fuzzy multi objective approach for optimal selection of suppliers and transportation decisions in an eco efficient closed loop supply chain network abstract establishment of a closed loop supply chain clsc network has attracted immense significance due to government policies and societal demand for environmental consciousness however to enhance the financial and ecological impact of the network the forward and reverse supply chain networks must integrate well so that decisions taken in both areas complement each other in this study we propose an eco efficient clsc design for extending the existing supply chain of an indian firm that assembles inkjet printers the network design is configured as a multi objective model in a multi period setting and is mathematically formulated into a mixed integer programming problem with fuzzy objectives fuzziness provides flexibility to the decision makers because they must accommodate the conflicting nature of the objectives the fuzzy multi objective model incorporates the firm s economic and environmental concerns into the decision making process by selecting environmentally responsible suppliers to procure components based on sustainable criteria choosing appropriate recovery options for end of use eou inkjet printers and planning an efficient transportation network design for reducing the carbon emission of the distribution and collection activities the uniqueness of the proposed fuzzy clsc optimization model lies in providing an integrated decision making framework that can aid the manufacturer in making crucial strategic tactical and operational decisions of optimal selection of suppliers component order allocation recovery flow allocation and vehicle routing planning the novelty of the model also lies in simultaneously minimising the overall cost of the activities undertaken maximizing the performance of the component suppliers and minimising the carbon emissions of the associated transportation activities a weighted fuzzy mathematical programming approach is utilised for generating a fuzzy properly efficient solution as the desired compromised solution for the clsc network problem configuration the relevance of the model is justified using a real data set derived from a case study of the firm based in the northern capital region ncr of india the findings indicate that the proposed integrated clsc network model enables the firm in gaining sustainably from the numerous electronic product reuse opportunities in the indian market further while costly to begin with choosing suppliers with higher sustainable performance and vehicles with lesser emission rate could substantially enhance firm s sustainable image and result in higher profits in the future

daily house price indexes construction modeling and longer run predictions we construct daily house price indexes for ten major u s metropolitan areas our calculations are based on a comprehensive database of several million residential property transactions and a standard repeat sales method that closely mimics the procedure used in the construction of the popular monthly case shiller house price indexes our new daily house price indexes exhibit similar characteristics to other daily asset prices with mild autocorrelation and strong conditional heteroskedasticity which are well described by a relatively simple multivariate garch type model the sample and model implied correlations across house price index returns are low at the daily frequency but rise monotonically with the return horizon and are all commensurate with existing empirical evidence for the existing monthly and quarterly house price series a simple model of daily house price index returns produces forecasts of monthly house price changes that are superior to various alternative forecast procedures based on lower frequency data underscoring the informational advantages of our new more finely sampled daily price series

the hyperbolic consumption model calibration simulation and empirical evaluation ur preferences for the long run tend to conflict with our short run behavior when planning for the long run we intend to meet our deadlines exercise regularly and eat healthfully but in the short run we have little interest in revising manuscripts jogging on the stairmaster and skipping the chocolate souffleala mode delay of gratification is a nice long term goal but instant gratification is disconcertingly tempting this gap between long run intentions and short run actions is apparent across a wide range of behaviors including saving choices a 1997 survey found that 76 percent of respondents believe they should be saving more for retirement looking only at respondents who believed they were at an age where you should be seriously saving already the survey found that 55 percent reported being behind in their savings and only 6 percent reported being ahead farkas and johnson 1997 the report on the survey concluded t he gaps between people s atti tudes intentions and behavior are troubling and threaten increased insecurity and dissatisfaction for people when they retire americans are simply not doing what logic and their own reasoning suggests they should be doing a 1993 luntz webber merrill lynch survey found similar answers when baby boomers were asked what percentage of your annual household income do you think you should save for retirement and what percentage of your annual

operations research for green logistics an overview of aspects issues contributions and challenges the worldwide economic growth of the last century has given rise to a vast consumption of goods while globalization has led to large streams of goods all over the world the production transportation storage and consumption of all these goods however have created large environmental problems today global warming created by large scale emissions of greenhouse gasses is a top environmental concern governments action groups and companies are asking for measures to counter this threat operations research has a long tradition in improving operations and especially in reducing costs in this paper we present a review that highlights the contribution of operations research to green logistics which involves the integration of environmental aspects in logistics we give a sketch of the present and possible developments focussing on design planning and control in a supply chain for transportation inventory of products and facility decisions while doing this we also indicate several areas where environmental aspects could be included in or models for logistics

a heuristic for single warehouse multiretailer supply chains with all unit transportation cost discounts abstract in supply chain management research transportation costs if explicitly considered at all are frequently assumed to be linear these costs often have a more complex form such as an all unit discount structure this piecewise cost function adds significant complexity when included in supply chain management problems and is therefore often ignored due to solution time or tractability concerns we present and evaluate a new heuristic procedure which provides good solutions to problems involving all unit discount cost functions while significantly reducing solution times the general nature of this procedure does not require assumptions about the supply chain structure or policies and is therefore applicable in a wide range of settings

