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Allocation of complex crowdsourcing tasks, which typically include heterogeneous attributes such as value, difficulty, skill required, effort required and deadline, is still a challenging open problem. In recent years, agent-based crowdsourcing approaches focusing on recommendations or incentives have emerged to dynamically match workers with diverse characteristics to tasks to achieve high collective productivity. However, existing approaches are mostly designed based on expert knowledge grounded in well-established theoretical frameworks. They often fail to leverage on user-generated data to capture the complex interaction of crowdsourcing participants’ behaviours. This paper aims to address this challenge.

The paper proposes a policy network plus reputation network (PNRN) approach which combines supervised learning and reinforcement learning to imitate human task allocation strategies which beat artificial intelligence strategies in this large-scale empirical study. The proposed approach incorporates a policy network for the selection of task allocation strategies and a reputation network for calculating the trends of worker reputation fluctuations. Then, by iteratively applying the policy network and reputation network, a multi-round allocation strategy is proposed.

PNRN has been trained and evaluated using a large-scale real human task allocation strategy data set derived from the Agile Manager game with close to 500,000 decision records from 1,144 players in over 9,000 game sessions. Extensive experiments demonstrate the validity and efficiency of computational complex crowdsourcing task allocation strategy learned from human participants.

The paper can give a better task allocation strategy in the crowdsourcing systems.

Although knowledge transfer in the context of projects and project-based organizations (PBOs) has gained increasing attention from academia and industry, it is not clear how knowledge transfers from projects to their parent PBOs. This research aims to explore the main factors influencing knowledge transfer from projects to their parent PBOs, and analyze how these factors integrate the transfer process as system components using the system dynamics (SD) method.

Based on the literature review, investigation and interview, this paper adopts the event analysis to obtain the influencing factors from historical cases and establishes a conceptual model of knowledge transfer from five dimensions, which simultaneously considers the knowledge sender, knowledge receiver and the relationship between the knowledge sender and receiver, knowledge features and transfer context. Then, the relationships between variables in the qualitative model were clarified, and a quantitative model including seven feedback loops was established using the SD model. Lastly, the system simulation and sensitivity analysis of the main parameters were realized in Vensim PLE software.

The simulation analysis results show that the model can simulate the knowledge transfer process from projects to the PBO to a certain extent. This research fully demonstrates the impact of variables from five dimensions on knowledge transfer and incorporates the knowledge gap and transfer threshold in the research category. Moreover, the rationality of seven feedback loops proposed in the model was verified. And the effects of various factors on the amount of knowledge transferred and the PBO's knowledge stock were examined through sensitivity analysis. Furthermore, recommendations for developing an integrated knowledge transfer mechanism of PBOs and projects to enhance transfer effect are offered.

This research provides other researchers with a systematic understanding of transfer process from projects to PBOs, and insight for further research on knowledge transfer in project and organization contexts. Furthermore, this study guides researchers to focus on the causal processes that constitute knowledge transfer and explores the expected and unexpected phenomena generated over time. However, some variables involved in the transfer process are simplified, and the establishment of a more complex dynamic model needs further research and discussion.

By establishing a simulation model for knowledge transfer from projects to their parent PBOs, this study helps project teams and PBOs grasp the overall picture of the transfer process. Especially, this paper provides target-oriented recommendations for project and PBO managers to implement effective knowledge transfer practices, which have certain practical values for knowledge cultivation, coordination, reuse and innovation in the organization.

This study contributes to knowledge management and project management literature by simulating the knowledge transfer process from projects to their parent PBOs. Additionally, this paper provides a reference for PBO and project managers to establish an integrated knowledge-transfer mechanism in the work process and comprehensively implement effective knowledge transfer practices.

The challenge of unforeseen uncertainties in exploratory projects requires the lead firm in a project alliance to effectively manage exploratory co-innovation. The purpose of this paper is to investigate the types of capabilities a lead firm required in exploratory projects and how these capabilities enable the exploratory innovation of the project alliance.

A multiple-case study was done to provide empirical evidence for the rationale of the capabilities of the lead firm. The provided analysis used abductive reasoning of two typical exploratory projects in China.

This paper identifies two types of capabilities: innovation-related capabilities and network-related capabilities. Furthermore, a process model of the capabilities of the lead firm is developed that enables exploratory co-innovation in a project alliance. The capabilities of the lead firm input varied at four different stages.

Innovation-related capabilities and network-related capabilities could form the foundation for the lead firm in an exploratory project alliance. This will enable an exploratory co-innovation and collaboratively overcome the barriers of exploratory projects.

