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As an important form of the e-commerce industry, online group buying is under the spotlight from with two sides: cheaper price but longer waiting time. The purpose of this paper is to adequately investigate the interaction between saving and waiting time of group buying comprehensively.

To fill the research gap, the authors elaborate a dual-channel supply chain (SC) with regular retail (individual buying) and group-buying channel, and formulate the demand based on the consumer utility with the positive effect of saving money and the negative effect of wasting time.

The authors find that power structure only changes the optimal prices, instead of the waiting time. The selling price mainly influences consumer demands, instead of the price discount of group buying. The SC profits are only positive to the channel preference, and it is the decisive parameter of consumers' choice. The price sensitivity lays a more remarkable impact on the SC compared to the time sensitivity. Above all, the price is the main factor of group buying, instead of time.

These results underscore the improvement for the dual-channel SC of group buying, providing managerial insights for the group-buying industry.

In the information commons (IC) space of library, it is very important to recognize the emotional state of users for better playing the role of IC. In view of this point, this paper aims to discuss the human expression of user emotion.

An emotional state recognition method based on body posture change under video monitoring is proposed. In this method, two parameters are proposed to represent the emotional state of users. Finally, the distribution of users’ overall emotional state is recognized.

It is found that the change of human posture reflects the emotional state of users to a certain extent. The spatial frequency of the user’s average body position change and per capita body position change can reflect the spatial distribution of individual and body position change, respectively.

The method in this paper can effectively overcome the inaccuracy of manual identification of video monitoring images, especially in the case of a large number of users and effectively help the construction of university library IC space and provide a basis for the setting of environmental parameters.

The purpose of this paper is to evaluate the service quality of university library more accurately and dynamically and improve the service efficiency of library. The paper realizes quantified representation of library service quality and overcomes the shortcoming of the traditional library evaluation system, which does not consider reader’s identity and cannot be evaluated separately. In addition, according to the function configuration of each department of library, a relation between library evaluation parameter and its organization structure is built. According to the evaluation results and the chain of relations, some suggestions for improving library service can be put forward; thus, it can improve the quality of library service and management efficiency.

In this paper, a four-dimensional (4-D) representation method is put forward to express four kinds of parameters, namely, the category of participants, the number of people evaluated, the rating level and the weight of parameters, which is expressed by chromaticity and a three-dimensional column coordinate space. Considering the existing evaluation methods such as LibQUAL+TM, the content of evaluation parameters, the grade of evaluation parameters and the weight of evaluation parameters are modified. Using the volume and the equivalent number of people under this evaluation system, the evaluation grade can be quantified and the total results can be evaluated quantitatively.

The evaluation model proposed in this paper is a 4-D system that is based on content parameters to evaluate the number of participants, score segments, evaluation content weights and reader information. It gives full consideration to the good advice of many scholars and combines the actual operation of domestic libraries. The situation effectively integrates successful experience abroad. Both the undergraduate and teacher sampling evaluation results and their analysis in this paper show the accuracy and credibility of the method.

Although the satisfaction index model has a good effect in foreign countries, taking into account that readers of university libraries in China are different from those in foreign countries in the evaluation methods of the tutorial, professional multi-level evaluation will produce greater errors in practical applications. The traditional four-level method based on Chinese education evaluation (excellent, good, pass and fail) has reached consensus among teachers and students in practical application, and it is easy to achieve consistency. Therefore, this paper also adopts four-level evaluation, that is, very satisfied, satisfied, generally satisfied and very dissatisfied. The embedded application will be able to perform dynamic evaluation and thus can be used in China. The evaluation of service quality in university libraries provides an effective new method.

This study aims to investigate the antecedents of mobile Internet users’ perception of information sensitivity (PIS) and willingness to provide personal information (WTP). It provides insights about how these antecedents influence users’ perceived information sensitivity and willingness to provide.

An online survey of mobile Internet users was conducted in China, generating a total of 1,000 qualified responses for analysis.

