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This aim of this article is to propose a technical solution for digital libraries to establish the information needs ontology based on a comprehensive understanding of personalized user information needs and offer an information push service by really simple syndication (RSS) in a ubiquitous computing environment.

First, the authors formalize an ontology model applicable to the ubiquitous computing environment to describe user information needs comprehensively. The information needs related to the user's research activities are regarded as the ontology, which is described with web ontology language (OWL), and thus an ontology knowledgebase is established. Second, in light of the user's explicit information needs, the digital library finds the hidden information needs from the ontology knowledgebase, and also extracts the information resources required by the user from the corresponding database and then pushes them to the user by means of RSS. Finally, users can browse through a man‐machine interface to access the information.

After these steps, an RSS information push service architecture is established based on the user information needs ontology, providing the users with dynamic, personalized and proactive information services.

The innovation of this research lies in the fact that the architecture that is put forward is helpful to improve the accuracy and integrity of information push service of digital library, and is also beneficial for the research on u‐library.

The purpose of this study is to introduce the concept of big data and provide a comprehensive overview to readers to understand big data application framework in libraries.

The authors first used the text analysis and inductive analysis method to understand the concept of big data, summarize the challenges and opportunities of applying big data in libraries and further propose the big data application framework in libraries. Then they used questionnaire survey method to collect data from librarians to assess the feasibility of applying big data application framework in libraries.

The challenges of applying big data in libraries mainly include data accuracy, data reduction and compression, data confidentiality and security and big data processing system and technology. The opportunities of applying big data in libraries mainly include enrich the library database, enhance the skills of librarians, promote interlibrary loan service and provide personalized knowledge service. Big data application framework in libraries can be considered from five dimensions: human resource, literature resource, technology support, service innovation and infrastructure construction. Most libraries think that the big data application framework is feasible and tend to apply big data application framework. The main obstacles to prevent them from applying big data application framework is the human resource and information technology level.

This research offers several implications and practical solutions for libraries to apply big data application framework.

The identification of network user relationship in Fancircle contributes to quantifying the violence index of user text, mining the internal correlation of network behaviors among users, which provides necessary data support for the construction of knowledge graph.

A correlation identification method based on sentiment analysis (CRDM-SA) is put forward by extracting user semantic information, as well as introducing violent sentiment membership. To be specific, the topic of the implementation of topology mapping in the community can be obtained based on self-built field of violent sentiment dictionary (VSD) by extracting user text information. Afterward, the violence index of the user text is calculated to quantify the fuzzy sentiment representation between the user and the topic. Finally, the multi-granularity violence association rules mining of user text is realized by constructing violence fuzzy concept lattice.

It is helpful to reveal the internal relationship of online violence under complex network environment. In that case, the sentiment dependence of users can be characterized from a granular perspective.

The membership degree of violent sentiment into user relationship recognition in Fancircle community is introduced, and a text sentiment association recognition method based on VSD is proposed. By calculating the value of violent sentiment in the user text, the annotation of violent sentiment in the topic dimension of the text is achieved, and the partial order relation between fuzzy concepts of violence under the effective confidence threshold is utilized to obtain the association relation.

As business globalisation and internet usage continue to grow, the internet‐based version of data warehouse systems (DWS) is expected to improve traditional DWS. However applying the web‐based interfaces to client‐server‐based DWS structures may cause problems such as inflexibility, inefficiency, loss of scalability, and threats to security. These arise due to the complexity of manipulation and management of heterogeneous data with various categories of decisional tasks. This paper seeks to develop a flexible mechanism by applying Extensible Markup Language as a foundation for an internet‐based DWS and to overcome the weaknesses of solely client‐server‐based DWS architecture.

For better control and security the proposed architecture utilises an embedded pull‐push mechanism to propagate the distributed decision information. This research also justifies the feasibility of the proposed mechanism by implementing a prototype, evaluating its performance, and conducting a real business case study.

The results indicate that the mechanism can not only improve DWS scalability and efficiency, but also enhance security.

The proposed architecture provides a support mechanism for business intelligence to efficiently and flexibly help companies make the right decisions in real time, grasp business opportunities and gain competitive advantage.

Push notification service (PNS) is an important approach to distribute personalized information to users timely and is getting more and more popular. However, users' privacy concerns are a major inhibiting factor in their continuance usage of PNS. This study investigates the effect of privacy protection functions provided by PNS sites in enhancing users' perceived fairness on the basis of justice theory to mitigate users' concerns of information privacy. The mechanism underlying such influence on users' continuance usage of PNS comprises privacy concern and privacy-control self-efficacy.

Four scenario-based surveys are conducted to test the proposed hypotheses. The authors test the research model with a sample of 360 participants by ANOVA and PLS.

Results show that the proposed privacy protection functions have direct positive effects on users' privacy-control self-efficacy, negative effects on privacy concern and indirectly affect their continuance usage of PNS. Furthermore, the interaction effects between two approaches have different impacts on users' privacy concern and privacy-control self-efficacy.

This study provides some suggestions and guidance for PNS providers to design effective privacy protection technologies.

As a smart service, location-based advertising (LBA) integrates advanced technologies to deliver personalized messages based on a user’s real-time geographic location and needs. However, research has shown that privacy concerns threaten the diffusion of LBA. This research investigates how privacy-related factors (i.e. LBA type, privacy self-efficacy (PSE) and consumer generation) impact consumers’ value-in-use and their intention to use LBA.

This study developed and examined an LBA value-in-use framework that integrates the role of LBA type, consumers’ PSE and consumer generation into the technology acceptance model (TAM). Data were collected through two experiments in the field with a total of 374 consumers. The proposed relationships were tested using PROCESS modeling.

