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We examine mutual funds’ compliance with the SEC’s ‘plain English’ rules promising to make disclosures accessible to ordinary investors through short and easy-to-read statements. We find that summary prospectus (497K) risk sections have nearly doubled in size over the last decade. Also, both risk and strategy sections are hard to read. Next, we explore if fund disclosure attributes signal information about fund performance, even in the absence of price discovery. Using a two-way fixed effect regression analysis with an interaction term, we show a relationship between plain English attributes and fund returns and volatility. Easy-to-read principal risk sections are associated with higher fund returns and volatility, but we find the opposite with investment strategy sections. We also explore whether readability effects persist in funds with high derivative word counts, a proxy for strategic and semantic complexity. We link the different information signals between the two sections to content and regulatory differences. Our findings highlight enforcement opportunities for the SEC.

We study the distribution channel decision of a manufacturer who considers whether to add an online channel (direct channel) to its brick-and-mortar retailer (indirect channel). The retailer faces the opportunity to invest in store assistance to help consumers choose products and thus reduce product returns. Special attention is given to the impact of product returns and retailer's store assistance investment on manufacturer's dual channel decision. We examine conditions under which the manufacturer uses dual channels and how various relevant factors affect its channel decision under two settings, depending on whether the retailer has its own online store or not. When the retailer does not have its online store, we find that (i) the addition of the direct channel raises the wholesale price; (ii) the direct channel addition hurts the retailer if the nonreplacement rate is low; (iii) the manufacturer has a lower incentive to add the direct channel when the retailer's service cost is lower or its returns reduction rate from service investment is higher; and (iv) the manufacturer should treat its own returns handling cost as a key factor in its channel structure decision. In addition, when the retailer operates an online store, we find that the manufacturer may have an incentive to add a direct channel such that both firms own direct channels.

This paper considers a one-retailer and one-supplier supply chain and addresses the question of how a retailer should use its ordering and pricing decisions to respond to its supplier’s temporary price discounts. The paper considers a hybrid environment – somewhere between deterministic and stochastic modelling approaches – that is, the retailer does not know when the next promotion from its supplier will occur but, once the promotion is announced, all its details are deterministic and often there is some time remaining before the promotion actually starts. We include in the objective function penalties on deviations from the original plan and explore the properties of the retailer’s ordering and pricing decisions under fixed and flexible set-up scenarios. We show that, when the set-up epochs are fixed, the retailer’s order quantities are monotonic and non-decreasing in situations where retail prices can be either fixed or flexible. When the set-up epochs are flexible, the ordering cycle is identical. Fin...

We consider a dynamic pricing model in which the instantaneous rate of the demand arrival process is dependent on not only the current price charged by the concerned firm, but also the present state of the world. While reflecting the current economic condition, the state evolves in a Markovian fashion. This model represents the real-life situation in which the sales season is relatively long compared to the fast pace at which the outside environment changes. We establish the value of being better informed on the state of the world. When reasonable monotonicity conditions are met, we show that better present economic conditions will lead to higher prices. Our computational study is partially calibrated with real data. It demonstrates that the benefit of heeding varying economic conditions is on par with the value of embracing randomness in the demand process. © 2015 Wiley Periodicals, Inc. Naval Research Logistics, 2015

This study investigates how strategic leaders influence knowledge stocks and manufacturing improvements in firms. In doing so, we identify two related but distinct problem-solving orientations among senior executives. The first orientation uses short-term remedies to control and contain the impact of a problem, which we label as symptomatic problem solving (SPS). The other orientation addresses a problem situation with the objective of developing new understanding and skills, and we label it as generative problem solving (GPS). We test our theoretical framework using two waves of survey data from a sample of metal casting manufacturers (metal foundries) in the United States. Our analysis shows that GPS positively affects both internal and external knowledge stocks, while SPS negatively influences internal knowledge stock. Knowledge stocks, in turn, facilitate incremental and radical manufacturing improvements. Our results suggest that the two executive problem-solving orientations can potentially counteract each other in enhancing and depreciating knowledge stocks, and subsequently affect a manufacturer's ability to attain improvements both in the short and long terms

