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In the brain imaging based on electrical impedance tomography, it is sometimes not able to attach 16 electrodes due to space restriction caused by craniotomy. As a result of this, the number of boundary measurements decreases, and spatial resolution of reconstructed conductivity distribution is reduced. The purpose of this study is to enhance reconstruction quality in cases of limited measurement.

A new data expansion method based on the shallow convolutional neural network is proposed. An eight-electrode model is built from which fewer boundary measurements can be obtained. To improve the imaging quality, shallow convolutional neural network is constructed which maps limited voltage data of the 8-electrode model to expanded voltage data of a quasi-16-electrode model. The predicted data is compared with the quasi-16-electrode data. Besides, image reconstruction based on L1 regularization method is conducted.

The results show that the predicted data generally coincides with the quasi-16-electrode data. It is found that images reconstructed with the data of eight-electrode model are the poorest. Nevertheless, imaging results when the limited data is expanded by the proposed method show large improvement, and there is a minor difference with the images recovered with the quasi-16-electrode data. Also, the impact of noise is studied, which shows that the proposed method is robust to noise.

To enhance reconstruction quality in the case of limited measurement, a new data expansion method based on the shallow convolutional neural network is proposed. Both simulation work and phantom experiments have demonstrated that high-quality images of cerebral hemorrhage and cerebral ischemia can be obtained when the limited measurement is expanded by the proposed method.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

The purpose of this paper is to investigate the impact of design features in in-feed advertising on its effectiveness. Previous research on various forms of advertising has demonstrated that design features can influence advertising effectiveness. However, given the distinct presentation mode and content of in-feed advertising compared to traditional forms, it is crucial to examine whether the effects of design features differ for this type of advertising. Through two studies, we examined how five specific design features affect consumers' purchase intention within the context of in-feed advertising. The mediating role of perceived value and the moderating role of product involvement are also proved.

Using the methods of online survey and online experiment, the author conducted two empirical studies. In study 2, the authors adopted the orthogonal array design to simplify experimental grouping.

The findings demonstrate that akin to conventional Internet advertising, the informational content, credibility and entertainment value of in-feed advertising exert a positive influence on its efficacy. Notably, the interactive nature of in-feed advertising significantly enhances users' inclination toward making purchases. Conversely, any form of interference can detrimentally impact its utility.

The study demonstrates five design characteristics that may impact the effectiveness of in-feed advertising, expanding the relevant theories about in-feed advertising. At the same time, this study contributes to the understanding of consumer responses to advertising. However, the two studies in this paper are conducted within the framework of WeChat, a popular Chinese social media platform, with the participants consisting exclusively of Chinese users.

Considering the rapid development of in-feed advertising in terms of quantity, content and form, the author believes that the results of this paper can help advertisers in their design thinking. The moderating effect of product involvement can be applied to optimize personalized advertising delivery schemes.

This paper focuses on a practical problem, that is, how to improve the effectiveness of in-feed advertising by modifying advertising design features.

This study aims to investigate the effect of high-performance HR practices (HPHRP) on the innovative work behaviour (IWB) of employees. Drawing on social exchange theory, when employees perceive their exchange relationship in terms of HPHRP and leadership support as fair, we hypothesize that employees will demonstrate greater IWB. However, drawing on social identity theory, we hypothesize that when the attitude of employees towards their employer with best employer practices is favourable, the impact of HPHRP mediated by organizational pride and organizational identification, has a greater impact on employee IWB.

Survey research was used to empirically validate the study involving employees (n = 370) who belong to the best employer brands in India. The data was analysed using Process Macro Models 7 for moderated mediation and Model 6 for serial mediation using bootstrapping procedures.

The results suggest that perceived leadership support moderated the indirect effect of HPHRP on IWB through organizational pride. Again, organizational pride and identification partially and serially mediated the impact of HPHRP on IWB.

Organizations must invest in HPHRP, with supportive leadership practices that can foster an emotional attitude of pride and a cognitive attitude of organizational identification to be an employer of choice resulting in employees’ IWB.

The study investigating the mediating impact of the emotional and cognitive attitudes of pride and organizational identification has not been previously explored, in the relationship between HPHRP and IWB, from a social identity perspective.

Learning from safety accidents and sharing safety knowledge has become an important part of accident prevention and improving construction safety management. Considering the difficulty of reusing unstructured data in the construction industry, the knowledge in it is difficult to be used directly for safety analysis. The purpose of this paper is to explore the construction of construction safety knowledge representation model and safety accident graph through deep learning methods, extract construction safety knowledge entities through BERT-BiLSTM-CRF model and propose a data management model of data–knowledge–services.

