Intra-household task allocation in online grocery shopping: Together alone

This paper explores how households organize the process of e-grocery buying in a click-and-collect context, down to the level of the two main subtasks: the online ordering and the picking-up. Self-collected survey data on 112 users of Belgian click-and-collect services first provide a quantitative perspective. But we primarily exploit in-depth interviews with 15 households. Both our quantitative and qualitative findings indicate that women today are still the main responsible for grocery shopping, even in an online context. Especially the ordering is a woman's task; the collecting is more equally divided across genders. But the key result is that couples exploit the opportunities for further task division provided by e-grocery shopping. In our survey we find that in 72.5% of the couples both partners are involved in the process, but that in roughly three quarters of these cases at least one of the tasks is performed independently. In other words, many couples do it ‘together alone’. Our qualitative analysis further shows that the roles of the partners have become more fixed, in that subtasks are assigned exclusively to one partner. As for the reasons behind the task allocation, we find indications of the relevance of time availability, relative resource, and gender arguments (respectively, the presence of young children, imbalances in educational status and income, and traditional roles), but also of purely pragmatic reasons.     

Attention allocation and international stock return comovement: Evidence from the Bitcoin market

We employ extreme Bitcoin returns as exogenous shock events to investigate the impact of investor attention allocation on worldwide stock return comovement. We find that (1) these shock events decrease worldwide stock return comovement, (2) there is an asymmetric effect in which a crash shock event has a greater impact on return comovement than a jump shock event, and (3) the impact of these shock events on equity comovement is more pronounced in emerging markets. Our results suggest that identifying extreme Bitcoin returns will benefit portfolio construction. Our results may be of considerable interest to investors, as well as to academics interested in portfolio diversification, asset comovement, and cryptocurrencies.     

Age‐Dependent Increasing Risk Aversion and the Equity Premium Puzzle

We introduce a new preference structure—age‐dependent increasing risk aversion (IRA)—in a three‐period overlapping generations model with borrowing constraints, and examine the behavior of equity premium in this framework. We find that IRA preferences generate results that are more consistent with U.S. data for the equity premium, level of savings and portfolio shares, without assuming unreasonable levels of risk aversion. We find that the relative difference between the two risk aversions (how much more risk‐averse old agents are relative to the middle‐aged) matters more than the average risk aversion in the economy (how much more risk‐averse both cohorts are). Our findings are robust with respect to a number of model generalizations.     

A credibility-based multi-objective temporary logistics hub location-allocation model for relief supply and distribution under uncertainty

Disaster response operations revolve around uncertainties. While uncertainties arising due to randomness can be avoided for post-disaster location problem, those arising because of impreciseness may persist long after the disaster's occurrence. Despite the uncertainties and lack of sufficient information about the extent of the damage, disaster response facilities must be established quickly after the occurrence of the disaster. Moreover, the decisions of whether to open, where to locate, and when to open disaster response facilities are based on the amount and quality of information available during the decision-making period. To address these issues, we develop a multi-objective location-allocation model for relief supply and distribution that accounts for the imprecise and time-varying nature of different parameters and time-varying coverage, while also accommodating the subjective attributes necessary to enable establishment and operation of the temporary logistics hubs (TLHs). A credibility-based fuzzy chance-constrained programming model is employed to account for the impreciseness inherent in predicting parameter values during disaster response. The results show where, when, and how many TLHs to open and how to allocate relief supplies. Meanwhile, the sensitivity analysis provides a broader understanding of the impact of limiting the number of TLHs as well as the confidence level and the spread of the symmetric triangular fuzzy numbers on the attainment of the model objectives.     

A multi-time scale management structure for airport ground handling automation

The sustainability of air travel relies on proper and timely aircraft ground handling at airports. This research proposes a ground handling management structure which allows the automation of operations to face the growing demand for this service. It is shown how at operations level, information exchange with the airport collaborative decision-making system turns possible on-line fleet assignment to ground handling tasks. This is done by designing different heuristics for assignment of fully automated or semi-automated vehicles to ground handling tasks. Numerical results for an actual airport are presented to illustrate the potential performance of automated ground handling operations.     

