How to foster frontline employee knowledge sharing within service‐oriented enterprises: Empirical evidence from China

Based on the context of Chinese workplace, the present research aims to explore the combined effects of proactive personality, supervisor–subordinate guanxi (s–s guanxi), and leaders’ innovation expectations on the knowledge sharing of frontline employees (FLEs). Questionnaire data from a sample of 301 FLEs within service‐oriented enterprises in China were used in this study. The results show that proactive personality and leaders’ innovation expectations are both positively related to employees’ psychological empowerment and knowledge sharing, and s–s guanxi significantly impacts psychological empowerment, but has a nonsignificant effect on knowledge sharing. This study expands the understanding of FLEs’ knowledge sharing behavior and enriches our understanding of the guanxi construction process during the interaction between supervisors and subordinates.     

When guanxi meets structural holes: Exploring the guanxi networks of Chinese entrepreneurs on digital platforms

In this exploratory study, we investigate how Chinese entrepreneurs on digital platforms interact and leverage guanxi (a system of relationships and social network) to buffer the negative impacts of structural holes on knowledge orchestration. We develop our research model and formulate ten hypotheses by drawing on the literature. We adopt a mixed-methods research approach in which we use quantitative surveys to test the hypotheses, and qualitative interviews to explain why certain relationships are stronger in one stage of entrepreneurial development than the other. The study contributes to the literature on digital entrepreneurship in two ways. First, this study offers an initial understanding of the dynamics of guanxi networks for knowledge mobilisation and knowledge coordination across start-up and growth stages of Chinese entrepreneurs on digital platforms. Second, by drawing on the relevant literature, our findings extend the current understanding of knowledge orchestration of digital entrepreneurs and contribute to the literatures of structural holes theory and guanxi.     

An empirical investigation of socio-cultural factors of information sharing in China

Understanding information sharing is an important challenge to modern organizations, and is likely to be increasingly considered when IT investment decisions are made world-wide. Our research study investigated the influence of cultural factors on information sharing in China. It was postulated that social network structures such as guanxi, Confucian dynamism, and collectivism could explain the degree to which information sharing took place between people in China. It was found that guanxi, Confucian dynamism, and collectivism all had a significant influence on information sharing.     

Both global and local: ICTs and joint ventures in China

Abstract. The expansion of global firms, supported by extensive information and communication technology (ICT) systems, is frequently seen as leading to the spread of best practices to different regions of the world. Some argue that these practices are bound up with the national origins of these firms, while others propose that local circumstances in specific economies are of prime importance. According to the first perspective, global firms will use ICTs in China that reflect their national origins, but the second approach emphasizes the importance of the Chinese local context in how and what ICTs are used. Based on evidence from two case studies of global UK multinationals with Chinese joint ventures, this paper argues that the ICTs used by these companies do relate to their national roots and that China is seen by them as a very unusual setting that is treated as a special case. For example, one company was prepared to roll out a global enterprise planning system elsewhere but refused to implement it in China, while the second company cordoned off their ICT systems in China from their other, more global systems. Cultural frames of reference are advanced as an important explanation of differences in the usage of ICTs in China. Building on these ideas, this paper argues that how difference is recognized, accommodated and (re)affirmed is significant for the performance of formal business processes. Formal and ICT‐enabled systems ‘work’ by being embedded in changing Chinese cultural practices such as guanxi, though this is frequently not recognized by Western managers. While the global nature of global firms may be overplayed, the local arrangements of joint ventures are very important in how ICT systems are implemented in which the embedding and disembedding require an understanding of sited cultural practices that underpin the performance of formal systems. What is at stake is how global firms and their ICT systems are able to adapt to Chinese circumstances, and, in the longer term, how Chinese joint venture partners, often previously state‐owned enterprises, adapt to different forms of control mediated by ICTs.     