Results reveal the differential effects of some major antecedents of mobile Internet users’ perceived information sensitivity and willingness to provide (individual disposition to value privacy, age, gender, app type and privacy concerns) and such impact vary across low-, medium- and high-privacy segments.

This study provides insights into the antecedents of mobile Internet users’ attitudes towards personal information privacy. It also extends the understanding of users’ perceived information sensitivity and willingness to provide such information comparatively among four countries.

The online Question and Answer community is full of a large number of science and technology topics, the discussion and dissemination of which play an important role in promoting the popularization of new technologies and cultivating public enthusiasm for science. However, the spread of false information and rumors weakens the community's positive effect, making the community more difficult for people to obtain useful information on such topics. Research on the influencing factors and governance of the spread of false information on science and technology topics has become the key to the spread of popular science.

Therefore, this paper uses the Elaboration Likelihood Model as the theoretical framework to examine the role of the factors influencing the spread of false information on science and technology topics in Zhihu community on the information persuasion and the impact on public behavior attitude from the core path and the edge path. This paper compiles a crawler program to capture 12,893 response information under the “Metaverse” topic in Zhihu community as an empirical sample and uses text mining and conducts visual correlation analysis to explore the key factors affecting the persuasive transmission path of information on science and technology topics.

The research finds that the content specialization, content consistency and content coherence of science and technology topics affect personal judgment from the aspect of information content through the core path and have a positive correlation with information persuasion; the number of comments, the length of the text and the publishing authors' influence from the edge image characteristics through the edge path are positively correlated with the information persuasion. Then, from the perspective of topic platform, government and topic participants, this paper puts forward a general plan to improve the information persuasion of science and technology topics so as to deal with false information.

Compared with the small data set of the traditional questionnaire survey, the research based on community empirical big data is more reliable. The model takes into account the attitude and behavior of users and is more suitable for the research on the transmission path of scientific and technological information in the internet era. This research provides a direction for analyzing the text characteristics and development trends of information in the field of science and technology and is conducive to promoting the optimization of the network information environment and building a good ecology, with the spread of rumors about science and technology topics curbed and the governance of false information strengthened.

Outsourcing is a common practice that is often adopted to reduce costs and enhance capabilities. The underlying logic of a firm's outsourcing strategy is not always evident due to multiple antecedents with interacting effects. This study identifies critical factors that influence outsourcing strategies and reveals their interactions with empirical evidence from Chinese construction firms.

The quantitative decision-making trial and evaluation laboratory (DEMATEL) method was applied to analyze the interrelationships among the antecedents of project outsourcing strategies. First, 24 experts from 13 Chinese construction firms were invited to evaluate and score the influence of each factor on the other. Second, the graph theory and matrix tools of DEMATEL were used to quantitatively obtain the causality among factors and the prominence of each factor within the system.

Among the antecedents, a firm's pursuit of cost efficiency, identity, technological capability and contracting capability are the most prominent factors influencing project outsourcing strategies. For the interactions among these factors, this study reveals that the focal firm's technological capability significantly influences its contracting capability, and they jointly influence the firm's outsourcing practices, the selection of outsourcing vendors and, eventually, its pursuit of cost efficiency. Moreover, legal restrictions in the institutional environment strongly shape this capability–cost efficiency relationship.

Twelve critical factors following different theoretical perspectives at varying levels of analysis were identified from the literature review. By revealing the interrelationships among these factors, this study develops a holistic framework that integrates the transaction cost and capability perspectives for understanding project outsourcing strategies embedded in different institutional environments.

This paper aims to study the establishment of cooperative supply game model considering transportation hub location, and design the profit allocation rule of the cooperative supply coalition.

Based on the economic lost-sizing (ELS) game model and considering the location of transportation hub and the topology design of basic traffic network, we build a supply game model to maximize the profit of cooperative supply coalition. Based on the principle of proportion and the method of process allocation, we suppose the procedural proportional solution of the supplier cooperative supply game.

