Data Collection Method

Using qualitative data collection method, it rely on random sampling and structured data collection instruments that fit diverse experiences into predetermined response categories. They produce results that are easy to summarize, compare, and generalize. Quantitative research is concerned with testing hypotheses derived from theory and/or being able to estimate the size of a phenomenon of interest. Depending on the research question, participants may be randomly assigned to different treatments.

If this is not feasible, the researcher may collect data on participant and situational characteristics in order to statistically control for their influence on the dependent, or outcome, variable. If the intent is to generalize from the research participants to a larger population, the researcher will employ probability sampling to select participants. From this research, the researcher used questionnaires and surveying technique in collecting data. In the surveying techniques, it involves direct questioning of respondents about price.

The researcher can choose whether to present the respondent with a range of possible prices, or force a response with no point of reference other than the concept and the question. While, for the questionnaires, researcher used the Web based questionnaire and structured questionnaire. By using web based questionnaire, it is the use of Internet based research. This would mean receiving an e-mail on which would click on an address that would take to a secure web-site to fill in a questionnaire. This type of research is often quicker and less detailed.

People might be in a hurry to complete it and so might not give accurate responses. In this research ,researcher used of 2500 questionnaires mailed. While, for the Structured questionnaire, it is the structure of the individual questions requires respondents to qualify their price based on an implied assumption about quality. The structure of the individual questions also was designed to capture consumers’ willingness to pay more for the five common wood products, given environmental certification.

Respondents were given a non-certified price for each of the five products and asked to identify the price they were willing to pay for an environmentally certified product. Their data using data analysis techniques. Data analysis techniques that stated in this research includes, factor analysis, correlation, ANOVA, Chi Square, and descriptive statistics. Factor analysis( maximum likelihood with varimax rotation) was conducted on 20 items. This resulted in a reduction to five underlying factors.

The factors were subjected to scale testing with resulting Cronbach alpas ranging from 0. 62 ( involvement in Certification) to 0. 90(importance of Certification). Correlation analysis . Correlation analysis is used by the researcher to test the relationship between factored. All hypothesized relationships were found to be significant and all but one was found to be directionally as hypothesized. Price was found to be positively correlated to consumer willingness to pay for certified wood products, the inference being that consumers perceive incremental value in certified products.

Analysis of Variance (ANOVA) is a data analytic technique based on the idea of comparing explained variance with unexplained variance, kind of like a comparison of the coefficient of determination with the coefficient of alienation. It uses a rather unique computational formula which involves squaring almost every column of numbers. ANOVA techniques was used to test the hypotheses of no difference between the cluster means in this research. Chi square.

In this research, researcher used chi square. A technique designed for less than interval level data is chi-square and the most common forms of it are the chi-square test for contingency and the chi-square test for independence. The chi-square test for contingency is interpreted as a strength of association measure, while the chi-square test for independence (which requires two samples) is a nonparametric test of significance that essentially rules out as much sampling error and chance as possible.

In this research it used chi square for the purpose of compared consumer segments on selected demographic characteristics. The consumer segments compared on selected demographic characteristics includes democrat, and environmental group member. Descriptive statistics. Descriptive statistic used in this research to measures of central tendency of mean. Examples include descriptive analysis of age, gender, education level, income level, republican , political view, democrat and environmental group member.