Heterogeneous Choice Research Articles

Examining the associations between high achievement in reading and school climate: evidence from five South American countries

An emergent literature has shown that some students overcome adversities related to their low Socio-Economic Status (SES) by attaining high academic achievement. One of the aims of this literature is to identify the factors that explain the capacity of students from low SES backgrounds to attain high academic achievement. However, upon reviewing this literature, I observed that few studies have comparatively investigated the associations between the capacity of students from low SES backgrounds to attain high achievement in reading and school climate characteristics. Additionally, I found that not many studies have researched whether student SES moderates these associations. This paper contributes to fill these two gaps by estimating associations between high achievement in reading and school climate characteristics. Moreover, it examines whether student SES moderates these associations. To do this, this research estimated logit and heterogeneous choice models using representative samples of students from Argentina, Brazil, Chile, Colombia, and Uruguay who participated in the 2018 Programme for International Student Assessment (PISA). The results show that high achievement in reading is positively correlated to certain teaching practices, such as perceived teacher enthusiasm during the instruction and adapting instruction to students’ needs. Conversely, it is negatively correlated to teacher feedback and teacher-directed instruction. Furthermore, the findings indicate that high achievement in reading is negatively correlated to the scarcity and low quality of educational material. Interestingly, the results show that student SES does not moderate these associations. In conclusion, these findings indicate that interventions targeting these areas of school climate may help to increase students’ probability of attaining high achievement in reading, regardless of their SES. Likewise, these results suggest that if these interventions are focused in low SES schools, they may contribute to bridge the gap in reading skills between students from low and middle or high socioeconomic backgrounds.

<p>Livelihood Impacts of Drought: Experiences from Households and Business Organizations in Western Cape Province of South Africa</p>

Drought is a recurring natural phenomenon with significant socio-economic and environmental impacts across South Africa. This research investigates the livelihood impacts of drought on households and organizations in the Western Cape Province of South Africa, utilizing a secondary dataset collected by the Human Sciences Research Council of South Africa. Descriptive statistics were used to describe and explore the dataset. Likewise, heterogeneous choice modeling was applied to investigate the factors influencing the levels of livelihoods impacts of drought among household and organizations. The findings underscored households’ greater vulnerability to drought compared to organizations across all the levels of drought impacts. Many households reported considerable and major impacts, which were largely due to differentials in adaptive capacity. While awareness of the drought was widespread, perception varied regarding the government’s effectiveness in managing the crisis, as less than half of the population of organizations (43.7%) and households (42.1%) have strong belief that the government was very effective in the management of drought disaster, while 30.9% and 34.6% of the organizations and households respectively, believed that the government was not effective enough with the management of drought crisis. Hygiene, chores, and gardening suffered the most among households, whereas disruption of business and financial burdens were predominant for organizations. Factors that significantly influenced the levels of drought impacts include age, institutional engagement of water restrictions, livelihood areas impacted by drought, and perceptions on water consumption rate. The study recommends heightened awareness of water conservation, compliance with restrictions, investment in infrastructure, and embracing community-based adaptation and disaster risk reduction initiatives. For organizations, emergency response plans, business continuity planning, and stakeholder engagement will be helpful to bolster resilience to drought.

Heterogeneous choice of personalized Mobility-as-a-Service bundles and its impact on sustainable transportation

The Mobility-as-a-service (MaaS) framework has the potential to induce changes in individual travel behavior towards more sustainable transportation alternatives by integrating multimodal travel services. However, insights into the behavioral responses of specific groups of people to MaaS, thus promoting green travel, are currently lacking. This paper intends to investigate the intergroup heterogeneous preferences on the choice of MaaS bundles and evaluate their contributions to eco-friendly travel. A stated choice experiment is designed, incorporating personalized MaaS service bundles complemented by different green travel-oriented ticketing strategies. The experiment caters to different groups of users related to public transport, cars, and other modes of transport. The results indicate a substantial improvement in the goodness-of-fit of the behavioral model after user classification, revealing significant heterogeneity in preferences among users regarding MaaS bundle choices. Notably, the impact of sub-tickets on nudging toward green transportation is more pronounced than that of monthly and discount tickets.

