Factors Affecting Consumers Acceptance of the MVM Technology - Research Proposal Example

Chapter 5 for plag check: This study used Kinnear and Taylor (1996) seven stages of research process as a backbone of this research process. A detail methodological diagram has been illustrated and explained in Figure 3. Aaker et al, (2007) addressed the importance for a research framework as it provides a systematic planned approach to a research project and ensures all the aspects within the research are consistent with each other. The choice of research approach depends very much on the nature of the research. (Aaker, et al 2007; Saunders et al 2003). Generally there are two main types of approaches; 1) Deductive approach and 2) Inductive approach (Saunders at al 2003; Holmes, 2001). Inductive approach begins with data collection, examining the data, followed by forming hypotheses and then construct theories. (Saundes et al, 2003). Different from inductive approach, Deductive approach is the process of reaching a conclusion from previously known facts (premises) and it is dependent on its premises; if the premises are true, then the conclusion must be true. Likewise, a false premise can possibly lead to false result (Crow, L.D., PhD. and Crow, A.C., PhD. 1968; Holmes S.; Woolfolk, 2001). In this study, the researcher used quantitative approach, which consisted of a customer survey. And before carrying out the survey, a Literature review has been undertaken in order to gain a better knowledge about the existing factors influencing consumers’ acceptance of the MVM Technology. Creating a Literature review is essential as it helps the researcher to build up knowledge base of the possible factors relating to this subject. (Cooper & Schindler 2001; Saunders et al, 2003) It was carried out to identify the possible factors influencing customers’ attitude and intention towards the MVM technology based on the extended TAM model. Afterwards, research framework and hypotheses of this study were developed based on the initial findings from the Literature review, and a quantitative customer questionnaire was conducted as a test for the hypotheses. Quantitative Research Method, according to Saunders et al (2003) is a systematic scientific investigation of properties and phenomena and their relationships; most commonly used in studying natural science, social sciences, or develop and employ mathematical models, theories, and hypotheses, which pertains to a natural phenomenon. 5.4.1 Justification of Research The purpose of this customer questionnaire is to test the research framework and hypotheses through gathering information on knowledge, attitudes, opinions, behaviours, facts and other information needed which are related to the topic or subject under study. (Radhakrishna, R.B., 2007). It allows the respondents to have more time in considering their responses carefully without interference from an interviewer (Aaker et al, 2007; Saunders et al, 2003) The result of the questionnaire should allow the researcher to find out the relationship between variables developed in the research framework through exploring customers’ experiences in using MVM system, the relationship between the usefulness and ease of using this system and the attitude and intention towards the technology. The target populations are both U.K. and U.S. consumers who aged from 18-35 Internet users and have the knowledge in computer. (The reason for choosing internet users in UK and US is because UK and US online shopping culture is more developed (forrester research, 2005, Mintel, 2006) compare to other countries, also MyVirtualModel is so far adopted by US and UK base E-retailers.) Moreover a lot of studies show that people who falls in the 18-35 age bracket are more likely to shop online, and willing to try on new technologies (Mintel, 2006). Both genders will be considered in the target population, although numerous studies agree that women report a higher level of computer anxiety and treated as primary shoppers (Hirst and Omar, 2007; Park and Stoel, 2002; Xu and Paulins, 2005). However men tends to shop more via the Internet (Lynch et al, 2001). Therefore both men and women will be included in this study. Reason for choosing Internet users is because compared to general population these users are more likely to be aware of the online shopping even if they do not shop on-line, internet users are essentially those who have the choice to shop on-line, by excluding the non-users, this sampling approach is more likely to capture an adequate number of e-shopping observations and will achieve better balance between the internet buyers and non-buyers. 5.4.3 Sampling approach and sampling frame According to Aaker et al, (2007) sampling method can be divided into two big categories and this includes: 1: probability sampling, 2: non-probability sampling. Probability sampling permits the researcher to demonstrate that sample is representative and is commonly associated with survey-based research. (Aaker et al., 2007; Saunders et al, 2003). In probability sampling every segment of the population are most likely included and this sampling method is beneficial in giving results that are projectable to the population segments with confidence Sampling frame and information on the sampling units are required prior to employing the process of sampling. Non-Probability selection is based on judgment of the researcher or convenience. The process of non-probability selection is faster, far less expensive and it helps control non-sampling errors. Types of sampling techniques as well as their differences are presented in Table 4 PROBABILITY SAMPLING TECHNIQUES Differences Simple Random Sampling A group of subjects is selected from the population entirely by chance; probability of choosing any given member from the population is the same; most basic method of drawing a probability sample, assigns equal probabilities of selection to each possible sample Stratified Random Sampling Sampling is done from a target population divided into homogeneous subgroups, of which the number of sampling units that were drawn from each subgroup may either be proportionate, disproportionate or optimum. Systematic Random Sampling Sampling interval with a target population which are naturally ordered is used Cluster Sampling In groups or cluster, sampling units were selected rather than individually NON-PROBABILITY SAMPLING TECHNIQUE Judgment Sampling Selection of units that are thought to be a representative of the target population Snowball Sampling When a population consists of individuals in specialized areas this sampling method are used. Convenience Sampling Units are selected on the basis of the interviewer’s accessibility or convenience Quota Sampling Selection of people non-randomly according to some fixed data The first approach was convenience-sampling method and information can be obtained quickly and inexpensively. However, in using this convenience sampling method, the respond rate would be a concern. The average responds rate for online surveys is around 10-20%. (Cho, 2007; Oppenheim, 2002; Saunders et al, 2003) To undertake the study the researcher has sent out a total of 68 invitation mail within the mailing list and asked them to forward the email to two or three of there friends if possible. They will be asked only to send the email invitation to people who are located in UK or US particularly to make sure the data falls within the target group. This snowball sampling method can dramatically lower the search costs, reduce the likelihood that the sample will represent a good cross section from the population, and increase the sample size to reduce the problem with low respond rate. Also one week after sending out the invitation, another email will be sent out to thank those who replied and remind those who did not. This approach may also increase the respond rate. (Saunders et al, 2003) As a result, a total of 68 email invitations were sent out from the researcher email list and hopefully the sample size will get two to three times bigger because of the snowball sampling method. Secondly, another 28 respondent from the online shopping forums were approached and promised to take part in the survey. Time and expenses were the main constraints in this research therefore the above mentioned methods were the best approaches to keep the sample size large enough to provide necessary confidence data. (Aaker, et al., 2007). 