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Online question-and-answer (Q&A) communities serve as important channels for knowledge diffusion. The purpose of this study is to investigate the dynamic development process of online knowledge systems and explore the final or progressive state of system development. By measuring the nonlinear characteristics of knowledge systems from the perspective of complexity science, the authors aim to enrich the perspective and method of the research on the dynamics of knowledge systems, and to deeply understand the behavior rules of knowledge systems.

The authors collected data from the programming-related Q&A site Stack Overflow for a ten-year period (2008–2017) and included 48,373 tags in the analyses. The number of tags is taken as the time series, the correlation dimension and the maximum Lyapunov index are used to examine the chaos of the system and the Volterra series multistep forecast method is used to predict the system state.

There are strange attractors in the system, the whole system is complex but bounded and its evolution is bound to approach a relatively stable range. Empirical analyses indicate that chaos exists in the process of knowledge sharing in this social labeling system, and the period of change over time is about one week.

This study contributes to revealing the evolutionary cycle of knowledge stock in online knowledge systems and further indicates how this dynamic evolution can help in the setting of platform mechanics and resource inputs.

Consumers are increasingly choosing social media over other channels and mechanisms for grievance redressal. However, not all social media grievances elicit a response from businesses. Hence, in this research the authors aim to explore the effect of the complainant's social characteristics and the complaint's social and content characteristics on the likelihood of receiving a response to a grievance from the business on social media.

The authors build a conceptual model and then empirically test it to explore the effect of the complainant's characteristics and the complaint's characteristics on the likelihood of response from a business on social media. The authors use data of consumer grievances received by an Indian airline operator on Twitter during two time periods – the first corresponding to lockdown during Covid-19 pandemic, and the second corresponding to the resumption of business as usual following these lockdowns. The authors use logistic regression and the hazard rate model to model the likelihood of response and the response delay, respectively, for social media customer grievances.

Complainants with high social influence are not more likely to get a response for their grievances on social media. While tagging other individuals and business accounts in a social media complaint has negative effect on the likelihood of business response in both the time periods, the effect of tagging regulatory bodies on the likelihood of response was negative only in the Covid-19 lockdown period. The readability and valence of a complaint were found to positively affect the likelihood of response to a social media grievance. However, the effect of valence was significant only in lockdown period.

This research offers insights on what elicits responses from a service provider to consumers' grievances on social media platforms. The extant literature is a plenty on how firms should be engaging consumers on online media and how online communities should be built, but scanty on grievance redressal on social media. This research is, therefore, likely to be useful to service providers who are inclined to improve their grievance handling mechanisms, as well as, to regulatory authorities and ombudsmen.

The purpose is to offer a discussion of how we can conceive of the organization of knowledge in digital culture and its changing nature. The article proposes to view of it as both a decentered (communicative) and centered (analytical gaze).

This study involves comparative analysis and discussion.

The analysis and discussion argue for the two positions of the organization of knowledge and point to how and what we can understand about features of digital culture’s collection practices.

The originality of this article is the conceptualization of the organization of knowledge as both a decentered and centered practice in digital culture, from which is developed a particular knowledge organization perspective on social reality.

This study aimed to investigate how the enrichment of medical documents' index terms by their comments improves the relevance and novelty of the top-ranked results retrieved by an NLP system.

A semi-experimental pre-test and post-test research was designed to compare NLP-based indexes before and after being expanded by the comment terms. The experiments were conducted on a test collection of 13,957 documents commented by F1000-Prime reviewers. They were indexed at title, abstract, body and full-text levels. In total, 100 seed documents were randomly selected and served as queries. The textual similarity of the documents and queries was calculated using Lucene-more-like-this function and evaluated by the semantic similarity of their MeSH. The results novelty was measured using maximal marginal relevance and evaluated by their MeSH novelties. Normalized discounted cumulative gain was used to compare the basic and expanded indexes' precisions at 10, 20 and 50 top ranks.

The relevance and novelty of the results ranked at the top precision points was improved after expanding the indexes by the comment terms. The finding implies that meta-texts are effective in representing their mother documents, by adding dynamic elements to their rather static contents. It also provides further evidence about the merits of the application of social intelligence and collective wisdom reflected in the actions and reactions of users in tackling the challenges faced by NLP-based systems.

This is the first study to confirm that social comments on scientific papers improve the performance of information systems in terms of relevance and novelty.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2022-0283.

