There are two main sources of data these being: novel data which is primary data obtained through the use of surveys, observations and experiments, and secondary data which already exists in the public domain, such as “books, documents for example, published statistics, annual reports and accounts of companies” (Hussey and Hussey, 1997:149). Within these two types, there are also differences between data on the grounds of their nature, i.e., whether they are quantitative or qualitative.
68 4.7.1 Secondary Data
All sources of information that are available before a research study is undertaken, fall in the category of secondary data. Such data is essential as background information in all positivistic research since it is needed as a basis from which to develop hypotheses for testing. Saunders et al. (2012:83) mention that “secondary literature sources such as books and journals are the subsequent publication of primary literature. These publications are aimed at a wider audience. They are easier to locate than primary literature as they are better covered by the tertiary literature”. Sekaran (2003:63) cites more sources, saying that “secondary data can be extracted from various sources, including books and periodicals, government publications and information sources, the media, census, stock market reports, and mechanised and electronic information of all kinds such as the bar code, scanner data, and the Internet”.
In the current study, secondary data are obtained by reviewing published material in books, research conference papers, and articles related to online shopping technology, B2C e- commerce in general, and in Saudi Arabia in particular.
4.7.2 Primary Data
Primary data is information that is collected directly by the researcher through working in the field and either observing, asking questions, or conducting experimentation. That data can be either quantitative or qualitative and can be gained by a range of methods. What is important about primary data is that it can throw new light on a topic and add to existing published knowledge, or even help to create a new stream of literature. However, the methods by which primary data are gathered must be rigorously reported so that the readers of such data can be assured that it is a true depiction of the reality and not merely a biased interpretation by the researcher.
4.7.3 Quantitative Data
Quantitative data are in the form of numbers (Punch, 2005), and are particularly useful when a researcher wants to gather measurable information about a topic (Hancock, 1998). Collis and Hussey (2013) note that such numerical data allow questions relating to size, levels of importance, and frequency to be answered. They continue that quantitative data is collected because it is assumed to be objective in nature and allows the researcher to apply statistical tests. Essentially, quantitative approaches, which originated in the natural sciences, are now well accepted in the social sciences and are seen in the use of survey methods, laboratory
69
experimentation, and numerical methods for example, mathematical modelling (Myers, 1997).
4.7.4 Qualitative Data
Qualitative data are non-numeric and appear in the form of words, images, sounds, etc., (Oates, 2006). They arise from communicating with the subject(s) being studied, either through interviewing, observation, or case studies (Thomas et al., 1998). As noted by Hancock (1998), such data reveal information about why a phenomenon occurs, in what way it happens, and what the implications of that might be, in contrast to the ‘how many, how often, and how much’ focus of quantitative data. Qualitative data are always collected by the researcher rather than some inanimate mechanism (Cresswell, 2003), and they allow a researcher to develop a deeper and fuller understanding of the phenomenon in question (Babbie, 2004). The main characteristics of the approaches that quantitative and qualitative data serve are detailed in Table 4.3 (Collis and Hussey (2003:55).
Table 4:3: A Comparison of the Deductive and Inductive Approaches
Qualitative Quantitative
Concerned with generating theories Uses small sample
Data is rich and subjective Reliability is low
Validity is high
Generalises from one setting to another
Concerned with hypothesis testing Uses large sample
Data is highly specific Reliability is high Validity is low
Generalise from sample to population
It is clear from Table 4.3 that both types of data have their strengths and weaknesses, and as noted by Amaratunga et al. (2002), there are no ideal solutions, merely a series of compromises.
In this study, both types of data are used. Secondary data is obtained through the existing literature, and primary data is obtained via the empirical work conducted during the questionnaire survey and interview exercise, both of which are detailed in Sections 4.11-4.14 that follow. Furthermore, within the empirical work, both quantitative and qualitative data are gathered as the research objectives require the collection of fact (description) and new knowledge (exploration).
This study comprises a mixed methods approach, which as noted by Robson (2002), can bring substantial advantages. Indeed, he states that “there is no rule that says that only one
70
method must be used in an investigation … studies may combine methods producing quantitative data with others yielding qualitative data” (Robson, 2002:370). This viewpoint is echoed by Best and Kahn (2006) who stress the benefit of including both qualitative and quantitative methods in the same study, and recommend this strategy as it allows researchers to obtain more information. And increasingly, researchers in the social and human sciences are adopting mixed methods research involving the collection of qualitative and quantitative data (Creswell, 2003). A key benefit of a mixed methods approach as noted by Creswell (2009), is that the biases in one method could counteract the biases in the other, thereby providing a means to find convergence in quantitative and qualitative methods.