Role of Branding on Hotel Culture and its Effects on Orientation and Coaching Process in the Hotel Industry, Empirical Study of Five Star Hotel in Northern Cyprus.
Dissertation-Chapter 1 Methodology
3.1 Introduction
This chapter describes the procedures and techniques used in this study to identify, select, process, and analyze data about the research covariates. The first section in this chapter described the nature of the study. The second section described the instrument of the study. The third section described the population and sampling process. The last section described the demographic characteristics of the sample members and their perception of the main variables in this study.
3.2 The nature of the study
Two different approaches are available to conduct research including the deductive and inductive approaches (Sekaran & Bougie, 2010; Zikmund, Babin, Carr, & Griffin, 2012). In the deductive approach, researchers start with theory and prior literature, develop hypotheses, and end up with empirical evidence. Meanwhile, in the inductive approach, the theory is derived from developed based on data and real observations (Sekaran & Bougie, 2010; Zikmund et al., 2012). This study followed the deductive approach to conducting this study. The study model was drawn on existing theories of culture and marketing and prior literature. The author developed causal relationships between branding, hotel culture, orientation, and coaching; then the author conducted an empirical investigation to test the suggested relationships. The purpose of such investigation was to explain causal relationships between covariates and to generalize the investigation findings.
3.3 The instrument of the study
Research instrument is a tool developed by researchers to collect data on a topic of interest from research subjects in order to achieve the research objective. There are numerous types of research instruments such as a questionnaire, interview, observation, focus group discussion, and among others. This study utilized a survey approach with a questionnaire to collect data about the research variables. The questionnaire has several advantages over other methods. The use of a questionnaire to collect data would allow for a generous reach at very low cost. It also allows for standard answers that can be analysed statically in an efficient manner (Dillman, Smyth, & Christian, 2014). This study designed a structured questionnaire to collect the data. The structure of the questionnaire contained a cover page and five sections. The cover page introduced the research title and objective, information on how to fill the questionnaire, and contacts information. The first section comprised a set of questions that are related to the respondents’ profiles. The second section involved eight items related to branding factor. The eight items were adopted from Zulu, S. P. (2015). The third section contained nine items related to hotel culture and they were taken from Chen, X. R. (2013). The fourth section comprised nine items related to employee orientation which were adopted from Sarpong-Nyavor, A. (2012). The last section included twelve items associated with coaching and they were adopted from Gettman, H. J. (2008). In result, the instrument contains thirty-six items related to the variables. All items were assessed on a six-point Likert-type scale.
The questionnaire was validated by 10 academic experts. The experts assessed the content validity of measures, wording of items, readability and clarity of items, and comprehensibility of the questionnaire. The feedback received led to many modifications in the item language and an overall reorganization of the questionnaire.
3.4 Population, sampling, and data collection
The population of this study was the employees who are working in the five-star hotels in Northern Cyprus, the respondents were 420, The total number of the prospective respondents was 387. The sample frame was taken from Robert L. Mason’s equation, the sample size should be 361. This study applied the convenience sampling technique to distribute the questionnaire. In total, the author distributed 420 questionnaires to the prospective respondents by hand. Out of these, this study received 386 complete answers which are valid for further analysis. This yields a response rate of demographic statics 70%.
3.5 Descriptive statistics
This section described both demographic profiles statistics and descriptive scores for each variable. Table 3.1 exhibits the demographic characteristics of the respondents. The table shows that males and females accounted for 75.5% and 24.5% of the sample members, respectively. 22.7% of the respondents were between 18 and 23 years old, 36.2% were between 24 and 34 years old, 31.0% were between 35 and 40, and the rest were above 40 years old. As for the respondent’s experience, 23% had less than one year experience, and approximately 10% had ten years of experience. Moreover, 36.2% had between 2 to 4 years of experience and 31% had between 5 to 9 years of experience. The department of the respondent was 29.7% Front Office, 38.6% Back Office, and 13.4% managerial. The demographic characteristics of the respondents indicated that the respondents were qualified to participate in the survey, and they would provide informative responses for all the research variables.
