Bayesian Mixed Logit Model Research Articles

Exploring Co-labeling Strategies in Local Food Markets: Insights from a Choice Experiment on Southern Buyers’ Preferences for Cherry Tomatoes

Labeling strategies are often discussed in the context of local food purchase. Substantial research has been undertaken to discern buyers’ preferences for different labeling strategies associated with a production practice or a geographic location. Some studies have also emphasized the substitution or complementarity effects that may occur across these different labels. Using a large choice experiment with 1820 respondents across six US southern states, this research evaluates buyers’ preferences for co-labeling strategies, focusing on the association of a production practice and certifications (USDA Organic and Certified Naturally Grown) alongside six different production locations, ranging from local to imported sources. We focus on pint baskets of cherry tomatoes, chosen due to their popularity among purchasers of fresh produce. Based on the results provided by a Bayesian Mixed Logit model, we derived the respondent-specific posterior distribution of the partworths associated with each production location and regressed each of those against demographic indicators. Our findings highlight that most buyers substitute between USDA Organic and Certified Naturally Grown (CNG), and a minority consistently opt for the same production practice option. In addition, we underscore that price, or an indication of origin predominantly guides nearly half of buyers’ choices. We find that the premium for CNG is slightly superior to the organic one. Last, older respondents and respondents with a higher degree of education value produce grown within their state over neighboring states and more distant origins.

Preferences for Living Arrangements in Dementia: A Discrete Choice Experiment.

Dementia affects about 55 million people worldwide. Demographic change and shifting lifestyles challenge the organization of dementia care. A discrete choice experiment (DCE) was conducted to elicit preferences for living arrangements in dementia in urban and rural regions of Germany. Preliminary work included review of previous literature and focus groups. The DCE consists of seven attributes (group size, staff qualifications, organization of care, activities offered, support of religious practice, access to garden, consideration of food preferences) with three levels each. Individuals from the general population between the ages of 50 and 65years were identified through population registration offices in three rural municipalities and one urban area, and 4390 individuals were approached via postal survey. A hierarchical Bayesian mixed logit model was estimated and interactions with sociodemographic characteristics were investigated. A total of 428 and 412 questionnaires were returned by rural and urban respondents, respectively. Access to a garden was perceived as the most important attribute (average importance 36.0% in the rural sample and 33.4% in the urban sample), followed by consideration of food preferences (15.8%, 17.8%), staff qualification (14.6%, 15.3%), care organization (11.4%, 12.3%), group size (12.2%, 11.1%), and range of activities (8.0%, 10.1%). The attribute relating to religious practice was given the least importance (2.1%, 0%). Preferences vary according to gender, age, religious beliefs, experience as an informal caregiver, and migrant background. Heterogeneous preferences for living arrangements for people with dementia were identified. The expansion of concepts with access to natural environments for persons with dementia might be a viable option for the formal care market in Germany. Further research is needed to meet the challenges of setting up and designing innovative living arrangements for people with dementia. Preferences vary by gender, age, religious beliefs, experience as an informal caregiver, and migrant background.

Heterogeneity in preferences for outcomes of integrated care for persons with multiple chronic diseases: a latent class analysis of a discrete choice experiment

PurposeFor an integrated care programme to be successful, preferences of the stakeholders involved should be aligned. The aim of this study is to investigate to which extent outcomes beyond health are valued and to study the heterogeneity of preferences of those involved in integrated care.MethodsA discrete choice experiment (DCE) was conducted to elicit preferences for eight Triple Aim outcomes, i.e., physical functioning, psychological well-being, social relationships & participation, enjoyment of life, resilience, person-centeredness, continuity of care and total health and social care costs. Stakeholders were recruited among Dutch persons with multi-morbidity, informal caregivers, professionals, payers, and policymakers. A Bayesian mixed-logit model was used to analyse the data. Subsequently, a latent class analysis was performed to identify stakeholders with similar preferences.Results739 stakeholders completed the DCE. Enjoyment of life was perceived as the most important outcome (relative importance: 0.221) across stakeholders, while total health and social care costs were perceived as least important (0.063). The latent class analysis identified four classes. The first class (19.9%) put most weight on experience with care outcomes. The second class (39%) favoured enjoyment of life. The third class (18%) focused relatively more on physical health. The fourth class (24%) had the least consistent preferences.ConclusionThis study has highlighted the heterogeneity in views of stakeholders in integrated care on what is important in health(care) for persons with multi-morbidity. To accurately value integrated care a variety of outcomes beyond health–e.g., enjoyment of life and experience with care–should be taken into account.

The Role of Trust in Explaining Food Choice: Combining Choice Experiment and Attribute Best-Worst Scaling.

