the differential impact of low carbon technologies on climate change mitigation cost under a range of socioeconomic and climate policy scenarios this paper considers the effect of several key parameters of low carbon energy technologies on the cost of abatement a methodology for determining the minimum level of performance required for a parameter to have a statistically significant impact on co2 abatement cost is developed and used to evaluate the impact of eight key parameters of low carbon energy supply technologies on the cost of co2 abatement the capital cost of nuclear technology is found to have the greatest impact of the parameters studied the cost of biomass and ccs technologies also have impacts while their efficiencies have little if any sensitivity analysis of the results with respect to population gdp and co2 emission constraint show that the minimum performance level and impact of nuclear technologies is consistent across the socioeconomic scenarios studied while the other technology parameters show different performance under higher population lower gdp scenarios solar technology was found to have a small impact and then only at very low costs these results indicate that the cost of nuclear is the single most important driver of abatement cost and that trading efficiency for cost may make biomass and ccs technologies more competitive

information and efficiency goal arrival in soccer betting an efficient market incorporates news into prices immediately and fully tests for efficiency in financial markets have been undermined by information leakage we test for efficiency in sports betting markets real world markets where news breaks remarkably cleanly applying a novel identification to high frequency data we investigate the reaction of prices to goals scored on the cusp of half time this strategy allows us to separate the market s response to major news a goal from its reaction to the continual flow of minor game time news on our evidence prices update swiftly and fully

a model of competition in the solar panel industry we develop a model of competition in the solar panel industry solar firms manufacture panels that are differentiated both vertically and horizontally and compete by setting quantities the equilibrium of the model is consistent with a set of stylized facts that we document including variation in prices markups and market shares across firms we calibrate the model using a new dataset data on prices costs and shipments of leading solar companies as well as solar sales in four leading markets the calibrated model is applied to evaluate the impact of a decline in the price of polysilicon a key raw material used in the manufacture of solar panels on the equilibrium price of solar panels

firm incentives to promote technological change in pollution control reply abstract the process of technological change in pollution control is broken into three basic steps innovation diffusion and optimal agency response firm incentives to promote these steps are then examined under five regulatory regimes direct controls emission subsidies emission taxes free marketable permits and auctioned marketable permits on a relative basis emission taxes and auctioned permits provide the highest firm incentives to promote technological change at times free permits generate lower incentives direct controls which are common regulatory tools usually provide the lowest relative firm incentives to promote technological change

94 effective policies for a two stage serial inventory system with stochastic demand a two stage inventory system is considered where poisson demand occurs at stage 1 and stage 1 replenishes its inventory from stage 2 which in turn orders from an outside supplier with unlimited stock each shipment either to stage 2 or to stage 1 incurs a fixed setup cost under the assumption that the supply leadtime at stage 2 is zero we characterize a simple heuristic policy whose long run average cost is guaranteed to be within 6 of optimality i e a 94 effective policy the paper also provides heuristic policies for more general inventory systems and reports computational results

representing induced technological change in models for climate policy analysis induced technological change itc whereby the relative price effects of reducing greenhouse gas emissions stimulate innovation that mitigates the cost of abatement is both tantalizing to decision makers and challenging to represent in the computational economic and engineering models used to analyze climate change policy this overview reconciles the divergent views of technology and technological change within different types of models elucidates the theoretical underpinnings of itc introduces the reader to the techniques of their practical implementation and evaluates the implications for models results

photovoltaic power stations in germany and the united states a comparative study by data envelopment analysis abstract this study compares photovoltaic pv power stations between germany and the united states to examine which country more efficiently provides renewable energy in their usages for the comparative analysis this study utilizes data envelopment analysis dea as a methodology to evaluate the performance of pv power stations from the perspective of both solar and land usages a total of one hundred sixty pv power stations eighty in germany and eighty in the united states are used for this comparison the demand for sustainable energy and energy security has been rapidly increasing over the past decade because of concerns about environment and limited resources pv solutions are one of many renewable technologies that are being developed to satisfy a recent demand of electricity germany is the world s top installer and consumer of pv power and the united states is one of the top five nations germany leads the way in installed pv capacity even though the nation has less solar resources and land area due to limited solar resources low insolation and sunshine and land area the united states should have a clear advantage over germany however the empirical result of this study exhibits that pv power stations in germany operate more efficiently than those of the united states even if the latter has many solar and land advantages the surprising result indicates that the united states has room for improvement when it comes to utilizing solar and land resources and needs to reform the solar policy for such a purpose feed in tariff fit may be an effective energy policy at the state level in the united states because the fit provides investors such as utility companies and other types of energy firms with financial incentives to develop large pv power stations and generation facilities for other renewable energy it may be true that the fit is a powerful policy tool to promote pv and other renewable installation and support a reduction of an amount of greenhouse gases however the fit poses a large financial burden to consumers with a massive increase in renewable energy installation like in germany and spain therefore it is necessary for the united states to consider how to align a policy with a speed of technology innovation to balance between the benefit and the cost derived from the policy implementation on renewable energy in addition this study discusses policy issues regarding cost allocation due to fit among stakeholders related to the electric power industry at the end this study proposes a new type of wholesale electricity market that provides simultaneous trading on electricity and greenhouse gas emissions by fully utilizing modern computer science technology that exists in universities and national laboratories of the united states

modeling synergies in multi criteria supplier selection and order allocation an application to commodity trading abstract we propose a novel meta approach to support collaborative multi objective supplier selection and order allocation ssoa decisions by integrating multi criteria decision analysis and linear programming lp the proposed model accounts for suppliers performance synergy effects within a hierarchical decision structure it incorporates both heterogeneous objective data and subjective judgments of the decision makers dms representing various groups with different voting powers vps we maximize the total value of purchasing tvp by optimizing order quantity assignment to suppliers and taking into consideration their synergies encountered in different time horizons we apply the proposed model to a contractor selection and order quantity assignment problem in an agricultural commodity trading act company we maximize the strategic effectiveness of both the customers and the suppliers minimize risks increase the degree of cooperation between trading partners on all levels of supply chain integration enhance transparent knowledge sharing and aggregation and support collaborative decision making

preference programming for robust portfolio modeling and project selection in decision analysis difficulties of obtaining complete information about model parameters make it advisable to seek robust solutions that perform reasonably well across the full range of feasible parameter values in this paper we develop the robust portfolio modeling rpm methodology which extends preference programming methods into portfolio problems where a subset of project proposals are funded in view of multiple evaluation criteria we also develop an algorithm for computing all non dominated portfolios subject to incomplete information about criterion weights and project specific performance levels based on these portfolios we propose a project level index to convey i which projects are robust choices in the sense that they would be recommended even if further information were to be obtained and ii how continued activities in preference elicitation should be focused the rpm methodology is illustrated with an application using real data on road pavement projects

