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The purpose of this study is to examine the strategies used by consumers to control themselves in the Singles’ Day promotion. It also examines how promotion and social influence affect consumers’ purchase behavior and post-purchase evaluation.

A mixed methods approach including a quantitative study (N = 480) and a follow-up qualitative study (N = 35) was conducted to verify the hypotheses and provide deeper insights.

This study demonstrates that consumers allocate in-store slack in shopping budgets to restrict unplanned purchases and in-store slack is positively related to post-purchase evaluation. Social influence, which helps consumers rationalize purchase decisions, has positive effects on planned purchases and post-purchase evaluation. Both promotion strength and promotion range moderate the relationship between in-store slack and unplanned purchases.

Most studies investigate how promotion designs affect consumers’ in-store decision-making. This study focuses on the Singles’ Day promotion in China and examines the tactics consumers use to control purchase behavior in the promotion.

Patent trade recommendations necessitate recommendation interpretability in addition to recommendation accuracy because of patent transaction risks and the technological complexity of patents. This study designs an interpretable knowledge-aware patent recommendation model (IKPRM) for patent trading. IKPRM first creates a patent knowledge graph (PKG) for patent trade recommendations and then leverages paths in the PKG to achieve recommendation interpretability.

First, we construct a PKG to integrate online company behaviors and patent information using natural language processing techniques. Second, a bidirectional long short-term memory network (BiLSTM) is utilized with an attention mechanism to establish the connecting paths of a company — patent pair in PKG. Finally, the prediction score of a company — patent pair is calculated by assigning different weights to their connecting paths. The semantic relationships in connecting paths help explain why a candidate patent is recommended.

Experiments on a real dataset from a patent trading platform verify that IKPRM significantly outperforms baseline methods in terms of hit ratio and normalized discounted cumulative gain (nDCG). The analysis of an online user study verified the interpretability of our recommendations.

A meta-path-based recommendation can achieve certain explainability but suffers from low flexibility when reasoning on heterogeneous information. To bridge this gap, we propose the IKPRM to explain the full paths in the knowledge graph. IKPRM demonstrates good performance and transparency and is a solid foundation for integrating interpretable artificial intelligence into complex tasks such as intelligent recommendations.

This intervention study outlines the continuing journey of a university towards its sustainability potentiality. We introduce the importance of sustainable development and link it to our intervention study of potentiality for sustainability from a Heideggerian phenomenological perspective. Through a case study of sustainability at New Mexico State University, we provide an insight into the development of a new dimension of university sustainability interface. This interface exists in terms of a dialogic of sustainability, as it relates to the balancing of competing needs, such as efficiency, heart, and brand identity. An important aspect of this interface is intervention, highlighting new possibilities for the top administrators regarding the university's goals and environmentalities. A qualitative and interpretive approach using ontological storytelling inquiry is employed. Data for the study were collected through in-depth interviews with university members from all hierarchical levels. This article raises interesting ontological issues for sustainability researchers, and has implications for strategy as practice.

The purpose of this paper is to introduce a new method of ontology‐based digital product data exchange. The digital product data are enriched with virtual prototype (VP) model information and the designed exchange process is discussed. Additionally, an algorithm enabling the ontology‐based data exchange method among missile guide systems is proposed and analyzed.

Semantic sevice‐oriented architecture (SSOA) is an innovative integration architecture for digital product information integration and process integration. In digital product ontology layer of SSOA, a new method of ontology‐based product data exchange is proposed. Compared with traditional information exchange, the method adds the VP's information to general digital products' information. The VP's information is described by building VP static structure ontology and dynamic behavior ontology. The exchange process of the novel method is discussed in detail. Finally, an example illustrating the data exchange among missile guide systems is given and the merits of the proposed method is analyzed.

Simulation information, especially VP information, is not always well defined and taken into account by product data exchange systems such as product data management or product lifecycle management. A formal description of VP information is often required in efficient and effective product data exchange. The goal is to define VP structure and behavior ontologies to enable ontology‐based digital product data exchange.

Using VP information including structure information and behavior information, the paper provides a new method of digital product data exchange.

