Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis

The main goal of this research is to provide a comprehensive understanding of the actual progresses in artificial intelligence, with emphasis on chatbots as emerging forms of customer assistance in online retailing. Drawing upon an analysis of the chatbot patents in the past 20 years, our findings show the increasing technology push towards the adoption of new conversational agents based on natural language. Findings also highlight the extent to which the research and development efforts are attempting to improve artificial intelligence systems that characterize chatbots. To this end, technology advancements are mainly focusing on: (i) improving chatbot ability to automatically draw inferences on users starting from multiple data sources, and (ii) using consumers’ knowledge adaptively to provide more customized solutions. Finally, results show the tight relationship between the digital assistants’ analytical skills and their ability to automatically interact with the users.     

Beyond the boundaries: Challenges for business,policy and society

This editorial article introduces the papers presented at the ITS Seoul 2018 and seven papers selected for the special issue of ITS Seoul 2018. Specifically, this article provides the results of keyword networks, research agendas and coauthor networks of ITS Seoul 2018. A summary of the seven papers accepted for the special issue of ITS Seoul 2018 is also included. Finally, this article concludes by introducing another paper that empirically explores the value of special issues by analyzing the characteristics of special issues of Telecommunications Policy.     

Using artificial neural network and multivariate analysis techniques to evaluate road operating conditions

Regional paved roads are low volume roads with a prevalence of heavy traffic. In the world, these roads concern about 80% of the total road network; however, the traffic that affects these roads is about 20%. Since regional roads are characterized by weak demand, budget for their management/maintenance is very low. This produces considerable difficulties in the choice of strategies for maintenance planning and scheduling. For this reason, the recurring topics of research in this field deal with typical roads issues and aim to develop low cost tools and methods. The study proposes a decision support system to evaluate regional paved roads operating condition in relation to the hydrogeological situation. In particular, the system allows to evaluate in a quick and easy manner, the operating conditions of the road, through low-cost tools (i.e. using low economic resources). This is very useful in the case of LVRs because administrations for these roads have a limited budget. The procedure is developed on a regional paved roads network based on more than 80 roads located in Southern Italy. Data is collected by direct surveys in the field and is integrated with cartography and information available in road agency records. From data analysis, obtained using two different techniques, an easy and quick use procedure is made. In particular, Model 1 is built through multivariate analysis and Model 2 using the artificial neural network (ANN) technique. The results show the validity of the two models in Regional paved roads operating conditions estimation in relation to hydrogeological situations of sites. Both models show good reliability. In particular, the first model (Model 1) is characterized by a high level of significance (p < 0.01) and by a coefficient of determination equal to 0.82. Comparative tests between the second model (Model 2) on which standard tests cannot be performed for obvious reasons, and the first model (Model 1). The results show that the ANN model (model 2), characterized by lower residual, simulates more accurately than the second (Model 1).     

The death of development theory: From Friedrich von Hayek to the Washington consensus

Abstract

Development strategies followed by many countries in the 20th century bestowed a relevant role to the State. During the 1970s, it all reversed, and free markets became paramount to efficiency. F. von Hayek and the Mount Pelerin Society led the way to eliminate the State as a significant economic player, while P.T. Bauer extended such ideas to development economics, which would eventually give way to the Washington Consensus. Beyond actual results of such policies, it is surprising to see the appeal of Bauer’s theoretical approach, considering that it is constructed disregarding both empirical evidence, as well as the abundant discussion on development that was taking place contemporarily. This article explores the theoretical process of such reversal in development economics theory.     

后补贴时代中国新能源汽车产业发展研究

2019年3月,四部委公布新一轮新能源汽车补贴政策,相比2018年标准平均退坡超50%。自政策公布之后,国内新能源汽车市场环境发生巨变,新能源汽车销量增长明显放缓,部分新能源汽车及零部件企业经营困难甚至倒闭,加之以特斯拉为首的外资新能源汽车企业陆续在华设厂投产,使国内新能源汽车市场竞争加剧,下行压力增大,新能源汽车产业正式进入后补贴时代,在此背景下,需要政府部门、相关企业重新评估市场现状,制定新的新能源汽车产业发展战略和路径,推动产业持续健康地发展。     

中国省际区域经济差距演进及协调发展

实现区域协调发展是新时代中国区域高质量发展的必然要求。改革开放以来,中国省际区域经济差距经历了差距拉大—逐渐缩小—缓慢增大—逐渐缩小—维持不变的过程,逐步趋于收敛,其深层原因在于经济发展基础、资本投入、区域要素配置、区域要素使用和制度因素的地区异质性。推进区域经济协调发展,要不断加强对中西部地区的资本投入,优化资源配置,提高全要素生产率,提升开放水平,推进贸易高质量发展,完善与区域协调发展总体战略要求相适应的宏观区域政策和区域管理体制。     