How to build an appropriate information ethics code for enterprises in Chinese cultural society

Information ethics codes play a vital role in clarifying the responsibilities of MIS (management information systems) professionals and providing them with a point of reference when dealing with ethical issues. In view of the important 21st Century role played by China, particularly Mainland China, which represents a hugely significant market to all global enterprises, it is hoped that this study will assist the business world in understanding the culture in which Chinese business is conducted, and will facilitate the building of a suitable information ethics code in the future. Academically, this paper aims to explain how Confucian ethics and the guanxi ¹ culture perspective affect MIS professionals’ ethical dilemmas and reactive processes. Specifically, it examines the reactive processes of MIS professionals in CHSyst (pseudonym) in Taiwan, Hong Kong and Mainland China. In practice, this study provides a good reference for enterprises such as the above that wish to find the most appropriate way to create an ethics code suitable for a Chinese company context to prevent Chinese MIS professionals from behaving unethically in their workplace. Such a code will serve to reduce the negative consequences of unethical conduct for the organization.     

Regional ICT access and entrepreneurship: Evidence from China

Entrepreneurship has become increasingly important for innovations and economic development. However, there is limited information systems research examining the role of regional ICT for entrepreneurs. This study investigates the direct effect of regional ICT access on individuals’ entrepreneurial performance and the interaction effect between regional ICT access and guanxi in the context of Chinese business and economy. Drawing upon a matched large-scale dataset, we found that regional ICT access in terms of access to the Internet, fixed phone, and mobile phone had a significant impact on performance. Furthermore, regional ICT access had a positive interaction effect with guanxi.     

Prediction of MHC II-binding peptides using rough set-based rule sets ensemble

Peptide binding to Major Histocompatibility Complex (MHC) is a prerequisite for any T cell-mediated immune response. Predicting which peptides can bind to a specific MHC molecule is indispensable to minimizing the number of peptides required to synthesize, to the development of vaccines and immunotherapy of cancer, and to aiding to understand the specificity of T-cell mediated immunity. At present, although predictions based on machine learning methods have good prediction performance, they cannot acquire understandable knowledge and prediction performance can be further improved. Thereupon, the Rule Sets ENsemble (RSEN) algorithm, which takes advantage of diverse attribute and attribute value reduction algorithms based on rough set (RS) theory, is proposed as the initial trial to acquire understandable rules along with enhancement of prediction performance. Finally, the RSEN is applied to predict the peptides that bind to HLA-DR4(B1^* 0401). Experimentation results show: (1) prepositional rules for predicting the peptides that bind to HLA-DR4 (B1^* 0401) are obtained; (2) compared with individual RS-based algorithms, the RSEN has a significant decrease (13%–38%) in prediction error rate; (3) compared with the Back-Propagation Neural Networks (BPNN), prediction error rate of the RSEN decreases by 4%–16%. The acquired rules have been applied to help experts make molecules modeling. An Zeng received the Ph.D. degree in computer applications technology from South China University of Technology in 2005. Nowadays she is a lecturer at the Faculty of Computer of Guangdong University of Technology. Her research interests are data mining, bioinformatics, neural networks, artificial intelligence, and computational immunology. In these areas she has published over 20 technical papers in various prestigious journals or conference proceedings. She is a member of the IEEE. Contact her at the Faculty of Computer, Guangdong Univ. of Technology, University Town, PanYu District, Guangzhou, 510006, P.R. China. Dan Pan received the Ph.D. degree in circuits and systems from South China University of Technology in 2001. He is a senior engineer in Guangdong Mobile Communication Co. Ltd at present. His research interests are data mining, machine learning, bioinformatics, and data warehousing, and applications of business modeling and software engineering to computer-aided business operations systems, especially in the telecom industry. In these areas he has published over 30 technical papers in refereed journals or conference proceedings. As a member of the International Association of Science and Technology for Development (IASTED) technical committee on artificial intelligence and expert systems, he served a number of conferences and publications. He is a member of the IEEE. Contact him at Guangdong Mobile Communication Co. Ltd., 208 Yuexiu South Rd., Guangzhou, 510100, P.R. China. Jian-bin He received the M.E. in computer science from South China University of Technology in 2002. He now is a data mining consultant at Teradata division of NCR (China), supporting telecom carriers to do data mining in data warehouses for market research. His research interests include statistical learning, semi-supervised learning, spectral clustering, multi-relational data mining and their application to social science. Contact him at NCR(China) Co. Ltd., Unit 2306, Tower B, Center Plaza, 161 Linhexi Road, Guangzhou, 510620, P.R. China.     

