Customer feedback Assignment

Customer feedback Assignment Words: 1565

Student Name(s) and old(s): 1) Fangled Huh 21300495 2) 3) Marker to complete 4) Late penalty: original mark Comments: Table of Contents 1 day = 10% off original mark 2 days = 20% off original mark 3 days = off 4 days or more = assignment marked 0% Introduction and Limitations The purpose of this report is help Dave Smith, the General Manager of the Landmark Hotel Auckland to improve the hotel’s current customer satisfaction measurement scheme by comparing a range of survey methods and recommends the most appropriate survey programmer for the hotel.

The report is broken down to two sections. The first section defines customer satisfaction and articulates the importance of measuring customer satisfaction. Section one also compares the functions of CSS and Transistor. Com and introduces the content analysis method to the Landmark Hotel. The second part of the report defines measures of central tendency and dispersion and presents calculations from the guest survey spreadsheet provided. Based on summary table 1 . 1, the report briefly describes what the calculations mean to the hotel and produced a short recommendation.

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The report is produced with several limitations, which need to be addressed and overcome for future research. The recommendation made to Landmark Hotel under the first part, regarding the most appropriate research method was selected based on one of only two options. Further, since there is no standard ways to perform content analysis, the report simply presented what appeared to be the most logical procedure. Finally, the recommendation regarding internal marketing was much generalized due to word limits.

PART A Defining Customer Satisfaction There is an overwhelming amount of outcome definitions characteristic customer satisfaction, many of which have not yet been empirically tested. According to Ye (1993), some academics and practitioners define customer satisfaction from an outcome-based approach. Alternatively, other perceives and defines customer satisfaction as a process. Engel and Blackwell (1982) defined customer satisfaction as “an evaluation that the chosen alternative is consistent with prior beliefs with respect to the alternative” (p. 501).

This definition is comparable with the disinformation theory, which proposes that guests are either satisfied or dissatisfied based on their expectations prior and subsequent to the purchase of the actual service experience. In this section, we are particularly concerned with the importance of measuring customer satisfaction. Fortunately, this question can be answered directly using the service-profit chain. The service-profit chain is simply a proposition of a series of linkages between “profitability, customer loyalty, and employee satisfaction, loyalty, and productivity’ (Highest, Jones, Loveland, Gasser & Schlesinger, 1994, p. 64). Customer satisfaction represents a crucial role in the service-profit chain because satisfaction is essentially a driver of customer loyalty (retention, repeated business ND referrals), which directly impacts the profitability of a hospitality firm. Customer satisfaction is extremely important because it produces word-of-mouth, reduces operating overheads and facilitates price premiums (Denote & Power, 2006). Hospitality firms constantly look for more effective ways to measure customer satisfaction.

Managers try to achieve greater accuracy in survey outcomes and use them to reliably address the gaps between management’s visions and the customer’s needs. Comparing Data Collection Methods Guest Feedback Forms Guest feedback forms, comment cards or customer satisfaction questionnaires (CSS) re frequent tools used by most hotels for measuring customer satisfaction. Barky (1992) stated two major disadvantages of guest comment cards, “poor construct validity… Poor statistical validity’ (Barky, 1992, p. 51). Yeshiva (1978) also hypothetically considered CSS as “more often than not, unreliable and statically invalid” (p, 72).

Barky (1992) further argues that guest comment cards may indicate customer satisfaction or dissatisfaction and related trends, but generally does not provide sufficient information for decision-making. Porto (2004) outlined several key advantages of using CSS during guest complaints. Porto claimed that asking the guest to fill in CSS would allow the staff extra time to resolve the problem and calms the guest. Transistor. Com In comparison with CSS, Transistor. Com is an online interaction platform. Unlike psychological changes of the hotel guests.

According to Lie, Ye and Law (2012), online reviews are more likely to convey guest’s true feelings, which make up for the missing information that was not captured by guest surveys. Transistor. Com and other meow platforms allow managers to interact with the guests, form one-to-one dialogues and perform qualitative content analysis. Content analysis is a systematic and objective approach to make inference from written data (Downed-Humboldt, 1992). Like all qualitative research methods, content analysis is concerned with meanings and contextual aspects of a service experience.

