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Despite the huge potential of social media, its functionality and impact for enhanced risk communication remain unclear. Drawing on dialogic theory by integrating both “speak from power” and “speak to power” measurements, the article aims to propose a systematic framework to address this issue.

The impact of social media on risk communication is measured by the correlation between “speak from power” and “speak to power” levels, where the former primarily spoke to two facets of the risk communication process – rapidness and attentiveness, and the latter was benchmarked against popularity and commitment. The framework was empirically validated with data relating to coronavirus disease (COVID-19) risk communication in 25,024 selected posts on 17 official provincial Weibo accounts in China.

The analysis results suggest the relationship between the “speak from power” and “speak to power” is mixed rather than causality, which confirms that neither the outcome-centric nor the process-centric method alone can render a full picture of government–public interconnectivity. Besides, the proposed interconnectivity matrix reveals that two provinces have evidenced the formation of government–public mutuality, which provides empirical evidence that dialogic relationships could exist in social media during risk communication.

The authors' study proposed a prototype framework that underlines the need that the impact of social media on risk communication should and must be assessed through a combination of process and outcome or interconnectivity. The authors further divide the impact of social media on risk communication into dialogue enabler, “speak from power” booster, “speak to power” channel and mass media alternative.

Measuring the performance of public participation is conducive to improving participation systems. However, such measurement, particularly in urban regeneration projects, is difficult because of the complex indicators and multiple stakeholders involved. The purpose of this paper is to measure the public participation level in urban regeneration projects in China.

This study adopts a perception difference-based method to measure the public participation level in urban regeneration projects in China. Specifically, an indicator system consisting of 12 indicators from three categories was first purposed. A perception difference-based method that integrates ANOVA test and Tukey test were then developed. The method was validated using five represented projects, and the results are interpreted based on a proposed measurement matrix.

Regardless of the type of indicator, the perception of the government aligns with the perception of private sector professions, however, deviates from the perception of citizens. By taking the mean score and the significance level among stakeholders of perception as two dimensions, different patterns of issues in the current participation practice in urban regeneration are manifested.

Theoretically, the proposed indicator system and perception difference-based method combined to provide a holistic view of public participation, which is verified to provide a better measurement. Practically, the authors’ methodology helps in revealing issues in current participation practice and further leading to designing coping strategies. Nonetheless, the proposed method requires further validation in participation practices in China and other countries.

By considering the perception mean and the significance level as two dimensions, a public participation measurement matrix is proposed. The performance in different indicators are classified into four stages accordingly, namely idling, starting, running-in and accelerating.

Presents suggested titles for libraries to obtain, selected from the 2001 Poets House Showcase at which 1,300 books of poetry from various publishers were displayed. Suggests a further source of information in this field.

The study aims to find out an appropriate volume of power to be procured through long-term power purchase agreements (PPAs), the volume to be sourced from the power exchange through day-ahead and term-ahead options and also a suitable volume to be sold at different points of time within a day, which would finally lead to the optimum cost of power procurement.

The study has considered a Delhi-based power distribution utility and has collected all relevant data from its archival sources. A stochastic optimization model has been developed to capture the problem of power procurement faced by the distribution utility, which is modelled as a mixed integer linear programming problem. Sensitivity analyses were carried out on the important parameters including hourly demand of power, unit variable cost of power available through PPAs, maximum back-down percentage allowed under PPAs, etc., to investigate their impact on daily cost of power under PPAs, daily cost of power under day-ahead and term-ahead options, daily sales revenue and also the net total daily cost of power procurement.

The findings include the appropriate volume of power procured from different suppliers through PPAs and from the power exchange under day-ahead and term-ahead options and also the surplus volume of power sold under the day-ahead arrangement. It has also computed the total cost of power purchased under PPAs, the cost of power purchased from the power exchange under day-ahead and term-ahead options and also the revenue generated out of the sale of surplus power under the day-ahead arrangement. In addition, it has also presented the results of sensitivity analyses, which provide rich managerial insights.

The paper makes two significant contributions to the existing body of power procurement literature. First, the stochastic mixed-integer linear programming model helps decision makers in determining the right volume of power to be purchased from different sources. Second, based on the findings of the procurement model, a power procurement framework is developed considering the dimensions of uncertainty in power supply and the cost of power procurement. This power procurement framework would aid managers in making procurement decisions under different scenarios.

COVID-19 and its precautions, including social distancing, have revolutionized traditional retailing- and consumption patterns. In this turbulent environment, the purpose of this study is twofold. First, this paper explores the direct effect of consumers’ internal/external health locus-of-control on their hygiene consciousness, which, in turn, affects their social distancing behavior. Second, this study posits that social distancing, in turn, impacts consumers’ current online grocery shopping behavior and their future online grocery shopping intentions, thus uncovering important insight.

To address these gaps, this paper develops a model that links consumers’ internal/external health locus-of-control to their adoption of e-tailing-based grocery services. Data collected through a web-based survey was analyzed by using partial least squares-based structural equation modeling.

The results indicate that consumers’ health locus-of-control indirectly affects the way they shop for their groceries during the pandemic. In particular, consumers’ internal (external) health locus-of-control drives higher (lower) hygiene consciousness and greater (lower) social distancing behavior. In turn, consumers’ online grocery shopping behavior was found to increase during the pandemic, with their corresponding intent to continue this behavior in the future. Moreover, this study finds the effects of consumers’ social distancing on their current grocery shopping behavior and future intentions to be contingent on consumer age, with stronger effects identified for older consumers.

