DATA COLLECTION PROCESS AND ANALYSIS

The data collection process and analysis method - used for this study - are explained in the following sections.

5.7.1 Data collection process

After the necessary adjustments of the instruments for data collection - as a result of the pilot study - had been made and approved by the promoters, the data collection process commenced. The researcher submitted a formal request to the Executive Secretary of Uganda Council of Science and Technology – the statutory body concern with research in the country - for permission to conduct the research and introductory letters to the Districts Administrative Officers of the Ajumani, Gulu, Kotido, Lira and Nebbi districts were secured. After permission had been granted and introductory letters issued by the Uganda Council of Science and Technology, the data collection started in the Gulu district where the local promoter went into the field with the researcher. In all the districts covered, research assistants were first trained in the data collection techniques. Research assistants administered the questionnaires to the SMEs and to the information providers. In order to ensure consistency and that the challenges were addressed, the researcher met with the research assistants every evening and formulated strategies for challenges faced during the day. The researcher interviewed the business policy makers. After the Gulu district, the data collection process proceeded in the Lira district, then the Kotido and Nebbi districts and, finally, in the Ajumani district. On average, the data collection process took six months and was conducted in 2005.

5.7.2 Data analysis

In survey research, content analysis and descriptive statistics are used for data analysis (Edwards and Talbot 1999:115). The way the researcher organised - and analysed - the data from the research instruments depended on the questions the researcher tried to address in the study. The coded responses from the questionnaires were analysed, quantitatively, using Epi Info and SPSS software. After the questionnaires were returned,

the researcher edited all the questionnaires - district by district - to ensure legibility and accuracy and, thereafter, handed them over to the statistician from the Institute of Statistics, Makerere University, who created a data entry screen using Epi Info. A data entry clerk was employed to enter the data. To ensure that the data entered was free of errors, the researcher - together with the statistician - cleaned the database before the data was transferred to SPSS for analysis into frequencies, percentages, pie charts and bar graphs. The researcher collaborated with the statistician and was involved throughout the data analysis process. The involvement was because the researcher did not want a mistake during any step of data analysis process to ruin the study. Neuman (1997:297) observes that a researcher who has a perfect sample, perfect measures and no errors in gathering data but who makes errors in the coding process - or in entering data into the computer - can ruin a whole research project. This is the kind situation the researcher wanted to avoid.

Data from interviews [unstructured questions] was analysed, using the content analysis method. Content analysis is the systematic, quantitative analysis of communication content - including verbal, visual, print, and electronic communication. In content analysis, “a researcher uses objective and systematic counting and recording procedures to produce a quantitative description of the symbolic content in a text” (Neuman 2003:311). In applying content analysis, the researcher identified the themes of the research - based on the objectives of the study - and classified the responses from each of the respondent, accordingly, so as to come up with a quantitative value that would facilitate decision-making. Edwards and Talbot (1999) argue that irrespective of the research design and the methods utilised, a stage of coding and classification of information must be undertaken. Classification simplified the task of obtaining a quantitative value from what policy makers said about the business information needs and from the problems the SMEs face in accessing business information - for a viable business information design.

5.7.3 Time frame and resources

Because it is impossible to anticipate all the potential stumbling blocks when doing research, one has to make time allowances for the unexpected that might intervene (Mouton 2001). The time frame for the processes involved in this study - given in Appendix VI - was modified as the research processes preceded. The study used 6 research assistants. Two research assistants were used in the Gulu district while the Lira, Kotido, Nebbi and Ajumani districts had one research assistant each. Carnegie - through the Makerere University Postgraduate and Research Committee - provided the research funds.

5.7.4 Problems encountered

Generally, the study was conducted without any major problems. Some of the practical problems encountered during the study include the ones described below.

5.7.4.1 Insecurity

Insecurity - due to the Lord Resistance Army (LRA) war on the way to the Ajumani district from the Gulu district and cattle rustling - was a great hindrance, especially in the Kotido district. This resulted in a lot of suspicion among the respondents. Because the research assistants were widely known among the business community, the respondents later developed a trust and responded, appropriately. It should be noted that though insecurity was a problem in the Kotido district, it was beneficial for the research in the Gulu district. Because of the war in most parts of the Gulu district, most business enterprises were concentrated in Gulu town. This made data collection easier.

5.7.4.2 Research fatigue

The different problems - experienced by northern Uganda - have resulted in many research projects being carried out in the region. This has created resentment among the population and a reluctance to participate. Some people thought that they did not benefit from the research carried out and there was, therefore, no need to participate in the study. Since the researcher had anticipated this – having been warned by an NGO researcher and from experience in the pilot study - the choice of social and known research

assistants among the business community was considered crucial. This worked perfectly well because there was good cooperation from the respondents.

5.7.4.3 Demand for money

There is a culture that is developing within the Ugandan society of demanding payment for whatever one does. Many respondents, such as the SMEs, demanded money to answer the questionnaires. Though in some cases a “reward” - in the form of soft drinks - was given to induce participation, much of the convincing was due to the competence and good social characters of the research assistants who were employed. It is not clear as to whether this was happening due to the high level of poverty existing in the area or to the commercialisation of politics in Uganda - where many people think they should be given reward for participation.