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A public emission reduction project offers saleable carbon credits to encourage individual residents to participate in activities with low carbon emissions: if the residents participate, they will earn carbon credits that can be sold to polluting firms for carbon offsetting. This study explores the economic and environmental implications of these projects.

The authors develop a multiperiod model to incorporate the decisions of individual residents and a polluting firm. The model captures residents' difference in estimating the price of carbon credits: A proportion of residents are naive residents who shortsightedly take the previous market price of carbon credits as the basis of their decision-making.

A public emission reduction project can improve the cost-efficiency of carbon reduction, increase both the profit of the polluting firm and consumer surplus, but may hurt the welfare of the participating residents. Reducing transaction costs of carbon credits may cause a greater loss to participating residents. As the ratio of naive residents decreases, the overall welfare of participating residents increases and the number of participating residents decreases.

To encourage more residents to reduce carbon emissions, the project should be promoted to new areas (e.g. rural areas) where there are more naive residents. Although reducing transaction costs is an effective way to increase the economic viability of the project, the government should pay attention to protecting the welfare of residents, and educating residents is an effective way to improve their overall welfare.

This paper is the first to reveal the economic and environmental implications of public emission reduction projects.

The purpose of this paper is to investigate the retailer’s strategy of information sharing in a green supply chain with promotional effort, and the impact of information sharing on the decisions and profits of the manufacturer and the retailer.

The developed models aim to maximize the profits of the manufacturer, the retailer and the green supply chain system. The game theory is used to obtain the equilibrium solutions of both the manufacturer and the retailer. A two-part compensation (TPC) contract is designed to motivate the retailer to share information with the retailer. Numerical examples are used to show the impact of parameters on decisions by Matlab 2014.

The results show that the green degree increases while the promotional effort level decreases when the manufacturer receives the larger demand information from the retailer; information sharing leads to a profit increase to the manufacturer and a profit loss to the retailer, but can increase the profit of supply chain under a certain condition; information sharing reduces the expected consumer surplus. The TPC contract designed in this paper can not only motivate the retailer to share information but also increases the consumer surplus.

The study has been done in a monopoly environment where only a retailer can forecast demand information. It is an interesting direction of future research when considering there are more retailers who can forecast such information in a supply chain.

There exist two main aspects that are different from the existing literature. The stochastic demand function related to the retail price, the green degree and the promotional effort have never appeared in previous literature. This paper considers a green product supply chain with a manufacturer who produces green products and a retailer who has an information advantage because of her promotional effort; this paper investigates the impact of information sharing on the consumer surplus and designs a contract to coordinate the green supply chain.

Many supply contracts are employed in practice to improve the performance of supply chains. But there is a lack of research that can offer guidance to practitioners in choosing the best supply contract among a group of popular contracts. This paper aims to fill this gap by developing an intelligent rule‐based supply contract design system for choosing the best contract and its parameters from a supplier's point of view.

The approach used in this paper is based on the comparison of several supply contracts that are encountered in supply chain practice. The paper aims at identifying the conditions under which one supply contract outperforms another from the supplier's perspective. To facilitate the implementation of the decision‐making rules that are developed in this research, an intelligent decision support system is developed.

Six popular contracts are analysed; returns policy (RP), quantity discount (QD), target rebate (TR), backup agreement (BA), quantity flexibility (QF), and quantity commitment (QC). The main findings are: QD contracts generate larger expected profits for the supplier than TR contracts do when the demand is exogenous, an RP contract is better than a QD contract when the wholesale profit margin is sufficiently large and that the optimal QC contract always provides a higher expected service level than BA and QF contracts.

The paper presents an approach for developing an intelligent supply contract design system that can offer guidance to practitioners in choosing the best supply contract for a particular supplier.

Rolling element bearing failures in paper mill machines are considered in relation to their critical role in the machine function. The use of expensive, sophisticated and highly automated equipment and machines and the intention to achieve higher quality products, longer machine life, higher machinery effectiveness and safer operating processes were the main driving force motivating efforts to improve the maintenance concept during the last 50 years. In this paper, a conceptual model that integrates the available condition information, the deterministic models used in condition monitoring based upon mechanical theory and the probabilistic models used in the area of operational research is developed and its applicability is discussed. This model covers fault detection of a mechanical component such as a rolling element bearing, prediction of its vibration level in the near future, assessment of the probability of failure of a component over a finite period of time of interest.

The purpose of this paper is to develop a statistical control chart based model for earlier defect identification.

The paper used statistical process control methods and an auto‐regression model to model the identification of the initiation point of a random defect. Conventional statistical process control (SPC) methods have been widely used in process industries for process abnormality detections. However, their practicability and achievable performance are limited due to the assumptions that a continuous process is operated in a particular steady state and that all variables are normally distributed. Because the case considered here does not meet the requirement of conventional SPC methods, we proposed adaptive statistical process control charts based on an autoregressive model to distinguish defects from normal changes in operating conditions. The method proposed has been tested on a set of vibration data of rolling element ball bearings

Several control charts have been used and compared in this paper to identify the initial point of a defect. Overall, the adaptive Shewhart average level chart is a good choice since it overcomes the drawback of adaptive moving charts by working out the limits using all the bearings' data, with no such a need for a subjective threshold level. They are also not very sensitive to the small casual changes in the data.

The model developed can be served as part of a prognosis tool for maintenance decision making since once the earlier warning point has been identified, corrective maintenance actions may be taken. It has practical application areas in vibration based monitoring or any monitoring scheme where a trend in the monitored measurements may exist. The method proposed is easy to use and can be implemented in any condition based maintenance software packages.

The approach proposed in this paper is a new application of existing methods and of original contribution from a point of view of applicability. It adds value to the existing literature and is of value to practitioners.