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This paper reviews the current literature on theoretical and methodological issues in discrete choice experiments, which have been widely used in non-market value analysis, such as elicitation of residents' attitudes toward recreation or biodiversity conservation of forests.

We review the literature, and attribute the possible biases in choice experiments to theoretical and empirical aspects. Particularly, we introduce regret minimization as an alternative to random utility theory and sheds light on incentive compatibility, status quo, attributes non-attendance, cognitive load, experimental design, survey methods, estimation strategies and other issues.

The practitioners should pay attention to many issues when carrying out choice experiments in order to avoid possible biases. Many alternatives in theoretical foundations, experimental designs, estimation strategies and even explanations should be taken into account in practice in order to obtain robust results.

The paper summarizes the recent developments in methodological and empirical issues of choice experiments and points out the pitfalls and future directions both theoretically and empirically.

This study provides empirical evidence of the economic valuation of ecosystem services. It examines the willingness-to-pay (WTP) and compensating surplus (CS) in response to policy change based on focus group discussion (FGD) and survey.

A randomized conjoint analysis based experiment was conducted in seven villages of Sundarbans in Bangladesh to elicit stated preference data and measure WTP and CS. Each respondent faced three options in every choice card-two hypothetical alternatives and one status quo scheme. Four alternatives – payment for ecosystem services, storm protection, erosion control and habitat for fish breeding – are randomly and simultaneously assigned to the two alternatives.

The findings suggest that age, income, education, family size and occupational status are the influential factor to choice the relevant attributes of ecosystem services and their levels. Villagers would like to pay annually Tk. 703, Tk. 281, and Tk. 59 for lower, moderate, and higher ecosystem services. With these WTP, they get surplus Tk. 760, Tk. 138, and Tk. 346 respectively.

The lower WTP does not necessarily imply low demand for ecosystem service, as the findings from WTP illustrate potential demand for ecosystem services of Sundarbans.

The study provides an important insight into the ecosystem services and values of Sundarbans mangrove forests for welfare and can inform policy for sustainable use of resources of this forest.

There is a crucial gap in understanding what could villagers be ready for WTP for better ecosystem services of Sundarbans mangrove forest, how do payment based ecosystem services, as a proxy for the conservation of Sundarbans mangrove, and to what extent the policy can be strengthened.

This study investigates whether higher catch rates near a marine protected area (MPA), and/or in other fishing areas within a choice set, attract more fishers. A survey conducted in the fishing grounds near an MPA located in south east of Mauritius in the Indian Ocean shows concentration of fishers in regions with lower catch rates. This contrasts with the predictions of the “fishing the line” hypothesis and the ideal free distribution (IFD) that fishers are likely to be attracted near the MPA with higher resource abundance.

Using the random utility model as the framework and the random parameter logit (RPL) model, the study attempts to explain spatial behaviour of fishers. Expected catch and catch variability are modelled using the Just and Pope (JP) production function. The study also estimates effort elasticities with respect to expected catch and catch variability and simulates the relocation of effort from area closure.

The paper concludes that higher catch does attract fishers but is a partial and very restrictive explanation of fishers' behaviour. The “fishing the line” hypothesis does hold to some extent, but it should not be taken for granted that rising catch rates in adjacent waters will increase fishing pressure. The paper concludes that factors such as catch variability, distance from homeport to fishing ground, potential physical risk and attitudes towards risk of fishers affect spatial behaviour of fishers and should be considered for the placement and size of MPAs. The study also finds that the responsiveness of effort to catch rates is lowest in areas which are already heavily fished and easily accessible.

The identification of fishing areas as complements (when fishing in one area increases fishing effort in another) and substitutes is valuable information for determining the placement and size of an MPA. A larger reserve is likely to have more displacement effect in this case than a smaller one. Therefore, a small or a network of a small reserve may be appropriate. The premise to select the site and size of the reserve is to avoid overconcentration of fishers in alternative fishing areas, which can be vulnerable to excessive fishing and unintended effects from fishers.

The paper contributes to an understanding of fishing behaviour and its impact on the configuration of marine reserves. It discusses the importance of effort elasticities to determine the placement and size of an MPA. Studies on this topic are very scanty in the Indian Ocean region. It also shows the application of location choice model, the RPL model and the JP production function in the fisheries sector for a small island.

This paper aims to understand the perception of smallholder farmers on climate change, identify major livestock related climate change adaptation (CCA) strategies and their determinants in selected neighboring districts of Tigray and Amhara regions of Ethiopia.

A total of 416 household heads were involved in a questionnaire survey using a multistage sampling approach. To understand the socio-economic factors that influence farmers’ perception on climate change (CC) and/or variability, a binary logit model was used. Multinomial logit model was used to identify the determinants of smallholder farmers’ choices of adaptation strategies.