on the sources of technological change assessing the evidence this paper uses a selective review of the economic literature on technological change to support four points that are important for interpreting and incorporating technological change into formal models of energy and the environment the review 1 supports the notion that no single source dominates the process of technological change it supports roles for rd 3 indicates that these spillovers are often indirect requiring own industry activities to utilize and 4 indicates that simple experience curve calibrations often used in formal models likely include a range of sources of technological change in addition to learning by doing some of which might not be induced by the sorts of policies typically considered in the climate context

batch size and stocking levels in multi echelon repairable systems in multi echelon repairable inventory systems with high set up cost for order and or high demand rates the use of batch ordering may be more cost effective than the common s 1 s ordering policy this paper addresses the issue of determining the optimal order batch size and stocking levels at the stocking locations in such a system a power approximation is used to estimate the total system stock and backorder levels from which the optimal batch size can be readily determined a search routine involving one pass searches are then followed to obtain the stocking levels at the depot and the local sites of the system this procedure has been evaluated using 900 test cases and has been found to be very effective the power approximation approach also results in a simple analytical relationship to test whether or not s 1 s is an optimal ordering policy for repairable items in a multi echelon environment

98 effective integer ratio lot sizing for one warehouse multi retailer systems a warehouse supplies n retailers constant external demand occurs at each retailer and shortages are not allowed there are linear holding costs and fixed costs for ordering at the warehouse and at each retailer the goal is to minimize the long run average cost over an infinite time horizon we define a new class of policies for this problem whose simple structure facilitates both computation and implementation the cost of a policy that is optimal within this class is shown to be within 2 of the cost of an optimal policy for the original problem in the worst case such a policy can be computed in on log n time

on the benefits of delayed ordering practical experience and scientific research show that there is scope for improving the performance of inventory control systems by delaying a replenishment order that is otherwise triggered by generalised and all too often inappropriate assumptions this paper presents the first analysis of the most commonly used continuous s s policies with delayed ordering for inventory systems with compound demand we analyse policies with a constant delay for all orders as well as more flexible policies where the delay depends on the order size for both classes of policies and general demand processes we derive optimality conditions for the corresponding delays in a numerical study with erlang distributed customer inter arrival times we compare the cost performance of the optimal policies with no delay a constant delay and flexible delays sensitivity results provide insights into when the benefit of delaying orders is most pronounced and when applying flexible delays is essential

a portfolio decision analysis approach to support energy research and development resource allocation abstract research sponsored by the us department of energy doe aims to facilitate a clean and independent energy future for the nation strategic planning for energy research and development r d can be complex and dynamic in part due to federal budgetary constraints and volatility managing r d funding to advance energy technologies in spite of these challenges is a crucial component of the nation s long term energy policy this study demonstrates a portfolio decision analysis pda approach to support r d resource allocation decisions for the doe office of fossil energy s carbon capture and storage r d program a multi attribute value model uses technology readiness levels trls and other metrics to represent the overall objectives of the r d program in order to evaluate alternative research portfolios given limited funding mathematical optimization identifies efficient funding allocations for each technology program area to maximize the multi attribute value generated from the total budget this is especially useful for responding to externally imposed budget changes as the case study demonstrates explicitly funding the most value generating options leads to greater expected r d programmatic value than typical strategies of equal or proportional distributions of a budget change among technology program areas

is certainty in carbon policy better than uncertainty abstract uncertainty in the strictness of carbon policy can have significant impacts on power generating firms capacity investment decisions and market outcomes we investigate the effects of this policy uncertainty on firms expected profits consumers surplus and firms cost for reaching a co 2 emission target our results derived from a game theoretical model and applied to realistic data indicate that uncertainty in the carbon policy induces more capacity investments in fossil and renewable technologies we find that it is optimal for firms with higher risk aversion to invest more in renewable technologies than their less risk averse rivals for policy makers our results suggest counter intuitively that retaining the flexibility to update emission targets whilst causing uncertainty in the carbon policy is beneficial this is because it provides higher expected consumer surplus and lower expected electricity price power generating firms are also better off under the policy uncertainty by having lower expected costs for reaching the emission goal and higher expected profits when firms risk aversions are low these results support the approach employed in european power markets to periodically update the co 2 emission cap depending on the prevailing circumstances rather than having certainty in the decrements of the caps over a longer time horizon our insights can help policy makers and firms to make better decisions by understanding how carbon policy uncertainty impacts the optimal capacity investments and how these investments might depend on the firms heterogeneity in risk aversion

pv sector in the european union countries clusters and efficiency abstract european union eu due to several challenges that exist nowadays has changed its energy policy in order to fulfill international commitments concerning greenhouse gas emission and to assure safety in supply and stable prices eu has been a leader in renewable energy in many eu countries solar energy is a possible and very viable option together with wind energy photovoltaic energy is the new support core of a low carbon eu economy in what concerns electricity production in this work clusters of countries were generated based on the energy produced by pv systems and the share of energy from pv systems in the total electricity produced by renewable sources this work also analyzed the production of energy from the photovoltaic sector in eu and compared it with the existing potential for this type of energy roughly half of the eu countries are producing energy within the limits of what is expected considering the irradiation on optimally inclined plane however some of them could improve the ratio between energy production and installed power considering the leader countries in energy production from photovoltaic czech republic and spain are the countries that exceed what it is expected

r d investment strategy for climate change abstract the economic costs of stabilizing greenhouse gas concentrations over the coming century depend critically on the development of new technologies in the energy sector our research and development r d investment strategy is the control variable for technology availability this paper proposes an analytic framework for determining optimal r d investment allocation and presents some numerical results to demonstrate the implementation of the methodology the value of technological advance in three targeted areas fossil based generation renewables and carbon capture and storage is represented by the increase in expected welfare in the presence of an emissions policy constraint of initially uncertain stringency r d expenditure increases the probability of advance optimal investment is determined by its relationship with success probability which is assumed to exhibit decreasing returns to scale relative to the value of success while the numerical results are speculative the paper offers insights into the nature of an optimal technology strategy for addressing climate change

a two level supply chain with partial backordering and approximated poisson demand abstract we consider a two level supply chain with a number of identical independent retailers at the lower echelon and a single supplier at the upper echelon controlled by continuous review inventory policy r q each retailer experiences poisson demand with constant transportation times we assume constant lead time for replenishing supplier orders from an external warehouse to the supplier and unsatisfied retailer orders are backordered in the supplier we assume that the unsatisfied demand is partially backordered in the identical retailers the partially backordering policy is implemented in the identical retailers using an explicit control parameter b which limits the maximum number of backorders allowed to be accumulated during the lead time we develop an approximate cost function to find optimal reorder points for given batch sizes in all installations the optimal value of b in the identical retailers and the related accuracy is assessed through simulation

advanced solar r d combining economic analysis with expert elicitations to inform climate policy the relationship between r d investments and technical change is inherently uncertain in this paper we combine economics and decision analysis to incorporate the uncertainty of technical change into climate change policy analysis we present the results of an expert elicitation on the prospects for technical change in advanced solar photovoltaics we then use the results of the expert elicitations as inputs to the minicam integrated assessment model to derive probabilistic information about the impacts of r d investments on the costs of emissions abatement

