Research Methodology in Political Science PDF

Rescurch Methodology in Political Science |l [ t Social science and Governmental Research to understand social services, governmen operations, and recommendations (or not) regarding future developments and + programmes, including whether or not government should be involved. Activist + research whic...

Rescurch Methodology in Political Science |l [ t Social science and Governmental Research to understand social services, governmen operations, and recommendations (or not) regarding future developments and + programmes, including whether or not government should be involved. Activist + research which aims to raise the views of the underprivileged or “underdogs” to prominence to the elite or master classes, the latter who often control the public view or positions. Foundational research, examines the foundations for a science, analyzes the beliefs, + and develops ways to specify how a knowledge base should change in light of new information. + Historical research allows one to discuss past and present events in the context of the present condition, and allows one to reflect and provide possible answers to current issues and problems. Historical research helps us in answering questions such as: Where have we come from, where are we, who are we now and where are we going? « Visual ethnography. It uses visual methods of data collection, including photo, voice, photo elicitation, collaging, drawing, and mapping. These techniques have been used extensively as a participatory qualitative technique and to make the familiar strange. + Autoethnography, the study of self, is a method of qualitative research in which the researcher uses their personal experience to address an issue. Data Analysis Interpretive Techniques As a form of qualitative inquiry, students of interpretive inquiry (interpretivists) often disagree with the idea of theory-free observation or knowledge. Whilst this crucial philosophical realization is also held by researchers in other fields, interpretivists are often the most aggressive in taking this philosophical realization to its logical conclusions. For example, an interpretivist researcher might believe in the existence of an objective reality ‘out there’, but argue that the social and educational reality we act on the basis of never allows a single human subject to directly access the reality ‘out there’ in reality (this is a view shared by constructivist philosophies). To researchers outside the qualitative research field, the most common analysis of qualitative data is often perceived to be observer impression, That is, expert or bystander. rs examine e observers the data, interpret it via forming an impression ’and report 4 their impression in a structured and sometimes quantitative form. )if(«j Coding In general, coding refers to the act of associating meaningful ideas with the data of interest. In the context of qualitative research, interpretative aspects of the coding process are often explicitly recognized, articulated, and celebrated; producing specific words or short phrases believed to be useful abstractions over the data. As an act of sense making, most coding requires the qualitative analyst to read the data and demarcate segments within it, which may be done at multiple and different times throughout the data analysis process. Each segment is labeled with a ‘code’ — usually a word or short phrase suggesting how the associated data segments inform the research objectives. In contrast with more quantitative forms are usually under-developed in a ‘pure’ complete, the analyst may prepare reports via codes, discussing similarities and differences forms of coding, mathematical ideas and qualitative data analysis. When coding is a mix of: summarizing the prevalence of in related codes across distinct original sources/contexts, or comparing the relationship between one or more codes. Some qualitative data that is highly structured (e.g., open-ended responses from surveys or tightly defined interview questions) is typically coded with minimal additional segmentation of the data. Quantitative analysis based on codes from statistical theory is typically the capstone analytical step for this type of qualitative data. A common form of coding is open-ended coding, while other more structured techniques such as axial coding or integration have also been described and articulated. Because qualitative analyses are often more inductive than the hypothesis testing nature of most quantitative research, the existing ‘theoretical sensitivity’ (i.e., familiarity with established theories in the field) of the analyst becomes a more pressing concern in producing an acceptable analysis. Contemporary qualitative data analyses are often supported by computer programmes (termed computer-assisted qualitative data analysis software) used with or without the detailed hand coding and labeling of the past decades. These programmes do not supplant the interpretive nature of coding, but rather are aimed at enhancing analysts’ efficiency at applying, retrieving, and storing the codes generated from reading the data. Many programmes enhance efficiency in editing and revision of codes, which allow for more effective work sharing, peer review, recursive examination of data, and analysis of large datasets. Common qualitative data analysis software includes: + + MAXQDA (mixed methods) QDA MINER + ATLASt + Dedoose (mixed methods) « NVivo A frequent criticism of