Methodology
This paper outlines the methods that will be adopted by the researcher in answering the research questions. The main aspects of the methodology that will be explained in this paper include the research method, research design, data collection techniques, description of the target population, sampling methods, and data analysis techniques. The validity and reliability of research instruments are also explored in this paper.
Research Methods
According to Tourangeau and Plewes (2013), there are three main research methods used in academic research. They include the mono-method, mixed method, and multi-method techniques (Tourangeau & Plewes 2013). As insinuated by its name, the mono-method involves the use of only one research technique â either quantitative or qualitative. Comparatively, the mixed method involves the use of both qualitative and quantitative techniques, while the multi-method technique employs two qualitative research styles (Research Rundown 2018; Tourangeau & Plewes 2013).
The mixed approach is the selected framework for this review because the researcher intends to use both qualitative and quantitative research approaches. According to Research Rundown (2018), the use of the mixed methods technique is a relatively new area of methodological integration, which has only been widely accepted in the past decade.
Simonovich (2017) says the mixed methods approach allows researchers to use two approaches (qualitative and quantitative), to transform research problems into research questions or hypotheses, and to vary sample sizes based on the methods used. Other key inherent characteristics of the mixed methods approach include the ability to use any type of data collection method available to the researcher, and the continual interpretation of findings, which can influence different interpretations of the research process (Research Rundown 2018).
As highlighted in the introduction section of this paper, the aim of the proposed study is to find out the employment status and job satisfaction levels of hospitality management graduates in China. This topic contains both qualitative and qualitative aspects of the investigation, as alluded to in the works of Lin, Wong and Ho (2013). For example, it involves the evaluation of quantitative aspects of employee performance, such as unemployment levels, employee pay, and employment status and qualitative measures of worker fulfilment, such as job satisfaction, employee towards work and employee recognition (Lin, Wong & Ho 2013).
The mixed method framework emerges as a practical model of merging both qualitative and quantitative dimensions of analysis into one study. It is also appropriate for this study because it allows the researcher to gain insights into the research problem, which could have otherwise been missed if only one technique was used (Simonovich 2017). Another justification for using this technique is its comprehensive nature, which allows the researcher to use advanced statistical analysis techniques, including bars, graphs and even pictures to analyse data (Simonovich 2017).
According to Doyle, Brady and Byrne (2016), one of the main advantages of using the mixed methods research approach is its easiness in describing and reporting findings. At the same time, researchers who want to explain unexpected results arising from a prior study have commonly used it (Research Rundown 2018). Excerpts from the works of Dillman, Smyth and Christian (2014) also show its proficiency in helping researchers to generalise qualitative data (to a measured degree) and in designing and validating instruments.
Some of the drawbacks of this method include the use of a lot of time for compiling and analysing data, the possible development of unequal evidence based on the use of multiple designs, and the little guidance available to researchers who intend to use transformative methods integrated with the mixed methods approach (Research Rundown 2018).
Based on the potential pitfalls associated with this type of method, Creswell (2014) and Beardsmore (2013) propose the use of a systematic framework for undertaking mixed methods reviews to overcome their weaknesses. These suggestions will be embraced in the proposed study to improve the quality of its findings and to overcome some of the weaknesses of the mixed methods approach. Four guidelines will be followed by the researcher in achieving this objective: understanding the implementation sequence of data collection, understanding which method takes priority during data collection, knowing how the findings will be integrated, and establishing whether a theoretical perspective will be used, or not (Research Rundown 2018; Creswell 2014; Beardsmore 2013). Some of these questions will be answered by understanding which research design will be selected for use in the study. Relevant designs are outlined below.
Research Design
According to the Centre for Innovation in Research and Teaching (2018), there are six main research designs associated with the mixed methods research approach. They include sequential explanatory, sequential exploratory, sequential transformative, concurrent nested, concurrent transformative and concurrent triangulation methods. A summary of each research design is provided below.
Sequential Explanatory
The sequential explanatory design gives a lot of attention to the collection of quantitative data. In this regard, qualitative information is often collected to explain or interpret the quantitative data collected. Stated differently, qualitative findings are used to supplement the quantitative data (Centre for Innovation in Research and Teaching 2018; Research Rundown 2018).
Sequential Exploratory
Unlike the sequential explanatory research design, the sequential exploratory method is mainly focused on the collection of qualitative information, as opposed to quantitative data. Here, quantitative data is used to interpret or explain qualitative research findings. Based on its nature, the sequential exploratory method is often used when researchers want to explore a specific phenomenon or when developing or testing a new instrument (McKim 2017; Centre for Innovation in Research and Teaching 2018; Research Rundown 2018).