This study shows how consumers’ internal/external health loci-of-control exert opposing effects on their social distancing behavior, as mediated by hygiene consciousness. Overall, the empirical analyzes corroborate the association of consumers’ social distancing- and online grocery shopping behavior (for consumers of different age profiles), both during and after the pandemic.

A higher-order Reissner-Mindlin plate element method is presented based on the framework of assumed stress quasi-conforming method and Hellinger-Reissner variational principle. A novel six-node triangular plate element is proposed by utilizing this method for the static and free vibration analysis of Reissner-Mindlin plates.

First, the initial assumed stress field is derived by using the fundamental analytical solutions which satisfy all governing equations. Then the stress matrix is treated as the weighted function to weaken the strain-displacement equations after the strains are derived by using the constitutive equations. Finally, the arbitrary order Timoshenko beam function is adopted as the string-net functions along each side of the element for strain integration.

The proposed element can pass patch test and is free from shear locking and spurious zero energy modes. Numerical tests show that the element can give high-accurate solutions, good convergence and is a good competitor to other models.

This work gives new formulations to develop high-order Reissner-Mindlin plate element, and the new strategy exhibits advantages of both analytical and discrete methods.

Aircraft structures are mainly connected by riveting joints, whose quality and mechanical performance are directly determined by vertical accuracy of riveting holes. This paper proposed a combined vertical accuracy compensation method for drilling and riveting of aircraft panels with great variable curvatures.

The vertical accuracy compensation method combines online and offline compensation categories in a robot riveting and drilling system. The former category based on laser ranging is aimed to correct the vertical error between actual and theoretical riveting positions, and the latter based on model curvature is used to correct the vertical error caused by the approximate plane fitting in variable-curvature panels.

The vertical accuracy compensation method is applied in an automatic robot drilling and riveting system. The result reveals that the vertical accuracy error of drilling and riveting is within 0.4°, which meets the requirements of the vertical accuracy in aircraft assembly.

The proposed method is suitable for improving the vertical accuracy of drilling and riveting on panels or skins of aerospace products with great variable curvatures without introducing extra measuring sensors.

As convenience and anonymity, people with mental illness are increasingly willing to communicate and share information through social media platforms to receive emotional and spiritual support. The purpose of this paper is to identify the degree of depression based on people's behavioral patterns and discussion content on the Internet.

Based on the previous studies on depression, the severity of depression is divided into four categories: no significant depressive symptoms, mild MDD, moderate MDD and severe MDD, and defined each of them. Next, in order to automatically identify the severity, the authors proposed social media digital cues to identify the severity of depression, which include textual lexical features, depressive language features and social behavioral features. Finally, the authors evaluate a system that is developed based on social media digital cues in the experiment using social media data.

The social media digital cues including textual lexical features, depressive language features and social behavioral features (F1, F2 and F3) is the relatively best one to classify four different levels of depression.

This paper innovatively proposes a social media data-based framework (SMDF) to identify and predict different degrees of depression through social media digital cues and evaluates the accuracy of the detection through social media data, providing useful attempts for the identification and intervention of depression.

The purpose of this paper is to examine a proposed model of location-based advertising (LBA) effectiveness upon the influence of integrative perceived values on consumers' attitude and behavioral responses in the immaturity of LBA in Vietnam.

A survey research method was utilized to collect data from mobile users. A real sample of 459 respondents was deemed and the Structural Equation Modeling (SEM) was applied to analyze data.

The results unveil that contextual offers, social facilitation, and advertising values have significantly positive effects on attitude; in turn, attitude mediates between these factors and purchase intention, information seeking and recommendation behaviors. Moreover, social facilitation is a significant stimulator of purchase intention. Otherwise, perceived encroached risk negatively impacts attitude.

Marketers should capture considerable attention to mobile natives' conscious awareness about a mechanism of tailoring their enthusiasm and behavioral responses at the embryonic stage of LBA growth in emerging countries like Vietnam.

This study fills the gap in the current literature by simultaneously exploring the importance of integrative perceived values to construct a hypothetical framework of consumers' responses and performance based on the uses and gratifications theory, inclusive perceived behavioral control derived from theory of planned behavior, associated with contextual value from the nature of LBA.

Aerospace assembly demands high drilling position accuracy for fastener holes. Hole position error correction is a key issue to meet the required hole position accuracy. This paper aims to propose a combined hole position error correction method to achieve high positioning accuracy.

The bilinear interpolation surface function based on the shape of the aerospace structure is capable of dealing with position error of non-gravity deformation. A gravity deformation model is developed based on mechanics theory to efficiently correct deformation error caused by gravity. Moreover, three solution strategies of the average, least-squares and genetic optimization algorithms are used to solve the coefficients in the gravity deformation model to further improve position accuracy and efficiency.

Experimental validation shows that the combined position error correction method proposed in this paper significantly reduces the position errors of fastener holes from 1.106 to 0.123 mm. The total position error is reduced by 43.49% compared with the traditional mechanics theory method.

The position error correlation method could reach an accuracy of millimeter or submillimeter scale, which may not satisfy higher precision.

The proposed position error correction method has been integrated into the automatic drilling machine to ensure the drilling position accuracy.

The proposed position error method could promote the wide application of automatic drilling and riveting machining system in aerospace industry.

A combined position error correction method and the complete roadmap for error compensation are proposed. The position accuracy of fastener holes is reduced stably below 0.2 mm, which can fulfill the requirements of aero-structural assembly.