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Optimal ordering decision for a retailer in a dual-sourcing procurement is an important research area. The main purpose of this paper is to explore a loss-averse retailer’s ordering decision in a dual-sourcing problem.

For a loss-averse retailer, the study obtains the optimal ordering decision to maximize expected utility. Based on sensitivity analysis, the properties of the optimal ordering decision are well discussed.

Under the optimal ordering quantity that maximizes expected loss aversion utility, the relevant expected profit of a retailer turns to be smaller under a bigger loss aversion coefficient. For this point, a retailer needs to balance between expected loss aversion utility maximization and expected profit maximization in deciding the optimal ordering policy in a dual-sourcing problem.

This paper reveals the influence of loss aversion on a retailer’s ordering decision in a dual-sourcing problem. Managerial insights are suggested to devise the optimal ordering policy for retailers in practice.

This paper aims to explore the effect of e‐marketplace on the supply chain's performance under the markdown policy. Profit and risk analyses are both conducted and channel coordination issues are examined.

The paper presents a markdown policy supply chain analytical model with e‐marketplace and examines the optimal markdown policy. The mean‐variance theory is employed to study both the risk and profit residing in the supply chain. Extensive numerical analysis is conducted. The paper investigates both the cases when e‐marketplace selling price is exogenous and endogenous.

The markdown policy can coordinate the supply chain as long as the parameters satisfy certain analytical conditions. The expected profit and risk in the supply chain are both increased when e‐marketplace is introduced. The retailer shares a larger portion of the increased expected profit but at the same time bears a higher risk.

In this study, similar to the mainstream literature in the related area, the supply chain consists of one manufacturer and one retailer, and there is one single selling season with one product. Despite being able to generate interesting analytical results, this model fails to capture the more complicated real world practices.

The existence of e‐marketplace can be beneficial to the whole supply chain in terms of expected profit improvement. When the expected profit increase brought about by e‐marketplace is large enough to compensate for both the operational cost of e‐marketplace and the increase of the risk, the retailer could consider introducing e‐marketplace to dispose of the excess inventory.

This paper is an original work. It is based on the reviewed literature and the model with markdown policy is new. This could be a reference for further research into optimal performance in the supply chain with e‐marketplace.

This paper aims to study the maintenance and replacement problem for a deteriorating repairable system with multiple vacations of one repairman. It proposes a new replacement policy and establishes corresponding replacement models.

It is assumed that the repair after the system failures is not “as good as new” and the repairman is in multiple vacations. The reaching of the effective age of the system is assumed to be mutually stochastic at working state, waiting state for repair and being repaired state. Under these assumptions, a replacement policy based on the effective age of the system is applied. The long-run expected downtime per unit time and the long-run expected profit per unit time as objective functions are chosen, respectively. By using geometric process theory and renewal process theory, the mathematic models have been established and the explicit expressions of the long-run expected downtime per unit time and the long-run expected profit per unit time are derived, respectively.

The optimal replacement policy can be calculated and determined by the computer to minimize the expected downtime or maximize the expected profit. The minimum expected downtime per unit time and maximum expected profit per unit time can also be determined.

This replacement policy and mathematic models can be used as reference to the failure system maintenance and replacement.

This paper aims to build a mathematical model to determine the price of an acre of developable land, whether it is part of a large open tract (farm) or a smaller residential parcel that can legally be subdivided. The primary purpose of the model is to explore the effect of various minimum lot‐size regulations on the price of these two types of vacant land. The study also attempts to explain apparently conflicting findings that have recently appeared in empirical studies of “down‐zoning” in the states of Maryland and New Jersey.

The mathematical model of land value is based on principles of asset valuation under uncertainty at various locations within a metropolitan area. The price of an acre of land is modeled as the present value of a stream of indirect utility to homeowners, and economic rents to farmers, developers or landlords, depending on an endogenous date of development. The cases of New Jersey and Maryland are compared using parameterized simulations, with minimum lot size allowed to vary.

