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The purpose of this study is to explore the impact of online reviews on answer adoption in virtual Q&A communities, with an eye toward extending knowledge exchange and community management.

Online reviews contain rich cognitive and emotional information about community members regarding the provided answers. As feedback information on answers, it is crucial to explore how online reviews affect answer adoption. Based on signaling theory, a research model reflecting the influence of online reviews on answer adoption is established and empirically examined by using secondary data with 69,597 Q&A data and user data collected from Zhihu. Meanwhile, the moderating effects of the informational and emotional consistency of reviews and answers are examined.

The negative binomial regression results show that both answer-related signals (informational support and emotional support) and answerers-related signals (answerers’ reputations and expertise) positively impact answer adoption. The informational consistency of reviews and answers negatively moderates the relationships among information support, emotional support and answer adoption but positively moderates the effect of answerers’ expertise on answer adoption. Furthermore, the emotional consistency of reviews and answers positively moderates the effect of information support and answerers’ reputations on answer adoption.

Although previous studies have investigated the impacts of answer content, answer source credibility and personal characteristics of knowledge seekers on answer adoption in virtual Q&A communities, few have examined the impact of online reviews on answer adoption. This study explores the impacts of informational and emotional feedback in online reviews on answer adoption from a signaling theory perspective. The results not only provide unique ideas for community managers to optimize community design and operation but also inspire community users to provide or utilize knowledge, thereby reducing knowledge search costs and improving knowledge exchange efficiency.

With the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components.

We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function.

First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components.

Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.

This paper aims to investigate a novel impact time control guidance (ITCG) law based on the sliding mode control (SMC) for a nonmaneuvering target using the predicted interception point (PIP).

To intercept the target with the minimal miss distance and desired impact time, an estimation of time-to-go is introduced. This estimation results in a precise impact time for multimissiles salvo attack the target at the same time. Even for a large lead angle, the desired impact time is achieved by using the sliding mode and Lyapunov stability theory. The singularity issue of the proposed impact time guidance laws is also analyzed to achieve an arbitrary lead angle with the desired impact time.

Numerical scenarios with desired impact time are presented to illustrate the performance of the proposed ITCG law. Comparison with the state-of-art impact time guidance laws proves that the guidance law in this paper can enable the missile to intercept the target with minimal miss distance and final impact time error. This method enables multiple missiles to attack the target simultaneously with different distances and arbitrary lead angles.

An ITCG law based on sliding mode and Lyapunov stability theory is proposed, and the switching surface is designed based on a novel estimation time-to-go for the missile to intercept the target with minimal miss distance. To intercept the target with initial arbitrary lead angles and desired impact time, the authors analysis the singular issue in SMC to ensure that the missile can intercept the target with arbitrary lead angle. The proposed approach for a nonmaneuvering target using the PIP has simple forms, and therefore, they have the superiority of being implemented easily.

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between resources. Therefore, this study aims to propose a multidimensional knowledge discovery solution for Tang tomb mural cultural relic resources.

Taking the Tang tomb murals collected by the Shaanxi History Museum as an example, based on clarifying the relevant concepts of Tang tomb mural resources and considering both dynamic and static dimensions, a top-down approach was adopted to first construct an ontology model of Tang tomb mural type cultural relics resources. Then, the actual case data was imported into the Neo4J graph database according to the defined pattern hierarchy to complete the static organization of knowledge, and presented in a multimodal form in knowledge reasoning and retrieval. In addition, geographic information system (GIS) technology is used to dynamically display the spatiotemporal distribution of Tang tomb mural resources, and the distribution trend is analysed from a digital humanistic perspective.

The multi-dimensional knowledge discovery of Tang tomb mural cultural relics resources can help establish the correlation and spatiotemporal relationship between resources, providing support for semantic retrieval and navigation, knowledge discovery and visualization and so on.

This study takes the murals in the collection of the Shaanxi History Museum as an example, revealing potential knowledge associations in a static and intelligent way, achieving knowledge discovery and management of Tang tomb murals, and dynamically presents the spatial distribution of Tang tomb murals through GIS technology, meeting the knowledge presentation needs of different users and opening up new ideas for the study of Tang tomb murals.

This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.

This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.

The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.

This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.

Stainless-clad bimetallic steels (SCBS) are widely investigated in some extremely environmental applications areas, such as polar sailing area and tropical oil and gas platforms areas, because of their excellent anticorrosion performance and relatively lower production costs. However, the properties of SCBS, including the mechanical strength, weldability and the anticorrosion behavior, have a direct relation with the manufacturing process and can affect their practical applications. This paper aims to review the application and the properties requirements of SCBS in marine environments to promote the application of this new material in more fields.

In this paper, the manufacturing process, welding and corrosion-resistant properties of SCBS were introduced systematically by reviewing the related literatures, and some results of the authors’ research group were also introduced briefly.

Different preparation methods, such as rolling composite, casting rolling composite, explosive composite, laser cladding and plasma arc cladding, as well as the process parameters, including the vacuum degree, rolling temperature, rolling reduction ratio, volume ratios of liquid to solid, explosive ratio and the heat treatment, influenced a lot on the properties of the SCBS through changing the interface microstructures. Otherwise, the variations in rolling temperature, pass, reduction and the grain size of clad steel also brought the dissimilarities of the mechanical properties, microhardness, bonding strength and toughness. Another two new processes, clad teeming method and interlayer explosive welding, deserve more attention because of their excellent microstructure control ability. The superior corrosion resistance of SCBS can alleviate the corrosion problem in the marine environment and prolong the service life of the equipment, but the phenomenon of galvanic corrosion should be noted as much as possible. The high dilution rate, welding process specifications and heat treatment can weaken the intergranular corrosion resistance in the weld area.

This paper summarizes the application of SCBS in marine environments and provides an overview and reference for the research of stainless-clad bimetallic steel.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

This study aims to explore the determinants that impact state Islamic University/Perguruan Tinggi Keagamaan Islam Negeri students’ intention to adopt online cash waqfs. In doing so, this study integrates knowledge of cash waqf and trust variables within the theory of planned behavior (TPB), allowing an examination of the mediating role of TPB variables and trust within the relationship between knowledge of cash waqf and intention for online cash waqf behavior.

To carry out an empirical analysis, the authors developed a well-structured questionnaire and distributed it to a group of students currently enrolled in PTKIN, obtaining 443 usable responses. The partial least squares-structural equation modeling (PLS-SEM) technique was used for the dual purposes of data analysis and hypothesis testing.

This study demonstrates that factors such as attitude, subjective norms, perceived behavioral control, trust and knowledge of cash waqf have a significant and favorable influence on the intention to donate through e-cash waqf. Knowledge of cash waqf impacts attitudes, subjective norms, perceived behavioral control and trust. The final analysis shows that attitude, subjective norms, perceived behavioral control and trust partially mediate the relationship between knowledge and intention in the online cash waqf context.

The aforementioned elucidates the paramount importance of trust in shaping individuals’ tendencies to engage in cash waqfs. The insights mentioned have the potential to be used by cash waqf establishments to promote transparency and accountability, ultimately bolstering the confidence of potential donors.

The concepts of waqf and the use of online cash waqf as a means of donation in developing countries are relatively new. In this study, the intention of students to adopt online cash waqf was predicted for the first time by considering their knowledge of cash waqf and their trust in online cash waqf transactions.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.