转变城市发展方式之低碳城市建设——基于德国经验借鉴

首先从产业能源体系、低碳交通网络及生态环境三方面梳理德国低碳城市建设实践,然后总结德国在低碳意识培养、战略目标制定、政策体系建设等方面值得借鉴的经验,最后从“公平-效率-质量”视角为我国低碳城市建设提出建设路径:加快创新驱动,提高建设效率;提供制度支持,注重建设公平;强调以人为本,提升建设质量。     

Application of evidential reasoning approach and OWA operator weights in road safety evaluation considering the best and worst practice frontiers

Data envelopment analysis (DEA) has recently become relatively popular with road safety experts. Therefore, various decision-making units (DMUs), such as EU countries, have been assessed in terms of road safety performance (RSP). However, the DEA has been criticized because it evaluates DMUs based only on the concept of self-assessment, and, therefore does not provide a unique ranking for DMUs. Therefore, cross efficiency method (CEM) was developed to overcome this shortcoming. Peer-evaluations in addition to self-evaluation have made the CEM to be recognized as an effective method for ranking DMUs. The traditional CEM is based only on the standard CCR (Charnes, Cooper and Rhodes) model, and it evaluates DMUs according to their position relative to the best practice frontier while neglecting the worst practice frontier. However, the DMUs can also be assessed based on their position relative to the worst practice frontier. In this regard, the present study aims to provide a double-frontier CEM for assessing RSP by taking into account the best and worst frontiers simultaneously. For this purpose, the cross efficiency and cross anti-efficiency matrices are generated.Even though a weighted average method (WAM) is most frequently used for cross efficiency aggregation, the decision maker's (DM) preference structure may not be reflected. For this reason, the present study mainly focuses on the evidential reasoning approach (ERA), as a nonlinear aggregation method, rather than the linear WAM. Equal weights are often used for cross efficiency aggregation; consequently, the effect of the DM's subjective judgments in obtaining the overall efficiency is ignored. In this respect, the minimax entropy approach (MEA) and the maximum disparity approach (MMDA) are applied for determining the ordered weighted averaging (OWA) operator weights for cross efficiency aggregation. The weighted cross efficiencies and cross anti-efficiencies are then aggregated using the ERA. Finally, the proposed method, called DF-CEM-ERA, is used to evaluate the RSP of EU countries as well as Serbian police departments (PDs).     

Dynamic efficiency evaluation of Italian judicial system using DEA based Malmquist productivity indexes

The aim of this study is the empirical analysis of the Italian judicial system, measuring its efficiency and productivity. For this purpose, in details, the Data Envelopment Analysis (DEA) and Malmquist indexes were used, since they are recognized by the current literature as successful techniques to evaluate the performance of decision making units, namely the courts of law in our field of application.The statistical data on the administration of justice in Italy, as reported in Dossier n. 11 May 2013, Senate Research Services, Research Office on Institutional Issues, Justice and Culture, XVII legislature, shows that the efficiency crisis of justice in Italy began in the 1970s of the last century, aggravating during the ‘80s, and reaching its most critical moment during the 1990s. Several studies emphasize the relevance of the effects of inefficiency upon the judicial system on the credit and financial markets.The present analysis, using data that covers a wide time span and is disaggregated at district level, has set the goal of measuring the efficiency of the individual Italian judicial offices while assessing the progress of productivity in its components, by the means of technological progress and scale efficiency. The efficiency analysis that was carried out transcends the aspect of judicial taxation, considering how the passage of time has impacted on judicial efficiency.Considering the judges and judicial administration employed, in the new, pending and finished cases during the years ranging from 2011 to 2016, the results highlighted a distinct heterogeneity among courts, depending on their geographical location. The five-year period that was considered, included the years in which the judicial geographical distribution reform entered into force, so to better comprehend how this complex reform influenced the recovery of efficiency of the judicial offices. Furthermore, by breaking down the index into change in efficiency and change in technology, this work offers a further glimpse into judiciary organization. The application of combined DEA method and Malmquist indexes for evaluating court efficiency in a large time frame showed very interesting and useful results, relevant for judicial administration.     

The long-run performance of acquiring firms in mergers and acquisitions: Does managerial ability matter?

This paper examines the association between the managerial ability of acquiring firms and their long-term performance after mergers and acquisitions (M&As). Based on M&A data for U.S. firms from 2000 to 2012, we find that acquiring firms with higher managerial ability achieve better long-term operating performance and stock returns. We also find that the positive effect of managerial ability on long-term performance is more pronounced when acquirers and target firms belong to the same industry. The result suggests that managers who have higher ability to manage their firms, i.e., to generate higher revenues for given resources, are more capable of achieving higher synergy benefits and better post-acquisition performance in same-industry acquisitions than in cross-industry acquisitions.