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This paper aims to conduct an empirical study to investigate whether an industry’s position affects the transmission of information and economic shocks.

This paper conducts an empirical study of inventory performance based on a large panel of 71 industries in the manufacturing, wholesale and retail sectors over a 10-year period (2007–2016).

It is found that the position of a focal industry in the supply chain network moderates the impacts of macroeconomic uncertainty shocks and shocks from supplier/customer industries on the focal industry’s inventory. On the one hand, more central industries are more sensitive to macroeconomic uncertainty shocks as well as spillover shocks from their supplier and customer industries. On the other hand, uncertainty shocks from more central industries have higher impact on their partner industries than those from less central industries.

A manager needs to take into account the network positions of suppliers/customers in supply network when making inventory decisions. For example, when sharing information with partners, the network position of a partner affects how important its information is.

The key novelty of this paper is the introduction of network structure that represents the supplier–customer relationships in the entire economy, and the modeling of uncertainty shocks transmitted through the supply chain network.

This study aims to investigates the influence of proactive personality on employee radical creativity through transformational leadership, professional ethical standards and creative self-efficacy.

The data were collected from 343 superior–subordinate dyads in China. A confirmatory factor analysis was performed to measure the validity of the variables. A regression analysis was performed to assess the relationship between model assumptions.

The results showed that: (1) Proactive personality was positively related to employee radical creativity. (2) Transformational leadership and professional ethical standards moderated the relationship between proactive personality and radical creativity. Specifically, the relationship between proactive personality and employee radical creativity was strong, as expected. It was the strongest in the presence of high transformational leadership and high professional ethical standards. (3) Creative self-efficacy acted as a mediator in this interaction.

This study is a pioneering investigation in the Chinese context. It empirically examines the interactive relationship between proactive personality and radical creativity through transformational leadership and professional ethical standards. Additionally, it substantiates creative self-efficacy as the psychological mechanism behind this interaction. Consequently, this study offers a comprehensive framework with potential implications for personality assessments in the workplace, leadership training, criteria formulation and enhancement of radical creativity.

In 2020, an outbreak of Salmonella Stanley linked to imported dried wood ear mushrooms affected 55 individuals in the United States of America. These mushrooms, commonly used in Asian cuisine, require processing, like rehydration and cutting, before serving. The US Centres for Disease Control and Prevention advise food preparers to use boiling water for rehydration to inactivate vegetative bacterial pathogens. Little is known about how food handlers prepare this ethnic ingredient and which handling procedures could enable Salmonella proliferation.

This study used content analysis to investigate handling practices for dried wood ear mushrooms as demonstrated in YouTube recipe videos and to identify food safety implications during handling of the product. A total of 125 Chinese- and English-language YouTube videos were analysed.

Major steps in handling procedures were identified, including rehydration, cutting/tearing and blanching. Around 62% of the videos failed to specify the water temperature for rehydration. Only three videos specified a water temperature of 100 °C for rehydrating the mushrooms, and 36% of the videos did not specify the soaking duration. Only one video showed handwashing, cleaning and sanitising of surfaces when handling the dried wood ear mushrooms.

This study found that most YouTube videos provided vague and inconsistent descriptions of the rehydration procedure, including water temperature and soaking duration. Food preparers were advised to use boiling water for rehydration to inactivate vegetative bacterial pathogens. However, boiling water alone is insufficient to inactivate all bacterial spores. Extended periods of soaking and storage could be of concern for spore germination and bacterial growth. More validation studies need to be conducted to provide guidance on how to safely handle the mushrooms.

This study will make a distinctive contribution to the field of food safety by being the first to investigate the handling procedure of a unique ethnic food ingredient, dried wood ear mushrooms, which has been linked to a previous outbreak and multiple recalls in the United States of America. The valuable data collected from this study can help target food handling education as well as influence future microbial validation study design and risk assessment.

Given the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity recommendation. Therefore, this study investigates the impact of UGC on purchase decisions and proposes new recommendation models based on sentiment analysis, which are verified in Douban, one of the most popular UGC websites in China.

After verifying the relationship between various factors and product sales, this study proposes two models, collaborative filtering recommendation model based on sentiment (SCF) and hidden factors topics recommendation model based on sentiment (SHFT), by combining traditional collaborative filtering model (CF) and hidden factors topics model (HFT) with sentiment analysis.

