The Research Process

In its simplest form, research can be seen as a process of discovery of new information or relationships amongst the variables considered to expand existing knowledge for some specified purpose or to solve problems which may be theoretical or practical in nature (Cavana et al., 2001; Creswell, 2003). According to Blaikie (2003) research can also be seen as a process to explore, describe, understand, explain, predict, change, evaluate and assess aspects of certain phenomena. It starts with a research problem or a practical problem which requires answering three types of questions that take a sequential order of: ‘what’, ‘why’ and ‘how’, which form the first layer in the research process or what is sometimes referred to as the research paradigm (Saunders et al., 2000). In fact, it is the platform that determines how knowledge or answers to the research problem are going to be obtained.

There are two major fields of research processes namely, positivist (scientific) and interpretive (social) research (Zikmund, 2000). Scientific research is conducted within the rules and conventions of science. It utilizes deductive reasoning through guidance of a specific theory towards achieving concrete empirically verifiable results of investigation (Saunders et al., 2000). Interpretive research is based on logic, reasoning and systematic examination of evidence. Ideally, this type of research should be capable of replication by the same or different researchers with similar results obtained (Zikmund, 2000). This research utilised the interpretive approach as an appropriate research method to tackle this research problem.

5.2.1 Selecting research design techniques

Zikmund (2000) and Blaikie (2003) state that explanatory research could take a quantitative approach; that is, gathering numerical data to ensure objective and accurate results. However, a qualitative approach, or data in words, is potentially useful to obtain more information. A common consensus has been established recently that mixed qualitative and quantitative research studies provide more robust and useful findings (Cavana et al., 2001; Creswell, 2003; Hair et al., 2006). Saunders

(2000) and Zikmund (2000) suggest that qualitative and quantitative methods could complement one another if applied efficiently, to enrich the data gathering particularly in new research areas, as is the case with this study.

For this study, which is essentially concerned with the future pattern of Oman’s sustainable economic development through the adoption of a strategy for developing a knowledge-based economy, the first step involved gathering information by holding meetings with various senior government officials, executives of leading private sector companies and relevant academics at Sultan Qaboos University. All of the above emphasized the importance of including all the relevant data and involving the main stakeholders in this process.

In addition, the knowledge economy literature also emphasises the importance of incorporating a benchmarking process through a tool known as the knowledge assessment methodology (KAM). This has been developed by the World Bank Institute to gauge a country’s readiness for a knowledge economy compared with other regions and countries (World Bank Institute, 2002; World Bank, 2004). Thus, a benchmarking process, a qualitative approach (in the form of interviews) and a quantitative approach (in the form of a questionnaire survey) were applied in the data gathering approaches with a view to producing practical and useful results. This multi-method research strategy tests the validity of measurements by means of triangulated cross-method comparisons.

Triangulation requires multiple sets of data tackling the same research question from different viewpoints (Cavana et al., 2001; Cresswell, 2003). Testing of variables by different methodologies may have important ramifications for the research problem as long as these methods are employed independently of one another, but are focused as tightly as possible upon the question being researched. Brewer and Hunter (2006) indicate that an advantage of multi-method studies is that when multiple tests are designed and performed by the same investigator in a short period of time, the same level of knowledge and skill are more likely to inform and consolidate each test. The research design of this project is summarized in Figure 5.1.

Figure 5.1: Different phases of the research methodology

Source: Adapted from Koo (2004, p. 68), modified to suit this research project.

Exploratory research was undertaken at the initial stage to crystallize problems that lead to identifying the information required for this research. In this process, the researcher consulted with academic colleagues at Victoria University in Melbourne and Sultan Qaboos University in Oman, government officials, and executives and managing directors of some grade excellent service companies in Oman, to explore issues related to this study. A thorough review of the knowledge economy literature was conducted to explore its evolvement, development and application in different

Research question Interpretive (social science) paradigm Exploratory research, descriptive research, explanatory research Research strategy Mixed methodology Data collection techniques In-depth interview of senior government officials Close-ended questionnaire to service companies Conclusion and recommendations Data analysis factor analysis

Overall data results

Literature on knowledge economy Knowledge economy four drivers Knowledge economy benchmarking

___ Shows the flow from research question to conclusion. --- Shows the use of literature, knowledge economy drivers and benchmarking to aid data collection, analysis and confirmation.

countries. A benchmarking process followed the previous two steps as recommended by the knowledge economy literature as an essential and powerful tool to unveil Oman’s knowledge economy readiness in the four main drivers relative to international, regional and some relevant countries’ levels.

A qualitative approach was also used as a subsequent step to gain insights on the issue from senior government officials whose positions qualified them to provide useful information on Oman’s economic development plans in general, and knowledge economy main drivers in particular: education and training, information and communication technologies, research and development, and government institutions that support such factors. Finally a quantitative approach was conducted to gain valuable information from targeted grade excellent service companies that could provide useful feedback and information on this new issue as main end users of knowledge economy development in Oman. This approach was part of the descriptive and explanatory approaches which try to explain, relate and find the appropriate factors or variables that would contribute to knowledge economy development.

These companies were selected according to their registration at the Oman Chamber of Commerce and Industry as of 2006. The choice was based on the anticipated valuable information they could provide in initiating knowledge economy policies in Oman. The importance of the service sector in Oman stems from the fact that it contributes more than 78 per cent of non-oil GDP and almost 60.5 per cent of overall GDP (MNE, 2006). More importantly this sector employs semi-skilled and skilled labor. For instant, about 84 per cent of the local labor force employed in commercial banks hold secondary certificates or above (Al-Lamki, 2005). Similar labor and education characteristics, but to a lesser extent, are also present in other major service sectors such as insurance, education and health care institutions (MNE, 2006). Thus, this sector has been viewed as the potential driving force of any knowledge economy quest as is the case in developed and fast growing developing countries.

A mail survey was used as a means to collect data for analysis. Statistical measures of the factorability and correlations between variables are analysed in Chapter 6 to identify factors, ranking and their relationship strength. The quantitative research approach played a major role in this research since it was used to answer questions

requiring numerical data to solve the problem. In quantitative studies, the data are transformed from words into numbers, are then subjected to different statistical manipulation, and are subsequently reported in both numbers and words (Cavana et al., 2001).

This research used factor analysis to analyse the data collected via the survey questionnaire to answer the questions proposed, to find appropriate and significantly related factors that assist in formulating a knowledge economy policy that takes into consideration all stakeholders’ ideas and concerns. As is the case with some knowledge economy data collection surveys, where some regression analyses were used such as Shapira et al. (2006) in Malaysia, this research concentrated on factor analysis. This proved to be more useful in answering the research question as Oman is yet to initiate a knowledge economy strategy. According to Chen and Gawande (2007) factor analysis is a useful tool for data reduction and provides a clearer picture of which factors act together according to their underlying dimensions. Other possible analysis techniques such as discriminate analysis and hierarchical regression analysis which were tried in this research fell short of providing useful findings due to the low and negligible correlations among the variables asdemonstrated in Chapter 6.