An Integrated Logistic Model for Predictable Disasters

In the aftermath of a disaster, the relief items are transported from temporary warehouses (Staging Areas, SAs) to the Points of Distribution (PODs). Reducing the response time to provide relief items to disaster victims and cost minimization are two important objectives of this study. We propose an integrated optimization model for simultaneously determining (1) locations of staging areas, (2) inventory assignments to these SAs, (3) selecting sizes and numbers of trucks, and (4) routing of trucks from SAs to PODs. We also introduce another variable, a value function, which forces the model to reduce the logistics response time. We study the interactions among these variables through extensive sensitivity analysis. The time horizon for supply of relief items to disaster areas is usually limited to six days after the disaster occurs. Therefore, we use the proposed optimization model in a rolling‐horizon manner, one day at a time. This reduces daily demand uncertainty. We analyze three disaster scenarios: (1) a low impact disaster, (2) a medium impact disaster, and (3) a high impact disaster. We conduct 720 experiments with different parameter values, and provide answers to the following questions that are useful for the logistic managers: (i) What are the right sizes (in terms of storage capacities) of SAs closer to the PODs? (ii) How should the budget be allocated in a disaster scenario? (iii) What mix of different types (in terms of sizes) of trucks should be selected in a given scenario? The most important managerial insights include: (i) operational budget beyond a limit does not improve the operational efficiency, (ii) when the budget is very low, it is essential to select smaller SAs close to the PODs in order to carry out operations in a feasible manner, (iii) when the impact of disaster is high, it is always beneficial to select larger SAs close to the PODs (as long as the budget is not very low), (iv) when the budget is high and the impact of disaster is not very high, the emergency management administrators need to select SAs prudently based on the tradeoff between the operational cost and the humanitarian value, and (v) the cost of operations is higher when all the trucks are of the same type compared to the case when there is a mix of different types of trucks. Also, we find that the optimal selection of SAs is not impacted by different combinations of the types of trucks. The focus of this study is on disasters that can be forecasted in advance and provide some lead time for preparations, for example, hurricanes. In order to understand the disaster management process of such disasters and develop our model, we (i) interviewed several emergency management administrators, and (ii) studied the disaster management processes available in documents released by various government agencies.     

Supply Constraint from Earthquakes in Japan in Input–Output Analysis

Disasters often cause exogenous flow damage (i.e., the [hypothetical] difference in economic scale with and without a disaster in a certain period) to production (“supply constraint”). However, input-output (IO) analysis (IOA) cannot usually consider it, because the Leontief quantity model (LQM) assumes that production is endogenous; the Ghosh quantity model (GQM) is considered implausible; and the Leontief price model (LPM) and the Ghosh price model (GPM) assume that quantity is fixed. This study proposes to consider a supply constraint in the LPM, introducing the price elasticity of demand. This study uses the loss of social surplus (SS) as a damage estimation because production (sales) is less informative as a damage index than profit (margin); that is, production can be any amount if without considering profit, and it does not tell exactly how much profit is lost for each supplier (upstream sector) and buyer (downstream sector). As a model application, this study examines Japan's largest five earthquakes from 1995 to 2017 and the Great East Japan Earthquake (GEJE) in March 2011. The worst earthquake at the peak tends to increase price by 10–20% and decrease SS by 20–30%, when compared with the initial month's prices/production. The worst damage tends to last eight months at most, accumulating 0.5-month-production damage (i.e., the sum of [hypothetical] differences in SS with and without an earthquake [for eight months] is 50% of the initial month production). Meanwhile, the GEJE in the five prefectures had cumulatively, a 25-month-production damage until the temporal recovery at the 37th month.     

Closed-loop supply chain configuration for new and reconditioned products: An integrated optimization model

