Research design is a framework or blueprint

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1st Jan 1970 Psychology Reference this

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A research methodology defines what the activity of research is, how to proceed, how to measure progress, and what constitutes success. This chapter is going to describe how the research is carried out in term of research design, data collection methods, sampling design, operational definitions of constructs, measurement scales, and methods of data analysis. The data and information obtained were further analyzed using Statistical Package for Social Science (SPSS) software.

3.1 Research Design

Research design is a framework or blueprint for conducting the marketing research project. It details the procedures required for solving the marketing research problems. In addition, a research design can be defined as a master plan specifying the methods and procedures for collecting and analyzing the information needed (Zikmund, 2003). Research design can be classified into four main types which include case study, survey, experimental, and comparative. In this current study, the research design that used is survey method. Therefore, setting a good research design will make sure the marketing research project is conducted efficiently and effectively

3.1.1 Quantitative Research

The quantitative research will be conducted in this research project. Quantitative research is used to determine how many people feel, think or act in a particular way. Besides, this type of research tends to include large samples range from size around 50 up to thousand of respondents. The aim of this research is to classify features, count them, and construct statistical model in an effort to explain what is observed in the research project. Questionnaires are designed to collect specific responses regarding respondents’ behavior, intention, and attitude toward green purchasing behavior. Therefore, by using quantitative research, the researchers can estimate factors that affecting green purchasing behavior in Malaysia.

3.1.2 Descriptive Research

Descriptive research can be defined as statistical research that used to describe data and the characteristics about the population or phenomenon that are being studied. Besides that, descriptive research answer the questions who, what, where, when and how. In current study, there are seven independent variables to be conducted in this research design which are social influence, environmental attitude, environmental concern, perceived seriousness of environmental problems, perceived environmental responsibility, perceived effectiveness of environmental behavior and concern for self-image in environmental protection. By using descriptive research in this study, researchers can determine Malaysian’s perception toward green purchasing behavior. In addition, this research design also can help the researchers to determine the frequency of green purchasing behavior in Malaysia. Moreover, descriptive research is less expensive and time consuming and can get to collect a large amount of data for detail study. Next, cross sectional under descriptive research can be divided into two types which are single cross -sectional design and multi cross-sectional design. In this study, single cross-sectional design is more appropriate. This is due to in single cross-sectional designs only one sample of respondents is drawn from the target population and information obtained from the sample only once. Additionally, this type of research design will be easier to conduct because it is less time consuming and cost efficiency. The questionnaires are given to respondents without repeated with the purpose to test the relationship of the seven independent variables in green purchasing behavior in Malaysia.

3.2 Data Collection Method

Data collection is the process of preparing and collecting data. The data collected in this research project is using written questionnaire hand- delivered to respondents. Data can be categorized into two types that are primary data and secondary data.

3.2.1 Primary Data

Primary data is a data gathered and assembled specially for the project at hand (Zikmund, 2003). Besides, primary data refer to information obtained firsthand by the researchers on the variables of interest for the specific purpose of the study ( Sekaran, 2003). For example, gather information through questionnaires, interviews, and observation. In this research project, questionnaire survey method used as a primary source of data. Further, 150 copies of questionnaires will be distributed to respondents. The target respondents are those Malaysian citizens in Kuala Lumpur area. The questionnaires are distributed and collected back on the spot within 5-10 minutes from respondents after they finished answering the questionnaires in order to reduce the risk of losing questionnaires and mistake make by respondents.

3.2.2 Secondary Data

Secondary data is data gathered and recorded by someone else prior to (and for purposes other than) the current needs of the researcher (Zikmund, 2003). This data is less expensive to collect than primary data and it takes less time to collect. This type of data provides useful information for the research study. The secondary data which support the research study obtain from online resources. Most of the journals have been collected from various databases such as ProQuest Online Resources, ScienceDirect, JSTOR and Scopus which provided in the University Tunku Abdul Rahman Library database. Besides, some of the journals are obtained from Google Scholar. Furthermore, several text books of business research also used as a secondary data in the research project.