quantitative coding approaches is against the transformation data structures, underpinned by ‘objective of qualitative data into predefined (nomothetic) data is properties’; the variety, richness, and individual characteristics of the qualitative argued to be largely omitted from such data coding processes, rendering the original collection of qualitative data somewhat pointless. To defend against the criticism of too much subjective variability in the categories and relationships identified from data, qualitative analysts respond by thoroughly articulating data, thereby their definitions of codes and linking those codes soundly to the underlying whilst preserving some of the richness that might be absent from a mere list of codes, researchers. satisfying the need for repeatable procedure held by experimentally oriented Recursive Abstraction As defined by Leshan 2012, this is a method of qualitative data analysis where qualitative datasets are analyzed without coding. A common method here is recursive abstraction, where datasets are summarized; those summaries are therefore furthered into summary and so on. The end result is a more compact summary that would have been difficult to accurately discern without the preceding steps of distillation. A frequent criticism of recursive abstraction is that the final conclusions are several times removed from the underlying data. While it is true that poor initial summaries will certainly yield an inaccurate final report, qualitative analysts can respond to this criticism. They do so, like those using coding method, by documenting the reasoning behind each summary step, citing examples from the data where statements were included and where statements were excluded from the intermediate summary. Coding and “Thinking” Some data analysis techniques rely on using computers to scan and reduce large sets of qualitative data. At their most basic level, numerical coding relies on counting words, phrases, or coincidences of tokens within the data; other similar techniques are the analyses of phrases and exchanges in conversational analyses. Often referred to as content analysis: a basic structural building block to conceptual analysis, the technique utilizes mixed methodology to unpack both small and large corpuses. Content analysis is frequently used in sociology to explore relationships, such as the change in perceptions of race over time (Morning 2008), or the lifestyles of temporal contractors. Content analysis techniques ths help to provide broader output for a larger, more accurate conceptual analysis. ‘| I Approaches and Methods in Qualitative Research | || Mechanical techniques are particularly well-suited for a few scenarios. One such scenario is for datasets that are simply too large for a human to effectively analyze, or where analysis of them would be cost prohibitive relative to the value of information they contain. Another scenario is when the chief value of a dataset is the extent to which it contains “red flags” (e.g, searching for reports of certain adverse events within a lengthy journal dataset from patients in a clinical trial) or “green flags” (e.g., searching for mentions of your brand in positive reviews of marketplace products). Many researchers would consider these procedures on their data sets to be misuse of their data collection and purposes. A frequent criticism of mechanical techniques is the absence of a human interpreter; computer analysis is relatively new having arrived in the late 1980s to the university sectors. And while masters of these methods are able to write sophisticated software to mimic some human decisions, the bulk of the “analysis” is still nonhuman. Analysts respond by proving the value of their methods relative to either a) hiring and training a human team to analyze the data or b) by letting the data go untouched, leaving any actionable nuggets undiscovered; almost all coding schemes indicate probably studies for further research. Data sets and their analyses must also be written up, reviewed by other researchers, circulated for comments, and finalized for public review. Numerical coding must be available in the published articles, if the methodology and findings are to be compared across research studies in traditional literature review and recommendation formats. Distinct Qualitative Paradigms Contemporary qualitative research has been conducted using a large number of paradigms that influence conceptual and metatheoretical concerns of legitimacy, control, data analysis, ontology, and epistemology, among others. Qualitative research conducted in the twenty-first century has been characterized by a distinct turn toward more interpretive, postmodern, and critical practices. Guba and Lincoln (2005) identify five main paradigms of contemporary qualitative research: positivism, postpositivism, critical theories, constructivism, and participatory/cooperative paradigms. Each of the paradigms listed by Guba and Lincoln are characterized by axiomatic differences in axiology, intended action/impact of research, control of research process/outcomes, relationship to foundations of truth and knowledge, validity and trust, textual representation and voice of the researcher and research participants, and commensurability with other paradigms. In particular, commensurability involves the extent to which concerns from 2 paradigms eg, “can be retrofitted to each other in ways that make the simultaneous practice of both possible”. Positivist