taming the bullwhip effect whilst watching customer service in a single supply chain echelon we study a generalised order up to policy that has highly desirable properties in terms of order and inventory variance and customer service levels it generates we quantify exactly the variance amplification in replenishment orders i e the bullwhip effect and the variance of inventory levels over time for i i d and the weakly stationary auto regressive ar moving average ma and auto regressive moving average arma demand processes we demonstrate that high customer service as measured by fill rate and smooth replenishments need not increase inventory cost substantially we observe that in some instances of the arma demand pattern this comes at the expense of a relatively small increase in safety stock whilst in other instances inventory levels can actually be reduced

on the replenishment policy when the market demand information is lagged we consider a situation where the most up to date information on the market demand and the inventory levels is not available to a replenishment decision maker in a single echelon of a supply chain the objective of the decision maker is to minimise the sum of the inventory and the production costs an intuitively attractive strategy under this setting might be to reduce the information time lag as much as possible by utilising information technologies such as rfid we call this strategy the time lag elimination strategy tes however this course of action requires investment in information systems and will incur a running cost we propose an alternative strategy that has similar economic consequences as the tes strategy but it does not require new information systems we call this strategy the controlling dynamics strategy cds the benefit coming from cds is quantified and is compared to that from tes we also quantify the benefits gained from the combined use of these two strategies a new ordering policy is introduced that is easy to implement without any forecasting systems and can reduce the production cost significantly

the impact of forecasting methods on the bullwhip effect abstract this paper considers the impact of forecasting methods on the bullwhip effect for a simple replenishment system in which a first order autoregressive process describes the customer demand and an order up to inventory policy characterizes the replenishment decision a bullwhip effect measure is derived for the optimal forecasting procedure that minimizes the mean squared forecasting error for the specified demand process similar measures are obtained for the moving average and exponential smoothing methods the findings indicate that different forecasting methods lead to bullwhip effect measures with distinct properties in relation to lead time and underlying parameters of the demand process moreover a simple rule is established to help managers select a forecasting method that yields the lowest inventory 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

supply chain forecasting when information is not shared the operations management literature is abundant in discussions on the benefits of information sharing in supply chains however there are many supply chains where information may not be shared due to constraints such as compatibility of information systems information quality trust and confidentiality furthermore a steady stream of papers has explored a phenomenon known as downstream demand inference ddi where the upstream member in a supply chain can infer the downstream demand without the need for a formal information sharing mechanism recent research has shown that under more realistic circumstances ddi is not possible with optimal forecasting methods or single exponential smoothing but is possible when supply chains use a simple moving average sma method in this paper we evaluate a simple ddi strategy based on sma for supply chains where information cannot be shared this strategy allows the upstream member in the supply chain to infer the consumer demand mathematically rather than it being shared we compare the ddi strategy with the no information sharing nis strategy and an optimal forecast information sharing fis strategy in the supply chain the comparison is made analytically and by experimentation on real sales data from a major european supermarket located in germany we show that using the ddi strategy improves on nis by reducing the mean square error mse of the forecasts and cutting inventory costs in the supply chain

quantifying the bullwhip effect in closed loop supply chains the interplay of information transparencies return rates and lead times abstract the bullwhip effect manifests itself in the form of an increased order and inventory variability in the uppermost nodes of the supply chain this dynamic phenomenon is not yet well understood in closed loop supply chain settings despite their growing importance in modern societies pursuing circular economy opportunities indeed the problem specific literature has provided somewhat conflicting findings to better understand the bullwhip effect in closed loop systems we obtain expressions for the order and inventory variance amplification in four archetypes that differ in the structure of information transparency interestingly we observe that the impact of return rates and lead times on the system performance strongly depend on the degree of supply chain visibility this perspective allows us to revisit discrepancies in prior works we later move the study from the operational to the economic prism here we prove the existence of an optimal return rate and we derive its expression in the four closed loop supply chain archetypes we show that the optimal rate is dependent on the node s cost structure the lead times and the variability of demand properties of the different closed loop systems and relevant managerial implications are also discussed in our work