Urbanization, civil conflict, and the severity of food insecurity in Africa

AbstractThe objective of this article is to examine the impact of urbanization and civil conflicts on the severity of food insecurity for a panel of 43 African countries over the period 2000–2020. Subsequently, the heterogeneous choice models approach was used for the estimations. The results show that urbanization and civil conflict increase food insecurity. The parallel line probability hypothesis results specifically show that a one‐unit increase in urban growth rate increases the probability of belonging to a high‐risk food insecurity category by more than .6 times. Furthermore, the results show that the impacts of urbanization on food insecurity are modulated by civil conflicts in Africa leading to the net effect of .692. This corresponds to the policy threshold of 2.315 when the net positive effect is canceled out. Therefore, this study strongly recommends the need for African economies to develop urban agriculture while controlling the pace of urbanization in order to reduce food insecurity and avoid possible civil wars.Related ArticlesAsare‐Nuamah, Peter, Anthony Amoah, and Simplice A. Asongu. 2023. “Achieving Food Security in Ghana: Does Governance Matter?” Politics & Policy 51(4): 614–35. https://doi.org/10.1111/polp.12540.Ayanoore, Ishmael, and Sam Hickey. 2022. “Reframing the Politics of Natural Resource Governance in Africa: Insights from the Local Content Legislation Process in Ghana.” Politics & Policy 50(1): 119–36. https://doi.org/10.1111/polp.12449.Oehmke, James F., Sera L. Young, Godfrey Bahiigwa, Boaz Blackie Keizire, and Lori Ann Post. 2018. “The Behavioral‐Economics Basis of Mutual Accountability to Achieve Food Security.” Politics & Policy 46(1): 32–57. https://doi.org/10.1111/polp.12244.

Estimating the impact of behavior heterogeneity on airfare choices

Previous studies on airfare choices have discussed various types of heterogeneity. Based on these findings, this study investigated a type of non-trading behavior observed in the context of airfare booking. Required by the pricing and revenue management decisions, airline often offers hierarchical airfares subject to capacity constraints. This presents challenges in identifying the heterogeneous choice behaviors among air travelers and in the consequent demand estimation. To differentiate the trading and non-trading behavior of respondents, a stated preference (SP) experiment that allows variation of choice set composition was applied. Among the data, over 40% of respondents were observed to choose only from the non-flexible fare class. Identifying such heterogeneity can improve choice modelling and help better understand airfare choice behaviors. In addition, taking into account behavior heterogeneity may produce significantly different demand forecasts, according to which airlines may devise distinctive marketing strategies. Despite the managerial implications, there are some potential privacy and safety issues that may raise the awareness of policy-makers, and this has also been discussed in this research.

Probabilistic choice set formation incorporating activity spaces into the context of mode and destination choice modelling

Understanding the constraints that individuals face during their spatial choices is important from a policy perspective. Such constraints, however, are often overlooked in the choice set generation process during model development. In order to address that gap, the current study proposes a probabilistic choice set formation based on Manski's framework assuming that the actual choice set of an individual is latent (unobserved). Though latent class models with heterogeneous choice sets have been used previously in the context of mode and route choice, their application in the context of spatial choices have been hindered due to the inherently large choice sets making the problem computationally intractable. To address this issue, we propose to computationally simplify the problem by utilising the geography-derived notions of Activity Spaces to delineate a range of potential choice sets per individual helping us to capture both issues of spatial awareness and time-space constraints. In order to account for the latent nature of the true choice set, we propose a Latent Class Choice Modelling (LCCM) framework to allocate the individuals probabilistically into the different resulting choice sets, with each class having a different choice set and a different set of parameters. Thus the LCCM is able to capture heterogeneity in the choice sets and in the sensitivities, at the same time. The proposed LCCM framework is empirically tested on joint mode and shopping destination choices captured through a GPS smartphone application. It is compared to a base MNL model estimated on the global choice set, an LCCM capturing heterogeneity only in the sensitivities and a LCCM with latent consideration choice sets, similarly to the proposed model, but with generic parameters across classes. Our proposed specification is able to outperform all of the remaining models, while also providing insights on the factors affecting individuals to be constrained in their location choices across space hinting to cases of spatial cognition, the importance of the home and workplace geography and the individual's socioeconomic status. Such insights can be important for developing more behaviourally realistic models that can be used by planners and policy makers to formulate more effective measures that better relate to the underlying population. Furthermore, the analysis provides insights into the discrepancies that can emerge by accounting for latent consideration sets in willingness-to-pay measures and demand elasticities, which could have significant implications in the effectiveness of policy measures.

