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Social bookmarking is a system which allows users to share, organise, search and manage bookmarks of web resources. However, with the rapid growth in the production of online documents, people are facing the problem of information overload. Social bookmarking web sites offer a solution to this by providing push counts, which are counts of users’ recommendations of articles, and thus indicate the popularity and interest thereof. In this way, users can use the push counts to find popular and interesting articles. A measure of popularity-based solely on push counts, however, cannot be considered a true reflection of popularity. The paper aims to discuss these issues.

In this paper, the authors propose to derive the degree of popularity of an article by considering the reputation of the users who push the article. Moreover, the authors propose a novel personalised blog article recommendation approach which combines reputation-based group popularity with content-based filtering (CBF), for the recommendation of popular blog articles which satisfy users’ personal preferences.

The experimental results show that the proposed approach outperforms conventional CBF, item-based and user-based collaborative filtering approaches. The proposed approach considering reputation-based group popularity scores on neighbouring articles indeed can improve the recommendation quality of traditional CBF method.

The recommendation approach modifies CBF method by considering the target user's group preferences, to overcome the limitation of CBF which arises from the recommending only items similar to those the user has previously liked. Users with similar article preferences (profiles) may form a group of users with similar interests. A group's preferences may also reflect an individual's preferences. The reputation-based group preferences of the target user's group can be used to complement the target user's preferences.

To promote the success of peer-to-peer accommodation, this study examines the effects of online host–guest interaction as well as the interaction's boundary conditions of listing price and reputation on listing popularity.

Using 330,686 data collected from Airbnb in the United States of America, the authors provide empirical evidence to answer whether social-oriented self-presentation and response rate influence listing popularity from the perspective of social exchange theory (SET). In addition, the authors investigate how these two kinds of online host–guest interactions work with listing price and reputation to influence listing popularity.

The results reveal the positive association between online host–guest interaction and listing popularity. Notably, the authors find that listing price strengthens but listing reputation weakens the positive effects of online host–guest interactions on listing popularity in peer-to-peer accommodation.

This study is the first attempt to adopt SET to explain the importance of online host–guest interactions in influencing listing popularity as well as examine the moderating role of listing price and reputation on the above relationship.

In online exchange platforms' sponsored search advertising, the array of product quality signals within a keyword search results list plays a crucial role in shaping buyers' purchasing decisions. This research seeks to explore the impact of various quality signals – namely, ranking position, seller reputation and product price – on ad clicks. Additionally, it examines the role of keyword attributes, such as specificity and popularity, in modulating the effects of these quality signals on advertising clicks.

A total of 5,763 effective data points were collected from a leading B2B electronic platform company, and we employed negative binomial regression with Heckman correction methods to test the hypotheses.

The results indicate that in online exchange platforms, search ad clicks are significantly and positively affected by displayed signals such as ranking position, seller reputation and product price information. Notably, a U-shaped relationship emerges between product price and ad clicks. Furthermore, keyword specificity and popularity distinctly moderate the impact of these displayed signals on ad clicks within online exchange platforms.

This paper addresses the gap in existing research on search advertising by methodically analyzing the impact of various signals displayed in search results and how keyword attributes moderate ad clicks, all through a signaling theory lens.

Social media platforms play a key role in information propagation and there is a need to study the same. This study aims to explore the impact of the number of close communities (represented by cliques), the size of these close communities and its impact on information virality.

This study identified 6,786 users from over 11 million tweets for analysis using sentiment mining and network science methods. Inferential analysis has also been established by introducing multiple regression analysis and path analysis.

Sentiments of content did not have a significant impact on the information virality. However, there exists a stagewise development relationship between communities of close friends, user reputation and information propagation through virality.

This paper contributes to the theory by introducing a stagewise progression model for influencers to manage and develop their social networks.

There is a gap in the existing literature on the role of the number and size of cliques on information propagation and virality. This study attempts to address this gap.

Waiting time, as an important predictor of queue abandonment and patient satisfaction, is important for resource utilization and patient experience management. Medical institutions have given top priority to reforming the appointment system for many years; however, whether the increased information transparency brought about by the appointment scheduling mechanism could improve patient waiting time is not well understood. In this study, the authors examine the effects of information transparency in reducing patient waiting time from an uncertainty perspective.

Leveraging a quasi-natural experiment in a tertiary academic hospital, the authors analyze over one million observational patient visit records and design the propensity score matching plus the difference in difference (PSM-DID) model and hierarchical linear modeling (HLM) to address this issue.

The authors confirm that, on average, improved information transparency significantly reduces the waiting time for patients by approximately 6.43 min, a 4.90% reduction. The authors identify three types of uncertainties (resource, process and outcome uncertainty) in the patient visit process that affect patients' waiting time. Moreover, information transparency moderates the relationship between three sources of uncertainties and waiting time.

The authors’ work not only provides important theoretical explanations for the patient-level factors of in-clinic waiting time and the reasons for information technology (IT)-enabled appointment scheduling by time slot (ITASS) to shorten patient waiting time and improve patient experience but also provides potential solutions for further exploration of measures to reduce patient waiting time.