revenue management for durable goods using trade ins with certified pre owned options abstract the economics research suggests that firms can use trade ins as a revenue management device for price discrimination between new and replacement buyers of durabprle goods offering different prices to different groups of customers creates a market segmentation effect this study examines such an effect by considering trade ins and certified pre owned options for a durable goods firm where certified pre owned cpo represents the used goods market generated from the return flow of trade in transactions the optimal pricing and or trade in rebate is determined and the strategic choice between the two options is examined an analytical model is developed that incorporates the key durable goods features into model formulation specifically the deterioration rate or durability in a reverse measure and the variation in quality of the used goods our research findings indicate that i the magnitude of trade in rebates increases with the deterioration rate and quality variation ii the segmentation effect outweighs the cannibalization effect when the deterioration rate is moderately high iii the strategic choice of trade ins and cpo options is critically dependent on these two features and iv the majority of profit improvement is generated from trade in provisions although the cpo option can serve as a second profit boosting device

the decision to move house and aggregate housing market dynamics using data on house sales and inventories this paper shows that housing market dynamics are driven mainly by listings and less so by transaction speed thus the decision to move house is key to understanding the housing market the paper builds a model where moving house is essentially an investment in match quality implying that moving depends on macroeconomic developments and housing market conditions the endogeneity of moving means there is a cleansing effect those at the bottom of the match quality distribution move first which generates overshooting in aggregate variables the model is applied to the 1995 2004 housingmarket boom

equity and time to sale in the real estate market evidence from the boston condominium market of the early 1990s reveals that an owner s equity position determines his experience as a seller an owner of a property with a high loan to value ratio sets a higher asking price has a higher expected time on the market and if he sells receives a higher price than an owner with proportionately less debt the down payment requirement for purchasers but not incumbent owners provides a simple explanation for this phenomenon among owner occupants the results provide supporting evidence for equity based aggregate theories of price volume movements in the housing market copyright 1997 by american economic association

effective location models for sorting recyclables in public management abstract the recycling of urban solid wastes is a critical point for the closing supply chains of many products mainly when their value cannot be completely recovered after use in addition to environmental aspects the process of recycling involves technical economic social and political challenges for public management for most of the urban solid waste the management of the end of life depends on selective collection to start the recycling process for this reason an efficient selective collection has become a mainstream tool in the brazilian national solid waste policy in this paper we study effective models that might support the location planning of sorting centers in a medium sized brazilian city that has been discussing waste management policies over the past few years the main goal of this work is to provide an optimal location planning design for recycling urban solid wastes that fall within the financial budget agreed between the municipal government and the national bank for economic and social development moreover facility planning involves deciding on the best sites for locating sorting centers along the four year period as well as finding ways to meet the demand for collecting recyclable materials given that economic factors consumer behavior and environmental awareness are inherently uncertain future outcomes to deal with these issues we propose a deterministic version of the classical capacity facility location problem and both a two stage recourse formulation and risk averse models to reduce the variability of the second stage costs numerical results suggest that it is possible to improve the current selective collection as well as hedge against data uncertainty by using stochastic and risk averse optimization models

a stochastic aggregate production planning model in a green supply chain considering flexible lead times nonlinear purchase and shortage cost functions in this paper we develop a stochastic programming approach to solve a multi period multi product multi site aggregate production planning problem in a green supply chain for a medium term planning horizon under the assumption of demand uncertainty the proposed model has the following features i the majority of supply chain cost parameters are considered ii quantity discounts to encourage the producer to order more from the suppliers in one period instead of splitting the order into periodical small quantities are considered iii the interrelationship between lead time and transportation cost is considered as well as that between lead time and greenhouse gas emission level iv demand uncertainty is assumed to follow a pre specified distribution function v shortages are penalized by a general multiple breakpoint function to persuade producers to reduce backorders as much as possible vi some indicators of a green supply chain such as greenhouse gas emissions and waste management are also incorporated into the model the proposed model is first a nonlinear mixed integer programming which is converted into a linear one by applying some theoretical and numerical techniques due to the convexity of the model the local solution obtained from linear programming solvers is also the global solution finally a numerical example is presented to demonstrate the validity of the proposed model

design of sustainable supply chains under the emission trading scheme increase in environmental concerns together with legislations are forcing industries to take a fresh look at the impact of their supply chain operations on the environment this paper introduces a mixed integer linear programming based framework for sustainable supply chain design that considers life cycle assessment lca principles in addition to the traditional material balance constraints at each node in the supply chain indeed the framework distinguishes between solid and liquid wastes as well as gaseous emissions due to various production processes and transportation systems the framework is used to evaluate the tradeoffs between economic and environmental objectives under various cost and operating strategies in the aluminum industry the results suggest that current legislation and emission trading schemes ets must be strengthened and harmonized at the global level in order to drive a meaningful environmental strategy moreover the model demonstrates that efficient carbon management strategies will help decision makers to achieve sustainability objectives in a cost effective manner