Optimal Approximate Choice Designs for a Two-step Coffee Choice, Taste and Choice Again Experiment

AbstractThis work deals with consumers' preferences about coffee. Firstly, a choice experiment is performed on a sample of potential consumers. Following this, a sensory test involving the tasting of two varieties of coffee is carried out with the respondents, after which the same choice experiment is supplied to them again. An innovative approach for building heterogeneous choice designs is specifically developed for the case-study, based on approximate design theory and compound design criterion. Panel Mixed Logit models are used, thereby allowing for the inclusion of correlation among consumers' responses; choice-sets are supplied to a proportion of respondents according to optimal weights. The estimation results of the Panel Mixed Logit model are satisfactory, confirming the validity of the proposed approach.

Heterogeneous choice in WTP and WTA for renting land use rights in rural china: Choice experiments from the field

China's institutional structures regarding land are unique and complex. Recent changes to the land laws now permit farmers to rent Land Use Rights (LUR) from other farmers. The purpose of this paper was to make some determination about the value of certain attributes important in determining the willingness of farmland tenants to pay agricultural rents, and the willingness of owners of land use rights accept a rental price.We use in-the-field discrete choice experiments (DCE) in Shandong, Sichuan, Shaanxi, Jiangsu and Hunan across two waves in 2018 to identify the WTP and WTA attributes for both landlords and tenants. Our underlying hypothesis was that landlords and tenants will likely place different utility weights on attributes of land because their interest between making and receiving a payment are different. This is confirmed in this study. We find little uniformity in WTP and WTA across provinces. Mixed Logit results confirm that not all Chinese farmers think alike and are heterogenous in how they weigh or value attributes. Overall, we find autarky land rental prices of 813.93RMB, 564.65 RMB, 1,193.96 RMB and 863.99 RMB for Shaanxi, Shandong, and Sichuan which are well within the observed range. We observe a fairly wide range of WTP and WTA values across provinces which reflect the individual characteristics of the growing regions surveyed. We also find generally that the WTP for attributes are higher than WTA. These are reflected by utility-rent elasticities which reveals that heWTP is more elastic than WTA. We conjecture that differences in WTP and WTA is attributed to certainty equivalent risk transfers and untethered access by farmers to the wage market.

Implementation approaches and barriers for rule-based and machine learning-based sepsis risk prediction tools: a qualitative study.

ObjectiveMany options are currently available for sepsis surveillance clinical decision support (CDS) from electronic medical record (EMR) vendors, third party, and homegrown models drawing on rule-based (RB) and machine learning (ML) algorithms. This study explores sepsis CDS implementation from the perspective of implementation leads by describing the motivations, tool choices, and implementation experiences of a diverse group of implementers.Materials and MethodsSemi-structured interviews were conducted with and a questionnaire was administered to 21 hospital leaders overseeing CDS implementation at 15 US medical centers. Participants were recruited via convenience sampling. Responses were coded by 2 coders with consensus approach and inductively analyzed for themes.ResultsUse of sepsis CDS is motivated in part by quality metrics for sepsis patients. Choice of tool is driven by ease of integration, customization capability, and perceived predictive potential. Implementation processes for these CDS tools are complex, time-consuming, interdisciplinary undertakings resulting in heterogeneous choice of tools and workflow integration. To improve clinician acceptance, implementers addressed both optimization of the alerts as well as clinician understanding and buy in. More distrust and confusion was reported for ML models, as compared to RB models. Respondents described a variety of approaches to overcome implementation barriers; these approaches related to alert firing, content, integration, and buy-in.DiscussionWhile there are shared socio-technical challenges of implementing CDS for both RB and ML models, attention to user education, support, expectation management, and dissemination of effective practices may improve feasibility and effectiveness of ML models in quality improvement efforts.ConclusionFurther implementation science research is needed to determine real world efficacy of these tools. Clinician acceptance is a significant barrier to sepsis CDS implementation. Successful implementation of less clinically intuitive ML models may require additional attention to user confusion and distrust.

