opening the grey box social communities knowledge and culture in acquisitions international acquisitions are today the most important foreign direct investment vehicle and the ensuing integration processes are notoriously fraught with problems we situate discuss and develop the main results of an early study in the knowledge based view tradition the award winning bresman birkinshaw and nobel 1999 article to enhance and develop the central contributions regarding social communities knowledge and culture we use the metaphor of unpacking the grey box we argue that heavy socialization is a rational learning strategy even if the acquirer aims at appropriating the target s technology or wishes to impose its dominant logic

will dynamic pricing outperform theoretical analysis and empirical evidence from o2o on demand food service market abstract this study attempts to identify the pricing strategy of three most commonly used on demand food service platforms in china based on detailed information of more than 240 000 orders and further evaluates the impact of pricing strategy on platform performance we find that some platforms adopt dynamic pricing strategies while other platforms adopt static pricing strategies considering the unique structure of the o2o on demand food service market in china we develop a dyadic two sided market theory and demonstrate that compared with static pricing strategies dynamic pricing strategies perform better consistent with our theory our empirical analysis also suggests that platforms adopting dynamic pricing strategies have a significantly higher level of demand compared with platforms adopting static strategies in addition our results indicate the importance of delivery speed red envelopes and ratings in promoting demand

close the gaps a learning while doing algorithm for single product revenue management problems we consider a retailer selling a single product with limited on hand inventory over a finite selling season customer demand arrives according to a poisson process the rate of which is influenced by a single action taken by the retailer such as price adjustment sales commission advertisement intensity etc the relationship between the action and the demand rate is not known in advance however the retailer is able to learn the optimal action on the fly as she maximizes her total expected revenue based on the observed demand reactions using the pricing problem as an example we propose a dynamic learning while doing algorithm that only involves function value estimation to achieve a near optimal performance our algorithm employs a series of shrinking price intervals and iteratively tests prices within that interval using a set of carefully chosen parameters we prove that the performance of our algorithm is among the best of all possible algorithms in terms of the asymptotic regret the relative loss compared to the full information optimal solution our result closes the performance gaps between parametric and nonparametric learning and between the post price mechanism and the customer bidding mechanism important managerial insight from this research is that the values of information on both the parametric form of the demand function as well as each customer s exact reservation price are less important than prior literature suggests our results also suggest that firms would be better off to perform dynamic learning and action concurrently rather than sequentially

simultaneously learning and optimizing using controlled variance pricing price experimentation is an important tool for firms to find the optimal selling price of their products it should be conducted properly since experimenting with selling prices can be costly a firm therefore needs to find a pricing policy that optimally balances between learning the optimal price and gaining revenue in this paper we propose such a pricing policy called controlled variance pricing cvp the key idea of the policy is to enhance the certainty equivalent pricing policy with a taboo interval around the average of previously chosen prices the width of the taboo interval shrinks at an appropriate rate as the amount of data gathered gets large this guarantees sufficient price dispersion for a large class of demand models we show that this procedure is strongly consistent which means that eventually the value of the optimal price will be learned and derive upper bounds on the regret which is the expected amount of money lost due to not using the optimal price numerical tests indicate that cvp performs well on different demand models and time scales this paper was accepted by assaf zeevi stochastic models and simulation

real time dynamic pricing with minimal and flexible price adjustment we study a standard dynamic pricing problem where the seller a monopolist possesses a finite amount of inventories and attempts to sell the products during a finite selling season despite the potential benefits of dynamic pricing many sellers still adopt a static pricing policy because of 1 the complexity of frequent reoptimizations 2 the negative perception of excessive price adjustments and 3 the lack of flexibility caused by existing business constraints in this paper we develop a family of pricing heuristics that can be used to address all these challenges our heuristic is computationally easy to implement it requires only a single optimization at the beginning of the selling season and automatically adjusts the prices over time moreover to guarantee a strong revenue performance the heuristic only needs to adjust the prices of a small number of products and do so infrequently this property helps the seller focus his effort on the prices of the most important products instead of all products in addition in the case where not all products are equally admissible to price adjustment due to existing business constraints such as contractual agreement strategic product positioning etc our heuristic can immediately substitute the price adjustment of the original products with the price adjustment of similar products and maintain an equivalent revenue performance this property provides the seller with extra flexibility in managing his prices