Table 3. 1: demographic statistics
| Variable | Details | Frequency | Percent |
| Gender | Male | 292 | 75.5 |
| Female | 95 | 24.5 | |
| Age | 18 – 23 years | 88 | 22.7 |
| 24 – 34years | 156 | 40.3 | |
| 35 – 40 years | 112 | 28.9 | |
| > 40 years | 31 | 8.0 | |
| Experience | < 1 year | 89 | 23.0 |
| 2-4 years | 140 | 36.2 | |
| 5-9 years | 120 | 31.0 | |
| >= 10 years | 38 | 9.8 | |
| Department | Front Office | 115 | 29.7 |
| Back Office | 220 | 56.8 | |
| Managerial | 52 | 13.4 |
Descriptive analyses (means and standard deviation) and a correlation matrix were estimated for each of the variables used in the survey. Table 3.2 shows the means and standard deviations for items of branding. The majority of respondents had a positive attitude toward the branding process in their hotels. Most respondents tended to choose “Agree” regarding all branding items, as the mean values ranged from 3.57 to 4.06.
Table 3. 2: Descriptive Statistics for branding
| No. | Items | Mean | Std. Deviation |
| 1 | Brand is important for the company’s mission | 4.06 | 1.009 |
| 2 | Brand is important for the company’s strategic development | 4.05 | 0.987 |
| 3 | Our company’s objective is to create a competitive advantage through brands | 3.98 | 1.195 |
| 4 | I have knowledge of the company’s positioning and value and apply the knowledge to my work | 3.69 | 1.218 |
| 5 | I am aware that the brand differentiates our company from our competitors | 3.82 | 1.306 |
| 6 | Our company combines various communication channels | 3.75 | 1.233 |
| 7 | Our company conveys information of company brand positioning and value to customers | 3.57 | 1.254 |
| 8 | Our company establishes added value for the brand | 3.82 | 1.255 |
| Overall | 3.84 | 1.18 |
Table 3.3 shows the means and standard deviations for items of hotel culture. The result indicated that the respondents perceived their hotel culture as a supportive culture (overall mean = 3.89) which appreciates employee works (3.86), encourages trust and cooperation between employees (3.98), helps good staff to advance (4.1), and tolerates employee mistakes (3.95). Yet, the respondents indicated that some bureaucratic cultures do exist in their hotels as all decisions are centralised at top (3.8) and that results are more important than procedures (3.66). The respondent also showed that management is picky with trivial things (3.65) and decree imposes changes (3.88).
Table 3. 3: Descriptive Statistics for hotel culture
| No. | Items | Mean | Std. Deviation |
| 1 | I am told when a good job is done. | 3.86 | .928 |
| 2 | Managers help good staff to advance. | 4.10 | 1.107 |
| 3 | My mistakes are tolerated. | 3.95 | 1.132 |
| 4 | Managers keep good staff in their departments. | 4.09 | 1.040 |
| 5 | Cooperation and trust between departments is well. | 3.98 | 1.090 |
| 6 | Management decree imposes changes. | 3.88 | 1.019 |
| 7 | Management is picky with trivial things. | 3.65 | 1.489 |
| 8 | All decisions are centralised at top. | 3.80 | .995 |
| 9 | Results are more important than procedures. | 3.66 | 1.335 |
| Overall mean | 3.89 | 1.13 |
Table 3.4 shows the means and standard deviations for items of orientation. Most respondents tended to choose “Agree” regarding all orientation items, as the mean values ranged from 3.73 to 4.00. It appeared from the respondents’ answers that the orientation process enhances employee satisfaction as one goes around their duties and knows what is expected of him at the workplace.
Table 3. 4: Descriptive Statistics for orientation
| No. | Items | Mean | Std. Deviation |
| 1 | I am highly attracted to my work. | 3.86 | 1.176 |
| 2 | I always come to work on time. | 4.00 | 1.046 |
| 3 | I always finish assigned jobs within time. | 3.80 | 1.052 |
| 4 | I always feel bothered for job failures. | 3.85 | 1.235 |
| 5 | My work and its related activities are more important than others. | 3.85 | 1.308 |
| 6 | My job provides the major source of gratification when compared to all other activities. | 3.73 | 1.348 |
| 7 | I perceive the importance of being identified with my work and evaluating others’ worth on that basis. | 3.80 | 1.052 |
| Overall mean | 3.84 | 1.17 |
Table 3.5 shows the means and standard deviations for items of coaching. The mean values ranged from 3.78 to 3.99. These figures indicated that most of the respondents tended to agree that they had received the necessary coaching to improve their self-awareness and provide them with new skills. Moreover, the respondents tended to agree that the coaching process enhances their satisfaction and performance in the workplace.
