Data mining framework based on rough set theory to improve location selection decisions: A case study of a restaurant chain

Location selection plays a crucial role in the retail and service industries. A comprehensive location selection model and appropriate analytical technique can improve the quality of location decisions, attracting more customers and substantially impacting market share and profitability. This study developed a data mining framework based on rough set theory (RST) to support location selection decisions. The proposed framework consists of four stages: (1) problem definition and data collection; (2) RST analysis; (3) rule validation; and (4) knowledge extraction and usage. An empirical study focused on a restaurant chain to demonstrate the validity of the proposed approach. Twenty location variables relevant to five location aspects were examined, and the results indicated that latent knowledge can be identified to support location selection decisions.     

Credit market frictions and political failure

We study how an excessively favorable regulatory environment for banks could arise even with a perfectly competitive credit market in a median voter world. In our occupational choice model with heterogeneous wealth endowments, market failure due to unobservability of entrepreneurial talent endogenously creates a misalignment between surplus maximizing reforms and reforms that are preferred by the median voter, who is a worker. This is in contrast to the world without market failure where the electorate unanimously vote in favor of surplus maximizing institutional reforms. This paper illustrates how market failure could lead to political failure even in the benchmark political system that is free from capture by interest groups.     

Optimal contracting with altruism and reciprocity

Motivated by the recent experimental evidence on altruistic behavior, we study a simple principal–agent model where each player cares about other players' utility, and may reciprocate their attitude towards him. We show that, relative to the selfish benchmark, efficiency improves when players are altruistic. Nevertheless, in contrast to what may be expected, an increase in the degree of the agent's altruism as well as a more reciprocal behavior by players has ambiguous effects on efficiency. We also consider the effects of the presence of spiteful players and discuss how monetary transfers between players depend on their degrees of altruism and spitefulness.     

Sample bias in contingent valuation: A comparison of the correction methods

Abstract

This article compares various methods for correcting contingent valuation aggregate benefits when the sample is known to be biased. A sample is defined as the population, and response rates are simulated on the basis of a measure of salience. The simulated response rates suffer from nonresponse bias and selection bias. Coefficient and benefit estimates that result from weighting and self‐selection correction approaches are compared with the true coefficient and benefit estimates. Our results indicate that at both low and high response rates the standard approach leads to bias, and either correction approach will reduce the bias in coefficient and benefit estimates.     

A number‐of‐modes reference rule for density estimation under multimodality

We consider kernel density estimation for univariate distributions. The question of interest is as follows: given that the data analyst has some background knowledge on the modality of the data (for instance, ‘data of this type are usually bimodal’), what is the adequate bandwidth to choose? We answer this question by extending Silverman's idea of ‘normal‐reference’ to that of ‘reference to a Gaussian mixture’. The concept is illustrated in the light of real data examples.     

Raising the bar (4)

This editorial summarizes and comments on the papers published in issue 11(4) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper deals with common factors and spatial dependence in the error term specification of a production function model. The second paper sets forth a New Economic Geography (NEG) model with production activities that vary in their complexity, so as to analyse the impact on specialization patterns across different regions. The third paper measures the efficiency of local public investments using a relatively unknown econometric technique in which the time span over which the variables in the regression equation are measured is increased by one time period every run. The fourth paper adopts a conditional quantile regression approach to determine the impact of people employed in informal jobs on the wage distribution in Colombia and five of its regions. Finally, the last paper proposes and tests two new Bayesian variable selection approaches for spatial econometric models.     

基于逆向选择视角下的快递企业品牌建设研究

基于信息不对称性产生的逆向选择一直是微观经济学、信息经济学研究的重点。随着电子商务的蓬勃兴起，我国快递行业发展进入快车道。但是，多数快递企业竞争手段单一，服务单一，不注重品牌建设，集中于低端市场，顾客忠诚度低。本文利用逆向选择模型分析快递市场，指出品牌建设有助于缓解和改善信息不对称性对于企业和消费者的伤害，明确品牌建设对于快递企业的意义和作用。     

高校设备招标中供应商选择存在的问题与对策探讨

招标采购作为一种科学高效的方式已被高校设备购置广泛采用,然而我国高校设备招标工作起步较晚,各环节不够完善,目前存在诸多问题。本文从四个方面界定供应商选择的标准与审核工作,在分析现阶段供应商选择存在问题的基础上,给出相应的解决办法。     

浅析电子商务市场中的信任机制——基于“柠檬市场”理论的分析

通常认为,互联网的出现有利于消除消费者的信息劣势,但事实是,电子商务市场的“柠檬”问题却因为网络的虚拟性实际上被强化了,它可能会降低人们对网络交易的信任感。为此,如何解决这些问题就需要我们进行深入的探讨。本文以“柠檬市场”理论为出发点,分析了信任缺乏的内在机理,并结合案例分析提出了建立网络信任的策略思路。     

不确定性环境下的战略变革模型

在一个不确定性环境里,如何发现企业的战略老化并及时变革使之生存下去是摆在企业管理者面前的一道难题。在不确定性环境中,要降低不确定性,形成战略时就要做到在任何单位时间内均拥有大量的战略假设;拥有范围较宽的战略假设且是从正确的来源获得战略假设。形成战略后可采用使机会最大化的否证法进行战略选择。战略实施实际上也是对战略假设的再检验过程。在一定的时间间隔上对战略进行评估,如果出现战略老化的迹象或支持所选择战略的任何假设改变了,那么就转向另一种战略。