Design of Instruments and Target - Research Proposal Example

Chapter 4: Methodology: Research Approach The collection and analysis of quantitative data in this dissertation takes a deductive approach. In taking a deductive approach to the quantitative data collection and analysis, this research starts with the ‘general’ and moves toward the ‘specific’ (Willis, 2007, p. 213). By moving from the general to the specific, deductive reasoning facilitates a strategy in which conclusions are logically drawn on the basis of the facts found. This is a top-down approach, or rather the deductive approach starts at the top and moves toward the bottom. In this regard, the researcher starts out with a conclusion which is generally expressed in the form of hypotheses or theories (Figure 1) (Evans, 2000). The researcher collects quantitative data and analyses the data with a view to confirming or disproving hypotheses or theories (Figure 2). In adopting a deductive approach, this dissertation starts at the top with hypotheses and theories and collects primary and secondary data with a view to testing the stated hypotheses and theories. Specifically, the quantitative data is collected, calculated and analysed with a view to testing three subcategories of motivation theories as set out in Chapter 1 of this dissertation: self-determined theory, hierarchy theory and hygiene theory. Thus the quantitative data tests the extent to which individuals act in terms of energy efficiency without the benefit of external/government influence through regulation and how individuals act or are influenced to act based on government/external interference. 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conducted using inductive reasoning. Inductive reasoning, unlike deductive reasoning takes a bottom-down approach or rather begins at the bottom and then sets about exploring and explaining the phenomenon investigated. This generally involves observing and examining patterns for meaning (Figure 3) (Roulston, 2010). Thus, rather than starting out with generalizations, inductive reasoning starts out with specifics and moves toward generalizations and theorizing. Unlike deductive reasoning, inductive reasoning does not seek to confirm or disprove hypotheses or theories, but attempts instead to form theories or contribute toward the formation of theories. Thus in collecting, calculating and analyzing the qualitative data, this researcher begins with a conceptual framework constructed around three theories under the umbrella of motivation theory: self-determined, hierarchy and hygiene theories. Together, self-determined, hierarchy and hygiene theories provide a conceptual framework for investigating how individuals behave relative to energy conservation absent external influences and how and to what extent external influences can alter how individuals behave in terms of energy renewal. Figure 3: Inductive Reasoning Research Philosophies Two philosophies are used in this research: interpretivism and positivism. Interpretivism is used in the analysis and interpretation of the qualitative data results. Positivism is used in analysis and interpretation of the quantitative data results. Interpretivism is based on the assumption that the social world is different from the natural world and as such, it is not possible to uniformly and objectively calculate social phenomena. Social phenomena can only be measured by reference to how individuals perceive and interpret their own experiences and interactions and how they respond to their interpretations of their experiences and interactions. Therefore, a social phenomenon operates outside of the natural sciences’ paradigm and is focused on the causal ‘meanings’ and ‘understandings’ of ‘social actors’ (Crotty, 2005, p. 69). Interpretivism assumes that objective reality is not always discoverable and that subjective realities can be used to accumulate subjective evidence of what amounts to a close approximation of reality. This is because; social actors are subjective in their thinking, interpretations and reactions so that multiple realities exist. In this regard, interpretivism proceeds on the basis that meaning and understanding from multiple individuals can aid in arriving at a close approximation of reality and truth (Willis, 2007). Phenomenology is a category of interpretivism and forms the primary basis of the qualitative data collected and analysed in this research. A phenomenological approach involves focusing on the experiences of those participating in the study and how those experiences are interpreted and understood. In this regard, a phenomenological approach involves gathering data from those who experience or have experienced the social phenomenon under investigation (Crotty, 2005). Therefore, in taking a phenomenological approach to the renewable energy, use policies and practices in Qatar, this research uses semi-structured interviews to identify and interpret expert residents’ experience with energy policies and practices and their interpretation of their experiences and how they