The results indicate that sentiment significantly influences purchase intention. Furthermore, the proposed sentiment-based recommendation models outperform traditional CF and HFT in terms of mean absolute error (MAE) and root mean square error (RMSE). Moreover, the two models yield different outcomes for various product categories, providing actionable insights for organizers to implement more precise recommendation strategies.

The findings of this study advocate the incorporation of UGC sentimental factors into websites to heighten recommendation accuracy. Additionally, different recommendation strategies can be employed for different products types.

This study introduces a novel perspective to the recommendation algorithm field. It not only validates the impact of UGC sentiment on purchase intention but also evaluates the proposed models with real-world data. The study provides valuable insights for managerial decision-making aimed at enhancing recommendation systems.

The paper aims to tackle the classification of Remote Sensing Images (RSIs), which presents a significant challenge for computer algorithms due to the inherent characteristics of clustered ground objects and noisy backgrounds. Recent research typically leverages larger volume models to achieve advanced performance. However, the operating environments of remote sensing commonly cannot provide unconstrained computational and storage resources. It requires lightweight algorithms with exceptional generalization capabilities.

This study introduces an efficient knowledge distillation (KD) method to build a lightweight yet precise convolutional neural network (CNN) classifier. This method also aims to substantially decrease the training time expenses commonly linked with traditional KD techniques. This approach entails extensive alterations to both the model training framework and the distillation process, each tailored to the unique characteristics of RSIs. In particular, this study establishes a robust ensemble teacher by independently training two CNN models using a customized, efficient training algorithm. Following this, this study modifies a KD loss function to mitigate the suppression of non-target category predictions, which are essential for capturing the inter- and intra-similarity of RSIs.

This study validated the student model, termed KD-enhanced network (KDE-Net), obtained through the KD process on three benchmark RSI data sets. The KDE-Net surpasses 42 other state-of-the-art methods in the literature published from 2020 to 2023. Compared to the top-ranked method’s performance on the challenging NWPU45 data set, KDE-Net demonstrated a noticeable 0.4% increase in overall accuracy with a significant 88% reduction in parameters. Meanwhile, this study’s reformed KD framework significantly enhances the knowledge transfer speed by at least three times.

This study illustrates that the logit-based KD technique can effectively develop lightweight CNN classifiers for RSI classification without substantial sacrifices in computation and storage costs. Compared to neural architecture search or other methods aiming to provide lightweight solutions, this study’s KDE-Net, based on the inherent characteristics of RSIs, is currently more efficient in constructing accurate yet lightweight classifiers for RSI classification.

Building information modelling (BIM) has transformed the traditional practices of the Architecture, Engineering and Construction (AEC) industry. BIM creates a collaborative digital representation of built environment data. Competitive advantage can be achieved with collaborative project delivery and rich information modelling. Despite the abundant benefits, BIM’s adoption in the AEC is susceptible to confrontation. A substantial impediment to BIM adoption often cited is data interoperability. Other facets of interoperability got limited attention. Other academic areas, including information systems, discuss the interoperability construct ahead of data interoperability. These interoperability factors have yet to be surveyed in the AEC industry. This study aims to investigate the effect of interoperability factors on BIM adoption and develop a comprehensive BIM adoption model.

The theoretical foundations of the proposed model are based on the European interoperability framework (EIF) and technology, organization, environment framework (TOE). Quantitative data collection from construction firms is gathered. The model has been thoroughly examined and validated using partial least squares structural equation modelling in SmartPLS software.

The study’s findings indicate that relative advantage, top management support, government support, organizational readiness and regulation support are determinants of BIM adoption. Financial constraints, complexity, lack of technical interoperability, semantic interoperability, organizational interoperability and uncertainty are barriers to BIM adoption. However, compatibility, competitive pressure and legal interoperability do not affect BIM adoption.

Finally, this study provides recommendations containing the essential technological, organizational, environmental and interoperability factors that AEC stakeholders can address to enhance BIM adoption.

To the best of the authors’ knowledge, this paper is one of the first studies to combine TOE and EIF in a single research model. This research provides empirical evidence for using the proposed model as a guide to promoting BIM adoption. As a result, the highlighted determinants can assist organizations in developing and executing successful policies that support BIM adoption in the AEC industry.

