When does division of labor lead to increased system output?

This paper develops a set of simplified dynamical models with which to explore the conditions under which division of labor leads to optimized system output, as measured by the rate of production of a given product. We consider two models: in the first model, we consider the flow of some resource into a compartment, and the conversion of this resource into some product. In the second model, we consider the growth of autoreplicating systems. In this case, we divide the replication and metabolic tasks among different agents. The general features that emerge from our models is that division of labor is favored when the resource to agent ratio is at intermediate values, and when the time cost associated with transporting intermediate products is small compared to characteristic process times. The results of our model are consistent with the behavior of the cellular slime mold Dictyostelium discodeum, which switches from a single-celled to a multi-celled state when resources become limited. We also argue that division of labor in the context of our replication model suggests an evolutionary basis for the emergence of the stem-cell-based tissue architecture in complex organisms. Finally, the results of this paper may be useful for understanding how, in an economic context, firm productivity is maximized at intermediate firm sizes.     

Minimal time control of fed-batch bioreactor with product inhibition

This paper is devoted to the minimal time control problem for fed-batch bioreactors, in presence of an inhibitory product, which is released by the biomass proportionally to its growth. We first consider a growth rate with substrate saturation and product inhibition, and we prove that the optimal strategy is fill and wait (bang-bang). We then investigate the case of the Jin growth rate which takes into account substrate and product inhibition. For this type of growth function, we can prove the existence of singular arc paths defining singular strategies. Several configurations are addressed depending on the parameter set. For each case, we provide an optimal feedback control of the problem (of type bang-bang or bang-singular-bang). These results are obtained gathering the initial system into a planar one by using conservation laws. Thanks to Pontryagin maximum principle, Green’s theorem, and properties of the switching function, we obtain the optimal synthesis. A methodology is also proposed in order to implement the optimal feeding strategies.     

Analysis of a group purchasing organization under demand and price uncertainty

Based on an industrial case study, we present a stochastic model of a supply chain consisting of a set of buyers and suppliers and a group purchasing organization (GPO). The GPO combines orders from buyers in a two-period model. Demand and price in the second period are random. An advance selling opportunity is available to all suppliers and buyers in the first-period market. Buyers decide how much to buy through the GPO in the first period and how much to procure from the market at a lower or higher price in the second period. Suppliers determine the amount of capacity to sell through the GPO in the first period and to hold in reserve in order to meet demand in the second period. The GPO conducts a uniform-price reverse auction to select suppliers and decides on the price that will be offered to buyers to maximize its profit. By determining the optimal decisions of buyers, suppliers, and the GPO, we answer the following questions: Do suppliers and buyers benefit from working with a GPO? How do the uncertainty in demand, the share of GPO orders in the advance sales market, and the uncertainty in price influence the players’ decisions and profits? What are the characteristics of an environment that would encourage suppliers and buyers to work with a GPO? We show that a GPO helps buyers and suppliers to mitigate demand and price risks effectively while collecting a premium by serving as an intermediary between them.     

Why Are Product Prices in Online Markets Not Converging?

Why are product prices in online markets dispersed in spite of very small search costs? To address this question, we construct a unique dataset from a Japanese price comparison site, which records price quotes offered by e-retailers as well as customers’ clicks on products, which occur when they proceed to purchase the product. The novelty of our approach is that we seek to extract useful information on the source of price dispersion from the shape of price distributions rather than focusing merely on the standard deviation or the coefficient of variation of prices, as previous studies have done. We find that the distribution of prices retailers quote for a particular product at a particular point in time (divided by the lowest price) follows an exponential distribution, showing the presence of substantial price dispersion. For example, 20 percent of all retailers quote prices that are more than 50 percent higher than the lowest price. Next, comparing the probability that customers click on a retailer with a particular rank and the probability that retailers post prices at a particular rank, we show that both decline exponentially with price rank and that the exponents associated with the probabilities are quite close. This suggests that the reason why some retailers set prices at a level substantially higher than the lowest price is that they know that some customers will choose them even at that high price. Based on these findings, we hypothesize that price dispersion in online markets stems from heterogeneity in customers’ preferences over retailers; that is, customers choose a set of candidate retailers based on their preferences, which are heterogeneous across customers, and then pick a particular retailer among the candidates based on the price ranking.     