exact and approximate evaluation of batch ordering policies for two level inventory systems we consider a two level inventory system with one warehouse and n identical retailers lead times transportation times are constant and the retailers face independent poisson demand in a previous paper we derived a recursive procedure for determining the policy costs for an average item in case of one for one replenishment policies in this paper we show how these results can be used for the exact or approximate evaluation of more general policies where both the retailers and the warehouse order in batches we compare our methods to the method recently suggested by a svoronos and p zipkin

dynamic portfolio selection of npd programs using marginal returns selecting program portfolios within a budget constraint is an important challenge in the management of new product development npd optimal portfolios are difficult to define because of the combinatorial complexity of project combinations however at the aggregate level of the strategic allocation of resources across product lines investment in a program is not an all or nothing decision but can beadjusted resulting in a higher or lower program benefit e g higher or lower quality in some cases resources can be adjusted even for individual projects with this insight one can usemarginal analysis to optimally allocate the scarce budget this article develops a dynamic model of resource allocation taking into account multiple interacting factors such as independent or correlated uncertain market payoffs that change over time increasing or decreasing returns from the npd investment carry over of the investment benefit over multiple periods and interactions across market segments we characterize optimal policies in closed form and derive qualitative decision rules for managers

evaluation of installation stock based r q policies fortwo level inventory systems with poisson demands we consider a two level inventory system with one warehouse and n retailers leadtimes transportation times are constant and the retailers face different poisson demand processes all facilities apply continuous review installation stock r q policies with different reorder points and batch quantities we show how to evaluate holding and shortage costs exactly in case of two retailers in case of more than two retailers we use the same methodology as an approximation when evaluating costs at a certain retailer the other retailers are then aggregated into a single retailer

joining the ccs club the economics of co2 pipeline projects this paper examines the conditions for a widespread adoption of carbon capture transport and storage ccs by a group of emitters that can be connected to a common co2 pipeline it details a modeling framework aimed at assessing the critical value in the charge for the co2 emissions required for each of the emitters to decide to implement capture capabilities this model can be used to analyze how the tariff structure imposed on the co2 pipeline operator modifies the overall cost of co2 abatement via ccs this framework is applied to the case of a real european co2 pipeline project we find that the obligation to use cross subsidy free pipeline tariffs has a minor impact on the minimum co2 price required to adopt the ccs in contrast the obligation to charge non discriminatory prices can either impede the adoption of ccs or significantly raise that price besides which we compared two alternative regulatory frameworks for co2 pipelines a common european organization as opposed to a collection of national regulations the results indicate that the institutional scope of that regulation has a limited impact on the adoption of ccs compared to the detailed design of the tariff structure imposed on pipeline operators

stochastic carbon sinks for combating carbon dioxide emissions in the eu abstract this paper carries out numerical calculations on the potential of carbon sinks in the eu emissions trading scheme ets and national commitments under conditions of stochastic carbon dioxide emissions from fossil fuels and carbon sequestration by forests chance constraint programming is used to analyze the role of stochastic carbon sinks for national and eu wide compliance costs the analytical results show that the inclusion of the carbon sink option can reduce costs for low enough marginal cost and risk discount but also that costless carbon sinks as by products from forestry are not part of a cost effective solution under a high reliability concern cost savings are reduced due to risk discounting under a reliability concern in particular when assigning chebyshev s inequality as compared with a normal probability distribution it is also shown that the supply of forest sinks on the market depends on the differences in marginal abatement cost between the trading and the non trading sectors and in risk discounting between achievements of the ets cap and the national commitment relatively low marginal abatement cost in the non trading sector and high risk discounting of national commitment achievements increase the supply of sinks in the market and hence reduces the equilibrium price the empirical application illustrates the importance of risk discounting for the magnitude of cost savings obtained from introducing forest carbon sinks in the eu ets and national commitments

baseline value specification and sensitivity analysis in multiattribute project portfolio selection abstract a key issue in applying multi attribute project portfolio models is specifying the baseline value a parameter which defines how valuable not implementing a project is relative to the range of possible project values in this paper we present novel baseline value specification techniques which admit incomplete preference statements and unlike existing techniques make it possible to model problems where the decision maker would prefer to implement a project with the least preferred performance level in each attribute furthermore we develop computational methods for identifying the optimal portfolios and the value to cost based project rankings for all baseline values we also show how these results can be used to i analyze how sensitive project and portfolio decision recommendations are to variations in the baseline value and ii provide project decision recommendations in a situation where only incomplete information about the baseline value is available

towards an attention based view of the firm the central argument is that firm behavior is the result of how firms channel and distribute the attention of their decision makers what decision makers do depends on what issues and answers they focus their attention on what issues and answers they focus on depends on the specific situation and on how the firm s rules resources and relationships distribute various issues answers and decision makers into specific communications and procedures the paper develops these theoretical principles into a model of firm behavior and presents its implications for explaining firm behavior and adaptation 1997 by john wiley sons ltd

active learning and optimal climate policy this paper develops a climate economy model with uncertainty irreversibility and active learning whereas previous papers assume learning from one observation per period or experiment with control variables to gain additional information this paper considers active learning from investment in monitoring specifically in improved observations of the global mean temperature we find that the decision maker invests a significant amount of money in climate research far more than the current level in order to increase the rate of learning about climate change this helps the decision maker make improved decisions the level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations as the uncertainty about climate change is smaller active learning reduces the optimal carbon tax the greater the risk the larger is the effect of learning the method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable for instance the precision at which we observe gdp unemployment or the quality of education

ecological modernization in the electrical utility industry an application of a bads goods dea model of ecological and technical efficiency abstract newly developed data envelopment analysis techniques permit simultaneous consideration of good and bad outputs in evaluating efficiency we use these techniques to determine joint ecological and technical efficiencies of the 437 largest fossil fueled electricity generating plants in the united states utilizing the epa s e grid and clean air markets databases and drawing on ecological modernization theory we evaluate whether innovations in organizational practices and technological solutions help achieve joint technical and environmental performance efficiencies

serial supply chains with economies of scale bounds and approximations we consider two models of stochastic serial inventory systems with economies of scale for which the forms of optimal policies are known in the first model each stage has a fixed order quantity while in the second model there is a fixed order cost for external supplies for each model we show that the optimal policy parameters can be bounded and approximated by a series of independent single stage optimal policy parameters we further construct closed form bounds and approximations for the single stage solutions and apply them to the serial systems these results provide simple and effective solutions that will help to facilitate implementations in practice they also allow us to see the connections between the serial and single stage systems and sharpen our intuition on optimal policy parameters and system behavior

