Time Allocation Behavior Research Articles

Trust towards autonomous driving, worthwhile travel time, and new mobility business opportunities

ABSTRACT When driving autonomous cars, individuals have the opportunity to engage in non-driving activities, resulting in improved well-being. By incorporating trust into the technology acceptance modelling framework, this study extends the understanding of behavioural intention from the adoption of autonomous cars to the allocation of worthwhile travel time. Within this extended framework, the structural equation model is employed to identify significant paths to time allocation behaviour. Specifically, trust is identified as a crucial determinant of such behavioural intention. Then, we use the hierarchical ordered probit model to analyse the extent of such time allocation, accounting for scaling heterogeneity in self-reported responses. Our empirical evidence demonstrates the vital role of trust in encouraging the allocation of worthwhile and productive travel time. Based on these results, we present various new mobility business opportunities as well as some policy implications from the perspective of trust.

A multiple discrete-continuous extreme value model with ordered preferences (MDCEV-OP): Modelling framework for episode-level activity participation and time-use analysis

This paper formulates a novel, multiple discrete-continuous extreme value model with ordered preferences (MDCEV-OP) to analyze multiple discrete-continuous (MDC) choices at a disaggregate level, including the number of instances different alternatives are chosen and the amount of consumption at each instance of choice. In doing so, the proposed model ensures a logically consistent prediction of multiple choice instances of an alternative. Specifically, the model prevents the prediction of positive allocation to the jth instance (i.e., a frequency of j episodes) of a good while predicting zero allocation to the (j-1)th or lower-numbered instances of that alternative. This is achieved by imposing a non-increasing order on the baseline-preference parameters of different choice instances of an alternative. The model results in a conditional likelihood function, where the likelihood arising from the optimality conditions of the utility maximization problem is conditioned on the ordering of baseline marginal utilities. Combining this strategy with independent and identically distributed (IID) Gumbel stochastic terms in the utility functions results in a closed-form likelihood expression that is not much more difficult than that of the MDCEV model. The proposed framework is applied for an empirical analysis of disaggregate, episode-level activity participation and time allocation behavior of non-working adults in Los Angeles, California. The empirical MDCEV-OP model provided better fit and predictive accuracy (in both estimation and validation datasets) for analyzing episode-level activity participation than a disaggregate MDCEV model that does not recognize the logical ordering of episodes. At the same time, the activity-level predictions aggregated from the episode-level predictions of the MDCEV-OP model do not deviate significantly from the predictions of an aggregate MDCEV model. These results highlight the efficacy of the proposed model for analyzing episode-level activity generation and time allocation.

Impacts of COVID-19 lockdown on time allocation for sedentary and physical activities – The context of Indian university students

IntroductionCovid-19 pandemic has impacted individuals’ time allocation decisions. As it is known that university students display behaviors different from the general population, very few studies have examined their activity participation and time allocation behavior during the pandemic. The present study investigates the changes in time allocations to sedentary, physically active, and eat-sleep activities before and during the pandemic. MethodsThe study hypothesizes that active mode (walk, bicycle) and transit users would compensate for the physical efforts by increasing physical activities at home during the lockdown. Students' perception of personal well-being, anxiety, and individual leisure during the pandemic and their impacts on time allocation decisions after controlling for demographic variables and temporal effects are also explored. A pan India behavioral data of 203 samples collected using an online survey conducted between May to July 2020, during India's lockdown phase, is used for analysis. A series of segmented analyses (using ANOVA's and Kruskal-Wallis Test) and empirical modeling (linear mixed-effect regression) were conducted based on the time use distribution. ResultsFindings showed that university students from low-income households and students who own a bicycle show a higher tendency to spend time in physical activities during lockdown periods. Students accessing college using active modes (before lockdown) allocate less time to sedentary and eat-sleep activities than physical activities during the lockdown period. Students' perception of Leisure items among those who use active modes is significantly different from those of private and public mode users. ConclusionsFrom a policy viewpoint, such investigation would help implicitly understand and publicize the health benefits of active modes and transit and encourage their use. For instance, policymakers and transport planners can temporarily allocate less-used motorized streets (due to the pandemic) to students who prefer walking and cycling as universities still function online in India.