carbon footprint and responsiveness trade offs in supply chain network design concern related to sustainability and greenhouse gases has grown among citizens as well as firms which are increasingly committing to carbon emission reduction targets however firms emissions come from direct and indirect sources and from the different stages of their supply chain therefore comprehensive supply chain approaches are essential to ensure the cost effectiveness of carbon management strategies these approaches should capture operational and environmental trade offs arising from the interaction between different supply chain processes such as procurement manufacturing transport and inventory management considering all these processes we propose a model for supply chain network design that takes demand uncertainty into account and includes decisions on supply chain responsiveness under different carbon policies caps on supply chain carbon footprints caps on market carbon footprints and carbon taxes our model supports the analysis of the effect of different policies on costs and optimal network configuration and allows us to distinguish between different product types functional or innovative products with detailed numerical examples we illustrate the type of analysis and managerial insights that can be derived with our model which include the assessment of supply chains potential for carbon abatement the study of the effect of different carbon policies on supply chain costs and network design the analysis of the impact of various product characteristics the test of an alternative profit maximisation model and the determination of the value of a supply chain carbon tax that should induce specific levels of carbon abatement

contractual structure and wealth accumulation can historical wealth distributions affect long run output and inequality despite rational saving convex technology and no externalities we consider a model of equilibrium short period financial contracts where poor agents face credit constraints owing to moral hazard and limited liability if agents have no bargaining power poor agents have no incentive to save poverty traps emerge and agents are polarized into two classes with no interclass mobility if instead agents have all the bargaining power strong saving incentives are generated the wealth of poor and rich agents alike drift upward indefinitely and history does not matter eventually d31 d91 i32 o17 q15

accounting for the u s earnings and wealth inequality we show that a theory of earnings and wealth inequality based on the optimal choices of ex ante identical households that face uninsured idiosyncratic shocks to their endowments of efficiency labor units accounts for the u s earnings and wealth inequality almost exactly

timing and eco nomic efficiency of climate friendly investments in supply chains abstract emission trading schemes such as the european union emissions trading system euets attempt to reconcile economic efficiency with ecological efficiency by creating financial incentives for companies to invest in climate friendly innovations using real options methodology we demonstrate that under uncertainty economic and ecological efficiency continue to be mutually exclusive this problem is even worse if a climate friendly project depends on investing in of a whole supply chain we model a sequential bargaining game in a supply chain where the parties negotiate over implementation of a carbon dioxide co2 saving investment project we show that the outcome of their bargaining is not economically efficient and even less ecologically efficient furthermore we show that a supply chain becomes less economically efficient and less ecologically efficient with every additional chain link finally we make recommendations for how managers or politicians can improve the situation and thereby increase economic as well as ecological efficiency and thus also the eco efficiency of supply chains

what is the role of the asking price for a house abstract this paper considers the role of the asking price in housing transactions both theoretically and empirically significant fractions of housing transactions involve sales prices that are either below or above asking price which might suggest that asking price has limited relevance however many housing transactions involve a sales price exactly equal to asking price a fact that has previously drawn little notice strongly suggesting that asking price does matter the paper develops a model where asking price is neither a binding commitment nor a ceiling yet still directs buyer search and impacts sales price using novel survey data the paper provides empirical evidence consistent with asking price playing a directing role in buyer search consistent with theory this effect is stronger for more atypical houses and in bust markets

search liquidity and the dynamics of house prices and construction the dynamics of house prices sales construction and population growth in response to city specific income shocks are characterized for 106 us cities a dynamic model of search in the housing market in which construction the entry of buyers house prices and sales are determined in equilibrium is then developed the theory generates dynamics qualitatively consistent with the observations and a version calibrated to match key features of the us housing market offers a substantial quantitative improvement over models without search in particular variation in the time it takes to sell induces transaction prices to exhibit serially correlated growth jel d83 r21 r23 r31 we explore the consequences of time consuming search and matching for the dynamics of house prices sales and construction at the city level first we char acterize the impact of city specific income shocks on the short run dynamics of average house prices home sales construction and population growth for a panel of us cities we then develop a model in which the entry of new buyers and the construction of new houses in response to such shocks are endogenously determined our theory generates serial correlation in the growth rates of house prices and construction even if income is strictly mean reverting following shocks 1 when calibrated to data on us cities our model accounts for over 80 percent of the variance of house price movements driven by city specific income shocks and nearly half of the observed autocorrelation of house price growth in our empirical analysis we estimate a structural panel vector autoregressive var model using city level observations on the variables listed above we focus

a stochastic model for risk management in global supply chain networks abstract with the increasing emphasis on supply chain vulnerabilities effective mathematical tools for analyzing and understanding appropriate supply chain risk management are now attracting much attention this paper presents a stochastic model of the multi stage global supply chain network problem incorporating a set of related risks namely supply demand exchange and disruption we provide a new solution methodology using the moreau yosida regularization and design an algorithm for treating the multi stage global supply chain network problem with profit maximization and risk minimization objectives

