CHAPTER 3: METHODOLOGY
3.1 Introduction
If a company like Yuanjin is going to meet the demand of its customers and reduce the amount of time it takes to manufacture products, it has to have strong ties with the top suppliers. It is possible that the textile and clothing industry will soon be in a position to provide competitive skills, high-quality items, and rapid lead times, all of which will contribute to the growth of the structure of the Chinese market. The major purpose of the research is to highlight how China’s textile industry has changed and expanded from the onset of the COVID-19 pandemic. This will mostly be done with a focus on Yuanjin. The following are the main research questions for this investigation:
How can Yuanjin exploit the present post-covid season to change and upgrade?
Which fashion trends right now are applicable to Yuanjin’s textile and apparel industries?
How can Yuanjin take advantage of changes and advancements in the market to obtain a competitive advantage?
3.2 Research Design
The pragmatic approach, together with the philosophy that underpins it, suggests that the qualitative technique is the one that should be used for this research if it is to achieve its aims and objectives. Due to the qualitative nature of the study, qualitative research can demonstrate how attitudes evolve through time. It is possible to demonstrate how people’s perspectives evolve over time via the use of qualitative research methods (Basias & Pollalis, 2018). Techniques of qualitative research are superior than methods of quantitative research due to the fact that qualitative research methods do not have the same constraints. When collecting non-numerical data, there is a possibility that explanations will be supplied that explain more about the data, as discovered by Hawkins (2018). These explanations further describe more about the data. The paper will have a great deal of leeway after obtaining qualitative data and determined what it indicates. It is also true that methods and processes that do not perform well may be altered to operate better in certain circumstances. This is something that can be done. Academics have the ability to use qualitative research methodologies in order to conduct speculative study on subjects that they believe will be fascinating. When each of these factors is considered, it’s possible that qualitative data collecting is more concentrated on the people who are participating in the research than was previously believed.
The author makes a suggestion for a thorough inductive method for the analysis of data, making use of qualitative evaluation data in this investigation. The inductive method will be used in order to condense a great deal of information and make it more concise (Tomaszewski, Zarestky, & Gonzalez, 2020). In addition, the inductive qualitative approach creates clear links between the objectives of the evaluation or investigation and the first data summary. The approach will give a framework for interpreting the underlying process of any interactions or activities that are exposed by the raw data, which is an additional advantage of using the method. This instrument comes in quite helpful. An approach for doing an analysis of qualitative data is known as the wide inductive methodology. It is made up of a range of fundamental methodologies that, when combined, provide findings that are precise and dependable (Tomaszewski, Zarestky, & Gonzalez, 2020). Although it is not as widely popular as other methods for building theories or models, the general inductive technique may be used to address certain assessment problems.
3.3 Data Collection
Along with conducting an online interview with open-ended questions, we will also conduct a case study on the Yianjin Garment Factory as part of the inquiry. In open-ended surveys, the respondents are not coerced into selecting answers from a predetermined selection of possibilities. In its place, individuals are given the option to respond with as much or as little detail as they see fit. A web survey is a kind of online survey that is often prepared by software before being uploaded to research websites, emailed to responders, or both. It eliminates the time-consuming process of creating comments and allows users to simply share their thoughts through mobile devices, which is a significant time saver. This does double duty by both simplifying the procedure and improving the accuracy of the operation (Benitez-Correa, Gonzalez-Torres, & Vargas-Saritama, 2019). When qualitative data is obtained using an online survey employing a questionnaire, the procedure may be completed more quickly and effectively, making it more desirable. In online surveys, respondents are not obligated to provide responses to questions posed in the presence of the interviewer. This indicates that surveys carried out online have the potential to reach a big number of individuals. Participants are able to complete an online survey or questionnaire at their own leisure and on a variety of devices, which is one of the advantages of doing the activity in an online setting. This is one of its many wonderful traits.
In order to evaluate qualitative data from a variety of sources and come to certain conclusions, the approach of case study will be used. A qualitative case study is a kind of research that allows you to examine a phenomena in a specific setting by integrating a number of data sources and presenting the phenomenon from a variety of viewpoints. This type of research can be found in the field of social science. Using this process, you can investigate anything you want to. A case study examines a real-world occurrence and evaluates it within the parameters of its own unique setting. This method was developed on the premise that context plays a crucial role.