In China, external supervision on construction safety mainly comes from the government and supervision engineers (SEs). However, the construction safety supervisory mechanism (CSSM) contains some dilemmas affecting the improvement of safety performance, such as the declining impact of SEs, the increasing rent-seeking behaviors of contractor and excessive government interference. This study aims to depict and analyze the CSSM in China from an evolutionary game view. The objectives are to understand the supervision strategy and evolutionary behaviors of different stakeholders, propose suggestions for improving safety performance and help the key safety supervision stakeholders, especially the government, formulate a suitable safety supervision strategy.

This research uses tripartite dynamic evolutionary game theory to study the CSSM in China and solve the stable equilibrium solution using system dynamics.

This study has revealed the game relationship of construction safety supervision mechanisms in China and solved the stable equilibrium solution. The results prove that a supervision engineer (SE) plays a crucial role in the CSSM, and “supervision engineer useless” is an unreasonable assertion. For government supervision agency (GSA), excessive inspection and free-market regulation are neither wise strategies. GSA can reduce the inspection frequency when general contractors (GCs) input high safety investments and SEs implement responsible supervision. But keeping proper government supervision to avoid GC's unlawful behaviors and SE's rent-seeking is indispensable. In addition, excessive governmental supervision will weaken SE's role, so the government should transfer some supervision powers to SE.

This study focuses on the dynamic evolution process between GSA, GC and SE. This method is different from most research that neglected the dynamic characteristic of system and game solution stability. The research methods not only contribute to construction safety supervision policy-making in China but also help to improve supervision efficiency in other countries and other fields.

This study aims to examine how job satisfaction (JS) affects two types of knowledge sharing (KS), in-role KS and extra-role KS. It also investigates the mediating effect of knowledge sharing self-efficacy (KSSE) and the moderating effect of team collaborative culture (TCC) between JS and two types of KS.

This study applies attribution theory to develop a cross-level model and validate it through paired data collected from 322 information technology professionals nested within 80 teams. Hierarchical linear modeling is used to test the hypotheses.

JS positively influences in-role and extra-role KS via KSSE and TCC positively moderates the relationship between JS and extra-role KS.

This study is one of the first to investigate the mechanism underlying the influence of JS on two types of KS. It also identifies the mediating and moderating effects of this mechanism.

Despite concerns about the effect of internet addiction, little is known about how psychological suzhi impacts the internet addiction of college students. This paper aims to investigate the relationship between psychological suzhi and internet addiction among college students.

Using the college student psychological suzhi scale and internet addiction test, 2,070 college students from 11 universities in North China, East China, South China and Southwest China were tested.

The detection rate of internet addiction in this college sample of students was 18.8%. There was a significant negative correlation between students’ psychological suzhi and internet addiction (r = −0.408, p < 0.01). Hierarchical regression analysis showed that adaptability and individuality in psychological suzhi significantly negatively predicted college students’ internet addiction tendency (p < 0.001).

This study is the first to show a relationship between psychological suzhi and internet addiction in college students. In detail, the adaptability and individuality of college students’ psychological suzhi are protective factors related to internet addiction. The results also suggested that the authors can prevent and intervene in internet addiction by modifying college students’ adaptability and individuality.

The purpose of this paper is to examine how team social media usage (SMU) affects two types of knowledge sharing (KS), namely, in-role and extra-role KS, and then individual job performance. The study also examines the mediating effects of two types of KS and the main and moderating effects of team performance norms on individual job performance.

This study applies the theory of communication visibility to develop a cross-level model and then validate it through a three-wave survey from 600 individuals in 120 teams. Hierarchical linear model is used to test the hypotheses.

The results suggest that team SMU improves team members’ in-role and extra-role KS, and thus enhances their individual job performance. The in-role and extra-role KS have partial mediating effects between team SMU and job performance. The results also show that team performance norms have a positive main effect on individual job performance, but negatively moderate the relationship between individual extra-role KS and job performance.

This study contributes to the operations management literature by examining the effects of team SMU from a multilevel perspective.

The findings provide managers with ways to improve individual KS and job performance.

This study is one of the first to investigate the effects of team SMU on individual KS and job performance. It also identifies the two-sided effects of team performance norms.