We deal with dynamic revenue management (RM) under competition using the nonatomic-game approach. Here, a continuum of heterogeneous sellers try to sell the same product over a given time horizon. Each seller can lower his price once at the time of his own choosing, and faces Poisson demand arrival with a rate that is the product of a price-sensitive term and a market-dependent term. Different types of sellers interact, and their respective prices help shape the overall market in which they operate, thereby influencing the behavior of all sellers. Using the infinite-seller approximation, which deprives any individual seller of his influence over the entire market, we show the existence of a certain pattern of seller behaviors that collectively produce an environment to which the behavior pattern forms a best response. Such equilibrium behaviors point to the suitability of threshold-like pricing policies. Our computational study yields insights to RM under competition, such as profound ways in which consumer and competitor types influence seller behaviors and market conditions. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 365–385, 2014

This article examines strategic outsourcing decisions for two competing manufacturers whose key components have quality improvement (QI) opportunities. We consider the effects of vertical and horizontal product differentiation on demand. In deriving the Subgame Perfect Nash Equilibria (SPNE), it is shown that either a symmetric outsourcing strategy (i.e., both manufacturers outsource) or an asymmetric sourcing strategy profile (i.e., manufacturers use different sourcing strategies) can be an SPNE. Insights are provided into how sourcing strategies are affected by the factors such as fixed setup cost, unit production cost, QI efficiency, and horizontal and vertical differentiations. It is found that larger horizontal differentiation expands the range over which symmetric outsourcing is an equilibrium. In addition, the outsourcing manufacturer may provide a higher QI level, produce a higher quantity, and offer a lower retail price than the insourcing one in the asymmetric sourcing setting. On the other hand...

This study investigates firms' R&D cooperation behavior in a supply chain where two firms first cooperate in R&D investments and then decide the production quantity according to a wholesale price contract. By using a concept named contribution level that measures a firm's technological contribution to the R&D cooperation in the supply chain, we show that both firms can achieve win�win via cartelization only if their contribution levels are Pareto matched, i.e., when each firm's contribution level is comparable to its partner's. When spillovers are endogenized, we further establish that an increasing spillover always benefits both firms without any R&D cooperation, but only benefits the firm whose contribution level is relatively low when under R&D cartels. Finally, we show that the path of first increasing spillovers to be perfect and then forming a cartel has a higher chance of achieving the best mode in terms of profitability.

Despite the widely held belief of the importance of innovation, the connection between innovation and firm performance is empirically inconclusive, partially owing to the limitations of existing innovation measures, which tend to ignore the effectiveness of innovation programs. In this study, we use the winning of innovation awards as a proxy for the effective execution of innovation. We conducted event-study analyses based on data from more than 1000 publicly traded firms that won innovation awards between 1998 and 2003. Our statistical tests provide strong evidence that the performance of award-winning firms is significantly higher as compared with several sets of control firms. Over an 8-year period, starting from 4 years before to 3 years after the year of winning the first innovation award, the test sample's mean (median) change in return on assets is nearly 33% (24%) higher than that of a control sample. The evidence also suggests that effective innovation programs can increase firms' revenue, cost efficiency, and market valuation. Over the period, the control-adjusted mean (median) change in sales, cost per dollar of sales, and Tobin's Q are 39.28% (20.71%), -5.52% (-3.80%), and 23.70% (3.16%), respectively. Panel data regression analysis provides additional insights on the performance impact of effective innovation programs. The results show that award winners are not only financially more successful but also enjoy an indirect benefit through better R&D execution, which increases firm profitability in both the short term and long term.

Because of the changing competitive environment, quality might have lost some of its luster and emphasis in business. The research question we aim to address in this paper is: Does quality still pay in the new competitive environment? Using replication research, we re-examine the impact of an effective total quality management (TQM) program on a firm's operating performance in the new competitive environment. We use publicly available data for award-winning firms and adopt several control-firm-selection approaches in our event study. Based on data from more than 500 firms, we find that over a 10-year period—6 years before to 3 years after winning their first quality award—firms in our sample perform significantly better than control groups in various operating performance measures. Not only do award-winning firms have better results after receiving awards, they also have superior performance records before the award. Our results suggest that quality is still critical to achieving long-term competitive advantages, and firms who continuously improve their quality continue to reap rewards by way of sales and financial performances exceeding those of their competitors.