Milk reduction, weight loss, feed shortage and frequent animal disease outbreak were indicated as major impacts of CC on livestock production. About 86.2% of the farmers’ exercise CCA measures where livestock health care and management (25%), followed by livelihood diversification (21.5%) and shifting and diversification of livestock species (20.9%) were the top three adaptation measures implemented. Education, knowledge on CCA strategies, access to veterinary service and extension, market access, annual income, non-farm income, total livestock unit, sex of household head and household size were the major determinant factors to farmers’ choice of CCA.

Concerned authorities working in CC related sectors should give due attention to improve smallholder farmers’ access to extension and veterinary services, market access and climate information to enhance their adaptive capacity to CC impacts. In addition, incorporating climate change awareness trainings into the existing extension packages is crucial to enhance the awareness of farmers on climate change and implement appropriate adaptation strategies. Moreover, it is very essential to provide appropriate herd management and marketing strategy based on the production system to avoid the significant price reduction during drought periods.

Concerned authorities working in CC related sectors should give due attention to improve smallholder farmers’ access to extension and veterinary services, market access and climate information to enhance their adaptive capacity to CC impacts. In addition, incorporating climate change awareness trainings into the existing extension packages is crucial to implement appropriate adaptation strategies. Moreover, it is very essential to provide appropriate herd management and marketing strategy based on the production system to avoid the significant price reduction during drought periods.

This research is focused on smallholder crop-livestock farmers, livestock-based CCASs and presents the determinant factors to their choice of adaptation.

In recent years, climate-smart agriculture (CSA) was introduced to Vietnam to enhance farmers’ resilience and adaptation to climate change. Among the climate-smart agricultural technologies (CSATs) introduced were water-saving techniques and improved stress tolerant varieties. This study aims to examine the determinants of farmers’ adoption of these technologies and the effects of their adoption on net rice income (NRI) in three provinces as follows: Thai Binh (North), Ha Tinh (Central) and Bac Lieu (South).

Determinants of adoption of CSATs and the adoption effects on NRI are analyzed by using a multinomial endogenous switching regression framework.

The results showed that gender, age, number of family workers, climate-related factors, farm characteristics, distance to markets, access to climate information, confidence on the know-how of extension workers, membership in social/agricultural groups and attitude toward risk were the major factors affecting the decision to adopt CSATs. However, the effects of these factors on the adoption of CSATs varied across three provinces. These technologies when adopted tend to increase NRI but the increase is much greater when these are combined.

It is important to consider first the appropriateness of the CSA packages to the specific conditions of the target areas before they are promoted. It is also necessary to enhance the technical capacity of local extension workers and provide farmers more training on CSATs.

This study is the first attempt to identify key determinants of adoption of CSATs either singly or in combination and the adoption effects on NRI in Vietnam.

There is a gap in knowledge about the Gulf Cooperation Council (GCC) because most studies are undertaken in countries outside the Gulf region – such as China, India, the US and Taiwan. The stock market contains rich, valuable and considerable data, and these data need careful analysis for good decisions to be made that can lead to increases in the efficiency of a business. Data mining techniques offer data processing tools and applications used to enhance decision-maker decisions. This study aims to predict the Kuwait stock market by applying big data mining.

The methodology used is quantitative techniques, which are mathematical and statistical models that describe a various array of the relationships of variables. Quantitative methods used to predict the direction of the stock market returns by using four techniques were implemented: logistic regression, decision trees, support vector machine and random forest.

The results are all variables statistically significant at the 5% level except gold price and oil price. Also, the variables that do not have an influence on the direction of the rate of return of Boursa Kuwait are money supply and gold price, unlike the Kuwait index, which has the highest coefficient. Furthermore, the height score of the variable that affects the direction of the rate of return is the firms, and the accuracy of the overall performance of the four models is nearly 50%.

Some of the limitations identified for this study are as follows: (1) location limitation: Kuwait Stock Exchange; (2) time limitation: the amount of time available to accomplish the study, where the period was completed within the academic year 2019-2020 and the academic year 2020-2021. During 2020, the coronavirus pandemic (COVID-19), which was a major obstacle, occurred during data collection and analysis; (3) data limitation: The Kuwait Stock Exchange data were collected from May 2019 to March 2020, while the factors affecting the stock exchange data were collected in July 2020 due to the corona pandemic.

The study used new titles, variables and techniques such as using data mining to predict the Kuwait stock market. There are no adequate studies that predict the stock market by data mining in the GCC, especially in Kuwait. There is a gap in knowledge in the GCC as most studies are in foreign countries, such as China, India, the US and Taiwan.