Multiobjective long-term planning of biopharmaceutical manufacturing facilities

Biopharmaceutical companies with large portfolios of clinical and commercial products typically need to allocate production across several multiproduct facilities, including third party contract manufacturers. This poses several capacity planning challenges which are further complicated by the need to satisfy different stakeholders often with conflicting objectives. This work addresses the question of how a biopharmaceutical manufacturer can make better long-term capacity planning decisions given multiple strategic criteria such as cost, risk, customer service level, and capacity utilization targets. A long-term planning model that allows for multiple facilities and accounts for multiple objectives via goal programming is developed. An industrial case study based on a large scale biopharmaceutical manufacturer is used to illustrate the functionality of the model. A single objective model is used to identify how best to use existing capacity so as to maximize profits for different demand scenarios. Mitigating risk due to unforeseen circumstances by including a dual facility constraint is shown to be a reasonable strategy at base case demand levels but unacceptable if demands are 150% higher than expected. The capacity analysis identifies where existing capacity fails to meet demands given the constraints. A multiobjective model is used to demonstrate how key performance measures change given different decision making policies where different weights are assigned to cost, customer service level, and utilization targets. The analysis demonstrates that a high profit can still be achieved while meeting key targets more closely. The sensitivity of the optimal solution to different limits on the targets is illustrated.     

Flexibility and Pricing Decisions for High-Volume Products with Short Life Cycles

We examine the competitive implications of a firm's ability to change over its facility for the manufacture of successive generations of high-volume products with short life cycles. This ability is known as changeover flexibility. The model introduced extends the existing literature in several directions. First, the model offers explicit treatment of the critical relationships between market entry time, changeover flexibility, product life cycles, and profit. Second, the model explicitly considers the effect of early market entry on the accumulation of manufacturing experience (learning), which reduces the unit production cost. Third, the product's optimal selling price is determined and its relation to the firm's changeover flexibility is examined. Last, facility flexibility is permitted to vary over a continuum. Therefore, we are able to capture decision making concerning the optimal degree of changeover flexibility. Both analytic and numerical results are reported, demonstrating the link between the operations and marketing domains in the context of a firm's optimal entrance and exit strategies. Among the key findings are (1) a firm more capable of reducing operating costs through learning over short life cycles optimally invests in more changeover flexibility, charges higher prices, and obtains greater profit; and (2) as the cost of flexible technologies decrease, a firm optimally increases its investment in changeover flexibility, enters markets earlier, and charges higher average prices over the product's life cycle.     

A Statistical Analysis of Prices of Electrical and Electronic Equipment after the Introduction of the WEEE Directive

In January 2003, the European Union (EU) issued a directive on e‐waste (waste from electrical and electronic equipment; WEEE) to deal with increasing quantities and the included hazardous components. The WEEE Directive is based on the principle of extended producer responsibility, which shifts the responsibility for end of life of products away from municipalities toward producers. This led some researchers to state that, in theory, the costs of waste treatment are passed on to consumers in terms of higher prices. This work addresses two fundamental questions: (1) Did the introduction of the WEEE Directive increase consumer prices of electrical and electronic equipment (EEE)? and (2) how much is this price increase? We carry out, for the first time in the literature, a quantitative research on price variation of the vast majority of EEE sold in the EU after the introduction of producers’ financial responsibility. The panel data include 972 price level indices, namely, six categories of EEE for 27 member states for six years. The main result is that the average variation of the prices for each category of EEE investigated actually increased and the variation was between 0.71% and 3.88%, depending on the specific category of EEE. The average increase of 2.19% is in line with the previous studies that estimated the impact of the WEEE Directive up to a 3% increase of the product price. The t‐test performed on the data shows a good statistical significance, which strengthens the relevance of the results. Finally, future directions for research are included.     