We study a revenue management problem involving competing firms. We assume the presence of a continuum of infinitesimal firms where no individual firm has any discernable influence over the evolution of the overall market condition. Under this nonatomic-game approach, the unanimous adoption of an equilibrium pricing policy by all firms will yield a market-condition process that in turn will elicit the said policy as one of the best individual responses. For both deterministic- and stochastic-demand cases, we show the existence of equilibrium pricing policies that exhibit well-behaving monotone trends. Our computational study reveals many useful insights, including the fact that only a reasonable number of firms are needed for our approach to produce near-rational pricing policies.

We consider a retailer’s decision of whether to develop an internally produced, private label version of a national brand and the role that this decision plays in coordinating the supply chain. Our model assumes that the perceived quality of the private label is lower than that of the national brand, and we allow for the two products to have different marginal costs. We further allow for a fixed development cost that the retailer must incur to develop private label capability, and distinguish two types of private labels depending upon whether they would or would not be developed as product line extensions by a vertically integrated supply chain. We refer to these two types as first-best (FB) and non-first-best (NFB) product line extensions, respectively. When the private label can be characterized as a NFB product line extension, its development creates adverse cannibalization effects, yet it also helps to mitigate the effects of double marginalization with respect to the national brand. We characterize the conditions under which the retailer will develop private label capability, and distinguish among the conditions under which this is either beneficial or detrimental to the overall performance of the supply chain.

This article studies two contract mechanisms to share demand and supply risk in a decentralized supply chain. In an option contract, the buyer reserves capacity with a supplier who guarantees delivery up to this limit. This insulates the buyer from any disruption risk, but the supplier faces both demand and supply risk. The second mechanism, the firm order contract, represents a conventional dyadic channel relationship where the buyer places a firm order and the supplier builds capacity but does not guarantee delivery if any disruption occurs. It is shown that the buyer's preference for using the different risk-sharing mechanisms switches back and forth (as the probability of disruption increases). Consequently, a supplier with a higher disruption risk may make higher expected profits compared to one with lower risk. In addition, the buyer may benefit from a higher wholesale price since it provides incentive for the supplier to participate without requiring the buyer to use higher order quantities. Two op...

Recently, firms have experienced severe disasters that caused major supply disruptions. In this paper we study the strategies of dual sourcing and inventory management of a manufacturer facing disrupted supplies. Although abundant research has been conducted in this field, researchers rarely address the problem in the presence of information asymmetry or imperfection, which occurs because unstable supplies are often highly volatile and unpredictable in early stages. Without accurate and prompt forecasts of upstream supplies, it is difficult for a manufacturer to manage the disruption risks in an optimal manner. Here, a Bayesian model is proposed to dynamically update the knowledge of supply risks, which uses Dirichlet prior distributions to achieve mathematical tractability in Bayesian updating. Optimal-sourcing strategies are studied under this framework. Simulation results show that the proposed approach is effective in cost reduction and robust in reacting to imperfect or incomplete initial knowledge of disruptions.

This paper examines a number of electronic data interchange (EDI) usage and implementation factors and their role in improving a firm's efficiency, productivity and competitiveness. Unlike other studies in the literature that use exclusively linear models, we apply nonlinear neural networks to model the relationship between performance improvement and a set of predictor variables of EDI usage and supply chain coordination activities. A variable selection method is employed to identify key factors to predict a firm's operational excellence due to EDI implementation. In addition, a bootstrap resampling scheme is used to evaluate the robustness of the results.