Although exploratory project attracts extensive attention for its unique characteristics and universal value, there is limited amount of research on the context of joint exploratory projects. This study starts from the role of lead firm in an exploratory project alliance, contributes toward the comprehension of the link between the lead firm’s capabilities and the process of exploratory co-innovation. The findings will be of value in supporting the management of exploratory innovation in a project alliance.

Silencing behavior among project team members (PTM) poses a potential threat to project results. Hence, breaking silence in projects is critical to motivate team members and beneficial for project outcomes. The purpose of this paper is to examine the relationship between transformational leadership (TL) of project manager (PM) and silence behavior of PTMs. It proposes a mediating role of feeling trusted (FT) to fill this gap by conducting an empirical research.

A theoretical model was developed and a series of hypotheses were proposed based on existing literature. Then, regression analysis was conducted on a sample of 219 team members of a diverse set of projects in China.

The paper empirically shows that TL of PM is significantly negatively related to team members’ defensive and prosocial silence (PS), but not with their acquiescence silence. In addition, the study also discovered that team members’ FT mediates the effects of TL on team members’ defensive and PS.

This study contributed to the project management literature by showing that feeling trusted link the relationship between TL of PM and PTMs’ silence. The studies’ findings also contribute to the silence theory in project context through discussions of the rationale behind the main effects. Practical implication is provided for PMs that making the most of TL can reduce the silence of PTM, through building trusted feelings. The limitation to this study is the research setting regarding culture-related issues that focused only on projects in China.

This research is one of the early studies that address the issue of silence behavior in project context, which is a contribution to the coordination and communication in project management.

The purpose of this paper is to propose an approach for predicting the movements of Chinese medicinal material price indexes using news based on text mining.

A research framework and three major methods, namely, domain dictionary construction, market convergence time calculation and dimensionality reduction integrating semantic analysis, are proposed for the approach. The proposed approach is applied in practice for predicting the price index movements of the top ten Chinese medicinal materials that receive the greatest media attention.

A set of experiments performed herein show that a predictive relationship exists between the news and the commodity market and that each of the three major methods improves the forecasting performance.

Because the field of Chinese medicinal materials lacks a corpus that can be used for sentiment analysis, the accuracy of a trained automatic sentiment classifier is lower than obtained by a manual method, which can cause the calculated convergence result to be inaccurate, thus affecting the final prediction model. The manual method of having people label news decreases the proposed method’s aspects of being intelligent and automatic.

Using the method proposed herein to predict the trends in Chinese medicinal materials prices helps farmers arrange a reasonable planting plan to pursue their best interests.

The method proposed herein to predict the trends in the prices of Chinese medicinal materials is conducive to the government arranging planned drug availabilities in order to avoid disasters in which herbs are looted.

The produced prediction result is meaningful in supporting farmers and investors to make better decisions in growing and trading Chinese medicinal material, which leads to financial returns on investments and the avoidance of severe losses.

This paper examines how weak ties and strong ties in the supply chain network influence the financing performance of small and medium enterprises (SMEs) through the mediation of information sharing and innovation capability.

Questionnaires were administered to 208 financial managers responsible for supply chain finance in SMEs in China. Data analysis techniques used included multiple regression analysis and fuzzy-set qualitative comparative analysis.

The authors found that weak ties had a more substantial impact on the financing performance of SMEs than strong ties did. Information sharing and innovation capability played a mediating role between weak and strong ties and the financing performance of SMEs. In addition, information sharing and innovation capability complement each other and jointly influence the financing performance of SMEs.

SMEs are suggested to actively embed themselves in the supply chain network to increase financing opportunities and reduce financing costs. The authors also recommend SMEs to enhance the level of their information sharing in the supply chain network and take advantage of their network ties to access and adopt new technology from other organisations and conduct collaborative innovation with partner institutions.

The paper extends the authors’ understanding of supply chain finance by exploring the intrinsic mechanism of how various constructs (weak ties, strong ties, information sharing and innovation capability) in the supply chain network have an impact on the financing performance of SMEs. In particular, the authors explore the under-researched mediating effect of information sharing and innovation capability on the relationship between network ties and the financing performance of SMEs.

The purpose of this paper is to provide delay announcements for call centers with hyperexponential patience modeling. The paper aims to employ a state-dependent Markovian approximation for informing arriving customers about anticipated delay in a real call center.