information distortion in a supply chain the bullwhip effect this article originally appeared in management science april 1997 volume 43 number 4 pp 546 558 published by the institute of management sciences consider a series of companies in a supply chain each of whom orders from its immediate upstream member in this setting inbound orders from a downstream member serve as a valuable informational input to upstream production and inventory decisions this paper claims that the information transferred in the form of orders tends to be distorted and can misguide upstream members in their inventory and production decisions in particular the variance of orders may be larger than that of sales and distortion tends to increase as one moves upstream a phenomenon termed bullwhip effect this paper analyzes four sources of the bullwhip effect demand signal processing rationing game order batching and price variations actions that can be taken to mitigate the detrimental impact of this distortion are also discussed

the bullwhip effect progress trends and directions the bullwhip effect refers to the phenomenon where order variability increases as the orders move upstream in the supply chain this paper provides a review of the bullwhip literature which adopts empirical experimental and analytical methodologies early econometric evidence of bullwhip is highlighted findings from empirical and experimental research are compared with analytical and simulation results assumptions and approximations for modelling the bullwhip effect in terms of demand forecast delay replenishment policy and coordination strategy are considered we identify recent research trends and future research directions concerned with supply chain structure product type price competition and sustainability

another look on the relationships between oil prices and energy prices this paper employs the quantile autoregressive distributed lags qardl model developed recently by cho et al 2015 to investigate the pass through of oil prices to a set of energy prices this approach allows analyzing simultaneously short term connections and long run cointegrating relationships across a range of quantiles it also provides insights on the short run predictive power of oil prices in predicting energy prices while accounting for the cointegration between oil prices and each of the considered energy prices in low medium and high quantiles two key findings emerge from this paper first all considered energy prices are shown to be cointegrated with oil price across quantiles meaning that a stationaryequilibriumrelationship exists between single energy price and oil price second we find evidence that oil price is a significant predictor of individual petroleum products prices and natural gas in the short run this paper has important policy implications for forecasters energy policy makers and portfolio managers

an arima supply chain model this paper presents a multistage supply chain model that is based on autoregressive integrated moving average arima time series models given an arima model of consumer demand and the lead times at each stage it is shown that the orders and inventories at each stage are also arima and closed form expressions for these models are given the paper also discusses the causes of the bullwhip effect a phenomenon in which variation in demand produces larger variations in upstream orders and inventory this discussion reveals how different modeling can lead to different insights because they make different assumptions about the cause of the bullwhip effect these observations are used to develop managerial insights about reducing the bullwhip effect

a threshold cointegration analysis of asymmetric price transmission from crude oil to gasoline prices abstract this study provides new supportive evidence for asymmetric adjustment in u s retail gasoline prices the asymmetric transmission is found to occur not just through the spot markets of crude oil and refinery gasoline but also through their future markets further evidence also shows that the observed asymmetry in price transmission primarily occurs downstream not upstream of the transmission process

rational actors tit for tat types and the evolution of cooperation abstract evolutionary models in economics have often been criticized for failing to allow for rational maximizing behavior the present paper represents a step toward correcting this deficiency by introducing rational actors into an evolutionary model of the finitely repeated prisoners dilemma at the same time the model endogenizes the uncertainty postulated in the classic model of kreps et al 1982 thus explaining cooperation by rational actors in the finitely repeated prisoners dilemma a testable implication of the model is that the level of voluntary cooperation in a society will be relatively high where geographical mobility is relatively low

inventories and the volatility of production a stylized fact associated with inventory behavior is that the variance of production exceeds the variance of sales this paper presents a model of production decisions with demand uncertainty that incorporates no nnegativity constraints on inventories even with no productivity shocks optimal behavior by the firm is consistent with this stylized fact either if demand exhibits positive serial correlation or if the firm can backlog excess demand the reason is that a demand shock affects both the actual inventory level given unchanged production and the desired level production must replenish the stock and adjust to the new desired level copyright 1987 by american economic association