The ontology model of knowledge representation of construction safety accidents is constructed by integrating entity relation and logic evolution. Then, the database of safety incidents in the architecture, engineering and construction (AEC) industry is established based on the collected construction safety incident reports and related dispute cases. The construction method of construction safety accident knowledge graph is studied, and the precision of BERT-BiLSTM-CRF algorithm in information extraction is verified through comparative experiments. Finally, a safety accident report is used as an example to construct the AEC domain construction safety accident knowledge graph (AEC-KG), which provides visual query knowledge service and verifies the operability of knowledge management.

The experimental results show that the combined BERT-BiLSTM-CRF algorithm has a precision of 84.52%, a recall of 92.35%, and an F1 value of 88.26% in named entity recognition from the AEC domain database. The construction safety knowledge representation model and safety incident knowledge graph realize knowledge visualization.

The proposed framework provides a new knowledge management approach to improve the safety management of practitioners and also enriches the application scenarios of knowledge graph. On the one hand, it innovatively proposes a data application method and knowledge management method of safety accident report that integrates entity relationship and matter evolution logic. On the other hand, the legal adjudication dimension is innovatively added to the knowledge graph in the construction safety field as the basis for the postincident disposal measures of safety accidents, which provides reference for safety managers' decision-making in all aspects.

Amidst the growing emphasis on privacy protection, this study aims to investigate how online interaction introduced in Lead Generation Ads (LGAs) affects consumers' Self-Disclosure Intention (SDI), particularly in the context of the Chinese advertising market.

This research employs two scenario-based online surveys to analyse in depth the impact of LGAs on consumers' SDI. The first study collects valid feedback from 220 consumers through an online questionnaire to assess the direct effect of perceived interactivity on SDI. The second study, using an experimental design with a sample of 265 participants, further explores the mediating roles of perceived control and perceived vulnerability in the relationship between perceived interactivity and SDI and examines the moderating effect of privacy invasion experience (PIE).

This study reveals the significant and positive influence of perceived interactivity on SDI, with perceived control acting as a mediator that enhances this effect. Conversely, perceived vulnerability weakens the positive impact of perceived interactivity on SDI. Additionally, we explore the moderating role of PIE and find that it significantly influences the relationship between perceived interactivity and SDI. These findings underscore the importance of considering consumer privacy sensitivity, particularly in the design of interactive marketing strategies and within highly interactive advertising environments.

Our research uncovers consumer privacy attitudes and behaviours in the Chinese market, providing insights into its unique dynamics of privacy and information disclosure. However, the geographical and cultural specificity of our study may limit its generalizability. Future studies should expand into various cultural and market contexts, considering the impact of digital technologies on consumer interactions and information disclosure, thereby enhancing the depth and applicability of global marketing strategies.

Advertising platforms should explore online interactive communication methods to enhance consumers' perceived interactions and alleviate privacy concerns. Also, platforms should be designed with system security in mind to prevent the leakage and misuse of consumer data, thus increasing consumers' SDI.

The study provides insights for marketers on designing more effective and privacy-sensitive online advertising strategies in the Chinese market. Understanding the factors influencing consumers’ willingness to share personal information can lead to more effective engagement in digital marketing campaigns.

By integrating interactivity theory with privacy computing theory, this research provides a new perspective on the role of online interaction in consumer privacy protection and information disclosure decisions. The findings not only enrich the theoretical frameworks of interactive marketing and privacy protection but also offer empirical support for marketing practitioners in regard to designing interactive advertising strategies, especially balancing consumer privacy protection with the enhancement of shopping intentions.

Currently, engineering project design lacks a design framework that fully combines subjective experience and objective data. This study develops an aided design decision-making framework to automatically output the optimal design alternative for engineering projects in a more efficient and objective mode, which synthesizes the design experience.

A database of design components is first constructed to facilitate the retrieval of data and the design alternative screening algorithm is proposed to automatically select all feasible design alternatives. Then back propagation (BP) neural network algorithm is introduced to predict the cost of all feasible design alternatives. Based on the gray relational degree-particle swarm optimization (GRD-PSO) algorithm, the optimal design alternative can be selected considering multiple objectives.

The case study shows that the BP neural network-cost prediction algorithm can well predict the cost of design alternatives, and the framework can be widely used at the design stage of most engineering projects. Design components with low sensitivity to design objectives have been obtained, allowing for the consideration of disregarding their impacts on design objectives in such situations requiring rapid decisions. Meanwhile, design components with high sensitivity to design objective weights have also been obtained, drawing special attention to the effects of changes in the importance of design objectives on the selection of these components. Simultaneously, the framework can be flexibly adjusted to different design objectives and identify key design components, providing decision reference for designers.

The framework proposed in this paper contributes to the knowledge of design decision-making by emphasizing the importance of combining objective data and subjective experience, whose significance is ignored in the existing literature.

Drawing from resource orchestration theory, this research proposed an integrative model that leverages insights into counter resource constraints and uncertainty in start-up business model innovation (BMI). It investigated the influences of entrepreneurial networks and effectuation on BMI through bricolage in uncertain environments.