Exploring variation in factors associated with increased likelihood of pretrial detention

• This study assesses individual- and case-level factors that are associated with pretrial detention in New York City. • Using heterogeneous choice models, we examine whether offense type varies across boroughs of New York City. • Results reaffirm the importance of a number of legal and extra-legal factors, such as race, on pretrial detention. • Results also suggest that the effect of offense type on pretrial detention varies significantly between jurisdictions.

Heterogeneous Choice Sets and Preferences

We propose a robust method of discrete choice analysis when agents' choice sets are unobserved. Our core model assumes nothing about agents' choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence, conditional on observables, between choice sets and preferences. We first characterize the sharp identification region of the model's parameters by a finite set of conditional moment inequalities. We then apply our theoretical findings to learn about households' risk preferences and choice sets from data on their deductible choices in auto collision insurance. We find that the data can be explained by expected utility theory with low levels of risk aversion and heterogeneous non‐singleton choice sets, and that more than three in four households require limited choice sets to explain their deductible choices. We also provide simulation evidence on the computational tractability of our method in applications with larger feasible sets or higher‐dimensional unobserved heterogeneity.

Heterogeneous choice in the demand for agriculture credit in China: results from an in-the-field choice experiment

PurposeIn this study, the authors examined demand-side credit in rural China with the aims of understanding attribute preferences and the willingness of farmers to pay for credit.Design/methodology/approachThe authors implemented an in-the-field discrete choice experiment (DCE) using a D-optimal block (6 × 9 × 3) design applied to 420 farm households across five Chinese provinces (Shandong, Sichuan, Shaanxi, Jiangsu and Henan) in the summer and fall of 2018. The DCE included six attributes including the interest rate, term of loan, type of loan, type of repayment, type of institution and mobile banking services.FindingsConditional and mixed logit results indicated a downward sloping credit demand curve with variable elasticity across regions. Provincial willingness-to-pay (WTP) indicators suggested that farmers were willing to pay a premium for long-term ( 0.03–0.687%) and low collateral credit loans ( 0.79–2.93%). Also, four of five provinces indicated a preference for loan amortization rather than lump-sum payment. Interestingly, in comparison to the Agricultural Bank of China (ABC), only farmers in Shandong, Sichuan and Shaanxi indicated a preference for rural credit cooperatives (RCCs)/banks and the Postal Savings Bank of China (PSBC). Another quite surprising result was bank services, in our case, access to mobile banking did not appear to induce WTP for agricultural credit. While conditional and mixed logit regression coefficients were similar (and therefore robust), the authors found that there was substantial heterogeneity across attribute preferences on term of loan, type of loan and amortization. Preferences for type of lender and mobile banking were generally homogenous. This result alone suggested that lenders should consider offering a suite of credit products with different attributes in order to maximize the potential pool of borrowers. While there were some differences across provinces, farmers appeared to be indifferent to lenders, and it did not appear that offering banking services such as mobile banking had any bearing on credit decisions.Research limitations/implicationsThis paper presents a first step in using in-the-field choice experiments to better understand rural finance in China. Although the sample size satisfies conventional levels of significance and rank conditions, the authors caution against attributing results to China as a whole. Different provinces have different institutional structures and agricultural growing conditions and economies and these effects may differentially affect WTP for credit. Although by all indications farmers were aware of credit, not all farmers, in fact a minority, actually borrowed from a financial institution. This is not unusual in China, but for these farmers, the DCE was posed as hypothetical. Likewise, the study’s design was based on a generic credit product typical of rural China, and the authors caution against making inferences about other products with different attributes and risk structures.Social implicationsThis study is motivated by the rapidly changing dynamic in China's agricultural economy. With specific reference to new laws and regulations about the transfer of land use rights (LURs), China's agricultural economy is undergoing significant and rapid change which will require better understanding by policy makers, lenders and practitioners of the changing credit needs of farmers, including the new and emerging class of commercial farmers.Originality/valueTo the best of the authors’ knowledge, the authors believe that the result provided in this paper present the first use of in-the-field DCE and are the first to be reported in either the English or Chinese literature on rural credit product design.