3.3 Sampling Design

Sampling design is a plan for selecting representative subgroup and the procedure by which a particular sample is chosen from a population. A good sampling design will help researchers to gain relevant information about the factors influencing green purchasing behavior in Malaysia. This section consists of research on target population, sampling frame and sampling location, sampling elements, sampling technique and sampling size.

3.3.1 Target population

A target population refers to the whole group of people, events, or things of interest that the researcher wishes to study (Sekaran, 2003). In this research project, the target respondents in determining factors affecting green purchasing behavior are the entire Malaysian citizens who stay in Malaysia.

3.3.2 Sampling frame and sampling location

A sample frame is a list that includes every members of the population from which a sample is to be taken. It is also a representation of elements of the target population. In determining the factor affecting green purchasing behavior in Malaysia the sample frame will be all Malaysian citizens in Kuala Lumpur area. Furthermore, the sampling location selected will be several shopping malls in Kuala Lumpur. The reasons of the selected sampling location is due to shopping malls there have a large scope of potential respondents which can provide a high respond rate on green purchasing behavior in Malaysia.

3.3.3 Sampling Elements

A sampling element is a single member or unit of the target population and this is the unit about which information will be obtained. The sampling element for the assessment should be clearly defined within the target population. In this study the element selected are Malaysia citizens in Kuala Lumpur area who visit in the shopping malls.

3.3.4 Sampling Technique

There are two types of sampling technique on how the respondents were chosen which are probability sampling and non-probability sampling. Probability sampling method is a sampling method that use some form of random selection and set up some process or procedure to ensure that the different units in population have equal probabilities of being selected. Probability sampling method consists of five different types there are simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. However, non-probability sampling method is a sampling method that does not involve random selection. Non-probability sampling fall into four categories: convenience sampling, judgment sampling, snowball sampling and quota sampling (Hair, Money, Samouel, Page, 2007).

Non-probability sampling will be used in this current study which is base on convenience sampling. Convenience sampling is methods where the elements are chosen in nonrandom manner and some member of the population have no chance of being included. The convenience sampling is being administered because it is fast, inexpensive, and easy and the elements are readily available than all sampling technique. Besides, the sampling units are available and easy to measure so it is an appropriate method to use in this research study. Therefore, the researchers will distributed the questionnaire to the respondents at the crowded areas in the shopping malls and stop by the visitors as they pass by in order to help the researchers to fill up the survey questionnaire.

3.3.5 Sampling Size

The sample size defines as the number of elements to be involved in the study. Furthermore, 150 copies of questionnaires will be distributed to visitors who having their shopping in the shopping malls.

3.4 Research Instrument

Research instrument is a testing device for measuring a given phenomenon for the purpose to find out what information is needed. The research instrument that has been selected in this study is questionnaire. A questionnaire can be defined as a research instrument which consists of a series of questions and other hints for the purpose of gathering information from target respondents. The survey questionnaires are not designed to influence or persuade respondents but it is used to discover information through the questions. The questionnaire for this research was adapt from previous research study Lee (2008), which studied on young green consumer in Hong Kong. Questionnaires are very cost effective when compared to face to face interviews and it is easy to analyze. In addition to that, completed questionnaire provide permanent result for researchers to review when needed. The questionnaire is a perfect research instrument as it is designed for large quantity of data which is suitable for quantitative research.

3.4.1 Questionnaire

The researchers used the closed-ended types of question in the survey questionnaire. The closed-ended question is a type of question where the respondents are given the option of choosing from a number of predetermined answers (Hair, Money, Samouel, Page, 2007). The reason for choosing closed-ended type question is because the answer are easy to analyze and understandable. Closed-ended questions require respondents to concentrate in the answer provided and they will not answer the irrelevant answer compare to open-ended types of questions. The current research questionnaire consists of two parts which are Section A: Respondents’ Personal Data and Section B: Constructs Measurement.

Section A: Respondents’ Personal Data

Section A is the respondents’ personal data which is the demography of the respondents. This section consists four questions which include gender, age, higher education level and monthly income level. Most of the questions in this section are multiple choices and contents straight-forward questions.