evaluating echelon stock r nq policies in serial production inventory systems with stochastic demand this paper studies echelon stock r nq policies in serial production inventory systems with stochastic demand we provide a recursive procedure to compute the steady state echelon inventory levels of the systems which can be used to evaluate the long run average holding and backorder costs as well as other performance measures the procedure is based upon an observation of a relationship between the inventory status of adjacent stages in a serial system we also device exact formulas for replenishment frequencies and setup costs our results apply to both continuous review systems with compound poisson demand and periodic review systems with independent identically distributed demands a preliminary numerical study was conducted to explore the cost effectiveness of echelon stock r nq policies for two stage systems with simple poisson demand we compared among the minimum costs of echelon stock r nq policies a lower bound on the minimum achievable costs and the minimum costs of installation stock r nq policies finally we present a modification of an existing approximate evaluation procedure

climate change and optimal energy technology r d policy public policy response to global climate change presents a classic problem of decision making under uncertainty theoretical work has shown that explicitly accounting for uncertainty and learning in climate change can have a large impact on optimal policy especially technology policy however theory also shows that the specific impacts of uncertainty are ambiguous in this paper we provide a framework that combines economics and decision analysis to implement probabilistic data on energy technology research and development r d policy in response to global climate change we find that given a budget constraint the composition of the optimal r d portfolio is highly diversified and robust to risk in climate damages the overall optimal investment into technical change however does depend in a non monotonic way on the risk in climate damages finally we show that in order to properly value r d abatement must be included as a recourse decision

large scale scenario analysis of future low carbon energy options abstract in this study we use a multi model framework to examine a set of possible future energy scenarios resulting from rd and portfolios lacking ccs and nuclear tend to be stochastically dominated by others we find that the dominance of ccs becomes even stronger as uncertainty in climate damages increases finally we show that there is significant value in carefully choosing a portfolio as relatively small portfolios can dominate large portfolios

near optimal r q policies for a two stage serial inventory system with poisson demand we consider a two stage serial inventory system whose cost structure exhibits economies of scale in both stages in the system stage 1 faces poisson demand and replenishes its inventory from stage 2 and the latter stage in turn orders from an outside supplier with unlimited stock each shipment either to stage 2 or to stage 1 incurs a fixed setup cost we derive important properties for a given echelon stock r q policy for an approximation of the problem where all states are continuous based on these properties we design a simple heuristic algorithm that can be used to find a near optimal r q policy for the original problem numerical examples are given to demonstrate the effectiveness of the algorithm

a portfolio model for siting offshore wind farms with economic and environmental objectives abstract siting offshore wind farms is a complex problem due to the wake interactions between wind farms we develop a profit maximizing portfolio model based on underlying network models to track the wake effects through a series of wind farms our portfolio model optimizes the siting of wind farms considering multiple wind directions and wind speeds and performs better than simple decision heuristics excluding sites from the portfolio has nonlinear impacts on the profitability of the portfolio of sites in that areas excluded from consideration have greater impacts on profit if they are grouped together or aligned parallel to the prevailing wind direction the model can be readily adapted to include additional cost factors

optimal policy for a two stage assembly system under random demand this paper considers an inventory system in which an end product is assembled from two components each of which is ordered from an external supplier only the end product has final demand which is assumed to be random using the functional equation approach of dynamic programming we characterize the forms of both the optimal order policy for the components and the optimal assembly policy of the end product for a multiperiod problem of arbitrary but finite length we believe that this work represents the only exact analysis of an mrp type assembly system when demand is stochastic

optimal and near optimal inventory control policies for a make to order inventory production system abstract this paper examines several inventory replenishment policies for a make to order inventory production system that consists of a production workshop and a warehouse demands arrive to the production workshop according to a poisson process and are processed in an fcfs manner the production workshop requires that the warehouse provides as needed raw materials for use in the production process the warehouse inventory is replenished according to an inventory replenishment policy the optimal replenishment policy which minimizes the average total cost per product is derived using a markov decision process approach the structure of the optimal replenishment policy is explored simple order up to myopic and heuristic replenishment policies are introduced the myopic and heuristic replenishment policies are easy to compute and yet perform almost as well as the optimal replenishment policy

technical note optimal control of an assembly system with multiple stages and multiple demand classes we consider an assembly system with multiple stages multiple items and multiple customer classes the system consists of m production facilities each producing a different item items are produced in variable batch sizes one batch at a time with exponentially distributed batch production times demand from each class takes place continuously over time according to a compound poisson process at each decision epoch we must determine whether or not to produce an item and should demand from a particular class arise whether or not to satisfy it from existing inventory if any is available we formulate the problem as a markov decision process and use it to characterize the structure of the optimal policy in contrast to systems with exogenous and deterministic production lead times we show that the optimal production policy for each item is a state dependent base stock policy with the base stock level nonincreasing in the inventory level of items that are downstream and nondecreasing in the inventory level of all other items for inventory allocation we show that the optimal policy is a multilevel state dependent rationing policy with the rationing level for each demand class nonincreasing in the inventory level of all nonend items we also show how the optimal control problem can be reformulated in terms of echelon inventory and how the essential features of the optimal policy can be reinterpreted in terms of echelon inventory

optimization of order up to s policies for two level inventory systems with compound poisson demand abstract we consider a two level inventory system with one warehouse and n retailers leadtimes are constant and the retailers face different compound poisson demand processes all facilities apply order up to s replenishment policies we show how to evaluate holding and shortage costs exactly

balancing solar pv deployment and rd d a comprehensive framework for managing innovation uncertainty in electricity technology investment planning abstract we present a new framework for studying the socially optimal level of generating capacity and public rd d investments for the electric power sector under decision dependent technical change uncertainty we construct a bottom up stochastic electricity generation capacity expansion model with uncertain endogenous rd d based technical change focusing on solar pv rd d investment planning for its current prominent role in sustainable energy and climate policy deliberations we characterize the decision dependent process of technical change uncertainty as unknown outcomes of rd d investments that increase the likelihood of success with increasing amounts of rd d and calibrate to a novel expert elicitation dataset that accounts for this decision dependence the problem is framed as a multi stage decision under uncertainty where the decision maker learns and adapts to new information between decision periods specifically our application considers four decision stages with the decision maker choosing investment levels for new capacity and solar pv rd d while learning about rd d outcomes that can reduce solar pv costs between each stage the problem is thus formulated to match the manner in which real world decisions about rd d investments in renewable energy are made and avoids common assumptions of perfect foresight or uncertainty but no learning that are often used in practice numerical results show that when uncertainty and learning features are both included the optimal solar pv rd d investment strategy changes from solutions using other methods considering uncertainty and learning results in solar rd d investment differences as high as 20 percent lower in the first stage and 300 percent higher in later stages we also show that when uncertainty is considered without learning the fraction of new solar pv capacity investments can be depressed overall this paper shows that it is possible to unify several realistic features of the deployment and development problem for the electricity sector to meet sustainability goals into one framework