and post positivist paradigms share commensurable assumptit?ns, but are largely incommensurable with critical, constructivist, and participatory paradigms of @/ research and knowledge. Likewise, critical, constructivist, and participatory paradigms are commensurable on certain issues (e, the intended action and textual representation of research). Qualitative research in the 2000s has also been characterized by concern with everyday categorization and ordinary storytelling. This “narrative turn” is producing an enormous literature as researchers present sensitizing concepts and perspectives that bear especially on narrative practice, which centers on the circumstances and communicative actions of storytelling. Catherine Riessman (1993) and Gubrium and Holstein (2009) provide analytic strategies, and Holstein and Gubrium (2012) present the variety of approaches in recent comprehensive texts. More recent developments in narrative practice has increasingly taken up the issue of institutional conditioning of such practices. QUALITATIVE RESEARCH Qualitative research forms a major role in supporting marketing decision making, primarily as an exploratory design but also as a descriptive design. Researchers may undertake qualitative research to help define a research problem, to support quantitative, descriptive or causal research designs or as a design in its own right. Qualitative research is often used to generate hypotheses and identify variables that should be included in quantitative approaches. It may be used after or in conjunction with approaches where illumination of statistical findings is needed. In some research designs are adopted in isolation, after secondary data sources have evaluated or even in an iterative process with secondary data sources. In discuss the differences between qualitative and quantitative research and quantitative cases qualitative been thoroughly this chapter, we the role of each in marketing research. We present reasons for adopting a qualitative approach to marketing research. These reasons are developed by examining the basic philosophical stances that underpin qualitative research. The concept of ethnographic techniques is presented, with illustrations of how such techniques support marketing decision-makers. The concept of grounded theory is presented, illustrating its roots, the steps involved and the dilemmas for researchers in attempting to be objective and sensitive to the expressions of participants. Action research is an approach to conducting research that has been adopted in a wide variety of social and management research settings. Action research is developing in marketing research and offers great potential for consumers, decision-makers and researchers alike. The roots of action research are presented, together with the iterative stages involved and the concept of action research teams. The considerations involved in conducting qualitative research when researching international markets are discussed, especially in contrasting approaches between the USA and Europe. Several ethical issues that arise in qualitative research are identified. Before the chapter moves on to the substantive issues, one key point to note in the application of qualitative research is the name applied to the individuals who take part in interviews and observations. Note the emphasis in the following example. « Example: (a) Research is War’: Dutch agency MARE is calling for respondents to be promoted to the status of participants in research. The method that it has been developing puts the respondent in the position of participant rather than a passive reactive pawn in research. We take two participants, show them an image or commercial, and then invite one participant to ask the other what he or she just saw. This results in a conversation that is not directed by researchers, which is an important aspect. Our intervention is mostly focused on finding a good match between two participants who can communicate with one another. The method reveals how a consumer absorbs information and reports about it to fellow consumers, and it shows the client which elements of a commercial message work and which elements do not. Clients were reluctant to use this approach when it was first used in 1995. MARE senses there is a market for it now, so with an amount of refining, adjusting and testing, it ran from September 2005. A multinational in the Netherlands which has young marketers will apply it in research among young consumers. This example illustrates the creative thinking necessary to get the most from qualitative research and the respect that should be given to individuals who may be asked to engage in a process that sometimes goes way beyond simple questioning. Embracing this attitude, the term ‘participant’ rather than ‘respondent’ or ‘informant’ the core qualitative research. ‘We now move on to the nature of qualitative research with three examples. Given the nature of its products and competitive environment, the first example illustrates why L'Oreal feels that qualitative research is of importance to it. The second example illustrates how Philips uses qualitative techniques to support its trend forecasting and product design. Note in this example the use of an analytical framework to help researchers and decisionmakers gain insight from the data they collect. In the third example, Sports Marketing Surveys uses qualitative brainstorming techniques and focus groups as part of