dynamic pricing of inventory capacity with infrequent price changes we consider a problem of dynamically pricing a single product sold by a monopolist over a short time period if demand characteristics change throughout the period it becomes attractive for the company to adjust price continuously to respond to such changes i e price discriminate intertemporally however in practice there is typically a limit on the number of times the price can be adjusted due to the high costs associated with frequent price changes if that is the case instead of a continuous pricing rule the company might want to establish a piece wise constant pricing policy in order to limit the number of price adjustments such a pricing policy which involves optimal choice of prices and timing of price changes is the focus of this paper we analyze the pricing problem with a limited number of price changes in a dynamic deterministic environment in which demand depends on the current price and time and there is a capacity inventory constraint that may be set optimally ahead of the selling season the arrival rate can evolve in time arbitrarily allowing us to model situations in which prices decrease increase or neither we consider several plausible scenarios where pricing and or timing of price changes are endogenized various notions of complementarity single crossing property supermodularity and total positivity are explored to derive structural results conditions sufficient for the uniqueness of the solution and the monotonicity of prices throughout the sales period furthermore we characterize the impact of the capacity constraint on the optimal prices and the timing of price changes and provide several other comparative statics results additional insights are obtained directly from the solutions of various special cases

decomposition of aggregate carbon intensity for the manufacturing sector comparison of declining trends from 10 oecd countries for the period 1971 1991 abstract as with total energy consumption or aggregate energy intensity changes in aggregate carbon intensity may also be decomposed or attributed to changes in various components including fuel mix for electricity generation final energy mix sub sectoral economic activity and sub sectoral energy intensities the adaptive weighted divisia rolling base year index specification is applied to total carbon emissions from the manufacturing sector of 10 oecd countries for the period 1971 1991 declines in aggregate carbon intensity for these countries range from 70 and may be primarily attributed to decreases in energy intensity i e increases in the average factor productivity of energy however these declines in aggregate carbon intensity appear to have a complex linkage to increases in energy prices as well as changes in other determinants of gross industrial output

on the surprising sufficiency of linear models for dynamic pricing with demand learning we consider a multiperiod single product pricing problem with an unknown demand curve the seller s objective is to adjust prices in each period so as to maximize cumulative expected revenues over a given finite time horizon in doing so the seller needs to resolve the tension between learning the unknown demand curve and maximizing earned revenues the main question that we investigate is the following how large of a revenue loss is incurred if the seller uses a simple parametric model that differs significantly i e is misspecified relative to the underlying demand curve we measure performance by analyzing the price trajectory induced by this misspecified model and quantifying the magnitude of revenue losses as a function of the time horizon relative to an oracle that knows the true underlying demand curve the price of misspecification is expected to be significant if the parametric model is overly restrictive somewhat surprisingly we show under reasonably general conditions that this need not be the case this paper was accepted by gerard cachon stochastic models and simulation

manufacturing energy use in oecd countries decomposition of long term trends abstract in this paper we examine manufacturing energy use in 13 oecd countries over the period 1971 1995 we describe changes in aggregate energy intensity using the adaptive weighting divisia decomposition method we contrast the development in the periods after the oil price shocks of 1973 and 1979 with the period of relatively stable energy prices after the oil price crash of 1986 the results show that manufacturing output grew in most countries pushing up energy use the share of electricity increased in almost every sector while there was a clear trend away from oil and coal towards natural gas changes in the structure of output drove up energy use between 1973 and 1994 in some countries and down in others changes in energy intensities had a profound and downward effect on manufacturing energy use in all countries however contrasting the period after oil prices fell in 1986 with earlier years we see that for most countries the rate of energy intensity decline slowed slightly but did not reverse with falling prices in a few countries efficiency improvements continued to have a strong effect this suggests that even without higher prices improvements of energy efficiency seems to take place

anonymous shell companies a global audit study and field experiment in 176 countries to test whether firms behave consistently with international law prohibiting anonymous incorporation we conducted a global audit study and field experiment using data from 1639 incorporation firms in 176 countries we requested anonymous incorporation and randomly assigned references to international law threat of penalties norms of appropriate behavior or a placebo we find a substantial number of firms willing to flout international standards and show that those in oecd countries proved significantly less compliant with rules than in developing countries or tax havens firms in tax havens displayed significantly greater compliance and were sensitive to experimental interventions invoking international law