investment in risky r d programs in the face of climate uncertainty we analyze how the socially optimal technology rd and that uncertainty in damages interacts with uncertainty in the returns to rd and r d that reduces the emissions to output ratio and argue that this is a good representation of r d into fossil fuel technologies for r d programs into non carbon technologies optimal investment is higher in riskier programs our empirical model indicates that the optimal investment in a risky program is about 3 1 2 times larger than in a program with certain returns for r d programs aimed at reducing emissions in fossil fuel based technologies our results show that qualitatively investment is higher in less risky programs under most uncertain damage scenarios our empirical model shows however that the risk profile of fossil fuel based r d programs generally has little quantitative impact on optimal investment the exception is that when the probability of a catastrophe inducing full abatement is very high investment is about twice as high in risky programs compared to programs with certain returns

modified echelon r q policies with guaranteed performance bounds for stochastic serial inventory systems we consider the classic continuous review nstage serial inventory system with a homogeneous poisson demand arrival process at the most downstream stage stage 1 any shipment to each stage regardless of its size incurs a positive fixed setup cost and takes a positive constant lead time the optimal policy for this system under the long run average cost criterion is unknown finding a good worst case performance guarantee remains an open problem we tackle this problem by introducing a class of modified echelon r q policies that do not require qi 1 qi to be a positive integer stage i 1 ships to stage i based on its observation of the echelon inventory position at stage i if it is at or below ri and stage i 1 has positive on hand inventory then a shipment is sent to stage i to raise its echelon inventory position to ri qias close as possible we construct a heuristic policy within this class of policies which has the following features first it has provably primitive dependent performance bounds in a two stage system the performance of the heuristic policy is guaranteed to be within 1 k1 k2 times the optimal cost where k1 is the downstream fixed cost and k2 is the upstream fixed cost we also provide an alternative performance bound which depends on efficiently computable optimal r q solutions to n single stage systems but tends to be tighter second the heuristic is simple it is efficiently computable and it performs well numerically it is even likely to outperform the optimal integer ratio echelon r q policies when k1 is dominated by k2 third the heuristic is asymptotically optimal when we take some dominant relationships between the setup or holding cost primitives at an upstream stage and its immediate downstream stage to the extreme for example when h2 h1 0 where h1 is the downstream holding cost parameter and h2 is the upstream holding cost parameter

emission path planning based on dynamic abatement cost curve abstract global climate change is one of the most serious environmental problems that has attracted an unprecedented global attention the scientific community has recognized that human activity is mostly responsible for global climate warming therefore states participating in the united nations framework convention on climate change unfccc have initiated a series of negotiations on how to develop their own emission reduction targets however the realization of these targets is at the expense of economic development to a great extent therefore an abatement plan is necessary to decide how and when to implement emission reduction targets a marginal abatement cost curve macc often used as an important quantitative tool to estimate abatement burden or evaluate abatement performance should be considered carefully in this paper we enrich the traditional macc by introducing the concept of an immediate unit marginal abatement cost to describe its intrinsic incremental abatement difficulty this cost is proved to be agreed with the actual situation in many ways and is therefore very suitable for practical use two factor learning curve are considered in the model which can go some way in improving the performance of the revised macc using a parameterization method the original problem can be converted into a tractable nonlinear programming problem we use an algorithm to search for the approximate global optimal solution the effectiveness and the efficiency of the algorithm are discussed respectively in the results we find that the abatement path distinguishes largely under different abatement targets some plausible reasons and policy advices are given

coordination mechanisms in decentralized serial inventory systems with batch ordering this paper studies a periodic review serial supply chain in which materials are ordered and shipped according to r nq policies three information scenarios are considered depending on the level of information available echelon local and quasilocal in the echelon scenario each stage can access the inventory and cost information within its echelon comprising the stage itself and all downstream stages in the local scenario each stage only accesses its own local information finally in the quasilocal scenario each stage knows its local information plus the actual customer demands we propose coordination schemes that regulate the stages to achieve the supply chain s optimal cost under each information setting all these coordination schemes fit comfortably within an emerging practice called supply chain finance which includes the organization and technology needed to implement them

selecting a portfolio of solar energy projects using multiattribute preference theory this article reports a procedure developed to assist the u s department of energy in selecting a portfolio of solar energy applications experiments the procedure has also been used in other government procurements and appears to be applicable in a variety of project funding processes the technical quality of each proposed applications experiment was summarized through the use of multiple evaluation measures or attributes these were combined into a single index of the overall technical quality of an experiment through the use of a multiattribute utility function recently derived results in measurable value theory were applied to derive an index of the overall technical quality of a portfolio of experiments budgetary and programmatic issues were handled through the use of constraints this approach allowed the portfolio selection problem to be formulated as an integer linear program details of the application are presented including a discussion of the data requirements and assessment procedure used the portfolio selection procedure was successfully applied and variations of it have been successfully used in four other solar energy procurements

growth and competition in renewable energy industries insights from an integrated assessment model with strategic firms abstract this article describes the development implementation and application of an integrated assessment modeling framework featuring renewable technology markets with producers engaged in cournot competition scenario results reveal how climate policy and inter firm learning spillovers interact with market structure to affect wind and solar pv prices adoption producer profits and carbon emissions competitive markets yield consistently lower markups than concentrated markets leading to significantly more adoption and lower emissions widespread solar pv adoption is a key component of the largest emissions reductions but this requires substantial price reductions that only occur if the solar pv market is competitive and learning spills over across producers whether a leading firm has a profit incentive to facilitate or obstruct learning spillovers depends on the availability of cost competitive substitute technologies if such a substitute exists the firm prefers strong spillovers that help its industry compete against the substitute if not the firm prefers weak spillovers that prevent competitors in its industry from seizing market share the relationship between price and cumulative capacity is endogenous in the modeling framework regression analysis of scenario results yields price learning rates which are similar to unit production cost learning rates in competitive markets but substantially lower even negative in concentrated markets

an econometric evaluation of the effect of firing a coach on team performance firing the manager is a drastic measure employed by firms to deal with poor performance however data on within firm dynamics are scarce and the firing of individual managers is rarely recorded in the firm level data currently available this makes the value of firing a manager difficult to assess data on sports offer a unique opportunity to study this phenomenon because the firing of a coach is usually well publicized using data on soccer the author evaluates the effect of the firing of a coach on team performance as teams do not face the same opponents before and after a coach is fired the issue of sample selectivity is addressed

or practice selecting a portfolio of environmental programs for a synthetic fuels facility this article describes how a u s department of energy steering committee used a decision analysis procedure to develop a portfolio of environmental and health research programs for a commercial scale synthetic fuels facility the procedure used information and insights from decision analyses conducted in five technical areas to support decision analysis at the portfolio level the problem was complex because it included many combinations of studies that could be funded multiple objectives in the five technical areas as well as at the portfolio level and uncertainties about research needs the availability of technical data and research costs the article discusses the rationale for using formal decision analysis the main features of the procedure and how the procedure provided the steering committee with a logical basis for evaluating a large number of diverse technical projects and with the help of health and environmental experts established research priorities and budget allocations in a logical and defensible manner

