Evaluation of equity in informal land development systems in two Nigerian cities

The informal land development system in Sub-Saharan Africa (SSA) is perceived to promote equity and could be leveraged to support sustainable urban development and management. However, scanty empirical evidence exists on the extent of the system’s provision of equity to support policy formulation and practice in the region. Based on stakeholder workshops, focus group discussions and questionnaire surveys, this study analyses the system’s provision of equity in Nigeria. The study finds all categories of people undertake informal developments. Consistent with literature, this finding reflects wide patronage of the informal land development system and its relevance. Nevertheless, contrary to the existing perception, the system’s provision of equity is low. The study recommends for the institution of pro-poor and gender sensitive land development and management policies and programmes to increase the levels of equity to support the achievement of the country’s sustainable urban development and management agenda

A rough set-based association rule approach implemented on exploring beverages product spectrum

[[abstract]]When items are classified according to whether they have more or less of a characteristic, the scale used is referred to as an ordinal scale. The main characteristic of the ordinal scale is that the categories have a logical or ordered relationship to each other. Thus, the ordinal scale data processing is very common in marketing, satisfaction and attitudinal research. This study proposes a new data mining method, using a rough set-based association rule, to analyze ordinal scale data, which has the ability to handle uncertainty in the data classification/sorting process. The induction of rough-set rules is presented as method of dealing with data uncertainty, while creating predictive if—then rules that generalize data values, for the beverage market in Taiwan. Empirical evaluation reveals that the proposed Rough Set Associational Rule (RSAR), combined with rough set theory, is superior to existing methods of data classification and can more effectively address the problems associated with ordinal scale data, for exploration of a beverage product spectrum.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

An information theoretic measure for the evaluation of ordinal scale data

This article describes a new measure of dispersion as an indication of consensus and dissention. Building on the generally accepted Shannon entropy, this measure utilizes a probability distribution and the ordered ranking of categories in an ordinal scale distribution to yield a value confined to the unit interval. Unlike other measures that need to be normalized, this measure is always in the interval 0 to 1. The measure is typically applied to the Likert scale to determine degrees of agreement among ordinal-ranked categories when one is dealing with data collection and analysis, although other scales are possible. Using this measure, investigators can easily determine the proximity of ordinal data to consensus (agreement) or dissention. Consensus and dissention are defined relative to the degree of proximity of values constituting a frequency distribution on the ordinal scale measure. The authors identify a set of criteria that a measure must satisfy in order to be an acceptable indicator of consensus and show how the consensus measure satisfies all the criteria. Copyright 2006 Psychonomic Society, Inc