It is necessary to provide an open-ended response whenever a question is posed that cannot be answered with a straightforward “yes” or “no,” “true” or “false,” “multiple-choice,” or “rated on a number or star-rating scale.” Users of products are obligated to offer feedback that is both objective and in their native language and vernacular (Abutabenjeh & Jaradat, 2018). It is different from providing them with a list of alternative responses and is what is generally referred to as feedback from the voice of the customer. One of the advantages of using open-ended questions is that they make it possible for individuals to communicate their ideas. As a direct result of this, the information that is provided is far more specific, comprehensive, and often subjective. The researcher has the opportunity to collect more data and views that are more germane to the topic at hand when they use open-ended survey questions.
By asking the participants in the survey open-ended questions, researchers may be able to understand more about what they genuinely believe and how they feel about the subject of the survey. Therefore, there is no doubt that the approach of open-ended inquiry is beneficial for achieving the purpose of the research, which is to collect the respondents’ honest perspectives (Brydges, Retamal, & Hanlon, 2020). Businesses may learn a lot about how consumers feel about their goods and services by conducting surveys with those customers. Using properly calibrated questionnaires, researchers have the ability to determine the levels of customer satisfaction experienced by consumers as well as the reasons why particular prospective customers discontinue using a company’s goods or services. In research studies, the use of open-ended questions encourages participants to discuss freely about their thoughts, beliefs, suggestions, and critiques, which often leads to the discovery of new insights for researchers (Chakraborty & Biswas, 2020). The advantages far outweigh the negatives, which include the fact that open-ended responses are difficult to analyze and do not easily fit into statistical analysis models. Other drawbacks include the fact that open-ended responses may not be used at all.
Participant responses in their own words encourage a better knowledge of them, as there is no predetermined number of viable responses to open-ended inquiries. As a result, there are no constraints on the quantity of data that may be acquired. Since there is no predetermined number of responses to open-ended inquiries, customers’ responses in their own words encourage a better knowledge of them. Because of the variety of perspectives from which people will respond to the questions, you will have the opportunity to learn more about a variety of individuals. Research participants are more likely to supply entirely original data and recommendations when open-ended questions are used, which is one of the benefits of employing these types of queries (Haven & Van Grootel, 2019). Because there is no limit on the number of responses that may be given, it is quite feasible for you to acquire new knowledge and get insights into problems from perspectives that you had never previously considered thanks to the contributions of actual people. When responding to open-ended inquiries, individuals are at liberty to provide as much or as little information as they see fit in their replies. Because they are expressed precisely how the responder expresses themselves and allow for more natural expression, open-ended responses are more challenging (Hawkins, 2018). Replies to open-ended questions often provide more accurate results than responses to multiple-choice questions or questions based on ratings. When researchers ask respondents open-ended questions about their own points of view, they are better able to comprehend the connections between the ideas, emotions, and experiences being discussed.
3.4 Data Sampling
When doing qualitative research, a limited representation (also known as a sample) of the whole population is used for each individual study. A subset is another name for this particular category. Who will take part in the study and how many people will take part in the study will be somewhat determined by the aims of the research, which may need the involvement of extra persons, and partially determined by the characteristics of the study group (like size and diversity). The participants in this investigation will be chosen by a process known as purposeful sampling. Purposeful sampling is often used and is one of the most common sample procedures. A total of 20 individuals were chosen to participate in the study. Of the 20 participants, 8 are current employees at Yuanjin Textile Factory. The remaining 12 are representatives of the textile industry from various Chinese garment and clothing factories. Specifically, the research targets employees within the managerial capacity, individuals with some level of decision-making power, and company executives. It does this by classifying respondents into different subgroups according to criteria that have been shown to be relevant to the research subject (Mfinanga, Mrosso, & Bishibura, 2019). It is possible to make this choice before any data has been collected. It is important to take into consideration not only the goals of the report but also the amount of time and resources at your disposal, as well as the size of the sample. The point of saturation is a common strategy that is used in the process of calculating the size of an anticipated sample size. We have reached the point of saturation in the process of acquiring data when new information is no longer assisting us in gaining further knowledge about the matter that is being studied. If the data that is being acquired is evaluated and analyzed as it is being obtained, then deliberate sampling may be able to assist in achieving the most accurate results.
