Using machine learning and big data for efficient forecasting of hotel booking cancellations

Cancellations are a key aspect of hotel revenue management because of their impact on room reservation systems. In fact, very little is known about the reasons that lead customers to cancel, or how it can be avoided. The aim of this paper is to propose a means of enabling the forecasting of hotel booking cancellations using only 13 independent variables, a reduced number in comparison with related research in the area, which in addition coincide with those that are most often requested by customers when they place a reservation. For this matter, machine-learning techniques, among other artificial neural networks optimised with genetic algorithms were applied achieving a cancellation rate of up to 98%. The proposed methodology allows us not only to know about cancellation rates, but also to identify which customer is likely to cancel. This approach would mean organisations could strengthen their action protocols regarding tourist arrivals.     

The influence of management and auditors on consolidation decisions

Historically, the decision over whether or not to consolidate was guided by bright-line rules, which outlined the minimum percentage of ownership required in a subsidiary for it to be considered controlled by a reporting entity and thus included in the consolidated financial statements (CFSs). Today, U.S. GAAP and IFRS use a principles-based approach, which is guided by the concept of control to determine whether a subsidiary is to be consolidated in the CFSs. In this context, a debate exists between managers and auditors about which subsidiaries should be consolidated. To deepen our understanding of how managers and auditors grapple with consolidation decisions, we interviewed several CFOs and audit partners to determine if they are anchored to legalistic mechanisms or if, instead, they are strategically developing ways to support the consolidation decision. Based on our interviews, we find that opportunistic transactions—criticized at the time of the rules-based approach—still exist due to the search for legalistic mechanisms that protect underlying choices influenced by economic incentives. Such results are crucial for analysts and investors to properly interpret consolidated financial performance.     

Do economic institutions matter for trade liberalization? Evidence from China’s Open Door Policy

Trade liberalization can promote export by inducing better resource allocation and more advanced technologies. Although the literature emphasizes the mechanism of geographic proximity, this paper identifies an institutional effect. Using infant mortality rate as an instrument that is irrelevant to export and geographic effects, we confirm that the openness due to China’s Open Door Policy promotes firm exports. We further document that the positive relationship between openness and firm exports is mediated by property rights protection and corporate autonomy, either of which reflects institutional quality at the constraint on the government’s strategic behavior. In particular, our estimates are robust to different samples, different estimation methods, and endogeneity bias.     

小企业加入非对称联盟动机对权力配置与绩效的影响——以水环境治理行业为例

以往有关联盟绩效的研究很少关注企业动机通过权力配置对绩效的多重影响，以及不同动机和权力配置的影响差异。以资源依赖理论和议价能力理论为基础，以中国245家水环境治理企业为样本，研究小企业加入联盟的动机通过感知位置权力与能力权力的配置，对非对称联盟创新绩效和财务绩效的联合效应。结果表明，战略动机通过感知权利互补和平衡促进技术创新；成本动机通过感知权利互补影响财务绩效，但无法通过感知权利平衡影响财务绩效。     

核心企业主导型创业生态系统构成与运行机制:以杭州云栖小镇为例

创业生态系统研究逐渐得到学术界重视，但缺乏基于类型学角度的具体探讨，一直处于抽象层面，这一研究现状不利于理论建构。聚焦核心企业主导型创业生态系统构成、核心企业在创业生态系统运行过程中的主导作用，实证研究国内创业生态系统运行机制，以杭州云栖小镇为案例的研究显示：①核心企业基于自身核心能力及网络中心位置，联合各类主体搭建价值网络体系，通过市场化的网络治理机制与跨界开放式创新，协调多主体在创业生态系统不同阶段、不同层次的复杂交互关系，服务于系统中创业企业发展；②在核心企业主导型创业生态系统平台搭建期，通过创业支持机制发挥主导作用。在组织运行期通过资源承诺机制、全链条孵化机制与网络嵌套机制发挥主导作用。在协同获取期，通过资源共享机制、企业协同机制发挥主导作用。     