Closed-Loop Supply Chain Management (CLSCM) is considered as a strategic response to the call for corporate sustainability while further expanding the scope of value creation to include product reconstruction. The Closed-Loop Supply Chain (CLSC) performance is directly related to the CLSC network design. The CLSC network design, with long-term and strategic connotations, involves selection of an integrated network of partner organizations to be engaged on one hand in the forward supply chain processes relevant to families of existing and new products and also involved in reverse supply chain activities relevant to reconstruction of the returned products. At the tactical level, Closed-Loop Supply Chain Configuration (CLSCC) attempts to address issues pertinent to launch of a new product and its reconstruction. The CLSC network design is well studied in the current literature, but addressing the CLSCC is neglected. To study the CLSCC problem we: (a) develop an integrated optimization model for problem; (b) present a real-world case study of a battery manufacturer; (c) based on the case study, we conduct a comprehensive set of computational experiments followed by a series of what-if analyses to compare profitability of the Forward Supply Chain Configuration (FSCC) versus the CLSCC; and (c) discuss the key observations and managerial implications drawn from the computational experiments, applicable to other real-world instances. The significant outcomes of the study suggest that: (i) performance of the firm׳s base case integrated CLSCC model is significantly better than the current supply chain model (ii) the sales-price ratio of new battery is found to be negatively related with the maximum acquiring price of used batteries; (iii) combination of sales price ratios of new and reconditioned batteries determines the total net profit for a given return rate. Finally, important managerial insights and scope for future research are discussed.     

Falling from the top: the fired physician executive

Today's health care market is volatile, and the job of a physician executive is becoming more risky. Recognizing signs of trouble and taking immediate action is essential. Ten early warning signs that you could be fired are: (1) Net profits dip unexpectedly; (2) investment income can't cover operating losses; (3) bond rating is downgraded; (4) revenues are not rising as fast as costs; (5) senior executives leave the team; (6) wage increases don't improve nursing vacancy rate; (7) unions begin whisper campaign; (8) medical staff elect an SOB; (9) hospital is slapped with a costly lawsuit; and (10) recruiters call to check on your status. Physician executives are quickly learning what it takes to overcome tough challenges and prevent premature job termination: Communication; no-surprise performance; continuous monitoring of key indicators; openness and plain talk; and no-more-business-as-usual attitude. What can you do to make your job loss as painless as possible? (1) Negotiate a contract upfront; (2) don't lose your temper; (3) ask for your wish list quickly; (4) be reluctant to sue your former employer; (5) tell your family as soon as possible; (6) take only a brief vacation; (7) consider a temporary assignment; (8) be prepared to be re-employed by your former employer; and (9) keep a positive attitude.     

Assessing the Performance of a Classification‐Based Vulnerability Analysis Model

In this article, a classification model based on the majority rule sorting (MR‐Sort) method is employed to evaluate the vulnerability of safety‐critical systems with respect to malevolent intentional acts. The model is built on the basis of a (limited‐size) set of data representing (a priori known) vulnerability classification examples. The empirical construction of the classification model introduces a source of uncertainty into the vulnerability analysis process: a quantitative assessment of the performance of the classification model (in terms of accuracy and confidence in the assignments) is thus in order. Three different app oaches are here considered to this aim: (i) a model–retrieval‐based approach, (ii) the bootstrap method, and (iii) the leave‐one‐out cross‐validation technique. The analyses are presented with reference to an exemplificative case study involving the vulnerability assessment of nuclear power plants.     

A simulation testing and analysis of aggregate production planning strategies

In this study, a hybrid discrete event simulation (DES) and system dynamics (SD) methodology is applied to model and simulate aggregate production planning (APP) problem for the first time. DES is used to simulate operational-level and shop-floor activities incorporated into APP and estimate critical time-based control parameters used in SD model of APP and SD is used to simulate APP as a collection of aggregate-level strategic decisions. The main objective of this study is to determine and analyse the effectiveness of APP strategies regarding the Total Profit criterion by developing a hybrid DES–SD simulation model for APP in a real-world manufacturing company. The simulation results demonstrated that the priority of APP strategies with regards to Total Profit criterion is: (1) the pure chase strategy, (2) the modified chase strategy, (3) the pure level strategy, (4) the modified level strategy, (5) the mixed strategy and (6) the demand management strategy, respectively. The APP system is first simulated under mixed strategy (basic scenario) conditions to include all APP capacity and demand options in constructed SD simulation model to show a comprehensive view of APP components and their interdependent interactions. Then, the obtained results will be used as Total Profit measure to compare with system's performance under some experimental scenarios applying different APP strategies.     

Multi-objective machine-component grouping in cellular manufacturing: A genetic algorithm

The cellular manufacturing system (CMS) is an important group technology (GT) application. The first step of CMS design is cell formation, generally known as machinecell formation (MCF) or machine-component (MCG). A genetic algorithm (GA) is a robust adaptive optimization method based on principles of natural evolution and is appropriate for the MCG problem, which is an NP complete complex problem. In this study, we propose a GA-based procedure to solve the MCG problem. More specifically, this study aims to minimize (1) total cost, which includes intercell and intracell part transportation costs and machines investment cots; (2) intracell machine loading imbalance; and (3) intercell machine loading imbalance under many realistic considerations. An illustrative example and comparisons demonstrate the effectiveness of this procedure. The proposed procedure is extremely adaptive, flexible, efficient and can be used to solve real MCG problems in factories by providing robust manufacturing cell formation in a short execution time.     