The paper chose to adopt a purposeful sampling since it has a number of benefits. In the first place, it is a way of picking samples that has a low overall cost. In this scenario, the researcher has to take into account the previous experiences of the volunteers in order to choose the most suitable participants for the systematic study (Haven & Van Grootel, 2019). Additionally, it shortens the total amount of time required. One further benefit is that researchers are able to extract the most out of the people they are investigating, which ultimately leads to more insightful conclusions from the research. In addition, purposeful sampling makes it easier to acquire qualitative data, which ultimately leads to improved, more high-quality findings as well as a deeper understanding of the topic being researched. When doing research on a certain subject, it is helpful to zero down on particular groups in order to obtain knowledge about that subject (Mik-Meyer, 2020). The researcher gathers information from people who are the best possible matches for the inquiry, which explains why the results make sense in the context of the study. Last but not least, the use of purposeful sampling helps to restrict the margin of error in the data that was gathered. This is because the information sources are an appropriate fit for the context of the study.
Purposeful sampling is a non-probability sampling method in which the variables for the sample group are chosen based on the researcher’s best judgment. This is sometimes called subjective sampling (Ishtiaq, 2019). For this problem, the sampling method depends a lot on the researcher’s judgment and what they already know. Researchers can get a lot of information from the collected data by using a method called “deliberate sampling.” This helps researchers explain to the wider public how important their results are. Everyone agrees that purposeful sampling is better than other types of sampling in terms of saving money and time. Consequently, it is one of the most common ways that researchers go about their work. Purposive sampling is a flexible research method that can be changed to make a survey more effective, since there are different ways to carry out the above steps (Melnikovas, 2018). When there aren’t many first-hand sources of data that can be used in a survey, purposeful sampling is often the only way to get good results because it gives researchers more control over the results. When purposive sampling is the main focus of a study, researchers can choose from a number of different ways to do qualitative research. It is sometimes necessary to use a different sampling strategy and method to get the data needed to draw a conclusion and meet the goals of these designs. By using the many practical approaches available through the purposive approach, research designs can be made more flexible (Mfinanga, Mrosso, & Bishibura, 2019). This makes it possible to use different methods to get the results you want. Researchers using purposive sampling may have to go through a number of steps, each of which may build on the one before it. This method works well because it gives researchers a wider range of options for non-probability sampling. Even though this often means making a new plan at the start of each phase, this method is important because of its benefits. The most common example of this benefit is the fact that, while a critical sample can be useful for figuring out how important an investigation is, the expert sampling technique makes it possible to look at all the data that has already been collected.
3.5 Data Analysis
The objective of using an inductive technique is to condense the raw textual information into a format that is concise and easy to understand. The method also seeks to create obvious linkages between the goals of the evaluation or study and the summaries that are derived from the raw data. Data from the case study as well as the responses from the 20 respondents will be used to identify key themes and issues within the Chinese textile industry. The overall intention is to understand how major stakeholders perceive the current efforts at Yuanjin and elsewhere within the industry, as far as the direction of the sector is concerned. This is one of the goals of the method. As an integral component of the strategy, the formation of these relationships is intended to take place (Mik-Meyer, 2020). This discussion will come to a close with an application of inductive data analysis, which will be used to develop a framework of the fundamental structure underlying observable experiences or processes in raw data. The general inductive approach is a set of straightforward and organized methods for evaluating qualitative data. These methods have the ability to provide outcomes that are reliable and accurate. When used to a specific set of assessment challenges, the general inductive methodology offers a method that is uncomplicated and uncomplicated in the way it goes about creating results (Saunders, Lewis, & Thornhill, 2007). When compared to the various methods of qualitative data analysis, it is probable that a greater percentage of evaluators would view a wide inductive methodology to be the simpler of the two.
For the purpose of generating ideas and identifying underlying themes, inductive content analysis makes use of a variety of textual materials and resources, such as research papers, old recordings, and other sorts of textual information. The inductive analysis might be considered a descriptive approach given that it is based on the facts and that it explains them. The concept of inductive content analysis is predicated on the notion that recurring topics may be discovered in massive volumes of data via the process of constantly contrasting and comparing various aspects of that material (Benitez-Correa, Gonzalez-Torres, & Vargas-Saritama, 2019). The inductive qualitative technique is the most effective strategy for doing research when there are either a limited number of prior studies on the topic at hand or no studies at all. In order for researchers to find out what the most significant problems are in their area of expertise, they could use the inductive technique, which entails narrowing the data down to a predetermined grouping of concepts or themes.
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Appendix 1: Qualitative Survey