a bi objective stochastic programming model for a centralized green supply chain with deteriorating products in recent years consumers and legislation have been pushing companies to design their activities in such a way as to reduce negative environmental impacts more and more it is therefore important to examine the optimization of total supply chain costs and environmental impacts together however because of the recycling of deteriorated items the environmental impacts of deteriorating items are more significant than those of non deteriorating ones the objective of this paper is to develop a stochastic mathematical model and to propose a new replenishment policy in a centralized supply chain for deteriorating items in this model we consider inventory and transportation costs as well as the environmental impacts under uncertain demand several transportation vehicles producing various greenhouse gas ghg levels are considered the best transportation vehicles and inventory policy are determined by finding a balance between financial and environmental criteria in this way we develop a linear mathematical model and present a numerical example from the real world to demonstrate its applicability and effectiveness we then perform a sensitivity analysis and provide some managerial insights finally more promising directions are suggested for future research

endogenous effective discounting credit constraints and wealth inequality models of nonexponential time discount ing help to explain a variety of regularities in economic behavior including contract choice stefano dellavigna and ulrike malmendier 2004 procrastination ted o donoghue and matthew rabin 1999 dan ariely and klaus wertenbroch 2002 and life cycle consumption patterns david laibson andrea repetto and tobacman 2007 this paper applies the quasi hyperbolic time discounting model to the study of wealth inequality a large literature analyzes the nature and causes of inequality and poverty traps 1 here first i theoretically examine a simple autarkic mechanism that can cause exogenous dispersion in wealth to persist and grow specifically quasi hyperbolic discount functions endogenously

procrastination and obedience in this lecture i shall focus on situations involving repeated decisions with time inconsistent behavior although each choice may be close to maximizing and therefore result in only small losses the cumulative effect of a series of repeated errors may be quite large thus in my examples decision makers are quite close to the intelligent well informed individuals usually assumed in economic analysis but cumulatively they make seriously wrong decisions that do not occur in standard textbook economics this lecture discusses and illustrates several pathological modes of individual and group behavior procrastination in decision making undue obedience to authority membership of seemingly normal individuals in deviant cult groups and escalation of commitment to courses of action that are clearly unwise in each case individuals choose a series of current actions without fully appreciating how those actions will affect future perceptions and behavior the standard assumption of rational forwardlooking utility maximizing is violated the nonindependence of errors in decision making in the series of decisions can be explained with the concept from cognitive psychology of undue salience or vividness for example present benefits and costs may have undue salience relative to future costs

a multi objective robust optimization model for multi product multi site aggregate production planning in a supply chain under uncertainty abstract manufacturers need to satisfy consumer demands in order to compete in the real world this requires the efficient operation of a supply chain planning in this research we consider a supply chain including multiple suppliers multiple manufacturers and multiple customers addressing a multi site multi period multi product aggregate production planning app problem under uncertainty first a new robust multi objective mixed integer nonlinear programming model is proposed to deal with app considering two conflicting objectives simultaneously as well as the uncertain nature of the supply chain cost parameters of the supply chain and demand fluctuations are subject to uncertainty then the problem transformed into a multi objective linear one the first objective function aims to minimize total losses of supply chain including production cost hiring firing and training cost raw material and end product inventory holding cost transportation and shortage cost the second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers zones in all periods working levels workers productivity overtime subcontracting storage capacity and lead time are also considered finally the proposed model is solved as a single objective mixed integer programming model applying the lp metrics method the practicability of the proposed model is demonstrated through its application in solving an app problem in an industrial case study the results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain

coordinated supply chain management abstract historically the three fundamental stages of the supply chain procurement production and distribution have been managed independently buffered by large inventories increasing competitive pressures and market globalization are forcing firms to develop supply chains that can quickly respond to customer needs to remain competitive these firms must reduce operating costs while continuously improving customer service with recent advances in communications and information technology as well as a rapidly growing array of logistics options firms have an opportunity to reduce operating costs by coordinating the planning of these stages in this paper we review the literature addressing coordinated planning between two or more stages of the supply chain placing particular emphasis on models that would lend themselves to a total supply chain model finally we suggest directions for future research

performance evaluation and a flow allocation decision model for a sustainable supply chain of an apparel industry abstract there is a growing concern that business enterprises and their supply chains focus primarily on economic activities and ignore their impact on the environment and society this paper aims to help decision makers managers and practitioners to achieve economic growth societal development and environmental protection by developing sustainable supply chain performance measures and proposes a partner selection and flow allocation decision making model survey data from 278 business organizations from the indian apparel industry supply chain network were used and an integrated method of structural equation modeling fuzzy analytical hierarchy process and fuzzy multi objective linear programming was applied to the proposed model the results of the structural equation modeling analysis indicate that the survey respondents considered sustainable production performance to be of prime importance which thus indicates its significance in developing a sustainable supply chain for the apparel industry to illustrate the use of the proposed model for partner selection and flow allocation decision making real time data from an apparel manufacturer are presented optimal results were obtained for two strategies sustainability and cost saving to show a cost benefit trade off when developing a sustainable supply chain using comparative performance a decision maker can choose an appropriate strategy based on cost benefit analysis of the presented trade offs