a research design to support the development of rugby league. These examples illustrate the rich insights into the underlying behaviour of consumers that can be obtained by using qualitative techniques. + Example: (a) A research commitment more than skin deep: L'Oreal is the largest supplier of toiletries and cosmetics in the world. The group tucks under its umbrella some of the best known brands and companies in the beauty business: cosmetics Rescarch Methodology in Political Science " ix‘ || houses Lancome, Vichy and Helena Rubenstein, and fragrance houses Guy Laroche, Cacharel and Ralph Lauren. Given the French penchant for qualitative research, and given the nature of the cosmetics industry, Anne Murray, Heaq of Research, was asked which type of research she favoured. We're pot particularly pro-quantitative or qualitative. Nevertheless, I do think qualitative in our area is very important. There are many sensitive issues to cover — environmental concerns, animal testing, intimate personal products, And increasingly, we have given to us very technical propositions from the labs, and what is a technical breakthrough to a man in a white coat is not necessarily 50 to a consumer. So the research department has to be that interface between the technical side and the consumer. (b) Trend forecasting at Philips: Marco Bevolo is in the future business. At Philips Design, the design department of the electronics multinational, he is responsible for identifying short-term trends in popular culture and aesthetics design. Marco believes his job has a lot in common with marketing research. Trend forecasting at Philips is carried out through a model developed by Marco and his team called Culture scan. The theoretical background of their approach comes from the Birmingham school of popular culture analysis as well as from the kind of cultural analysis performed by scholars who study phenomena such as ‘punks’ in Western cities as if they were a tribe in New Guinea. Rather than hinting at tangible design solutions - colour, ‘touch and feel’ or shape of TVs, MP3 players or other specific products, Culture scan is supposed to provide an insight into the broader, longer term undercurrents in popular culture and aesthetics design all over the world. These broad trends are then customised by Philips decision teams. Culture scan uses both an internal and external network of experts to collect information on These insights are then filtered by objective tools outcomes and make them actionable. The predictive is 18 to 36 months with the trends refined every two a wide variety of trends. in order to validate the horizon of Culture scan or three years. In qualitative research, research agencies and companies are continually looking to find better ways to understand consumers’ thought processes and motivations. This has led to a wealth of research approaches, including techniques borrowed from anthropology: ethnography, sociology and psychology. For example, Intel has a specialist team of researchers, including ethnographers, anthropologists and psychologists, whose principal form of research is in the home. ‘People don't tell you things because they don't think you'll be interested. By going into their homes you can see where and how they use theif computers,’ says Wendy March, Intel’s interaction designer of Intel Architecture. - l| | e T < and Methods in Qualitative Research Approaches = | Primary Data: Qualitative Versus Quantitative Research The primary data are originated by the researcher for the specific purpose of addressing the problem at hand. Primary data may be qualitative or quantitative in nature, as shown in Figure. Secondary data Primary qualitative Primary quatitative Exploration Description Experimont data data Dogmatic positions are often taken in favour of either qualitative research or quantitative research by marketing researchers and decision-makers alike. The positions are founded upon which approach is perceived to give the most accurate understanding of consumers. The extreme stances on this issue mirror each other. Many quantitative researchers are apt to dismiss qualitative studies completely as giving no valid findings — indeed as being little better than journalistic accounts. They assert that qualitative researchers ignore representative sampling, with their findings based on a single case or only a few cases. Equally adamant are some qualitative researchers who firmly reject statistical and other quantitative methods as yielding shallow or completely misleading information. They believe that to understand cultural values and consumer behaviour requires interviewing or intensive field observation. Qualitative techniques they see as being the only methods of data collection sensitive enough to capture the nuances of consumer attitudes, motives and behaviour. There are great differences between the quantitative and qualitative approaches to studying and understanding consumers. The arguments between qualitative and quantitative marketing researchers about their relative strengths and weaknesses are of real practical value. The nature of marketing decision making encompasses a vast array of problems and types of decision-maker. This means that seeking a singular and uniform approach to supporting decision-makers by focusing on one approach is futile. Defending qualitative approaches for a particular marketing research problem through the positive benefits it bestows and explaining the negative