Household Production and Time Allocation Behaviour to Climate Change of Nepal

This study investigates empirically how forest resources production and time allocation’s behavior links with climate change issues by using a household survey in a mid-hill village of Nepal. We use Cobb Douglas’s production function theory to develop a household production function econometric model. We use two-character households: unemployed and forest-dependent population for observation of time allocation behavior for household production. In addition, we use poverty and illiteracy of household characters for understanding its effect on household decision behavior and production behavior. In outcomes of the study, household production behavior of rural people results in higher dependency on forest biomass and its consequence climate change cause issue.

Gender Patterns in Labor Allocation to Avocado Production: Evidence from Kenya

Farmers face gender differentiated unique social and economic circumstances which may in part determine their time allocation behavior. Using primary survey data from Murang’a County, Kenya, this study employs the double hurdle and Tobit models to investigate gendered patterns of labor allocation in avocado production under contract and non-contract scenarios, non-farm activities as well as the intensity of time use. Results show that while avocado commercialization through contract farming has to some extent altered traditional gender roles in farming, there is still limited participation of women in avocado marketing under contract farming. Hence, interventions aimed at enhancing smallholder avocado production should incorporate mechanisms that will enable women participate at all levels of the avocado value chain.

Marriage Market Dynamics, Gender, and the Age Gap

We present a general discrete choice framework for analyzing household formation and dissolution decisions in an equilibrium limited-commitment collective framework that allows for marriage both within and across birth cohorts. Using Panel Study of Income Dynamics and American Community Survey data, we apply our framework to empirically implement a time allocation model with labor market earnings risk, human capital accumulation, home production activities, fertility, and both within- and across-cohort marital matching. Our model replicates the bivariate marriage distribution by age, and explains some of the most salient life-cycle patterns of marriage, divorce, remarriage, and time allocation behavior. We use our estimated model to quantify the impact of the significant reduction in the gender wage gap since the 1980s on marriage outcomes.

Multitasking during Travel in Mumbai, India: Effect of Satiation in Heterogeneous Urban Settings

AbstractMultitasking is an essential aspect of an individual’s overall activity participation and time allocation behavior, and travel is one of the few activities which provides the scope for natu...

Bayesian methods applied to the generalized matching law.

We demonstrate the usefulness of Bayesian methods in developing, evaluating, and using psychological models in the experimental analysis of behavior. We do this through a case study, involving new experimental data that measure the response count and time allocation behavior in pigeons under concurrent random-ratio random-interval schedules of reinforcement. To analyze these data, we implement a series of behavioral models, based on the generalized matching law, as graphical models, and use computational methods to perform fully Bayesian inference. We demonstrate how Bayesian methods, implemented in this way, make inferences about parameters representing psychological variables, how they test the descriptive adequacy of models as accounts of behavior, and how they compare multiple competing models. We also demonstrate how the Bayesian graphical modeling approach allows for more complicated modeling structures, including hierarchical, common cause, and latent mixture structures, to formalize more complicated behavioral models. As part of the case study, we demonstrate how the statistical properties of Bayesian methods allow them to provide more direct and intuitive tests of theories and hypotheses, and how they support the creative and exploratory development of new theories and models.