income and wealth heterogeneity in the macroeconomy how do movements in the distribution of income and wealth affect the macroeconomy we analyze this question using a calibrated version of the stochastic growth model with partially uninsurable idiosyncratic risk and movements in aggregate productivity our main finding is that in the stationary stochastic equilibrium the behavior of the macroeconomic aggregates can be almost perfectly described using only the mean of the wealth distribution this result is robust to substantial changes in both parameter values and model specification our benchmark model whose only difference from the representative agent framework is the existence of uninsurable idiosyncratic risk displays far less cross sectional dispersion and skewness in wealth than u s data however an extension that relies on a small amount of heterogeneity in thrift does succeed in replicating the key features of the wealth data furthermore this extension features aggregate time series that depart significantly from permanent income behavior

housing dynamics an urban approach abstract a dynamic linear rational equilibrium model in the tradition of alonso rosen and roback is consistent with many outstanding stylized facts of housing markets these include a that the markets are local in nature b that construction persistence is fully compatible with mean reversion in prices and c that price changes are predictable calibration exercises to match moments of the real data have notable successes and failures the volatility in local income processes as reflected in hmda mortgage applicant data can account for much of the observed price and construction volatility except for the most inelastically supplied local markets the model s biggest failure lies in its inability to match the strong persistence in high frequency price changes from year to year

an optimization approach for supply chain management models with quantity discount policy abstract owing to the difficulty of treating nonlinear functions many supply chain management scm models assume that the average prices of materials production transportation and inventory are constant this assumption however is not practical vendors usually offer quantity discounts to encourage the buyers to order more and the producer intends to discount the unit production cost if the amount of production is large this study solves a nonlinear scm model capable of treating various quantity discount functions simultaneously including linear single breakpoint step and multiple breakpoint functions by utilizing the presented linearization techniques such a nonlinear model is approximated to a linear mixed 0 1 program solvable to obtain a global optimum

the role of the list price in housing markets theory and an econometric model summary houses are routinely sold at prices below but rarely sold at prices above their list prices list prices appear to be price ceilings that preclude the possibility of sales at higher prices this paper presents a theory of sellers behaviour that explains why there are list prices in housing markets and why list prices are distinct from sellers reservation prices the theory forms the basis of an econometric model that has been estimated using data from the baltimore md area the estimated model predicts sale and reservation prices conditional on list prices the predictions of sale prices are considerably more accurate than those obtained from a standard hedonic price regression the estimated model also explains why sellers may not be willing to reduce their list prices even after their houses have remained unsold for long periods of time houses are routinely sold at prices below and are virtually never sold at prices above their list prices the list price of a house appears to be a price ceiling that precludes the possibility of selling at a higher price this phenomenon is stable over time so it is not caused by market disequilibrium what is the role of list prices in housing markets can list prices be used to predict sellers reservation prices can they be used to make predictions of sale prices that are more accurate than predictions obtained from standard hedonic regressions this paper develops an econometric model of the behaviour of sellers in housing markets that answers these questions the model explains why there are list prices in housing markets and how sellers establish list and reservation prices in addition the model predicts sale and reservation prices conditional on list prices the predictions of sale prices are considerably more accurate than those obtained from a hedonic price regression the model also explains why sellers may not be willing to reduce their list prices even after their houses have remained unsold for long periods of time there have been several previous attempts to model the formation of list prices in housing markets guasch and marshall 1985 and stull 1978 developed search models in which list prices must be set but these models do not admit the possibility that sale prices may bse below list prices chinloy 1980 developed a model in which the seller s reservation price is assumed to be a constant fraction of the list price but chinloy did not explain why list and reservation prices are distinct or why they are proportional to one another these difficulties are not present in the model developed in this paper the theory underlying the model is developed in section 2 the model is presented in section 3 estimation results and some applications are given in section 4 additional applications are given in section 5 and concluding comments are given in section 6

an empirical stationary equilibrium search model of the housing market this article specifies and estimates a computationally tractable stationary equilibrium model of the housing market the model is rich and incorporates many of its unique features buyers and sellers simultaneous search behavior heterogeneity in their motivation to trade transaction costs a trading mechanism with posting prices and bargaining and the availability of an exogenous advertising technology that induces endogenous matching estimation uses maximum likelihood methods and multiple listing services data the estimated model is used to simulate housing market outcomes when a the amount of information displayed on housing listings increases and b real estate agent s commission rates change

