Optimal Auction with Resale

This paper investigates the design of seller–optimal auctions when winning bidders can attempt to resell the good. In that case, the optimal allocation characterized by Myerson (1981) cannot be achieved without resale. I find a sufficient and necessary condition for sincere bidding given the possibility of resale. In two–bidder cases, I prove that the Myerson allocation can be achieved under standard conditions supplemented with two assumptions. With three or more bidders, achieving the Myerson allocation is more difficult. I prove that it can be implemented in special cases. In those cases, the Myerson allocation is generated through a sequence of resale auctions, each optimally chosen by a reseller.     

Two-step values for games with two-level communication structure

TU games with two-level communication structure, in which a two-level communication structure relates fundamentally to the given coalition structure and consists of a communication graph on the collection of the a priori unions in the coalition structure, as well as a collection of communication graphs within each union, are considered. For such games we introduce two families of two-step values inspired by the two-step procedures staying behind the Owen value (Owen, in: Henn, Moeschlin (eds) Essays in mathematical economics and game theory, Springer, Berlin, pp 76–88, 1977) and the two-step Shapley value (Kamijo in Int Game Theory Rev 11:207–214, 2009) for games with coalition structure. Our approach is based on the unified treatment of several component efficient values for games with communication structure and it generates two-stage solution concepts that apply component efficient values for games with communication structure on both distribution levels. Comparable axiomatic characterizations are provided.     

Population monotonicity in matching games

The matching game is a cooperative profit game defined on an edge-weighted graph, where the players are the vertices and the profit of a coalition is the maximum weight of matchings in the subgraph induced by the coalition. A population monotonic allocation scheme is a collection of rules defining how to share the profit among players in each coalition such that every player is better off when the coalition expands. In this paper, we study matching games and provide a necessary and sufficient characterization for the existence of population monotonic allocation schemes. Our characterization implies that whether a matching game admits population monotonic allocation schemes can be determined efficiently.

     

DEA-based fixed cost allocation in two-stage systems: Leader-follower and satisfaction degree bargaining game approaches

This paper proposes new fixed cost allocation approaches for allocating a fixed cost among decision-making units (DMUs) with two-stage structures under the framework of data envelopment analysis (DEA). Firstly, we give the set of possible fixed cost allocations, prove that all DMUs can be overall efficient when evaluated by a common set of weights after fixed cost allocation. Secondly, from a centralized point of view, we consider the competition between the DMUs’ two stages in fixed cost allocation and regard these two kinds of stages as two unions. Then, we incorporate leader-follower models to propose a fixed cost allocation approach to handle the situation in which the two unions make decisions sequentially. Based on the result of these models, a concept of satisfaction degree of each union on a fixed cost allocation is presented. A satisfaction degree bargaining game model is then proposed to obtain a fixed cost allocation which is a bargaining equilibrium of the two unions. We show that the proposed approaches always obtain a fixed cost allocation that is proportionally invariant. Additionally, the satisfaction degree bargaining game approach automatically guarantees the uniqueness of the fixed cost allocation. These properties make the fixed cost allocation generated by our approaches more stable and more acceptable. Finally, a numerical example and an application of fixed cost allocation among bank branches are given to illustrate the proposed approach and to compare it with a benchmark approach among the current studies, respectively.     

Determination of the optimal number of kanbans and kanban allocation in a FMS: A simulationbased study

A simulation-based study is presented to compare the performance of a set of kanban allocation rules in a flexible manufacturing system (FMS) operating in a pull mode. This paper also presents a simulation-based direct search approach to determine the optimal number of kanbans and their simultaneous allocation to different part types. This paper presents a realistic cost function that includes a penalty for failing to meet the demand on time, and a penalty for rescheduling delivery of materials from vendors. The model captures limited flexibility in the form of operational flexibility in a FMS. Future extensions to this study are discussed.     