alternatives of a quantitative approach is healthy — and will and vice versa. Business and marketing decision-makers use both approaches can continue to need both. The distinction between qualitative and quantitative research be in the context of research designs. There is a close parallel in the distinctions between K atory ) is and conclusive e research’ and ‘qualitative and X quantitative research’. There ! parallel, but the terms are not identical. Thereo are circumstances where qualitatiye aho eyl re:earch can be used to present detailed descriptions that cannot be measured in a quantifiable manner: for example, in describing ch.arlacteristi.cs and styles of mus.ic that may be used in an advertising campaign or in desc.nbmg tlfe interplay of how families g through the process of choosing, planning and buying a holiday. C(lmverse]y. there may be circumstances where quantitative measurements are used cmllcluslvely to a?swer specific hypotheses or research questions using descriptive or experimental texfhmques. Beyond answering specific hypotheses or research questions, thef—e r{mly be sufficient data to allow data mining or an exploration of relationships between individual measurements to take place. The concept of data mining allows decision-makers to be supported through exploratory quantitative research. PROCESS OF QUALITATIVE RESEARCH Qualitative research is the approach usually associated with the social constructivist paradigm which emphasises the socially constructed nature of reality. It is about recording, analysing and attempting to uncover the deeper meaning and significance of human behaviour and experience, including contradictory beliefs, behaviours and emotions. Researchers are interested in gaining a rich and complex understanding of people’s experience and not in obtaining information which can be generalized to other larger groups. The Process The approach adopted by qualitative researchers tends to be inductive which means that they develop a theory or look for a pattern of meaning on the basis of the data that they have collected. This involves a move from the specific to the general and is sometimes called a bottom-up approach. However, most research projects also involve a certain degree of deductive reasoning. Qualitative researchers do not base their research on pre-determined hypothese s. Nevertheless, they clearly identify a problem or topic that they want to explore and may be guided by a theoretical lens - a kind of overarching theory which provides a framework for their investigation. p Thle approa.ch to dav!a collection and analysis is methodical but allows for greater ;xlbx xt}" than ll} quantl'tatlve research. Data is collected in textual form on the basis of observation and interaction with the participants e.g. through participant observation, indepth interv iews and focus grou, ps. It isi not cony, i i erted into numerical form and iis not statistically analysed. R \. Data collection may be carried out in several stages rather than once and for all. The researchers may even adapt the process mid-way, deciding to address additional issues or dropping questions which are not appropriate on the basis of what they learn during the process. In some cases, the researchers will interview or observe a set number of people. In other cases, the process of data collection and analysis may continue until the researchers find that no new issues are emerging. Principles Researchers will tend to use methods which give participants a certain degree of freedom and permit spontaneity rather than forcing them to select from a set of pre- determined responses (of which none might be appropriate or accurately describe the participant’s thoughts, feelings, attitudes or behaviour) and to try to create the right atmosphere to enable people to express themselves. This may mean adopting a less formal and less rigid approach than that used in quantitative research. It is believed that people are constantly trying to attribute meaning to their experience. Therefore, it would make no sense to limit the study to the researcher’s view or understanding of the situation and expect to learn something new about the experience of the participants. Consequently, the methods used exploratory (particularly when very researchers are free to go beyond the why, how, in what way etc. In this may be more open-ended, less narrow and more little is known about a particular subject). The initial response that the participant gives and to ask way, subsequent questions can be tailored to the responses just given. Qualitative research often involves a smaller number of participants. This may be because the methods used such as in-depth interviews are time and labour intensive but also because a large number of people are not needed for the purposes of statistical analysis or to make generalizations from the results. The smaller number of people typically involved in qualitative research studies and the greater degree of flexibility does not make the study in any way “less scientific” than a typical quantitative study involving more subjects and carried out in a much more rigid manner. The objectives of the two types of research and their underlying philosophical assumptions are simply different. THE NATURE OF QUALITATIVE RESEARCH Qualitative research encompasses a variety of methods that can be applied in a flexible manner, to enable participants to reflect upon and express their views or to observe their