forced sales and house prices the market for housing differs in several important ways from the textbook model of a liquid asset market with exogenous fundamentals this implies that the price at which a house is sold can be influenced not only by general supply and demand conditions but also by idiosyncratic factors including the urgency of the sale and the effects of the ownership transfer on the physical quality of the house first houses are productive only when people are living in them owning an empty house is equivalent to throwing away the dividend on a financial asset second houses are fragile assets that need maintenance and are vulnerable to van dalism unoccupied houses are particularly vulnerable and expensive to protect third short term rental contracts involve high transactions costs resulting from the moving costs of renters and the need of homeowners to protect their property against damage fourth houses are expensive indivisible and heterogeneous assets each house has certain unique characteristics which are likely to appeal to certain poten tial buyers and not to others so selling a house requires matching it with an appro priate buyer because of the high costs of intermediation in housing this task is normally undertaken by a real estate broker rather than a dealer fifth most home owners must finance their purchases using mortgages collateralized debt contracts that transfer home ownership to the mortgage lender through a foreclosure process if the homeowner defaults the expansion of mortgage credit in the early 2000s and the recent decline in house prices have led to an unprecedented increase in foreclosures since 2006 foreclosures transfer houses to financial institutions which must maintain and pro tect them until they can be sold foreclosed houses are likely to sell at low prices both because they may have been physically damaged during the foreclosure pro cess and because financial institutions have an incentive to sell them quickly in a liquid market an asset can be sold rapidly with a minimal impact on its price but

assessing the impact of cost optimization based on infrastructure modelling on co2 emissions traditionally logistics design is driven by a need to reduce costs and improve customer service recently the environmental concerns from transport have been increasingly discussed the traffic levels and associated energy consumption are influenced by supply chain structure modal split and vehicle utilization this paper aims to assess the impact of the traditional cost optimization approach to strategic modelling on overall logistics costs and co2 emissions by taking into account the supply chain structure number of depots and different freight vehicle utilization ratios 90 75 and 60 the simulation model based on a european case study from the automotive industry considers strategic and operational level decisions simultaneously the analysis shows that the optimum design based on costs does not necessary equate to an optimum solution for co2 emissions therefore there is a need to address economical and environmental objectives explicitly as part of the logistics design

the reduction of greenhouse gas emissions from freight transport by pooling supply chains it is well known that freight consolidation is an effective way to improve the utilization of logistics resources in fact today this policy is locally and fragmentally implemented at the operational level we propose here to explore the environmental impact of pooling of supply chains at the strategic level merging supply chains with real data from two main french retailers and through an optimization model we compute co2 emissions for two transport modes road and rail as regards the general dependency of the emissions produced by the modes of transport on their loads the emissions functions of the two modes are both piecewise linear and discontinuous functions the supply network pooling proposed here is an efficient approach to reducing co2 emissions even if the attention is focused on the emissions the transportation costs are also studied and analyzed

waste paper procurement optimization an agent based simulation approach abstract this paper proposes an agent based simulation model to study and analyse the performance of various procurement and production policies in the recycled paper industry the proposed model includes the recycled pulp production process as well as the waste paper inventory and procurement processes a detailed simulation model developed in partnership with a large recycled pulp producer in north america was developed in order to emulate the procurement manager s behaviour therefore based on the observed behaviour of the procurement manager a procurement behaviour model which takes both market price and inventory requirement into account is introduced this paper also introduces a waste paper market model that simulates a market price and enables the control of price forecast accuracy two series of experiments were carried out in order to study the performance of procurement and production policies in several productions contexts results show that production volume flexibility has a negative impact on costs inventory and quality however it is possible to partially reduce these issues with the introduction of contracts with volume flexibility although only a limited effect has been observed in our experiments a more significant strategy to improve costs consists in reducing production rate to the minimum level required to meet demand

evolution of sustainability in supply chain management a literature review abstract an ever increasing demand for products and their consumption has put pressure on industrial output and their supply chains and that demand has resulted in negative impacts on the environment and society increasing rates of pollution and environmental calamities caused by industrial production have urged several researchers and industry experts to work on sustainable production and consumption issues within the context of sustainable supply chain management sscm this paper comprehensively covers the exponential growth of the topic through an evolutionary lens this article attempts to understand the evolution of sustainability issues by analysing trends across industries economies and through the use of various methodologies a comprehensive thematic analysis was performed on 1068 filtered articles from 2000 to 2015 highlighting the development and importance of the body of knowledge the study proposes a conceptual framework to classify various factors along the triple bottom line pillars of sustainability issues in the context of supply chains an in depth study is conducted on 190 articles covering all pillars of sustainability as per the proposed conceptual framework on sscm we observe that studies focusing on all three dimensions of sustainability are comparatively scarce more focus on industry specific studies is required because problems addressing industries that are serious polluters especially those in emerging economies remains largely unaddressed it is observed that the studies addressing social issues are scarce and more focus is required on the measurement of social impacts along the supply chain finally we propose future avenues to extend research on the sscm domain while keeping in mind the need to address industry specific and economy specific problems from the triple bottom line perspective