Rebound effects of price differences

Goal, Scope and Background  Traditionally, comparative life cycle assessments (LCA) have not considered rebound effects, for instance in case of significant price differences among the compared products. No justifications have been made for this delimitation in scope. This article shows that price differences and the consequent effects of marginal consumer expenditure may influence the conclusions of comparative LCA significantly. We also show that considerations about rebound effects of price differences can be included in LCAs. Methods  The direct rebound effect of a price difference is marginal consumption. Based on statistical data on private consumption in different income groups (Statistics Denmark 2005a, 2005b), the present article provides an estimate of how an average Danish household will spend an additional 1 DKK for further consumer goods, when the household has gained money from choosing a cheaper product alternative. The approach is to use marginal income changes and the following changes in consumption patterns as an expression for marginal consumption. Secondly, the environmental impact potentials related to this marginal consumption are estimated by the use of environmental impact intensity data from an IO-LCA database (Weidema et al. 2005). Finally, it is discussed whether, and in which ways the conclusions of comparative LCAs can be affected by including the price difference between product alternatives. This is elucidated in a case study of a comparative LCA screening of two different kinds of Danish cheese products (Fricke et al. 2004). Results  Car purchase and driving, use and maintenance of dwelling, clothing purchase and insurance constitutes the largest percentages of the marginal consumption. In a case study of two cheeses, the including the impact potentials related to the price difference results in significant changes in the total impact potentials. Considering the relatively small price difference of the two products, it is likely also to have a significant influence on the results of comparative LCAs more generally. Discussion  The influence of marginal consumption in comparative LCAs is relevant to consider in situations with large differences in the price of the product alternatives being compared, and in situations with minor differences in the impact potentials related to the alternatives. However, different uncertainties are linked to determining the pattern for marginal consumption and the environmental impact potential related to this. These are first of all related to the method used, but also include inaccurate data of consumption in households, aggregation and weighting of income groups, aggregation of product groups, estimation and size of the price difference, and the general applicability of the results. Conclusion  Incorporating marginal consumption in consequential LCAs is possible in practice. In the case study used, including the rebound effects of the price difference has a significant influence on the result of the comparative LCA, as the result for the impact categories acidification and nutrient enrichment changes in favour of the expensive product. Recommendations and Perspectives  It is recommended that the rebound effects of price differences should be included more frequently in LCAs. In order to ensure this, further research in marginal consumption and investment patterns and IO data for different countries or regions is required. Furthermore, this study does not consider the economic distributional consequences of buying an expensive product instead of a cheaper product (e.g. related to how the profit is spent by those who provided the product). It should also be noted, that more expensive products not necessarily result in less consumption, as those who provided the product also will spend the money they have earned from the sale. Ideally, these consequences should also be further investigated. Likewise, the development of databases to include marginal consumption in PC-tools is needed. In general, considerations of marginal consumption would favour expensive product alternatives, depending, however, on the type of consumer. ESS-Submission Editor: Dr. David Hunkeler (david.hunkeler@aquaplustech.ch)     

Optimal buffer allocation in a multicell system

Motivated by a layout design problem in the electronics industry, we study in this article the allocation of buffer space among a set of cells. Each cell processes a given part family and has its own revenue-cost structure. The objective of the optimal allocation is to maximize the net profit function (total production profits minus total buffer allocation costs). According to the flow pattern of jobs, the cells are categorized into two types. A type 1 cell is modeled as a Jackson network; a type 2 cell is modeled as an ordered-entry system with heterogeneous servers. Both models have finite waiting room, due to the buffer capacity allocated to the cells. We show that under quite general conditions, the production rate of each cell of either type is an incresing and concave function of its buffer allocation. Exploiting this property, a marginal allocation scheme efficiently solves the optimal buffer allocation problem under increasing concave production profits and convex buffer space costs.     

Simultaneous determination of lot size and production rate at capacity-constrained multiple-product systems

In the capacity constrained manufacturing systems where multiple product types are manufactured, the products are often produced in lots. Although the lot production may increase the system throughput by reducing changeover times, it may also increase production lead time because each item in a large lot has a long waiting time. Hence, a production manager should consider both throughput and lead time at the same time when deciding production lot sizes. This paper, which is an extension to the previous work done in Koo et al. (2007) that assumes homogeneous setup times, addresses a lot sizing problem in the system with multiple product types and unequal setup times. We develop a non-linear optimization model for simultaneous determination of throughput rate and lot size for each product. Since this optimization model cannot be solved analytically, we propose a heuristic solution procedure by analyzing the characteristics of the problem. Some numerical examples are presented to validate the proposed model, and finally the performance of the heuristic procedure is evaluated by comparison with the results of simulation experiments.     