Understanding heterogeneous preferences of hotel choice attributes: Do customer segments matter?

This study focuses on understanding the heterogeneous preferences for hotel choice attributes across different segments in leisure and business contexts. Data were collected using a choice-based conjoint (CBC) survey from a sample of 513 hotel customers. Using a latent class model (LCM), the results show that there are substantial heterogeneous preferences for hotel choice attributes across segments within the same context. Regarding the impact of price on hotel choice, this study reveals that while business travelers are generally price sensitive, leisure travelers differ within the three segments. Further, not only did leisure travelers in all segments greatly value the entertaining attribute, but so did Segment 5 business travelers in their 40s–60s with high incomes. This study suggests that hotel managers should understand the specific characteristics of customers by segment and the heterogeneous choice preferences by customer segment in order to develop effective marketing strategies.

CROSS-NATIONAL COMPARISONS OF STUDENTS’ SCIENCE SUCCESS BASED ON GENDER VARIABILITY: EVIDENCE FROM TIMSS

Identifying key determinants of success plays an important role in efforts of assessing the current state of educational practices and implementing effective actions to improve academic performance. Given how important is accurate identification of these determinants for valid comparisons, the aim of this research was to present extensive comparative results on 8th grade students' science success for 39 countries. To this end, a total number of 229,493 students' information obtained from the last cycle of Trends in International Mathematics and Science Study was handled. Unlike previous studies in which success has been tried to be explained with some factors, this research extended the literature by investigating the effective factors as well as gender-related variability on science success with a holistic view. Using heterogeneous choice models, unobserved heterogeneity caused by gender difference was tested and controlled. The findings showed that gender variability was evident for 10 countries. Furthermore, factors associated with students' future educational goals, home educational resources and confidence were found as the common determinators of science success in all participant countries. Another notable finding was all factors, except time spent on doing homework, tended to differentiate the success status between girls and boys of 22 countries. Keywords: cross-country comparison, gender variability, heterogeneous choice models, science success.

Heterogeneous choice of home renewable energy equipment conditioning on the choice of electric vehicles

New mobility tools like electric vehicle and e-bike have been an important strategy in many cities for the reduction of traffic problems and the implementation of renewable energy infrastructures. The choice of individuals on mobility tools however may depend on the magnitude of a comparable cost. Home renewable energy equipment like solar panel which generates energy at home may potentially reduce the electricity expenditure of e-mobility. This paper therefore aims to investigate the choice behavior of individuals on their home renewable energy equipment conditioning on the choice of mobility tools. More specifically, we identify the differences among individuals in their preferences and the latent groups. Using the stated preference data collected in the city of Weiz, Austria, we estimated a latent class choice model with social demographics representing the user group membership. Results show that the synergy effect between EV and solar panels and self-sufficient home energy system is more attractive to people with low income although their willingness to buy are lower than people with high income.