what accounts for the variation in retirement wealth among u s households even among households with similar socioeconomic characteristics saving and wealth vary considerably life cycle models attribute this variation to differences in time preference rates risk tolerance exposure to uncertainty relative tastes for work and leisure at advanced ages and income replacement rates these factors have testable implications concerning the relation between accumulated wealth and the shape of the consumption profile using the panel study of income dynamics and the consumer expenditure survey we find little support for these implications the data are instead consistent with rule of thumb mental accounting or hyperbolic discounting theories of wealth accumulation jel di d91 e21

a hybrid l shaped method to solve a bi objective stochastic transshipment enabled inventory routing problem abstract recently greenness has become a very much needed condition in the transportation industry in this study we develop a green transshipment enabled model for the inventory routing problem irp in a many to one distribution network where demand for each product is realistically assumed to be uncertain the proposed framework is a bi objective stochastic programming model the first objective function aims to minimize the expected value of the supply chain costs including inevitable shortage costs the second objective function aims to minimize the total quantity of the greenhouse gas ghg emission produced by the vehicles and disposed products we introduce a very practical innovative application of transshipment option to control transportation cost reduce ghg emissions and absorb the uncertainty in order to solve the proposed model an efficient hybrid algorithm combining l shaped method a sort of decomposition approach for stochastic optimization and compromise programming a well known approach for multi objective optimization is proposed the results show that how companies can make a reasonable tradeoff between the cost and environmental concerns and emphasize the role of transshipment option as a lever to improve both economic and environmental performance and absorb the demand fluctuations

environmental performance impacts of vendor buyer coordination abstract effective coordination is a hallmark of successful supply chain management without such coordination vendors and buyers will act independently to make decisions that optimize their own objectives e g maximize their respective profits or minimize their costs this non coordinated approach is unlikely to be optimal when one considers the supply chain as a whole most vendor buyer coordination research concentrates only on an objective of minimizing total system costs but with the increasing environmental awareness in business and the general public many organizations acknowledge that strategies and practices which incorporate environmental considerations are essential to acquire a competitive advantage the objectives of this research are concerned not only with the economic impact of vendor buyer coordination on the organizations involved but also with the wider effects on society such as the effects of pollution on the environment this research demonstrates how to effectively incorporate environmental issues into vendor buyer coordination first we study the impacts of cost minimizing vendor buyer coordination models on environmental performance when compared with independent non coordinated optimization second we develop a single vendor multi buyer coordination model that includes both costs and environmental performance measures in its objective function a numerical example and a real case study show how both the total system cost and the environmental performance can be simultaneously improved

the relative performance of real estate marketing platforms mls versus fsbomadison com we compare house sales on a for sale by owner fsbo platform to multiple listing service mls sales and find that fsbo precommission prices are no lower but that fsbo is less effective in terms of time to sell and probability of a sale we do not find direct evidence of the importance of network size as a reason for the lower effectiveness of fsbo we do find evidence of endogenous platform differentiation patient sellers use fsbo while patient buyers transact more often on the mls where they avoid patient sellers we discuss the implications for platform competition two sided markets and welfare

a homeowner s dilemma anchoring in residential real estate transactions abstract we examine whether and how listing strategies impact sale prices in residential home sales literatures in housing economics negotiations and auctions offer diverse predictions around this question on the one hand housing studies typically treat home prices as an objective function of property and neighborhood characteristics yet the large and robust literature on anchoring effects tversky and kahneman 1974 suggests a positive relationship between listing prices and sale prices finally evidence from the auctions literature suggests the opposite pattern through herding behaviors we analyzed more than 14 000 transactions taking into account observable property heterogeneity geographical location and timing of the sales we find that higher starting prices are indeed associated with higher selling prices consistent with anchoring for the average home in our sample over pricing between 10 and 20 leads to an increase in the sale price of 117 163 this effect is particularly strong in areas with higher rates of mortgage foreclosure or serious delinquency additional analyses show that our results are unlikely to be driven by seller motivations or unobserved home qualities we contrast our findings with recommendations and private beliefs of real estate agents who provide services and advice for about 90 of home sales in the us

hot and cold seasons in the housing market every year housing markets in the united kingdom and the united states experience systematic above trend increases in prices and transactions during the spring and summer hot season and below trend falls during the autumn and winter cold season house price seasonality poses a challenge to existing housing models we propose a search and matching model with thick market effects in thick markets the quality of matches increases rising buyers willingness to pay and sellers desire to transact a small deterministic driver of seasonality can be amplified and revealed as deterministic seasonality in transactions and prices quantitatively mimicking seasonal fluctuations in uk and us markets