Content analysis can be described as an intensive exploration of a single customer review and typically, managers look for rich and vivid descriptions in the review, rather than generalized knowledge. However, content analysis and comparable qualitative research methods may lack scientific validity. Thus, it is difficult for managers to make reliable impersonations from a confined sample size. Research Methods and Design The Landmark Hotel needs to go beyond measuring performances and begin to understand perceptions and gain practical and context-dependent knowledge relating to specific guest experiences.

I recommend the Landmark Hotel to focus on qualitative content analysis. Content analysis can be performed on online guest reviews as well as guest comment cards. Additionally, I recommend the use of open- ended question in guest comment cards in order to provide greater insights to the guest’s feelings (Lukas, Hair, Bush & Rotarian, 2005). According to Guthrie and Babysitter (2006), content analysis requires a randomly selected sample, clearly defined criteria of analysis and a systematic data categorization method, so that statistical analysis of the data can be performed.

Downed-Humboldt (1992) proposed an eight step procedure that the researcher should follow when conducting content analysis. These steps can be briefly described as 1) selecting unit of analysis, 2) defining the categories, 3) defining the categories, 4) testing for reliability and validity, 5) define or revise coding rules, 6) pre-testing the revised category schemes 7) data doing and 8) reassessing reliability and validity. According Markova and Rasp (2010), reliability of content analysis can be improved by developing coders for similar contents.

Data coding allow researchers to measure frequency and percentage through tabulations, compute measures of central tendency and dispersion, test for difference, association and interdependence by performing t-tests and chi-square analysis using SPAS applications. Integration After the results have been analyses and interpreted, the researcher can choose to integrate and present the research outcomes within the hotel using an analytical port that is credible and believable.

The report clearly defines the research problem/issue and the research methodology, which clearly articulates the objectives of the research, the research design used, descriptions of samples and the sampling section. This section should contain presentations of findings that are relevant to the research problem. The report should also contain a conclusion section, a recommendation and a limitation section which illustrates “extraneous events that place certain restrictions on the report” (Lukas, et al. , 2005, p. 557). PART B Calculations and Definitions of Measurements

Considering the guest survey spreadsheet, I have calculated the measures of central tendency and dispersion for each behavioral intention scale. For measures of central tendency, I have computed the mean, median and mode respectively. These measures are used as data reduction, which describes the set of responses through a single value. The mean is “the arithmetic average of the sample” (Lukas et al. , 2005, p. 436). The mean is derived from the sum of all values pertained from the responses and divided by the exact number of valid responses.

The median is “the middle value of a rank-ordered distribution” (Lukas et al. 2005, p. 436). The mode is defined as “the most common value in the set of responses to a question” (Lukas et al. , 2005, p. 436). Standard deviation is a measure of dispersion. It is defined as “the average distance of the distribution values from the means” (Lukas et al. , 2005, p. 438). The Excel function which I have used to compute the standard deviation of the data given was STEED. S. STEED. S estimates standard deviation from a sample rather than the entire population.

Data Analysis Table 1. 1: Summary Table Mean Median Mode standard Deviation STEED. S Overall staff service was of a high standard . 27 2 0. 91 I felt welcome and looked after 2. 50 3 0. 68 The maintenance of the hotel was of a high standard 2. 93 0. 58 Upon arrival my room was clean to a high standard 2. 80 0. 85 The room enabled me to get good night’s rest 2. 73 1 . 05 Breakfast was an enjoyable experience 2. 70 0. 65 This hotel demonstrates good environmental practices 0. 69 I would recommend this hotel to others 0. 27 0. 45 I have stayed at this hotel before 0. 3 0. 38 I would stay in another Scenic Hotel after my experience here 0. 47 0. 51 The guest survey spreadsheet provided a number of intention statements aimed to obtain some ideas about guest experiences for certain aspects of the hotel. The management hoped to explore the guest’s intended behaviors as much as possible and the likelihood that guests will demonstrate predictable behavior towards staying at the hotel in the foreseeable future. Table 1. 1 shows that first and second rating scale demonstrated a lower average value in comparison with other rating scales.

Evidently, service standard and staff competence to make guests feel accustomed during their stays did not meet the required expectations. Question to others. Recommendations I postulate that service quality could be a major contributory factor to declines in booking rates. According to Paranormal, Estimate and Berry (1985), there are ten determinants of service quality – competence, courtesy, reliability, responsiveness and understanding are five relatively important determinants directly influenced by staff.

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