Artificial neural network models for airport capacity prediction

This paper proposes artificial neural network models to predict the arrival/departure capacity of airports. Multilayer perceptron (MLP), recurrent neural networks (RNN), and long short-term memory (LSTM) models have been trained using capacity and meteorological data from Hartsfield–Jackson Atlanta International Airport (ATL) from 2013 to 2017. The models’ predictive performances were validated against the observed capacity of ATL in 2018. The qualitative and quantitative analysis of the trained models confirmed that the artificial neural networks approach is effective in predicting airport capacity. In addition, the transferability of the models for Boston Logan International Airport (BOS) is examined. Capacity prediction performance for BOS measures the transferability of the models trained with the ATL data. MLP showed good transferability without taking any other measures, and RNN and LSTM were able to predict the BOS capacity well after fine-tuning.     

The role of epistemic communities in the “constitutionalization” of internet governance: The example of the European Commission High-Level Expert Group on Artificial Intelligence

In the last few years, digital constitutionalism has emerged as a novel, alternative, Internet Governance approach aiming at ordering and limiting the exercise of power by both states and private operators, as well as at promoting people's control over digital technology development.Although digital constitutionalism is encountering growing popularity, the prevalent non-binding nature of its initiatives, the discrepancy between the jurisdictional border and transnational digital processes, and the technological embedment of governance mechanisms, have hindered the effectiveness of its impact.This paper identifies epistemic communities as a crucial factor for the constitutionalization of the digital technologies since they have the necessary technical expertise and policy commitment to create norms and standards at transnational level, informing the policy choices of both state and non-state actors.In order to illustrate this nexus, the article performs an in-depth investigation on the case of the European Commission High-Level Expert Group on Artificial Intelligence (HLEG-AI). The analysis revealed that the HLEG-AI effectively gathered an epistemic community strongly committed with fundamental rights promotion and capable to influence the following policy-making activities of the European Commission, as well as of other non-state stakeholders, whose involvement is essential in order to embed digital constitutionalism principles within the design of AI systems.     

Investor sentiment and stock returns: Global evidence

We assess the impact of investor sentiment on future stock returns in 50 global stock markets. Using the consumer confidence index (CCI) as the sentiment proxy, we document a negative relationship between investor sentiment and future stock returns at the global level. While the separation between developed and emerging markets does not disrupt the negative pattern, investor sentiment has a more instant impact in emerging markets, but a more enduring impact in developed markets. Individual stock markets reveal heterogeneity in the sentiment-return relationship. This heterogeneity can be explained by cross-market differences in culture and institutions, along with intelligence and education, to varying degrees influenced by the extent of individual investor market participation.     

Understanding service attributes of robot hotels: A sentiment analysis of customer online reviews

Robots and artificial intelligence are essential to the future of the hospitality industry, and they are receiving increasing interest from hotel managers and researchers. However, the adoption of robotic services in hotel operations is a challenging task owing to the current level of technology and lack of understanding on the relationship between various aspects of robotic services and customer satisfaction. Moreover, no prior study has examined the service attributes of robots in hotels. To fill these gaps, this study analyzes customers’ sentiments on major hotels employing robotic services expressed through online reviews. A list of robot quality and operational area attributes is first constructed, through which underperforming robot service areas are identified. Sentiments on robotic services have a positive correlation with hotel service satisfaction, which plays an important role in determining the overall satisfaction of customers. The analysis and findings are valuable to researchers and managers for future research and adoption of robotic services in hotels.     

A tale of two recommender systems: The moderating role of consumer expertise on artificial intelligence based product recommendations

Recommender systems are used in e-Commerce websites to make product recommendations or deliver personalized content to users. We constructed a beer recommendation program using review data from existing online community to test the hypotheses. This research aims to bridge the gap between marketing and computer science by investigating the moderating effects of consumer knowledge (expertise) on the performance and evaluation of two widely-used recommendation systems – user-based collaborative filtering and content-based. The results show that expert consumers prefer user-based collaborative filtering systems, whereas there is no difference between the two systems among novice consumers. Theoretical and managerial implications are discussed.     

The influence of intelligent manufacturing on financial performance and innovation performance: the case of China

ABSTRACT

Artificial intelligence is increasingly used in advanced manufacturing systems to realise intelligent manufacturing. However, there is still a lack of empirical research on the impact of intelligent manufacturing on enterprise performances, especially for China. The author adopts the enterprise panel data of intelligent manufacturing implemented by China’s manufacturing industry in 2014 to 2019, and uses propensity score matching with difference in differences (PSM-DID) method to investigate the impact of intelligent manufacturing on financial performance and innovation performance. The research yields two main conclusions. First, the implementation of intelligent manufacturing has a significant role in promoting the financial performance and innovation performance of manufacturing enterprises. Second, technology-intensive industries improve the quantity of innovation by implementing intelligent manufacturing, thus promoting the improvement of short-term financial performance, but the improvement of innovation quality has a negative impact on short-term financial performance. In labour-intensive industries, the relationship between financial performance and innovation performance is not obvious.     

神经网络在财务管理中的应用

过去的二十年,神经网络越来越多地应用到财务领域中,主要是基于它所具有大规模并行、自组织、自适应、容错和自学习的能力。本文对神经网络在财务领域中的应用趋势、特征进行了分析,研究表明多数应用采用了含有一个隐含层的BP神经网络,并同时和传统的统计模型进行了比较分析。此外,这些研究还表明神经网络在财务管理领域的应用中取得了较满意的结果。     

Emotion as an Argumentation Engine: Modeling the Role of Emotion in Negotiation

The purpose of this paper is to present a model of emotion in negotiation, which reflects the active role emotions play in decision taking as modifiers of theory-of-mind models, goals and strategies. The model is based on empirical studies of human interaction in different activities such as plea bargains, simulated negotiations, doctor patient consultations, and virtual human–human interactions. We use empathy as an example of emotion, which has a natural and powerful function in the shaping and re-contextualization of decision processes. We study also the linguistic realization of emotions as forms of argumentation in authentic discourse.     

Can Emotional Intelligence be developed?

This paper explores approaches to the development of Emotional Intelligence (EI) and to the critical question ‘can EI be developed?’ Technical data on the instruments used to measure EI, the Emotional Intelligence Questionnaire (EIQ) devised by Dulewicz and Higgs (2000c) and the EQ-i designed by Bar-On (1997), are reported. Findings from three studies involving managers, team leaders and the skippers and crews from a round-the-world yacht race are presented to explore whether Emotional Intelligence scores change after training and other experiences. A revised model to explain how the elements of Emotional Intelligence are related to each other is presented and tested, and possible explanations of why some elements are more amenable to development actions are proposed.     

试析商务智能技术在经济管理信息系统中的应用

商务智能技术（Business Intelligence）进入中国已近40年时间,今天众多领域的广泛应用推动了中国信息化进程。目前国内在税务、财政、外汇管理等重要政府经济管理部门都建立了自己的子系统或决策支持系统（DSS）,初步的应用已经体现出BI技术在提高效率和决策科学性,在保持合理运行成本方面的作用。