In this paper, we consider revenue management for a service supply chain with one supplier and one retailer. The supplier has a limited capacity of a perishable product and both the supplier and the retailer face customers. Each customer may choose to buy a product from either the supplier or the retailer by considering prices and the cost associated with switching. For the centralized model, the supplier determines the selling prices for both herself and the retailer, and the retailer simply collects a commission fee for each product sold. We derive monotone properties for the revenue functions and pricing strategies. Further, we show that the commission fee increases the retailer’s price while decreasing the supplier’s and leads to efficiency loss of the chain. For the decentralized decision-making model, the supplier and the retailer compete in price over time. Two models are considered. In the first, the retailer buys products from the supplier before the selling season and in the second the retailer shares products with the supplier in retailing. For both models, we discuss the existence of the equilibrium and characterize the optimal decisions. Numerical results are presented to illustrate properties of the models and to compare the supply chain performance between the centralized and the decentralized models.

We conducted a newsvendor experiment in which (i) the subjects were presented with multiple pieces of information that they could possibly use to anchor their decision and (ii) the subjects participated either as individuals or in groups of three. The primary objective was to determine whether the subjects tended to consistently anchor to the mean or change their anchor based on the experimental setting. The secondary objective was to study the impact of group dynamics on their decision-making approach. We observed that the subjects did not anchor to any one particular value, but rather chose an anchor that was closer to the optimal value. In addition, we observed that although there was no difference in their relative tendencies to anchor, the subjects in groups demonstrated a lower propensity for error than their individual counterparts.

We study a continuous-review acquisition problem, in which the raw material price follows a discrete-state Markov process and demand is compound Poisson. We show that one optimal policy is of the order-up-to type. Under our mean reversion and time continuity conditions, we further show that the order-up-to levels are decreasing at the current price level. At the same time, our computational study verifies that both conditions are indispensable for the monotonicity result. The study also hints at the connection between discrete- and continuous-state price processes.

We consider how a merger between two naturally differentiated dealers affects their interactions with a common supplier and identify conditions under which the merger can increase or decrease the combined net worth of the two firms. Among other things, we find that the attractiveness of merging depends upon the extent to which end demand can be stimulated by either an upstream supplier or the dealers. Specifically, the greater the supplier's ability to invest in stimulating end demand, the more likely it is that the naturally differentiated firms will be better off operating independently than merging. On the other hand, if the greatest opportunities for stimulating demand are through the service that is provided by the dealers, then merging their operations will be more attractive. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007

An essential fact of decisions made under uncertainty, particularly in business contexts, is that multiple decisions often have to be made jointly. Firms in several industries like medicine, apparel and publishing must jointly determine the price and production quantity of their products well in advance of the selling season. The multiplicity of permutations in such settings is at once an opportunity and a challenge. Normative prescriptions to solve this problem have generally ignored behavioral aspects of decision-making, while behavioral research has paid limited attention to multi-dimensional decisions. In this study, we experimentally examine subjects' performance when they jointly determine price and quantities and find that subjects systematically deviate from the theoretically optimal price and quantity levels. When we decompose the decisions into price and quantity sequentially, we do not find improvement in subjects' decisions. However, when demand uncertainty is removed, or when information about market demand is provided after pricing decision is made, subjects improve their decisions.

Product design has increasingly been recognized as an important source of competitive advantage. This study empirically estimates the impact of effective design on the market value of the firm. We use a firm's receipt of a product design award as a proxy for its design effectiveness. Based on data from 264 announcements of design awards given to commercialized products between 1998 and 2011, we find that award announcements are associated with statistically significant positive stock market reactions. Depending on the benchmark model used to estimate the stock market reaction, the market reaction over a two-day period (the day of announcement and the preceding day) ranges from 0.95% to 1.02%. The market reaction is more positive for smaller firms and for firms whose award winning products are consumer goods. However, a firm's growth potential, industry competitiveness, and whether a firm is a first time or repeated award winner do not significantly affect the market reaction.

This paper explores production and outsourcing decisions for two Original Equipment Manufacturers (OEMs) who produce partially substitutable products and have opportunities to invest in reducing the manufacturing cost. In such an environment, competition drives both OEMs to set lower prices and invest more than would maximize their combined profits, particularly when product substitutability is high. However, outsourcing provides a mechanism by which the two OEMs can credibly signal that they will not overinvest in cost reduction, mitigating a mutually destructive cost competition. Our paper explores the role that an external supplier(s) can play in dampening competition between the OEMs when there are opportunities to invest in cost reduction. In particular, we characterize the conditions under which a supplier can profitably enter the market by inducing the OEMs to outsource production. We first examine a basic model of two identical OEMs in which there is a single common supplier and a single component...

