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This paper aims to provide a detailed review of weak interaction biosensors and several common biosensor methods for magnifying signals, as well as judiciously guide readers through selecting an appropriate detecting system and signal amplification method according to their research and application purpose.

This paper classifies the weak interactions between biomolecules, summarizes the common signal amplification methods used in biosensor design and compares the performance of different kinds of biosensors. It highlights a potential electrochemical signal amplification method: the G protein signaling cascade amplification system.

Developed biosensors which, based on various principles, have their own strengths and weaknesses have met the basic detection requirements for weak interaction between biomolecules: the selectivity, sensitivity and detection limit of biosensors have been consistently improving with the use of new signal amplification methods. However, most of the weak interaction biosensors stop at the research stage; there are only a minority realization of final commercial application.

This paper evaluates the status of research and application of weak interaction biosensors systematically. The G protein signaling cascade amplification system proposal offers a new avenue for the research and development of electrochemical biosensors.

The purpose of this paper is to analyze the effect of batching on bullwhip effect in a model of multi‐echelon supply chain with information sharing.

The model uses the system dynamics and control theoretic concepts of variables, flows, and feedback processes and is implemented using iThink^® software.

It has been seen that the relationship between batch size and demand amplification is non‐monotonic. Large batch sizes, when combined in integer multiples, can produce order rates that are close to the actual demand and produce little demand amplification, i.e. it is the size of the remainder of the quotient that is the determinant. It is further noted that the value of information sharing is greatest for smaller batch sizes, for which there is a much greater improvement in the amplification ratio.

Batching is associated with the inventory holding and backlog cost. Therefore, future work should investigate the cost implications of order batching in multi‐echelon supply chains.

This is a contribution to the continuing research into the bullwhip effect, giving supply chain operations managers and designers a practical way into controlling the bullwhip produced by batching across multi‐echelon supply chains. Economies of scale processes usually favor large batch sizes. Reducing batch size in order to reduce the demand amplification is not a good solution.

Previous similar studies have used control theoretic techniques and it has been pointed out that control theorists are unable to solve the lot sizing problem. Therefore, system dynamic simulation is then applied to investigate the impact of various batch sizes on bullwhip effect.

The Demand Amplification Effect has been well described in the literature over many years, yet it is clear that the effect is still prevalent in many supply chains. In this paper, a practical approach is described for identifying and measuring demand amplification. The approach was applied within the upstream automotive component supply chain in the U.K. The causes of demand amplification within this scenario are analyzed and compared to those identified in previous work. The work described is the first part of a wider project, the aim of which is to develop a comprehensive approach to enable management to counteract the problem of demand amplification.

The purpose of this paper is to understand the effect of batching on bullwhip effect in a model of multi‐echelon supply chain with information sharing.

The model uses the system dynamics and control theoretic concepts of variables, flows and feedback processes and is implemented using iThink^® software.

It has been seen that the relationship between batch size and demand amplification is non‐monotonic. Large batch sizes, that when combined in integer multiples can produce order rates that are close to the actual demand, produce little demand amplification, i.e. it is the size of the remainder of the quotient that is the determinant. It is further noted that the value of information sharing is greatest for smaller batch sizes, for which there is a much greater improvement in the amplification ratio.

Batching is associated with the inventory holding and backlog cost. Therefore, future work should investigate the cost implications of order batching in multi‐echelon supply chains.

This is a contribution to the continuing research into the bullwhip effect, giving supply chain operations managers and designers a practical way into controlling the bullwhip produced by batching across multi‐echelon supply chains.

Previous similar studies have used control theoretic techniques and it has been pointed out that control theorists are unable to solve the lot sizing problem. Therefore, system dynamic simulation has been applied to investigate the impact of various batch sizes on bullwhip effect.

The demand amplification effect has been well described in the literature over many years. This paper reports the results of a research project carried out in the UK automotive component supply chain, which set out to eliminate the effect in practice. The paper describes the progression from the identification of demand amplification, through a practical approach for its measurement, to the development of a methodology to overcome the negative impacts of the effect across three echelons of the supply chain. The results of a six‐month trial implementation are reported.

Faced with the financing problem of small-medium enterprises (SMEs), China has attempted to establish as many as third party's collateral institutions. The paper aims to study the design of collateral arrangements including collateral fee rates, risk sharing, collateral capital requirements, types of collateral institutions and recollateral institution, etc.

The paper extends the model of Holmstrom and Tirole to develop the analytic framework of the theory of financing collateral. From the perspective of contract design, the paper establishes a moral hazard model focusing on the minimum capital requirement of the borrower under the condition of risk neutral and limited liability, while considering the structure of lender-collateral institution-borrower.

According to the research, only under certain conditions can third party's collateral arrangements tackle the financing problems of SMEs. Diversification, anti-collateral and linked-transactions are three means to improve financing conditions, but the most important way is efficient monitoring by collateral institutions, especially when it has relative advantage over the lender. In order to improve financing conditions of SMEs, China should rely more on efficient monitoring by banks not on excess development of collateral institutions, meanwhile relax rigid collateral supervision policies. Collateral institutions should be industry-specific, association or transaction-related type.