The simulations reconcile earlier empirical studies on Maryland and New Jersey. The observed absence of any price effect of down‐zoning in rural Maryland appears to be caused by the fact that development is not imminent there. In New Jersey, development is imminent virtually everywhere, and a high proportion of today's vacant land value is due to its development potential. This means that down‐zoning will typically lead to dramatic declines in vacant land value in New Jersey.

The study relies on state averages, so its results should not be applied to particular parcels in Maryland or New Jersey. The study incorporates uncertainty in expected developer profits, but not in future political decisions.

By clarifying the context in which zoning changes will or will not lead to decline in a landowner's asset value, the study can inform legal and political debates over re‐zonings in the USA. Included in these debates is the claim that some re‐zonings violate the “takings” clause of the USA constitution.

The majority of papers on this subject are empirical, using a hedonic or an appraisal methodology. This paper provides a coherent theoretical model of per‐acre land prices under different levels of zoning restriction. It can be used for simulation or prediction with relatively few input parameters.

With the rapid development of e-commerce, multi-sourcing with supply contracts and spot buying has become more and more popular in reality. The main purpose of the paper is to explore a loss-averse buyer's optimal procurement policy in a multi-sourcing under e-commerce surroundings.

The study introduces the loss aversion utility function to characterize the loss aversion effect and derives a loss-averse buyer's optimal procurement policy in a multi-sourcing with a wholesale price contract and spot market.

A loss-averse buyer could order no items in a wholesale price contract and only needs to replenish commodities from spot market under certain conditions. In addition, the study shows that spot capacity has important influences on a loss-averse buyer's optimal ordering decision in the wholesale price contract.

This is the first paper to study the loss aversion effect on a buyer's procurement decision in a multi-sourcing. The results present important managerial insights for a loss-averse buyer to devise optimal ordering policies in a multi-sourcing under e-commerce surroundings.

This paper's purpose is to suggest that manufacturers strategically place soft orders for assembly materials with suppliers in Silk Road Economic Belt countries who probably doubt the realization of the soft orders placed.

First, a two-stage Stackelberg competition is constructed, taking into account the supplier's trust level in formulating the decision process in the assembly supply chain. The authors then provide a buyback contract to coordinate the supply chain, in which the manufacturer obtains enough supplies by sharing some of the perceived risks of not fully trusted suppliers. Furthermore, the authors conduct a numerical study to investigate the influence of trust under a decentralized case and a buyback contract.

The authors found that all supply chain partners in Silk Road Economic Belt countries experience potential losses due to not fully trusting certain conditions. The study also shows that, in Silk Road Economic Belt countries, operating under a buyback contract is better than being without one in terms of assembly supply chain performance.

On the one hand, the authors only consider the asymmetry of demand information without considering that of cost structure information. On the other hand, a natural extension of the paper is to integrate single-period transactions into the multi-period transaction problem setting. As all these issues require substantial effort, the authors reserve them for future exploration.

Doing business with not-fully-trustworthy partners in Silk Road Economic Belt countries is risky, and this study reveals how trust works in global cooperation and with strategic reactions in situations of partial trust.

The purpose of this paper is to develop a model for the production planning decision of a dairy plant in a multi-product setting under supply disruption risk and demand uncertainty while determining the optimal product-mix and material planning requirement.

A mixed-integer nonlinear programming model is proposed to determine the optimal product-mix that maximizes the expected profit of a dairy. The data are collected through visits to the dairy site, conducting brainstorming sessions with the plant manager and marketing head at the corporate office. Disruption data are collected from the India Meteorological Department, Odisha.

From the analysis, it is recommended that the dairy should not produce curd during the planning period. Moreover, turnover from toned, double toned and baby food is maximum than that of the curd and these products are produced in the planning period. The expected profit increases from its present value when an optimal product-mix is followed. Sensitivity analysis is performed to analyze the effect of demand uncertainty, supply disruption and production quota. The expected profit decreases as the supply failure probability increases.

The model is implemented in a dairy plant under Orissa State Cooperative Milk Producers Federation, Odisha, India. The proposed methodology has not been validated, theoretically. The concerned dairy is based on the Indian context, but the authors believe that the study is highly relevant to other dairies as well.

This study provides a methodology for dairy plant managers to plan production effectively under supply disruption risk with demand uncertainty. It also suggests material requirement planning at different factories of the dairy plant.

