Up in smoke: demarketing and consumer smoking cessation

The concept of demarketing refers to the use of marketing techniques to reduce or eliminate demand for a product or service. A review of the demarketing literature relating to health and specifically antismoking initiatives indicated that, while research on this topic exists, much of it is not grounded in an acceptable attitudinal or behavioural theory. After determining the importance placed by a sample of 18–24‐year olds on nine demarketing initiatives, two dimensions were identified that best explained this construct. Items within these dimensions were summed and averaged to form single variables, which were then used to form the attitudinal component of the Model of Goal Directed Behaviour. The findings showed that two of these variables – one that captured product packaging aspects and another that consisted of place and price items – significantly influenced the desire to quit and indirectly influenced the intention to quit. Anticipated positive emotions, frequency of quitting attempts and perceived control over quitting also positively influenced the desire and/or intention to quit. The article concludes with a discussion that interprets these findings from a theoretical and practical perspective and suggests directions for future research.     

不确定环境下的地震应急救援路径优化研究

针对地震应急救援的特点,引入不确定理论,在地震灾害的背景下,研究震后动态网络环境下的应急救援路径选择问题。用不确定变量表示网络中各路段的破坏程度,综合考虑路径破坏程度及车辆路径连续性等约束条件,以救援时间最短为目标,基于不确定理论建立了动态优化模型,并用改进的遗传算法求解,最后设计算例验证了模型和算法的有效性。     

基于最大熵原理的政府投资工程委托代建风险研究

本文根据政府投资工程的风险特点,引入了熵的概念,建立了最大熵风险分析模型,利用熵权的特性求出各指标的客观权重,同时利用专家打分法得出各指标的主观权重,将两者结合作为各指标的综合权重,为进一步对风险指标的深入分析及风险决策研究奠定了良好的基础。最后,用实例验证了该模型的可行性和实用性。     

计算机视觉的理论框架探索

本文就计算机视觉的理论框架进行阐述,对计算机视觉理论框架存在的问题进行分析,提出计算机视觉理论框架的新发展,以确保通过计算机视觉获得的景物信息更加完整。     

农技人员推广导向对农户品牌行为影响的作用机理——基于扎根理论的探索性研究

本文立足农资品牌成长的特定环境, 从农技基层推广人员的视角出发, 运用扎根理论研究方法, 归纳不同推广导向下形成的不同类型产品推广方式, 构建农资产品推广导向对农户品牌行为的作用机理模型, 为探讨中国特殊背景下农资产品推广导向与农户品牌行为的关系提供有益的理论依据和研究框架, 以期在实践中发挥促进农资品牌推广和推动农资品牌成长的指导作用.     

The composite iteration algorithm for finding efficient and financially fair risk-sharing rules

We consider the problem of finding an efficient and fair ex-ante rule for division of an uncertain monetary outcome among a finite number of von Neumann–Morgenstern agents. Efficiency is understood here, as usual, in the sense of Pareto efficiency subject to the feasibility constraint. Fairness is defined as financial fairness with respect to a predetermined pricing functional. We show that efficient and financially fair allocation rules are in one-to-one correspondence with positive eigenvectors of a nonlinear homogeneous and monotone mapping associated to the risk sharing problem. We establish relevant properties of this mapping. On the basis of this, we obtain a proof of existence and uniqueness of solutions via nonlinear Perron–Frobenius theory, as well as a proof of global convergence of the natural iterative algorithm. We argue that this algorithm is computationally attractive, and discuss its rate of convergence.     

A probabilistic ghost in the experimental machine

This paper focuses on the opposition between two contemporary research programs in economics: behavioral economics (BE) and experimental market economics (EME). Our claim is that the arguments of this opposition can be clarified through the lens of another opposition in the philosophy of probability and in probability theory, between Bayesianism and frequentism. We show how this probabilistic opposition has indirectly shaped a controversy in psychology that opposes two research programs – Heuristics and Biases and Ecological Rationality – which play respective roles in the foundations of individual rationality in BE and EME. To understand these theoretical interrelationships, we investigate the 1996 controversy between Kahneman, Tversky, and Gigerenzer. Those psychologists held different views on how probabilistic representations influence the context-dependency of rationality. This provides a rationale to suggest that a probabilistic ghost may be haunting the experimental machine in economics, and explains how and why the oppositions between BE and EME are structured around the interplay between the norms of rationality and the context in which rationality is exercised.     

Collaboration strategy decision-making using the Miles and Snow typology

Engaging in collaboration may be the best way for a firm to enhance its competitive advantages, since this can offer faster access to both resources and capabilities. This study aims to develop a framework for making collaboration partner choice decisions. The authors design a strategic game model of collaboration using Miles and Snow typology. An empirical data set collected from the S&P COMPUSTAT database is adopted to verify the model, and several managerial implications are derived. This model helps a company choose a competitor as a collaborative partner and helps in the selection of a collaboration strategy.     

本土理论供给不足地域性建筑的发展——来自云南当代建筑创作的启示

本文首先对云南本土理论及地域建筑的发展历程进行叙述,同时对未来地域性建筑的发展趋势进行展望。描述了云南本土理论落后于地域建筑创作实践及大多本土理论未能有效指导和帮助地域创作实践的现状。在说明对本土理论思想形成的土壤营造的重要意义之后,阐明了本土理论与地域性建筑发展之间的理想关系。     

Semiparametric estimation of multi-asset portfolio tail risk

When correlations between assets turn positive, multi-asset portfolios can become riskier than single assets. This article presents the estimation of tail risk at very high quantiles using a semiparametric estimator which is particularly suitable for portfolios with a large number of assets. The estimator captures simultaneously the information contained in each individual asset return that composes the portfolio, and the interrelation between assets. Noticeably, the accuracy of the estimates does not deteriorate when the number of assets in the portfolio increases. The implementation is as easy for a large number of assets as it is for a small number. We estimate the probability distribution of large losses for the American stock market considering portfolios with ten, fifty and one hundred assets of stocks with different market capitalization. In either case, the approximation for the portfolio tail risk is very accurate. We compare our results with well known benchmark models.