5.4.4 Data collection The questionnaire will be distributed and collected through an Internet survey website. Although when doing a survey with website testing, data from an online survey may be less accurate than observation research, however it is still treated as a reliable method to research respondents’ attitudes. (Grossnickle and Raskin, 2001; Churchill 1987; Zhang, 1999). Moreover since this study is related to Internet users and they are involved in a website testing, using an Internet survey website is the most convenient and time saving approach for both the researcher and the respondents. According to Wright, (2005),the advantages of using the internet survey data collection includes the following: 1) a large amount of data are collected in a relatively short period of time; 2) it eliminates the necessity for researchers to enter or process the data; 3) hundreds of respondents can fill out the survey and answer in a few days; 4) all these responses can automatically be inserted into a database such as Microsoft access; 5) Data from web-based questionnaires can automatically be validated 6) easy access to individuals in distant locations; 7) able to reach difficult to contact participants 5.4.5 Questionnaire Design The process of developing the questionnaire in this study was carefully structured. The researcher make sure what variables are needed to be tested and measured in order to achieve relevance and accuracy. (Cho, 2007; Zikmund, 1997). The development process was divided into a few steps and followed the study objectives accordingly, in order to to facilitate the task and subsequent processing of the data, moreover, to achieve and maintain the respondent’s involvement (Aaker et al, 2007; Miller and Read, 1998). In order to minimize the potential errors during the research, the questionnaires were designed by following the outlined framework done by Malhotra (1999): 1) The questionnaires should specify the information that is needed in the research; 2) The type of interviewing method and content of the individual question should be determined; 3) To overcome the inability or unwillingness of the respondent to answer questions should be designed; 4) The structure of the question should be decided; 5) the wordings of the question and the questions order should be determined; 6) the researcher should decide on questionnaire layout and reproduce it; and lastly 7) a questionnaire’s pre-test, revision and final version were needed. In designing questionnaires the researcher should consider defining all variables that require an answer, detail of the variables needed to be measure will be discussed in the following section. Researcher should make sure that the questionnaire can be reviewed and it answers the objectives of the research. Moreover, the questions must be clear enough to be understandable to the respondents. (Saunders et al, 2003). 5.4.6 Measurement In a lot of studies, which adopt TAM as a research model to explain customers’ acceptance of certain technologies, the Structural Equation Modelling (SEM) would be used to validate a theory using survey data. This model is effective when applied to very complex systems of relationships where there are many variables influencing many other variables (“Techniques and Tools: Structured Equation Modelling,” 2004). Most of the time the SEM modelling was adopted due to its explanatory ability, its comprehensive statistics of model testing as well as its ability to develop models that can test theories on a number of specified relations. (Cheung 2001; Cho, 2007; Rubio and Gillespie, 1995) One of the objectives in this study was to identify the relationship between a number of variables (PEOU, PU, CE, ATT and INT), therefore SEM has been selected to construct a model for this survey. This questionnaire measured five latent variables, which were taken from a number of sources, alongside with few other questions to investigate customers’ acceptance of the MyVirtualModel technology. Latent variables are sometimes known as hypothetical variables or expermental variables and they are the causes or predictors, in which the effects are being studied. In order to observe their effects, analytic type of survey like lab experiment is set up to vary these factors. (Cho, 2007; Oppenheim,1997;) 5.4.8 Procedures Before distributing the questionnaire, a pilot testing is essential, because this process make sure that the instructions, questions and answers were clear and understood. With this test researcher is able to study the reaction of the respondents and redo or reconstruct the weak parts of the questionnaire. Pilot testing serves as trial run, which allows researcher to identify potential problems in the proposed study (Saunders et al, 2003) 5.4.9 Data analysing method After gathering results in the questionnaire, data will be analysed in order to identify the reactions of the respondents. The first step of data analysis, as stated by Aaker et al. (2007), is analysing each question or measuring by itself, which can be done by tabulating the data. To assess if any association is present between two (typically) nominal variables, the data are then subjected to cross-tabulation. Primary data, based on the website survey will be analysed with quantitative approach. Analysis and cross-tabulation function can be found in the my3q online survey website. In addition to that, the statistical data, which is generated by EXCEL, was also provided by my3q.com, which enabled the researcher to draw comparative figures. 5.5 Reliability and validity for the study Norland (1990), states that reliability is referred to, as random error in measurements, it also indicates accuracy and precision of the measuring instrument. In this research, the data gathered from the questionnaire is carefully analyzed and tabulated with the use of SPSS. This process is done to make sure that the measurements were pure and concise. Moreover to make sure that same result will be obtained when the research will be repeated or duplicated. Validity, based on Norland (1990), is the amount of systematic or built-in error in measurement, which is established using a panel of experts and a field test. The validity of the result obtained from the questionnaire can also be tested with SPSS. Read More