the optimal research and development portfolio of low carbon energy technologies a study of china to support decision making for an optimal portfolio strategy for low carbon energy technology research and development r d this study proposes a dynamic two stage stochastic programming model taking into account both the uncertainty of technological change and damages of climate change based on china s economic and technology level and expert elicitation an r d investment portfolio strategy looking at three low carbon technologies carbon capture and storage ccs solar photovoltaic pv and nuclear including nine projects is investigated through the proposed model the optimized results show that the optimal r d technology portfolio is robust to different levels of risk in climate damage however the total social costs for the optimal r d technology portfolio is lowest in the medium risk of climate damage scenario under different opportunity costs the composition of the optimal r d portfolio varies however projects for each of the three technologies always constitute the optimal r d portfolio furthermore the implication is that a technology synergistic r d strategy is conducive to enhancing the level of co2 abatement and reducing the total social cost

optimal policies and approximations for a serial multiechelon inventory system with time correlated demand since clark and scarf s pioneering work most advances in multiechelon inventory systems have been based on demand processes that are time independent this paper revisits the serial multiechelon inventory system of clark and scarf and develops three key results first we provide a simple lower bound approximation to the optimal echelon inventory levels and an upper bound to the total system cost for the basic model of clark and scarf second we show that the structure of the optimal stocking policy of clark and scarf holds under time correlated demand processes using a martingale model of forecast evolution third we extend the approximation to the time correlated demand process and study in particular for an autoregressive demand model the impact of lead times and autocorrelation on the performance of the serial inventory system

long term forecasts for energy commodities price what the experts think the ability to forecast energy prices in the long term is important for a wide range of reasons from the formulation of countries energy and transportation policies to the defensive strategies of nations to investment decisions within the private sector despite the importance of these predictions however forecasters and market pundits face a difficult challenge when trying to forecast over the long term while statistical models can credibly rely on assumptions about the relationship between variables in the short term they are frequently less reliable in the long term as political and technological transformations profoundly change how the economy works over time towards improving long term predictions for energy commodities this paper uses the elicitation and aggregation of experts beliefs to put forward forecasts for crude oil and natural gas prices by incentivizing experts to tell the truth and minimising their own biases through the application of the bayesian truth serum with this approach we generated both short term and long term forecasts and used the short term forecast to validate the quality of the experts predictions

technological change and uncertainty in environmental economics abstract technological change is widely believed to play a crucial role in mastering the challenges of man made climate change the drivers and impacts of technological change have therefore become an important research issue in the field of climate economics while models to analyze the interactions between economy energy and the environment initially treated technological change as exogenous more recent modeling approaches often represent technological change as endogenously induced typically models of induced technological change in climate economics are based on perfect foresight in a deterministic world however both technological change and climate impacts are subject to large uncertainties that may substantially affect the design of efficient climate policies against this background the special issue presents five articles contributing to the study of uncertainty and technological change in climate change economics

lower bounds for multi echelon stochastic inventory systems we establish lower bounds on the minimum cost of managing certain production distribution networks with setup costs at all stages and stochastic demands these networks include serial assembly and one warehouse multi retailer systems we obtain the bounds through novel cost allocation schemes we evaluate the bounds performance for one warehouse multi retailer systems by comparing them with simple heuristic policies the bounds are quite tight for systems with a small number of retailers we also present simplified proof of known optimality results for serial and assembly systems

setting environmental policy when experts disagree how can a decision maker assess the potential of environmental policies when a group of experts provides divergent estimates on their effectiveness to address this question we propose and analyze a variant of the well studied alpha maxmin model in decision theory in our framework and consistent to the paper s empirical focus on renewable energy r d investment experts subjective probability distributions are allowed to be action dependent in addition the decision maker constrains the sets of priors to be considered via a parsimonious measure of their distance to a benchmark average distribution that grants equal weight to all experts while our model is formally rooted in the decision theoretic framework of olszewski rev econ stud 74 567 595 2007 it may also be viewed as a structured form of sensitivity analysis we apply our framework to original data from a recent expert elicitation survey on solar energy the analysis suggests that more aggressive investment in solar energy r d is likely to yield significant dividends even or rather especially after taking expert ambiguity into account

managing risks from climate impacted hazards the value of investment flexibility under uncertainty abstract incomplete knowledge about climate change and the related uncertainty in climate prediction makes adaptation inherently difficult we introduce a real options framework to determine the optimal adaptation to catastrophic risk that takes into account climate change uncertainty the framework can be used to select the optimal adaptation project from a number of alternative projects or to determine the optimal investment sequence of the considered projects in applying the model to the management of bushfire risk at a local government area we find that the framework can significantly increase the value of adaptation investment above the current net present value and also improve upon deterministic dynamic models we also find that it is important to consider sequential investment to preserve investment flexibility under the uncertainty of climate change when decision makers can afford multiple investment projects the loss associated with the use of a simple net present value rule can be substantial and it is important to use a deterministic dynamic model or a real options model

on backstops and boomerangs environmental r d under technological uncertainty abstract in areas such as climate change the recent economic literature has been emphasizing and addressing the pervasive presence of uncertainty this paper considers a new and salient form of uncertainty namely uncertainty regarding the environmental characteristics of green innovations here rd ii a decreasing probability of finding a backstop leads to the toleration of higher pollution levels slower rd iii learning about the probability of a backstop is driven by failures only and leads to decreasing research incentives and iv small to moderate delays in the resolution of technological uncertainty do not affect the optimal policy

incentives for advanced pollution abatement technology at the industry level an evaluation of policy alternatives abstract in this research we evaluate the incentive effects of five environmental policy instruments to promote the development and adoption of advanced pollution abatement technology in a heterogenous industry from most to least incentive the policy instruments can be rank ordered as follows i auctioned permits ii emissions taxes and subsidies iii issued marketable permits iv performance standards including performance standards in this list necessitates the assumption that they are differentiated between heterogeneous firms before the technology adoption in a way which replicates the initial emissions control distribution of the efficient incentive based instruments with the starting point normalized in this fashion the instrument rankings are invariant with respect to the size of firms the size of the industry or the industry s abatement cost structure

