Performance effects of innovation in two-sided markets: The paradigmatic case of OTAs

Online Travel Agents (OTAs) play an important intermediary role in the two-sided travel distribution market. A critical factor that enhances a firm's competitive advantage is innovation. Yet, the analysis of innovation in the OTA context is scarce. The main objective of this article is to fill this gap and examine the effect of OTA innovations on firm performance. We analyze the effect of two-sided market specific innovations (same-side and cross-side) on performance and contribute to the literature by expanding the theoretical understanding of innovations. We find that producer-to-consumer innovations have a greater effect on OTA performance than producer-to-producer and consumer-to-consumer innovations. A fundamental managerial implication is that exchange management is an area to be enhanced when innovating in travel market distribution.     

M5 competition uncertainty: Overdispersion,distributional forecasting,GAMLSS, and beyond

The M5 competition uncertainty track aims for probabilistic forecasting of sales of thousands of Walmart retail goods. We show that the M5 competition data face strong overdispersion and sporadic demand, especially zero demand. We discuss modeling issues concerning adequate probabilistic forecasting of such count data processes. Unfortunately, the majority of popular prediction methods used in the M5 competition (e.g. lightgbm and xgboost GBMs) fail to address the data characteristics, due to the considered objective functions. Distributional forecasting provides a suitable modeling approach to overcome those problems. The GAMLSS framework allows for flexible probabilistic forecasting using low-dimensional distributions. We illustrate how the GAMLSS approach can be applied to M5 competition data by modeling the location and scale parameters of various distributions, e.g. the negative binomial distribution. Finally, we discuss software packages for distributional modeling and their drawbacks, like the R package gamlss with its package extensions, and (deep) distributional forecasting libraries such as TensorFlow Probability.     

Logistics optimization through a social approach for food distribution

The management of supply chains is becoming more important in economic and social environments. Currently, the social sustainability is a factor that must be considered to design governmental strategies and policies. The objective of this research paper was to show, with a case study an approach to optimize distribution and delivery logistics of food in a social assistance program of school breakfast using mathematical models that include transportation distance, optimal locations, and vehicle routing through different clusters. By using qualitative variables like poverty levels, food insecurity and social exclusion, different clustering methods are proposed with the purpose of identifying the common characteristics in the studied population; and at the same time, reducing the distribution complexity. The results show an efficient approach to design a supply chain that includes economic and social factors. The new model developed in this paper can be used to plan social assistance governmental programs, to identify the specific needs and characteristics of the beneficiaries, minimizing the total cost of the distribution network logistics when delivering food for school meals.     

Modelling distribution of aggregate expenditure on tourism

The aim of this article is to obtain a statistical distribution that describes the aggregate expenditure of tourists related to their length of stay at a given location. This distribution enables us to estimate two parameters simultaneously; one controls the length of stay and the other, the expense incurred. We propose two distribution models, for which closed-form expressions are obtained. Covariates are introduced in order to study the factors that affect the aggregate expenditure. The results obtained indicate that the models achieve a reasonably good fit, with and without covariates.     

国防产业联盟协同创新网络政府治理：基于语义挖掘技术的策略向度研究

国防产业联盟发展的关键在于科学管理协同创新网络。政策注意力聚焦点反映政府治理创新网络的策略向度，不同政府层级间的注意力分布结构差异表明该策略向度的偏向性。通过人工构建主题词袋，计算主题词TF-IDF权值及余弦相似度，对中央和地方共96份政策文件、1 926份新闻文章进行规模化语义分析，整体评估政府治理国防产业联盟协同创新网络的策略适应性，并测量其在实施与宣传过程中的偏向性。结果发现，网络拓展是首要策略选择，网络管理方式为引导而非参与，关系耦合度低，网络愿景策略运用有限。地方政府在实施过程中出现了策略偏异和策略调整；政策宣传更接近地方政府的策略向度。     

浅析二项分布、泊松分布和正态分布之间的关系

二项分布、泊松分布和正态分布一直是学习和研究概率统计的基础。在一定条件下,这三个分布之间存在着密切关系。文章通过求极限分布,研究了二项分布与泊松分布、二项分布与正态分布之间的关系,并利用特征函数和分布函数相互唯一确定这一性质,分析了泊松分布和正态分布之间的关系。     

企业物流配送模式选择的TOPSIS多目标决策研究

介绍目前主要的物流配送模式，建立物流配送模式选择的评价指标体系，利用熵权法和AHP方法相结合，得出企业配送模式选择中的各个评价指标的权重，使评价结果更具有说服力。并且引入TOPSIS法有效解决配送模式选择的多目标决策问题，并对各备选模式进行了定量排序，为企业物流配送模式的决策提供依据。     

铁路集装箱场区安全布局评价研究

铁路集装箱场区的布局在体现基本运输功能和满足生产工艺要求的基础上，要综合考虑其各种安全因素。通过分析铁路集装箱场区安全布局的内外部影响因素，建立安全布局的综合评价指标体系，采用基于Rough Set的算法进行综合评价。通过算例对铁路集装箱场区的布局进行综合评价，结果证明了算法的实用性和可行性。     

NIT picking: The macroeconomic effects of a Negative Income Tax

I study a revenue-neutral reform of the U.S. income tax and welfare system that involves the adoption of a Negative Income Tax (NIT). The reform is undertaken in a life-cycle economy with individual heterogeneity and uninsurable idiosyncratic labor risk. The optimal NIT consists of a 22% rate and a transfer equivalent to 11% of per-capita GDP. The ex-ante average welfare gain is a 2.1% annual increase of individual consumption. I show that a NIT outperforms a flat tax reform (income tax plus deduction) by a considerable margin. The key consequence of the reform is that high-productivity agents increase their relative importance in the labor supply at the expense of low-productivity agents.     

股权分置、公司治理与股利分配决策：现金股利还是股票股利？

以2004~2007中国上市公司为样本,应用LOGISTIC回归对-股权分置改革前后我国上市公司股利分配决策进行理论与实证分析。结果表明,股权分置改革后,我国上市公司发放股票股利呈现增多的趋势,第一大股东、第二大股东持股比例越高,以及董事会人数越多,公司越倾向于现金股利分配,但机构投资者持股比例越高,越倾向于发放股票股利。同时,企业成长性强的公司倾向于发放股票股利,而现金流量好的公司往往不发放股票股利,企业规模与股票分配决策无关。