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The purpose of this paper is to assess policy and management of hypertension and diabetes in Ghana.

The authors conducted 26 key informant interviews with policy makers, payers, providers and participants from advocacy groups associated with the management of hypertension and diabetes both at national and district levels in Ghana; conducted focus group discussions with a total of 18 hypertensive and diabetic patients; and analyzed documentation detailing activities that have been undertaken in response to the management of hypertension and diabetes in Ghana. The authors then conducted a content analysis after combining the three sources of information.

Using a stepwise policy process, the Ghanaian health sector has developed overarching policies and strategies on management of diabetes, hypertension, other non-communicable diseases, tobacco, alcohol and nutrition-related issues. Availability of funds and over-concentration on communicable diseases are the main barriers to the implementation of policies. Besides, response of the health sector to address the problems of hypertension and diabetes is focused more on clinical management than prevention; while the structures and processes to manage diabetes and hypertension is available at all levels of service delivery, more needs to be done on preventive aspects.

This is the first study in Ghana to combine individual interviews, focus groups and document analysis to review policy development, implementation and response activities on the management of hypertension and diabetes. The authors believe that the evidence from this research will inform future policy initiatives on hypertension and diabetes management in Ghana.

The purpose of this paper is to examine factors that explain dropout of children from primary schools in Lohit district of Arunachal Pradesh, India.

The field survey was carried out in two phases, one, during January to April of 2010 and two, between August and November of 2011. The entire research work is based on stratified random sampling. The population in Lohit district is a set of tribal and non-tribal (mostly general) people. The district has two major tribes – Mishmi and Khamti.

The authors find that children dropout of school is affected by number of factors such as earning compulsions, household work, access to school, school time not suitable and parental unawareness.

It is imperative to mention here that “earning compulsion” can be described only as a derivative of the major problem of abject poverty.

By highlighting the role of appropriate intervention as well as incapacitation, the authors believe that the findings presented above shed light on some important factors that explain dropouts.

The evidence provided in this paper underscores the importance of social interactions in analysing individual outcomes.

The findings may have significant bearings in reducing dropout rates in India.

Existing literature offers conflicting evidence on how prior product knowledge influences amount of information search. A majority of these studies are based on variants of cost benefit frameworks where consumers engage in search until the benefits from information search exceed search costs. The purpose of this paper is to develop an expectancy theory‐based framework to model consumers' information search and its antecedents, including motivation to search as an intervening construct.

The framework is tested using data from real consumers engaged in their actual purchase decisions, in an emerging market context, using longitudinal survey research design. The data are analysed using structural equation modeling to test the hypothesized model. The model shows an acceptable fit with X2 (271, 487)=640.252, p < 0.00 and 0.95 CFI.

Results indicate that the relationship between prior product knowledge to information search is mediated by motivation to search. Prior product knowledge influences motivation to search through its influence on the consumer's perceived ability to search and his/her perceived value of additional information. Furthermore, perceived ability to search is the strongest predictor of motivation to search. The parsimony of the proposed framework in providing a simpler account of factors influencing the search process along with its managerial implications is discussed.

The findings suggest that perceived ability to search and perceived value of additional information are two important levers that managers could use for achieving desired results. Furthermore, perceived ability to search is an important mediator, which completely mediates the relationship between prior product knowledge and motivation to search. These findings also provide strong indications about the need to simplify the search process for consumers, especially in the context when novelty is predominantly marketed.

The paper introduces a motivational measure of search in the literature and shows that the motivational measure is indeed the proximal measure to other antecedent constructs compared to a behavioral measure of search. Perceived ability to search and perceived value of additional information are shown as important mediators between prior product knowledge and motivation to search.

This study aims to assess housing affordability and estimate demand using a hedonic regression model in the context of Lucknow city, India. This study assesses housing affordability by considering various housing and household-related variables. This study focuses on the impoverished urban population, as they experience the most severe housing scarcity. This study’s primary objective is to understand the demand dynamics within the market comprehensively. An understanding of housing demand can be achieved through an examination of its characteristics and components. Individuals consider the implicit values associated with various components when deciding to purchase or rent a home. The components and characteristics have been obtained from variables relating to housing and households.

A socioeconomic survey was conducted for 450 households from slums in Lucknow city. Two-stage regression models were developed for this research paper. A hedonic price index was prepared for the first model to understand the relationship between housing expenditure and various housing characteristics. The housing characteristics considered for the hedonic model are dwelling unit size, typology, condition, amenities and infrastructure. In the second stage, a regression model is created between household characteristics. The household characteristics considered for the demand estimation model are household size, age, education, social category, income, nonhousing expenditure, migration and overcrowding.

Based on the findings of regression model results, it is evident that the hedonic model is an effective tool for the estimation of housing affordability and housing demand for urban poor. Various housing and household-related variables affect housing expenditure positively or negatively. The two-stage hedonic regression model can define willingness to pay for a particular set of housing with various attributes of a particular household. The results show the significance of dwelling unit size, quality and amenities (R² > 0.9, p < 0.05) for rent/imputed rent. The demand function shows that income has a direct effect, whereas other variables have mixed effects.

This study is case-specific and uses a data set generated from a primary survey. Although household surveys for a large sample size are resource-intensive exercises, they provide an opportunity to exploit microdata for a better understanding of the complex housing situation in slums.

All the stakeholders can use the findings to create an effective housing policy. The variables that are statistically significant and have a positive relationship with housing costs should be deliberated upon to provide the basic standard of living for the urban poor. The formulation of policies should duly include the housing preferences of the economically disadvantaged population residing in slum areas.

This paper uses primary survey data (collected by the authors) to assess housing affordability for the urban poor of Lucknow city. It makes the results of the study credible and useful for further applications.

This study aims to examine the current state of academic research pertaining to the role played by artificial intelligence (AI) in the achievement of a critical sustainable development goal (SDG) – poverty alleviation and describe the field’s development by identifying themes, trends, roadblocks and promising areas for the future.

The authors analysed a corpus of 253 studies collected from the Scopus database to examine the current state of the academic literature using bibliometric methods.

This paper identifies and analyses key trends in the evolution of this domain. Further, the paper distils the extant literature to unpack the intermediary mechanisms through which AI and related technologies help tackle the critical global issue of poverty.

The corpus of literature used for the analysis is limited to English language studies from the Scopus database. The paper contributes to the extant research on AI for social good, and more broadly to the research on the value of emerging technologies such as AI.

Policymakers and government agencies will get an understanding of how technological interventions such as AI can help achieve critical SDGs such as poverty alleviation (SDG-1).

The primary focus of this paper is on the role of AI-related technological interventions to achieve a significant social objective – poverty alleviation.

To the best of the authors’ knowledge, this is the first study to conduct a comprehensive bibliometric analysis of a critical research domain such as AI and poverty alleviation.