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Purpose – Structural embeddedness of social networks within and beyond work organizations has shown its association with the innovation at work for employees from literature. Structural embeddedness includes three dimensions: the diversity, density, and trust of accessed networks. This chapter attempts to compare how structural embeddedness mechanizes on innovation at work differently for employees in hi-tech and non-hi-tech sectors.Methodology/approach – We analyzed 1,817 cases of currently employed respondents from the 2005 Taiwan national survey on social capital. All the indicators on structural embeddedness are operationalized from position-generated networks, and we performed regression models for total, hi-tech, and non-hi-tech samples.Findings – Except the universal effects of diversity on innovation at work for employees in both hi-tech and non-hi-tech sectors, density and trust of accessed networks significantly affect innovation at work only for employees in non-hi-tech sectors. There is a slight interaction effect between trust and density on innovation at workplaces. Those individuals with high-degree trust in accessed networks tend to have a lower degree of innovation while their network density is high. It implies that complementary networks seem to be more useful for applying new ideas at the workplace for non-hi-tech workers.Originality/value of chapter – This chapter contributes to the literature by presenting the importance of structural embeddedness of accessed social networks for innovation at work.

The purpose of this paper is to utilize key insights from social network theory (SNT) to enhance understanding of overcoming the liability of outsidership as a prerequisite for firm internationalization. Specifically, it examines the influence of structural attributes of networks on the motivational stance of both network insiders and outsiders in relation to overcoming the liability of outsidership. A related aim is to explore the role of network positions of insider actors in terms of its impact on the speed of market entry.

The paper draws on the extant literatures on firm internationalization, particularly the liability of outsidership, and SNT to identify to what extent SNT can be utilized to deeply understand the process of overcoming the liability of outsidership. The authors put forward eight propositions linking structural and positioning attributes of networks with overcoming the liability of outsidership.

SNT provides strong potential for a more comprehensive understanding of the internationalization phenomena through shedding light on the relationship between the liability of foreignness and the liability of outsidership. The paper demonstrates that while the cost of overcoming the liability of outsidership is higher in closed target network as compared to open networks, the expected benefits of an insidership position in closed or open networks are affected by the outsider firm’s perception of the liability of foreignness in the market it wishes to enter. Considering the differential enabling characteristics of closed and open networks in terms of facilitating tacit knowledge sharing as opposed to explicit information flows, the authors reveal that liability of foreignness operates as a negative moderator for the relationship between network structure and the willingness of the outsider to invest in gaining insidership. The analysis of the paper also shows that the positional attributes of the network insider are relevant in outsiders’ motivation in terms of the speed of market entry that they seek to achieve.

This study theoretically contributes to the internationalization research through integrating SNT with the liability of outsidership understanding of firm internationalization. This is a timely attempt as no systematic application of the conceptual apparatus of SNT in the internationalization research context has been studied. It adds a more coherent inside-out perspective into the overcoming the liability of outsidership discussion which has been extensively dominated by an outside-in perspective.

Despite the fast progress in structural health monitoring (SHM), the efficient use in practice of emerging techniques for large civil engineering structures is still a challenge. This paper outlines a practical framework to optimize both the number and the locations of sensors to measure frequency response functions (FRFs) that will be processed and used to predict the location and the damage level in a model of an existing suspension bridge.

Sensors number and placement (SNPO) procedure is proposed and carried out on a 3D FE model of the 502 m long Oued Dib suspension bridge (Algeria) to determine the degrees of freedom (DOFs) that will receive the sensors. For this purpose, accessible candidate positions on the model are first determined and then reduced by taking the DOFs with the lowest values of the Fisher information matrix (FIM) associated with each of the DOFs taken individually. A genetic algorithm with an objective function equal to the square root of the sum of the squares of the non-diagonal elements of the MAC matrix and a mutation function that allows increasing and decreasing the number of the chromosomes (sensors) of the individuals showed stable convergence to optimal solutions. FRFs at sensor positions generated from the 3D FE model and altered with artificial noise to simulate experimental conditions have been used to constitute a database to train and test a feed-forward neural network.

A framework for SHM integrating a genetic algorithm to optimize both the number and placement of the sensors on the structure.

The procedure can be applied only for single predefined/potential damage detection.

The evidence from this study suggests that the proposed procedure provides a consistent framework to implement a SHM scheme for existing large infrastructures.

Vital infrastructures require special structural protection that can be achieved through effective SHM. This study contributes to the deployment of SHM for existing civil engineering structures.

In addition to the integrated SHM framework proposed in this study, the latter includes an efficient genetic algorithm capable to optimize both the number and the placement of the sensors.

Nowadays, database management system has been applied in library management, and a great number of data about readers’ visiting history to resources have been accumulated by libraries. A lot of important information is concealed behind such data. The purpose of this paper is to use a typical data mining (DM) technology named an association rule mining model to find out borrowing rules of readers according to their borrowing records, and to recommend other booklists for them in a personalized way, so as to increase utilization rate of data resources at library.

Association rule mining algorithm is applied to find out borrowing rules of readers according to their borrowing records, and to recommend other booklists for them in a personalized way, so as to increase utilization rate of data resources at library.

Through an analysis on record of book borrowing by readers, library manager can recommend books that may be interested by a reader based on historical borrowing records or current book-borrowing records of the reader.

If many different categories of book-borrowing problems are involved, it will result in large length of encoding as well as giant searching space. Therefore, future research work may be considered in the following aspects: introduce clustering method; and apply association rule mining method to procurement of book resources and layout of books.