The research surveyed 481 start-ups in China. LISREL 8.80 and SPSS 22.0 were employed to test the validity and reliability of key variables, respectively. Additionally, hypotheses were examined through multiple linear regression.

First, entrepreneurial networks and effectuation were positively related to BMI, and combining these two factors improved BMI for start-ups. Second, bricolage contributed to BMI and played mediating roles in translating entrepreneurial networks and effectuation into BMI. Third, environmental uncertainty weakened the linkage between bricolage and BMI.

Future research should replicate the results in other countries because only start-ups in China were investigated in the study, and it is necessary to extend this research by gathering longitudinal data. This research emphasized the mediating effects of bricolage and the moderating influence of environmental uncertainty, and new potential mediating and moderating factors should be explored between resources and BMI.

There are three significant theoretical contributions. First, the findings enrich the literature on the complex antecedents of BMI by combining the impacts of entrepreneurial networks and effectuation. Second, an overarching framework is proposed explaining how bricolage (resource management) links entrepreneurial networks and effectuation and BMI. Third, it demonstrates the significance of environmental uncertainty in the bricolage–BMI linkage, deepening the understanding of the bricolage boundary condition.

The primary purpose of this study is not only to examine the connections between self-determined motivation, attitudes toward change and participation in change, but also to explore the moderating impact of perceived organizational support on organizational change, and the mediating role of attitudes toward change in the link between perceived competence and participation in change.

The data were collected from one semiconductor manufacturing company (study 1) and one logistics service company (study 2). Employees who experienced organizational change before were invited to finish the survey. The partial least squares-structural equation modelling (PLS-SEM) technique and SPSS PROCESS (model 14) were utilized to analyze the data.

The study findings indicated that the perceived autonomy and relatedness were positively connected with perceived competence, which in turn would lead to better attitude toward change. Additionally, it was found that the perceived competence and attitude toward change would positively predict participation in change. More importantly, perceived organizational support would reinforce the positive relationship between attitude toward change and participation in change.

Although there are many organizational change reports, relatively little attention has been paid not only to the mediating role of attitudes toward change in the implication of organizational change but also to the moderating impact of perceived organizational support on the final success of organizational change.

: 本研究的主要目的, 除了探討自決動機和對變革的態度兩者與參與變革的關係;也探究組織支持感對組織變革所起的緩和作用, 以及對變革的態度在感知的才能和參與變革兩者的關聯上所起的調節作用。

: 有關的數據取自一間半導體製造商 (研究一) 和一間物流服務公司 (研究二) 。 曾體驗過組織變革的僱員被邀參與一項調查, 研究人員採用結構方程模式: 偏最小平方法 PLS-SEM、以及SPSS PROCESS (模型14), 來分析調查得來的數據。

: 研究結果顯示、感知的自主和關聯性兩者與感知的才能有正關聯的關係, 而這反過來則會引來對變革有較良好的態度。研究結果亦顯示、感知的才能和對變革的態度兩者均能積極預測變革的參與;更重要的是、組織支持感會強化對變革的態度與參與變革之間的正關聯。

: 雖然有關組織變革的研究報告唯數不少, 惟於組織變革上的啟示而言, 探討對變革的態度所起的調節作用的研究實唯數不多, 而且、探討組織支持感對組織變革能否最終成功所起的緩和作用的研究似頗稀少。

While prior studies predominantly focus on the overall impact of digital transformation on environmental, social and governance (ESG) performance, this study employs dynamic capability theory to examine two different dimensions of digital transformation, namely digital transformation quantity and digital transformation structure, and how they influence the ESG performance of enterprises. The mediating roles of social attention and green innovation are investigated to further explore the underlying mechanisms.

The authors apply fixed effects models and empirically test the hypotheses using samples of Chinese A-share listed companies from 2011 to 2020. In addition, difference-in-differences and instrumental variable methods are used in the robustness test.

When digital transformation is categorized into quantity and structure, the impact mechanisms are found to be distinct. Externally, digital transformation quantity attracts social attention, aiding enterprises in evolutionary adaptability and acquiring resources to support ESG practices. Internally, digital transformation structure fosters green innovation, enabling enterprises to overcome technical obstacles and harness technology’s potential to enhance their ESG performance.

This study contributes to the current knowledge by differentiating digital transformation into quantity and structure, which helps to further explore the mechanism of digital transformation on ESG and address the research gap. Meanwhile, the concept of adaptability in the dynamic capability theory is employed to construct the model, offering a deeper perspective and expanding the theory. This nuanced investigation of the mediating effects of social attention and green innovation elucidates how different dimensions of digital transformation contribute to the development and utilization of dynamic capabilities, thereby enhancing enterprises’ ESG performance.