A Specialized Inventory Problem in Banks: Optimizing Retail Sweeps

Deposits held at Federal Reserve Banks are an essential input to the business activity of most depository institutions in the United States. Managing these deposits is an important and complex inventory problem for two reasons. First, Federal Reserve regulations require that depository institutions hold certain amounts of such deposits at the Federal Reserve Banks to satisfy statutory reserve requirements against customers' transaction accounts (demand deposits and other checkable deposits). Second, some inventory of such deposits is essential for banks to operate one of their core lines of business: furnishing payment services to households and firms. Because the Federal Reserve does not pay interest on such deposits used to satisfy statutory reserve requirements, banks seek to minimize their inventory of such deposits. In 1994, the banking industry introduced a new inventory management tool for such deposits, the retail deposit sweep program, which avoids the statutory requirement by reclassifying transaction deposits as savings deposits. This is an interesting inventory problem for fungible items, where the conversion process is reversible. We examine two methods for operating such sweeps programs within the limits of Federal Reserve regulations, and we develop a stochastic dynamic programming model to implement one such method, the threshold method.     

Complexity and Adaptivity in Supply Networks: Building Supply Network Theory Using a Complex Adaptive Systems Perspective*

Supply networks are composed of large numbers of firms from multiple interrelated industries. Such networks are subject to shifting strategies and objectives within a dynamic environment. In recent years, when faced with a dynamic environment, several disciplines have adopted the Complex Adaptive System (CAS) perspective to gain insights into important issues within their domains of study. Research investigations in the field of supply networks have also begun examining the merits of complexity theory and the CAS perspective. In this article, we bring the applicability of complexity theory and CAS into sharper focus, highlighting its potential for integrating existing supply chain management (SCM) research into a structured body of knowledge while also providing a framework for generating, validating, and refining new theories relevant to real‐world supply networks. We suggest several potential research questions to emphasize how a CAS perspective can help in enriching the SCM discipline. We propose that the SCM research community adopt such a dynamic and systems‐level orientation that brings to the fore the adaptivity of firms and the complexity of their interrelations that are often inherent in supply networks.     

Proportional odds model – a quantile approach

The paper discusses a quantile-based definition for the well-known proportional odds model. We present various reliability properties of the model using quantile functions. Different ageing properties are derived. A generalization for the class of distributions with bilinear hazard quantile function is established and the practical application of this model is illustrated with a real-life data set.     

Estimation of relative risk for events on a linear network

Motivated by the study of traffic accidents on a road network, we discuss the estimation of the relative risk, the ratio of rates of occurrence of different types of events occurring on a network of lines. Methods developed for two-dimensional spatial point patterns can be adapted to a linear network, but their requirements and performance are very different on a network. Computation is slow and we introduce new techniques to accelerate it. Intensities (occurrence rates) are estimated by kernel smoothing using the heat kernel on the network. The main methodological problem is bandwidth selection. Binary regression methods, such as likelihood cross-validation and least squares cross-validation, perform tolerably well in our simulation experiments, but the Kelsall–Diggle density-ratio cross-validation method does not. We find a theoretical explanation, and propose a modification of the Kelsall–Diggle method which has better performance. The methods are applied to traffic accidents in a regional city, and to protrusions on the dendritic tree of a neuron.

     

A mixed‐method examination of ego‐resiliency,adjustment problems,and academic engagement in children of Latino migrant farmworkers

Children from Latino migrant farmworker (LMFW) families are one of the most educationally disenfranchised and marginalized populations of students in the United States. These children face similar disadvantages to other low‐income immigrant families, but often experience unique contextual stressors due to high mobility that places them at high risk for mental health problems, risk‐taking behaviors, and poor academic engagement. Despite these high vulnerabilities few researchers have focused their efforts on LMFW children specifically, or addressed resilience factors in particular. Ego‐resiliency is an enduring psychological construct reflecting how individuals overcome day‐to‐day challenges. We used a convergent mixed method cross‐sectional design to examine the effects of LMFW children's (N = 66, ages 6–18, Mage = 12.79) depressive and conduct problems on their academic efficacy/mastery, and whether ego‐resiliency counteracted these relations. Ego‐resiliency was negatively associated with depression and conduct problems, and positively related to academic efficacy/mastery. Conduct problems were negatively related to academic efficacy/mastery, but depression was not. Ego‐resiliency also moderated the relation of depression to academic efficacy/mastery. Qualitative results provided a deeper explanation of contributing factors to LMFW children's adjustment, how adjustment problems affected their academic success, and the coping mechanisms and resilience factors used by LMFW children to overcome difficult experiences.     

Modelling lifetimes by quantile functions using Parzen's score function

The present paper introduces methods of constructing quantile functions as models of lifetimes with monotone and nonmonotone hazard functions. This is accomplished on the basis of the relationships the hazard quantile function has with the score function introduced by Parzen in connection with the tail heaviness of probability distributions. Three models illustrated here contain several existing models as particular cases. The appropriateness of the models in real situations is also demonstrated.     

Estimating P[X>Y] from exponential samples containing spurious observations

In this paper we discuss the problem of estimating P[X>Y] when X and Y are independent exponential random variables and the sample from each population contains one spurious observation. The estimates ate derived for exchangeable, identifiable and censored models and their performances are evaluated numerically.     

Bivariate extreme value distributions

Let (X_i, Y_i), i = 1, 2,…, n, be n independent observations from a bivariate population and let X_(n) = max X_i and Y_(n) = max Y_i. This article gives a necessary and sufficient condition for the weak convergence of the distribution function of (X_(n), Y_(n)) to a nondegenerate distribution.     

Coopetitive Buyer–Supplier Relationship: An Investigation of Bargaining Power,Relational Context,and Investment Strategies

This study proposes an analytical approach combined with a behavioral experiment for a joint examination of the competitive and cooperative (i.e., coopetitive) relationship between a buyer and a supplier. Specifically, the article considers the scenario in which the buyer and the supplier invest in strategic capabilities to increase their relative bargaining power. The article examines how dynamic investments in strategic assets are influenced by the locus of bargaining power and by the underlying context (synergistic vs. adversarial) of the interfirm relationship. The dynamic evolution of bargaining power is also examined. A dynamic game model is considered to examine the evolution of investment strategies in critical resources and to investigate the issues of bargaining power in a buyer–supplier dyad. Equilibrium expressions for the investment strategies of the buyer and the supplier are presented and their implications for buyer–supplier relationships are examined. The behavioral experiment complements the analytical model and examines the correspondence between optimal behavior suggested by the analytical model and the boundedly rational behavior of decision makers in an experimental context. The results from the model and behavioral experiments suggest that the strategies are a function of the risk‐adjusted returns obtained from investments. The experiment shows that, in a synergistic relational context when the buyer maintains bargaining power, the investment shifts of the buyer and the supplier accord well with theoretical predictions. In an adversarial relational context, the results of the experimental study do not correspond well with that predicted by the theoretical model. The implications of the results are discussed and directions for future research are presented.