Search results

The purpose of this paper is to identify the key determinants of the information value of enterprises’ micro-blogs, drawing on the consumer’s perspective. This paper examines the effects of such information value on consumers’ purchase intention through the building of online brand equity. The paper also investigates how perceived usefulness intervenes in the relationship between micro-blog information value and consumer purchase intention.

The proposed research model is examined empirically using a survey of 315 users of the Sina micro-blog. The statistical analysis applies a method based on variance using partial least squares.

The results show that online retailers’ micro-blog posts, which are characterized by informativeness and persuasiveness as perceived by customers, positively impact online retailers’ brand equity, which in turn influences consumer purchase intention. In addition, perceived information usefulness is found to be an important contextual factor that moderates the relationship between perceived persuasiveness and online retailer brand equity.

This work adds significance to the literature by extending the research on micro-blog marketing and also provides practical recommendations for online retailers on the operation of micro-blogs.

This paper aims to investigate the magnetostrictive phenomenon in a single electrical steel sheet, which may cause vibration and noise in the cores of transformers and induction motors. A measurement system of magnetostriction is created and the principal strain of magnetostriction is modeled. Furthermore, the magnetostriction property along arbitrary alternating magnetization directions is modeled.

A measurement system with a triaxial strain gauge is developed to obtain the magnetostrictive waveform, and the principal strain is computed in terms of the in-plane strain formula. A three-layer feed-forward neural network model is proposed to model the measured magnetostriction property of the electrical steel sheet.

The principal strain of magnetostriction of the non-oriented electrical steel has strong anisotropy. The proposed estimation model can be effectively used to model the anisotropic magnetostriction with an acceptable prediction time.

This paper develops the neural network combined with fast Fourier transform (FFT) to model the principal strain property of magnetostriction under alternating magnetizations, and its validation has been verified.

This purpose of this paper is to present a new approach of solving quantum control problem.

State‐transition‐matrix (STM) is used to solute quantum control problem.

The paper obtains the matrix representation for wave function, normalization, and some other quantum operators, and then gives the possible methods to establish the STM model and solve it.

Based on this, many tools of the widely used control theory can be adopted to denote or analyze the quantum system.

The purpose of this paper is to show how a quartz crystal microbalance modified with poly (epichlorohydrin) (PECH) is fabricated and used for detection of acetone vapor using a spin‐coating method.

Measurements are based on the frequency shifts due to the adsorption of acetone vapor on the surface of the modified electrodes. A first‐order linear time‐invariant (LTI) system model is used to simulate the sensor response.

It is found that frequency shifts are linear to the concentrations of analyte, and cycle test examination shows good repeatability. The sensitivity to acetone vapor is better than other volatile compounds. A good match result is obtained with the LTI system model.

The device performance opens a potential way for analyzing acetone vapor.

This study assesses the impacts of the social institutions of a transitional economy on its market by examining how China’s political, economic and cultural institutions influence consumers’ sentiment and their purchase planning behaviors. We propose and empirically validate a four‐factor model of consumer sentiment that captures the impacts of these powerful social institutions. The validity of the model was supported with data from a multi‐level stratified survey that involved 9 cities and 3,960 consumers across a number of product categories. Our findings confirm the salience of social institutions in affecting consumers’ sentiment as well as their consumption behaviors in China.

The vast majority of evidence about knowledge management (KM) is based on studies within a mass‐producing context and at intra‐organizational level. Little has been reported in the complex products and systems (CoPS) literature about KM processes across firm boundaries. To contribute to this gap, this paper reviews the literature of CoPS, inter‐organizational collaboration and KM, discusses some challenges of inter‐organization KM faced by CoPS manufacturers, and explores a research framework which is helpful to provide a preliminary understanding of inter‐organizational KM within a CoPS context.

Literature review and research experience are presented.

The study has identified some challenges faced by CoPS manufacturers when they try to manage knowledge from an innovative network, and developed a framework extending KM processes into an inter‐firm collaborative network for CoPS development. Both, project level collaboration and firm level linkages need to be taken into consideration when attempting to implement KM at inter‐organizational level. Knowledge acquisition from network, knowledge integration, and knowledge sharing in the network are the main inter‐organizational KM activities in a CoPS context.

As KM based on inter‐organizational collaboration has received little attention in prior studies, especially in CoPS conditions, this study is an exploratory discussion of KM issues within a CoPS context, combining the cross‐school theories of inter‐organizational linkages, KM and CoPS innovation. This paper tries to account for knowledge‐related activities involved in CoPS development, identifying some challenges in CoPS innovation.

This paper aims to explore and analyze how a focal firm, coming from emerging economies, of the multinational technology standard alliance ecosystem engages different actors of the alliance in value co-creation practice, contributing to product collaborative innovation and reciprocal standards cooperation.

Based on in-depth interviews, primary company, and secondary documents, this paper conducts an exploratory single case study of TechAlpha to investigate the practice of value co-creation in the multinational technology standard alliance (MTSA).