Unions and the Welfare Impact of Foreign Direct Investment — A Wisdom Extension

Abstract. This paper extends the recent literature, e.g. Leahy and Montagna (Economic Journal 110: 80–92, 2000), in relation to the link between unionization, inward foreign direct investment (FDI) and country welfare in an oligopoly market structure. It is shown that the common results, that unions may reduce welfare under FDI while multinational enterprises (MNEs) will strictly trade off union wages at each location, are generally driven by the assumption relating to the scope of the bargaining with the union, namely the ‘right to manage’ (RTM). In particular, our extension to efficient bargaining (EB) demonstrates that union power may increase welfare in the presence of FDI, while the MNEs’ choice between FDI and exports will include profit‐sharing arbitrage with unions, in addition to the usual wage comparison considerations.     

A multi-period ambulance location and allocation problem in the disaster

To achieve quick response in the disaster, this paper addresses the issue of ambulance location and allocation, as well as the location problem of temporary medical centers. Considering budget and capacity limitations, a multi-period mixed integer programming model is proposed and two hybrid heuristic algorithms are designed to solve this complex problem. The proposed model and algorithm are further verified in a real case study, and the numerical experiments demonstrate the effectiveness of our proposed model. Specifically, we obtain several findings based on the computational results: (1) The best locations of ambulance stations should change in each period because the demand rate changes over time. (2) Involving temporary medical centers is necessary to reduce the average waiting time of injured people. (3) It may not be optimal to allocate ambulances from the nearest ambulance stations because of potentially limited station capacity.

     

Unemployment Insurance and the Timing of Layoffs and Recalls

Abstract. This note provides the motivation to fill a gap in the empirical literature by showing that the optimal firm response to workers’ job search behaviour (Mortensen, Industrial and Labor Relations Review 30: 505–517, 1977) is to lay off those workers with high unemployment insurance and recall workers as they approach expiry of their benefits.     

Improved algorithmic results for unsplittable stable allocation problems

The stable allocation problem is a many-to-many generalization of the well-known stable marriage problem, where we seek a bipartite assignment between, say, jobs (of varying sizes) and machines (of varying capacities) that is “stable” based on a set of underlying preference lists submitted by the jobs and machines. Building on the initial work of Dean et al. (The unsplittable stable marriage problem, 2006), we study a natural “unsplittable” variant of this problem, where each assigned job must be fully assigned to a single machine. Such unsplittable bipartite assignment problems generally tend to be NP-hard, including previously-proposed variants of the unsplittable stable allocation problem (McDermid and Manlove in J Comb Optim 19(3): 279–303, 2010). Our main result is to show that under an alternative model of stability, the unsplittable stable allocation problem becomes solvable in polynomial time; although this model is less likely to admit feasible solutions than the model proposed in McDermid and Manlove (J Comb Optim 19(3): 279–303, McDermid and Manlove 2010), we show that in the event there is no feasible solution, our approach computes a solution of minimal total congestion (overfilling of all machines collectively beyond their capacities). We also describe a technique for rounding the solution of a stable allocation problem to produce “relaxed” unsplit solutions that are only mildly infeasible, where each machine is overcongested by at most a single job.     

Operator performance and subjective response in control of flexible manufacturing systems

Abstract

In this study, allocation of functions and system size (number of machines) were manipulated to test their effects on operator performance and subjective response in a flexible manufacturing system (FMS). An experiment was conducted using a cross-over design with three independent variables: number of machines, task allocation, and sequence of task presentation. Operator performance was measured by response time, and subjective response assessed using two questionnaires. Physiological measures were also taken (EKG and respiratory rate). The results revealed that the number of machines in the system did not affect performance or subjective or physiological response while the effect of allocation level was significant for both performance and subjective response.     

An enhanced loading model for the probabilistic workload control under workload imbalance

Load-oriented manufacturing control (LOMC), a well known probabilistic approach to workload control, is based on limiting and smoothing workload using one static parameter for each workcentre, called load limit (LL). The value of this parameter is set by the shop managers based on the planned lead time at each workcentre. In this paper the use of LL is shown to be inappropriate for the smoothing of workloads when the workload is not sufficiently balanced. We propose to enhance the LOMC model by introducing two sets of parameters:

(i) limiting parameters (LPs), that are statical parameters of the workcentres, set by the shop managers. LPs are used to limit the workload released to the shop;

(ii) smoothing parameters (SPs), that are dynamical parameters of the workcentres, computed as a function of their real workload. SPs are used to smooth the jobs workload over downstream workcentres.