An analytical framework for evaluating peer-to-peer business models

While existing research on peer-to-peer (P2P) file-sharing services has increased our understanding in many respects, it has not yet supplied a comprehensive theoretical framework that explains business failures of P2P file-sharing network service models. We develop such an analytical model and base it on seven specific market constraints – technical, economic, structural, legal, political, cognitive, and cultural – that are specifically relevant for P2P services. We show how our model can be used as a tool for strategic analysis of P2P business model performance using Napster as a particular case of study. We show also how P2P file-sharing networks have migrated through a series of system typologies by incorporating technological innovations in response to market constraints. Finally, we offer a new theoretical conceptualization that views P2P file-sharing networks as electronic markets.     

The effect of an information ethics course on the information ethics values of students - A Chinese guanxi culture perspective

The development of information technology has a significant influence on social structure and norms, and also impacts upon human behavior. In order to achieve stability and social harmony, people need to respect various norms, and have their rights protected. Students’ information ethics values are of critical and radical importance in achieving this goal. Using qualitative approach, the present study utilizes Kohlberg’s CMD model to measure improvement in students’ “information ethics values” through “technology mediated learning (TML)” models, and to assess the extent to which it is influenced by gender and Chinese guanxi culture. We find that while e-learning improves female students’ “respect rules,” “privacy,” “accessibility” and “intellectual property” values more than male students, the percentages relating to “intellectual property” for females in the higher stages remain lower than for males. Moreover, these results are interpreted from a Chinese guanxi culture perspective. In light of these results, educators should take account of such improvements when designing effective teaching methods and incentives.     

An Agent-Based Socio-Technical Approach to Impact Assessment for Cyber Defense

ABSTRACT

This paper presents a novel simulation for estimating the impact of cyber attacks. Current approaches have adopted the probabilistic risk analysis in order to estimate the impact of attacks mostly on assets or business processes. More recent approaches involve vulnerability analysis on networks of systems and sensor input from third-party detection tools in order to identify attack paths. All these methods are focusing on one level at a time, defining impact in terms of confidentiality, integrity, and availability, failing to place people and technology together in an organization’s functional context. We propose an interdependency impact assessment approach, focusing on the responsibilities and the dependencies that flow through the supply chain, mapping them down into an agent-based socio-technical model. This method is useful for modeling consequences across all levels of organizations networks—business processes, business roles, and systems. We are aiming to make chaining analysis on threat scenarios and perform impact assessment, providing situational awareness for cyber defense purposes. Although the model has various applications, our case study is specifically focusing on critical information infrastructures due to the criticality of the systems and the fact that the area is still lacking security-focused research and heavily relies on reliability theory and failure rate.     

Diffusion Schemes for Load Balancing on Heterogeneous Networks

Several different diffusion schemes have previously been developed for load balancing on homogeneous processor networks. We generalize existing schemes, in order to deal with heterogeneous networks. Generalized schemes may operate efficiently on networks where each processor can have arbitrary computing power, i.e., the load will be balanced proportionally to these powers. The balancing flow that is calculated by schemes for homogeneous networks is minimal with regard to the l ₂ -norm and we prove this to hold true for generalized schemes, too. We demonstrate the usability of generalized schemes by a number of experiments on several heterogeneous networks.     