innovation in pollution control comparisons of the various institutional arrangements for controlling pollutant emissions from individual sources effluent fees effluent control subsidies marketable permits and direct command and control regulation have usually focused on their static efficiency properties and institutional feasibility e g dales 1968 zerbe 1970 baumol and oates 1975 kneese and schultze 1975 marin 1978 mills and white 1978 spence and weitzman 1978 russell 1979 a relatively neglected area has been the study of how each arrangement influences innovation in pollution control a few studies e g kneese and schultze 1975 marin 1978 mills and white 1978 russell 1979 have casually claimed that the control methods that rely on economic incentives provide superior incentives for innovation but there have been few systematic studies of the question this paper provides a simple model of pollution control innovation by a profitmaximizing polluter who is subject to the various control methods the consequences of the methods will be explored in three major contexts first we assume that the polluter and the innovation is a small enough part of the overall pollution problem so that none of the important marginal conditions are changed by the innovation second we assume that the polluter and the innovation are important enough so that marginal conditions are changed by the innovations but that the governmental authority determining pollution control incentives or levels fails to make the appropriate adjustments third we again assume that the innovation causes marginal conditions to change but in this case the governmental authority makes the appropriate adjustments we use the term ratcheting to describe this last phenomenon in all cases we assume that the innovating polluter correctly predicts the reactions of the governmental authority and bases his innovation decisions on that prediction a profit maximizing entrepreneur would normally be expected to adopt any innovation that promised gains present discounted value to him in excess of initial

production and inventory control of a single product assemble to order system with multiple customer classes we consider the optimal production and inventory control of an assemble to order system with m components one end product and n customer classes a control policy specifies when to produce each component and whenever an order is placed whether or not to satisfy it from on hand inventory we formulate the problem as a markov decision process and characterize the structure of an optimal policy we show that a base stock production policy is optimal but the base stock level for each component is dynamic and depends on the inventory level of all other components more specifically it is nondecreasing we show that the optimal inventory allocation for each component is a rationing policy with different rationing levels for different demand classes the rationing levels for each component are dynamic and also nondecreasing in the inventory level of all other components we compare the performance of the optimal policy to heuristic policies including the commonly used base stock policy with fixed base stock levels and find them to perform surprisingly well especially for systems with lost sales

unpacking multimethodology impacts of a community development intervention multimethodology interventions are being increasingly employed by operational researchers to cope with the complexity of real world problems in keeping with recent calls for more research into the realised impacts of multimethodology we present a detailed account of an intervention to support the planning of business ideas by a management team working in a community development context drawing on the rich steam of data gathered during the intervention we identify a range of cognitive task and relational impacts experienced by the management team during the intervention these impacts are the basis for developing a process model that accounts for the personal social and material changes reported by those involved in the intervention the model explains how the intervention s analytic and relational capabilities incentivise the interplay of participants decision making efforts and integrative behaviours underpinning reported intervention impacts and change our findings add much needed empirical case material to enrich further our understanding of the realised impacts of operational research interventions in general and of multimethodology interventions in particular

mobilizing private finance for low carbon innovation a systematic review of barriers and solutions this paper analyses the field of innovation studies regarding barriers to low carbon innovation and consequences for finance investment and divestment and contributes to a more holistic understanding of the underlying mechanisms a combination of technological barriers combined with economic barriers institutional and political barriers contribute to sub optimal low carbon investment all along the innovation cycle policy makers need to take a systemic approach to enable the redirection of diverse private financial sources instruments range from cutting dirty r d subsidies and support for clean technology innovation and diffusion levelling the institutional playing field and making risks of high carbon and low carbon technologies transparent to providing a consistent but adaptive long term transition strategy this would allow financiers to gradually shift their investments away from high carbon mainstream markets and scale low carbon technology niche markets however financiers also need to sharpen their competencies with regard to new clean technologies and markets

the damage costs of climate change toward more comprehensive calculations it is argued that estimating the damage costs of a certain benchmark climate change is not sufficient what is needed are cost functions and confidence intervals although these are contained in the integrated models and their technical manuals this paper brings them into the open in order to stimulate discussion after briefly reviewing the benchmark climate change damage costs region specific cost functions are presented which distinguish tangible from intangible losses and the losses due to a changing climate from those due to a changed climate furthermore cost functions are assumed to be quadratic as an approximation of the unknown but presumably convex functions results from the damage module of the integrated climate economy model fund are presented next uncertainties are incorporated and expected damages are calculated it is shown that because of convex loss functions and right skewed uncertain ties the risk premium is substantial calling for more action than analysis based on best guess estimates the final section explores some needs for further scientific research

inventory management with asset based financing most of the traditional models in production and inventory control ignore the financial states of an organization and can lead to infeasible practices in real systems this paper is the first attempt to incorporate asset based financing into production decisions instead of setting a known exogenously determined budgetary constraint as most existing models suggest we model the available cash in each period as a function of assets and liabilities that may be updated periodically according to the dynamics of the production activities furthermore our models allow different interest rates on cash balance and outstanding loans which is an enhancement over most traditional models in that inventory financed by a loan may be more expensive than that by out of pocket cash we demonstrate the importance of joint consideration of production and financing decisions in a start up setting in which the ability to grow the firm is mainly constrained by its limited capital and dependence on bank financing we then explain the motivation for asset based financing by examining the decision making at a bank and a set of retailers in a newsvendor setting

it s not now or never implications of investment timing and risk aversion on climate adaptation to extreme events abstract public investment into risk reduction infrastructure plays an important role in facilitating adaptation to climate impacted hazards and natural disasters in this paper we provide an economic framework to incorporate investment timing and insurance market risk preferences when evaluating projects related to reducing climate impacted risks the model is applied to a case study of bushfire risk management we find that optimal timing of the investment may increase the net present value npv of an adaptation project for various levels of risk aversion assuming risk neutrality while the market is risk averse is found to result in an unnecessary delay of the investment into risk reduction projects the optimal waiting time is shorter when the insurance market is more risk averse or when a more serious scenario for climatic change is assumed a higher investment cost or a higher discount rate will increase the optimal waiting time we also find that a stochastic discount rate results in higher npvs of the project than a discount rate that is assumed fixed at the long run average level

uncertainty and endogenous technical change in climate policy models until recently endogenous technical change and uncertainty have been modeled separately in climate policy models in this paper we review the emerging literature that considers both these elements together taken as a whole the literature indicates that explicitly including uncertainty has important quantitative and qualitative impacts on optimal climate change technology policy

the profitability of wagering on nfl games a reappraisal of previously suggested strategies for betting on football games using results of the period 1975 1981 casts considerable doubt on the profitability of relying on the past history of games for guidance in placing bets

exact evaluation of batch ordering inventory policies in two echelon supply chains with periodic review this paper studies a two echelon supply chain with stochastic and discrete consumer demand batch order quantities periodic inventory review and deterministic transportation times reorder point policies manage inventories at every location average inventory backorders and fill rates are evaluated exactly for each location safety stock is evaluated exactly at the lower echelon and a good approximation is detailed for the upper echelon numerical data are presented to demonstrate the model s utility it is found that system costs generally increase substantially if the upper echelon is restricted to carry no inventory of if the upper echelon is required to provide a high fill rate in many cases it is optimal to set the upper echelon s reorder point to yield near zero safety stock yet in some cases this simple heuristic can significantly increase supply chain operating costs finally policies selected under the assumption of continuous inventory review can perform poorly if implemented in an environment with periodic review