This paper presents empirical findings from a combination of two elicitation techniques—discrete choice experiment (DCE) and best–worst scaling (BWS)—to provide information about the role of consumers’ trust in food choice decisions in the case of credence attributes. The analysis was based on a sample of 459 Taiwanese consumers and focuses on red sweet peppers. DCE data were examined using latent class analysis to investigate the importance and the utility different consumer segments attach to the production method, country of origin, and chemical residue testing. The relevance of attitudinal and trust-based items was identified by BWS using a hierarchical Bayesian mixed logit model and was aggregated to five latent components by means of principal component analysis. Applying a multinomial logit model, participants’ latent class membership (obtained from DCE data) was regressed on the identified attitudinal and trust components, as well as demographic information. Results of the DCE latent class analysis for the product attributes show that four segments may be distinguished. Linking the DCE with the attitudinal dimensions reveals that consumers’ attitude and trust significantly explain class membership and therefore, consumers’ preferences for different credence attributes. Based on our results, we derive recommendations for industry and policy.

Explaining variability in tourist preferences: A Bayesian model well suited to small samples

Abstract Discrete choice experiments are becoming more popular in the tourism and travel literature. While Bayesian methods to analyze discrete choice experiment data have been used in other disciplines, they have not been used in the tourism literature. In this article, we develop a Bayesian Mixed Logit Model in which we use a little known prior distribution developed by Lewandowski, Kurowicka, and Joe (LKJ) and half Cauchy distributions as an alternative to the more traditionally used inverse Wishart distribution as a prior scheme for the covariance matrix of random parameters in mixed logit estimation. Using multiple simulated data sets, we show that use of the LKJ prior scheme improves the estimation of coefficients, especially for small data sets. Finally, we test the model with an actual small discrete choice data set examining tourist preferences for reducing glacier recession, and discuss the implications of the model for research and policy.

Switching behavior in the Italian electricity retail market: Logistic and mixed effect Bayesian estimations of consumer choice

The paper highlights the importance of both local effects and market structure in determining the switching decision in retail electricity markets, and also introduces a new definition of household as the bundle of features of its members. We apply a Bayesian mixed Logit model to analyze the switching behavior in the Italian electricity retail market. The data set includes social, demographic, geographic and economic information regarding 18,448 households and 37,217 individuals together with their opinions, expectations and choices regarding national services. Results show that heterogeneity in the geographic and social context of choice and in the household composition has a major impact on the significance and on the identification of switching determinants implying that there is no one-size-fits-all policy to encourage switching and that further efforts should be dedicated to the definition of an optimal scale of analysis.

Valuing attributes of forest restoration in a semi-arid watershed

Approximately 1.5 M residents of the Phoenix metropolitan area rely upon the Salt Verde River watershed in central Arizona, USA, to meet their water demands. However, the health of the semi-arid watershed is at risk. Densely populated forests increase the probability of catastrophic wildfire and threaten the watershed’s integrity. Restoration reduces the risk of catastrophic wildfire and improves the health and productivity of the watershed. While current research indicates public support of watershed restoration, little guidance exists for land managers regarding the relative benefits of restoration projects. We estimate benefits of watershed restoration projects in the Salt-Verde River watershed using a choice experiment. The survey focuses on residents of the Phoenix metropolitan area as beneficiaries of watershed restoration and includes public access, surface water quality, groundwater recharge, critical habitat, and cultural significance as attributes. Willingness to pay estimates are obtained using a Bayesian mixed logit model. Respondents have a positive and statistically significant willingness to pay for all attributes. The highest willingness to pay is a one-time fee of $41.92 for restoration projects that protect critical habitats for endangered and threatened species. Our results also provide one of the first estimates for groundwater recharge as an attribute of watershed restoration. The benefit estimates obtained can directly inform land managers regarding restoration in semi-arid landscapes and assist in clearly delineating difficult to quantify environmental benefits in cost-benefit analyses of proposed future projects.

ABC Index: quantifying experienced burden of COPD in a discrete choice experiment and predicting costs

ObjectiveThe Assessment of Burden of COPD (ABC) tool supports shared decision making between patient and caregiver. It includes a coloured balloon diagram to visualise patients’ scores on burden indicators. We...

Market strategy for promoting green consumption: Consumer preference and policy implications for laundry detergent

AbstractGreen consumption is a very common phrase in our daily lives, yet product characteristics that mainly contribute to the diffusion of green products are largely unknown. Based on microeconomic theory, we conduct a conjoint survey of consumer preferences for a ubiquitous green product—laundry detergent. We analyze the correlation between consumers' demographic variables and attributes of laundry detergents through a hierarchical Bayesian mixed logit model. We find that consumer preferences for attributes display significant heterogeneity. Age and income significantly influence the marginal preferences for attributes. An examination of consumer willingness to pay and of the relative importance of each attribute reveals that price and base material are the most important attributes. Green attributes, such as skin irritation potential and biodegradability, tend to be less important. This study also examines preference heterogeneity based on previous purchase experience. To promote green consumption, we emphasize the need for policies that reduce the value‐action gap.

