The Individually Responsible and Rational Decision Approach to Economic Lot Sizes for One Vendor and Many Purchasers: A Comment*

Joglekar and Tharthare [6] presented an alternate approach for minimizing total inventory carrying and ordering costs of a vendor and the purchaser(s). This approach permits the vendor and the purchaser(s) to rationally select their operating policies. Joglekar and Tharthare claimed that their approach is more economical than the joint lot-size approach. In this note we identify some conceptual issues in their approach and demonstrate the superiority of the joint lot-size approach with the help of an example.     

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.     

First passage game

Appealing to the theory of stochastic games, a two-person, zero-sum first passage game, which may be viewed as a generalization of the first passage decision problem, is developed. In the first passage game, the players have stationary optional strategies and the values are unique and these can be computed using an algorithm for terminating stochastic games. It is also shown that the solution of a recurrence game is closely related to that of the first passage game. Finally, it is shown that a finite step stochastic game with nonstationary transition probabilities and payoffs can be converted to a first passage game whose solution yields a solution of the original finite step game. The first passage game so obtained has stationary transition probabilities and payoffs. Because of its special structure, the solution method reduces to a dynamic programming recursion in the context of games.     

The state and civil society in disaster response: post-tsunami experiences in Tamil Nadu

This paper, based on the report "The State and Civil Society in Disaster Response: An Analysis of the Tamil Nadu Tsunami Experience," (Srinivasan, Nagaraj, & Venkatesh, 2005) is essentially an empirical analysis of state and civil society responses in Tamil Nadu (India) to the tsunami of December 26, 2004. It examines interventions by state and non-state agencies, as well as people's experiences in the relief and rehabilitation phases to identify factors influencing both positive and negative outcomes of the tsunami response. Issues related to vulnerability and exclusion, equity, transparency and accountability in different sectors of disaster intervention are explored to highlight themes revolving around reach and efficacy of relief and recovery processes. These analyses bring out some interesting lessons with regard to the importance of institutional autonomy, non-politicized decision-making, and synergetic state-civil society interfaces in fostering inclusive, transparent and accountable rehabilitation processes. The roles played by institutional responsiveness and flexibility in shaping an effective disaster response also emerge very clearly from this study of the Tamil Nadu experience. Another crucial finding points to the need for detailed, reliable and disaggregated geo-demographic and socioeconomic records as a resource base for informing relief and rehabilitation interventions. The study draws extensively from the experiences and insights of people affected by, and involved in tsunami response, and from secondary knowledge resources available on the disaster.     

Exploring the Feasibility of Farmers' Rights

In many developing countries, there is concern that a conventional system of plant breeders' rights provides no rewards to farmers for their role in the conservation and enhancement of agro‐biodiversity. To redress this imbalance, developing countries are incorporating farmers' rights provisions in their plant variety protection legislation. This article examines the feasibility of farmers' rights provisions based on intellectual property rights. It argues that the farmers' rights provisions crafted by some developing countries will involve enormous operational difficulties, while IPR‐based farmers' rights are unlikely to provide significant economic returns to farmers or farming communities. At the same time, farmers' rights provisions, as currently conceived, are likely significantly to dilute the incentives for innovation provided to institutional plant breeders.     

Value of and Interaction between Production Postponement and Information Sharing Strategies for Supply Chain Firms

We analyze the value of and interaction between production postponement and information sharing, which are two distinct strategies to reduce manufacturers’ uncertainty about demand. In both single‐level and two‐level supply chains, from the manufacturer's perspective, while information sharing is always valuable, production postponement can sometimes be detrimental. Furthermore, the value of production postponement is not merely driven by savings in inventory holding cost as postponement enables the manufacturer to avoid both excess and shortfall in production. We find that production postponement and information sharing strategies may substitute, complement, or conflict with each other, depending on the extent of the increase in the unit production cost when production is postponed. In a two‐level supply chain, from the retailer's perspective, information sharing and production postponement can be beneficial or detrimental. When information sharing is beneficial to the retailer, the retailer always shares her demand information with the manufacturer voluntarily. In addition, this voluntary information sharing is truthful because inflated or deflated demand information hurts the retailer through a higher wholesale price or a stock‐out. However, the retailer never shares her demand information voluntarily if the manufacturer has already adopted production postponement because production postponement and information sharing strategies always conflict with each other. Even when the retailer does not benefit from information sharing, we show that the manufacturer can always design an incentive mechanism to induce the retailer to share the demand information, irrespective of whether the manufacturer has already implemented production postponement or not. The above findings underscore the need for a careful assessment of demand uncertainty‐reduction strategies before the supply chain players embark upon them.     

Some problems in determining the number of acceptors needed in a family planning programme to achieve a specified reduction in the birth rate

Abstract The paper attempts to revive professional interest in a problem originally considered by Lee and Isbister and which has assumed added importance recently because of the increasing number of national family planning programmes that are being instituted, which require the determination of the number of acceptors needed in a family planning programme in order to achieve a specified reduction in the birth rate. The publication of subsequent papers on births averted by programmes, notably by Potter and Wolfers, each of whom had made some criticisms of the paper by Lee and Isbister, has tended to obscure the differences in the nature between the problem raised by Lee and Isbister, and that discussedby Potter or Wolfers. The paper tries to bring out these differences and points out one of the limitations of the estimates of births averted obtained by using either Potter's or Wolfers's methods, viz. the inability to determine the time period to which the birth reduction refers, thereby further complicating the issues involved in assessing the social and economic implications of births averted by a family planning programme. The paper also points out some of the unrecognizedtechnical considerations which arise in dealingwith the 'target-setting' problem raised by Lee and Isbister and suggeststhat stochasticmodel studies might offera clue for evolving practical methods for tackling this problem.     

Self‐consistent estimation of mean response functions and their derivatives

Many methods have been developed for the nonparametric estimation of a mean response function, but most of these methods do not lend themselves to simultaneous estimation of the mean response function and its derivatives. Recovering derivatives is important for analyzing human growth data, studying physical systems described by differential equations, and characterizing nanoparticles from scattering data. In this article the authors propose a new compound estimator that synthesizes information from numerous pointwise estimators indexed by a discrete set. Unlike spline and kernel smooths, the compound estimator is infinitely differentiable; unlike local regression smooths, the compound estimator is self‐consistent in that its derivatives estimate the derivatives of the mean response function. The authors show that the compound estimator and its derivatives can attain essentially optimal convergence rates in consistency. The authors also provide a filtration and extrapolation enhancement for finite samples, and the authors assess the empirical performance of the compound estimator and its derivatives via a simulation study and an application to real data. The Canadian Journal of Statistics 39: 280–299; 2011 © 2011 Statistical Society of Canada