a robustness study of a multi echelon inventory model via simulation abstract this paper examines the robustness of a standard model of multi echelon inventory systems specifically the models discussed in axsater oper res 48 5 2000 686 a simulation model was developed to explore the model s ability to predict system performance for a two echelon one warehouse multiple retailer system using r q inventory policies under conditions that violate the model s fundamental modeling assumptions in particular the impact of non stationary demand on this stationary demand inventory model was examined the model performs well at the low demand and large retailer order batch size situations but our testing of the model indicated that care must be taken when applying this model to situations that violate its fundamental assumption these results should help practitioners to better understand the assumptions of these models and to determine when or when not to apply these models in practice

multi level inventory systems with stochastic demand when products are distributed over a large region it is common to have several local stocking locations close to the final customers these local inventories are in turn customers of a higher level stocking site for example a central warehouse the resulting inventory system see figure 1 is denoted a distribution system or an arborescent system open image in new window figure 1 two level distribution system

relative pricing of binary options in live soccer betting markets abstract live soccer betting markets differ from other binary options markets in that all fundamental information is observable the options mature in less than two hours and the markets are highly liquid this study presents a new method for the identification of hidden information in market prices the method is based on two independent poisson distributions and on a numerical algorithm for the aggregation of all market price information into one rational number the method is applied to an empirical dataset of real time market prices in 29 413 soccer games the results indicate that the method selects the most profitable markets and allows for a significant improvement in average investment returns

stock wars inventory competition in a two echelon supply chain with multiple retailers this paper studies the competitive and cooperative selection of inventory policies in a two echelon supply chain with one supplier andn retailers stochastic demand is monitored continuously retailers incur inventory holding and backorder penalty costs the supplier incurs holding costs for its inventory and backorder penalty costs for backorders at the retailers the latter cost reflects the supplier s desire to maintain adequate availability of its product to consumers previous research finds the supply chain cost minimizing reorder point policies the cooperative solution the competitive solution is a nash equilibrium a set of reorder points such that no firm can deviate from the equilibrium and lower its cost it is shown that nash equilibria exist and a method is presented to find all of them in some settings the cooperative solution is a nash equilibrium competition does not necessarily lead to supply chain inefficiency in other settings competition leads to costs that are substantially higher than optimal usually but not always the competitive supply chain carries too little inventory three cooperation strategies are discussed change incentives change equilibrium and change control a set of contracts is provided that changes the firms incentives so that the optimal policy is a nash equilibrium an equilibrium change can improve performance but does not guarantee optimal performance to change control the firms let the supplier choose all reorder points a key component in vendor managed inventory that change leads to optimal supply chain performance

instrument choice for environmental protection when technological innovation is endogenous this paper compares qualitatively and quantitatively the welfare effects of emissions taxes auctioned emissions permits and free grandfathered permits when technological innovation is endogenous we find that there is no unambiguous case for preferring any of these policy instruments the relative welfare ranking of instruments depends on the costs of innovation the extent to which innovations can be imitated the slope and level of the marginal environmental benefit function and the number of polluting firms we illustrate the types of situations when there can be significant welfare discrepancies between the policies and when there are not

coordination mechanisms of supply chain systems supply chain management scm has become an important management paradigm as supply chain members are often separate and independent economic entities a key issue in scm is to develop mechanisms that can align their objectives and coordinate their activities so as to optimize system performance in this paper we provide a review of coordination mechanisms of supply chain systems in a framework that is based on supply chain decision structure and nature of demand this framework highlights the behavioral aspects and information need in the coordination of a supply chain the identification of these issues points out several directions of future research in this area

structuring resource allocation decisions a framework for building multi criteria portfolio models with area grouped options multi criteria portfolio modelling has been extensively employed as an effective means to allocate scarce resources for investment in projects when considering costs benefits and risks some of these modelling approaches allow the grouping of projects into organisational areas thus also supporting the decision of resource allocation among organisational units in a way that is collectively efficient for the organisation however structuring in practice a portfolio model using this latter type of approach is not a trivial task how should areas be defined where should new projects be included how should one define the criteria to evaluate performance as far as we know there is very little indication in the operational research and decision sciences literatures on how to structure this type of model this paper suggests different ways to structuring portfolio models where projects are divided into areas and evaluated by multiple criteria and illustrates their use in two action research projects drawing on these experiences it then suggests a general framework for the structuring of such models in practice directions for future research are also identified

misunderstanding of the binomial distribution market inefficiency and learning behavior evidence from an exotic sports betting market abstract this paper uses the setting of a volleyball game and an exotic sports betting on the point difference of volleyball games to test whether people correctly understand the probabilities related to outcomes of a process which follows a binomial distribution we find that people consistently underestimate the probabilities of outcomes that correspond to extreme ends of the distribution this is consistent with the extremeness aversion bias documented in decision making studies whereas previous studies on the extremeness aversion bias find the existence of the bias in a consumer choice setting we document that this bias also exists in an investment setting we find evidence of learning behavior over time however it is not sufficient to eliminate the bias

optimal policies for multi echelon inventory problems with batch ordering in many production distribution systems materials flow from one stage to another in fixed lot sizes for example a retailer orders a full truckload from a manufacturer to qualify for a quantity discount a factory has a material handling system that moves full containers of parts from one production stage to the next in this paper we derive optimal policies for multi stage serial and assembly systems where materials flow in fixed batches the optimal policies have a simple structure and their parameters can be easily determined this research extends the multi echelon inventory theory in several ways it generalizes the clark scarf model by allowing batch transfers of inventories rosling 1989 shows that assembly systems can be interpreted as serial systems under the assumption that there are no setup costs we show that the series interpretation still holds when materials flow in fixed batches which satisfy a certain regularity condition finally veinott 1965 identifies an optimal policy for a single location inventory system with batch ordering this paper generalizes his result to multi echelon settings

one warehouse multiretailer systems with centralized stock information we consider a distribution system with a central warehouse and multiple retailers the warehouse orders from an outside supplier and replenishes the retailers which in turn satisfy customer demand the retailers are nonidentical and their demand processes are independent compound poisson there are economies of scale in inventory replenishment which is controlled by an echelon stock batch transfer policy for the special case with simple poisson demand we develop an exact method for computing the long run average holding and backorder costs of the system based on this exact method we provide approximations for compound poisson demand numerical examples are used to illustrate the accuracy of the approximations we also present a numerical comparison between the average costs of a heuristic echelon stock policy and an existing lower bound on the average costs of all feasible policies

modelling energy technologies in a competitive market abstract energy economic models must predict the mix of energy technologies in competitive energy markets we examine a market composed of several competing technologies with geographically heterogeneous cost distributions an approach for determining both the market share and average market cost of energy produced by these technologies is derived the formalism developed which is based on a conditional least cost distribution function can be used to correct the convertional logit treatment of these quantities in several existing models and to better interpret empirical data in order to determine more realistic cost distribution functions for energy technologies