First, from the perspective of contract design, the paper analyzes the comprehensive institutional arrangements of third party's collateral considering mutual relationships of component elements and develops the analytic framework of the theory of third party's collateral, especially points out necessary conditions of its efficient arrangements. Second, the paper studies various efficient financing mechanisms under the institutional arrangements of third party's collateral and focusing on the role of monitoring and monitors, and the paper also has important policy implications, i.e. the paper should develop specific collateral institutions and promote monitoring role of credit institutions.

The purpose of this paper is to explore the effect of inventory record inaccuracy due to behavioral aspects of workers on the order and inventory variance amplification.

The authors adopt a continuous-time analytical approach to describe the effect of inbound throughput on the inventory and order variance amplification due to the workload pressure and arousal of workers. The model is numerically solved through simulation and results are analyzed with statistical general linear model.

Inventory management policies that usually dampen variance amplification are not effective when inaccuracy is generated due to workers’ behavioral aspects. Specifically, the psychological sensitivity and stability of workers to deal with a given range of operational conditions have a combined and multiplying effect over the amplification of order and inventory variance generated by her/his errors.

The main limitation of the research is that the authors model workers’ behavior by inheriting a well-known theory from psychology that assumes a U-shaped relationship between stress and errors. The authors do not validate this relationship in the specific context of inventory operations.

The paper gives suggestions for managers who are responsible for designing order and inventory policies on how to take into account workers’ behavioral reaction to work pressure.

The logistics management literature does not lack of research works on behavioral decision-making causes of order and inventory variance amplification. Contrarily, this paper investigates a new kind of behavioral issue, namely, the impact of psycho-behavioral aspects of workers on variance amplification.

This study attempts to determine the relative contribution of each of the causes of the bullwhip effect and to identify which causes of the bullwhip effect have relatively significant impacts on the variability of orders in supply chains.

Computer simulation models are developed. A fractional factorial design is used in collecting data from the simulation models. Statistical analyses are conducted to address the research objectives.

When all of the nine possible causes of the bullwhip effect are present in the simulation models, the following six factors are statistically significant: demand forecast updating, order batching, material delays, information delays, purchasing delays and level of echelons. Among these six factors, demand forecast updating, level of echelons, and price variations are the three most significant ones.

Simulation models for the beer distribution game are developed to represent supply chains. Different supply chain structures can be constructed to examine the causes of the bullwhip effect.

In order to mitigate the bullwhip effect, supply chain managers need to share actual demand information and coordinate production and distribution activities with their partners.

This study measures the relative contribution of each of the causes of the bullwhip effect and provides evidence that transparent and accurate information flow and supply chain coordination could be a key to reduce the amplification of demand in supply chains.

This study aims at exploring the topology of two risk communication cases, Bovine Spongiform Encephalopathy (BSE) in 2008 and H1N1 in 2009, in South Korea and investigating the progression of risk events related to media's role in risk amplification.

Content analysis of major Korean media is conducted. BSE and H1N1 stories in 2008 and 2009 are collected and analyzed. First, the basic nature of media coverage of the events such as frequency of stories is surveyed. Second, framings adopted in media to cover two cases are analyzed.

The result indicates that unfolding events related to BSE and H1N1 risk show a similar timeline with the frequency of media coverage of the given risks. Also, media adopted political framings for BSE and health/medial framings for H1N1.The authors cautiously suggest that the framings in media have influenced the politicization of BSE risk issue among the public, but, at the same time, the media framings on H1N1 have attenuated potential politicization of H1N1's risk.

This paper demonstrates the relationship between the process of social amplification of risk and media framings in Korea.

The purpose of this paper is to explore whether and how the bullwhip effect, as found in product supply chains, might also manifest itself in services, as well as what policies can be successful for mitigating it.

A combination of analytic methods was used – inductive case analysis and analysis of data from two service supply chains in the telecom industry.

Empirical evidence from two cases was examined and provides support for the presence of a service bullwhip effect. Quantitative and qualitative case data were used to explore how this effect manifests itself in services, the distinctive drivers of the bullwhip effect in services, and the managerial actions that can either trigger or mitigate these bullwhip effects. In total, eight propositions are developed and three types of characteristics that potentially make the bullwhip effect worse in services than in manufacturing are identified: the destabilizing effects of manual rework in otherwise automated service processes; the omission of accurate and timely data on rework volumes upstream in the chain, pointing at future bullwhip effects downstream; and the lack of a supply‐chain mindset within the various departments jointly responsible for delivering the service, leading to longer delays in reacting to service bullwhips as they develop over time.

The research is based on two cases within a single industry, limiting generalizability. The propositions developed need testing in a wider set of contexts, including hybrid service and product supply chains.

The implications of this research can help organizations prevent or reduce the negative impact of planned and unplanned fluctuations in their service supply chains.

This paper explores an area that has been well researched in manufacturing, but not in services, and it contributes to both the theory and practice of service supply chains.