expect a successful and effective energy renewable market to operate. The objective is to determine, from the perspective of domestic experts, if Qatar’s renewable energy policies are sufficient to modify domestic patterns that are consistent with environmentally friendly outcomes. Positivism on the other hand looks for objective realities and proceeds on the basis that a phenomenon can be observed and measured. Thus from a positivist perspective, reality is objective and can be determined through natural laws and methods. Positivism assumes that anything that can be observed can also be measured and reduced to defined and quantitative results. A positivist approach to research therefore involves the formulation of hypotheses and testing of these hypotheses through the collection and analysis of empirical data. Theories may also be tested through empirical data, which is always reduced to statistical data forms (Blaikie, 2007). Put another way, positivism assumes that reality is objective and has an existence, which is segregated from the human mind. The objective reality is capable of measurement and reveals a discoverable objective reality (Byrne and Ragin, 2009). In taking the positivism approach to this study, surveys are administered to residents who are asked to rate their interpretation of and response to renewable energy policies in Qatar. These interpretations and responses are measured and reduced to statistical data for the purpose of calculating and defining an objective reality. Research Methods This research study can best be described as an exploratory and descriptive study which seeks to identify attributes for and obstacles to, sustaining and implementing successful and efficient renewable energy policies. A pragmatic research method is also taken and involves a mixed methodology. In this regard both qualitative and quantitative methods are used in the collection and analysis of data (Johnson, et al., 2007). The collection and analysis of qualitative and quantitative data carries on ‘in many phases in the research process’ and through taking this approach, the researcher gains and shares a more dynamic understanding of the ‘research problems than either approach alone’ can produce (Creswell and Clark, 2011, p. 5). In using a mixed methods research approach, the researcher is cautioned to ensure that neither the qualitative nor quantitative data outcomes are permitted to be isolated. By interpreting the quantitative and qualitative results together, the researcher is assured of greater validity of the results (Tashakkori and Teddlie, 2010). According to Creswell and Clark (2011), the researcher is minded to merge and converge the qualitative and quantitative data. The idea is to ensure that the quantitative and qualitative data are supportive and complimentary of one another. Creswell and Clark (2011) further emphasis that it is inadequate for a researcher to ‘simply collect and analyse quantitative and qualitative data’, but rather the researcher is required to mix the data so as to ‘form a more complete’ image of the ‘problem’ (Creswell and Clark, 2011, p. 7). For the purposes of this research, a triangulation method was used in the mixed methods research. A triangulation mixed methods research requires that in addition to collecting qualitative and quantitative data, the researcher merges the two data sources and rely on the results for forming a better understanding of the ‘research problem’ (Tashakkori and Teddlie, 1998, p. 28). In taking the triangulation mixed method, the researcher compares the two data results and observes and thinks about consistency in the results (Camerino, et al., 2012). According to Camerino, et al., (2012), the triangulation mixed methods approach is the most commonly used mixed methods and its purpose is to “obtain different, yet complementary, data” relating to the same phenomenon in order to provide optimal insight into the problem under research investigation (p. 8). In particular, a triangulation mixed methods approach aims at complimenting effects. The strengths and weaknesses of the quantitative data are complimented by the strengths and weaknesses of the qualitative data. For example, quantitative data usually involves large sample sizes while qualitative data involves smaller sample sizes. Therefore the weaknesses in the small sample size under qualitative data are complimented by the larger sample size in the quantitative data. However, since qualitative data involves small sample sizes, the data obtained is far more robust and detailed than the data obtained from larger sample sizes under quantitative data. Therefore, the quantity of quantitative data and the quality of qualitative data combine to improve research results (Camerino, et al., 2012). The triangulation mixed method used in this research involves the collection of primary and secondary data. The data results are compared and merged pursuant to consistencies and inconsistencies in the results. The results of each of the data sources are compared and contrasted for confirmation, complimentary