Interrelationships between ICT, social disadvantage, and activity participation behaviour: A case of Mumbai, India

Studies on the social role of transport disadvantage have influenced the policy discourse, especially in the developed world. However, the potential of information and communication technologies (ICT) to improve access to opportunities has been rarely explored. In a scenario where disparities exist in both physical proximity and access to ICT, this study aims to analyse the interrelationships between three key areas viz. ICT, social disadvantage, and activity participation behaviour. A time use survey representative of Mumbai’s housing disparity was conducted for 1205 individuals. The data showcased the differences in household socio-economic characteristics, individual personal characteristics, ICT use patterns, activity participation, and time allocation patterns. Structural equation modelling was used to evaluate exclusionary factors and their interconnectedness. It was found out that ‘social advantage’ had a significant positive relationship with ‘access to ICT’ and ‘farness to services’. The effects of exclusionary factors, along with activity and individual specific variables were tested on activity participation and time allocation behaviour using type II Tobit models. Finally, marginal effects of ‘access to ICT’ and ‘farness to services’ on activity participation and time allocation behaviour were estimated. The findings suggested that an increase in access to ICT increased in-home leisure participation and travel time allocation. However, no significant positive relationship was established between access to ICT and in-home mandatory activities. Policy implications of the findings were discussed highlighting the importance of an integrated framework to improve both physical access and the access to ICT to tackle the issue of social exclusion.

Effects of a Universal Childcare Subsidy on Mothers’ Time Allocation

This paper examines the effects of a universal childcare subsidy on childcare decisions and mothers’ employment by using Korea’s policy reform of 2012, which provided a full childcare subsidy to all children aged 0 to 2. I find that the introduction of a universal childcare subsidy increased the use of childcare centers by children aged 0-2, which led to less maternal care compared to that provided to children aged 3-4. However, the expanded subsidy had little effect on mothers’ labor supply. Moreover, the policy effects vary by individual and household characteristics. The effects of the expanded subsidy are mainly found in low-income households and less educated mothers. Highly educated mothers and high-income households are likely to focus more on the quality of childcare service. These results imply that a simple reduction in childcare costs would bring only limited effects on mothers’ time allocation behavior; thus, more attention should be paid to improving the quality of childcare services.

An Analysis of Out-of-home Non-work Activity Time Use and Timing Behaviour Based on Work Schedule and Trip Time

This paper attempts to integrate the discrete of activity timing and the continuous data of time allocation based on the concept of utility. The analysis combines the concept of discrete-continuous simulation equations framework to represent the interactions between activity timing and time allocation behaviour during the day. Activity timing choice was modelled as a discrete choice variable involving three alternatives broad periods: home-to-work period, work-based period and post home period. For fixed time workers, it was found that the model in which activity time allocation is assumed to be determined first influence activity timing show statistical measure of fit. Significant parameter of trip characteristics and social economic variables also influence activity timing choice. Activity timing choice model based on time-allocation data can be used to estimate the number of induced and reduce trips and evaluate the impacts of alternative transportation improvement projects to decision to carry out the activities and trips.

Comment on “Who Faces Higher Prices? An Empirical Analysis Based on Japanese Homescan Data”

Abe and Shiotani (2014) are concerned with household-level price differences amonghouseholds. This type of research has two different roots of investigation.The first is toconstruct household-level consumer price indices (CPIs) with different household char-acteristics, namely, the age of the head of household, household income, and householdlocation, for example, Kitamura (2008). The second is to examine the relationshipbetween the household-level actual prices and life-cycle consumption and time alloca-tion behavior, for example, Aguiar and Hurst (2007). This paper follows the second lineof research. It is quite sensible to investigate whether Aguiar and Hurst type of observa-tions can be found in Japan.The advantages of homescan data over the Retail Price Survey conducted by the Japa-nese Government lie in the former’s rich information on the varieties of goods, the pur-chase prices paid by individual households, and the frequency of shop visits. At themoment, Abe and Shiotani construct shopping behavior-related variables, such as thenumber of different stores, a Herfindahl–Hirschman index of store shares, the totalnumber of goods bought by a household, a bargain index, a store chain index, and aquality index, and use these indicators as explanatory variables in the household-levelprice index.Although Abe and Shiotani’s use of this information conveys some interestingaspects of the Japanese household behavior, there could be some alternative ways to usethe information from the homescan data. For example, Abe and Shiotani argue thatelderly people face higher prices than the young, which is contrary to the results ofAguiar and Hurst (2007). They provide some further analyses of this interesting finding,by finding that the elderly spend more at specialized stores (presumably mom-and-popretail shops) and supermarkets, and less at drug stores and home_improvement_storescompared to the young.The regression results in Abe and Shiotani’s (2014) Table 7 showthat store choice can explain part of the price-level differentials between households.However, Abe and Shiotani note from their Table 8 that the elderly face higher pricesthan the young even within the same store type and that the mechanism behind thehigher prices among the elderly needs further investigation.

