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Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.

The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.

The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.

This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.

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.

The paper aims to find the correlation between the microparameters and the macroparameters of the soil. The study aims to calibrate the macroscale and microscale parameters of rolling resistance contact models to successfully apply the discrete element method to do some research of the geotechnical problem.

The paper opted for an exploratory study using the PFC3D to simulate the triaxial tests that include more than 50 cases and the coupling analysis method, which considering several effect of various factors.

The paper provides a quantitative relationship between the macroparameters and microparameters of the rolling resistance linear model and a method for fast calibration of macroscopic parameters is proposed and verified by a triaxial test example.

This paper provides the quantitative relationship of micro and macroparameters in the rolling resistance linear model by studying a single factor and considering the coupling effect of various factors and a fast method for the calibration of microparameters based on the rolling resistance linear model is proposed.

Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.

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 study aimed to explore the spatial accessibility dynamics of urban parks and their driving forces from 1901 to 2010 in terms of the dynamic relationships between spatial morphology and road networks, taking Nanjing City as an example.

This study mapped and examined the spatiotemporal distribution of urban parks and road networks in four time points at Nanjing: the 1910s, 1930s, 1960s and 2010s, using the analysis methodology of spatial design network analysis, kernel density estimation and buffer analysis. Two approaches of spatial overlaying and data analysis were adopted to investigate the accessibility dynamics. The spatial overlaying compared the parks' layout and the road networks' core, subcore and noncore accessible areas; the data analysis clarified the average data on the city-wide and local scales of the road networks within the park buffer zone.

The analysis of the changing relationships between urban parks and the spatial morphology of road networks showed that the accessibility of urban parks has generally improved. This was influenced by six main factors: planning implementation, political policies, natural resources, historical heritage and cultural and economic levels.

The results provide a reference for achieving spatial equity, improving urban park accessibility and supporting sustainable urban park planning.

An increasing number of studies have explored the spatial accessibility of urban parks through the relationships between their spatial distribution and road networks. However, few studies have investigated the dynamic changes in accessibility over time. Discussing parks' accessibility over relatively long-time scales has practical, innovative and theoretical values; because it can reveal correlational laws and internal influences not apparent in short term and provide reference and implications for parks' spatial equity.

This paper explores two museums in Taiwan, both former sites of incarceration, and asks how they reflect Taiwan’s evolving relationship with the past. Taiwan has successfully emerged from its authoritarian past into a democratic present; yet, it still bears the scars of its traumatic and violent history in the places where trauma and pain was exacted over Taiwanese people by different regimes. Two of these places are former prisons, now museums with common histories of incarceration, but very different approaches to presentation of traumatic pasts. This paper aims to understand the selective presentation of narratives of punishment in prison museums in Taiwan and what they reflect about Taiwan’s national identity.

This research used a qualitative ethnographic methodology, approaching prison museums as research sites with multidimensional textual, spatial and visual data. This study used a narrative ethnology approach to analyse the content, structure and social context surrounding the stories told about punishment at the sites.

While the Jingmei White Terror Memorial Park documents past abuses under the authoritarian Kuomindang Government (1945–1987), the narratives presented at the Chiayi Prison Museum, constructed under Japanese colonial rule (1895–1945), ignore past colonial violence. This study argues that the invisibility of past colonial violence in Chiayi prison museum acts to strengthen Taiwan’s multicultural national identity, while Jingmei WTMP acts to valorise political prisoners as heroic fighters for Taiwan’s democracy and human rights.

This research makes a contribution to the museum studies literature through extending understanding of the relationship between former carceral spaces and national identity projects.

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.

This study aims to explore the relationship between financing constraints and the innovation performance of Internet enterprises in the cross-border innovation cooperation network. The study also analyzes the moderating effect of the location of the cross-border innovation cooperation network.

The authors selected patent data, related transaction data and other data of A-share listed companies on Shanghai and Shenzhen stock exchanges from 2014 to 2019. The generalized moment estimation method of instrumental variables (IV-GMM) method was used to analyze the relationship between financing constraints and the innovation performance of Internet firms and the moderating effect of the cross-border innovation cooperation network location. The threshold value of the moderating effect of the network structure hole was calculated with the threshold model.

The empirical results show a significant inverted U-shaped relationship between financing constraints and the innovation performance in the cross-border innovation cooperation network of Internet enterprises. Network centrality positively moderates this relationship. There is a threshold for the adjustment effect of network-structural holes, and the adjustment intensity of structural holes changes before and after the threshold.

This study provides a new perspective for Internet firms in innovation cooperation networks to alleviate the negative impact of financing constraints on innovation performance. The inverted U-shaped relationship between financing constraints and the innovation performance of Internet enterprises is in two stages. The moderating range of network centrality and the structural hole besides the threshold of the moderating effect of a structural hole are detailed.

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.