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This study aims to integrate fall-protection function into the elderly clothing to meet both the daily life and fall-protection needs of the elderly people, thereby upgrading the performance of elderly clothing.

This study identified the design strategies of elderly clothing using an Extended Kansei Engineering methodology. Extended Kansei Engineering methodology is a new design framework developed from the traditional Kansei Engineering methodology to meet the design requirements of the product-service system. This study focuses on the product section of product-service system design. According to the product design process of the Extended Kansei Engineering methodology, this study first collected and organized the design elements and Kansei words of elderly clothing. Then a questionnaire was designed using Semantic Differential Scale. Finally, the questionnaire survey was conducted and the collected data was analysed to understand the consumption preferences of elderly people. A total of 399 elderly people aged 65 and older provided valuable design insights for this survey.

The research findings include the product design strategies for the development of elderly clothing, as well as a product prototype canvas and a product prototype elderly clothing developed based on the design strategies.

The research findings can provide competitive design strategies for the development of elderly clothing, thereby upgrading the performance of elderly clothing.

This elderly clothing integrates fall-protection function to reduce the risk of injury for elderly people due to falls, thereby helping society alleviate the medical and healthcare pressure caused by falls for elderly people.

The research findings can provide competitive design strategies for the development of elderly clothing. Furthermore, the Extended Kansei Engineering methodology introduced in this study can provide product and service designers with design methods that are more in line with the development trend of modern product-service system business models.

Live-streaming e-commerce is becoming a new way for many consumers to shop. During the live broadcast process, the interaction between anchors and customers plays a decisive role on consumers' purchasing decisions. This study aims to explore how two types of interaction between the anchor and the customers (i.e. task-oriented interaction and relationship-oriented interaction) affect customers' purchase decisions.

The study establishes a model based on online trust theory and multi-sensor interaction theory. To validate the model, we carried out five simulated live-streaming events and collected data through a scenario-based survey of the viewers participating in the live-streaming (N = 244). Structural equation modeling was employed to test the hypotheses.

Both task-oriented interaction and relationship-oriented interaction have a positive impact on users' purchase decisions through the mediation of virtual touch, emotional trust and cognitive trust. Sense of power has opposite moderating effects on the impacts of relationship-oriented interaction on emotional trust and cognitive trust.

This study enriches the theory of live-streaming e-commerce by demonstrating the decisive roles of two types of anchor–customer interaction, the mediation roles of virtual touch, cognitive trust, and emotional trust in customer purchase decisions, as well as the moderating effect of sense of power on customer decision-making processes. The findings provide practical insights for anchors and live-streaming platforms about how they should arrange live-streaming content to enhance consumer purchasing decisions.

This study aims to evaluate the structural oil shocks effect on stock returns of Indian renewable energy companies across market conditions.

This study applies the structural vector autoregression model to estimate sources of oil shocks such as oil supply shock, aggregate demand shock and oil price-specific demand shock. In the next step, the panel quantile regression model estimates the effect of these oil shocks on stock return across market conditions. Monthly data are collected from January 2009 to December 2019. All renewable energy companies listed on the National Stock Exchange of India are considered for the analysis.

In the whole sample analysis, this study finds that oil shocks negatively affect stock returns in most of the market conditions except oil price-specific demand shock. In sub-groups, oil shocks driven by supply and aggregate demand also negatively affect stock return in most market conditions. This study finds the positive interaction of oil price-specific demand shock. A majority of these positive interactions happen in bearish market conditions. In the whole sample, the asymmetric effects of shocks driven from oil supply and oil price-specific demand are seen in most quantiles or market conditions. At the same time, aggregate demand shock does not affect asymmetrically. In the sub-group analysis, standalone renewable energy companies stock returns are least asymmetrically affected by these oil shocks. The asymmetries of oil supply-driven shock on stock returns of the renewable energy sub-group companies are found in most quantiles.

First, this is a company-level study of the stock returns response to the structural oil shocks in the renewable energy sector. Second, to the best of the authors’ knowledge, this type of study is the first in the Indian context. Third using panel quantile regression model along with capital asset pricing model framework, the authors investigate these effects across market conditions.

An investigation was conducted into the impact of various process parameters on the surface and subsurface quality of glass-ceramic materials, as well as the mechanism of material removal and crack formation, through the use of ultrasonic-assisted grinding.

A mathematical model of crack propagation in ultrasonic-assisted grinding was established, and the mechanism of crack formation was described through the model. A series of simulations and experiments were conducted to investigate the impact of process parameters on crack depth, surface roughness, and surface topography during ultrasonic-assisted surface and axial grinding. Additionally, the mechanism of crack formation was explored.

During ultrasonic-assisted grinding, the average grinding forces are between 0.4–1.0 N, which is much smaller than that of ordinary grinding (1.0–3.5 N). In surface grinding, the maximum surface stresses between the workpiece and the tool gradually decrease with the tool speed. The surface stresses of the workpiece increase with the grinding depth, and the depth of subsurface cracks increases with the grinding depth. With the increase of the axial grinding speed, the subsurface damage depth increases. The roughness increases from 0.780um/1.433um.