The results reveal that pull (vs push) LBA causes higher value-in-use in terms of perceived usefulness and perceived ease of use, leading to greater usage intention. Further, the differences in the mediated relationship between pull- and push-LBA are larger among consumers of low PSE (vs high PSE) and Generation Z (vs other generations). The findings suggest that the consumer value-in-use brought about by LBA diminishes when using push-LBA for low PSE and Generation Z consumers.

This research is the first to integrate the privacy-related interactions of LBA type and consumer characteristics into TAM to develop a TAM-based LBA value-in-use framework. This study contributes to the literature on service value-in-use, smart services and LBA by clarifying the boundary conditions that determine the effectiveness of LBA in enhancing consumers’ value-in-use.

Over the last 50 years, increased attention for personalization paved the way for one-to-one marketing efforts, but firms struggle to deliver on this promise. The purpose of this manuscript is to provide a complete picture on personalization, develop a future research agenda and put forth concrete advice on how to move the field forward from a theoretical, methodological, contextual, and practical viewpoint.

This research follows a systematic literature review process, providing an in-depth analysis of 135 articles (covering 184 studies) to distill the (1) key building blocks and components of personalization and (2) theoretical, contextual, and methodological aspects of the studies.

This manuscript uncovers six personalization components that can be linked to two personalization building blocks: (1) learning: manner, transparency, and timing and (2) tailoring: touchpoints, level, and dynamics. For each of these components, the authors propose future research avenues to stimulate personalization research that accounts for challenges in today's data-rich environments (e.g. data privacy, dealing with new data types). A theoretical, contextual, and methodological (i.e. industry, country and personalization object) review of the selected studies leads to a set of concrete recommendations for future work: account for heterogeneity, embed theoretical perspectives, infuse methodological innovation, adopt appropriate evaluation metrics, and deal with legal/ethical challenges in data-rich environments. Finally, several managerial implications are put forth to support practitioners in their personalization efforts.

This research provides an integration of personalization research beyond existing and outdated review papers. Doing so, it accounts for the impact of new technologies and Artificial Intelligence and aims to advance the next generation of knowledge development on personalization.

The purpose of this paper is to describe UWIRS (Ubiquitous Web Information Retrieval Solution), an agent‐based Web Information Retrieval (WIR) solution designed taking into account the unique features of the World Wide Web (WWW) and the limitations of existing WIR solutions for ubiquitous environments.

UWIRS can offer recommendation services by using the Multi‐Agent Vizier Recommendation Framework (Vizier). Vizier was designed under a generic approach and therefore can provide services to information retrieval applications so these may offer product recommendations that consider several adaptation/personalization dimensions (e.g. user dimension, context, among others).

Overall, the main challenge resides on: location, retrieval, integration and presentation of information from the WWW, quickly and accurately, to satisfy a user's singular information needs.

In UWIRS, agents cooperate in order to retrieve personalized information, considering user needs, goals, preferences and contextual features. UWIRS's agents are responsible for: interpreting user input and adding adaptation information by means of a query enrichment process; identifying and selecting the appropriate data sources taking into consideration the Profile Set (composed of User, Device and Information‐Provider Profiles); executing query routing and the information retrieval process; integrating and filtering the retrieved results; and lastly, coherent presentation of quality and relevant ubiquitous information (anytime, anywhere and anyhow) that satisfies the user's particular information needs and constraints associated to his/her access device.

Financial technology (Fintech) brings about innovative financial services, such as the possibility of introducing mobile wealth management applications (apps) into consumers' lives. Despite the rapid development of such apps, few studies have focused on users' switching intentions from traditional wealth management services to mobile settings (apps).

Through a survey research method, a total of 378 responses were collected to examine the model. The partial least squares (PLS) technique was employed for data analysis.

To fill this research gap, this paper adopts a push-pull-mooring (PPM) theoretical framework to develop a model for exploring users' switching intentions. According to the empirical results, several push (i.e. perceived inconvenience), pull (i.e. transaction efficiency, perceived personalization and mobile wealth management scenarios) or mooring (i.e. product market expertise and affective commitment) factors are identified that significantly affect switching intention. This study provides theoretical contributions and practical implications for the existing wealth management literature and also offers future research directions.

This study innovatively extends the PPM framework to the traditional and mobile wealth management domains to understand users' switching intentions from offline wealth management services to mobile wealth management apps. The authors uncover several push, pull and mooring factors that are critical for determining users’ switching decisions.

The article aims to identify areas of potential research support that none of the traditional supportive actors (libraries, IT units, information units) have concerned themselves with, arguing for new tasks and roles for the academic library, specifically the special librarian.

Areas of “overload” in the digital practice of contemporary researchers are identified and then connected to various personalized digital tools. The article explores the idea that attention to new aspects of researchers information needs creates a potential for developing personalized meta-services at academic libraries.

It is possible to identify a wealth of new services that can, if put into practice, substantially redefine the relationship between academic librarians and researchers. This entails a turn from service aimed at novice users to sophisticated end-users. Such ideas also carry implications for LIS education programs and the need to build on special librarians who uphold competence in distinct knowledge domains. Two forms of domain-specific meta-services are explored: as support for collaboration and support for presentation.

It is suggested that academic libraries systematically utilize the “full cost” model of project funding in order to exhibit concrete benefits of personalized meta-services. The article holds implications for both academic libraries and for LIS educational institutions.

Personalized meta-services constitute a relatively fresh topic and have previously not been explored in connection with academic libraries.