Identifying influential nodes in weighted complex networks using an improved WVoteRank approach

Influence maximization is an important research problem in the field of network science because of its business value. It requires the strategic selection of seed nodes called “influential nodes,” such that information originating from these nodes can reach numerous nodes in the network. Many real-world networks, such as transportation, communication, and social networks, are weighted networks. Influence maximization in a weighted network is more challenging compared to that in an unweighted network. Many methods, such as weighted degree rank, weighted h-index, weighted betweenness, and weighted VoteRank techniques, have been used to order the nodes based on their spreading capabilities in weighted networks. The VoteRank method is a popular method for finding influential nodes in an unweighted network using the idea of a voting scheme. Recently, the WVoteRank method was proposed to find the seed nodes; it extends the idea of the VoteRank method by considering the edge weights. This method considers only 1-hop neighbors to calculate the voting score of every node. In this study, we propose an improved WVoteRank method based on an extended neighborhood concept, which takes the 1-hop neighbors as well as 2-hop neighbors into account for the voting process to decide influential nodes in a weighted network. We also extend our proposed approach to unweighted networks. We compare the performance of the proposed improved WVoteRank method against the popular centrality measures, weighted degree, weighted closeness, weighted betweenness, weighted h-index, and weighted VoteRank on several real-life and synthetic datasets of diverse sizes and properties. We utilize the widely used stochastic susceptible–infected–recovered information diffusion model to calculate the infection scale, the final infected scale as a function of time, and the average distance between spreaders. The simulation results reveal that the proposed method, improved WVoteRank, considerably outperforms the other methods described above, including the recent WVoteRank.

     

The changes on synchronizing ability of coupled networks from ring networks to chain networks

In this paper, two different ring networks with unidirectional couplings and with bidirectional couplings were discussed by theoretical analysis. It was found that the effects on synchronizing ability of the two different structures by cutting a link are completely opposite. The synchronizing ability will decrease if the change is from bidirectional ring to bidirectional chain. Moreover, the change on synchro- nizing ability will be four times if the number of N is large enough. However, it will increase obviously from unidirectional ring to unidirectional chain. It will be N 2/(2π2) times if the number of N is large enough. The numerical simulations confirm the conclusion in quality. This paper also discusses the effects on synchronization by adding one link with different length d to these two different structures. It can be seen that the effects are different. Theoretical results are accordant to numerical simulations. Synchronization is an essential physics problem. These results pro- posed in this paper have some important reference meanings on the real world networks, such as the bioecological system networks, the designing of the circuit, etc.     

Auto-CFD-NOW: A pre-compiler for effectively parallelizing CFD applications on networks of workstations

Computational Fluid Dynamics (CFD) applications are highly demanding for parallel computing. Many such applications have been shifted from expensive MPP boxes to cost-effective Networks of Workstations (NOW). Auto-CFD-NOW is a pre-compiler that transforms Fortran CFD sequential programs to efficient message-passing parallel programs running on NOW. Our work makes the following three unique contributions. First, this pre-compiler is highly automatic, requiring a minimum number of user directives for parallelization. Second, we have applied a dependency analysis technique for the CFD applications, called analysis after partitioning. We propose a mirror-image decomposition technique to parallelize self-dependent field loops that are hard to parallelize by existing methods. Finally, traditional optimizations of communication focus on eliminating redundant synchronizations. We have developed an optimization scheme which combines all the non-redundant synchronizations in CFD programs to further reduce the communication overhead. The Auto-CFD-NOW has been implemented on networks of workstations and has been successfully used for automatically parallelizing structured CFD application programs. Our experiments show its effectiveness and scalability for parallelizing large CFD applications. This work is supported in part by the China National Aerospace Science Foundation, and by the U.S. National Science Foundation under grants CCR-9812187, CCR-0098055, CCF-0325760, CCF 0514078, and CNS 0549006.     