Cloud Service Based Measuring Consumer'sPreferences

This study focuses on the end-user marketplace for cloud computing. we have a tendency to conduct a mensuration to indicate shopper adoption behavior for these services, notably infrastructure as a service (IaaS). Bayesian mixed logit model and therefore the variable probit model area unit wont to analyze the info collected by a conjoined survey. From this investigation, we discover that the service charge and stability area unit the foremost vital adoption factors. We have a tendency to additionally gift Associate in Nursing analysis on the connection between terminal devices and IaaS, classified by core attributes like value, stability, and storage capability. From these relationships, we discover that larger storage capability is a lot of necessary for mobile devices like laptops than desktops. supported the results of the analysis, this study additionally recommends helpful methods to modify enterprise managers to concentrate on a lot of applicable service attributes, and to focus on appropriate terminal device markets matching the options of the service.

Strategic Management of Cloud Computing Services: Focusing on Consumer Adoption Behavior

The emergence of cloud computing services has led to an increased interest in the technology among the general public and enterprises marketing these services. Although there is a need for studies with a managerial relevance for this emerging market, the lack of market analysis hampers such investigations. Therefore, this study focuses on the end-user market for cloud computing in Korea. We conduct a quantitative analysis to show consumer adoption behavior for these services, particularly infrastructure as a service (IaaS). Bayesian mixed logit model and the multivariate probit model are used to analyze the data collected by a conjoint survey. From this analysis, we find that the service fee and stability are the most critical adoption factors. We also present an analysis on the relationship between terminal devices and IaaS, classified by core attributes such as price, stability, and storage capacity. From these relationships, we find that larger storage capacity is more important for mobile devices such as laptops than desktops. Based on the results of the analysis, this study also recommends useful strategies to enable enterprise managers to focus on more appropriate service attributes, and to target suitable terminal device markets matching the features of the service.

Analyzing public preferences and increasing acceptability for the Renewable Portfolio Standard in Korea

In order to respond to the challenge of climate change, similar to other countries, Korea has announced various policies to vitalize the development and uptake of renewable energy. The Renewable Portfolio Standard (RPS) is the most striking example of a policy in this area. This study employs a conjoint survey and Bayesian mixed logit model to analyze consumer preferences for specific attributes of the RPS policy. It analyzes households' marginal willingness to pay (MWTP) for the RPS with specific attributes and simulates the degree of household acceptability of the policy through a scenario analysis. Comparison between costs and benefits of implementing the policy is also attempted by analyzing the households' MWTP with the actual transition expense of RPS implementation incurred by electricity supply companies. The simulation results provide implications for improving RPS policy implementation; households consider the creation of new jobs as the most important policy attribute, followed by increase in electricity prices, damage to forests, reduction in CO2 emissions, and length of power outages. Moreover, the Korean household is willing to accept an increase of up to 1.39% in its electricity prices (relative to 2012), and the median MWTP of each household for RPS implementation is KRW 734.99/month (USD 0.67/month).

Strategic demand forecasts for the tablet PC market using the Bayesian mixed logit model and market share simulations

Since the release of the Apple iPad and the explosion of consumer demand for tablet PCs, a number of companies are entering into the tablet PC market, creating a situation that is becoming more fiercely competitive, complex, and difficult to predict. Under the singularity of the Korean tablet PC market, into which both the iPad and Galaxy Tab (with an Android operating system) were simultaneously released, this study closely analyses consumer preferences for tablet PCs. It uses the Bayesian mixed logit model, which can reflect consumers’ heterogeneous preferences based on data collected from a conjoint method, and using the estimates of the consumer utility function with model verification, it offers forecasts for the tablet PC market under six likely situations.

Skew and attribute non-attendance within the Bayesian mixed logit model

We investigate non-attendance to choice set attributes and the accommodation of preference heterogeneity within the mixed logit model. We propose a generalisation of the mixed logit enabling the degree of skew of marginal utility distributions to be estimated. The implementation is Bayesian with the marginal likelihood used as an arbiter of model performance. We find strong evidence of skew in the distributions of marginal utilities for most attributes. Models incorporating skew are preferred in all cases. The irrelevance of an attribute to significant numbers of respondents is a possible cause of such skew. We test alternative empirical accommodations of self-reported attribute non-attendance (ANA) and continue to find strong evidence of skew in the distributions of marginal utilities even having accounted for ANA. We find that, contrary to some recent findings, respondents who report having ignored an attribute typically do indeed have a zero marginal utility for that attribute.

Modeling Disinterest and Dislike: A Bounded Bayesian Mixed Logit Model of the UK Market for GM Food

Mixed logit models represent a powerful discrete choice analytical model but require assumptions about the functional form of the parameter distributions. The use of unbounded distributions, such as the normal distribution, may be regarded as unsuitable where theory indicates that all are negatively affected by increases in an attribute, such as price. Bounded distributions such as the triangular and log-normal are unable to model the case where a section of the population is indifferent towards an attribute, while the remainder are negatively disposed toward it. Train and Sonnier’s bounded mixed logit model accommodates these features and is employed in this paper. A censored normal and Johnson’s S b distribution are used to model preferences in the UK for food attributes, including price and GM technology. Bi-modal distributions are identified regarding GM food: some are unlikely to ever consume it, some are close to indifference and willing to consume at relatively small discounts while the remainder are fairly unresponsive to further price reductions.