考虑消费者双重偏好的低碳供应链减排策略研究

为了削弱传统零售商在渠道博弈中的垄断地位，制造商尝试建立在线渠道与零售商展开竞争。本文在考虑消费者低碳偏好的基础上，又将消费者的渠道偏好进行区分，通过不同决策模式的对比及数值算例分析，寻求低碳供应链最优的减排边界。研究表明：1分散决策时，制造商的低碳决策会受消费者渠道偏好的影响；集中决策时，制造商的低碳决策保持不变。2不同决策模式的减排边界由渠道偏好决定，渠道偏好较大时，分散决策的减排边界更高；渠道偏好较低时，集中决策的减排边界更高；渠道偏好中立时，两者的减排边界相同。3制造商可以通过升级低碳技术、实行低碳化管理等方式降低减排成本，同时通过低碳产品认证、广告宣传等方式提高消费者对低碳产品的认可程度。     

Control charts based on dependent count data with deflation or inflation of zeros

The process of serially dependent counts with deflation or inflation of zeros is commonly observed in many applications. This paper investigates the monitoring of such a process, the first-order zero-modified geometric integer-valued autoregressive process (ZMGINAR(1)). In particular, two control charts, the upper-sided and lower-sided CUSUM charts, are developed to detect the shifts in the mean process of the ZMGINAR(1). Both the average run length performance and the standard deviation of the run length performance of these two charts are investigated by using Markov chain approaches. Also, an extensive simulation is conducted to assess the effectiveness or performance of the charts, and the presented methods are applied to two sets of real data arising from a study on the drug use.     

Designing Graphs that Promote Both Risk Understanding and Behavior Change

Graphs show promise for improving communications about different types of risks, including health risks, financial risks, and climate risks. However, graph designs that are effective at meeting one important risk communication goal (promoting risk‐avoidant behaviors) can at the same time compromise another key goal (improving risk understanding). We developed and tested simple bar graphs aimed at accomplishing these two goals simultaneously. We manipulated two design features in graphs, namely, whether graphs depicted the number of people affected by a risk and those at risk of harm (“foreground+background”) versus only those affected (“foreground‐only”), and the presence versus absence of simple numerical labels above bars. Foreground‐only displays were associated with larger risk perceptions and risk‐avoidant behavior (i.e., willingness to take a drug for heart attack prevention) than foreground+background displays, regardless of the presence of labels. Foreground‐only graphs also hindered risk understanding when labels were not present. However, the presence of labels significantly improved understanding, eliminating the detrimental effect of foreground‐only displays. Labels also led to more positive user evaluations of the graphs, but did not affect risk‐avoidant behavior. Using process modeling we identified mediators (risk perceptions, understanding, user evaluations) that explained the effect of display type on risk‐avoidant behavior. Our findings contribute new evidence to the graph design literature: unlike what was previously feared, we demonstrate that it is possible to design foreground‐only graphs that promote intentions for behavior change without a detrimental effect on risk understanding. Implications for the design of graphical risk communications and decision support are discussed.     

Explicit analytical solutions for ARL of CUSUM chart for a long-memory SARFIMA model

This paper aims to derive explicit analytical solutions for Average Run Length (ARL) of CUSUM chart for the SARFIMA(P,D,Q)_S process with exponential white noise. Measurement of performance was done with the ARL in terms of percentage error and CPU time. The results obtained from the explicit formulas were compared focusing on the performance using the numerical integral equation (NIE) method. Both methods had similarly excellent agreement with the percentage error at less than 0.25%. Meanwhile, the explicit formulas consumed less CPU time than the NIE method. It is clear that the explicit formulas are a good alternative in real applications.     

Looking into the ‘black box’ – unlocking the effect of integration on acquisition performance

Extending research on the performance of Mergers and Acquisitions (M&As), this paper seeks to explain how the post-acquisition integration phase affects acquisition performance. Despite extensive research efforts, there remains a scant understanding of how acquisition implementation, particularly in the post-acquisition integration phase, impacts the performance of M&As. Based on an extensive study of eight acquisitions, in this paper, a grounded model detailing the mechanisms by which the post-acquisition integration phase affects acquisition performance is developed. The model posits that integration-related factors do not bear directly upon acquisition performance. Instead, their effect is mediated by functional organizations in both firms. When focusing into these functional mediating dynamics, we observe that integration-related processual, behavioral and cultural factors affect the identified functional mediators in different ways. Going forward, we echo calls for integrated perspectives to the study of M&A and M&A performance in particular.     