Optimal Aggregation of Binary Classifiers for Multiclass Cancer Diagnosis Using Gene Expression Profiles

Multiclass classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. There have been many studies of aggregating binary classifiers to construct a multiclass classifier based on one-versus-the-rest (1R), one-versus-one (11), or other coding strategies, as well as some comparison studies between them. However, the studies found that the best coding depends on each situation. Therefore, a new problem, which we call the ldquooptimal coding problem,rdquo has arisen: how can we determine which coding is the optimal one in each situation? To approach this optimal coding problem, we propose a novel framework for constructing a multiclass classifier, in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. Although there is no a priori answer to the optimal coding problem, our weight tuning method can be a consistent answer to the problem. We apply this method to various classification problems including a synthesized data set and some cancer diagnosis data sets from gene expression profiling. The results demonstrate that, in most situations, our method can improve classification accuracy over simple voting heuristics and is better than or comparable to state-of-the-art multiclass predictors.     

Local,regional and global markets: what drives the tuna fisheries?

Tuna products are amongst the most popular seafoods in the world and widely traded across the globe. Their global trade developed at a very early stage in the growth and development of tuna fisheries. In this article, recent evolutions of tuna markets in terms of products (for both sashimi and cannery-grade tuna products), market structures, and trade are introduced followed by a comprehensive study of global integration through price linkages. Most studies show a high degree of market integration and competition through prices at the world-wide level. Finally, we introduce some original results about the relationship between catches and prices (estimated coefficients of demand elasticity and flexibility), and provide answers to a few key questions for tuna fisheries and markets, including: How do consumers respond to price changes? Are fish price changes fully transmitted to consumers? Is there any economic incentive for fishers to comply with reduced catch quotas? Do fishers target particular tuna species according to the relative price of tuna species?     

Assessment of Optimal Selected Prognostic Factors

The identification and assessment of prognostic factors is one of the major tasks in clinical research. The assessment of one single prognostic factor can be done by recently established methods for using optimal cutpoints. Here, we suggest a method to consider an optimal selected prognostic factor from a set of prognostic factors of interest. This can be viewed as a variable selection method and is the underlying decision problem at each node of various tree building algorithms. We propose to use maximally selected statistics where the selection is defined over the set of prognostic factors and over all cutpoints in each prognostic factor. We demonstrate that it is feasible to compute the approximate null distribution. We illustrate the new variable selection test with data of the German Breast Cancer Study Group and of a small study on patients with diffuse large B‐cell lymphoma. Using the null distribution for a p‐value adjusted regression trees algorithm, we adjust for the number of variables analysed at each node as well. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

An international supplier selection model with inventory and transportation management decisions

In this paper, we develop a mixed integer programming model for a supplier selection problem in an international context. The main features that characterize the international supplier selection are first identified. We show that when operating in an international context, the supplier selection process should consider the following issues: several buyers?? sites; inventory decisions, in particular the safety stocks that are held by buyers to cope with the delivery lead time uncertainty; inventory capacity constraints in buyers?? sites; selection of transportation modes, each having a specific delivery frequency and a transportation capacity; and multiple products and multiple time periods. Then, we propose a supplier selection model that takes into account such characteristics and that is suited for the international context. Finally, we solve the model with the commercial optimization software Cplex and we perform computational experiments based on a realistic case study from the automotive industry in order to prove the solvability and the usefulness of the model. Sensitivity analyzes are also performed for a number of model parameters.     

Event-based minimum-time control of oscillatory neuron models

We present an event-based feedback control method for randomizing the asymptotic phase of oscillatory neurons. Phase randomization is achieved by driving the neuron’s state to its phaseless set, a point at which its phase is undefined and is extremely sensitive to background noise. We consider the biologically relevant case of a fixed magnitude constraint on the stimulus signal, and show how the control objective can be accomplished in minimum time. The control synthesis problem is addressed using the minimum-time-optimal Hamilton–Jacobi–Bellman framework, which is quite general and can be applied to any spiking neuron model in the conductance-based Hodgkin–Huxley formalism. We also use this methodology to compute a feedback control protocol for optimal spike rate increase. This framework provides a straightforward means of visualizing isochrons, without actually calculating them in the traditional way. Finally, we present an extension of the phase randomizing control scheme that is applied at the population level, to a network of globally coupled neurons that are firing in synchrony. The applied control signal desynchronizes the population in a demand-controlled way.     

