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The purpose of this paper is to analyse and predict the housing prices in Petaling district, Malaysia and its six sub-regions with a set of housing attributes using functional relationship model.

A new multiple unreplicated linear functional relationship model with both the response and explanatory variables are subject to errors is proposed. A total of 41,750 housing transacted records from November 2008 to February 2016 were used in this study. These data were divided into 70% training and 30% testing sets for each of the selected sub-regions. Individual housing price was regressed on nine housing attributes.

The results showed the proposed model has better fitting ability and prediction accuracy as compared to the hedonic model or multiple linear regression. The proposed model achieved at least 20% and 40% of predictions that have less than 5% and 10% deviations from the actual transacted housing prices, respectively. House buyers in these sub-regions showed similar preferences on most of the housing attributes, except for residents in Shah Alam who preferred to stay far away from shopping malls, and leasehold houses in Sri Kembangan are more valuable. From the h-nearest houses indicator, it is concluded that the housing market in Sungai Buloh is the most volatile in Petaling District.

As the data used are the actual housing transaction records in Petaling District, it represents only a segment of Malaysian urban population. The result will not be generalized to the entire Malaysian population.

This study is expected to provide insights to policymakers, property developers and investors to understand the volatility of the housing market and the influence of determinants in different sub-regions. The potential house buyers could also use the model to determine if a house is overpriced.

This study introduces measurement errors into the housing attributes to provide a more reliable analysis tool for the housing market. This study is the first housing research in Malaysia that used a large number of actual housing transaction records. Previous studies relied on small survey samples.

The purpose of this paper is to explore the role of NGOs in facilitating economic recovery to the tsunami devastated regions in Southern Thailand. This includes large international NGOs as well as small community based or local NGOs and how these organizations engage with one another as well as with government authorities and of course the local community to aid recovery. In particular, focus will be on how NGOs are able to assist local residents, especially those engaged in the informal sector in rebuilding their livelihoods in a region that has been devastated by a natural disaster.

The approach taken in the paper has concentrated on analysing the response of various NGOs as well as industry representatives and government authorities in considering how response efforts and recovery initiatives have impacted, and will continue to impact on the lives and livelihoods of those living in affected communities as rebuilding takes place.

Given that in Thailand just over 70 per cent of the population is employed in the informal sector of the economy one of the key findings of this paper is that central to economic recovery is the need for policy makers directing recovery strategies to reflect measures that are broadly supportive of the informal sector across different industries including tourism and fisheries, and which provides the basis of economic livelihood for a large proportion of the affected Thai population.

The paper shows that recovery strategies must engage with and directly involve the community to ensure long‐term economic recovery that is able to both build local resilience and provide the basis of livelihood support for the future sustainability of the local population.

The purpose of this paper is to use Group Method of Data Handling (GMDH)-type artificial neural network to model the affecting factors of housing price in Isfahan city housing market.

This paper presents an accurate model based on GMDH approach to describing connection between housing price and considered affecting factors in case study of Isfahan city based on trusted data that have been collected from 1995 to 2017 for every six months. The accuracy of the model has been evaluated by mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE) in this case.

Due to the obtained value of MAPE, RMSE and MAE and also their interpretation, accuracy of modelling the factors affecting housing price in Isfahan city housing market using GMDH-type artificial neural network that has been conducted in this paper, is acceptable.

Due to limitation of reliable data availability about affecting factors, selected period is from 1995 to 2017. Accessing to longer periods of reliable data can improve the accuracy of the model.

The key point of this research is reaching to a mathematical formula that accurately shows the relationships between housing price in Isfahan city and effective factors. The simplified formula can help users to use it easily for analysing and describing the status of housing market in Isfahan city of Iran.

This study aims to conduct the domain mapping of consumer behaviour research in the context of solar energy. The study can help in understanding the intellectual structure, evolution of keywords and key research producers (at the author, institutional and source level) related to the domain of solar energy consumer research.

This study uses R-studios’ bibliometrix package for analysing the bibliographical data collected from the Scopus database. Analysis has been conducted at the descriptive level (summary, author, institution and source) and analytical level (co-citation analysis, co-occurrence analysis, thematic maps and historiography).

This study finds out the most relevant authors, institutions and sources using criteria such as production, citations and H-index. Relevant research clusters have been identified using the clustering of authors, co-citations and keywords. Thematic mapping has identified the basic and motor themes. Historical citation analysis shows the direct linkage of previous studies. Overall, this study reports the most relevant bibliometric indicators in the domain of solar energy consumer research.

Identified patterns can help policymakers, business experts, social marketers and energy conservation organisations to study consumer behaviour.

Thiis bibliometric study can effectively assess sustainable development goals and suggest improved action plans.

This study examined bibliometric analysis in solar energy products (SEPs), recognised varied domains of research work on consumers’ intention to purchase solar household products and mapped them into six groups. This study provides an overview of 40 years of research on consumer behaviour towards SEPs and discusses its findings to identify the research gap.

The present study identifies the factors that impact behavioral intentions to adopt solar water heaters (SWHs) and examines their relationship with behavioral intentions using an extended “Unified Theory of Acceptance and Use of Technology” (UTAUT) model.

The study used a primary survey to collect data from 423 respondents across seven Indian states selected through purposive sampling. The collected data was analyzed using IBM SPSS software and “Structural Equation Modeling” (SEM) was performed using SmartPLS 3.5.5.