Fired? Here's an exit strategy

Who gets fired in a boom job market? People are fired more often for things they failed to do than for mistakes they made. The new rules of engagement are: There is no probationary period; resistance to technology is a quick ticket out; a lack of emotional commitment to the role you're hired to play is usually fatal; personality defects that keep others from producing are not tolerated. The most common reason for being fired, however, is lack of fit. Whether you're laid off or fired, don't ask for explanations. The fact is, the people with the power to get rid of you don't want you to stay. What matters is maximizing what they'll do for you on departure. To get the most favorable terms with the least financial and ego damage, here's a game plan: (1) Get a favorable reference--in writing--from your boss; (2) gather work samples and good performance appraisals you've received; (3) negotiate for as much severance pay as possible; (4) negotiate for outplacement assistance; (5) gather contact names from co-workers; and (6) leave in style.     

A framework for sustainable forest resource allocation: A Canadian case study

This paper addresses the problem of public-owned forest resource allocation observed in Canada. An integrated framework based on mill abilities to create value (expressed as economic, environmental and social benefits) is proposed. It encompasses three phases: (1) election of sustainable allocation criteria, (2) evaluation of mill performance with regard to the allocation criteria and (3) allocation of wood volumes according to mill performance. The framework is applied to a case study proposed by Ministry of Forests, Fauna and Parks (MFFP) in Québec. It is implemented as follows: first, the international standards, Forest Stewardship Council (FSC) and Global Reporting Initiative (GRI) are used to identify relevant allocation criteria covering the three sustainability dimensions (economy, environment and society). Second, the Group-Analytic Hierarchy Process (Group-AHP) is used to weight the allocation criteria and evaluate mill sustainability performance. Finally, optimization models are formulated to allocate the wood following two strategies: (1) maximizing the total created value by all mills and (2) promoting inter-firm fairness. The numerical results show that integrating sustainability concerns in the evaluation process has a significant impact on the allocation decisions. Moreover, adopting a wood allocation strategy seeking to guarantee fairness between forest companies is a win–win strategy as it also leads to maximizing the created value with a minimum deviation from the optimal targeted value. Lessons learned from this collaboration with MFFP are presented in order to help other interested researchers and public organizations develop their own roadmap to sustainable public resource allocation.     

Three‐Stage Decision‐Making Model under Restricted Conditions for Emergency Response to Ships Not under Control

A ship that is not under control (NUC) is a typical incident that poses serious problems when in confined waters close to shore. The emergency response to NUC ships is to select the best risk control options, which is a challenge in restricted conditions (e.g., time limitation, resource constraint, and information asymmetry), particularly in inland waterway transportation. To enable a quick and effective response, this article develops a three‐stage decision‐making framework for NUC ship handling. The core of this method is (1) to propose feasible options for each involved entity (e.g., maritime safety administration, NUC ship, and ships passing by) under resource constraint in the first stage, (2) to select the most feasible options by comparing the similarity of the new case and existing cases in the second stage, and (3) to make decisions considering the cooperation between the involved organizations by using a developed Bayesian network in the third stage. Consequently, this work provides a useful tool to achieve well‐organized management of NUC ships.     

The ideal physician entrepreneur

How does the sometimes elusive and high-stakes world of venture capital really work? How can physician executives with innovative ideas or new technologies approach venture capitalists to help them raise capital to form a start-up company? These important questions are explored in this new column on the physician as entrepreneur. The ideal physician executive is described as: (1) an expert in an area that Wall Street perceives as hot; (2) a public speaker who can enthusiastically communicate scientific and business plans to a variety of audiences; (3) a team leader who is willing to share equity in the company with other employees; (4) a recruiter and a motivator; (5) an implementer who can achieve milestones quickly that allow the company to go public as soon as possible; and (6) a realist who does not resent the terms of the typical deal. The lucrative world of the venture capitalists is foreign territory for physician executives and requires a great idea, charisma, risk-taking, connections, patience, and perseverance to navigate it successfully.     