Local Estimation of the Conditional Stable Tail Dependence Function

We consider the local estimation of the stable tail dependence function when a random covariate is observed together with the variables of main interest. Our estimator is a weighted version of the empirical estimator adapted to the covariate framework. We provide the main asymptotic properties of our estimator, when properly normalized, in particular the convergence of the empirical process towards a tight centred Gaussian process. The finite sample performance of our estimator is illustrated on a small simulation study and on a dataset of air pollution measurements.     

Decisions,Science, and Values: Crafting Regulatory Alternatives Analysis

Emerging “prevention‐based” approaches to chemical regulation seek to minimize the use of toxic chemicals by mandating or directly incentivizing the adoption of viable safer alternative chemicals or processes. California and Maine are beginning to implement such programs, requiring manufacturers of consumer products containing certain chemicals of concern to identify and evaluate potential safer alternatives. In the European Union, the REACH program imposes similar obligations on manufacturers of certain substances of very high concern. Effective prevention‐based regulation requires regulatory alternatives analysis (RAA), a methodology for comparing and evaluating the regulated chemical or process and its alternatives across a range of relevant criteria. RAA has both public and private dimensions. To a significant degree, alternatives analysis is an aspect of product design; that is, the process by which private industry designs the goods it sells. Accordingly, an RAA method should reflect the attributes of well‐crafted product design tools used by businesses. But RAA adds health and environmental objectives to the mix of concerns taken into account by the product designer. Moreover, as part of a prevention‐based regulatory regime, it implicates important public values such as legitimacy, equity, public engagement, and accountability. Thus, an RAA should reflect both private standards and public values, and be evaluated against them. This article adopts that perspective, identifying an integrated set of design principles for RAA, and illustrating the application of those principles.     

For an integrative theory of social behaviour: Theorising with and beyond rational choice theory

Most sociologists are not content with merely relating macrosocial phenomena to preceding macrosocial causes in their causal explanations of social phenomena. Instead they are seeking to provide (non‐reductive) microfoundations with which they can corroborate and make understandable the connection between macrosocial phenomena. In order to do so a theory (or theories) of human action is required. One such theory, rational choice theory (RCT), has long been viewed with strong suspicion in sociology. I show such suspicion to be partially justified. RCT cannot be a general theory of social behaviour. Nonetheless, there are important insights in various versions of RCT that should not be discarded. In order to improve upon RCT and move toward a more unified or integrative theory of action social‐psychological research has to be taken note of. I demonstrate how dual‐process theories and the research on heuristics can help sociologists move beyond RCT without contradicting some of its more basic insights.     

What might Normalisation Process Theory bring to policy implementation studies? Learning lessons and uncovering questions through a case study of the profound implementation failure of a new policing policy

Normalisation Process Theory (NPT), used nationally and internationally to explore implementation within health services research, is used for the first time within policing to understand profound policy implementation failure and to generate broader discussion of policy implementation theory. The policy in question (Police to Primary Care [P2PC]) was an intervention designed to notify GPs when women are assessed by police as at high risk of future domestic abuse. Designed to improve interagency communication, it took place amidst radical organisational change. Using qualitative interviews with domestic abuse specialist and frontline officers, this paper addresses how NPT helps to explain the (non)implementation of P2PC, how such an analysis differs from other policy implementation approaches, and what this means for our understandings of policy implementation more broadly. NPT proved useful in understanding mechanisms leading to (non)implementation of the intervention: fuzzy alignment with existing practice, faulty communication of purpose, and inattention to discretionary implementation spaces. It helped us understand why the intervention came to be invisible. Dwarfed by its organisational context, made institutionally hard to read by a lack of formal protocols, and given restricted view to police officers, it was compromised by a failure to instigate systems of organisational learning. More broadly, NPT helped reveal practices intersecting top‐down and bottom‐up implementation theory. The paper concludes by asking how NPT and theories of street‐level bureaucracy might be better used in tandem and, particularly, how this might help explorations of policy implementation where human actors are joined by technological actors in interpreting and making policy in vivo.     

A Decision Framework for Managing Risk to Airports from Terrorist Attack

This article presents an asset‐level security risk management framework to assist stakeholders of critical assets with allocating limited budgets for enhancing their safety and security against terrorist attack. The proposed framework models the security system of an asset, considers various threat scenarios, and models the sequential decision framework of attackers during the attack. Its novel contributions are the introduction of the notion of partial neutralization of attackers by defenders, estimation of total loss from successful, partially successful, and unsuccessful actions of attackers at various stages of an attack, and inclusion of the effects of these losses on the choices made by terrorists at various stages of the attack. The application of the proposed method is demonstrated in an example dealing with security risk management of a U.S. commercial airport, in which a set of plausible threat scenarios and risk mitigation options are considered. It is found that a combination of providing blast‐resistant cargo containers and a video surveillance system on the airport perimeter fence is the best option based on minimum expected life‐cycle cost considering a 10‐year service period.