Sequential Transformative
The sequential transformative method does not stipulate which type of data should be collected first (either qualitative or quantitative data could be collected in the first phase of research). Instead, it postulates that the results of both methods of data collection should be integrated into the data analysis phase. Based on its non-confined nature, researchers mainly use this design when they want the freedom to choose data that fit a specific theoretical perspective (Centre for Innovation in Research and Teaching 2018; Research Rundown 2018).
Concurrent Nested
The concurrent nested technique often emphasises on the collection of one type of data (either qualitative or quantitative) and uses the other in an embedded manner. Researchers who use this technique often apply it in situations where they seek to gain information at different levels of analysis or when they want to address a different question apart from the dominant one (Centre for Innovation in Research and Teaching 2018; Research Rundown 2018).
Concurrent Transformative
The concurrent transformative method involves the use of a selected theoretical perspective in explaining a research phenomenon. The theoretical perspective is often embedded in the purpose of the research through associated questions that should guide the methodological approaches to be used. The concurrent transformative method is often used in situations where a researcher seeks to evaluate a theoretical perspective at different levels of analysis (Centre for Innovation in Research and Teaching 2018; Research Rundown 2018).
Concurrent Triangulation
The concurrent triangulation technique uses two or more methods of data collection to cross-validate information. In other words, the data collection process occurs concurrently. Typically, researchers who adopt this technique use the strengths of one method of data collection to overcome the strengths of another (Centre for Innovation in Research and Teaching 2018; Research Rundown 2018). This research design will be the overriding framework for this study because there is a need to cross-validate information obtained from the different levels of analysis (employment status and job satisfaction levels) as well as the multiple sources of research information.
In other words, the concurrent triangulation method will be instrumental in understanding how the two aspects of investigation (employment status and job satisfaction) will compare with each other to provide a straightforward and coherent explanation of the research issues. Hence, the ability of this research design to provide a framework for cross-validating the employment status and job satisfaction levels provides the overriding motivation for its adoption.
Data Collection
There will be two main sources of data in the proposed study: questionnaires and secondary research materials. They are explained below.
Questionnaires
As highlighted in this paper, the mixed methods research approach will provide the overriding framework for this study. It will also affect the data collection process because both qualitative and quantitative information will be obtained. Data will be collected from the respondents using structured questionnaires, which will be administered as a survey. Since it will be geographically impossible to meet all the research respondents physically, the questionnaires will be administered virtually. The research informants will have an opportunity to input their own data in the questionnaires and the completed surveys will be stored electronically.
The web-based survey will be employed in the proposed study because of its relative ease of data gathering. In other words, it will be simpler for the researcher to issue the data collection instruments virtually than to meet the informants face-to-face and provide them with the physical copies of the questionnaires. According to studies developed by Thissen, Park and Nguyen (2013), collecting data through online questionnaires is not only cost-effective but also fast.
However, the greatest motivator for using this type of data collection method is the opportunities it provides researchers in terms of data automation because, as will be seen in subsequent sections of this paper, the data analysis methods selected for the proposed study will also be hinged on automated methods. Therefore, through the collection of digitised data, it will be possible for the researcher to input and handle data much more effectively than an alternative situation where data has to be inputted manually.
Another motivator for using this type of data collection method is its low likelihood of errors that could affect data collection and handling processes (Thissen, Park & Nguyen 2013; Dodou & De Winter 2014). This advantage stems from the automation process, which is free from human errors that may be associated with data input processes. Relative to this discussion, studies show that this type of data collection process is associated with a high response rate because many informants find it convenient to answer research questions at the comfort of their homes and at a time that is convenient to them through online questionnaires (Thissen, Park & Nguyen 2013; Dodou & De Winter 2014).
Some of the drawbacks associated with web-based surveys and that could affect the quality of information obtained in the research is the absence of the interviewer in the data collection process. Therefore, it may be difficult for the respondent to get clarification about specific areas of the questionnaire that may be unclear. At the same time, studies show that online questionnaires are prone to survey fraud because some research informants simply answer questions to get an incentive for doing so and not necessarily to give their authentic views about a research issue (Thissen, Park & Nguyen 2013; Dodou & De Winter 2014).
The research informants in the proposed study will not be paid to participate in it. Therefore, it is expected that they will provide genuine views about the research statements. Although further details about the research participants will be highlighted in subsequent sections of this paper, it is expected that the views provided by them will specifically contribute to the advancement of the study.
The online questionnaire will be divided into two parts. The first one will collect demographic data from the respondents. Here, information relating to the respondentsâ gender, age, and work experience will be explored. The purpose of doing so is to understand their personal characteristics and evaluate whether there are any differences or variations in opinions based on the same. The second part will gather the respondentsâ views regarding 24 research statements that relate to four dimensions of analysis (see appendix 1). The first dimension of analysis will evaluate the respondentsââ attitudes towards work.