Example:

Age : ( ) < 15

( ) 15-24

( ) 25-34

( ) 35-44

( ) 45-54

( ) 55-64

( ) > 65

Section B: Construct Measurement

However, section B of the survey questions is more on the knowledge and understanding of respondents. In this section consists of eight parts in determining whether the seven independent variables such as social influence, environmental attitude, environmental concern, perceived seriousness of environmental problems, perceived environmental responsibility, perceived effectiveness of environmental behavior, concern for self-image in environmental protection and the dependent variable, green purchasing behavior will affect respondents’ green purchasing behavior. The questions in this section are using the degree of agreement and disagreement, Likert scale.

Example:

Section B:

Please circle the most appropriate response in respect of the following items.

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

1

2

3

4

5

Social Influence

Social influence is the changes in one’s thoughts, feelings, attitudes or behaviors that result from communication with another individual such as friends, families, colleagues and others.

1.

I will learn about environmental products from my friends, families, colleagues and others.

1

2

3

4

5

3.4.2 Administrative of the questionnaire in the research

In descriptive research, the research methodologies and procedures can be classified into survey method, observation method, self-report and tests. The survey method was chosen to be conducted in the current research. This is due to surveys method is very useful when a researcher wants to collect data on phenomena that cannot be directly observed. Furthermore, survey method can be divided into two board types that are questionnaire and interviews. The researcher choose questionnaire in this survey method.

Survey data can be collected in a number of ways such as personal administered, telephone administered, self-administered and online survey. Self-administered survey method will be used for the current research study. A self-administered survey method is one of the method in which the respondents completes the survey on his or her own and it is a traditional “paper and pencil survey. The reason that researchers choose this method is due to low cost in survey and no interview evaluation apprehension occurs. In the current research, survey forms are distributed to the respondents who ever visit at the shopping malls and the survey forms are collected on the spot within 5-10 minutes after the respondents finished answering the questionnaire.

3.4.3 Pilot testing

The main objective to carry out a pilot testing on the questionnaire is to test whether the respondents fully understand with the survey questionnaire that have been distributed to them and to determine whether the questionnaire have any grammatical errors. Pilot testing was carried out in order to avoid ambiguous and misleading wording in the questionnaire. Furthermore, pilot test carried out to test the reliability of the questionnaire.

The pilot test was carried out by involving thirty respondents from Kampar areas. From the feedback given by respondents the questionnaire do not have any major mistake and the respondents manage to follow the instruction in the questionnaire and answer the questionnaire successfully.

The pilot test done by researchers is to ensure that the questionnaire will be reliable in order to provide more precise and clear result in the research study. The pilot test indicated that there are no mistakes and all the variables in the questionnaire are reliable (refer to table 3.1: reliability test). Nunnally (1987) suggest that the minimum level 0f 0.60 would be an acceptable level. Therefore, there are no modifications of questions.

3.4.4 Main Test

The main test of study has been carried out after the pilot testing. Total of 150 questionnaires will be distributed to respondents at several shopping malls in Kuala Lumpur. The respondents manage to follow the instruction in the questionnaire and answer the questionnaire successfully. Response rate from the collection data is 100 percent.

3.5 Constructs Measurement (Scale and Operational Definitions)

Basically, the research question in the questionnaire is measure based on four common types of scale such as nominal scale, ordinal scale, interval scale and ratio scale. In current research the questionnaire is measure based on nominal scale and interval scale.

Nominal scale is a scale in which the numbers or letters assigned to objected serve as labels for identification or classification, a measurement scale of the simplest type (Zikmund, 2003). Nominal scale is used to collect data hold in demographic section. Besides, in nominal scale the numerical values are the name of the characteristic. In the questionnaires the nominal values for instance is gender has values 1=Male, 2=Female where the order is not in sequence whereas in ordinal scale the attributes can be rank-ordered. In an ordinal measurement the interval between values is non interpretable whereas in interval scale the distance between values is interpretable. Hence due to that, it makes sense to calculate an average of an interval variable but it doesn’t for ordinal scale. Lastly, for ratio scale there is always an absolute zero that is significant. It’s vital to recognize that there is a hierarchy implied in the level of measurement idea. At lower levels of measurement, assumptions tend to be less restrictive and data analyses tend to be less susceptible and as at each level up the hierarchy, the current level includes all of the qualities of the one below it and adds something new and the same goes for all levels respectively.

