Factors Influencing Willingness to Pay for Improved Urban Services in Selected Slum Communities: Empirical Evidence From Lagos Megacity

Elias, P ; Fasona, M ; Babatola, O ; Omojola, A (2017-09)

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The diminishing resource-capacities of governments for intervention-cum-development purposes vis-à-vis the threats of exacerbating degeneration of existing slums, driven by uncontrollable influx of immigrants, motivated this research. It analyses the factors of willingness to contribute diversely to improve urban service provision in selected slum communities of Lagos Megacity. Cluster sampling technique was used to identify groups of households in three communities namely Orile-Agege, Bariga and Itire-Ijesha with homogeneous socioeconomic conditions. Altogether, 1,118 households were sampled for the social survey. Descriptive statistics were employed to characterize household-heads’ personal attributes and social assets while it employed the logit regression to model the factors influencing willingness to make supplementary contributions. Nine factors, namely age, gender, employment, tenure, monthly income, and four others, were hypothesized as showing no significant influence on each of the three-fold dimensions of willingness to contribute to improving urban services. The findings show that while three factors – age, occupation and monthly income show statistical significance in the model on financial contribution; the two other models, namely willingness to volunteer personal labour and the willingness to volunteer professional experience, exhibited more inclusive number of significant variables. Conclusively, the critical relevance of monthly-income in the willingness model underscores the importance of strategizing to enhance slum-dwellers’ income-earning capacity to improve on the quantum of the internally-sourced intervention resources. Notwithstanding, further researches employing more variables and larger populations will provide more clues on the interactions among the hypothesized variables in order to guarantee a better policy-application of the obtained results.