The paper provides a helpful inspiration for Big Data mining and software development, which will improve their efficiency and insight on users’ behavior and psychology.

The paper proposes a framework to help users understand others’ behavior, which will aid them better take part in group and community with more contribution and delightedness.

DM technology has been used to discover information concealed behind Big Data in library; the library personalized recommendation problem has been analyzed and formulated deeply; and a method of improved association rules combined with artificial bee colony algorithm has been presented.

For many years, ABB has been setting the standard for flexible automation in a wide range of industries. Combining pace with precision, the IRB 340 FlexPicker, for example, is opening up new markets as it drastically reduces the cost of pick and place operations. A range of refinements, including a brand new software package dubbed PickMaster, a wash‐down version of the IRB 340 robot and an upgraded controller for unparalleled speed and motion control, now give FlexPicker even more robotic muscle.

The purpose of this paper is to improve the efficiency of particle optimization method by using direct and indirect surrogate modeling in inverse design problems.

The new algorithm emphasizes the use of a direct and an indirect design prediction based on local surrogate models in particle swarm optimization (PSO) algorithm. Local response surface approximations are constructed by using radial basis neural networks. The principal role of surrogate models is to answer the question of which individuals should be placed into the next swarm. Therefore, the main purpose of surrogate models is to predict new design points instead of estimating the objective function values. To demonstrate its merits, the new approach and six comparative algorithms were applied to two different test cases including surface fitting of a geographical terrain and an inverse design of a wing, the averaged best-individual fitness values of the algorithms were recorded for a fair comparison.

The new algorithm provides more than 60 per cent reduction in the required generations as compared with comparative algorithms.

The comparative study was carried out only for two different test cases. It is possible to extend test cases for different problems.

The proposed algorithm can be applied to different inverse design problems.

The study presents extra ordinary application of double surrogate modeling usage in PSO for inverse design problems.

While the activities of the Ku Klux Klan are central to accounts of the Civil Rights Movement, and, by extension, closely tied to the development of social movement theory since the 1960's, no previous study has been able to construct an unbiased profile of Klan membership. This paper draws on a set of 94 FBI interviews with Alabama Klansmen in 1963 and 1964 to compile a representative sample of local Klan membership and evaluate the determinants of individual participation. Using this sample, I examine the extent to which Klan adherents differed from the surrounding population, as well as the structure of bias in previous attempts to profile Klan membership. I conclude by highlighting the importance of social networks in linking individuals to reactive social movement organizations, which adds an important relational dimension to existing research focused on grievances produced by macro-level processes.

The purpose of this paper is to investigate marketing practices in professional service firms (PSFs). PSFs' marketing practices are not well understood, despite their increasing importance to economies worldwide and recognition of their unique characteristics and the marketing challenges they face. The study also examined whether PSF performance outcomes is better modeled through a competency approach suggested by the resource‐based view, or through the extent of use (practices) approach.

Empirical data were collected from professional service providers through an online survey of senior professional service providers across a range of services, including law, engineering, accounting and finance and management consultancy.

Results show interaction marketing was the most common PSF practice and the combination of extent of use and competency, rather than extent of use alone, is a better predictor of firm performance. The results also demonstrate the relevance of the plurality of practices.

The study shows that transaction marketing and database marketing are particularly necessary for financial and market performance, while both interaction marketing and database marketing particularly underpin customer performance. All practices need to be conducted extensively and well for optimum outcomes. The study is cross‐sectional in nature and does not enable a judgment about causal inferences; rather, relationships between constructs are presented.

Professional service providers should focus on competency of practice, as well as extent of practice. However, not all professional service providers do this. Importantly, having a customer service focus is not sufficient to achieve positive market and financial outcomes.

The results presented in the paper have important implications for researchers when modeling and measuring marketing practices and for professional service managers when undertaking marketing activities.

Based on ethnographic fieldwork carried out among market sellers in Equatorial Guinea’s capital Malabo at the height of its oil-boom in 2010–2012, this paper explores how prices were negotiated and set. It describes how the marketplace constitutes an important institution in Guinean society, not only as a site for provisioning, but also as a space for fostering relationships, engaging in politics and seeking social justice. The case of Equatorial Guinea helps us to re-think the notion of the just price as it is established through contingent and negotiated relations between traders, their customers and powerful political actors, rather than being the outcome of supply and demand or the result of struggles over the production and reproduction of labour. The emphasis on the political dimension of the just price speaks to key debates in the moral economy literature.

The differential magnetic gradient tensor system is usually constructed from the three-axis magnetic sensor array. While the effects of measurement error, sensor performance and baseline distance on localization performance of such systems have been widely reported, the research about the effect of spatial design of sensor array is less presented. This paper aims to provide a spatial design method of sensor array and corresponding optimization strategy to localization based on magnetic tensor gradient to get the optimum design of the sensor array. Based on the results of simulation, magnetic localization systems constructed from the proposed array and the traditional array have been built to carry out a localization experiment. The results of experiment have verified the effectiveness of magnetic localization based on the proposed array.

The authors focus on the localization of the magnetic target based on magnetic gradient by using three-axis magnetic sensor array and combine a design method with corresponding optimization strategy to get the optimum design of the sensor array.

This paper provides an array design and optimization method for magnetic target localization based on magnetic gradient to improve the localization performance.

In this paper, the authors focus on the magnetic localization based on magnetic gradient by using three-axis magnetic sensors and study the effect of the spatial design of sensor array on localization performance.