A literature review of electronic marketplace research: Themes, theories and an integrative framework

In this paper, we presented a literature review of the current status of electronic marketplace (EM) research. It consists of 109 journal articles published in 19 journals that are appropriate outlets for electronic commerce research. The results show that an increasing volume of EM research has been conducted from diverse theoretical perspectives. Based on content analysis, we identified eight research themes, five types of methodologies and six categories of background theories which most EM researches were grounded in. By combining research themes and the patterns of the background theories, an integrative framework of EM was proposed to represent the paradigms of EM researches. The framework shows that EM phenomena can be addressed from three perspectives: information systems, inter-organizational/social structure and strategic management perspectives. This framework suggests a parsimonious and cohesive way to explain key EM research issues such as EM adoption, success and impact.

Managing Quality-of-Service in Internet Applications Using Differentiated Services

Advances in networks during the past decades have fostered the deployment of a variety of Internet applications. Many of these applications have a range of Quality-of-Service (QoS) requirements, some involving network throughput, delay, and reliability. Consequently, there is growing need for network services that can differentiate applications having QoS requirements from those without and to be able to further classify applications with QoS requirements into different classes at the IP-network level. The Internet Engineering Task Force (IETF) has proposed Differentiated Services (DiffServ) to provide QoS in IP-based networks. The goal of DiffServ is to define configurable types of packet forwarding that can provide service differentiation for large aggregates of network traffic. We report on our investigation of Relative Proportional Differentiated Services to implement DiffServ in IP-based networks and one that supports the provisioning and management of QoS for Internet Applications. The main contributions of the paper are the introduction of a novel traffic conditioning architecture for the marker and shaper/policer which relies on feedback from a metering component, and the provision for a QoS manager to enable a network administrator or a management application to dynamically adjust control parameters.     

Study of General Icomplete Star Interconnection Networks

The star networks,which were originally proposed by Akers and Harel,have suffered from a rigorous restriction on the number of nodes.The general incomplete star networks(GISN) are proposed in this paper to relieve this restriction.An efficient labeling scheme for GISN is given,and routing and broadcasting algorithms are also presented for GIS.The communication diameter of GISN is shown to be bounded by 4n-7.The proposed single node broadcasting algorithm is optimal with respect to time complexity O(nlog2n).     

SNEFL: Social network explicit fuzzy like dataset and its application for Incel detection

In this paper, with respect to reviewing and comparing existing social networks’ datasets, we introduce SNEFL dataset: the first social network dataset that includes the level of users’ likes (fuzzy like) data in addition to the likes between users. With users’ privacy in mind, the data has been collected from a social network. It includes several additional features including age, gender, marital status, height, weight, educational level and religiosity of the users. We have described its structure, analysed its features and evaluated its advantages in comparison with other social network datasets. On top of that, using unique feature of SNEFL dataset (fuzzy like) for the first time a rule-based algorithm has been developed to detect involuntary celibates (Incels) in social networks. Despite Incels activities in online social networks, until now no study on computer science has been performed to identify them. This study is the first step to address this challenge that society is facing today. Experimental results show that the accuracy of the proposed algorithm in identifying Incels among all social network users is 23.21% and among users who have fuzzy like data is 68.75%. In addition to the Incel detection, SNEFL dataset can be used by researchers in different fields to produce more accurate results. Some study areas that SNEFL dataset can be used in are network analysis, frequent pattern mining, classification and clustering.

     

On Probabilistic Networks for Selection, Merging, and Sorting

We study comparator networks for selection, merging, and sorting that output the correct result with high probability, given a random input permutation. We prove tight bounds, up to constant factors, on the size and depth of probabilistic (n,k)-selection networks. In the case of (n, n/2)-selection, our result gives a somewhat surprising bound of on the size of networks of success probability in , where δ is an arbitrarily small positive constant, thus comparing favorably with the best previously known solutions, which have size . We also prove tight bounds, up to lower-order terms, on the size and depth of probabilistic merging networks of success probability in , where δ is an arbitrarily small positive constant. Finally, we describe two fairly simple probabilistic sorting networks of success probability at least and nearly logarithmic depth. Received January 22, 1996, and in final form February 14, 1997.