They will be required to answer eight questions relating to this dimension of study. The second dimension investigated will relate to employee pay. Six statements will be attributed to this aspect of analysis. âRecognitionâ will be the third dimension explored in the study and it will investigate the respondentsâ views regarding performance measures and the methods adopted by managers in recognising employee contributions in the workplace.
The fourth dimension of analysis will explore the informantsâ views regarding opportunities for growth in the industry. Here, emphasis will be made to understand their views regarding opportunities for career development and their effect on job satisfaction levels. Four statements will be asked to get the respondentsâ views regarding the above-mentioned factors. In sum, the four dimensions analysed in the second part of the questionnaire will have 24 statements. The table below summaries these dimensions and the number of statements attached to them.
Table 3.1. Dimensions analysed and number of statements.
The respondents will express their views regarding the aforementioned dimensions through a 5-point Likert scale, which will require them to âstrongly agree,â âagree,â be âneutral,â âdisagree,â or âstrongly disagreeâ with the 24 statements alluded to above. The formula used to calculate the score intervals for their responses (based on the 5-point Likert scale) would be deduced by subtracting the minimum score from the maximum score and dividing the outcome by the number of levels of responses. The process is defined by the formula outlined below.
Score interval = (Maximum score â Minimum score) / Number of levels
= 5 â 1 / 5 = 0.8
The “degree of agreement” will also be defined by a rating scale, which appears below.
Table 3.2. The degree of Agreement and Rating Scale
Target Population
According to Singer and Ye (2013), it is often pointless for researchers to undertake surveys if they cannot account for their research subjects. According to the recommendations of Boulianne (2013), the characteristics of the target population should be at the core of the development of the research questions and guide the general design of the questionnaire. As highlighted at the beginning of this report, the aim of this study is to understand the employment status and job satisfaction levels of hospitality management graduates in China. The sample population will be defined by this research question because the researcher intends to recruit 75 respondents who graduated with different degrees in hospitality management. The respondents will be recruited from three international hotels operating in Beijing, China.
Sampling Technique
The snowball sampling method will be used to recruit informants. This type of technique is based on probability sampling and relies on initial contacts to get in touch with other respondents (Thissen 2014; Schonlau & Couper 2016). Therefore, ideally, the number of respondents is expected to increase as more employees complete the survey (Behr et al. 2014; Fang, Wen & Prybutok 2014). The snowball sampling method will be adopted because the researcher has developed a good rapport with some employees of the three hotels where the respondents will hail from. However, permission will be sought from the hotel managers to undertake the study.
The snowball sampling method will also be employed because the researcher intends the overall sample to be representative of the target population (graduate management students). In other words, it will be appropriate to use the snowball sampling method to identify respondents who had a graduate degree from the larger sample of workers in the three hotels mentioned. Relative to these benefits, West and Kreuter (2015) say that this sampling method is ideal for researchers who want to minimise the cost of research and possibly save time. The same benefits will be transferred to the proposed study.
Nonetheless, one of the challenges associated with the use of this sampling design is a limited sample size, which will is typically confined to only a small and largely homogenous target population (Tourangeau et al. 2014). However, this limitation will not be a problem in this study because the researcher intends to sample a homogenous population of graduate management students. Therefore, the homogeneity of the sample is a strength and not a weakness.
Published Sources
Secondary research materials will also be used as the second method of data collection. The inclusion criterion will be defined by the use of materials that were published in the last five years (2013-2018). Books and journals will also be selected as the preferred sources of secondary data because they have a high credibility rating compared to other sources of information (McKim 2014). At the same time, industry reports, and government data will be sourced from credible websites. However, such information will complement the main sources of secondary research data, which are books and journals.
The published materials will also be sourced from credible databases, including Jstor, Emerald Insight, and Google Scholar (among others). The purpose of using secondary research information on the study is to compare the empirical findings with pre-existing information about job satisfaction levels and employee status among graduate students. Therefore, it will be possible to understand points of convergence or divergence when both sets of information are compared with one another.
Validity and Reliability of Instruments
The validity and reliability of dimensions analysed in the questionnaire were assessed using the Cronbach Alpha method. Table 3.3 below highlights the findings.
Table 3.3. Cronbach Alpha Findings for the Study Dimensions.
According to the table above, the values of the alpha coefficient are reported for all the four dimensions that will be explored in the study (attitudes towards work, pay, recognition, and opportunities for growth). According to Behr et al. (2013), Engellant, Holland and Piper (2016), Cronbach alpha values that are higher than 0.5 are often considered reliable. Such was the case for the findings highlighted above because the Cronbach alpha value for the four dimensions is 0.937. This means that the data collection instrument is reliable.