This paper aims to analyze the potentials of dynamic, commitment and revenue-sharing contracts; that a nonrebate offering manufacturer can use to safeguard his profit while his competitor offers customer rebates in a supply chain consisting of two manufacturers and a common retailer.

We consider a two-period supply chain model to explore optimal decisions under eight possible scenarios based on the contract and rebate offering decisions. Because the manufacturers are selling substitutable products, therefore, a customer rebate on one of the products negatively impacts the selling quantity of other. Optimal price, rebate, and quantities are examined and compared to explore the strategic choice for both the rebate offering and non-rebate offering manufacturer. Comparative evaluation is conducted to pinpoint how the parameters such as contract parameters and its nature affect the members.

The results demonstrate that all these contracts instigate the rebate offering manufacturer to provide a higher rebate, but do not ensure a higher profit. If the revenue sharing contract is offered to the common retailer, the effectiveness of the rebate program might reduce significantly, and the rebate offering manufacturer might receives lower profits. A non-rebate offering manufacturer might use a commitment contract to ensure higher profits for all the members and make sure the common retailer continues the product.

The effect of customer rebate vs. supply chain contract under competition has not yet been explored comprehensively. Therefore, the study contributes to the literature regarding interplay among pricing decision, contract choice and rebate promotion in a two-period setting. The conceptual and managerial insights contribute to a better understanding of strategic decision-making for both competing manufacturers under consumer rebates.

While providing users with important innovation resources, an enterprise's open innovation community also encounters numerous challenges. The purpose of this study is to develop and implement a set of evaluation systems that can identify the ecological characteristics of open innovation communities. The ultimate goal is to provide guidance for the construction and establishment of these communities.

Firstly, from the perspective of information ecology, according to the connotation requirements of the four information elements of “people, information, technology and environment” in the information ecosystem, this paper determines the evaluation indicators of enterprise's open innovation community from the aspects of integrity and dynamics. Then, based on the improved analytic hierarchy process, the weight of each index is calculated, and a complete evaluation system of open innovation community is established. Finally, the fuzzy comprehensive evaluation method is used to conduct empirical research on Haier Open Partnership (HOPE) platform, analyze its ecological situation and existing problems and put forward the corresponding construction recommendations.

The application of HOPE platform shows that the evaluation index system built in this study has good applicability, and the whole research process and research method have certain reference value for future studies. At the same time, the study found that the HOPE platform has good ecological characteristics, but there are also some problems. This study can directly promote the construction of the platform.

This paper, for the first time, combines the information ecology theory with the open innovation community. The results demonstrate that the open innovation community is an information ecosystem, which can be evaluated ecologically. Furthermore, to ensure the calculation's scientific accuracy, the index weight is determined by constructing a judgment matrix based on expert questionnaires.

The aim of this paper is to research the acceptance mechanism of building information modeling (BIM) technology and to explore the differences among Architecture/Engineering/Construction (A/E/C) professionals with different individual characteristics. The proposed acceptance mechanism of BIM technology is intended to be used by industry stakeholders to propose decisions and measures, and improve the degree of BIM adoption.

Traditional hypothesis testing is adopted by the current study to empirically research the specific mechanism of A/E/C professionals accepting BIM technologies. In the one phase, a conceptual model based on technology acceptance model (TAM) and technology organization environment (TOE) theory was established and a large-scale questionnaire survey was conducted. In the other phase, structural equation modeling (SEM) was used to analyze acquired sample data, so as to empirically test the validity of the proposed linkage.

The results show first that perceived ease of use has no significant influence on perceived usefulness, and perceived usefulness has no significant effect on behavior intention as well. Second, BIM technical features and government BIM policies have positive effects on perceived usefulness, BIM technical features and organization supports have positive effects on perceived ease of use. Third, the BIM acceptance mechanism of A/E/C professionals is diverse from respondents with different characteristics, e.g. regions and working time.

The authors highlight the large sample size, as well as the nationwide context, of the questionnaire survey. Meanwhile, acceptance differences among A/E/C professionals with different demographic characteristics have been clarified using profound data and t-test. The findings of this study enrich the research on the acceptance mechanism of BIM technology, and contribute to relevant stakeholders taking targeted measures to promote the effective application of BIM technology nationwide.

This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.

This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.

Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.

Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.

A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.

Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.

The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.