Through numerical examples, the validity and applicability of the proposed model and the procedural proportional solution were verified by comparing the procedural proportional solution with the weighted Shapley value, the equal division solution and the proportional rule.

This paper constructs a feasible mixed integer programming model for cooperative supply game. We also provide the algorithm of the allocation rule of cooperative supply game and the property analysis of the allocation rule.

The purpose of this paper is to present a method that addresses the data sparsity problem in points of interest (POI) recommendation by introducing spatiotemporal context features based on location-based social network (LBSN) data. The objective is to improve the accuracy and effectiveness of POI recommendations by considering both spatial and temporal aspects.

To achieve this, the paper introduces a model that integrates the spatiotemporal context of POI records and spatiotemporal transition learning. The model uses graph convolutional embedding to embed spatiotemporal context information into feature vectors. Additionally, a recurrent neural network is used to represent the transitions of spatiotemporal context, effectively capturing the user’s spatiotemporal context and its changing trends. The proposed method combines long-term user preferences modeling with spatiotemporal context modeling to achieve POI recommendations based on a joint representation and transition of spatiotemporal context.

Experimental results demonstrate that the proposed method outperforms existing methods. By incorporating spatiotemporal context features, the approach addresses the issue of incomplete modeling of spatiotemporal context features in POI recommendations. This leads to improved recommendation accuracy and alleviation of the data sparsity problem.

The research has practical implications for enhancing the recommendation systems used in various location-based applications. By incorporating spatiotemporal context, the proposed method can provide more relevant and personalized recommendations, improving the user experience and satisfaction.

The paper’s contribution lies in the incorporation of spatiotemporal context features into POI records, considering the joint representation and transition of spatiotemporal context. This novel approach fills the gap left by existing methods that typically separate spatial and temporal modeling. The research provides valuable insights into improving the effectiveness of POI recommendation systems by leveraging spatiotemporal information.

Drawing on identity theory and the symbolic interactionism perspective of identity theory, this study aims to construct a moderated mediation framework to test the effects of perceived overqualification (POQ) on knowledge sharing (KS) through professional identity threat (PIT) and the moderating role of coworkers' help-seeking behavior (CHSB).

This paper uses a quantitative multistudy research design with a combination of a scenario experiment (Study 1) and a two-wave field study among 220 supervisor-subordinate dyads at a power company in China. Using analysis of variance, confirmatory factor analysis (CFA) and bootstrapping method, the authors validated the research hypothesis.

In the scenario experiment study (study 1), the authors find that POQ is positively related to PIT and that CHSB negatively moderates the positive impact of POQ on PIT. The field study (study 2) replicated the above findings and found that PIT mediates the negative effect of POQ on KS. In addition, CHSB negatively moderates the mediating role of PIT between POQ and KS.

First, the current study extended the nomological network of POQ research by examining its influence on employees' KS. Second, this study empirically investigated the mediating role of PIT, which provided a new explanatory mechanism for the influence of POQ. Finally, this study demonstrates the moderating role of CHSB—a situational factor that has been ignored in previous studies.

A vital job for one sharing business is dynamically dispatching shared items to balance the demand-supply of different sharing points in one sharing network. In order to construct a highly efficient dispatch strategy, this paper proposes a new dispatching algorithm based on the findings of sharing network characteristics.

To that end, in this paper, the profit-changing process of single sharing points is modeled and analyzed first. And then, the characteristics of the whole sharing network are investigated. Subsequently, some interesting propositions are obtained, based on which an algorithm (named the Two-step random forest reinforcement learning algorithm) is proposed.

The authors discover that the sharing points of a common sharing network could be categorized into 6 types according to their profit dynamics; a sharing network that is made up of various combinations of sharing stations would exhibit distinct profit characteristics. Accounting for the characteristics, a specific method for guiding the dynamic dispatch of shared products is developed and validated.

Because the suggested method considers the interaction features between sharing points in a sharing network, its computation speeds and the convergence efficacy to the global optimum scheme are better than similar studies. It suits better to the sharing business requiring a higher time-efficiency.