an empirically simulated investigation of the impact of demand forecasting on the bullwhip effect evidence from u s auto industry this study empirically examines the impacts of three major aspects of demand forecasting on the magnitude of the bullwhip effect three research questions are addressed to investigate the association between 1 forecast accuracy 2 aggregate forecasting and 3 responsive forecasting and the bullwhip effect using forecasted demand generated from popular time series forecasting models and real life demand data the study investigates the relationship between the forecasted results and the consequential bullwhip effect the findings show that the forecasting methods used lead to the variation of the bullwhip effect moreover the lead time reduction and the stable demand forecast are beneficial to reduce the bullwhip effect however our empirical results differ from previous findings in two ways i improving forecast accuracy does not necessarily reduce the bullwhip effect and ii aggregate forecasting does not always reduce the bullwhip effect

evolution in economic games abstract this paper examines the conditions under which evolutionary processes select equilibrium strategies of agents or firms under plausible dynamics optimal selection takes place provided that economic agents are small relative to the environment that is each such agent has a negligible effect on others payoffs however when this assumption is not met survival need not imply optimality examples in the contexts of bargaining bidding and market competition are presented

fill rate in a periodic review order up to policy under auto correlated normally distributed possibly negative demand we investigate the inventory service metric known as the fill rate the proportion of demand that is immediately fulfilled from inventory the task of finding analytical solutions for general cases is complicated by a range of factors including correlation in demand double counting of backlogs and proper treatment of negative demand in the literature two approximate approaches are often proposed our contribution is to present a new fill rate measure for normally distributed auto correlated and possibly negative demand we treat negative demand as returns our approach also accounts for accumulated backlogs the problem reduces to identifying the minimum of correlated normally distributed bivariate random variables there exists an exact solution but it has no closed form however the solution is amenable to numerical techniques and we present a custom microsoft excel function for practical use numerical investigations reveal that the new fill rate is more robust than previous measures existing fill rate measures are likely to cause excessive inventory investment especially when fill rate targets are modest a strongly positive or negative autocorrelation in demand is present or negative demands exist our fill rate calculation ensures that the target fill rate is achieved without excessive inventory investments

hope springs eternal learning and the stability of cooperation in short horizon repeated games abstract this paper considers learning rates in finitely repeated prisoners dilemmas if players think their opponents might be relatively cooperative e g tit for tat or grim types they will cooperate in finitely repeated prisoners dilemmas see kreps et al j econom theory 27 1982 245 however if there are actually no cooperative types players will eventually learn this and cooperation will break down this paper shows that this learning is extremely slow so it will take an extremely long time for cooperation to break down thus suppose the world is either good or bad the probability of a grim type is 0 if the world is good and zero if the world is bad successive generations pair up to play finitely repeated prisoners dilemmas players observe play in previous generations and use bayes rule to update their prior that the world is good we show that if the world is really bad then falls o 2 log 1 per generation on average thus if is small there is less cooperation if the world is good but cooperation may become more stable for a representative 19 period repeated prisoners dilemma beliefs fall one percentage point on average after a thousand generations to derive these learning rates we must refine existing results on the sensitivity of repeated games to kreps et al 1982 type perturbations specifically we show cooperation is possible in perturbed prisoners dilemmas repeated o log 1 times this improves significantly on the o 1 results in previous work the paper thus provides two new reasons why cooperation tends to be stable even in short horizon repeated games

