Analysis of the Chinese Airline Network as multi-layer networks

This paper encapsulates the Chinese Airline Network (CAN) into multi-layer infrastructures via the “k-core decomposition” method. The network is divided into three layers: Core layer, containing airports of provincial capital cities, is densely connected and sustains most flight flow; Bridge layer, consisting of airports in Tier 2 and Tier 3 cities, mainly connects two other layers; and Periphery layer, comprising airports of remote areas, sustains little flight flow. Moreover, it is unveiled that CAN stays the most robust when low-degree nodes or high flight flow links are removed, which is similar to the Worldwide Airline Network (WAN), albeit less redundant.     

On the multi-dimensionality and sampling of air transport networks

Complex network theory is a framework increasingly used in the study of air transport networks, thanks to its ability to describe the structures created by networks of flights, and their influence in dynamical processes such as delay propagation. While many works consider only a fraction of the network, created by major airports or airlines, for example, it is not clear if and how such sampling process bias the observed structures and processes. In this contribution, we tackle this problem by studying how some observed topological metrics depend on the way the network is reconstructed, i.e. on the rules used to sample nodes and connections. Both structural and simple dynamical properties are considered, for eight major air networks and different source datasets. Results indicate that using a subset of airports strongly distorts our perception of the network, even when just small ones are discarded; at the same time, considering a subset of airlines yields a better and more stable representation. This allows us to provide some general guidelines on the way airports and connections should be sampled.     

A tourist kit ‘made in Italy’: An ‘intelligent’ system for implementing new generation destination cards

This study investigates the advantages and the potentiality of the ‘tourist kit’, an Italian solution based on the concept of a prepaid card that is issued by a large postal operator. The destination card can be reloaded by tourists according to their needs and its validity is not restricted to short periods. Thus, the kit provides tourists with an integrated, practical, and flexible tool capable of making their stay more enjoyable as it allows cardholders to choose and buy many products and services at discounted prices. The kit creates customer loyalty by utilising smart technology aimed at collecting accurate tourist information. This model deserves attention because it is probably the world's first case of a large postal operator entering the tourism sector with the proposal of an integrated and advanced destination card scheme. This research also discusses interesting opportunities and challenges related to the implementation of new generation tourist cards.     

Evaluating the multi-period efficiency of East Asia airport companies

The aim of this study is to analyze how internal operating sub-processes and annual operations of airport companies influence the overall efficiency. The multi-period Network Data Envelopment Analysis is used to evaluate the efficiencies and the efficiency changes for East Asia airport companies. The results indicate that the overall efficiencies of airport companies during a specified period of time are affected by the system efficiency and the sub-processes’ efficiencies in individual periods. Furthermore, the overall efficiency change is determined by the sub-processes’ efficiency changes. According to the operating decision analysis matrix, managers can discover the inefficient sub-processes and formulate the improvement countermeasures.     

Merger and acquisitions in South African banking: A network DEA model

Banking in South Africa is known for its small number of companies that operate as an oligopoly. This paper presents a strategic fit assessment of mergers and acquisitions (M&A) in South African banks. A network DEA (Data Envelopment Analysis) approach is adopted to compute the impact of contextual variables on several types of efficiency scores of the resulting virtual merged banks: global (merger), technical (learning), harmony (scope), and scale (size) efficiencies. The impact of contextual variables related to the origin of the bank and its type is tested by means of a set of several robust regressions to handle dependent variables bounded in 0 and 1: Tobit, Simplex, and Beta. The results reveal that bank type and origin impact virtual efficiency levels. However, the findings also show that harmony and scale effects are negligible due to the oligopolistic structure of banking in South Africa.     

Exploring the core factors of online purchase decisions by building an E-Commerce network evolution model

With the continuous development of the Internet and information technology, online shopping has become a popular purchase mode. The in-depth analysis of consumer decision-making in online shopping is an important issue. Our purpose is to study how the factors of the shopping web pages corporately affect online purchase decisions and determine which are the core factors that affect consumer purchase decisions. We screen the influencing factors on the shopping webpage and deploy e-commerce network evolution based on various weight combinations of these factors to generate sales distributions of online products. By comparing these simulated sales distributions to the real data, the optimal weight of each factor is obtained. The results show that sales volume and the number of high-quality negative comments are the most important factors influencing consumers' decision-making, the number of comments and the number of comments with pictures are relatively minor factors, store type and video presentation of the products have the least impact. The optimal simulated sales distribution is very close to the real case and verifies that the introduced network evolution technology is applicable. The proposed model can be used as a uniform evaluation platform for correlational study, which is an important link in the purchase research chain.     

An empirical investigation of director selection in movie preproduction: A two-sided matching approach

This paper examines how movie producers recruit directors in the preproduction phase as mutual choices in a two-sided matching model. It conceptualizes that movie attributes and filmmaker characteristics determine the matching outcomes (“who directed which movie”) and in turn indirectly affect movie box office. We exploit a dataset of 4,807 feature films from 1990 to 2010 to examine empirically the complementarities between the movie/producer side and the director side in terms of movie budget, filmmaker track records and social relations. A series of simulations suggest that social relations facilitate positive assortative matching. Further simulation analyses are conducted to quantify the financial implications of movie–director mismatches, as well as the indirect effects of production budget and producer characteristics. The simulation results show that: a) the financial implications of having a mismatched director can be substantial; and b) the indirect effect of production budget and producer characteristics affect movie box office in an interactive manner. These findings can help filmmakers to better understand the financial impacts of movie–director choices and make more informed decisions at the early phase of preproduction.     

网络环境下经济行为边界的确定

现代社会是信息社会,互联网和计算机应用是最明显的特征。人们基于网络参与经济决策与市场交易活动,道德理念、行为准则和行为安排发生了较大的变化。网络技术:一方面,极大地降低了交易费用;另一方面,由于经济行为的隐蔽性,追求经济利益的行为缺乏有效监督,人的趋利避害和机会主义倾向更容易诱发蓄意性诱导行为。在网络环境下,如何界定“经济人”的行为模式,怎样减少经济行为负的外部效应成为经济学理论研究的问题。本文主要讨论网络环境中“经济人”经济行为边界的确定。     

Of stars and galaxies – Co-authorship network and research

We examine the association between network centrality and research using the accounting research community setting. We establish co-authorship network using papers published in the five top accounting journals from 1980 to 2016. We find that the co-authorship network in accounting is a “small world” with some most connected authors playing a key role in connecting others. We use machine learning to label published papers with multiple topics and find patterns in topics over time. More importantly, we find that co-authorship network centrality is positively associated with future research productivity and topic innovation and that the impact of centrality on productivity is higher with more senior authors. Further, centrality of an author’s co-authors also has an incrementally positive impact. We conclude that network centrality positively influences research output.     

双层网络嵌入下结构洞对企业二元创新的影响研究

网络结构特征影响企业知识转移与知识组合效果,进而对创新绩效产生复杂作用。利用我国165家上市企业2007—2018年专利面板数据,实证检验企业知识与协同双层网络嵌入对二元创新绩效的影响,并分析战略柔性和开放度对上述关系的调节作用。研究结果表明,企业知识网络结构洞正向影响利用式创新绩效,负向影响探索式创新绩效;协同网络结构洞与二元创新均存在负相关关系。同时,战略柔性和开放度调节双层网络结构洞与二元创新的关系,且变量间存在有效匹配关系：知识网络结构洞—开放度促进利用式创新绩效提升,而协同网络结构洞—战略柔性促进探索式创新绩效提升。研究结论为解决结构洞与企业创新关系的分歧带来新思路,同时为企业创新绩效提升提供理论借鉴。