We consider a stochastic inventory control problem with Markovian capacity and the option of order rejection. We show its optimal policy to be the combination of a capacity-dependent modified base-stock production policy and a capacity-dependent critical-point order acceptance policy. When capacity is stochastically monotone, we show that the policy parameters change over the current capacity level in an intuitive way. All these results can be extended to the infinite-horizon case, with or without cost discounting. Our computational study substantiates the benefits from both exploiting the Markovian behavior of the capacity and rejecting orders when necessary.

We study the optimal production-inventory-outsourcing policy for a firm with Markovian in-house production capacity that faces independent stochastic demand and has the option to outsource. We find very simple optimal policy forms under fairly reasonable assumptions. In addition, when the capacity Markov process is stochastically monotone, the policy parameters decrease in the firm’s current capacity level under additional assumptions. All these results extend to the infinite-horizon and undiscounted-cost cases. We analyze comparative statics and the necessity of some technical conditions, and discuss when the outsourcing option is more valuable.

Increasingly, customer service, rapid response to customer requirements, and flexibility to handle uncertainties in both demand and supply are becoming strategic differentiators in the marketplace. Organizations that want to achieve these benchmarks require sophisticated approaches to conduct order promising and fulfillment, especially in today’s high-mix low-volume production environment. Motivated by these challenges, the Available-to-Promise (ATP) function has migrated from a set of availability records in a Master Production Schedule (MPS) toward an advanced real-time decision support system to enhance decision responsiveness and quality in Assembly To Order (ATO) or Configuration To Order (CTO) environments. Advanced ATP models and systems must directly link customer orders with various forms of available resources, including both material and production capacity. In this paper, we describe a set of enhancements carried out to adapt previously published mixed-integer-programming (MIP) models to the specific requirements posed by an electronic product supply chain within Toshiba Corporation. This model can provide individual order delivery quantities and due dates, together with production schedules, for a batch of customer orders that arrive within a predefined batching interval. The model considers multi-resource availability including manufacturing orders, production capability and production capacity. In addition, the model also takes into account a variety of realistic order promising issues such as order splitting, model decomposition and resource expediting and de-expediting. We conclude this paper with comparison of our model execution results vs. actual historical performance of systems currently in place.

PurposeInformation sharing is an important component of cooperation in supply chain management. However, it has long been debated whether there is value in information sharing, how large the value is, if any, and what factors affect it. The purpose of the paper lies in investigating these three issues by comparing and analyzing 12 information models in supply chains.Design/methodology/approachTo achieve the above purpose, the paper first presents a general information‐sharing model in supply chains and characterizes three major factors in the model (objective, supply chain partnership constraint, information sharing constraint). Based on the general model, 12 representative models are selected from the literature and their relationship and distinctions are compared and analyzed.FindingsBy insights from comparative analysis of these representative models, the paper concludes that information sharing in supply chains is valuable. However, the value and affecting factors are dependent on analytical methods. It would be meaningless simply to compare the numerical values.Practical implicationsThe framework developed in this paper provides a useful guidance for the practical managers in evaluating and measuring the value of information‐sharing strategies.Originality/valueThe paper critically reviews representative information‐sharing models in supply chains. This work is helpful in answering some questions that have been long debated in this area and in inspiring new endeavors to overcome the limitations of current research.

This paper presents a general disruption management approach for a two-stage production and inventory control system. A penalty cost for deviations of the new plan from the original plan is incorporated and the concept of a disruption recovery time window is introduced. We define two classes of problems: one with fixed setup epochs and another with flexible setup epochs. With linear or quadratic penalty functions for production/ordering quantity change and fixed setup epochs, the best recovery plan is obtained by solving a quadratic mathematical programming problem. With convex penalty functions for quantity changes and flexible setup epochs, it is shown that the second stage orders have identical order quantities within each production cycle. Therefore, in a lot-for-lot system, the ordering and production quantities for both stages are the same. As a special case, we consider disruption recovery problems with short time windows spanning one or two production cycles. We also discuss solution procedures fo...

