Accurate information is vital in decision making. In poverty study, inaccurate, dishonest, incomplete, and misleading information especially related to income and wealth, disrupted the effectiveness of the analysis and the purpose the research. As a result, programs, strategies, and solutions implemented using the data to resolve problems and eradicate poverty will not be effective because it might not accurately reach authentic poor and extremely poor targeted groups. Therefore, researchers and enumerators must ensure the data is of high quality, well accurate and effective to prevent wrong decision making, including unethical behaviour and improper distribution of government grants and incentives. This study aims to investigate the issues and challenges in obtaining accurate, reliable, and quality livelihood and wealth data across B40 household in one district in Kedah, Malaysia. This data is important for the government to strategize the best way in helping them to improve their livelihood and reduce inequality of wealth. This study employed a qualitative research design and multi-method data collection including survey, physical observation, interview, and documents review. The respondents were heads and members of the household of B40 groups in this district. The data was analysed using a thematic analysis technique to transform the data into useful knowledge for strategies development. The main findings show that individual or household tend to provide incomplete, untrue, and false information about their income and wealth because they are worried it will have negative effects on them such as losing the various government assistance and incentives they receive and enjoy and increase their taxable income. In addition, trust and confidentiality and privacy of personal data are also the issues. This study is significance in highlighting the accuracy issue of the information which researchers, government and agencies who are interested in getting the data need to consider and find ways to resolve. Consequently, accurate and effective poverty data will enable government to develop appropriate poverty eradication policy as well as proper distribution of national wealth ecosystem in realizing Shared Prosperity Vision 2030, sustainability livelihood agenda; reach a high-income nation; and improve quality of live; consistent with SDG1 (No poverty).
Adato, M., Carter, M. R., & May, J. (2006). Exploring poverty traps and social exclusion in South Africa using qualitative and quantitative data. The Journal of Development Studies, 42(2), 226-247.
Alcock, P. (1997). Understanding poverty. Macmillan International Higher Education.
Baigent, C., Harrell, F. E., Buyse, M., Emberson, J. R., & Altman, D. G. (2008). Ensuring trial validity by data quality assurance and diversification of monitoring methods. Clinical trials, 5(1), 49-55.
Banting, K. G. (1979). Poverty and educational priority. In Poverty, Politics and Policy (pp. 109-138). Palgrave Macmillan, London.
Bentley, P. J., & Meek, V. L. (2018). Development and future directions of higher degree research training in Australia. In Doctoral education for the knowledge society (pp. 123-146). Springe
Canivez, G. L. (2019). Evidence-based assessment for school psychology: Research, training, and clinical practice. Contemporary School Psychology, 23(2), 194-200.
Dawood, S. R. S., Ghazali, S., & Samat, N. (2019). Digital divide and poverty eradication in the rural region of the northern Peninsular Malaysia. The Indonesian Journal of Geography, 51(2), 67-77.
Ensor, J. E., Wennstrom, P., Bhatterai, A., Nightingale, A. J., Eriksen, S., & Sillmann, J. (2019). Asking the right questions in adaptation research and practice: Seeing beyond climate impacts in rural Nepal. Environmental science & policy, 94, 227-236.
Fox, W., & Bayat, M. S. (2008). A guide to managing research. Juta and company Ltd.
Greville, H., Haynes, E., Kagie, R., & Thompson, S. C. (2019). ‘It shouldn’t be this hard’: exploring the challenges of rural health research. International journal of environmental research and public health, 16(23), 4643.
Heslop, C., Burns, S., & Lobo, R. (2018). Managing qualitative research as insider-research in small rural communities. Rural and Remote Health, 18(3), 250-254.
Islam, M. (2003). Identifying Data Collection Problem in a Rural Setting and Working Towards Technology-based Solutions (Doctoral dissertation, Centre for the Public Health).
Jann, B., Krumpal, I., & Wolter, F. (2019). Social desirability bias in surveys—Collecting and analyzing sensitive data [Special Issue of Methods, Data, Analyses (MDA)].
Jason, H. (2007). Understanding rural entrepreneurs at the county level: data challenge. In Frameworks for Entrepreneurship Research in Food, Agricultural and Rural Development Workshop. Federal Reserve Bank of Kansas City.
Kenneth, S., Ahmad, A., & Zainab. (2021). Multidimensional Poverty in Malaysia : Improving Measurement and Policies in the 2020s. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/36392 License: CC BY 3.0 IGO.”
Lister, R., Beresford, P., Green, D., & Woodward, K. (2019). Where are'the Poor'in the Future of Poverty Research?. In Researching poverty (pp. 284-304). Routledge.
Meehan-Andrews, T., Jones, J., & Humphreys, J. (2006). How do we Canvass Rural Consumer Viewpoints for Health Care Planning and Quality Assurance? Methodological Considerations for Data Collection. Australian Journal of Primary Health, 12(3), 72-77.
Merriam, S. B., & Simpson, E. L. (1995). A guide to research for educators and trainers of adults. Krieger Publishing Co., PO Box 9542, Melbourne, FL 32902-9542.
Moon, K., & Blackman, D. (2014). A guide to understanding social science research for natural scientists. Conservation biology, 28(5), 1167-1177.
Oquendo, M. A., Duarte, C., Gouveia, L., Mari, J. J., Mello, M. F., Audet, C. M., & Wainberg, M. L. (2018). Building capacity for global mental health research: challenges to balancing clinical and research training. The Lancet. Psychiatry, 5(8), 612.
Strijker, D., Bosworth, G., & Bouter, G. (2020). Research methods in rural studies: Qualitative, quantitative and mixed methods. Journal of Rural Studies, 78, 262-270.
Sweeney, S., Vassall, A., Foster, N., Simms, V., Ilboudo, P., Kimaro, G., & Guinness, L. (2016). Methodological issues to consider when collecting data to estimate poverty impact in economic evaluations in low?income and middle?income countries. Health Economics, 25, 42-52.
Tait, H., & Williamson, A. (2019). A literature review of knowledge translation and partnership research training programs for health researchers. Health Research Policy and Systems, 17(1), 1-14.
Zhou, Y., & Liu, Y. (2019). The geography of poverty: Review and research prospects. Journal of Rural Studies.
In-Text Citation: (Ali et al., 2022)
To Cite this Article: Ali, A., Ahmad, W. N. W., Mohamad, A. M., Zaki, A. M., & Hidayah, N. N. (2022). Issues, Challenges and Strategies in Obtaining Reliable and Quality Livelihood and Wealth Data Across B40 Community in Malaysia. International Journal of Academic Research in Business and Social Sciences, 12(8), 859– 871.
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