Customization competition between branded firms: Continuous extension of product line from core product

We study a competition of product customization between two branded firms by a game-theoretic approach. Firms produce products with two attributes: one attribute indicates a characteristic with regard to “function” or “design” of a product and the other indicates “taste” or “flavor” of the product, which reflects consumers’ brand/taste preferences. Two branded firms have their own specific core products and our customization is defined as a continuous extension of their product line from the core product only along the “function” attribute. In particular, we allow asymmetric positions of core products, which may create the position advantage/disadvantage between firms. We suppose that consumers incur their selection costs with regard to finding their most favorable item among a rich variety of products and firms incur their customizing costs with regard to extending their product lines. We first show that in the equilibrium, branded firms should fundamentally adopt their customizations to cover the center space in the market as far as possible, regardless of the position of the competitor’s core product. Therefore, the position of the core product contributes to the creation of a competitive advantage: when one firm’s core product is located more closely to the center of the market than the competitor’s, its customization can always cover more range of the center space in the market, while keeping its degree of customization smaller than the competitor’s. Furthermore, we show some implications of unit-cost improvement: in a short run, a firm is better off concentrating on the improvement of the unit selection cost rather than the unit customizing cost. In contrast, in a long run, both firms can benefit from the improvement of the unit customizing cost.     

Data envelopment analysis for environmental assessment: Comparison between public and private ownership in petroleum industry

Environmental assessment recently becomes a major policy issue in the world. This study discusses how to apply Data Envelopment Analysis (DEA) for environmental assessment. An important feature of the DEA environmental assessment is that it needs to classify outputs into desirable (good) and undesirable (bad) outputs because private and public entities often produce not only desirable outputs but also undesirable outputs as a result of their production activities. This study proposes the three types of unification for DEA environmental assessment by using non-radial DEA models. The first unification considers both an increase and a decrease in the input vector along with a decrease in the direction vector of undesirable outputs. This type of unification measures “unified efficiency”. The second unification considers a decrease in an input vector along with a decrease in the vector of undesirable outputs. This type of unification is referred to as “natural disposability” and measures “unified efficiency under natural disposability”. The third unification considers an increase in an input vector but a decrease in the vector of undesirable outputs. This type of unification is referred to as “managerial disposability” and measures “unified efficiency under managerial disposability”. All the unifications increase the vector of desirable outputs. To document their practical implications, this study has applied the proposed approach to compare the performance of national oil firms with that of international oil firms. This study identifies two important findings on the petroleum industry. One of the two findings is that national oil companies under public ownership outperform international oil companies under private ownership in terms of unified (operational and environmental) efficiency and unified efficiency under natural disposability. However, the performance of international oil companies exhibits an increasing trend in unified efficiency. The other finding is that national oil companies need to satisfy the environmental standard of its own country while international oil companies need to satisfy the international standard that is more restricted than the national standards. As a consequence, international oil companies outperform national oil companies in terms of unified efficiency under managerial disposability.     

Environmental safety stock: The impacts of regulatory and voluntary control policies on production planning,inventory control,and environmental performance

This paper analyzes the impacts of different pollution control policies on a firm’s decisions of production planning and inventory control. Based on a stochastic model with both demand and environmental uncertainties, we derive the optimal policies of production planning and inventory control under both regulatory and voluntary pollution control approaches, and investigate their operational and environmental effects. We establish that the conventional wisdom which suggests that reduction of environmental waste at the end of a production process also decreases the stock and throughput levels of a production system is not necessarily true. Rather, a regulatory environmental standard that limits the total amount of waste may induce the firm to raise its planned stock level, which would lead to a higher expected amount of environmental wastes before the standard is enforced as well as environmental risks at other stages of the production process. The additional planned stock level, which is termed “environmental safety stock,” can be reversed by using the voluntary control approach that provides the firm with the flexibility to occasionally exceed the environmental standard. We also conduct numerical experiments to analyze the effects of different values of model parameters under different control approaches. The analytical results provide new insights to the impacts of a firm’s production and inventory decisions on the natural environment as well as to the choices of pollution control approaches by decision makers in both the private and public sectors.     