technical note dynamic pricing and demand learning with limited price experimentation in a dynamic pricing problem where the demand function is not known a priori price experimentation can be used as a demand learning tool existing literature usually assumes no constraint on price changes but in practice sellers often face business constraints that prevent them from conducting extensive experimentation we consider a dynamic pricing model where the demand function is unknown but belongs to a known finite set the seller is allowed to make at most m price changes during t periods the objective is to minimize the worst case regret i e the expected total revenue loss compared with a clairvoyant who knows the demand distribution in advance we demonstrate a pricing policy that incurs a regret of ologmt or m iterations of the logarithm furthermore we describe an implementation of this pricing policy at groupon a large e commerce marketplace for daily deals the field study shows significant impact on revenue and bookings the e companion is available at https doi org 10 1287 opre 2017 1629

knowledge transfer in international acquisitions this paper reports on a multimethod study of knowledge transfer in international acquisitions using questionnaire data we show that the transfer of technological know how is facilitated by communication visits meetings and by time elapsed since acquisition while the transfer of patents is associated with the articulability of the knowledge the size of the acquired unit and the recency of the acquisition using case study data we show that the immediate post acquisition period is characterized by imposed one way transfers of knowledge from the acquirer to the acquired but over time this gives way to high quality reciprocal knowledge transfer

international acquisition success social community and dominant logic dimensions international acquisitions intended to achieve knowledge transfers and improvements of innovation capacity can only be successful if the acquirer devotes balanced attention to a building a unified social community and b achieving requisite commonality in dominant logic the balance between these two dimensions of success depends on the activity class considered in some activity classes imposing the acquiring firm s dominant logic will be dysfunctional and therefore the post acquisition managerial focus may need to shift towards social community building bresman birkinshaw and nobel s 1999 acclaimed jibs paper should be commended for identifying the social community dimension as a critical driver of international acquisition success

knowledge transfer in international acquisitions a retrospective in this retrospective we summarise and discuss the findings of our 1999 jibs paper knowledge transfer in international acquisitions and we consider how research in this area has evolved over the last decade the paper s key contribution was to show how the post acquisition integration process in a sample of three international acquisitions led to the creation of a social community characterised by two way knowledge sharing between the acquirer and acquired companies we discuss how the timing of this publication as an early contribution to the knowledge based perspective on the firm helped its visibility and we consider the boundary conditions around our findings

energy intensity developments in 40 major economies structural change or technology improvement this study analyzes energy intensity trends and drivers in 40 major economies using the wiod database a novel harmonized and consistent dataset of input output table time series accompanied by environmental satellite data we use logarithmic mean divisia index decomposition to 1 study trends in global energy intensity between 1995 and 2007 2 attribute efficiency changes to either changes in technology or changes in the structure of the economy and 3 highlight sectoral and regional differences we first show that heterogeneity within each sector across countries is high these general trends within the sectors are dominated by large economies first and foremost the united states in most cases heterogeneity is lower within each country across the different sectors regarding changes of energy intensity at the country level improvements between 1995 and 2007 are largely attributable to technological change while structural change is less important in most countries notable exceptions are japan the united states australia taiwan mexico and brazil where a change in the industry mix was the main driver behind the observed energy intensity reduction

optimal starting times for end of season sales and optimal stopping times for promotional fares many industries face the problem of selling a fixed stock of items over a finite horizon these industries include airlines selling seats before planes depart hotels renting rooms before midnight theaters selling seats before curtain time and retailers selling seasonal goods such as air conditioners or winter coats before the end of the season given a fixed number of seats rooms or coats the objective for these industries is to maximize revenues in excess of salvage value when demand is price sensitive and stochastic pricing is an effective tool to maximize revenues in this paper we address the problem of deciding the optimal timing of a single price change from a given initial price to either a given lower or higher second price under mild conditions we show that it is optimal to decrease resp to increase the initial price as soon as the time to go falls below resp above a time threshold that depends on the number of yet unsold items

