Factors Influencing Consumption Behaviour towards Aquatic Food among Asian Consumers: A Systematic Scoping Review.

Asia accounts for over 70% of total global aquatic food consumption, but aquatic food consumption behaviours and attitudes among Asian consumers are poorly documented and understood. This paper synthesises literature on factors influencing aquatic food consumption behaviour in Asia and the potential to support transitions toward more sustainable food consumption patterns. We identified 113 studies for inclusion in a scoping review, and identified five clusters of publications: (1) product attributes, availability, and accessibility (24% of publications); (2) willingness to pay for aquatic foods (25%); (3) psychosocial factors (e.g., attitudes and subjective norms) (17%); (4) sociodemographic and lifestyle factors (21%); and (5) miscellaneous factors, including food safety and social status (13%). This study indicates that multiple interacting factors influence aquatic food consumption behaviours among Asian consumers, among which price is central. Knowledge of, and attitudes toward, the perceived quality and safety of aquatic foods were identified as important but were mediated by household characteristics. Sustainable production practices, country of origin, and ecolabels were found to be less influential on consumption behaviour. We found that improving consumers' knowledge and attitudes about the quality and safety of aquatic foods might positively influence aquatic food consumption behaviour. Future multidisciplinary research is required to better understand interactions among the multiple factors that influence Asian consumers' aquatic food consumption behaviour.

A simple satisficing model.

Economic theory is built on the assumption that people are omniscient utility maximizers. In reality, this is unlikely to be true and often people lack information about all alternatives that are available to them; either because the information is unavailable or that the cost of searching for and evaluating that information is high. In this paper, we develop a simple and tractable model that captures satisficing behavior. We show that the model can retrieve consistent parameters under a large range of experimental conditions. We test our model on synthetic data and present an empirical application. We discuss the implications of our results for the use of satisficing choice models in explaining choice.

The value of blue-space recreation and perceived water quality across Europe: A contingent behaviour study.

This study estimates the value of recreational visits to blue-space sites across 14 EU Member States, representing 78% of the Union's population. Across all countries surveyed, respondents made an average of 47 blue-space visits per person per year. Employing travel cost and contingent behaviour methods, the value of a visit is estimated at €41.32 which adds up to a recreational value of €631bn per year for the total adult population surveyed. Using the Bathing Water Directive's water quality designation, the analysis shows that a one-level improvement in water quality leads to 3.13 more visits (+6.67%), whereas a one-level deterioration leads to 9.77 fewer annual visits (-20.83%). This study provides valuations of benefits of recreation and changes of recreational values due to changes in surface water quality, which can be compared to the implementation and monitoring costs of efforts under the EU's Bathing Water, Water Framework and Marine Strategy Framework Directives.

Including Opt-Out Options in Discrete Choice Experiments: Issues to Consider.

Providing an opt-out alternative in discrete choice experiments can often be considered to be important for presenting real-life choice situations in different contexts, including health. However, insufficient attention has been given to how best to address choice behaviours relating to this opt-out alternative when modelling discrete choice experiments, particularly in health studies. The objective of this paper is to demonstrate how to account for different opt-out effects in choice models. We aim to contribute to a better understanding of how to model opt-out choices and show the consequences of addressing the effects in an incorrect fashion. We present our code written in the R statistical language so that others can explore these issues in their own data. In this practical guideline, we generate synthetic data on medication choice and use Monte Carlo simulation. We consider three different definitions for the opt-out alternative and four candidate models for each definition. We apply a frequentist-based multimodel inference approach and use performance indicators to assess the relative suitability of each candidate model in a range of settings. We show that misspecifying the opt-out effect has repercussions for marginal willingness to pay estimation and the forecasting of market shares. Our findings also suggest a number of key recommendations for DCE practitioners interested in exploring these issues. There is no unique best way to analyse data collected from discrete choice experiments. Researchers should consider several models so that the relative support for different hypotheses of opt-out effects can be explored.

The Determinants of Brownfields Redevelopment in England.

This paper uses discrete choice models, supported by GIS data, to analyse the National Land Use Database, a register of more than 21,000 English brownfields-previously used sites with or without contamination that are currently unused or underused. Using spatial discrete choice models, including the first application of a spatial probit latent class model with class-specific neighbourhood effects, we find evidence of large local differences in the determinants of brownfields redevelopment in England and that the reuse decisions of adjacent sites affect the reuse of a site. We also find that sites with a history of industrial activities, large sites, and sites that are located in the poorest and bleakest areas of cities and regions of England are more difficult to redevelop. In particular, we find that the probability of reusing a brownfield increases by up to 8.5 % for a site privately owned compared to a site publicly owned and between 15 and 30 % if a site is located in London compared to the North West of England. We suggest that local tailored policies are more suitable than regional or national policies to boost the reuse of brownfield sites.

