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This study aims to analyze the distribution of novelty among scholarly papers in the field of library and information science (LIS) in China. Specifically, this study explores the distribution of novelty of papers in various journals, research topics and different periods. It is possible to understand the characteristics of LIS research in China and what factors have influenced it.

This paper collects articles published in Chinese library science journals indexed by the Chinese Social Sciences Citation Index from 2000 to 2022. The BERTopic model is used based on abstracts of the papers and to obtain the topic of each paper. Based on the combination innovation theory of reference pairs cited by focal papers, novelty scores of all papers are calculated. Next, this paper analyzes the novelty of papers under different topics. Finally, this paper analyzes the differences in author collaboration patterns across various topics, aiming to explain how these differences relate to the novelty of papers from a collaborative perspective.

This study shows that archival research topics have lower novelty than papers on journal evaluation and patent technology in Chinese LIS. Research papers in this field are gradually becoming more novel over time. Papers on different topics and with varying degrees of novelty exhibit distinct author collaboration patterns, with low-novelty topics more frequently featuring solo authorship, while high-novelty topics tend to involve a higher percentage of inter-institutional collaboration.

This study investigates the novelty characteristics of research papers on different topics in the field of LIS in China. The authors’ contribution includes visualizing research hotspots and trends in the field and analyzing authors’ collaboration patterns at the level of research topics, thereby providing new perspectives on the factors affecting the novelty of these papers.

The purpose of this Real Impact Research Article is to empirically explore one of the most controversial and elusive concepts in knowledge management research – practical wisdom. It develops a 10-dimensional practical wisdom construct and tests it within the nomological network of counterproductive and productive knowledge behavior.

A survey instrument was created based on the extant literature. A model was developed and tested by means of Partial Least Squares with data obtained from 200 experienced employees recruited from CloudResearch Connect crowdsourcing platform.

Practical wisdom is a multidimensional construct that may be operationalized and measured like other well-established knowledge management concepts. Practical wisdom guides employee counterproductive and productive knowledge behavior: it suppresses knowledge sabotage and knowledge hiding (whether general, evasive, playing dumb, rationalized or bullying) and promotes knowledge sharing. While all proposed dimensions contribute to employee practical wisdom, particularly salient are subject matter expertise, moral purpose in decision-making, self-reflection in the workplace and external reflection in the workplace. Unexpectedly, practical wisdom facilitates knowledge hoarding instead of reducing it.

Managers should realize that possessing practical wisdom is not limited to a group of select, high-level executives. Organizations may administer the practical wisdom questionnaire presented in this study to their workers to identify those who score the lowest, and invest in employee training programs that focus on the development of those attributes pertaining to the practical wisdom dimensions.

The concept of practical wisdom is a controversial topic that has both detractors and supporters. To the best of the author’s knowledge, this is the first large-scale empirical study of practical wisdom in the knowledge management domain.

Over the past two decades, the study of team resilience has evolved from focusing primarily on team performance to recognizing its importance in various aspects of team functioning, including psychological health, teamwork, and overall Well-Being. This evolution underscores the need for a broader, more inclusive understanding of team resilience, advocating for a shift from a narrow performance-centric view to a holistic perspective that encompasses the multifaceted impact of resilience on teams.

In advocating for this holistic perspective, this chapter reviews the extant literature, highlighting that resilience is not merely about sustaining performance but also about fostering a supportive, adaptive, and psychologically safe environment for team members. Significant areas for further exploration, including the nuanced nature of adversities teams face, the processes underpinning resilient behaviors, and the broad spectrum of outcomes resilience can influence beyond task performance are also discussed.

The chapter serves as a call to action for a more inclusive examination of how resilience manifests and benefits teams in organizational settings. The proposed shift in perspective aims to deepen understanding of team resilience, promoting strategies for building resilient teams that thrive not only in performance but in all aspects of their functioning.