bayesian dynamic pricing policies learning and earning under a binary prior distribution motivated by applications in financial services we consider a seller who offers prices sequentially to a stream of potential customers observing either success or failure in each sales attempt the parameters of the underlying demand model are initially unknown so each price decision involves a trade off between learning and earning attention is restricted to the simplest kind of model uncertainty where one of two demand models is known to apply and we focus initially on performance of the myopic bayesian policy mbp variants of which are commonly used in practice because learning is passive under the mbp that is learning only takes place as a by product of actions that have a different purpose it can lead to incomplete learning and poor profit performance however under one additional assumption a constrained variant of the myopic policy is shown to have the following strong theoretical virtue the expected performance gap relative to a clairvoyant who knows the underlying demand model is bounded by a constant as the number of sales attempts becomes large this paper was accepted by gerard p cachon stochastic models and simulation

periodic pricing of seasonal products in retailing this paper studies intertemporal pricing policies when selling seasonal products in retail stores we first present a continuous time model where a seller faces a stochastic arrival of customers with different valuations of the product for this model we characterize the optimal pricing policies as functions of time and inventory we use this model as a benchmark against which we compare more realistic models that consider periodic pricing reviews we show that the structure of the optimal pricing policies in this case is consistent with the procedures observed in practice retail stores successively discount the product during the season and promote a liquidation sale at the end of the planning horizon we also show that the loss experienced when implementing periodic pricing reviews instead of continuous policies is small when the appropriate number of reviews is chosen several interesting economic insights emerge from our analysis for example uncertainty in the demand for new products leads to higher prices larger discounts and more unsold inventory finally we study the effect of announced discount policies on prices and profits we show that stores that have adopted this type of strategy usually set prices such that with high probability the merchandise is sold during the first periods and the largest discounts rarely take place

dynamic pricing under a general parametric choice model we consider a stylized dynamic pricing model in which a monopolist prices a product to a sequence of t customers who independently make purchasing decisions based on the price offered according to a general parametric choice model the parameters of the model are unknown to the seller whose objective is to determine a pricing policy that minimizes the regret which is the expected difference between the seller s revenue and the revenue of a clairvoyant seller who knows the values of the parameters in advance and always offers the revenue maximizing price we show that the regret of the optimal pricing policy in this model is theta sqrt t by establishing an omega sqrt t lower bound on the worst case regret under an arbitrary policy and presenting a pricing policy based on maximum likelihood estimation whose regret is cal o sqrt t across all problem instances furthermore we show that when the demand curves satisfy a well separated condition the t period regret of the optimal policy is log t numerical experiments show that our policies perform well

nonparametric advertising budget allocation with inventory constraint abstract in this paper we study the optimization problem of the advertising budget allocation for revenue management faced by a marketer besides the advertising budget the marketer is subject to an inventory constraint during the promotion season the marketer can affect sales by spending on advertising but does not initially know the relationship between the advertising expense and consequent sales we propose a nonparametric learning while doing budget allocation policy for the problem specifically we first conduct a sequence of advertising experiments to learn predict the market sales response through observing realized sales exploration then based on the learned sales function determine the following budget allocation planning exploitation in particular during the exploration and exploitation phases we need to balance the advertising and inventory budgets simultaneously we show that our policy is asymptotically optimal as the size of the market increases by constructing a worst case example we show that our policy achieves near best asymptotic performance we also provide numerical illustrations to show how our policy works and discuss how its performance changes as the system parameters vary we also glen some managerial implications of our model and policy from the numerical results

dynamic pricing with an unknown demand model asymptotically optimal semi myopic policies we consider a monopolist who sells a set of products over a time horizon of t periods the seller initially does not know the parameters of the products linear demand curve but can estimate them based on demand observations we first assume that the seller knows nothing about the parameters of the demand curve and then consider the case where the seller knows the expected demand under an incumbent price it is shown that the smallest achievable revenue loss in t periods relative to a clairvoyant who knows the underlying demand model is of order t in the former case and of order log t in the latter case to derive pricing policies that are practically implementable we take as our point of departure the widely used policy called greedy iterated least squares ils which combines sequential estimation and myopic price optimization it is known that the greedy ils policy itself suffers from incomplete learning but we show that certain variants of greedy ils achieve the minimum asymptotic loss rate to highlight the essential features of well performing pricing policies we derive sufficient conditions for asymptotic optimality