impacts of forecast inventory policy and lead time on supply chain inventory a numerical study abstract this paper first proposes the use of metaheuristic to combine with exponential smoothing methods in forecasting future demands and in determining the optimal inventory policy values for each node in a supply chain network based on historical demand or order streams without the need of any prior knowledge about the demand distribution or distribution fitting the effects of five demand forecasting methods two inventory policies and three lead times on the total inventory cost of a 3 echelon serial supply chain system are then investigated the effect of sharing the demand information for planning the inventories is also compared with that of no sharing for testing 15 quarterly and 15 monthly time series were taken from the m3 competition and are considered as the multi item demand streams to be fulfilled in the supply chain the results indicate that 1 the damped pegel forecasting method is the best in terms of prediction errors because it outperforms others in three of five measures followed by the simple exponential smoothing that wins one of the remaining two and ties the damped pegel in one 2 the supply chain inventory cost increases with increasing lead time and echelon level of the supply chain when the s s policy is used but not the r q policy 3 the r q inventory policy generally incurs lower supply chain inventory cost than the s s policy 4 sharing demand information reduces inventory cost and the reduction is higher for s s than for r q 5 the best demand forecasting method for minimizing inventory cost varies with the inventory policy used and lead time and 6 the correlation between forecasting errors and inventory costs is either negligible or minimal

coordinating lead times and safety stocks under autocorrelated demand we consider a supply chain in which orders and lead times are linked endogenously as opposed to assuming lead times are exogenous this assumption is relevant when a retailer s orders are produced by a supplier with finite capacity and replenished when the order is completed the retailer faces demands that are correlated over time either positively or negatively which may for example be induced by a pricing or promotion policy the auto correlation in demand affects the order stream placed by the retailer onto the supplier and this in turn influences the resulting lead times seen by the retailer since these lead times also determine the retailer s orders and its safety stocks which the retailer must set to cover lead time demand there is a mutual dependency between orders and lead times the inclusion of endogenous lead times and autocorrelated demand represents a better fit with real life situations however it poses some additional methodological issues compared to assuming exogenous lead times or stationary demand processes that are independent over time by means of a markov chain analysis and matrix analytic methods we develop a procedure to determine the distribution of lead times and inventories that takes into account the correlation between orders and lead times our analysis shows that negative autocorrelation in demand although more erratic improves both lead time and inventory performance relative to iid demand positive correlation makes matters worse than iid demand due to the endogeneity of lead times these effects are much more pronounced and substantial error may be incurred if this endogeneity is ignored

impact of market demand mis specification on a two level supply chain this paper investigates the impact of mis specifying the market demand process on a serially linked two level supply chain box jenkins models are used to represent both the true and a mis specified market demand processes it is shown that the impact of mis specification on cost is minor if the supply chain tries to minimise the market demand forecast errors furthermore our analysis suggests that mis specification does not always result in additional costs a managerial insight is revealed poor forecast accuracy is not always bad for the total supply chain costs in other words employing more accurate forecasting methods may actually result in higher total supply chain costs

the data driven newsvendor with censored demand observations motivated by data from a large european retail chain we tackle the newsvendor problem with censored demand observations by a distribution free approach based on a data driven approach for this purpose we extend the model introduced in chap 3 to improve the forecast accuracy we simultaneously estimate unobservable lost sales determine the coefficients of the exogenous variables which drive demand and calculate the optimal order quantity since demand exceeding supply cannot be recorded we use the timing of hourly sales occurrences to establish daily sales patterns these sales patterns allow conclusions on the amount of unsatisfied demand and thus the true customer demand to determine the coefficients of the inventory function we formulate a linear programming model that balances inventory holding and penalty costs based on the censored demand observations in a numerical study with data generated from the normal and the negative binomial distribution we compare our model with other parametric and non parametric estimation approaches we evaluate the performance in terms of inventory and service level for non price dependent demands and different censoring levels we find that the data driven newsvendor model copes especially well with highly censored data and price dependent demand in most settings with price dependent demand it achieves similar or higher service levels by holding lower inventories than other benchmark approaches from the literature finally we show that the non parametric approaches are better than the parametric ones based on real data with several exogenous variables where the true demand distribution is unknown