Classification Error in Dynamic Discrete Choice Models: Implications for Female Labor Supply Behavior

Two key issues in the literature on female labor supply are (i) whether persistence in employment status is due to unobserved heterogeneity or state dependence, and (ii) whether fertility is exogenous to labor supply. Until recently, the consensus was that unobserved heterogeneity is very important and fertility is endogenous. Hyslop (1999) challenged this. Using a dynamic panel probit model of female labor supply including heterogeneity and state dependence, he found that adding autoregressive errors led to a substantial diminution in the importance of heterogeneity. This, in turn, meant he could not reject that fertility is exogenous. Here, we extend Hyslop (1999) to allow classification error in employment status, using an estimation procedure developed by Keane and Wolpin (2001) and Keane and Sauer (2005). We find that a fairly small amount of classification error is enough to overturn Hyslop's conclusions, leading to overwhelming rejection of the hypothesis of exogenous fertility.     

A Behavioral Interpretation of Situation Awareness: Prospects for Organizational Behavior Management

Situation awareness (SA) is a construct used in human factors research and application. It is typically employed in the design of equipment to facilitate rapid and adaptive responding in dynamic and high-risk environments. Although the theory backing the SA concept is not entirely compatible with behavioral philosophy, components of the analysis and measures employed in SA work can benefit researchers and practitioners in Organizational Behavior Management (OBM). The present discussion includes (a) the definition and context for SA, (b) a behavioral interpretation of SA, (c) the assessment tools used in SA work, and (d) the relevance of SA to behavioral research. This discussion is pertinent to behavior analysts who work in industries where SA terminology is used and seek analytic tools to guide the design of effective interventions.     

Testing Models With Multiple Equilibria by Quantile Methods

This paper proposes a method for testing complementarities between explanatory and dependent variables in a large class of economic models. The proposed test is based on the monotone comparative statics (MCS) property of equilibria. Our main result is that MCS produces testable implications on the (small and large) quantiles of the dependent variable, despite the presence of multiple equilibria. The key features of our approach are that (i) we work with a nonparametric structural model of a continuous dependent variable in which the unobservable is allowed to be correlated with the explanatory variable in a reasonably general way; (ii) we do not require the structural function to be known or estimable; (iii) we remain fairly agnostic on how an equilibrium is selected. We illustrate the usefulness of our result for policy evaluation within Berry, Levinsohn, and Pakes's (1999) model.     

Retailer's Response to Alternate Manufacturer's Incentives Under a Single‐Period,Price‐Dependent,Stochastic‐Demand Framework*

This article considers the joint development of the optimal pricing and ordering policies of a profit‐maximizing retailer, faced with (i) a manufacturer trade incentive in the form of a price discount for itself or a rebate directly to the end customer; (ii) a stochastic consumer demand dependent upon the magnitude of the selling price and of the trade incentive, that is contrasted with a riskless demand, which is the expected value of the stochastic demand; and (iii) a single‐period newsvendor‐type framework. Additional analysis includes the development of equal profit policies in either form of trade incentive, an assessment of the conditions under which a one‐dollar discount is more profitable than a one‐dollar rebate, and an evaluation of the impact upon the retailer‐expected profits of changes in either incentive or in the degree of demand uncertainty. A numerical example highlights the main features of the model. The analytical and numerical results clearly show that, as compared to the results for the riskless demand, dealing with uncertainty through a stochastic demand leads to (i) (lower) higher retail prices if additive (multiplicative) error, (ii) lower (higher) pass throughs if additive (multiplicative) error, (iii) higher claw backs in both error structures wherever applicable, and (iv) higher rebates to achieve equivalent profits in both error structures.     

Addressing Nonlinearity in the Exposure-Response Relationship for a Genotoxic Carcinogen: Cancer Potency Estimates for Ethylene Oxide

