Price dispersion and optimal price categories with limited memory consumers

In this paper, we study consumers with limited memory and examine the effects of their price categorization on the pricing strategies of competing firms. The valuations of consumers are assumed to be heterogeneous. We find that it is possible to observe price dispersion even when each firm charges a single price if the consumers categorize prices non‐optimally. Moreover, we demonstrate that the likelihood of a price dispersion outcome is reduced when consumers with limited memory set up the price categories optimally. These findings suggest that the consumers' limited memory and their sub‐optimal behavior, that is, their inability to choose price categories optimally can be a reason for observed price dispersion.     

Does educational diversity of managers matter for the performance of team‐managed funds?

We study the effect of the educational diversity of managers on the performance of team‐managed mutual funds using a large sample of U.S. equity funds from 1994 to 2013. We consider diversity in terms of both final educational degree and field of educational specialisation. We find that, in general, both types of diversity have a positive impact on fund performance, and our results are robust over a wide range of performance metrics and changes in market conditions.     

Using performance-based warranties to influence consumer purchase decisions

Abstract

Traditional warranty analysis focuses on the reliability of a product and offers warranty designs that compensate a consumer if the item fails. We introduce the concept of a performance-based warranty (PBW) that guarantees that a product will operate at or above some baseline level of performance, such as a minimum energy efficiency for an appliance. We illustrate how consumer behavior can change in the presence of a PBW and define the parameters for which a manufacturer may increase revenue. Finally, we present an algorithm to solve for the optimal PBW design given a consumer’s belief about the expected performance of the product.     

Introduction to the policy articles on Trump to Biden: Implications for Canadian Agriculture

President Biden was sworn in on January 20, 2021 after a 4‐year term by President Trump. Certainly, Trump's norm breaking presidency impacted Canada in significant ways and the agricultural sector was no exception. In this issue, we have a set of four short articles discussing the possible implications on Canadian agriculture of transitioning from a Trump to Biden presidency. Issues related to Canada‐U.S. agricultural trade, political norms and uncertainty, U.S. domestic support, participation in trade agreements, and U.S.‐China relations are all considered.     

Blockchain in Additive Manufacturing and its Impact on Supply Chains

Additive manufacturing (AM) appears to be a particularly attractive use case for blockchain. This research combines inductive in‐depth interviews with the Delphi method to explore what potentials blockchain technology in AM creates, which adoption barriers firms need to overcome, and how supply chains will be affected by the integration of these two potentially disruptive technologies. The results suggest opportunities that are related to intellectual property (IP) rights management, the monitoring of printed parts throughout their lifecycle, process improvements, and data security. The most important barriers for blockchain adoption in AM are an absence of blockchain‐skilled specialists on the labor market, missing governance mechanisms, and a lack of firm‐internal technical expertise. By addressing important limitations of AM, blockchain is expected to improve the competitiveness of AM in parts’ production, catalyzing the trend toward more decentralized manufacturing resulting in more agile, resilient, and flexible supply chains and reduced logistics costs. Beyond that, blockchain‐based AM platforms are expected to enhance supply chain visibility, drive supply chain digitalization, support supply chain finance, and contribute to the emergence of shared factory systems.     

乡村旅游核心利益相关者协调发展评价研究——以青海省海东市互助土族自治县小庄村为例

文章基于利益相关者理论的视角，选取青海省海东市互助县小庄村为案例地，通过田野调查和文献梳理分析出核心利益相关者的利益诉求和矛盾冲突，并构建乡村旅游核心利益相关者协调发展评价体系，采用EWM-Fuzzy综合评价模型和灰色关联模型对地方政府、旅游企业、社区居民及外来游客四类核心利益相关者利益诉求的紧急程度、利益关系协调发展状态及整体协调发展关系进行测评分析。研究表明，小庄村四类核心利益相关者对不同利益诉求的整体感知较好，不同利益诉求的紧急程度和协调发展状态均存在如下较大差异:四类核心利益相关者的利益诉求主要处于中度协调和轻度协调两种发展状态，优质协调发展状态的利益诉求表现相对较少，且存在濒临失调发展状态的利益诉求表现；小庄村旅游核心利益相关者相互间的协调发展关系呈现出多元化的发展状态，地方政府、旅游企业同其他利益相关者的利益关系协调发展的影响大小顺序完全一致，地方政府、社区居民同其他利益相关者的利益关系协调发展的影响大小顺序相对应，而外来游客、社区居民同其他利益相关者的利益关系协调发展的影响大小顺序基本相反；小庄村旅游核心利益相关者协调发展路径组合未达到纳什均衡状态，其协调发展模式为非对称互惠协调发展模式。上述验证结果与小庄村旅游发展的实际情况基本吻合，证明了评价体系的科学性。     

高分1号冬小麦解译面积核算方法研究

[目的]以高分1号(GF-1)融合2m卫星遥感影像为基础数据源,结合土地利用现状数据、高分多源遥感影像和地面样方等数据,对冬小麦分类提取中存在的面积误差问题进行研究和分析。[方法]文章以河南省永城市为研究区,在冬小麦提取结果聚类处理基础上,基于线性地物缓冲区数据,采用GIS空间运算实现线性地物面积扣除,接着分析了样方数据和土地利用现状数据再扣除零星地物面积比例上的差异,并采用样方零星地物平均扣除系数对全市各乡镇耕地与非耕地中冬小麦提取面积进行了相关统计和误差分析。[结果]永城市冬小麦最终解译面积11. 29万hm~2,其中线性地物和零星地物扣除面积分别为6 613. 08hm~2和3 875. 22hm~2,占研究区冬小麦解译面积的5. 86%和3. 32%,与统计上报数据相比,其处理前后误差由14. 12%降低至4. 41%,有效地提高冬小麦提取面积精度。[结论]误差来源分析与修正对冬小麦解译面积核算精度具有重要影响,该研究为县级区域尺度下冬小麦面积提取核算提供了思路和借鉴。