Table 3. 5: Descriptive Statistics for coaching
| No. | Items | Mean | Std. Deviation |
| 1 | Coaching improve my self-awareness. | 3.99 | 1.039 |
| 2 | I gained a much clearer understanding of my strengths | 3.93 | 1.093 |
| 3 | I gained a much clearer understanding of my developmental needs | 3.95 | 1.049 |
| 4 | I gained a better understanding of my own motivation through coaching. | 3.84 | 1.117 |
| 5 | Coaching increase my awareness of the effects of my own words and actions. | 3.84 | .954 |
| 6 | I increasingly assume responsibility for my impact on my work environment | 3.78 | .946 |
| 7 | I learned new concepts through the coaching process. | 3.98 | .992 |
| 8 | Coaching provide me with new skills. | 3.98 | .850 |
| 9 | I definitely learn new behaviors through coaching. | 3.93 | 1.042 |
| 10 | others around me acknowledge a distinct change in my behavior, style or interactions with others. | 3.85 | 1.128 |
| 11 | I clearly see the impact of my enhanced performance in the workplace. | 3.92 | 1.085 |
| 12 | I feel more confident about what I am doing on the job as it relates to areas addressed in coaching. | 3.89 | 1.126 |
| Overall mean | 3.91 | 1.04 |
Table 3.6 shows the correlation matrix between the variables. The correlations ranged between 0.596 and 0.678 and all were significant at p < 0.05. The results indicated that there is a satisfactory relationship between the research variables without violating the multicollinearity assumptions as the correlation between variables did not exceed 0.7 (Gujarati, 2009).
Table 3. 6: the descriptive statistics and the bivariate correlations
| Variable | Mean | Std. Deviation | Branding | Culture | Orientation | Coaching |
| Branding | 3.8414 | .66723 | 1 | |||
| Culture | 3.8860 | .64709 | .616** | 1 | ||
| Orientation | 3.8413 | .72261 | .596** | .678** | 1 | |
| Coaching | 3.9063 | .63397 | .601** | .636** | .695** | 1 |
** Significant at p < 0.05
3.6 Method of analysis
This study used Structure equation modelling with Partial Least Square (PLS-SEM) to test the proposed model. Recently, PLS-SEM becomes the prominent technique for data analysis in several disciplines including, Management (Alsaad, Yousif, & AlJedaiah, 2018a; Hair, Sarstedt, Hopkins, & Kuppelwieser, 2014b), Tourism (do Valle & Assaker, 2016), Marketing (Hair, Sarstedt, Ringle, & Mena, 2011b), MIS (Alsaad, Mohamad, & Ismail, 2017; 2018b; Ringle, 2012), and among others. PLS-SEM offers numerous benefits that make it well suited for this study. PLS focuses on an ability of a model to predict endogenous variables rather than just explaining the variability of the endogenous variables (Hair, Hult, Ringle, & Sarstedt, 2014a). Therefore, quantitative methodologists have strongly argued that PLS-SEM is well suited for testing complex predictive models where the theory is still being developed (Elrehail, Emeagwali, Alsaad, & Alzghoul, 2017; Hair, Ringle, & Sarstedt, 2011a). As the case of this study, the author proposed, for the first time, a complex framework that links Branding to Orientation and Coaching through Culture. Moreover, PLS-SEM depends on bootstrapping strategy to estimate the significance level of predictors and mediating variables, producing a more accurate estimate to examine the direct and mediating effects. Bootstrapping strategy is indeed the most recommend strategy to examine the mediating effect (Nitzl, Roldan, & Cepeda, 2016; Preacher & Hayes, 2008). Accordingly, the author is confident that PLS-SEM is suitable for this study.
3.7 Summary of the chapter
This chapter describes the research methods and procedures. Overall, this study adopted the deductive approach to conduct this research. The instrument of this study was a questionnaire which was validated and assessed prior the data collection. The population of this study was hotel employees in Northern Cyprus. The author used a convenience sampling technique to distribute the questionnaire. The characteristics of the respondents and their assessment of the research variable were discussed in detail. The next chapter discusses the data analysis in detail.
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