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Telecommunication (telecom) fraud is one of the most common crimes and causes the greatest financial losses. To effectively eradicate fraud groups, the key fraudsters must be identified and captured. One strategy is to analyze the fraud interaction network using social network analysis. However, the underlying structures of fraud networks are different from those of common social networks, which makes traditional indicators such as centrality not directly applicable. Recently, a new line of research called deep random walk has emerged. These methods utilize random walks to explore local information and then apply deep learning algorithms to learn the representative feature vectors. Although effective for many types of networks, random walk is used for discovering local structural equivalence and does not consider the global properties of nodes.

The authors proposed a new method to combine the merits of deep random walk and social network analysis, which is called centrality-guided deep random walk. By using the centrality of nodes as edge weights, the authors’ biased random walks implicitly consider the global importance of nodes and can thus find key fraudster roles more accurately. To evaluate the authors’ algorithm, a real telecom fraud data set with around 562 fraudsters was built, which is the largest telecom fraud network to date.

The authors’ proposed method achieved better results than traditional centrality indices and various deep random walk algorithms and successfully identified key roles in a fraud network.

The study used co-offending and flight record to construct a criminal network, more interpersonal relationships of fraudsters, such as friendships and relatives, can be included in the future.

This paper proposed a novel algorithm, centrality-guided deep random walk, and applied it to a new telecom fraud data set. Experimental results show that the authors’ method can successfully identify the key roles in a fraud group and outperform other baseline methods. To the best of the authors’ knowledge, it is the largest analysis of telecom fraud network to date.

As firms, especially manufacturers, seek value‐creating opportunities, many are moving operations to low‐cost labor centers. Can firms in the mature economies seize these windows of opportunity to increase productivity in immature economies before wages rise to make their own profits, thus increasing shareholder value? This paper contemplates the ideas that a knowledge‐focused management philosophy, whether technological, process‐oriented, organization structure focused, or cultural can provide managers with techniques to seize this opportunity to create value by increasing labor productivity with less expensive labor. Measuring the value created after implementation of knowledge‐focused management programs can be hard and usually requires comparison to pre‐implementation metrics.

This paper aims to examine optimal decisions for information security investments for a firm in a fuzzy environment. Under both sequential and simultaneous attack scenarios, optimal investment of firm, optimal efforts of attackers and their economic utilities are determined.

Throughout the analysis, a single firm and two attackers for a “firm as a leader” in a sequential game setting and “firm versus attackers” in a simultaneous game setting are considered. While the firm makes investments to secure its information assets, the attackers spend their efforts to launch breaches.

It is observed that the firm needs to invest more when it announces its security investment decisions ahead of attacks. In contrast, the firm can invest relatively less when all agents are unaware of each other’s choices in advance. Further, the study reveals that attackers need to exert higher effort when no agent enjoys the privilege of being a leader.

In a novel approach, inherent system vulnerability of the firm, financial benefit of attackers from the breach and monetary loss suffered by the firm are considered, as fuzzy variables in the well-recognized Gordon – Loeb breach function, with the help of fuzzy expectation operator.

This study reports that the optimal breach effort exerted by each attacker is proportional to its obtained economic benefit for both sequential and simultaneous attack scenarios. A set of numerical experiments and sensitivity analyzes complement the analytical modeling.

In a novel approach, inherent system vulnerability of the firm, financial benefit of attackers from the breach and monetary loss suffered by the firm are considered, as fuzzy variables in the well-recognized Gordon – Loeb breach function, with the help of fuzzy expectation operator.

During the past two decades, China has been rapidly rising in nearly every aspect. With the growing prominence of economic prosperity in China, numerous multinational corporations and companies across the globe have entered this vast market in order to benefit from this enlarging economy. This development also creates an emerging market in China to educate senior managers of these transnational firms in the form of cross‐border partnerships among regional universities. The EMBA programme, a more internationally oriented educational product, is thriving in the Greater China Area. This study aims to examine how universities in China, Hong Kong, and Taiwan are partnering with other institutions in order to deliver collaborative EMBA programmes for this educational market.

The article uses case study as research approach by selecting ten famous cross‐border EMBA programs from elite universities in China, Hong Kong, and Taiwan for analysis.

The result shows that distinctive patterns of organisational behaviour are present in terms of how selective universities in Greater China organise their cross‐border EMBA programmes. By combining abundant academic resources with their partners, Chinese institutions aim to enhance their programme reputation and mainly serve the territorial needs of executive managers within China. Hong Kong, serving a bridging role, is inclined to cooperate with leading universities in Western countries and attract all kinds of students across the globe, including Chinese ones. Alternatively, Taiwanese universities cooperate with major universities or institutions in China in order to serve the needs of Taiwanese businessmen in China instead of Chinese nationals or foreign students. These different approaches indicate a labour division among universities in these three societies, with China targeting primarily the domestic market, Hong Kong aiming at the global market, and Taiwan seeking to serve its country's population.

The different approaches employed by universities reveal how neighbouring societies react to the rise of China respectively. The uneven division of universities among these three societies might to some extent reflect the concepts of “centre” and “periphery” developed by Philip G. Altbach.