected from respondents employed in Taoban Japanese restaurants that use same quality management system. Three hundred forty front-line employees from seventeen Taoban Japanese restaurants were asked to fill out the questionnaire. A total of 304 available questionnaires were analyzed. The profile of the respondents included that they were, in the majority, female (76%), fewer than 40 years old (81%), with 1-3 years’ tenure at current positions (47%). Most of the respondents (72%) had a college or university level education. Confirmatory factor analysis (CFA) with maximum likelihood estimation in LISREL 8.80 was utilized to examine the factor structure of the HQCS. Research postulated a priori measurement model linking observed variables with latent factors, and then tested that model for its ability to fit the data using CFA. The fit of the measurement model for the data was based on the 2 χ statistic, standardized root mean square residual (SRMR), comparative fit index (CFI), and goodness-of-fit index (GFI). In the event that poorly fitting models emerged from the initial series of analyses, further model re-specification would be needed to improve the model fit based on standardized residuals and modification indices. Large standardized residuals and modification indices identified pairs of indicators in which the covariance was either over predicted or under predicted by the model. One of the two items was deleted based on redundant content, salience, or content that was ambiguous for determining its placement within the model. The CFA was then rerun to determine whether the modification resulted in an improved fit. This process was continued until a reasonable model was generated. The initial estimation of the 24 item of two-factor structure emotional labor model did not generate a satisfactory result ( 2 χ =565.92, SRMR=0.053, CFI=0.97, GFI=0.76). This indicated a poor fit between the sample The Business Review, Cambridge * Vol. 12 * Num. 1 * Summer * 2009 78 data and the model. The data were subsequently subjected to a specification search as previously described. This search resulted in a final model consisting of 19 items (item 9, 13, 14, 31 and 37 had been deleted), with 10 items loaded into the service quality factor, and 9 items loaded into the TQM factor. The final model provided an improved and reasonable fit for the data ( 2 χ =296.63, SRMR=0.045, CFI=0.98, GFI=0.91). Table 4 lists the dimension and attribute factor loadings and reliability scores. Both service quality and TQM indicators with loadings ranging from 0.72 to 0.87 demonstrated that the HQCS attributes were moderately strong measures of employee’s quality consciousness. In addition, the composite reliability for the service quality and TQM factors were 0.94 and 0.93, respectively, which exceeded the recommended 0.70 (Hair et al., 1998; Nunnally, 1978), and therefore, evidenced the good internal consistency of the HELS. Table 4 CFA results of HQCS (n=304) Dimension and attribute Completely standardized loadings Dimension/ attribute reliability Error varianc e Service quality .94 .18 2 Neat appearance of front-line employee will increase service quality .736 .678 .24 4 Moment of truth will significantly affect service quality .768 .713 .23 6 Appropriate Provision of customer required service will increase service quality .866 .826 .12 8 Precise execution of role-prescribed service will increase service quality .795 .743 .21 11 Short on-line waiting time will increase service quality .817 .766 .18 12 Courtesy and friendliness of front-line employee will increase service quality .851 .807 .13 15 Communication between customer and employee is an important factor for affecting service quality .811 .759 .16 16 Personal attention given by front-line employee will increase service quality .818 .769 .17 17 Listening and understanding the specific needs of customers will increase service quality .793 .740 .18 18 Never give any excuse for responding customer requests will increase service quality .829 .782 .16 Total quality management .93 .23 19 Continuous service quality related training of company employee will increase quality competitiveness .848 .797 .16 26 Effective communication between manager and employee is an important factor for affecting quality competitiveness .731 .658 .26 27 Every employee willingly helps others who have work related service problems will affect quality competitiveness .825 .765 .17 28 Every employee has the belief that quality management is everyone’s duty will affect quality competitiveness .872 .825 .13 30 Every employee has the belief that quality is the most important source of business competitiveness will affect quality competitiveness .837 .784 .23 33 Every employee has the belief that deliver the service right at first time will affect quality competitiveness .717 .644 .38 35 Every employee willingly provides service improvement idea to company will affect quality competitiveness .830 .777 .15 36 Every employee positively collects related customer opinions and provides to company will affect quality competitiveness .734 .663 .29 39 Customer evaluates the consuming value by considering cost and the quality of whole service delivering system (includes service, employee and place) .758 .692 .23 Fit statistics 2 χ =296.63, SRMR=0.045, CFI=0.98, GFI=0.91 Note: the number of attribute is the original item number CONCLUSIONS In highly global and competitive marketplace, every service enterprise really needs to make endeavor of employee management in service system to pursue the competitive advantage of excellent service quality and customer satisfaction. The quality consciousness of front-line employee affects his service attitude and service behavior. Furthermore, service quality and customer satisfaction are affected by front-line employees’ service behavior and performance. Usually employee with high positive quality consciousness is likely to be willing to participate in quality improvement efforts and to take on more responsibility for service quality. Therefore, when manager try to make endeavor of service quality and customer satisfaction improvement, employees’ quality consciousness definitely is the critical management topic in present human resource management and service management. This research proposed a novel hospitality quality consciousness scale to help restaurant for understanding the present situation of its employee quality consciousness. The Major dimensions of employee quality consciousness have been identified as TQM and service management, and a pool of measurement items has been confirmed. An instrument has also been formed that exhibits a high degree of validity and reliability. Furthermore, the HQCS is most valuable when it is used periodically to track restaurant employees’ quality consciousness The Business Review, Cambridge * Vol. 12 * Num. 1 * Summer * 2009 79 performance and to pinpoint areas requiring more managerial attention and action for improving employees’ quality consciousness. In addition, human resource manger in restaurant can use the HQSC as an assessment tool to identify the more “suitable” job applicant. Since research scope of this research was limited in restaurant industry, this HQCS requires further replication in different hospitality contexts to ensure its consistency and generalization. Therefore, researchers can apply this pilot HQCS and propose a general hospitality quality consciousness scale or apply this pilot HQCS in the relationship study with quality consciousness. REFERENCES Ahearne, M., Jelinek, R., and Jones, E. (2007). 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In terms of measuring the quality consciousness. under other hospitality industry scopes to build up a complete hospitality quality consciousness scale. QUALITY CONSCIOUSNESS COMPONENTS Taner (2001) gave the definition of quality consciousness. integrate into the component of employee’s quality consciousness and are TQM, service quality and service management. THE SCALE DEVELOPMENT PROCESS The first step in the development of any scale