In the era of mobile internet, the social Q&A community has built a large-scale and complex knowledge label network through its internal knowledge units, and the scale and structure of the network have changed over time. By analysing the structural characteristics and evolution rules of knowledge label networks, the main purpose of this study is to understand the internal mechanisms of the replacement of old and new knowledge and the expansion of knowledge element boundaries, so as to explore the realization path of knowledge management in the new era from the perspective of complex networks.

This paper uses distributed crawlers to capture 419,349 samples from the Zhihu platform. Each sample contains 33 characteristic dimensions, and the natural year is used as the sliding window to divide the whole. In this study, the global knowledge label network and 11 local knowledge label networks are first constructed. Then, the degree distribution analysis and central node exploration of the knowledge label network are carried out using the complex network method. Finally, the average shortest path and average clustering coefficient of the network are analysed by the time series method, and the ARIMA model is used to predict the evolution of the correlation coefficient.

The research results show that the dissimilation degree of the degree distribution of the knowledge label network has gradually decreased from 2011 to 2021, and the attention of users in the knowledge community has shown a trend of distraction and diversification over time. With the expansion of the scale of the knowledge label network and the transformation to an information network, the network sparsity is becoming more and more obvious, and the knowledge granularity of the Q&A community is being refined and diversified. The prediction of the correlation coefficient of the knowledge label network by the ARIMA model shows that the connection between the labels is lacking diversity and the opinion strengthening phenomenon tends to strengthen, which is more likely to form the “echo chamber effect”, resulting in mutual isolation and even opposition between different circles. The Q&A community is about to enter a mature stage, and the corresponding status of each label has been finalized. The future development trend of label networks will be reflected in the substitution between labels, and the specific structure will not change significantly.

The Q&A community model is the trend in Web 2.0 community development. This study proves the effectiveness of complex networks and time series prediction methods in knowledge label network mining in the Q&A community.

Considering the emergence of e-commerce platforms and their integration into marketing channels, this paper aims to investigate how artificial intelligence (AI) resources – both technological and human – possessed by e-commerce platforms can enhance their channel power by acquiring market-based assets (relational and intellectual).

Based on resource-based theory and resource orchestration theory, the authors developed a framework tested using survey data gathered from the sellers, which incorporated six key variables: the e-commerce platform’s AI technology resources and human resources, rational and intellectual market-based assets, intraplatform competition and channel power. The analyses are performed using the regression analysis technique.

The empirical findings indicate that both technological and human AI resources are crucial in building channel power. In addition, market-based assets serve as a mediator in this relationship, while intraplatform competition moderates the effect of intellectual market-based assets on channel power negatively.

This study contributes to the existing literature by exploring how e-commerce platforms’ AI resources affect their channel power. The results offer valuable guidance to managers and researchers on optimizing AI resources to improve channel power.

The aim of this paper is to identify the main challenges and limitations of current business process management (BPM) development directions noticed by researchers, as well as to define the areas of the main BPM paradigm shifts necessary for the BPM of tomorrow to meet the challenges posed by Industry 4.0 and the emerging Industry 5.0. This is extremely important from the perspective of eliminating the existing broadening gap between the considerations of academic researchers and the needs of business itself.

A systematic literature review was conducted on the basis of the resources of two digital databases: Web of Science (WoS) and SCOPUS. Based on the PRISMA protocol, the authors selected 29 papers published in the last decade that diagnosed the challenges and limitations of modern BPM and contained recommendations for its future development. The content of the articles was analyzed within four BPM core areas.

The authors of the selected articles most commonly point to the areas of organization (21 articles) and methods and information technology (IT) (22 articles) in the context of the challenges and limitations of current BPM and the directions of recommended future BPM development. This points to the prevalence among researchers of the perspective of Industry 4.0 – or focus on technological solutions and raising process efficiency, with the full exclusion or only the partial signalization of the influence of implementing new technologies on the stakeholders and in particular – employees, their roles and competencies – the key aspects of Industry 5.0.

The proposal of BPM future development directions requires the extension of the BPM paradigm, taking into account its holistic nature, especially unpredictable, knowledge-intensive business processes requiring dynamic management, the need to integrate BPM with knowledge management (KM) and the requirements of Industry 5.0 in terms of organizational culture. The limitation is that the study is based on only two databases: WoS and SCOPUS and that the search has been narrowed down to publications in English only.

The proposal of BPM future development directions also requires the extension of the BPM paradigm, taking into account the specific challenges and limitations that managers encounter on a daily basis. The presented summaries of the challenges and limitations resulting from the literature review are accompanied by recommendations that are primarily dedicated to practitioners.