Daily Travel Time Analysis with Duration Model

Travel demand management strategies and transportation control measures are inherently linked to the time dimension. In this paper, the duration model approach, which integrates the notion of the temporal dynamics, is applied to analyze the commuters' daily travel time cost. The relationships between daily travel time and sociodemographic attributes and activity and travel characteristics are explored. The time use pattern is partly represented by the derivative and competing relationships of activity and travel. The research results indicate that the behavior of most commuters can be described by travel time minimization mechanism. This research enriches the quantitative analysis method of travel time and is of great importance for a precise understanding of commuters' time allocation behavior.

Explaining Gender Differences in Housework Time in Germany

This study evaluates couples’ time use behaviour with regard to housework in Germany with data from the 2001/2002 and 1991/1992 German Time Use Survey. Despite the fact that women reduced their hours worked within the household context over the past decades, the unequal division of housework between men and women still persists. This study aims both at analysing the determinants of the allocation of time spent on housework, as well as why gender differences in household time use behaviour still exist. With the aid of structural equation modelling, it is shown that the decrease in time spent on housework by women can largely be explained by changes in the effects that wages, household goods consumption and the aspiration for market goods consumption have on time spent on housework. Men’s time allocation behaviour has remained remarkably constant. It is also observed that women’s time allocation behaviour with regard to household work is becoming more similar to that of men.

Exploring Variation Properties of Time Use Behavior on the Basis of a Multilevel Multiple Discrete–Continuous Extreme Value Model

This study attempts to examine the variation properties of time use behavior on the basis of a multilevel multiple discrete–continuous extreme value model, which describes both activity participation and time allocation behavior by incorporating various variance components. Five major variation components are dealt with, including interindividual, interhousehold, temporal, spatial, and intraindividual variations. The MobiDrive data, continuous 6-week daily travel data, allow identification of these variations simultaneously. Two types of models are empirically examined: the model without consideration of the influence of explanatory variables (null model) and the model that introduces explanatory variables (full model). Estimation results of the null model confirm that intraindividual variation still accounts for more than 50% of the total variation (except for mandatory activities) even after incorporation of the aforementioned four other types of variations jointly. In contrast, the results from the full model reveal that most types of unobserved variations (especially the intraindividual variation) still dominate in the total variation even after the relevant observed information is introduced. These findings provide useful insights into both model development and data collection methods as well as to the understanding of the mechanisms of time use decisions.

Investigating multiple activity participation and time-use decisions by using a multivariate Kuhn-Tucker demand system model

This paper investigates time allocation behavior in activity planning. Considering a 7-day planning period, the paper empirically investigates time allocation behavior with respect to non-skeletal activity types. Non-skeletal activities indicate all activities except work/school activities. Activities under consideration are classified into 15 generic types and in addition to these; the econometric method used in this paper allows consideration of all other undefined/unplanned activities as a ‘composite activity’ within the time-budget. The concept of activity utility is used to model the perception of individual activity types. Activity-type indicator variables are used to investigate inter-activity relationships in baseline preference and time allocation. CHASE survey data collected in Toronto are used to estimate the empirical model. All parameters of the model are considered to be distributed multivariate normal. Bayesian estimation technique is used to estimate the large number of parameters resulting from the multivariate distribution assumption of the parameters. The estimated model reveals considerable behavioral insight into the time allocation among different activity types.