Likert scaling is simply a statement which the respondent is asked to evaluate a subjective question or topic in general the level of agreement or disagreement is measured. Besides, according to Sekaran (2003), Likert scale is designed to examine how strongly subject agree or disagree with the statement on a 5-points scale. Five ordered response levels which are often used in the questionnaire shown as following.

Strongly disagree

Disagree

Neutral

Agree

Strongly agree

In section B of the questionnaire Likert scale was applied to measure the response in the survey. Likert scale helps the researchers to identify clearly and measure the degree of the answer from the questions. Furthermore, Likert scale is a bipolar scaling method, measuring either positive or negative response to a statement. Sometimes a four-point scale is used since the middle option which is “neutral” is not available. On the other hand too much of a neutral will also affect the precision of the data. To obtain a precise and accurate data many steps involved which some of them consist of data editing, data coding, data transcription and data cleaning.

3.6 Data Processing

The word data is commonly known as information. It consists of large amounts of information in a standardized format. Generally, data processing is a separate step in the information processing cycle. In information processing, data is obtained, entered, validated, processed, stored, and output both in response to queries or in the form of reports while on the other hand, data processing refers to the actions of recording or handling one or more sets of data. Furthermore, data processing defines as the process by means of which data is transformed into information. Data processing adapted in calculations can be used to refer to the employment of a software application to work on a particular of input data in order to create some sort of output. The output or result varies from a multimedia file to an image, or a text file. For instance, entering receipts and expenditures for the month in a spreadsheet program and printing a report is consider as data processing. In the survey, data processing consists of several steps which are questionnaire checking, data editing, data coding, data transcription and data cleaning to ensure high quality of data.

Step 1: Questionnaire Structure

A framework of questions are prepared and checked thoroughly to ensure everything is done correctly. The questionnaire is checked by distributing several sets of questionnaire while it is still in progress. Hence, any error can be detected and correction can be made beforehand to assure the subsequent set of questionnaires can be distributed to all with no error.

Step 2: Data Editing

The next step is data editing which review questionnaire that had completed in order to increase the accuracy and precision. Some of the questionnaire distributed may be incomplete or unanswered by respondents. Thus, we will have to check out those incomplete questionnaires. It is usually discarded or returned to unsatisfactory respondents to filling out the missing value to reduce response bias to minimal.

Step 3: Data Coding

The next step is data coding which transferring a code, representing a certain response to a certain question. Coding can be done after the whole questionnaire have been completed.

In Part A, for instance:

Question 1, “Male” is coded as 1 and “Female” is coded as 2.

Question 2, <15 is coded as 1"15-24" is coded as 2, "25-34" is coded as 3, "35-44" is coded as 4, "45-54" is coded as 5, "55-64" is coded as 6 and >64 is coded as 7.

Question 3,”UPSR” is coded as 1,”PMR is coded as 2, SPM/UEC is coded as 3,”STPM/ A-level/Pre U is coded as4,”certificate” is coded as 5,”Diploma”is coded as6, “undergraduate” is coded as7,”postgraduate” is coded as 8, and “Others” is coded as 9.

Question 4, “≤ RM1000” is coded as 1, “RM1001 to RM2000 is coded as 2, “RM2001 to RM3000” is coded as 3, “RM3001 to RM4000″ is coded as 4,”RM4001 to RM5000″ is coded as 5,”RM5001 to RM10,000″ is coded as 6,” and “≥ RM10,001” is coded as 7

For Part B, there are total 48 questions. All the questions in this part will be coded with the number 1 to 5 for different degree. “Strongly Disagree” is coded as 1, “Disagree” is coded as 2, “Neutral” is coded as 3, “Agree” is coded as 4 and “Strongly Agree” is coded as 5.

Step 4: Data transcription

Once the checking and editing of data is done, transcribing the data is revising. Data transcription is a process to send all the data collected into the computer in preparation for analysis.