information acquisition for capacity planning via pricing and advance selling when to stop and act this paper investigates a capacity planning strategy that collects commitments to purchase before the capacity decision and uses the acquired advance sales information to decide on the capacity in particular we study a profit maximization model in which a manufacturer collects advance sales information periodically prior to the regular sales season for a capacity decision customer demand is stochastic and price sensitive once the capacity is set the manufacturer produces and satisfies customer demand to the extent possible from the installed capacity during the regular sales period we study scenarios in which the advance sales and regular sales season prices are set exogenously and optimally for both scenarios we establish the optimality of a control band or a threshold policy that determines when to stop acquiring advance sales information and how much capacity to build we show that advance selling can improve the manufacturer s profit significantly we generate insights into how operating conditions such as the capacity building cost and market characteristics such as demand variability affect the value of information acquired through advance selling from this analysis we identify the conditions under which advance selling for capacity planning is most valuable finally we study the joint benefits of acquiring information for capacity planning through advance selling and revenue management of installed capacity through dynamic pricing

multiculturalism from a cognitive perspective patterns and implications multiculturalism the internal representation of multiple cultural meaning systems has critical implications for global managers and multinational corporations mncs understanding multiculturalism is becoming increasingly important given that the locations within which mnc activity resides and the composition of the workforce even within a given location are more diverse building on the connectionism perspective we offer a novel cognitive conceptualization of multiculturalism that incorporates the individual s multicultural cognitive content and structure based on that we explain how specific sociocultural experiences interact with existing individual cognitions to form different patterns of multiculturalism specifically we propose five stylized patterns compartmentalization integration inclusion convergence and generalization and explain how they are developed through specific sociocultural experiences we discuss how different patterns of multiculturalism influence specific capabilities of multicultural mnc managers and their effectiveness in a variety of critical mnc tasks we believe the cognitive connectionist perspective which has not been brought before into international business discussions of culture and cultural capabilities holds great promise for better understanding global managers capabilities and development

innovation in multinational corporations control and communication patterns in international r d operations this paper addresses issues of global innovation in multinational corporations by examining the patterns of communication and control in international rd 2 local and international adaptors both focus their communication on their internal corporate network and 3 international creators have strong internally and externally oriented networks of relationships the implications for the management of global innovation are discussed 1998 john wiley sons ltd

manufacturing energy use in eight oecd countries decomposing the impacts of changes in output industry structure and energy intensity this paper examines trends in manufacturing energy use in eight oecd countries decomposing the changes that occured between 1973 and 1987 into the effects of changes in aggregate manufacturing activity industry structure and energy intensities measured at the industry group level while manufacturing production grew in every country except the uk the rate of growth was variable from nation to nation structural change led to modest reductions in energy use in most countries although in norway structural change led to substantial growth in energy use the reduction in energy intensities was strikingly uniform across all nations ranging from 20 norway to 36 japan over the period of the analysis while other studies have used divisia decomposition techniques we use an alternative method based on laspeyres indices a comparison of the two techniques shows that they yield closely similar empirical results although the laspeyres approach is more easily interpreted while the interactions between changes in structure and intensity are arbitrarily assigned to the two factors by the divisia approach the lapeyres method yields interaction terms that explicitly account for such effects

asean tigers and sustainability of energy use decomposition analysis of energy and co2 efficiency dynamics abstract this study is a comparative analysis of the development of energy intensity and co2 emission intensity in the asean countries in the years 1971 97 the reasons and driving forces behind the changes are studied in the article using a complete decomposition methodology the decomposition analysis explains energy use or co2 emissions with three different factors activity effect structural effect and intensity effect the authors provide an analysis of dynamic changes of energy consumption and co2 emission flows intensity effects on energy use and co2 emissions revealed large differences in the performance of asean countries an interesting finding of the study is that in the 1990s the intensity effects on co2 emissions in asean countries have started to increase indicating decreasing co2 efficiencies of the economies the general observation on the basis of decomposition analyses is that the phase of industrialization is increasing the energy intensity of the nations and when the increased energy demand is fulfilled with fossil fuels the co2 emissions will inevitable grow however it has to be recognized that the co2 emissions per capita in asean countries are very low except in singapore compared with many oecd countries