and support implications. In other words the results of surveys, interviews, literature and other sources of secondary data are combined and converged for comparative and contrast values. Data Collection: Design of Research Instruments and Research Target Primary Data Collection A purposive and convenience sampling method is used in this research for the recruitment and participation of a population of experts in renewable energy in Qatar. A convenience sampling is used for the recruitment of and participation of a population of energy users in Qatar. The convenience sampling participates in the surveys while the purposive sampling participates in the semi-structured interviews. The surveys are presented in two languages: English and Arabic. Purposive sampling is best understood as a non-random sample which is aimed at the collection of data from a population that is expected to have the requisite knowledge and experience for providing the information that the research study is aimed at obtaining (Tashakkori and Teddlie, 2010). In order to obtain a purposive sample population the researcher identified and recruited experts who have experience with managing efficient energy and promoting or advising on renewable energy and who have been exposed to renewable energy policies and practices in Qatar. The purposive population sample were asked to participate in and did participate in a semi-structured interview designed to identify their knowledge of and experience with renewable energy strategies and their experiences and perceptions of the reality of Qatar’s renewable energy policies and practices. This is a phenomenological approach which is compatible with purposive sampling since the aim of the interview is to gather data from individuals who have experienced or are experiencing the phenomenon under investigation (Creswell, 2012). Semi-structured interviews were used to provide the researcher with the flexibility to ask questions for clarification or for following up with additional questions in the event that new information was offered or it became clear that the interview subject wanted to offer information that was not included in the question. Semi-structured interviews involve a pre-prepared list of questions that permit the researcher to go off-script in appropriate circumstances (Wengraf, 2001). Thus the researcher prepared a list of questions that were merely preparatory in nature and with the understanding that the researcher would go off-script when necessary (Appendix 1). The convenience sampling technique is used to recruit individual citizens/residents of Qatar. Also known as ‘accidental’ or ‘haphazard’ sampling, convenience sampling is among the most popular sampling technique used in the behavioural sciences (Gravetter and Forzano, 2015, p. 151). In the interest of time, money and resources, convenience sampling involves the recruitment of individuals who are easy to reach. As Gravetter and Forzano (2015) explain that convenience sampling is best understood as a sampling technique in which individual participants ‘are selected on the basis of their availability and willingness to respond’ (p. 151). In other words, residents of Qatar was approached and recruited electronically from social media networks and other online locations where relatively large populations gather. The convenience sampling is used to complete a survey designed to measure variables associated with attitudes toward renewable energy policies and practices and the participant’s own energy efficiency practices and knowledge. The survey is multi-dimensional in that one part of the survey is designed as a blind item in which statements containing the variables are rated pursuant to a Likert scale. They survey will also contain matrix and open-ended questions (See Appendix 2). Each statement in the survey is accompanied by the Likert scale and participants are asked to select the appropriate rating for each statement. The open-ended questions permit the participant to freely express themselves (Creswell, 2012). In order to properly recruit participants for the semi-structured interviews all potential participants were provided a consent form (Appendix 3). The consent form informed the potential participants of the purpose of the research and the research topic. They were asked to sign the form if they agreed to participate in the study. The interviews and consent forms are presented almost simultaneously in that once a consent form was signed, the interviews commenced. The semi-structured interviews are arranged in person with the potential participant. The interviews are conducted online and by phone at a time that is convenient for both the researcher and the participant. Semi-structured interviews were slated for 30 minutes to 1 hour. Altogether the target for the interviews was 500 as this number is substantial enough to satisfy the ends of quantitative data: observable and measurable data. The target for interviewing was 10. Secondary Data Collection Secondary data are archived data or data collected for a