Customer-intensive services refer to the service that a provider needs to invest in customers with high patience and experience. Within a certain rate range, the slower service rate and the longer service time, the higher customer’s utility; however, this may cause queue congestion. And the advertising of service provider will affect the revenue. The purpose of this paper is to investigate the effects of advertising on the optimal price, service rate and the optimal revenue of such service provider at different development stages.

This paper investigates the service strategies of service provider based on advertising effects. The authors first divide service provider into insufficient customers or sufficient customers according to the development stage, then analyze the impact of advertising at different stages. The authors focus on the formulation of the optimal price, service rate and the optimal revenue of service provider at different stages.

This paper finds that in the insufficient customers stage, the service provider’s strategy of “small profits but quick turnover” is conducive to quickly accumulating customers. With the development of service provider, the advertising indirectly increases the revenue of service provider by maintaining popularity. The result also shows that with the development of service provider, the initiative of such service market has gradually been mastered by service provider, from “buyer market” to “seller market.”

The finding provides an alternative explanation for the impact of advertising on service provider’s optimal strategies; it also solves the settings of service price and rate of customer-intensive service provider at different development stages. This study is essential to create the optimal revenue and solve supply–demand conflicts (such as doctor–patient conflict) between service provider and customers.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

This paper aims to propose an integrated supplier selection, order allocation, transportation planning model, along with investment planning for corporate social responsibility (CSR), over a given multi-period horizon under uncertainty. Furthermore, a customer’s behavior to pay more money for items with CSR attributes is considered in the total market demand.

The objective functions, i.e. social value of purchasing, total profit (TP), total delivery lead-time, total air pollution, total water pollution and total energy consumption with regard to a number of constraints are jointly considered in a multi-product system. It is worth noting that operational- and sustainable-related parameters are usually vague and imprecise in this area. Therefore, this paper develops a new fuzzy multi-objective optimization model to capture this inherent fuzziness in critical data.

Through the numerical examples in the textile industry, the application of the model and usefulness of solution procedures are carried out. The numerical results obtained from the proposed approach indicate the efficiency of the solution algorithm in different instances. Moreover, the authors observe that social investment of the buyer, to stimulate market demand, can affect the TP and also involve the total contribution of suppliers in social responsibility.

This research work concentrates on providing a procurement and inventory model through the lens of sustainability to enable textile supply chain managers and related industries to apply the approach to their inventory control and supply management. Totally, the proposed methodology could be applied by many fabric buyers of textile industry tackling purchasing issues and attempting to perfect understanding of social supply chains.

With the advent of technology and internet banking, the role and value of bank’s websites have increased. Additionally, the Islamic banking boom has also increased the role of Shariah-based banking in the market. But neither web-based information nor Shariah board members have been investigated for their possible effects on the branding of Islamic banks. Against this backdrop, this study aims to explore web-based information and Shariah board as a source of branding of Islamic financial institutions (IFIs).

An interpretivism-based thematic inquiry is carried out through semi-structured interviews of 22 customers of Islamic banks.

The findings of the study highlighted the fact that customers’ perceived web-based information is in line with the Shariah objectives but showed low level of trust on that information. They assumed that the practices are not consistent with this information. Moreover, the Shariah board members were considered as brand ambassadors, and customers valued board members more than the Shariah board and Islamic bank itself. Findings further highlight the more knowledge customers have about the Shariah board members (experience, qualification, achievements, etc.) the greater is the impact on the branding of the IFIs.

This study offers a novel perspective by considering the value of web-based information and Shariah board on branding of Islamic banks. As there is no such study available in literature, up to the best of researchers' knowledge, the qualitative inquiry may suffice the study objectives and research questions.

This study aims to sketch a bibliometric portrait of the International Journal of Innovation Science (IJIS) and attempts to evaluate its publication patterns from 2011 to 2020 by unfolding the key aspects of its publication trends for the audience of the journal and scholars of bibliometric studies as well.

This study analyzes papers published in the IJIS from 2011 to 2020 by using the required bibliometric measures to analyze the key aspects of the publishing trends of IJIS.

This study finds that a total of 487 authors published 271 articles in IJIS during 2011–2020. The USA leads the table with 89 papers followed by India (29 papers) and China (26 papers). The degree of collaboration in IJIS ranged from 0.36 to 0.94. Moreover, this study finds that the keyword “design/methodology/approach” is the central theme of research in IJIS around which all other keywords revolve.

This study focuses on the publication patterns of the IJIS over a period of ten years. Patterns of research output in 271 publications are comprehended and analyzed. For making a ten-year bibliometric study, the papers published before 2011 were excluded from the purview of research.

Readers of the IJIS, teachers and research scholars interested in bibliometric studies can benefit from insights into the scholarly papers published in IJIS from 2011 to 2020.

This study would provide the readers of IJIS to ascertain significant contributions, top cited papers, the most prolific authors, geographical distribution of papers, keyword co-occurrence and bibliographic coupling.