Preferences for public involvement in health service decisions: a comparison between best-worst scaling and trio-wise stated preference elicitation techniques.

Stated preference elicitation techniques, such as discrete choice experiments and best-worst scaling, are now widely used in health research to explore the public's choices and preferences. In this paper, we propose an alternative stated preference elicitation technique, which we refer to as 'trio-wise'. We explain this new technique, its relative advantages, modeling framework, and how it compares to the best-worst scaling method. To better illustrate the differences and similarities, we utilize best-worst scaling Case 2, where individuals make best and worst (most and least) choices for the attribute levels that describe a single profile. We demonstrate this new preference elicitation technique using an empirical case study that explores preferences among the general public for ways to involve them in decisions concerning the health care system. Our findings show that the best-worst scaling and trio-wise preference elicitation techniques both retrieve similar preferences. However, the capability of our trio-wise method to provide additional information on the strength of rank preferences and its ability to accommodate indifferent preferences lead us to prefer it over the standard best-worst scaling technique.

Accounting for Attribute-Level Non-Attendance in a Health Choice Experiment: Does it Matter?

An extensive literature has established that it is common for respondents to ignore attributes of the alternatives within choice experiments. In most of the studies on attribute non-attendance, it is assumed that respondents consciously (or unconsciously) ignore one or more attributes of the alternatives, regardless of their levels. In this paper, we present a new line of enquiry and approach for modelling non-attendance in the context of investigating preferences for health service innovations. This approach recognises that non-attendance may not just be associated with attributes but may also apply to the attribute's levels. Our results show that respondents process each level of an attribute differently: while attending to the attribute, they ignore a subset of the attribute's levels. In such cases, the usual approach of assuming that respondents either attend to the attribute or not, irrespective of its levels, is erroneous and could lead to misguided policy recommendations. Our results indicate that allowing for attribute-level non-attendance leads to substantial improvements in the model fit and has an impact on estimated marginal willingness to pay and choice predictions.

Elimination and selection by aspects in health choice experiments: prioritising health service innovations.

Priorities for public health innovations are typically not considered equally by all members of the public. When faced with a choice between various innovation options, it is, therefore, possible that some respondents eliminate and/or select innovations based on certain characteristics. This paper proposes a flexible method for exploring and accommodating situations where respondents exhibit such behaviours, whilst addressing preference heterogeneity. We present an empirical case study on the public's preferences for health service innovations. We show that allowing for elimination-by-aspects and/or selection-by-aspects behavioural rules leads to substantial improvements in model fit and, importantly, has implications for willingness to pay estimates and scenario analysis.

Examining labelling effects within discrete choice experiments: an application to recreational site choice.

Data from a discrete choice experiment aimed at eliciting the demand for recreational walking trails on farmland in Ireland is used to explore whether some respondents reach their choices solely on the basis of the alternative's label. To investigate this, this paper exploits a discrete mixtures approach that also encompasses continuous distributions to reflect the heterogeneity in preferences for the attributes and alternatives. We find evidence that a proportion of respondents choose on the basis of the label only and that differences emerge between rural and urban respondents. We provide a number of alternative explanations for why this may occur. Results highlight a large impact on welfare measures when we accommodate the fact that a proportion of respondents choose on the basis of the label only.

Public perceptions of coronary events risk factors: a discrete choice experiment.

OBJECTIVES: To assess public perceptions of coronary heart disease (CHD) risk factors. DESIGN: Discrete choice experiment questionnaire. SETTING: Six provincial centres in Northern Ireland. PARTICIPANTS: 1000 adults of the general public in Northern Ireland. PRIMARY AND SECONDARY OUTCOMES: The general public's perception of CHD risk factors. The effect of having risk factor(s) on that perception. RESULTS: Two multinomial logit models were created. One was a basic model (no heterogeneity permitted), while the other permitted heterogeneity based on respondents' characteristics. In both models individuals with very high cholesterol were perceived to be at the highest risk of having a coronary event. Respondents who reported having high cholesterol perceived the risk contribution of very high cholesterol to be greater than those who reported having normal cholesterol. Similar findings were observed with blood pressure and smoking. Respondents who were male and older perceived the contribution of age and gender to be lower than respondents who were female and younger. CONCLUSIONS: Respondents with different risk factors perceived such factors differently. These divergent perceptions of CHD risk factors could be a barrier to behavioural change. This brings into focus the need for more tailored health promotion campaigns to tackle CHD.