A simulation model was used to compare the enhanced model, based on two parameters sets, with the traditional LOMC model, based on a single parameter set. The simulation runs were earned out with different conditions of due-date assignments, dispatching rules and production mix. The statistical analysis performed on experimental results confirmed that the enhanced model achieves significantly better due dates under unbalanced workload conditions.     

Tasks and Types: An Application of Mechanism Design to Self-Selection in Labour Markets

The Baron–Myerson (1982) regulatory mechanism is applied to the screening activity of a monopolist, who hires workers differentiated by quality and assigns them to different tasks. The employer charges a price to the workers for the screening service: necessary and sufficient conditions are provided for a self-selective price function to exist. It is shown that under the optimal price function tasks are assigned in such a way that workers' effort is increasing in workers' quality. It is not necessarily true, however, that the price function must be increasing in workers' quality. A simple two-types model is provided, showing the same results. Also the extension of the model to a dynamic context and, particularly, the requirements of a credible pre-commitment available to the screener are discussed.     

A framework for sustainable forest resource allocation: A Canadian case study

This paper addresses the problem of public-owned forest resource allocation observed in Canada. An integrated framework based on mill abilities to create value (expressed as economic, environmental and social benefits) is proposed. It encompasses three phases: (1) election of sustainable allocation criteria, (2) evaluation of mill performance with regard to the allocation criteria and (3) allocation of wood volumes according to mill performance. The framework is applied to a case study proposed by Ministry of Forests, Fauna and Parks (MFFP) in Québec. It is implemented as follows: first, the international standards, Forest Stewardship Council (FSC) and Global Reporting Initiative (GRI) are used to identify relevant allocation criteria covering the three sustainability dimensions (economy, environment and society). Second, the Group-Analytic Hierarchy Process (Group-AHP) is used to weight the allocation criteria and evaluate mill sustainability performance. Finally, optimization models are formulated to allocate the wood following two strategies: (1) maximizing the total created value by all mills and (2) promoting inter-firm fairness. The numerical results show that integrating sustainability concerns in the evaluation process has a significant impact on the allocation decisions. Moreover, adopting a wood allocation strategy seeking to guarantee fairness between forest companies is a win–win strategy as it also leads to maximizing the created value with a minimum deviation from the optimal targeted value. Lessons learned from this collaboration with MFFP are presented in order to help other interested researchers and public organizations develop their own roadmap to sustainable public resource allocation.     

U.S. Aviation Regulations Increase Probability of Midair Collisions

A purely stochastic Monte Carlo model is used to compare the relative midair collision course probabilities and mean closing velocities of four systems of rules for aircraft cruising altitudes as a function of altitude error: (1) current U.S. federal rules, (2) random altitudes, and (3) two proposed alternatives to the current rules. This model increments error while: (1) counting collisions among cruising pairs of aircraft following the four rules being tested on random headings between randomly placed airports, and (2) calculating mean closing velocities for each rule. The calculations verify that: (1) federal rules increase collision course probabilities by about four times more than for a chaotic system of aircraft cruising at randomly selected altitudes, (2) risk is directly proportional to the level of compliance, and (3) mean closing velocities resulting from the current rule are slightly less than for random altitudes, while being almost twice as high as for the proposed rules. High closing velocities are shown to increase the collision probability.     

Programme budgeting in the health sector

The growth of the public sector has been accompanied by an increased interest in this sector among economists and non-economists alike. Much of this interest has been directed towards the overall size of the public sector, and the efficient allocation of resources within the public sector has remained comparatively neglected. This paper outlines some of the problems of resource allocation facing decision-makers in the public sector, and reviews the actual and potential uses of one decision-making tool—programme budgeting—in improving resource allocation. The health care sector is chosen to illustrate the technique of programme budgeting, the practical and conceptual problems of implementation, and the limitations as well as the possibilities offered by this approach.     