Organizational scholars studying compensation often place an emphasis on certain employee groups (e.g., executives). Missing from this discussion is research on the compensation systems for low-wage jobs. In this review, the authors argue that workers in low-wage jobs represent a unique employment group in their understanding of rent allocation in organizations. The authors address the design of compensation strategies in organizations that lead to different outcomes for workers in low-wage jobs versus other workers. Drawing on and integrating human resource management (HRM), inequality, and worker literatures with compensation literature, the authors describe and explain compensation systems for low-wage work. The authors start by examining workers in low-wage work to identify aspects of these workers’ jobs and lives that can influence their health, performance, and other organizationally relevant outcomes. Next, the authors explore the compensation systems common for this type of work, building on the compensation literature, by identifying the low-wage work compensation designs, proposing the likely explanations for why organizations craft these designs, and describing the worker and organizational outcomes of these designs. The authors conclude with suggestions for future research in this growing field and explore how organizations may benefit by rethinking their approach to compensation for low-wage work. In sum, the authors hope that this review will be a foundational work for those interested in investigating organizational compensation issues at the intersection of inequality and worker and organizational outcomes.

Across many high-stakes contexts, teams influence their members’ physical and psychological Well-Being. For example, teams can provide social support and backup behaviors to reduce demands on team members. On the contrary, teams engaged in conflict or other deleterious processes can serve as a source of stress for their members. Despite these potential impacts, existing research primarily focuses on the impact of teamwork on team-level, rather than individual-level outcomes. This chapter argues that teams play an important role in members’ Well-Being, synthesizing existing research on the topic and focusing on synthesizing research that suggests teams play an important and overlooked role in members’ Well-Being, and providing recommendations for future research in this domain.

The practical need for understanding and improving team resilience has increased, and more research is needed to provide an evidence-base for guiding organizational practices and policies. In this chapter, the authors highlight what we see as critical challenges and opportunities for advancing the science of team resilience. We focus on conceptual and methodological challenges involved in conducting field-based research on team resilience, as the authors believe field-based research is a particularly critical approach for advancing the science of team resilience. The authors first provide a brief review of recent theoretical work in defining team resilience. Then the authors describe key challenges that must be managed in field studies seeking to refine and capitalize on this critical area of research to provide solutions capable of supporting individual, team, and organizational outcomes. These challenges include defining trajectories of resilient team performance, understanding the consequences of repeated episodes of team resilience, formal specifications of events precipitating resilient team performance, measuring the event appraisal and communication process, and adopting measurement methods with high temporal resolution. Finally, the authors provide directions for future research to address these gaps.

In this paper, community identification has been considered as the most critical task of social network analysis. The purpose of this paper is to organize the nodes of a given network graph into distinct clusters or known communities. These clusters will therefore form the different communities available within the social network graph.

To date, numerous methods have been developed to detect communities in social networks through graph clustering techniques. The k-means algorithm stands out as one of the most well-known graph clustering algorithms, celebrated for its straightforward implementation and rapid processing. However, it has a serious drawback because it is insensitive to initial conditions and always settles on local optima rather than finding the global optimum. More recently, clustering algorithms that use a reciprocal KNN (k-nearest neighbors) graph have been used for data clustering. It skillfully overcomes many major shortcomings of k-means algorithms, especially about the selection of the initial centers of clusters. However, it does face its own challenge: sensitivity to the choice of the neighborhood size parameter k, which is crucial for selecting the nearest neighbors during the clustering process. In this design, the Jaya optimization method is used to select the K parameter in the KNN method.

The experiment on real-world network data results show that the proposed approach significantly improves the accuracy of methods in community detection in social networks. On the other hand, it seems to offer some potential for discovering a more refined hierarchy in social networks and thus becomes a useful tool in the analysis of social networks.

This paper introduces an enhancement to the KNN graph-based clustering method by proposing a local average vector method for selecting the optimal neighborhood size parameter k. Furthermore, it presents an improved Jaya algorithm with KNN graph-based clustering for more effective community detection in social network graphs.