Estimating labour supply elasticities under rationing: a structural model of time allocation behaviour

Abstract This paper presents a structural model of the allocation of time to various non‐market activities and market work by couples and single men and women. Parameters are estimated using a sample taken from the UK 2000 Time Use Survey. Own‐wage effects are found to be positive for both men and women and are larger for cohabiting individuals than for singles. The presence of young children leads to a much larger increase in the time spent in home production by women than by men. However, the presence of young children causes men to increase their total time spent working by more than women.

Time allocation and vigilance behaviour of Greater Flamingos (Phoenicopterus roseus) wintering in the Gulf of Gabès, Tunisia

We studied time allocation and vigilance behaviour of Greater Flamingos (Phoenicopterus roseus) wintering in the Gulf of Gabès. In particular, we tested the relationships between time devoted to vigilance and that devoted to foraging and sleeping, and investigated variation in individual vigilance level with group size and group activity. Our results suggest that vigilance behaviour is costly for flamingos wintering in the Gulf of Gabès, in that significant trade-offs were found between vigilance and foraging, and between vigilance and sleeping. We also found that vigilance level of individual flamingos was dependent on group activity and group size. Overall, flamingos were most vigilant during mixed activities and vigilance level increased with group size. The latter result could be due to the increase in competition and social friction with group size. Nous avons étudié l'allocation du temps et la vigilance chez le flamants rose (Phoenicopterus roseus) hivernant dans le Golfe de Gabès. En particulier, nous avons examiné la relation entre la vigilance et les autres principales activités des individus, à savoir l'alimentation et le repos, et nous avons testé les effets de la taille du groupe et de son activité sur le degré de vigilance des individus. Globalement, nos résultats suggèrent que la vigilance est coûteuse pour les flamants roses, dans la mesure où elle réduit le temps alloué à l'alimentation et celui alloué au repos. D'autre part, la vigilance individuelle semble dépendre de la taille du groupe et de son activité générale. C'est en effet au cours des activités mixtes et au sein des groupes nombreux que les individus semblent les plus vigilants. Ce dernier résultat serait du à l'augmentation de l'intensité de la compétition et des frictions entre les individus avec la taille du groupe.

On altruists and egoists in activity participation and travel: who are they and do they live together?

Formulation and specification of activity analysis models require better understanding of time allocation behavior that goes beyond the more recent within household analyses to understand selfish and altruistic behavior and how this relates to travel behavior. Using data from 1,471 persons in a recent 2-day time use/activity diary and latent class cluster analysis we identify 11 distinct daily behaviors that span from the intensely self-serving to intensely altruistic. Predicted cluster membership is then used to study within household interactions. The analysis shows strong correlation exists between social role and patterns of altruistic behavior. However, a substantial amount of heterogeneity is also found within social roles. In addition, travel behavior is also very different among altruistic and self-serving time allocation groups. At the household level, a substantial number of households contain persons with similar behavior. Another group of households contains a mix of self-serving and altruistic persons that follow specialized household roles within their households. The majority of households, however, are populated by altruistic persons. Single person households are more likely to be in the self-serving groups but not in their entirety. Altruism at home is directed most often toward the immediate family members. This is less pronounced when we examine altruistic acts outside the home.

Modeling Individuals' Frequency and Time Allocation Behavior for Shopping Activities Considering Household-Level Random Effects

A comprehensive frequency and time allocation modeling system for shopping activities is described. The modeling system is person-based but explicitly considers fixed and random household effects. It has three components: a weekly shopping frequency model, a daily shopping frequency model, and a time allocation model for individual shopping episodes. The frequency models consider activity generation as a latent response—the propensity to participate in shopping activities. This latent response is modeled by using an ordinal response model. Both the weekly and daily frequency models are multilevel ordinal logit models, in which the household is the highest level and the individual is the lowest level. The multilevel ordinal logit models incorporate household-level influences on an individual's shopping behavior in terms of fixed effects and a random intercept. The time allocation models are hazard duration models that consider household-level random heterogeneity. The entire modeling system is sequential f...