Theory of integer-valued data envelopment analysis

Conventional data envelopment analysis (DEA) models assume real-valued inputs and outputs. In many occasions, some inputs and/or outputs can only take integer values. In some cases, rounding the DEA solution to the nearest whole number can lead to misleading efficiency assessments and performance targets. This paper develops the axiomatic foundation for DEA in the case of integer-valued data, introducing new axioms of “natural disposability” and “natural divisibility”. We derive a DEA production possibility set that satisfies the minimum extrapolation principle under our refined set of axioms. We also present a mixed integer linear programming formula for computing efficiency scores. An empirical application to Iranian university departments illustrates the approach.     

A dual simplex-based method for determination of the right and left returns to scale in DEA

This study reviews the concept of the “right” and the “left” returns to scale (RTS) in data envelopment analysis (DEA), and a dual simplex-based method, for determining these two notions in RTS, is proposed, which has computational advantages as compared to the customary method.     

Anchor points in DEA

Anchor points play an important role in DEA theory and application. They define the transition from the efficient frontier to the “free-disposability” portion of the boundary. Our objective is to use the geometrical properties of anchor points to design and test an algorithm for their identification. We focus on the variable returns to scale production possibility set; our results do not depend on any particular DEA LP formulation, primal/dual form or orientation. Tests on real and artificial data lead to unexpected insights into their role in the geometry of the DEA production possibility set.     

Chapter 11 Simulation studies of efficiency,returns to scale and misspecification with nonlinear functions in DEA

Using statistically designed experiments, 12,500 observations are generated from a 4-pieced Cobb-Douglas function exhibiting increasing and decreasing returns to scale in its different pieces. Performances of DEA and frontier regressions represented by COLS (Corrected Ordinary Least Squares) are compared at sample sizes ofn=50, 100, 150 and 200. Statistical consistency is exhibited, with performances improving as sample sizes increase. Both DEA and COLS generally give good results at all sample sizes. In evaluating efficiency, DEA generally shows superior performance, with BCC models being best (except at corner points), followed by the CCR model and then by COLS, with log-linear regressions performing better than their translog counterparts at almost all sample sizes. Because of the need to consider locally varying behavior, only the CCR and translog models are used for returns to scale, with CCR being the better performer. An additional set of 7,500 observations were generated under conditions that made it possible to compare efficiency evaluations in the presence of collinearity and with model misspecification in the form of added and omitted variables. Results were similar to the larger experiment: the BCC model is the best performer. However, COLS exhibited surprisingly good performances — which suggests that COLS may have previously unidentified robustness properties — while the CCR model is the poorest performer when one of the variables used to generate the observations is omitted.     

E-DEA: Enhanced data envelopment analysis

Data envelopment analysis (DEA) has enjoyed a wide range of acceptance by researchers and practitioners alike as an instrument of performance analysis and management since its introduction in 1978. Many formulations and thousands of applications of DEA have been reported in a considerable variety of academic and professional journals all around the world. Almost all of the formulations and applications have basically centered at the concept of “relative self-evaluation”, whether they are single or multi-stage applications. This paper suggests a framework for enhancing the theory of DEA through employing the concept of “relative cross-evaluation” in a multi-stage application context. Managerial situations are described where such enhanced-DEA (E-DEA) formulations had actually been used and could also be potentially most meaningful and useful.     

An application of cooperative game among container terminals of one port

In this paper a two-stage game that involves three container terminals located in Karachi Port in Pakistan is discussed. In the first stage, the three terminals have to decide on whether to act as a singleton or to enter into a coalition with one or both of the other terminals. The decision at this stage should presumably be based on the predicted outcome for the second stage. The second stage is here modelled as a Bertrand game with one outside competitor, the coalition and the terminal in Karachi Port (if any) that has not joined the coalition. Furthermore, three partial and one grand coalition among the three terminals at Karachi Port are investigated. The concepts of “characteristic function” and “core” are used to analyse the stability of these coalitions and this revealed that one combination does not satisfy the superadditivity property of the characteristic function and can therefore be ruled out. The resulting payoffs (profits) of these coalitions are analysed on the basis of “core”. The best payoff for all players is in the case of a “grand coalition”. However, the real winner is the outsider (the terminal at the second port) which earns a better payoff without joining the coalition, and hence will play the role of the “orthogonal free-rider”.     