Setups and effective capacity: the impact of lot sizing techniques in an MRP environment

This study investigates how lot sizing techniques influence the profit performance, inventory level, and order lardiness of an assembly job shop controlled by MRP. Four single-level lot sizing techniques are compared by simulation analysis under two levels of master schedule instability and two levels of end item demand. A second analysis investigates the influence of a multilevel lot sizing technique, the generalized constrained-K (GCK) cost modification, on the four single-level techniques at low demand and low nervousness. The analyses reveal a previously unreported phenomenon. Given the same inventory costs, the single-level lot sizing techniques generate substantially different average batch sizes. The lot sizing techniques maintain the following order of increasing average batch size (and decreasing total setup time):

economic order quantity (EOQ)

period order quantity (POQ)

least total cost (LTC)

Silver-Meal heuristic (SML)

The causes for different average batch sizes among the lot sizing techniques are analysed and explained. Demand lumpiness, inherent in multilevel manufacturing systems controlled by MRP, is found to be a major factor. The number of setups each lot sizing technique generates is the primary determinant of profit performance, inventory level, and order tardiness. EOQ, a fixed order quantity technique, is less sensitive to nervousness than the discrete lot sizing techniques. EOQ_, however, generates the smallest average batch size, and, therefore, the most setups. Since setups consume capacity, EOQ, is more sensitive to higher demand. SML generates the largest average batch sizes, and is, therefore, less sensitive to increased demand. At low demand, the other lot sizing techniques perform better on all criteria. They generate smaller batches and, therefore, shorter actual lead times. The GCK cost modification increases the average batch size generated by each lot sizing technique. GCK improves the profit and customer service level of EOQ the lot sizing technique with the smallest batches. GCK causes the other lot sizing techniques to generate excessively large batches and, therefore, excessively long actual lead times.     

The Optimality of a Simple Market Mechanism

Strategic behavior in a finite market can cause inefficiency in the allocation, and market mechanisms differ in how successfully they limit this inefficiency. A method for ranking algorithms in computer science is adapted here to rank market mechanisms according to how quickly inefficiency diminishes as the size of the market increases. It is shown that trade at a single market–clearing price in the k–double auction is worst–case asymptotic optimal among all plausible mechanisms: evaluating mechanisms in their least favorable trading environments for each possible size of the market, the k–double auction is shown to force the worst–case inefficiency to zero at the fastest possible rate.     

Decision latitude,job demands,and employee well-being

Abstract

Karasek (1979) drew attention to the possibilities that job characteristics may be non-linearly associated with employee well-being, and that they may combine interactively in relation to well-being. This paper examines those issues, and finds that both linear and non-linear components are present in relationships between job features and well-being. However, there is no evidence for a synergistic interaction between decision latitude and job demands. Those job features are differentially predictive of two aspects of well-being: job-related depression-enthusiasm and anxiety-contentment.     

A multiple buyer – supplier relationship in the context of SMEs’ digital supply chain management*

Abstract

By underlining the relevance of the use of ICTs, knowledge sharing and electronic markets for SMEs, it emerges the need for stimulating a debate on digitisation process of supply chain management (SCM). Electronic infrastructure in the service sector are reducing each kind of cost and improving multiply buyer–supplier relationships, facilitating negotiations and transactions. However, since the coordination costs are still high, the use of ICTs is limited. This phenomenon thus attracts the interests of scholars and practitioners. Although it still needs to further investigate. Especially, the optimal use of ICTs within SMEs’ SCM have not been studied yet. Therefore, by leveraging on four proxies: ICTs specialised human resources, knowledge sharing activities, buyer–supplier relationships, adoption of electronic markets this optimal was analysed via structural equation modelling based on a sample of 1254 SMEs operating in the service sector in Italy.