The institutionalization of part-time work: Cross-national differences in the relationship between part-time work and perceived insecurity

We propose an institutionalization of part-time work model to account for the cross-national variation in workers' perceptions of insecurity in their jobs and in the labor market, arguing that part-time work is institutionalized as high quality or marginal employment depending on the extent to which it is voluntary, gendered, and legally protected. Using heterogeneous choice models on 2005 ISSP data linked to country-level characteristics, we find that the relationship between part-time work and insecurity is gendered and contingent upon the type of insecurity (cognitive job insecurity, labor market insecurity, or affective job insecurity) and whether or not one works part-time on a voluntary basis. At the individual level, working in a part-time job is associated with greater cognitive job insecurity but lower labor market and affective job insecurity. At the national level, the expected negative association between the part-time work rate and insecurity is most consistent for affective job insecurity. The findings also indicate that the strength of the association between working in a part-time job and insecurity varies by the national institutional context of part-time work, including the degree of gender segregation of part-time work and legal protections for part-time workers. Overall, the results from this study provide support for our institutionalization of part-time work perspective. Part-time work is not inherently secure or insecure employment. The amount of insecurity associated with this type of non-standard work is contingent upon the prevailing local myths or scripts that structure the ways that the state, employers, and workers view part-time work.

Modelling heterogeneity: on the problem of group comparisons with logistic regression and the potential of the heterogeneous choice model

The comparison of coefficients of logit models obtained for different groups is widely considered as problematic because of possible heterogeneity of residual variances in latent variables. It is shown that the heterogeneous logit model can be used to account for this type of heterogeneity by considering reduced models that are identified. A model selection strategy is proposed that can distinguish between effects that are due to heterogeneity and substantial interaction effects. In contrast to the common understanding, the heterogeneous logit model is considered as a model that contains effect modifying terms, which are not necessarily linked to variances but can also represent other types of heterogeneity in the population. The alternative interpretation of the parameters in the heterogeneous logit model makes it a flexible tool that can account for various sources of heterogeneity. Although the model is typically derived from latent variables it is important that for the interpretation of parameters the reference to latent variables is not needed. Latent variables are considered as a motivation for binary models, but the effects in the models can be interpreted as effects on the binary response.

Combining Strictly Asymmetric Choice Rules

Newton (2019) gives results on combining heterogeneous choice rules that satisfy an asymmetry condition. This note restates and proves the theorems of Newton (2019) for a strict asymmetry condition.

Conceptions of National Identity and Ambivalence towards Immigration

National identities are often conceived of as factors that lend structure and stability to citizens’ political opinions on issues such as immigration. While citizens who define national membership in ethno-cultural terms are less likely to support immigration, those with a civic conception are more likely to do so. The authors propose that defining national identity along both ethno-cultural and civic lines may give rise to conflicting considerations, leading people to experience ambivalence, implying that national identities may serve less as a stabilizing force than suggested by previous research. Findings from heterogeneous choice models and a unique survey experiment show that German citizens with mixed conceptions of national identity had more variable and more malleable opinions than individuals with ideal-type conceptions during the 2015/2016 European refugee crisis. The findings point to an identity-based source of ambivalence and extend current understandings of how people form attitudes towards immigration.

Assessing Effect of Bridging Social Capital on the Attitudes Toward Immigrants in the U.S.: Does Race Matter?

This study examines how bridging social capital affects attitudes toward immigrants in the U.S. Bridging social capital, a term which refers to social capital across heterogeneous groups of people beyond inner circles, might play an important role in understanding people’s way of perceiving difference and diversity. Considering inequality of social capital for racial minorities in the U.S., this study also examines whether the impact of bridging social capital on attitude towards immigrants varies by different racial and ethnic groups in the U.S. The analysis was based on the 2006 U.S. Social Capital Community Survey (SCCS) data set. A multinomial regression analysis and a heterogeneous choice model were conducted to test the aims of this study. The findings indicate that people who have a higher level of bridging social capital are more likely to hold favorable attitudes toward immigrants. In particular, the positive association between ‘trust towards others who are different’ and attitudes toward immigrants varied across racial groups: the positive effect becomes weaker for African Americans and other races, compared to whites. Overall, our findings provide important knowledge for understanding public attitudes toward immigrants in relation to bridging social capital. Moreover, the findings on inequality of social capital returns among minorities demonstrate the importance of understanding structural racial discrimination toward racial minorities in American society. Special attention should be given to underlying mechanisms.