Step 5: Data Cleaning

Data cleaning involving consistency checking which implemented by use of the Statistical Package for Social Science (SPSS) software to ensure that the data have been correctly inputted from the data collection form.

3.7 Data Analysis

Once the completed questionnaire has been collected, the data is entering into Statistical Package for Social Science (SPSS).

3.7.1 Descriptive Analysis

Descriptive analysis and frequency distribution were used to present respondent’s personal data or classification variables such as age, gender, occupation, race, income, and others. Mean, mode, frequency, range, standard deviation, and variance were obtained for interval scales independent and dependent variables. Additionally, descriptive statistics such as mean, mode, median, maximum, minimum, standard deviation, and so on can be obtained so that the researchers can get a good idea of how the respondents have reacted to the items and how good of the item and measure are.

3.7.2 Scale Measurement

Reliability Test

Variable

No. of Items

Cronbach’s Alpha

Ranking

Social Influence

6

0.794

6

Environmental Attitude

6

0.848

4

Environmental Concern

6

0.859

3

Perceived Seriousness of Environmental Problems

6

0.899

1

Perceived Environmental Responsibility

6

0.791

7

Perceived Effectiveness of Environmental Behavior

6

0.756

8

Concern for Self-image in Environmental Protection

6

0.881

2

Green Purchasing Behavior

6

0.809

5

Reliability is the degrees of which measures are free from error therefore yield consistent result. Reliability applied to a measure when similar results are obtained over time across situation. Two dimensions underlie the concept of reliability: one is repeatability and the other is internal consistency. Accessing the repeatability of a measure is the first aspect of gauging reliability (Zikmund, 2003). Cronbach’s alpha measures how well a set of items (or variables) measures a single dimensional latent construct. However, when data have a multidimensional structure, Cronbach’s Alpha will usually be low. Basically, Cronbach’s Alpha is not a statistical test but it is a coefficient of reliability (or consistency). Besides that, Cronbach’s Alpha test was on run on the data collected to determine the reliability of data collected. The Cronbach’s Alpha value of less than 0.60 generally judge as has poor internal-consistency reliability. If the Cronbach’s Alpha is more than 0.70, the internal-consistency reliability is satisfactory. Nunnally (1978) suggested that the minimum level of 0.60 would be an acceptable level. Cronbach’s Alpha can be written as a function of the number of test items. Moreover, Cronbach’s Alpha will generally increase as correlations between the items increase. Thus, the coefficient is also known as internal consistency or the internal consistency reliability of the test (Cronbach, 1951). Cronbach’s Alpha can take value between negative infinity and 1 (although only positive values make sense). Based on Table 3.1, the Cronbach’s Alpha of the construct was ranged between 0.756 and 0.899. Therefore, this shows that the seven independent variables and dependent variable are reliable. These is due to the variables had exceeded the minimum criterion of 0.60.

Table 3.1: Reliability Test

N= 30

Source: Developed for the research

3.7.3 Inferential Analysis

Pearson correlation coefficient is used to measure the linear association between two metric variables (Hair et al., 2003). A correlation test was applied in the study in order to examine the strength of relationship between the variables toward consumer’s green purchasing behavior. The number representing the Pearson correlation is referred to as a correlation coefficient which ranges from -1.00 to +1.00, with zero representing absolutely no association between two metric variables. The result -1.00 or +1.00 is possible and represents a perfect association between two variables. From the correlation, the significant relationship between the 7 variables and the overall green purchasing behavior will test using Person correlation method.

The multiple regression method is used to represent the best prediction of a dependent variable (DV) from several independent variables (IV). This used to examine the simultaneous effects of independent variables (IV) on a dependent variable (DV). Multiple Regression test use to measure the relationship between 7 independent variables with green purchasing behavior. From this analysis, the most influential variable and the least influential variable can be identified.

3.8 Conclusion

Chapter three discusses the reach design, data collection methods, sampling design, research instrument, construct measurement, data preparation process, and data analysis methods, which were used in current research. The following chapter will present the patterns of the results and analysis of the result which are relevant to the research questions and hypotheses. Chapter four will give a detailed analytical understanding and illustrate the result of all the applied methodologies in chapter three.

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