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Drawing on the conservation of resources (COR) theory, we propose a mediated moderation showing how proactive personality (PP) and job crafting toward interests (JC-interests) influence the relationship between interest incongruence and cyberloafing.

We used a three-wave survey and collected data from 429 full-time employees working in different industries in China.

We found that interest incongruence was positively related to cyberloafing. Furthermore, this positive relationship was more significant when employees were low in PP or engaged in low levels of JC-interests. In addition, the moderating effect of PP was mediated by JC-interests.

These findings are helpful for organizations in figuring out how to mitigate the detrimental effects of interest incongruence by providing more support to proactive employees and implementing various JC interventions.

This study suggests that PP and JC-interests (resource gain strategy) could mitigate the positive effect of interest incongruence on employees’ cyberloafing.

This paper aims to investigate how perpetrators who engage in unethical pro-organizational behavior (UPB) feel and respond in the aftermath of such behavior.

This paper used a two-wave time-lagged design and collected data from 260 full-time employees working in different industries in China.

The results indicated that UPB was negatively and indirectly associated with internal whistle-blowing through shame. Perceived moral leadership weakened the effect of shame on internal whistle-blowing.

Based on affective events theory, this paper explored an integrated behavior-emotion-behavior sequence. This paper proposed that the negative emotion, shame, evoked by UPB subsequently influences the extent to which UPB perpetrators engage in internal whistle-blowing.

The internal force is more complicated in a combined load case than in a single load case, and the influence of the combined load on the stress cannot be neglected. The purpose of this paper is to study the mechanical behavior of the flexible riser under combined load conditions of tension and internal pressure or external pressure.

The mechanical behavior of the flexible riser under combined load conditions is studied by numerical simulation with a nine-layer detailed finite element model. The layers of flexible riser are modeled separately, and the interactions between layers have been taken into consideration in numerical simulation.

Under tension and internal pressure or external pressure, the pressure armor will bear extra external pressure because of the squeezing actions between layers caused by tension, and the extra external pressure will increase proportionately with the increase of the tension. Under internal pressure and tension, the internal stress for tension armor was nearly unchanged compared to that under unique tension load, whereas under external pressure and tension, the change of internal stress for tension armor was significant. Prediction methods of internal force for pressure armor and tension armor under pressure and tension are given, and the result from the formula agrees well with the simulation results.

The prediction methods on the internal force of flexible riser proposed in this study are proven accurate, with numerical simulation results, and the prediction methods are convenient for engineering applications.

This study aims to examine if the participation of live-stream influencers (LSIs) affects tipping frequency on live streaming platforms, and further investigate the mediating and moderating mechanisms.

Quasi-experiment and difference-in-differences models are used for data analysis. Propensity score matching is used to address potential unobservable endogeneity.

Real-time live streaming data reveal that LSIs’ participation significantly improves tipping frequency in live streaming rooms. Also, more users are attracted to the live streaming rooms and more users become active in participation. Additionally, the positive impact of LSIs’ participation is enhanced in the live streaming rooms with a greater number of relationship links between users.

The findings clarify the new role of influencers and reveal the mechanisms on how LSIs benefit the platforms.

The findings offer novel insights into implementing influencer marketing to interactive social media platforms, by encouraging influencer participation, user relationship building and influencer network growth.

This study highlights the value of LSIs for interactive social media platforms in terms of organic growth, revenue generation and cost reduction.

The Chemical Integrated Information Service Network (Chl2Net) is a comprehensive information service system which includes chemical, technical, economic, market, news and management information based on computer and modern communication technology, and built by the China National Chemical Information Centre (CNCIC). This system provides varied services for users both at home and abroad through an online service, a hotline call service, a consulting service and publishing service.

This study aims to investigate the impact of technological turbulence on entrepreneurial orientation (EO) in Chinese e-commerce enterprises. It also examines the mediating roles of business ties and political ties, and the moderating effect of transaction uncertainty on these relationships.

A sample of 173 Chinese e-commerce enterprises was analyzed using survey data. Structural equation modeling was employed to test the proposed hypotheses, including the direct effects of technological turbulence on EO, the mediating roles of business and political ties, and the moderating effect of transaction uncertainty.

The results indicate a positive correlation between technological turbulence and EO. Business ties mediate the relationship between technological turbulence and EO, while political ties do not. Transaction uncertainty negatively moderates the relationship between business ties and EO but does not significantly affect the relationship between political ties and EO. Additionally, EO positively impacts market performance.

This study extends the understanding of how external environmental factors, such as technological turbulence, influence EO in the context of Chinese e-commerce. It highlights the differential roles of business and political ties and provides insights into the moderating effects of transaction uncertainty. The findings offer practical implications for e-commerce firms seeking to enhance their entrepreneurial capabilities in turbulent environments.