modelling food logistics networks with emission considerations the case of an international beef supply chain intrinsic characteristics of food products and processes along with growing sustainability concerns lead to the need for decision support tools that can integrate economic considerations with quality preservation and environmental protection in food supply chains in this study we develop a multi objective linear programming molp model for a generic beef logistics network problem the objectives of the model are i minimizing total logistics cost and ii minimizing total amount of greenhouse gas emissions from transportation operations the model is solved with the ee constraint method this study breaks away from the literature on logistics network models by simultaneously considering transportation emissions affected by road structure vehicle and fuel types weight loads of vehicles traveled distances return hauls and product perishability in a molp model we present computational results and analysis based on an application of the model on a real life international beef logistics chain operating in nova andradina mato grosso do sul brazil and exporting beef to the european union trade off relationships between multiple objectives are observed by the derived pareto frontier that presents the cost of being sustainable from the point of reducing transportation emissions the results from the pie chart analysis indicate the importance of distances between actors in terms of environmental impact moreover sensitivity analysis on practically important parameters shows that export ports capacities put pressure on the logistics system decreasing fuel efficiency due to the bad infrastructure has negative effects on cost and emissions and green tax incentives result in economic and environmental improvement

how important is discount rate heterogeneity for wealth inequality abstract this paper investigates the role of discount rate heterogeneity for wealth inequality the key idea is to infer the distribution of preference parameters from the observed age profile of wealth inequality the contribution of preference heterogeneity to wealth inequality can then be measured using a quantitative life cycle model i find that discount rate heterogeneity increases the gini coefficient of wealth by around 0 07 to levels that are close to the data the share of wealth held by the richest 1 of households rises by around 0 04 but falls short of the data by more than 10 percentage points discount rate heterogeneity also helps to account for the large wealth inequality observed among households with similar lifetime earnings

production and shipment lot sizing in a vendor buyer supply chain with transportation cost abstract previous research on the joint vendor buyer problem focused on the production shipment schedule in terms of the number and size of batches transferred between the two parties it is a fact that transportation cost is a major part of the total operational cost however in most joint vendor buyer models the transportation cost is only considered implicitly as a part of fixed setup or ordering cost and thus is assumed to be independent of the size of the shipment as such the effect of the transportation cost is not adequately reflected in final planning decisions there is a need for models involving transportation cost explicitly for better decision making in this study we analyze the vendor buyer lot sizing problem under equal size shipment policy we introduce the complete solution of the problem in an explicit and extended manner that has not existed in the literature we incorporate transportation cost explicitly into the model and develop optimal solution procedures for solving the integrated models all unit discount transportation cost structures with and without over declaration have been considered numerical examples are presented for illustrative purpose

analyzing the impacts of carbon regulatory mechanisms on supplier and mode selection decisions an application to a biofuel supply chain this paper analyzes the impacts of carbon regulatory mechanisms on replenishment decisions in a biofuel supply chain we employ mathematical models for operations which integrate replenishment and supplier transportation mode selection decisions these models explicitly account for carbon emissions that may result from transportation and inventory storage activities this research is motivated by observations indicating that nearly 19 of the energy consumption and 25 of the energy related carbon dioxide emissions worldwide arise from transportation because freight transportation is expected to continue to grow we consider the impacts of different carbon regulatory mechanisms on transportation and inventory replenishment decisions in a biofuel supply chain a set of extensive numerical experiments uses the biofuel supply chain context to analyze the impacts of different regulatory mechanisms including carbon cap carbon tax carbon cap and trade and carbon offset on performance we use existing methodologies to calculate emissions as a function of distance traveled load weight and transportation mode used we also use publicly available data to derive representative biomass transportation costs as a consequence our numerical results are meaningful and give a realistic representation of the relationships between emissions from different transportation modes and the resulting costs the results of our computational experiments indicate that carbon regulatory mechanisms have a non trivial impact on replenishment schedules and as a consequence costs and emissions in the supply chain

a more timely house price index using listings data we construct a new repeat sales house price index that describes house values at the contract date when the price is determined rather than the closing date when the property is transferred we showthat this difference in timing helps explain several puzzles about house prices including their strong short term serial correlation and their weak correlation with stock prices and macroeconomic news shocks in addition we showthat a variant of our index that relies exclusively on listings data for recent transactions accurately reveals trends in house prices several months before existing price indexes like case shiller become available

towards supply chain sustainability economic environmental and social design and planning abstract costumers and governments are pressuring companies to become more sustainable however the lack of research on how to incorporate these issues makes this a challenging task to fill this gap a generic multi objective mathematical programming model for the design and planning of supply chains integrating the three dimensions of sustainability is presented the economic pillar of sustainability is addressed in this work considering the costs of the supply chain then recipe an environmental assessment methodology indicated in the literature and by the european commission as the most developed one currently available is for the first time applied to supply chain design optimization finally a social indicator appropriate to assess strategic decisions is proposed this social indicator considers the impact of social and political concerns on company s performance the relevance of this model as a decision support system is highlighted with its application to a real case study of a portuguese battery producer and distributor a set of strategies to select the best solution among the obtained optimal ones is presented results show that the model allows improvements in all the three dimensions of sustainability and offers important managerial insights