This paper develops a mathematical model for the production planning decision of a dairy plant that determines the optimal product-mix, which maximizes the expected profit of a dairy under disruption risk and demand uncertainty (in the Indian context).

Travel time at inter-stops is a set of important parameters in bus timetabling, which is usually assumed to be normal (log-normal) random variable in literature. With the development of digital technology and big data analytics ability in the bus industry, practitioners prefer to generate deterministic travel time based on the on-board GPS data under maximum probability rule and mean value rule, which simplifies the optimization procedure, but performs poorly in the timetabling practice due to the loss of uncertain nature on travel time. The purpose of this study is to propose a GPS-data-driven bus timetabling approach with consideration of the spatial-temporal characteristic of travel time.

The authors illustrate that the real-life on-board GPS data does not support the hypothesis of normal (log-normal) distribution on travel time at inter-stops, thereby formulating the travel time as a scenario-based spatial-temporal matrix, where K-means clustering approach is utilized to identify the scenarios of spatial-temporal travel time from daily observation data. A scenario-based robust timetabling model is finally proposed to maximize the expected profit of the bus carrier. The authors introduce a set of binary variables to transform the robust model into an integer linear programming model, and speed up the solving process by solution space compression, such that the optimal timetable can be well solved by CPLEX.

Case studies based on the Beijing bus line 628 are given to demonstrate the efficiency of the proposed methodology. The results illustrate that: (1) the scenario-based robust model could increase the expected profits by 15.8% compared with the maximum probability model; (2) the scenario-based robust model could increase the expected profit by 30.74% compared with the mean value model; (3) the solution space compression approach could effectively shorten the computing time by 97%.

This study proposes a scenario-based robust bus timetabling approach driven by GPS data, which significantly improves the practicality and optimality of timetable, and proves the importance of big data analytics in improving public transport operations management.

The purpose of this paper is to analyze the effects of private investor's fair preference on the governmental compensation mechanism based on the uncertainty of income for the public-private-partnership (PPP) project.

Based on the governmental dilemma for the compensation of PPP project, a generalized compensation contract is designed by the combination of compensation before the event and compensation after the event. Then the private investor's claimed concession profit is taken as its fair reference point according to the idea of the BO model, and its fair utility function is established by improving the FS model. Thus the master-slave counter measure game is applied to conduct the behavior modeling for the governmental compensation contract design.

By analyzing the model given in this paper, some conclusions are obtained. First, the governmental optimal compensation contract is fair incentive for the private investor. Second, the private fair preference is not intuitively positive or negative related to the social efficiency of compensation. Only under some given conditions, the correlation will show the consistent effect. Third, the private fair behavior’s impact on the efficiency of compensation will become lower and lower as the social cost of compensation reduces. Fourth, the governmental effective compensation scheme should be carried out based on the different comparison scene of the private claimed portfolio profit and the expected revenue for the project.

This study analyzes the effects of private investor's fair preference on the validity of governmental generalized compensation contract of the PPP project for the first time; and the governmental generalized compensation contract designed in this study is a pioneering and exploratory attempt.

With repeal of the extraterritorial income exclusion expected in 2004, many U.S. companies selling abroad must rethink tax strategies related to export profit. Many firms with net operating loss (NOL) carryforwards, foreign tax credit (FTC) carryforwards, and interest-charge domestic international sales corporations (ICDs) can reduce marginal tax rates (MTRs) below rates otherwise applying to domestic sales. This article provides several case examples illustrating how U.S. exporters can minimize the MTR applicable to export profit. MTRs often depend on the period over which the company expects to absorb its NOL or FTC carryforward, the firm’s discount rate, and, in the case of ICDs, the prevailing T-bill rate. Assuming a 34% corporate tax rate, exporters with NOL (FTC) carryforwards can reduce the MTR on export profit to zero (17%) in some cases. Also, over the range of variables this article examines, the ICD reduces the MTR on export profit to between 34 and 21%. The cases illustrate how NOL and FTC carryforwards and ICDs affect exporters’ MTRs and provide educators with useful tools for discussing the tax aspects of exporting.