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The purpose of this study is to develop a framework for the perceived intelligence of VAs and explore the mechanisms of different dimensions of the perceived intelligence of VAs on users’ exploration intention (UEI) and how these antecedents can collectively result in the highest level of UEI.

An online survey on Amazon Mechanical Turk is employed. The model is tested utilizing the structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approach from the collected data of VA users (N = 244).

According to the SEM outcomes, perceptual, cognitive, emotional and social intelligence have different mechanisms on UEI. Findings from the fsQCA reinforce the SEM results and provide the configurations that enhanced UEI.

This study extends the conceptual framework of perceived intelligence and enriches the literature on anthropomorphism and users’ exploration. These findings also provide insightful suggestions for practitioners regarding the design of VA products.

Fine-tuning pre-trained language models (PLMs), e.g. SciBERT, generally require large numbers of annotated data to achieve state-of-the-art performance on a range of NLP tasks in the scientific domain. However, obtaining fine-tuning data for scientific NLP tasks is still challenging and expensive. In this paper, the authors propose the mix prompt tuning (MPT), which is a semi-supervised method aiming to alleviate the dependence on annotated data and improve the performance of multi-granularity academic function recognition tasks.

Specifically, the proposed method provides multi-perspective representations by combining manually designed prompt templates with automatically learned continuous prompt templates to help the given academic function recognition task take full advantage of knowledge in PLMs. Based on these prompt templates and the fine-tuned PLM, a large number of pseudo labels are assigned to the unlabelled examples. Finally, the authors further fine-tune the PLM using the pseudo training set. The authors evaluate the method on three academic function recognition tasks of different granularity including the citation function, the abstract sentence function and the keyword function, with data sets from the computer science domain and the biomedical domain.

Extensive experiments demonstrate the effectiveness of the method and statistically significant improvements against strong baselines. In particular, it achieves an average increase of 5% in Macro-F1 score compared with fine-tuning, and 6% in Macro-F1 score compared with other semi-supervised methods under low-resource settings.

In addition, MPT is a general method that can be easily applied to other low-resource scientific classification tasks.

The contractors’ consummate performance behavior is the key to achieving the project’s value added, but existing research has paid little attention to how to stimulate this behavior. Based on contractual functions and regulatory focus theory, this study examined how the allocation of contractual functions and the contractors’ regulatory focus affect their consummate performance behaviors. At the same time, considering the important position of guanxi between owner and contractor, this study also examined the moderating effect of guanxi on the relationship between the contractors’ regulatory focus and consummate performance behaviors.

This study first constructs a conceptual model that incorporates contractual functions (control, coordination and adaptation), contractors’ regulatory focus (promotion focus, prevention focus) and the effect of guanxi on contractors’ consummate performance behavior. Next, partial least squares structural equation modeling is used to analyze the survey data of 297 Chinese construction project professionals.

This study has the following four findings. First, contractual control has a negative effect on contractors’ promotion focus but a positive effect on their prevention focus. Contractual coordination and adaptation have a positive effect on contractors’ promotion focus but a negative effect on their prevention focus. Second, contractors’ promotion focus has a positive effect on their consummate performance behaviors, while their prevention focus has a negative effect on such behaviors. Third, both of contractors’ promotion focus and prevention focus play a mediating role in the relationship between contractual functions and their consummate performance behaviors. Finally, guanxi plays a moderating role in the relationship between contractors’ regulatory focus and their consummate performance behaviors.

Theoretically, this study enriches the research on the antecedents of contractors’ regulatory focus and extends the literature on contractual and guanxi management in construction projects. In practice, this study can provide guidance for improving contractors’ consummate performance behaviors and reasonable allocation of contractual functions.

This study aims to develop a comprehensive framework for addressing delays in tunnel construction projects by leveraging predictable risk factors. Tunnel projects often encounter scheduling delays due to inherent complexities and uncertainties, necessitating a proactive approach to prevent project underperformance.

The integrated risk prioritization and determination of activity-wise delay (IRPAD) framework is divided into four phases: identification and prioritization of risk factors, determination of activity-wise risk coefficients using MCDM-based methodology, obtaining the critical risk path, and developing an activity-wise risk matrix. Fault tree analysis (FTA) and event tree analysis (ETA) are employed to determine activity-wise risk coefficients based on expert responses.

The framework’s applicability in Indian tunnel projects is demonstrated through a real-world case study with 95% validation accuracy. The IRPAD framework enhances the delay analysis process and facilitates the provision of effective activity-wise mitigation measures.

The IRPAD framework predicts delays in infrastructure projects thus enhancing resilience and sustainability, supporting SDGs 9 and 11. It can be applied to a wide range of construction projects to improve project performance.

This research introduces novel concepts such as the three fold activity-wise risk matrix and the critical risk path, contributing to the development of the IRPAD framework for delay reduction. This framework offers valuable insights to practitioners in the construction industry.