The purpose of this paper is to propose and demonstrate criteria for omnibearing imbalance of macroeconomic system structure (regions, industries, urban and rural areas, departments, ownership, etc.) and their strategic optimization, for structural optimization of the global regional macroeconomic system, providing universal application of the formula for calculating, and quantitative basis.

Relevant statistical data will compare receipts (GBC) model calculation to quantitatively determine structural imbalance and the formation of structural optimization and direction and intensity of the strategic program.

Contemporary system science believes that all things take the form of systems, and that the output function depends on the internal structure of systems. Therefore, the system structure must be judged by the output benefit. Although the output benefit of a society's macroeconomic system is enslaved to the system's external environment (the peripheral environment, international economy, or even global economy), the state of the system's internal structure directly determines its output benefit. In reverse, the output benefit of the macroeconomic system is also the reference to evaluate its internal structure.

Research on the macroeconomic system structural imbalances and optimization with universal applicability.

The paper is of great significance with regard to the theory, methodology, and practice for structural optimization of the global regional macroeconomic system.

This paper aims to present a picture of the past and the present status of the Distance Education College (DEC) of East China Normal University (ECNU). It describes what the DEC has achieved in each phase, and probes into some essential problems that the DEC has attempted to solve.

This article provides a comprehensive description of the development of the DEC by following a case study method.

The DEC goes through three stages. In the first phase, a teacher‐focused policy and disciplined management are formed. In the second phase, a quality‐first policy is emphasized, and two training modes are developed: the human‐centered management mode and the trainee‐oriented training mode. In the third phase, the DEC initiates further innovation and uses a new platform.

ECNU has witnessed and participated in the development of modern distance education in China. It remains successful in developing distance education. The effort made by the DEC well showcases the overall development and growth of modern distance education in China.

This article presents the development of the DEC and will help readers understand the developmental process of distance education colleges in China.

Opinion mining (OM), also known as “sentiment classification”, which aims to discover common patterns of user opinions from their textual statements automatically or semi-automatically, is not only useful for customers, but also for manufacturers. However, because of the complexity of natural language, there are still some problems, such as domain dependence of sentiment words, extraction of implicit features and others. The purpose of this paper is to propose an OM method based on topic maps to solve these problems.

Domain-specific knowledge is key to solve problems in feature-based OM. On the one hand, topic maps, as an ontology framework, are composed of topics, associations, occurrences and scopes, and can represent a class of knowledge representation schemes. On the other hand, compared with ontology, topic maps have many advantages. Thus, it is better to integrate domain-specific knowledge into OM based on topic maps. This method can make full use of the semantic relationships among feature words and sentiment words.

In feature-level OM, most of the existing research associate product features and opinions by their explicit co-occurrence, or use syntax parsing to judge the modification relationship between opinion words and product features within a review unit. They are mostly based on the structure of language units without considering domain knowledge. Only few methods based on ontology incorporate domain knowledge into feature-based OM, but they only use the “is-a” relation between concepts. Therefore, this paper proposes feature-based OM using topic maps. The experimental results revealed that this method can improve the accuracy of the OM. The findings of this study not only advance the state of OM research but also shed light on future research directions.

To demonstrate the “feature-based OM using topic maps” applications, this work implements a prototype that helps users to find their new washing machines.

This paper presents a new method of feature-based OM using topic maps, which can integrate domain-specific knowledge into feature-based OM effectively. This method can improve the accuracy of the OM greatly. The proposed method can be applied across various application domains, such as e-commerce and e-government.

This paper focuses on the differences in domain intellectual structure discovery between author bibliographic coupling analysis (ABCA) and author co-citation analysis (ACA) considering all authors. The purpose of this study is to examine whether and in what ways these two all-author network approaches yield different results.

The sample was collected from the database of Web of Science, including all articles published in Scientometrics and Journal of Informetrics from 2011 to 2020. First, 100 representative authors were selected from each set, and ABCA matrices and ACA matrices were constructed. Second, factor analysis was carried out on the matrices, to detect the intellectual structure of scientometrics and informetrics.

The intellectual structures identified by ABCA and ACA are similar overall, but the results differ somewhat when it comes to specific structures. The ABCA is more sensitive to some highly collaborative research teams and presents a clearer picture of current intellectual structures and trends while ACA seems to have some advantages in representing the more traditional and proven research topics in the field. The combined use of ABCA and ACA allows for a more comprehensive and specific intellectual structure of research fields.

This paper compares the performance of ABCA and ACA detecting the intellectual structure of the domain from the perspective of all authors, revealing the intellectual structure of scientometrics and informetrics comprehensively.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2020-0540.