Some Comments on the Validity of EOQ Formula under Inflationary Conditions

In an earlier issue of Decision Sciences, Jesse, Mitra, and Cox [1] examined the impact of inflationary conditions on the economic order quantity (EOQ) formula. Specifically, the authors analyzed the effect of inflation on order quantity decisions by means of a model that takes into account both inflationary trends and time discounting (over an infinite time horizon). In their analysis, the authors utilized two models: Current-dollars model and Constant-dollars model. These models were derived, of course, by setting up a total cost equation in the usual manner then finding the optimum order quantity that minimizes the total cost. Jesse, Mitra, and Cox [1] found that EOQ is approximately the same under both conditions; with or without inflation. However, we disagree with the conclusion drawn by [2] and show that EOQ will be different under inflationary conditions, provided that the inflationary conditions are properly accounted for in the formulation of the total cost model.     

Construction Safety Risk Modeling and Simulation

By building on a genetic‐inspired attribute‐based conceptual framework for safety risk analysis, we propose a novel approach to define, model, and simulate univariate and bivariate construction safety risk at the situational level. Our fully data‐driven techniques provide construction practitioners and academicians with an easy and automated way of getting valuable empirical insights from attribute‐based data extracted from unstructured textual injury reports. By applying our methodology on a data set of 814 injury reports, we first show the frequency‐magnitude distribution of construction safety risk to be very similar to that of many natural phenomena such as precipitation or earthquakes. Motivated by this observation, and drawing on state‐of‐the‐art techniques in hydroclimatology and insurance, we then introduce univariate and bivariate nonparametric stochastic safety risk generators based on kernel density estimators and copulas. These generators enable the user to produce large numbers of synthetic safety risk values faithful to the original data, allowing safety‐related decision making under uncertainty to be grounded on extensive empirical evidence. One of the implications of our study is that like natural phenomena, construction safety may benefit from being studied quantitatively by leveraging empirical data rather than strictly being approached through a managerial perspective using subjective data, which is the current industry standard. Finally, a side but interesting finding is that in our data set, attributes related to high energy levels (e.g., machinery, hazardous substance) and to human error (e.g., improper security of tools) emerge as strong risk shapers.     

Contracting Under Vendor Managed Inventory Systems Using Holding Cost Subsidies

Vendor managed inventory systems are becoming increasingly popular. An important issue in implementing a vendor managed inventory scheme is the contracting terms that dictate the ownership of the inventory and the responsibility of inventory replenishment decisions. Thus the performance of a vendor managed system crucially depends on these terms and on how inventory‐related costs are shared in a supply chain. We consider a system where a manufacturer supplies a single product to a retailer who faces random demand in a competitive market. The retailer incurs a fixed cost per order, inventory holding cost, and a penalty cost for a stockout (unsatisfied demand is back‐ordered). Further, the manufacturer incurs a penalty cost when there is a stockout at the retailer and a fixed replenishment cost. We assume that the players are rational and act noncooperatively. We compare the performance of retailer managed inventory systems, where the retailer places orders and makes replenishment decisions, with vendor managed inventory systems, wherein the vendor or manufacturer makes inventory and replenishment decisions. Specifically, in the vendor managed inventory system, we propose and evaluate holding cost subsidy‐type contracts on inventories offered by the retailer to improve system performance. We evaluate this contract in the context of three widely used inventory systems—deterministic economic order quantity, continuous review (Q, r) policies, and periodic review policies—and show when such contracts may improve channel performance.     

Estimating the parameters of mixed linear models with modal estimators

This paper presents a procedure to estimate the variance components and fixed effects of mixed linear models. The mode of the joint posterior distribution of all the parameters is obtained by an iterative technique.

The proposed method is illustrated with one-way and two-fold nested random models. Two numerical examples demonstrate the iterative solution.     

The hunt for a cure for Parkinson's disease

Several exciting new scientific advances have been made in the past decade toward both understanding the causes of and finding a cure for Parkinson's disease. Heartened by an acceleration in research findings in the past several years, the government has recently called for an infusion of funds from both the National Institutes of Health and private foundations into this burgeoning area of biomedical research. Most currently available conventional treatments for the disease only temporarily delay symptom presentation while doing nothing to halt disease progression. However, the rapidly accelerating pace of research in this field has left researchers hopeful that Parkinson's will be the first major age-related neurodegenerative disease for which we have a viable cure. In this article, advances in various areas of Parkinson's disease research are reviewed.     

Bayes estimates of mixing proportions in finite mixture distributions

With reference to the problem of estimating the mixing proportions in a finite mixture distribution with known components, employing Dirichlet prior, closed form expressions for the posterior means and variances are obtained. To avoid the difficulties in computing the estimates, an approximation procedure is introduced. Numerical studies carried out for normal mixtures indicate the closeness of the approximations and their superiority over the maximum likelihood estimates at least in the case of small samples.     

Bayes estimates of mixing parameters in finite mixture diexributions

Using the ‘grouping vector’ notion and employing a Dirichlet prior to the unknown mixing parameters viz., the unknown mixing proportiona, the Bayee estimates of the mixing proportions in finite mixtures of known distributions are obtained. These estimates are based on the optimal grouping of the sample data. An algorithm is proposed to obtain the optimal grouping of the eample observations when the component densities belong to the family of densities possessing the monotone likelihood ratio property. A numerical study is carried out for the case of mixtures of two normal densities.     

New CEO Openness to Change and Strategic Persistence: The Moderating Role of Industry Characteristics

Drawing on the upper echelons, managerial discretion and strategic contingency perspectives we examine the relationships between newly chosen CEOs' openness to change and firm strategic persistence in the post-succession phase. This study is different from prior studies on the consequences of CEO succession in that it focuses on specific characteristics of the new CEO (that reflect his/her knowledge-base and cognitive orientations) and the industry context rather than purely on the event of succession. Based on a sample of 132 successions in 118 firms in the US manufacturing sector, and after controlling for industry concentration, board power, firm size and pre-succession performance, we find a negative relationship between CEOs' openness to change and post-succession strategic persistence. Interestingly, our findings indicate that this relationship is moderated by industry characteristics in that the negative association between CEO openness to change and strategic persistence is significant in high-discretion but not in low-discretion industries. Contributions of the paper to the CEO succession and strategic change literatures along with the managerial implications of our findings are discussed in the concluding section of the paper.     

A Note on “An Efficient Zero-One Formulation of the Multilevel Lot-Sizing Problem”

In a recent paper, McKnew, Saydam, and Coleman [3] presented a novel zero-one integer programming formulation of the multilevel dynamic, deterministic lot-sizing problem in assembly systems. They stated that “the relaxed linear programming solution to this formulation will always be integer’ [3, p. 280] since the constraint matrix is totally unimodular. In this note, we point out that the constraint matrix is not totally unimodular and therefore the authors’claim that a linear relaxation of the zero-one integer formulation always yields an integer solution is not true.