Exploring the trade-off between immediate gratification and delayed network externalities in the consumption of information goods

Our motivation for this paper originates from recent advances in consumption and payment technologies available for mobile commerce. Ubiquitous computing is enabling consumers worldwide to reach digital content and services whenever and wherever they request it. This capability further fuels “impatience” in consumption of such information goods. We model such consumer behavior using a hyperbolic discounting approach. A subset of these products, especially software, also inherit delayed network externalities as part of their consumption characteristics. This builds a tension between decision to consume now or to expedite consumption. We build a stylized model to assess the impact of immediate gratification on the profit maximizing behavior of a monopolist firm which produces an information good with network externalities. We find that serving “impatient” consumers is always profitable for a monopolist. For lower levels of network externalities, the monopolist can increase first period and decrease second period prices in equilibrium. As network externalities effect increases, prices converge to the traditional market (with exponential discounters) levels.     

Unoriented two-stage DEA: The case of the oscillating intermediate products

Data envelopment analysis (DEA) allows us to evaluate the relative efficiency of each of a set of decision-making units (DMUs). However, the methodology does not permit us to identify specific sources of inefficiency because DEA views the DMU as a “black box” that consumes a mix of inputs and produces a mix of outputs. Thus, DEA does not provide a DMU manager with insight regarding the internal source of the organization’s inefficiency.     

Robust simulation with a base environmental scenario

In the design of a system, the comparison of possible solutions using simulation is generally performed with fixed environmental conditions. In practice, however, unexpected changes can occur for example in the part mix of a manufacturing facility or in the customer demand. Such changes, which are considered as modifications in environmental factors, can impact the system response. As a consequence, a solution A that is better than B for a given environment, can yield poorer performance than B for another environment. Therefore, we are interested in robust simulation studies, which aim at taking into account several possible environments. In methods based on Taguchi’s principles, no distinction is made between these environments in the robustness computation. In the suggested heuristic approach, we focus on problems where a particular environment is expected when the system will be in operation (the others being unexpected environments). This particular environment will be considered in the study as a “base environmental scenario”. The robustness of a solution of the design problem is computed as an approximate measure of what will be saved or lost if the environment becomes the unexpected. Reference curves are suggested to allow these solutions to be empirically compared in accordance with the decision-maker’s requirements. A simplified example is provided. The results are different from those obtained using a signal to noise ratio, which is typically used in Taguchian approaches.     

Evaluating the performance of Swedish savings banks according to service efficiency

This article develops principles for an evaluation of the efficiency of a savings bank. It starts out from the observation that such a bank is less profit oriented than a commercial bank. The customer is a vital stakeholder to the savings bank implying a greater emphasis on customer service provision. We are using data envelopment analysis (DEA) as a method to consider the service orientation of savings banks. We thereby demonstrate how an evaluation of the performance of savings banks according to “service efficiency” differs from an evaluation based on the traditional “profit” or shareholder concept. We determine the number of Swedish savings banks being “service efficient” as well as the average degree of service efficiency in this industry.     

Modeling reverse logistics process in the agro-industrial sector: The case of the palm oil supply chain

As today’s consumers are more and more concerned with the environmental impacts of products and services they buy, enterprises have been more and more concerned with “green operations”. One of the key aspects of green logistics management is reverse logistics. This paper shows how the potential of managing reverse logistics flows can be implemented in the agro-industrial sector. As an example, the palm oil supply chain is considered. This study is carried out under the focus of the “closed-loop supply chain (CLSC) framework” in which forward and backward product flows are considered simultaneously. A mathematical model is proposed in order to represent the dynamic interaction between flows. The objective function considers energy, cost and economic profits. Different implementation scenarios of recovery processes are proposed and interactions between direct and reverse flows in the chain are evaluated. Results are analyzed using proper statistical tools, showing that the simultaneous analysis of direct and reverse flows positively impact the net economic profits in this complex supply chain of the agro-industrial sector.     