Based on the extended resource-based view (ERBV), this paper finds that in the MTSA ecosystem, actor engagement sets the anchor for the focal firm in the MTSA to dominate the resource interaction, achieving a greater interaction through goal co-discussion, standard co-construction and achievement co-sharing. Resource interaction is composed of standard resource identification, standard resource sharing, and standard resource alignment, putting a high value on the practice of value co-creation. Value co-creation dominated by the focal firm of the MTSA is embodied in the synergy of actor engagement and resource interaction.

This paper contributes to the relevant literature by illustrating how the focal firm coming from emerging economies of the MTSA enables value co-creation through adjusting the situation of actor engagement and exerting its standards resource interaction. This paper also advances the process of acquisition, integration, and reconstruction of heterogeneous resources throughout the MTSA by offering a new supplementary perspective and new evidence from a Chinese firm.

The purpose of this paper is to analyze the differential effects of two external search strategies on radical innovation (RI) and incremental innovation (II) and explore the mediating role of knowledge integration capability (KIC).

The paper is based on the data collected from a sample of 241 firms from Chinese electronic information industry. The author conducted a hierarchical regression analysis using SPSS and PROCESS to test the proposed hypotheses.

The results showed that both external search breadth and depth have positive effects on RI/II performance. The author also found that the effect of search breadth on RI is greater than that on II, and the effect of search depth on RI is less than that on II. Moreover, the author discovered that KIC fully or partially mediates the relationship between external search strategies and RI/II.

The paper provides a finer grained understanding concerning the difference in the impacts of the two external search strategies on RI/II performance. The paper also adds to the existing literature by explaining the path in which external knowledge search influences RI/II through the mediation effect of KIC.

The purpose of this paper is to explore humanities teachers’ perceptions of patriotism in Singapore by addressing two questions. First, what are teachers’ understandings of patriotism? Second, what are teachers’ attitudes toward patriotism as a quality of good citizenship?

The qualitative case study approach was used, with semi-structured interviews and classroom observations as data sources. The participants were four teachers from diverse backgrounds with distinct perceptions of patriotism. Data analysis methods included writing teacher profiles and thematic coding.

Teachers were generally positive toward patriotism and understood it in four ways: cosmopolitan, nationalistic, social-movement and person oriented. These themes were not mutually exclusive but distributed across the participants in varying extents. These findings show that patriotism is susceptible to individual meaning-making, and there are different scales and expressions of patriotism.

The results from this small case study cannot be generalized. However, owing to globalization, it is likely that alternative ways of understanding patriotism might become more widespread and salient in citizenship education. Hence, the authors recommend that more studies be conducted on larger samples and using other methods.

This study goes in-depth into a case where teachers had positive feelings toward patriotism, and it draws on the context of Singapore to understand how and why this is so. It also revealed conceptions of patriotism that differ from the more common constructs in the educational literature, suggesting that people from post-colonial countries with different histories, might conceive of patriotism differently from others.

The majority of existing studies about named entity recognition (NER) concentrate on the prediction enhancement of deep neural network (DNN)-based models themselves, but the issues about the scarcity of training corpus and the difficulty of annotation quality control are not fully solved, especially for Chinese ancient corpora. Therefore, designing a new integrated solution for Chinese historical NER, including automatic entity extraction and man-machine cooperative annotation, is quite valuable for improving the effectiveness of Chinese historical NER and fostering the development of low-resource information extraction.

The research provides a systematic approach for Chinese historical NER with a three-stage framework. In addition to the stage of basic preprocessing, the authors create, retrain and yield a high-performance NER model only using limited labeled resources during the stage of augmented deep active learning (ADAL), which entails three steps—DNN-based NER modeling, hybrid pool-based sampling (HPS) based on the active learning (AL), and NER-oriented data augmentation (DA). ADAL is thought to have the capacity to maintain the performance of DNN as high as possible under the few-shot constraint. Then, to realize machine-aided quality control in crowdsourcing settings, the authors design a stage of globally-optimized automatic label consolidation (GALC). The core of GALC is a newly-designed label consolidation model called simulated annealing-based automatic label aggregation (“SA-ALC”), which incorporates the factors of worker reliability and global label estimation. The model can assure the annotation quality of those data from a crowdsourcing annotation system.

Extensive experiments on two types of Chinese classical historical datasets show that the authors’ solution can effectively reduce the corpus dependency of a DNN-based NER model and alleviate the problem of label quality. Moreover, the results also show the superior performance of the authors’ pipeline approaches (i.e. HPS + DA and SA-ALC) compared to equivalent baselines in each stage.

The study sheds new light on the automatic extraction of Chinese historical entities in an all-technological-process integration. The solution is helpful to effectively reducing the annotation cost and controlling the labeling quality for the NER task. It can be further applied to similar tasks of information extraction and other low-resource fields in theoretical and practical ways.