Motivated by real call center data, the patience distribution is modeled by the hyperexponential distribution and is analyzed by its realistic significance, with and without delay information. Appropriate M/M/s/r+H₂ queueing model is structured, including a voice response system that is employed in practice, and a state-dependent Markovian approximation is applied for computing abandonment. Based on this approximation, a method is proposed for estimating virtual delays, and it is investigated about the problem of announcing virtual delays to customers upon their arrival.

There are two parts of findings from the results obtained from the case study and a numerical study of simulation comparisons. First, using an H₂ distribution for the abandonment distribution is driven by an empirical study which shows its good fit to real-life call center data. Second, simulation experiments indicate that the model and approximation are reasonable, and the state-dependent Markovian approximation works very well for call centers with larger pooling. It is concluded that our approach can be applied in a voice response system of real call centers.

Many results pertain to announcing delay information, customer reactions and links to estimating hyperexponential distribution based on real data that have not been established in previous studies; however, this paper analytically characterizes these performance measures for delay announcements.

In this paper the aim is that Aramid/alginate blended nonwoven fabrics were prepared, and the flame retardancy of the blended nonwoven fabrics was studied by thermogravimetric analysis, vertical flame test, limiting oxygen index (LOI) and cone calorimeter test.

The advantages of different fibers can be combined by blending, and the defects may be remedied. The study investigates whether incorporating alginate fibers into aramid fibers can enhance the flame retardancy and reduce the smoke production of prepared aramid/alginate blended nonwoven fabrics.

Thermogravimetric analysis indicated that alginate fibers could effectively inhibit the combustion performance of aramid fibers at a higher temperature zone, leaving more residual chars for heat isolation. And vertical flame test, LOI and cone calorimeter test testified that the incorporation of alginate fibers improved the flame retardancy and fire behaviors. When the ratio of alginate fibers for aramid/alginate blended nonwoven fabrics reached 80%, the incorporation of alginate fibers could notably decreased peak-heat release rate (54%), total heat release (THR) (29%), peak-smoke production rate (93%) and total smoke production (86%). What is more, the lower smoke production rate and lower THR of the blends vastly reduced the risk of secondary injury in fires.

This study proposes to inhibit the flue gas release of aramid fiber and enhance the flame retardant by mixing with alginate fiber, and proposes that alginate fiber can be used as a biological smoke inhibitor, as well as a flame retardant for aramid fiber.

The purpose of this study is to examine how the quality management of small and medium-sized enterprises (SMEs) impacts their supply chain financing performance (SCFP). This study also investigates the mediating roles of organisational dependence between quality management and the SCFP of SMEs, as well as the moderating role of environmental dynamics.

Questionnaires were administered to 248 financial managers responsible for supply chain finance (SCF) in SMEs in China. Data analysis techniques used include necessary condition analysis and multiple regression analysis.

Research findings show that, in SCF, the quality management of SMEs positively predicts their SCFP through the mediation of the organisational dependence of the focal enterprises in the supply chain network. Environmental dynamics are also found to moderate the relationship between quality management and SCFP through the organisational dependence of capital providers.

To the best of our knowledge, this is the first study to explore the relationships between SMEs' quality management and their SCFP. Also, this study provides a new theoretical lens through which to study SCF by introducing signalling theory.

In some three-dimensional (3D) printing application scenarios, e.g., model manufacture, it is necessary to print large-sized objects. However, it is impossible to implement large-size 3D printing using a single projector in digital light processing (DLP)-based mask projection 3D printing because of the limitations of the digital micromirror device chips.

A multi-projector DLP with energy homogenization (EHMP-DLP) scheme is proposed for large-size 3D printing. First, a large-area printing plane is established by tiling multiple projectors. Second, the projector set’s tiling pattern is obtained automatically, and the maximum printable plane is determined. Third, the energy is homogenized across the entire printable plane by adjusting gray levels of the images input into the projectors. Finally, slices are automatically segmented based on the tiling pattern of the projector set, and the gray levels of these slices are reassigned based on the images of the corresponding projectors.

Large-area high-intensity projection for mask projection 3D printing can be performed by tiling multiple DLP projectors. The tiled projector output energies can be homogenized by adjusting the images of the projectors. Uniform ultraviolet energy is important for high-quality printing.

A prototype device is constructed using two projectors. The printable area becomes 140 × 210 mm from the original 140 × 110 mm.

The proposed EHMP-DLP scheme enables 3D printing of large-size objects with linearly increasing printing times and high printing precision. A device was established using two projectors to practice the scheme and can easily be extended to larger sizes by using more projectors.