The effects of sensitization and habituation in durable goods markets

We develop a model to study the impact of changes in price sensitivity on the firm as it introduces multiple generations of a durable product where unit costs are a convex function of quality. We incorporate the psychological processes of sensitization and habituation into a model of discretionary purchasing of replacement products motivated by past experience. When price sensitivity decreases with each purchase (sensitization), the myopic firm offers a higher quality product at a much higher price with each generation. When price sensitivity increases with each purchase (habituation), the myopic firm engages in price skimming. When sensitization is followed by habituation, the myopic firm eventually provides higher quality than the market is willing to pay for, leading to a steep drop-off in sales and profits. The actions of the forward-looking firm depend on the discount rate. A firm with a low discount rate builds its customer base before offering a higher quality and higher priced product. In contrast, a firm with a high discount rate quickly increases price and quality following the same path to falling profits of the myopic firm. These results provide insight into the firm and consumer behaviors underlying the phenomenon of “performance oversupply” identified in the innovation literature.     

Integrated data envelopment analysis: Global vs. local optimum

Chiou et al. (2010) (A joint measurement of efficiency and effectiveness for non-storable commodities: integrated data envelopment analysis approaches. European Journal of Operational Research 201, 477–489) propose an integrated data envelopment analysis model in measuring decision making units (DMUs) that have a two-stage internal network structure with multiple inputs, outputs, and consumptions. They claim that any optimal solutions determined by their DEA model are a global optimum, not a local optimum. We show that such a conclusion is a false statement due to their misuse of Hessian matrix in examining the concavity of the objective function, and their DEA model is actually a non-convex optimization problem. As a result, their DEA model is unusable in practice due to a lack of efficient algorithm for this particular non-convex DEA model. We further show that Chiou et al.’s (2010) model is a special case of a well-known two-stage network DEA model, and it can be transformed into a parametric linear program for which an approximate global optimal solution can be obtained by solving a sequence of linear programs in combination with a simple search algorithm.     

BiLevel programming Data Envelopment Analysis with constrained resource

A new BiLevel programming Data Envelopment Analysis (DEA) approach is created to provide valuable managerial insights when assessing the performance of a system with Stackelberg-game relationships. This new approach allows us to evaluate the firm performance in decentralized decisions, which consist of the objective(s) of the leader at its first level and that is of the follower at the second level. This approach can help decentralized companies to optimize their performance using multiple inputs to produce multiples outputs in a cost-effective way, where both the system “black-box” and subsystem performance are exposed in details. We show the algorithms and solutions to our new models. We illustrate and validate the proposed new approach using two case studies: a banking chain and a manufacturing supply chain. The computation shows that subsystem being efficient at all levels results in an overall efficiency achievement in a decentralized BiLevel structure.     

The affect heuristic

This paper introduces a theoretical framework that describes the importance of affect in guiding judgments and decisions. As used here, “affect” means the specific quality of “goodness” or “badness” (i) experienced as a feeling state (with or without consciousness) and (ii) demarcating a positive or negative quality of a stimulus. Affective responses occur rapidly and automatically—note how quickly you sense the feelings associated with the stimulus word “treasure” or the word “hate”. We argue that reliance on such feelings can be characterized as “the affect heuristic”. In this paper we trace the development of the affect heuristic across a variety of research paths followed by ourselves and many others. We also discuss some of the important practical implications resulting from ways that this heuristic impacts our daily lives.     

基于交互式模糊规划方法的可持续闭环供应链网络规划

在市场需求、设施开设成本和产品回收率不确定的条件下,采用一种交互式可能性规划方法,研究由多个工厂、分销点、市场和废旧点构成的可持续闭环供应链网络设计问题。基于可持续闭环供应链网络结构,构建以企业运营成本和环境伤害最小、社会效益最大为目标的混合整数规划模型。同时,引入改进Epsilon约束方法将多目标优化问题转化为单目标优化问题,在此基础上提出一种两阶段可能性规划方法,基于TH模糊方法对不确定性参数进行处理。最后,通过数值实例,验证本文所建可持续闭环供应链网络模型的有效性,并对悲观-乐观值、不确定参数最低可接受水平β、可调参数γ进行敏感性分析;通过与其他模糊方法对比表明,采用TH模糊方法能得到稳定的最优解。