Patriotism is often described as the “love of country” that individuals display in the acclamation of their national community. Despite the prominence of this sentiment in various societies around the world, organizational research on patriotism is largely absent. This omission is surprising because entrepreneurs, human resource (HR) divisions, and firms frequently embrace both patriotism and patriotic organizational practices. These procedures include (among other interventions) national symbol embracing, HR practices targeted toward military members and first responders, the adulation of patriots and celebration of patriotic events, and patriotic-oriented corporate social responsibility (CSR). Here, the authors argue that research on HR management and organization studies will likely be further enhanced with a deeper understanding of the national obligation that can spur employee productivity and loyalty. In an attempt to jumpstart the collective understanding of this phenomenon, the authors explore the antecedents of patriotic organizational practices, namely, the effects of founder orientation, employee dispersion, and firm strategy. It is suggested that HR practices such as these lead to a patriotic organizational image, which in turn impacts investor, customer, and employee responses. Notably, the effect of a patriotic organizational image on firm-related outcomes is largely contingent on how it fits with the patriotic views of other stakeholders, such as investors, customers, and employees. After outlining this model, the authors then present a thought experiment of how this model may appear in action. The authors then discuss ways the field can move forward in studying patriotism in HR management and organizational contexts by outlining several future directions that span multiple levels (i.e., micro and macro). Taken together, in this chapter, the authors introduce a conversation of something quite prevalent and largely unheeded – the patriotic organization.

This study examines the effect of delegation of decision rights, moral justification (MJ), and ethical climate (EC) on managers’ misreporting in the financial services sector. We employed an online research panel called Qualtrics, to collect data based on a sample of 127 middle-level managers from various US financial services firms. We find that MJ mediates the relation between delegation and misreporting, suggesting delegation of decision rights increases employees’ misreporting indirectly by increasing MJ. We also find that EC significantly moderates the relationship between MJ and misreporting. Furthermore, our test of the moderated-mediation effect reveals that the indirect effect of the delegation of decision rights on misreporting through MJ is stronger when there is a higher level of instrumental climate (IC) and a lower level of principle climate (PC).

Personal data is today recognized as an asset in the digital economy, generating billion-dollar annual revenues for many companies. But how much value do users derive from their seemingly free apps (zero-price services), and what user costs are associated with this value exchange? By adopting a human-centric lens, this article scrutinizes the complex trade-offs users face trying to capture the benefits and unperceived costs that such usage entails.

Using a mixed-method research design, this study is anchored in empirical survey data from 196 participants in Linköping, Sweden. The authors investigate users’ willingness to pay for these services in relation to different types of costs.

The results indicate that users can derive significant value from the use of free services, which can be interpreted as a win-win situation between users and companies. Regarding costs, this research shows that the most significant costs for users are associated with procrastination, sleep deprivation and reduced focus, which can be challenging to identify and evaluate from the users’ perspective.

This study shows that zero-price services provide significant benefits like enhancing social connectivity and offering a wide variety of content. Significant drawbacks, such as increased procrastination and sleep disturbances, highlight the psychological effects of these platforms. These impacts include behavioral changes, emphasizing the influence of online platforms on user engagement. Furthermore, a trend toward single-purchase preferences over free services suggests changing consumer attitudes toward digital payment models. This underscores the need for further research on non-monetary aspects in zero-price markets for better understanding and regulation of the digital economy.

This study shows that users appreciate the accessibility and potential of zero-price services but are wary of privacy concerns. It underscores the need for companies to balance profit objectives with user experiences and privacy requirements. Offering a range of ad-free premium services to meet diverse customer needs can be effective. Users’ high valuation of privacy and transparency suggests businesses should focus on human-centric, privacy-respecting strategies. Increased transparency in data usage and giving users greater data control could enhance the user experience and foster sustainable customer relationships.

The study calls for policymakers to focus on non-monetary risks of zero-price services, such as behavioral changes and digital well-being impacts. They should consider implementing regulations to protect users, especially children, from manipulative designs such as “dark patterns”. Policymakers must balance user protection with innovation, leading to a sustainable zero-price economy. For zero-price service users, awareness of non-monetary costs, like procrastination and sleep deprivation, is vital. Understanding that “free” services have hidden costs is important, especially for younger generations. Managing privacy settings and selective service choices can protect privacy and well-being.

This research shifts the focus from simply valuing personal data based on market prices to assessing the worth of free services themselves. By listing various hidden costs, it underscores the need for increased user awareness and greater corporate transparency. Uniquely, it finds that users prefer making one-time purchases over using zero-price services, extending prior assumptions in the field. Additionally, it also characterizes the zero-price economy ecosystem, highlighting differences between market types and provides a deeper understanding of the zero-price market and its related concepts.