Ethylene oxide (EO) has been identified as a carcinogen in laboratory animals. Although the precise mechanism of action is not known, tumors in animals exposed to EO are presumed to result from its genotoxicity. The overall weight of evidence for carcinogenicity from a large body of epidemiological data in the published literature remains limited. There is some evidence for an association between EO exposure and lympho/hematopoietic cancer mortality. Of these cancers, the evidence provided by two large cohorts with the longest follow-up is most consistent for leukemia. Together with what is known about human leukemia and EO at the molecular level, there is a body of evidence that supports a plausible mode of action for EO as a potential leukemogen. Based on a consideration of the mode of action, the events leading from EO exposure to the development of leukemia (and therefore risk) are expected to be proportional to the square of the dose. In support of this hypothesis, a quadratic dose-response model provided the best overall fit to the epidemiology data in the range of observation. Cancer dose-response assessments based on human and animal data are presented using three different assumptions for extrapolating to low doses: (1) risk is linearly proportionate to dose; (2) there is no appreciable risk at low doses (margin-of-exposure or reference dose approach); and (3) risk below the point of departure continues to be proportionate to the square of the dose. The weight of evidence for EO supports the use of a nonlinear assessment. Therefore, exposures to concentrations below 37 microg/m3 are not likely to pose an appreciable risk of leukemia in human populations. However, if quantitative estimates of risk at low doses are desired and the mode of action for EO is considered, these risks are best quantified using the quadratic estimates of cancer potency, which are approximately 3.2- to 32-fold lower, using alternative points of departure, than the linear estimates of cancer potency for EO. An approach is described for linking the selection of an appropriate point of departure to the confidence in the proposed mode of action. Despite high confidence in the proposed mode of action, a small linear component for the dose-response relationship at low concentrations cannot be ruled out conclusively. Accordingly, a unit risk value of 4.5 x 10(-8) (microg/m3)(-1) was derived for EO, with a range of unit risk values of 1.4 x 10(-8) to 1.4 x 10(-7) (microg/m3)(-1) reflecting the uncertainty associated with a theoretical linear term at low concentrations.     

The Role of Environmental Accidental Risk Assessment in the Process of Granting Development Consent

Environmental impact assessment (EIA) is a procedure that must be followed for certain types of development before they are granted development consent. The procedure requires the developer to compile an environmental impact report (EIR) describing the likely significant effects of the project on the environment. A regulatory requirement in Slovenia is that an accidental risk assessment for a new installation should be a part of an EIR. The article shows how risk assessment (RA) related to accidental release of methylene diphenyl diisocyanate (MDI) or a polyvalent alcohol mixture from a new planned unit of a chemical factory in the Alpine region of Slovenia was performed in the framework of an EIA for the purpose of obtaining a construction permit. Two accidental scenarios were considered: (a) a spill of 20 m³ of MDI or polyvalent alcohol mixture into the river Soča (the river runs close to the chemical factory) and (b) a fire in the warehouse storing the raw material, where emission of toxic gases HCN, NO_x, and CO is expected during combustion of MDI. One of the most important results of this case is the agreement among the developer, the competent authority, and a consultant in the field of EIA and RA to positively conclude the licensing process despite the absence of formal (regulatory) limit values for risk. It has been approved that transparent, reasonably uncertain, and semi-quantitative environmental risk assessment is an inevitable component of an EIA, and an essential factor in informed, licensing-related decision making.     

Supplier involvement in integrated product development: evidence from a group of Italian SMEs

Integrated product development (IPD) is gaining increased attention from practitioners and the academic community as a source of innovation and competitive advantage. However undeniable the importance of the issue is as to how the different actors involved in the process interact among themselves and the supporting factors not being well understood even in the SME context, the availability of empirical research and a comprehensive framework to drive this research remains unavailable. This article contributes to these research gaps by providing theoretical and empirical findings. First, a research framework on IPD is identified. The proposed framework represents a conceptualisation of IPD principles as consisting of three groups of integration enablers, which aim to achieve high internal (among departments) and external (with suppliers and customers) integration: (a) organisational enablers, (b) technological enablers and (c) methodologies. Then, a multiple case study approach is used in order to empirically explore external integration with suppliers in product development in 22 SMEs from the machine tool sector.     

Cost‐Effective Application of Thermal Protection on LPG Road Transport Tanks for Risk Reduction Due to Hot BLEVE Incidents

A simplified risk and cost‐benefit analysis is presented for the application of thermal protection (TP) on propane and LPG highway tanker trucks operating in North America. A risk analysis is performed to determine the benefits of risk reduction by TP, relative to the costs of applying and maintaining TP on a tanker truck. The results show that TP is cost effective if the tanker truck spends enough time (or travels enough distance) in areas of moderate or high population density. The analysis is very sensitive to a number of inputs, including: (i) value of life, (ii) hot boiling liquid expanding vapor explosion frequency, (iii) public exposure to severe hazards, and (iv) life cost of TP. With this simplified analysis, it is possible to generate tanker truck exposure times to the public that justify the application of TP based on cost and benefit considerations.