specific research or academic purpose other than the research conducted by the user. Secondary data can be found in a number of sources and are primarily found in the library or on-line libraries or scholarly sites such as Jstor, Springer, Wiley, Google Scholar and so on (Stewart and Kamins, 1993). Thus secondary data is distinguished from primary data as the latter involves field collection specifically for the research conducted (McNabb, 2010). There are a number of useful and available secondary data sources outside of scholarly journal articles and text books. These other secondary data sources include governmental, organizational, and scholarly data sets compiled for the purpose of information or for the purpose of aiding in further research (Schutt, 2006). In addition to these secondary data sources, this research will also use relevant websites maintained by government, organizations, news bureaus and inter-governmental organizations. Data Analysis Qualitative Data Analysis Qualitative data analysis involves looking at the results and exploring, observing and reporting what the data reveals. The researcher takes an approach in which the data is observed and all possible explanations are exhausted with the result that the most logical and reasonable explanation is left unchallenged. The researcher identifies commonalties and discrepancies in the data and attempts to determine whether or not the commonalities and discrepancies are linked (Caudle, 2004). Quantitative Data Analysis Quantitative data analysis permits the collection of quantified data, which are statistically measurable (Wetcher-Hendricks, 2011). The results of the surveys are calculated using SPSS software and are reported statistically. In using the SPSS software, a multiple regression analysis is conducted. A multiple regression analysis identifies and measures the relationship between ‘two or more independent variables’ and explains its relationship to ‘variations in dependent variables’ (Allen, 1997, p. 76). The independent variables in the survey are perceptions of the government’s renewable energy policies, perceptions of the government’s renewable energy practices, perceptions of companies’ renewable energy policies and practices, and resident’s energy efficiency attitudes and practices. The dependent variables are the impact of government and corporate energy efficiency policies and practices on resident’s energy efficiency knowledge and practices. The independent and dependent variables are entered into the SPSS software and calculated using the multiple regression template. Reliability Reliability refers to the degree to which the research report and the results are believable. To this end, a research report and its results are reliable when anyone who reads the report is confident that the results can be relied upon (Creswell, 2012). In order to ensure that anyone reading the research report can rely on or have confidence in the research results, a number of measures were adopted by the researcher. The reliability of the survey was tested through a pilot test among 150 of the Qataris in the UK by The Culture Attaché Office, Embassy of The State Of Qatar in the UK. The survey was further tested among the researcher’s colleagues. Other measures were taken to ensure the reliability of the results. To begin with, the researcher created an audit trail documenting the collection, categorizing, coding and safekeeping of the data and its results. In other words, the researcher kept ‘track’ of interviews and surveys and in doing so, ensured that they were in the sole possession of the researcher and unavailable to anyone else (Cast, 2010, p. 1039). Interviews and contemporaneous notes taken at the time of the interviews were coded, and annotated and kept by the researcher to safeguard against loss, destruction and modification of the data. Field notes and contemporaneous notes were also necessary to ensure that the researcher did not have to rely on memory. Similarly, the surveys were kept in the sole custody of the researcher to ensure that the researcher did not have to rely on memory. In conducting the interviews, the researcher used a technique referred to as member checking to eliminate the risk of unreliable responses to a question. Member checking is a technique in which the researcher reads back or repeats a response to an interview question where the participant’s response is ambiguous or potentially misunderstood. After reading the participant’s response, the researcher asked the participant if that was what he or she meant to say (Harper and Cole, 2012). With regards to the surveys, a pilot test, was conducted among experts and colleagues. The purpose of a pilot test is to test the usability and validity of the research instrument. The survey is distributed among colleagues and experts and after completion the participants are asked a number of questions. Questions asked relate to the ability to understand the questions, the questions relevance to the research topic, and so on. By using a pilot test, the researcher has the