The article indicates the area people and culture as one of the four core areas of BPM. It emphasizes the necessity to account to a greater degree for the influence of people, their knowledge, experience and engagement, as well as formal and informal communication, without which it is impossible to use the creativity, innovativeness and dynamism of the individual and the communities to create value in the course of business process execution.

To the authors' knowledge, this is the first systematic review of the literature on the limitations of modern BPM and its future in the context of Industry 4.0 and Industry 5.0.

The purpose of this study is to examine research on academic libraries and the social web published from July 1, 2019, to June 30, 2023.

The article search and filtering procedures mirrored those of Choi and Harper (2020) and Carlsson (2015), resulting in a total sample size of 93 articles. These articles underwent examination based on the same eight variables (i.e. journal outlet, research theme, publication year, social web type, method, keyword, study participant type and study country) as employed by Choi and Harper (2020) and Carlsson (2015), with the addition of two new variables (i.e. research purpose and the impact of COVID-19).

The research article volume has consistently maintained a stable trend. A notable difference from Choi and Harper (2020) and Carlsson (2015) is the rise of “user perspectives” as the second most prevalent theme. Unlike Choi and Harper (2020), the “survey” method is predominant. Many research purposes, excluding “marketing and promotion,” lack attention. Additionally, there’s a dearth of studies on the impact of COVID-19.

The findings from the study not only offer a snapshot of the current research landscape on academic libraries and their engagement with the social web but also offer insights for future scholarly endeavors.

There is a limited effort in exploring the recent literature regarding the role of the social web in academic libraries. This study serves as a valuable guide for contributing to this dynamic research stream and provides various up-to-date implications.

It is widely known that fast-fashion retailers are struggling to keep up with consumer attention for quick responses within the fashion industry. With the advance of Internet and e-commerce, consumers prefer to purchase online. Online platform information has become an essential source for exploring consumer attention. However, there is often a mismatch between the information provided by retailers and the feedback received from consumers, leading to an imbalance between the supply side and demand side of online information. The purpose of this study is therefore to provide a unified approach to discover consumer attention from the design topic aspect by revealing the information imbalance between supply side and demand side.

To address the issue of online information imbalance and discover consumer attention, this study proposed an approach that focuses on the design topic perspective. The design topic is a collection of design elements that represent a clothing-design feature more comprehensively and accurately compared to a single design element. The proposed approach begins with generating design topics through topic modeling based on online information provided by retailers on e-commerce platforms. Two indicators, influence degree and attention degree, are then used to quantify the intensity of supply information and consumer attention related to design topics. Finally, design topic strategy diagrams are constructed to reveal information imbalance and discover consumer attention.

The experimental case demonstrates the existence of information imbalance, indicating that the intensity of supply information and consumer attention from the perspective of design topics is not uniform, although both follow the Pareto principle. The results of consumer attention distribution with heavy power-law tails are consistent with current research findings. This further demonstrates that the proposed approach is capable of discovering consumer attention in the design topic strategy diagrams.

The issue of information imbalance between retailers and consumers poses a challenge in keeping up with customer attention. The proposed approach offers a practical solution by visually identifying the symptoms of information imbalance and discovering consumer attention through design topic strategy diagrams. This approach provides fast-fashion retailers with a valuable reference to seize market opportunities, improve product design and adjust marketing or management strategies.

This study proposes a novel approach to disclose the issue of information imbalance between supply side and demand side and therefore to discover consumer attention from the perspective of design topics. In addition, guidelines for applying the proposed approach for fast-fashion marketing and management are presented.

The integration of social media and e-commerce has resulted in a rising phenomenon among individual content providers (ICPs), who used to offer free content, to provide consumers with paid content, such as online courses, Q&As or consultations. Despite the prevalence of ICPs’ content monetization, empirical research has rarely studied its underlying mechanism. This paper examines how the characteristics of free content contributed by ICPs on social media platforms influence their paid content sales, focusing on the perspective of human brand.

The empirical setting is an online knowledge exchange platform, where users are allowed to provide free content (e.g. answers) on the social media platform and launch paid content (e.g. lectures) on the e-commerce platform. A machine learning technique is employed to construct measures for the characteristics of free content, and fixed-effects estimation is presented to confirm which factors have a significant influence on the sales of paid content.

The empirical results show that the quality, diversity and expertness of free content have a significant positive impact on the sales of the ICP-paid content, with the brand popularity of ICP playing a mediating role.

This study is the first attempt to demystify the relationship between content contribution and ICPs’ content monetization from the perspective of human brand. The findings validate the effectiveness of the “Selling by Contribution” strategy and provide valuable insights for ICPs and social media platforms.