跨文化背景下商业广告设计的视觉元素关注度研究——以餐饮类平面广告为例

本文以餐饮类平面广告为实验材料,研究了中国和美国被试者对平面广告中的图形、色彩、文字、编排及构图等视觉元素的关注度。本研究从文化认知理论出发,以文化认知差异为前提,探寻了东西方族群对商业广告中出现的视觉信息的不同处理方式。以商业广告中视觉设计的原则为标准,解构了平面广告设计中的视觉构成元素并进行一一比较,得出商业平面广告设计中中美两国被试者的视觉元素关注度差异。最终获取了各种视觉元素的评估结果和相对权重,形成了商业图形广告设计元素关注度的先后顺序。这一实验结果对跨文化认知心理理论在跨国广告设计中的应用有借鉴和启发作用,可以为跨国公司和设计师提供技术指导,设计出更符合消费者需求的商业广告。     

一种加权聚类划分决策树算法

针对斜划分决策树算法普遍存在时间效率低、部分算法仅能应用于二分类问题，提出了一种基于加权距离的聚类决策树算法。通过Relief-F算法为预测属性计算权重，并将权重用于树结点中数据的聚类过程，使用分簇结果对结点进行多路划分，得到可直接用于多分类问题的决策树。理论分析和实验结果表明，该算法与经典轴平行决策树相比，拥有更好的泛化能力以及相近的算法时间复杂度，与大部分斜决策树相比，在付出更少计算代价的前提下，获得了近似的正确率以及模型简洁度。     

动态能力、企业规模与双元创新关系研究——基于fsQCA方法的实证分析

对186家企业问卷数据进行模糊集定性比较分析（fsQCA），探寻3种类型动态能力和企业规模等因素对双元创新的组合效应以及不同因素之间的互动关系。研究发现，分别存在两种等效路径支撑中国企业实现探索式创新和利用式创新；吸收能力作为核心条件存在，联合不同水平的机会识别、资源拼凑和企业规模，大大提高企业实现双元创新的可能性；此外，资源拼凑兼具探索性和利用性双重特征，联合机会识别促进双元创新，其中，资源丰裕的大规模企业更具优势。采用QCA构型研究方法，推动了企业创新行为选择的因果逻辑性研究，从单维视角向多维交互的整体视角转变，明确了各种类型动态能力与双元创新之间的关系以及不同能力间的依赖/替代关系。     

创业企业何以提高创新绩效——基于创业学习与商业模式创新协同联动视角的QCA方法

以150个创业企业为样本，基于创业学习和商业模式创新理论，运用模糊集定性比较分析方法（fsQCA），探究经验学习、认知学习、新颖型商业模式创新和效率型商业模式创新对创新绩效的影响路径及机制。研究发现，存在新颖型商业模式创新等4条创新绩效产出关键路径；相较于效率型商业模式创新，新颖型商业模式创新在关键路径中更容易提高创新绩效；利用QCA方法证实了影响创业企业创新绩效的组态内部各要素之间的替代性。结论丰富了创新绩效产出内部机制，可为创业企业提高创新绩效提供指导和借鉴。     

Does the spatial representation affect criteria weights in environmental decision-making? Insights from a behavioral experiment

The need and interest to consider cognitive and motivational biases has been recognized in different disciplines (e.g. economics, decision theory, risk analysis) and has recently reached environmental decision-making. Within this domain, the intrinsic presence of a spatial dimension of both alternatives and criteria calls for the use of maps throughout the decision-making process to properly represent the spatial distribution of the features under analysis. This makes spatial Multi Criteria Decision Analysis (MCDA) a particularly interesting domain to explore new dimensions of cognitive biases. This study proposes a behavioral experiment aimed at discovering to what extent the spatial visualization (i.e. maps) of criteria versus the non-spatial one (i.e. tables) can bias the weight elicitation phase of a spatial MCDA process. The experiment simulates a very common analysis in environmental and land use planning: land suitability analysis. Our findings show that there are significant consequences on how important we perceive a certain criterion to be, depending on whether it is represented as a map or as a table among a mix of maps and tables. Indeed, the map representation of the same criterion leads to higher weights attributed to that criterion compared to the table representation. Visualizing the same information as a map or as a table, although technically equivalent, is thus not psychologically equivalent for Decision Makers. The results of this experiment are expected to have implications for spatial decision-making processes, by generating better awareness on the impacts of map-mediated land suitability analysis.