opportunity to improve the survey instrument before distributing it for the purposes of this research (Panter and Sterba, 2011). Further, in ensuring that the results of the surveys and interviews were reliable, the researcher selected only questions that are relevant to the research objectives and research questions. This was a necessary strategy for eliminating the risk of obtaining information that was not relevant and therefore not usable. Moreover, the questions were kept as simple and clear as possible to reduce, if not eliminate, the risk of confusion and therefore unreliable responses. In order to safeguard against boredom and rushed responses, the surveys and interviews were designed to take the shortest time possible. The replicability of the study also contributes to the reliability of the study. Replicability refers to the possibility of the research results being transferrable to another study on the same or very similar research. In addition if the study can be applied to or conducted on the same population or a different population and produce similar or the same results, the research study and its results are replicable (Whitley and Kite, 2013). This research study was applied to a population of residents in Qatar and did not require special adjustments for the specific needs of the population, it is therefore highly replicable. In order to ensure further reliability, the interviews and surveys were administered in Arabic and English. The interview results as well as the survey results were then translated into English by a bilingual expert who verified that the results were duly and appropriately interpreted. Therefore, having regard to the measures adapted in this study, this research is reliable. Conclusion This chapter set out the research methodology used in this dissertation and provided an explanation and justification for the collection and analysis of the data. The data described in this chapter is primary and secondary data. The research philosophy, sampling, validity and reliability of the study are also described. This chapter also states the significance of this study. References : Allen, M.P. 1997. Understanding Regression Analysis. New York, NY: Plenum Press. Blaikie, N. 2007. Approaches to Social Enquiry. 2nd Edition. Cambridge, UK: Polity Press. Byrne, D. and Ragin, C.C. 2009. The SAGE Handbook of Case-based Methods. London: SAGE Publications, Ltd. Camerino, O.; Castaner, M. and Anguera, M.T. 2012. Mixed Methods Research in the Movement Sciences. Oxon, UK: Routledge. Cast, D.L. and Ledford, J. R. 2010. Single-subject Research Methodology in Behavioral Sciences. New York, NY: Routledge. Caudle, S.L. 2004. ‘Qualitative Data Analysis’. In Wholey, J.S.; Hatry, H.P.; and Newcomer, K.E. (Eds.) Handbook of Practical Program Evaluation. San Francisco, CA: Jossey-Bass, Ch. 15. Creswell, J.W. and Clark, V.L.P. 2011. Designing and Conducting Mixed Methods Research. 2nd Ed. Thousand Oaks, CA: Sage. Creswell, J.W. 2012. Qualitative Inquiry and Research Design: Choosing among Five Approaches. Thousand Oaks, CA: Sage. Crotty, M. 2005. The Foundations of Social Research: Meaning and Perspective in the Research. London, UK: SAGE Publications. Evans, J.St. B.T. 2000. ‘What Could and Should not be a Strategy in Reasoning.’ In Schaeken, W.; De Vooght, G.; Vandierendonck, A..and d’Ydewalle, G. (Eds.) Deductive Reasoning and Strategies. Mahwah, NJ: Lawrence Erlbaum Associates, Inc. Ch. 1. Gravetter, F. and Forzano, L-A. 2015. Research Methods for the Behavioral Sciences. Stanford, CT: Cengage Learning. Harper, M. and Cole, P. March 2012. ‘Member Checking: Can Benefits be Gained Similar to Group Therapy?’ The Qualitative Report, 17(2): 510-517. Johnson, R.B.; Onwuegbuzie, A.J. and Turner, L.A. April 2007. ‘Toward A Definition of Mixed Methods Research.’ Journal of Mixed Methods Research, 1(2): 112-133. McNabb, D.E. 2010. Research Method for Political Science: Quantitative and Qualitative Approaches. 2nd Ed. New York, NY: ME Sharp. Monette, D.; Sullivan, T. and DeJong, K. 2014. Applied Social Research: A Tool for the Human Services. Belmont, CA: Brooks/Cole. Panter, A.T. and Sterba, S.K. 2011. Handbook of Ethics in Quantitative Methodology. New York, NY: Routledge. Roulston, K. 2010. Reflective Interviewing: A Guide to Theory and Practice. Thousand Oaks, California: SAGE. Schutt, R. 2006. Investigating the Social World: The Process and Practice of Research 5th Ed. Thousand Oaks, CA: Pine Forge Press. Stewart, D.W. and Kamins, M.A. 1993. Secondary Research: Information Sources and Methods. 2nd Ed. Thousand Oaks, CA: SAGE. Tashakkori, A. and Teddlie, C. 2010. SAGE Handbook of Mixed Methods and Social and Behavioural Research. Thousand Oaks, CA: SAGE. Tashakkori, A. and Teddlie, C. 1998. Mixed Methodology: Combining Qualitative and Quantitative Approaches. Thousand Oaks, California: SAGE. Wengraf, T. 2001. Qualitative research interviewing: Biographic Narrative and Semi-Structured Methods. London, UK: SAGE. Wetcher-Hendricks, D. 2011. Analysing Quantitative Data: An Introduction for Social Researchers. Hoboken, NJ: John Wilen & Sons, Inc. Whitley, B.E., Jr. and Kite, M.E. 2013. Principles of Research in Behavioral Science.3rd New York, NY: Routledge. Willis, J. W. 2007. Foundations of Qualitative Research: Interpretive and Critical Approaches. Thousand Oaks, CA: Sage. Bibliography Colombo, S. 2014. Bridging the Gulf: EU-GCC Relations at a Crossroads. Rome: Istituto Affari Internazionali. Gross, P.; Kovacevic, R.M. and Pflug, G. C. 2013. ‘Energy Markets.’ In Kovacevic, R.M.; Pflug, G.C. and Vespucci, M.T. (Eds.) Handbook of risk management in energy production and trading. New York, NY: Springer, Ch. 1. Jackson, S. 2012. Research Methods and Statistics: Critical Thinking Approach. Belmont, CA: Wadsworth. Park, P. 2013. International Law for Energy and the Environment. Boca Raton, FL: Taylor & Francis, Group. Qader, M.R., 2009. Electricity Consumption and GHG Emissions in GCC Countries. Energies, 2: 1201–1213. Talus, K. 2014. Research Handbook on International Energy Law. Glos., UK: Edward Elgar Publishing, Limited. US Energy Information Administration. 2014. Today in Energy. EIA http://www.eia.gov/todayinenergy/detail.cfm?id=16311 [Accessed 28 October 2014]. Wilhite,H., Nakagami,H., Masuda,T., Yamaga,Y., and Haneda, H., 1996. ‘Across- culture Analysis of Household Energy use Behaviour in Japan and Norway.’ Energy Policy, 24 (9): 795-803. Summary This research is an exploratory and descriptive study which seeks to identify attributes for and obstacles to, sustaining and implementing successful and efficient renewable energy policies. A pragmatic research method is also taken and as such, involves a mixed methodology. The mixed methods research was selected for improving the reliability of the research results. This is because mixed methods research allow for and facilitate the collection of both qualitative and quantitative data. Reliability issues are resolved because the strengths in one data source compensates for the weaknesses in the other data source. For example, the small sample size often used in qualitative data is compensated by the large sample size often used in quantitative data. Similarly, the lack of detail absent in quantitative data is offset by the great detail found in qualitative data. Therefore using a mixed methods approach is far more reliable than using one method over another. In conducting a mixed methods approach two research philosophies are used in this research. The first of these philosophies is interpretivism which assumes that truth is subjectively constructed. This philosophy is consistent with the aims of qualitative data sources which seek to gain insight and understanding from the perspectives of those who have experienced or are experiencing the phenomenon under investigation. The second philosophy is positivism which assumes that truth can be objectively constructed and as such can be observed and measured. This is consistent with the objectives of quantitative data which seek to observe and measure facts. The recruitment and participation of a population consisting of energy users and experts in renewable energy in Qatar are pursued through a purposive and convenience sampling method. The use of a convenience sampling method is aimed at the recruitment of and participation of energy users among the general adult population in Qatar. The convenience sampling method is used for the participation in the surveys and the purposive sampling is used for participants in the semi-structured interviews. The participants in the semi-structured interviews are from a population of experts on renewable energy in Qatar. Therefore, the survey is aimed at a target population of 500 while the interviews are aimed at a target population of 10. Two research instruments are necessitated by the mixed methods research. A survey which is lacking in detailed responses is used in the quantitative data collection. The brevity of the responses allows for the collection of data from a relatively large population sample. The qualitative data is collected from a smaller population sample as it is much more robust and detailed. In complying with research ethics, the data is collected from the participants with their knowledge, consent and voluntary participation. The qualitative data is analysed using an exploratory approach. In other words the results are explored and observed until all explanations are exhausted. The quantitative data is calculated using SPSS software in which variables are measured using a regression analysis. The quantitative results are statistically reported. The reliability of the survey is tested through a pilot test in which the survey was distributed among 150 participants prior to use in this research. The survey was also tested for reliability through a small number of the researcher’s colleagues. A number of other measures were taken to ensure the reliability of the research results. These further measures included but were not limited to, clarity of questions asked, creating an audit trail, safe custody of the data and replicability of the study. Read More