Equipment selection and task assignment for multiproduct assembly system design

A multiproduct assembly system produces a family of similar products, where the assembly of each product entails an ordered set of tasks. An assembly system consists of a sequence of workstations. For each workstation, we assign a subset of the assembly tasks to be performed at the workstation and select the type of assembly equipment or resource to be used by the workstation. The assembly of each product requires a visit to each workstation in the fixed sequence. The problem of system design is to find the system that is capable of producing all the products in the desired volumes at minimum cost. The system cost includes the fixed capital costs for the assembly equipment and tools and the variable operating costs for the various workstations. We present and illustrate an optimization procedure that assigns tasks to workstations and selects assembly equipment for each workstation.     

A stated preference investigation into the Chinese demand for farmed vs. wild bear bile

Farming of animals and plants has recently been considered not merely as a more efficient and plentiful supply of their products but also as a means of protecting wild populations from that trade. Amongst these nascent farming products might be listed bear bile. Bear bile has been exploited by traditional Chinese medicinalists for millennia. Since the 1980s consumers have had the options of: illegal wild gall bladders, bile extracted from caged live bears or the acid synthesised chemically. Despite these alternatives bears continue to be harvested from the wild. In this paper we use stated preference techniques using a random sample of the Chinese population to estimate demand functions for wild bear bile with and without competition from farmed bear bile. We find a willingness to pay considerably more for wild bear bile than farmed. Wild bear bile has low own price elasticity and cross price elasticity with farmed bear bile. The ability of farmed bear bile to reduce demand for wild bear bile is at best limited and, at prevailing prices, may be close to zero or have the opposite effect. The demand functions estimated suggest that the own price elasticity of wild bear bile is lower when competing with farmed bear bile than when it is the only option available. This means that the incumbent product may actually sell more items at a higher price when competing than when alone in the market. This finding may be of broader interest to behavioural economists as we argue that one explanation may be that as product choice increases price has less impact on decision making. For the wildlife farming debate this indicates that at some prices the introduction of farmed competition might increase the demand for the wild product.     

Industrialization of mAb production technology: The bioprocessing industry at a crossroads

Manufacturing processes for therapeutic monoclonal antibodies (mAbs) have evolved tremendously since the first licensed mAb product (OKT3) in 1986. The rapid growth in product demand for mAbs triggered parallel efforts to increase production capacity through construction of large bulk manufacturing plants as well as improvements in cell culture processes to raise product titers. This combination has led to an excess of manufacturing capacity, and together with improvements in conventional purification technologies, promises nearly unlimited production capacity in the foreseeable future. The increase in titers has also led to a marked reduction in production costs, which could then become a relatively small fraction of sales price for future products which are sold at prices at or near current levels. The reduction of capacity and cost pressures for current state-of-the-art bulk production processes may shift the focus of process development efforts and have important implications for both plant design and product development strategies for both biopharmaceutical and contract manufacturing companies.     

Process Variety Modeling for Process Configuration in Mass Customization: An Approach Based on Object-Oriented Petri Nets with Changeable Structures

Mass customization strategies could be usefully deployed by companies whose products are characterized by a modular design. Typically, each module serves a specific aspect of the overall product function at varying performance levels. Each product variant (constructed through a unique combination of modular performance levels), therefore, serves to customize the overall performance of the product, thus serving the unique needs of each customer. The high demand for each module guarantees economies of scale and, eventually, low cost to customer. The rationale of configuring production processes for producing individual product variants originates from the fact that massive process data is commonly available in a firm and there exists a generic process structure underlying the production of similar products in a family. To design a decision support mechanism that constructs process configuration corresponding to a given product configuration, this paper develops a formal modeling of process variety using Petri nets. Object-oriented Petri nets (PNs) with changeable structures (OPNs-CS) are applied to deal with the issues of generic representation, constraints compliance, and operational sequence requirements. Object-oriented PN (OPN) models facilitate generic representation of product and process variety as well as their instantiations. The OPNs-CS model is tested with simulation. Based on simulation results, the optimal configuration of production processes can be determined for each individual product as well as the cohort of a product family. To illustrate the feasibility and potential of OPNs-CS based process variety modeling, a case study of process configuration for mass customized textile spindles is reported.