A mathematical model of crack propagation in ultrasonic-assisted grinding was established, and the mechanism of crack formation was described through the model. The deformation involved in the grinding process is large, and the FEM-SPH modeling method is used to solve the problem that the results of the traditional finite element method are not convergent and the calculation efficiency is low.

The objective of this study is to investigate the interaction effect between incentive type (financial and compassionate incentives) and the ethicality of merchant strategy on consumer willingness to post positive reviews, while also examining potential variations in consumer responses based on consumption experience, shopping frequency and social class.

Building upon construal level theory, we hypothesized the moderating influence of the ethicality of merchant strategy and examined the three-way interaction among consumers’ demographic characteristics (i.e. consumption experience, shopping frequency and social class), incentive type and the ethicality of merchant strategy. To empirically test our hypotheses, we conducted four experiments and employed ANOVA for data analysis.

The ethicality of merchant strategies moderates the association between incentive type and consumer willingness to post positive reviews, with compassionate incentives eliciting more pronounced moral judgments toward merchant strategies compared to financial incentives. The moderating effect of the ethicality of merchant strategy on the relationship between incentive type and consumer willingness to post positive reviews is particularly strong among consumers who have favorable consumption experiences, engage in frequent shopping and belong to lower social classes.

This study contributes to the existing literature on online reviews by examining the impact of compassionate incentives on consumer review behaviors, analyzing the ethicality of merchant strategies within the realm of online reviews and investigating variations in consumer responses to merchant strategies regarding consumption experience, shopping frequency and social class.

This study aims to explore why Chinese consumers pay for digital content products by investigating the experiences of Chinese consumers living in first-tier and second-tier cities regarding paid digital knowledge products.

A total of 19 in-depth interviews were conducted to collect data, and the phenomenological reduction was adopted to analyze data.

This study reveals that Chinese consumers use paid digital knowledge products to alleviate stress and anxiety stemming from real-life competition and the fear of falling behind. While consumers acknowledge the limited assistance that paid knowledge products can offer, their acceptance and expectations of paid digital knowledge products remain positive.

Paid digital knowledge represents an innovative phenomenon, with few scholars outside China having studied it. This study contributes a conceptual framework to understand the motivations of Chinese consumers with high purchasing power residing in first-tier and second-tier cities to invest in digital content.

Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.

Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.

In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.

The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.

Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.

The success of public–private partnership (PPP) projects is highly correlated to the successful management of risks encountered during the operation phase. PPP projects are especially exposed to risk due to the long operation period over which revenues need to be generated to recoup substantial initial investment and operational running costs. Despite the critical impact of risk exposure, limited research has been specifically undertaken on the matter of operational risk management. This study seeks to address this oversight by identifying and evaluating operational risk management strategies for PPPs.

Vulnerability theory is the theoretical lens used, with context drawn from Chinese PPP projects. Based on the data collected from expert interviews and questionnaires, 28 operational risk management strategies are identified. A fuzzy synthetic method is employed to analyze the effectiveness of the 28 strategies.

The findings reveal that providing an exit mechanism clause into the contract, establishing a comprehensive performance evaluation mechanism and developing a clear compensation mechanism are the top three effective strategies. This study also reveals that risk mitigation approaches that reduce vulnerability prove more effective than attempts to reduce external threats. Specifically, strategies aimed at managing contract, political, technical and financial risk are the most effective.

The findings of this study extend current knowledge regarding the risk management of PPP projects. They also offer a reference by which practitioners may select effective operational risk management pathways and thereby, galvanize the sustainable development of PPPs.

This paper aims to compare the aging behavior of water-based coatings and solvent-based coatings in sulfuric acid environments and to discuss the related mechanism.

A sulfuric acid solution with a concentration of 5 Wt.% was selected for immersion test at 23°C. The failure behavior of the coating was studied by combining the transformation rules of the macroscopic morphology and basic properties with the results of electrochemical impedance spectrum analysis.

The results showed that the surface smoothness of the water-based coating was lower than that of the solvent-based coating. The glossiness, thickness and hardness of the water-based coating exhibited more significant changes. The electrochemical test also indicated that the water-based coating was infiltrated by a large number of corrosive media, which may have induced corrosion under the coating. In contrast, the solvent-based coating showed good shielding properties, but the adhesion was seriously affected by the corrosive medium.

This work clarified the difference of failure behavior and mechanism between water-based coatings and solvent-based coatings in acidic environment and provided a theoretical basis for the selection and mechanism research of anticorrosive coatings.

Drawing on appraisal theory of emotion, this study aims to establish and test a moderated mediation model underlying the process of exploitative leadership by investigating the mediating role of job anxiety and the moderating role of psychological entitlement.

We collected two-wave questionnaire data from 355 supervisors with matched responses from 1,065 subordinates in Hubei province of China. Hierarchical multiple regression and PROCESS macro were applied to test our hypotheses.

The results indicated that supervisor perceived overqualification prompted supervisor job anxiety, which then led to raised exploitative leadership. Additionally, we found that supervisor psychological entitlement intensified the direct effect of supervisor perceived overqualification on supervisor job anxiety as well as the indirect effect of supervisor perceived overqualification on exploitative leadership through supervisor job anxiety.

Although researchers have documented a growing number of consequences of exploitative leadership, less focus has been placed on its antecedents. The study extends our understanding of why, how and when supervisors engage in exploitative behaviors.