According to Birt et al. (2016), the trustworthiness of a research process largely depends on the quality of information conveyed in it. In line with this statement, the validity of the findings will be safeguarded by the member-check technique. It refers to a process where a researcher shares their findings with the respondents to establish whether the views presented in the final report convey what the informants meant to say (Newby 2013; West & Kreuter 2013). Therefore, its purpose will be to make sure that the information presented in the final report measures up to the views and sentiments of the research respondents. This means that the findings of the research will be shared with the research participants before publishing. Any variations between the final report findings and the respondentâs views will be reported and possibly explained.
Limitations of Study
According to Bowling (2014), study limitations refer to aspects of research that were beyond the researcherâs control. One limitation of the study is its indicative nature because a targeted sample size of 75 respondents is not enough to deduce strong inferences about employment status or job satisfaction levels of management graduates in China. Therefore, the findings of this study are only indicative of employment status and job satisfaction levels among management graduate students in China.
Ethical Considerations
The ethical considerations described in this paper largely refer to the conduct of the researcher. Israel (2015) says it is important to evaluate this issue in research studies that use human subjects. Relative to this view, the ethical issues relevant to this study are described below.
Informed Consent
According to the USC (2018) and Alderson (2017), informed consent refers to the voluntary consent of research participants to take part in a study. At the same time, McGonagle, Brown and Schoeni (2015) posit that informed consent is a process that strives to ensure the protection and respect for research subjects. All the informants who will take part in the proposed study will give their consent to do so. In other words, they will not be coerced or paid to participate in the study.
Privacy and Confidentiality
Researchers, such as Couper and Singer (2013) and Israel (2013), have broadly explored issues of privacy by contending that the sensitivity of information presented in a research study needs to be the guiding principle for ascertaining the correct level of confidentiality that should be accorded to the research participants. The identities of the hotels that the research participants will be sought from will remain confidential to safeguard their reputation.
To do so, information will be collected from the respondents anonymously and all possible identifiers will be excluded from the final research report. The suggestions of Szolnoki and Hoffmann (2013) to safeguard the privacy of research informants will also be adopted by sharing information on a âneed-to-knowâ basis. Therefore, all the views expressed in the research will be presented anonymously. In other words, the identity of the research participants will not be revealed.
Data Management
As highlighted in earlier sections of this paper, some of the information collected for purposes of the review will be obtained from online questionnaires. This data will be stored in the researcherâs computer and protected with a password. Therefore, only the researcher will gain access to this information. After completing the research process, the information collected will be destroyed.
Data Analysis Tools
The information collected in the proposed study will be analysed using the Statistical Package for the Social Science (SPSS) software (version 23) and Microsoft Excel (2010). The two methods (SPSS and Excel) are software-based tools that are often used in the analysis of quantitative data. These software packages are selected for use in the proposed study because of their high accuracy and multiple data analysis techniques, such as descriptive and inferential analytical tools. At the same time, the researcher anticipates that there will be a lot of information that will be obtained in the research, such that it would be difficult to analyse the same information manually.
The SPSS method is specifically selected for use in the proposed study because of its advanced data analysis and management techniques, such as descriptive methods, which will be instrumental in developing graphs, bars, and charts that will represent the respondentsâ views. At the same time, the same descriptive analysis techniques will be instrumental in providing different measures of data, such as standard of deviation, frequencies, the degree of agreement and percentages.
Correlations within dimensions will also be measured using different data analysis tools, such as Pearsonâs Correlation, Spearmanâs and linear regression techniques. Particularly, these tools will be integral in understanding correlations between different dimensions of analysis. The T-test and one-way ANOVA techniques will also be instrumental in understanding the effects of demographic variables on the dimensions analysed. The correlation between variables will also be studied by measuring the direction and degree of relations within an interval of +1 and -1. All positive values would imply a positive relationship, while all negative values will imply a negative relationship. We will use a scale proposed by West (2013) to assess the strength of the correlation. It appears in table 4.4 below.
Table 4.4. Measurement Scale.
Research Timeline
The timeline for completing the study is as explained in table 4.5 below
Summary
This paper has highlighted research processes that will be adopted in the proposed study. The mixed methods approach has been selected as the overriding research framework for this study because it contains aspects of qualitative and quantitative research. Its multi-layered nature justifies its use in the research. The concurrent triangulation research design was also selected for this review because it provides a framework for corroborating qualitative and quantitative findings.
The use of this research design also means that the collection of both qualitative and quantitative findings will occur concurrently. The researcher intends to undertake 75 surveys virtually among a group of respondents who will be selected from three international hotels operating in Beijing, China. Stemming from resource and geographical constraints, the surveys will be administered virtually and the findings analysed using the SPSS (version 23) and Microsoft Excel methods. As mentioned in this paper, the views of the respondents will be measured using a 5-point Likert scale and the Cronbach alpha findings to measure the dimensions that will be explored shows a finding of 0.937, which means that the dimensions explored are reliable.
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