recent evolutionary theorizing about economic change this famous passage from marshall s principles of economics it first appeared in the fifth edition which came out in 1907 nicely brings out two issues which are as germane to economics today as they were when marshall wrote the first is the heavy reliance by economists in their formal theorizing on the notion of equilibrium the other is the appeal that biological conceptions3x201d have for many economists particularly when their focus is on economic change

evolution in the finitely repeated prisoner s dilemma abstract this paper examines some aspects of evolutionary dynamic behavior in the finitely repeated prisoner s dilemma the fitness of cooperation found in the best known simulation of this type that by robert axelrod stems from strategy set restrictions the game used for the simulation has a continuum of pure cooperation equilibria and no pure defection equilibrium some new simulations are presented here for the finitely repeated game although cooperation is ultimately exploited and extinguished dynamic paths can pseudo converge in ways that allow partial cooperation to flourish for extended periods of time

oil price fluctuation volatility spillover and the ghanaian equity market implication for portfolio management and hedging effectiveness abstract this study attempts to contribute to the literature on stock markets and energy prices by examining the dynamic volatility and volatility transmission between oil and ghanaian stock market returns in a multivariate setting using the recently developed var garch var agarch and dcc garch frameworks in turn the models results are used to compute and analyze the optimal weights and hedge ratios for oil stock portfolio holdings for comparison purposes and to put the paper more in the perspective of west africa the nigerian stock market is also included in the analysis our findings point to the existence of significant volatility spillover and interdependence between oil and the two stock market returns while spillover effects are stronger for nigeria the transmission of volatility is much more apparent from oil to stock than from stock to oil in the case of ghana also the study demonstrates evidence of short term predictability in oil and stock price changes through time and reveals that conditional volatility changes more rapidly as result of substantial effects of past volatility rather than past news shocks for all market returns moreover we show that there is a slightly more effective hedge in the two stock markets under the dcc garch framework our preferred model compared to the other two models although hedging effectiveness is much greater for ghana on the whole our findings for optimal hedge ratios are consistent with other studies and particularly the view that oil assets should be an integral part of a diversified portfolio of stocks and suggest that a better understanding of volatility links is crucial for portfolio management in the presence of oil price risk finally the existence of multivariate asymmetric effects and dynamic conditional correlations as revealed by the var agarch and dcc garch models make it clear that the assumptions of symmetric effects and constant conditional correlations are not supported empirically

cooperation secret handshakes and imitation in the prisoners dilemma building on a j robson 1990 j theoret biol 144 379 396 we introduce into the repeated prisoners dilemma mutants who have the ability to send a costly signal i e the secret handshake before each round of the game and to condition their actions on whether or not they observe the same signal from their opponent we show that as mutation probabilities approach zero in the limit cooperation occurs a positive fraction of the time using simulations to study the behavior of the system with nonzero mutation probabilities we obtain similar results surprisingly in some cases an increased payoff to unilateral defection actually raises the level of cooperation journal of economic literature classification numbers c70 c72 d60

inventory performance under staggered deliveries and autocorrelated demand production plans often span a whole week or month even when independent production lots are completed every day and service performance is tallied daily such policies are said to use staggered deliveries meaning that the production rate for multiple days are determined at a single point in time assuming autocorrelated demand and linear inventory holding and backlog costs we identify the optimal replenishment policy for order cycles of length p with the addition of a once per cycle audit cost we optimize the order cycle length p via an inverse function approach in addition we characterize periodic inventory costs availability and fill rate as a consequence of staggering deliveries the inventory level becomes cyclically heteroskedastic this manifests itself as ripples in the expected cost and service levels nevertheless the cost optimal replenishment policy achieves a constant availability by using time varying safety stocks this is not the case with suboptimal constant safety stock policies where the availability fluctuates over the cycle

the message in north american energy prices how similar is the price behavior of north american natural gas fuel oil and power prices using current state of the art econometric methodology we explore the degree of shared trends across north american energy markets across these markets there appear to be effective arbitraging mechanisms for the price of natural gas and fuel oil but not for the price of electricity