Optimal effort in the principal-agent problem with time-inconsistent preferences

This paper incorporates an agent’s time-inconsistent preferences into the Sannikov (2008) contract model to explore the effects of an agent’s preferences on his own behaviors: the incentive effort choice, the optimal retirement time and the consumption flow during his whole career life. We find the agent’s time inconsistency makes it difficult for him to be motivated and makes him need more compensation. An agent’s time-inconsistency erodes both the principal and his own income. The time-inconsistent agent will choose a lower incentive effort level, retire at an earlier time and have a lower consumption flow compared with his time-consistent peer. The time-inconsistent preference exactly influences the agents behavior and makes the agency problem more serious. Therefore, the firm has to cost more to stimulate such a time-inconsistent agent, which will damage the firms profits, as well as the efficiency.     

Mathematical programming for nominating exchange students for international universities: The impact of stakeholders’ objectives and fairness constraints on allocations

We consider the problem of nominating exchange students to attend international universities where places are limited. We take into account three objectives: The sending university aims to maximize the number of nominations, the students seek nomination for a highly preferred university and, finally, the receiving universities strive for excellent incoming students. Pairwise comparison of students should guarantee the following fairness: A student with higher academic achievements should be preferred over a student with lower academic achievements. We provide mathematical programming models of the nomination problem which maximize the overall objectives and guarantee different types of pairwise fairness. Several years of real data from a major school are employed to evaluate the models’ performance including a benchmark against the heuristic that is used by the school. We show analytically and experimentally that the heuristic approach fails to guarantee some pairwise fairness. Our results reveal the following four insights: First, compared to the current approach, up to 6.6% more students can be nominated with our optimization model while ensuring all pairwise fairness perspectives. Second, on average, students are nominated with better academic achievements. Third, the problem instances can be solved to optimality within a fraction of a second even for large-size instances comprising more than 500 students and about 150 schools offering nearly 450 exchange places. This is important for its use in practice. Last, up to 17.9% more students can be nominated when considering the overall objective to maximize nominations.     

On the optimality of social status seeking

We present an endogenous growth model in which households display their social status by holding not only capital but also bonds. According to conventional wisdom, the quest for social status provides an incentive for individuals to accumulate wealth, which stimulates economic growth and elevates it to a socially optimal level. Instead, we show that portfolio allocation is crucial to the growth-enhancing effect of the quest for social status. If households exhibit their social status by accumulating physical capital and holding government bonds, the quest for social status may not increase economic growth. As a result, social status seeking cannot achieve the social optimum. Calibrating our model to data, we find that if government bonds constitute part of the wealth for households’ quest for social status, the quest for social status decreases economic growth.     

How to build a factor portfolio: Does the allocation strategy matter?

Factor-based allocation embraces the idea of factors, as opposed to asset classes, as the ultimate building blocks of investment portfolios. We examine whether there is a superior way of combining factors in a portfolio and provide a comparison of factor-based allocation strategies within a multiple testing framework. Factor-based allocation is profitable beyond exploiting genuine risk premia, even when applying multiple testing corrections. Investment portfolios can be efficiently diversified using factor-based allocation strategies, as demonstrated by robust economic performance over various economic scenarios. The naïve equally weighted factor portfolio, albeit simple and cost-efficient, cannot be outperformed by more sophisticated allocation strategies.     

Robust martingale selection problem and its connections to the no‐arbitrage theory

We analyze the martingale selection problem of Rokhlin in a pointwise (robust) setting. We derive conditions for solvability of this problem and show how it is related to the classical no‐arbitrage deliberations. We obtain versions of the Fundamental Theorem of Asset Pricing in models spanning frictionless markets, models with proportional transaction costs, and models for illiquid markets. In all these models, we also incorporate trading constraints.