We propose an interactive Goal Programming (GP) for operational recovery problems that are present in diverse areas of application. After defining the problem we discuss its relevance to scenarios taken from airline scheduling, supply chain management and call centers operations. We then construct the GP procedure for operational recovery decision making and illustrate the mechanics of the proposed procedure through two examples: an abstract example based on a minimum spanning tree problem and a more practical example of a production-inventory problem.

Newsvendor decision making is ubiquitous in the global economy. Very often, newsvendor decision makers are overworked; thus, making ordering decisions is one of myriad things on their plate. They do not have the energy to focus solely on the newsvendor decisions and yet have to make them under significant information and cognitive constraints. Existing experimental research on human newsvendors has completely ignored this aspect of decision making and has focused entirely on settings in which the newsvendor decision is the only thing the subject is working on. We investigate the impact of presence of other tasks on the effectiveness of the distracted newsvendor’s ordering decisions. We conduct experiments manipulating the level of cognitive load that the subjects face during newsvendor decision making and find that, on average, subjects under cognitive load (i.e., distracted subjects) tend to order less than those under no cognitive load (i.e., non-distracted subjects) in both the high and low margin conditions, but the difference is not significant in the low margin condition. Additional experiments show that in the high margin condition, the effect of cognitive load on newsvendor ordering decisions is partially mediated by financial risk preference, but not social risk preference. Distracted subjects tend to be more risk averse, resulting in lower order quantities. Based on these results, we provide guidelines to managers on how they should determine the workloads of employees tasked with newsvendor decisions.

Since the seminal work of Markowitz (1952,1959,1987), the mean-variance methodology for the portfolio selection problem has been central to research activities of this area and has a lot of applications during the past four decades. Extensions of the mean-variance theory include all kinds of its derivatives and the capitial asset pricing model. (see, e.g., [Xia, Wang and Deng (1998b)]).

The core of the Markowitz Mean-Variance Model is to take the expected return of a portfolio as the investment return and the variance of the expected return of a portfolio as the investment risk. According to Markowitz (1952, 1959, 1987), for a given specific return level, one can derive the minimum investment risk by minimizing the variance of portfolio; or for a given risk level which the investor can tolerate, one can derive the maximum return by maximizing the expected returns of a portfolio. The main input data for the Markowitz mean-variance model are expected returns and variance of expected returns of these securities. Simplifying the number and types of the input data has been one of the main research topics in this field for the last four decades. Although some breakthroughs, such as the index model, have been implemented, all of those methods have some drawbacks due to some known reasons [Elton and Gruber (1995), Ballestero and Romero (1996)].

In many industries, original equipment manufacturers (OEMs) must obtain critical components from a few powerful suppliers. To the extent that the OEMs are also concentrated, the interactions between the suppliers of critical components and the OEMs are strategic, and have implications for how an incumbent OEM chooses its product line and interacts with potential rivals. We demonstrate that, by adding a low-end product line extension, an OEM can induce a strategic supplier to offer more favorable pricing. Moreover, depending upon the cost structure and relative performance of the product line extension, the OEM may benefit even more from the low-end line extension if it is produced by a rival instead of by itself, even if it cannot obtain any licensing income from it. Among other things, we show that this can result in a decentralized OEM accommodating competition from rivals producing product line extensions that would not be developed in a vertically integrated supply chain. In an extension, we re-examine the common assumption that the supplier unilaterally dictates a single wholesale price that is available to all downstream buyers. We demonstrate that, by committing to offer a “lowest available” wholesale price to all downstream buyers, a supplier can encourage an incumbent OEM to share its technology (or otherwise accommodate the entry of a rival) so that the supplier, the incumbent OEM, and the rival are all better off.

Newsvendor decision making is ubiquitous in the global economy. Very often, newsvendor decision makers are overworked; thus, making ordering decisions is one of myriad things on their plate. They d...