The results suggest that social influence is the most significant factor affecting SWH adoption, followed by effort, performance expectancy and facilitating conditions. The perceived cost negatively affects behavioral intentions and social influence on behavioral intentions is partially mediated by facilitating conditions. People prefer SWHs if they are easy to install and compatible with other home appliances. Positive perception of friends and family, easy access and government incentives contribute to SWH adoption.

SWH adoption can be promoted by designing sector-specific programs and improving ease of installation, operation, maintenance and after-sale services.

This study explores the behavioral intentions of individuals in India to adopt SWHs. India is a developing tropical country with a high potential for SWH adoption but has not received much attention. Further, the research integrates the perceived cost construct in the UTAUT model and examines the partial mediation impact of facilitating conditions to improve the model’s comprehensibility.

The adoption of residential rooftop solar panel systems (SPS) in India is at a nascent stage. Therefore, this study aimed to examine the factors affecting consumers’ intention to purchase SPS by expanding the theory of planned behavior (TPB) with three environmental psychology factors. The study was targeted at potential users’ intention to purchase SPS, thus it further explored the moderating role of perceived government subsidy policy (PGSP) in determining consumers’ purchase intention of SPS.

Using G*power software, the minimum sample size of 189 was calculated; accordingly, 292 valid responses were gathered from potential users of SPS from three Indian states, namely Rajasthan, Punjab and Haryana, via an online questionnaire survey with the help of purposive sampling method. Structural equation modeling technique of partial least squares was employed to analyze the data.

Results demonstrated that attitude, subjective norms, perceived behavioral control, perceived consumer effectiveness (PCE) and PGSP significantly influence purchase intention of SPS. Green trust and green self-identity did not influence the purchase intention of SPS. Further, PGSP strengthens the effect of attitude, green trust, PCE on purchase intention of SPS while it weakens the effect of subjective norms on purchase intention of SPS.

This study contributes to the existing literature by integrating green trust, green self-identity, PCE and PGSP into the TPB model to better understand factors affecting consumers’ purchase intention towards SPS in India.

The study examined perceptions and beliefs that influence the intention to adopt solar energy solutions in the Zambian Housing Sector. This is important because empirical evidence for measures aimed at improving the adoption of solar energy solutions with SSA in general or a Zambian context, in particular, are largely missing from the literature.

Hierarchical multiple linear regression was used to analyse quantitative data collected through an online questionnaire survey. A total of 947 valid responses were obtained from a convenient sample of household heads.

The results show that attitude towards solar energy solutions, subjective norms, perceived benefits, perceived trust, knowledge about solar energy solutions, load-shedding and social norms, in that order of magnitude, influence the intention to adopt solar energy solutions. Perceived behavioural control, perceived risk and perceived cost did not influence the intention to adopt solar energy solutions.

The results provide empirical evidence of important factors to drive the adoption of solar energy solutions in Zambia. The results further show that knowledge about available solar energy solutions, rather than general knowledge about renewable energy, influence the adoption intention of solar energy solutions.

This study examined the factors that influence households’ intention to adopt solar energy solutions in Zambia. This, in view of low adoption rates of solar energy solutions even in the wake of a widespread electricity power generation deficit across sub-Sahara Africa (SSA) has plagued the region with daily electricity load shedding lasting several hours at a time. Given the vast potential for solar energy generation in the region, solar energy solutions have become an attractive option to grid-based electricity, and many households have intentions of adopting these solutions.

Through the lens of the theory of planned behaviour (TPB), the study surveyed adult household members in Zambia who contributed towards the household’s income. The participants were selected using the snowballing technique, which yielded a sample of 961 respondents. The results were analysed using structural equation modelling.

The results show that attitude, trust, benefits and subjective norms influence the intention to adopt solar energy solutions. Trust and benefits also influence the intention to adopt solar energy solutions indirectly through attitude. Therefore, measures aimed at increasing the adoption of solar energy solutions should focus on improving the attitude, perceived benefits, trust in the solutions and consider subjective norms.

The findings add to the understanding of the factors that influence the intention to adopt solar energy solutions in Zambia. Therefore, the findings can be used to inform measures aimed at improving solar energy uptake in Zambia. The study also reports on the previously unreported mediating role of attitude towards solar energy solution on the associations between perceived benefits and trust with solar energy solutions adoption intention.

The purpose of this paper is to identify the fundamentals of a performance measurement system (PMS) as discussed in the literature for the past 32 years in an attempt to provide a research agenda (RA) for future research.

The paper uses a systematic review of the business, public and non-profit sector literature in examining what constitutes the fundamentals of PMS, and how these fundamentals have influenced the use of data (especially on non-financial data), development of measuring methods, measuring attributes and measuring process.

The paper finds that there are a small number of articles providing that can be considered to have provided substantial discussion of the fundamentals of PMS. While there is no consensus on what constitute the fundamentals of PMS, using content analysis, citation analysis and on the strict criteria of necessary and/or sufficient for the existence of a PMS, this paper managed to characterize the fundamentals into six categories. This paper found that the field of PMS has not change much during the past 30 or more years, and there remains various pragmatic and research gaps that need to be addressed.

The results, outcomes, and analysis of this paper have both practical and academic implications. The gaps and recommendations for future research is consolidated into a RA that provides practitioners to evaluate existing PMS, avoid issues and seek ways to develop a conceptual (theoretical) PMS that is of greater practical significance.

The results of this study contribute toward providing an update of the current state of development and research into PMS; and managed to identify existing practical issues and research gaps of PMS, and provided a RA on which ongoing and future research efforts on this topic can be built upon.