Investors prefer returns and dislike risks. They pursue the highest risk premia (the difference between the expected returns and the riskless interest rate) in financial markets. Modem finance theory helps investors make their choice about how to allocate their limited funds to different assets. Portfolio theory which is originally proposed by Markowitz (1959) is considered the beginning of modem finance theory. Since then, a lot of researchers came up with many models and algorithms during the last five decades [Deng, Wang and Xia (2000)].

Since investors rebalance their portfolios over time, it turns out that single period investment models are not enough to help investors make their decisions about how to allocate their limited wealth to different assets. Thus multi-period models of investment are much more realistic and they are extensively used for practical purposes in the financial industry. There are some successful applications of multi-period investment models such as the Russel-Yasuda Kasai asset/liability model [Carino et al. (1994)], the Towers Perrin-Tillinghast asset and liability management system [Mulvey (2000)].

The theory of portfolio selection of Markowitz (1952) applies mean and variance to characterize return and risk for a combination of more than two financial assets traded in a frictionless economy. Unlimited short selling is allowed and the rates of return on these assets are assumed to have finite variances. Rothschild and Stiglitz (1970, 1971) introduced the concept of second degree stochastic dominance. They showed that when there are more than two risky assets, if there exists a portfolio of assets that the second degree stochastically dominates all the portfolio with the same expected rate of return, then this dominant portfolio must have the minimum variance among all the portfolios. This observation is one of the motivations for characterizing portfolios that have the minimum variance for various levels of expected rate of return. The study of the mean-variance efficiency by Gonzalez-Gaverra (1973), Merton (1972) and Roll (1977) expanded Markowitz model to discuss various issues in portfolio management. To understand the formulation of mean-variance as return-risk, Chamberlain (1983) made an effort to characterize the complete family of probability distributions that are necessary and sufficient for the expected utility of terminal wealth to be a function only of the mean and variance of terminal wealth or for mean-variance utility functions. Epstein (1985) showed that the mean-variance utility functions were implied by a set of decreasing absolute risk aversion postulates.

Originally proposed by Sharpe (1964), Lintner (1965) and Black (1972), the Capital Asset Pricing Model has long shaped the way academics and practitioners think about average returns and risk. The essential prediction of the model is that the market portfolio of invested wealth is mean-variance efficient in the sense of Markowitz (1959).

The uncertainty about future events makes the behavior of economic agents unpredictable and, at times, brings about turbulence to financial markets. Assumptions about their behavior in resource allocation under an uncertain and ever-changing environment make up the foundation for theories of economics and finance to develop. These theories have thus gone a long way to apply mathematical analytical tools to model both the behavior of economic agents and future events of financial markets. Resource allocation methods derived from mathematical models of modem finance in turn play an influential role in the practice of financial institutions, and in a way, become a non-negligible player in the game of financial markets.

In the real financial markets, any movement of money between assets incurs a transaction cost proportional to the size of the transaction, paid from the bank account. In most cases, investors or portfolio managers usually start with an existing portfolio and make decisions of adjustment, probably, due to the changes of information about these securities. Since the revision entails both purchases and sales of securities that both incur transaction costs, the transaction cost is a V-shaped function of the difference between a new portfolio and the existing one. Obviously, the transaction cost has a direct impact on one’s investment performance, So, transaction costs have rightly become an important factor of concern and frustration for investors. The net return of a portfolio of securities should be evaluated by taking the costs into consideration. Arnott and Wagner (1990) observed that ignoring the transaction costs might result in inefficient portfolios. The experimental analysis done by Yoshimoto (1996) also verifies this fact.

Among various forms of strategic alliance, technology licensing agreements have attracted significant managerial and scholarly attention. In this paper, we examine the differential abnormal returns derived by a licensor and licensee in the backdrop of whether a focal licensing agreement is horizontal (i.e. between firms in the same industry) or non-horizontal (across different industries). Our analysis shows that although on the whole, investors view licensors more favorably than licensees after the announcement of a licensing agreement, they use two different logics--the first, a market power logic and the second, a learning logic, in evaluating the focal licensor and licensee. In horizontal agreements, licensors are positively evaluated by investors when they pair with licensees that are relatively better than them in terms of prior performance and capital intensity. On the other hand, in non-horizontal agreements, licensees generate greater positive abnormal returns when they signal the possession of g...