Search results

This paper aims to draw upon motivated information processing theory to examine the sequential mediating roles of perspective taking and boundary spanning between transformational leadership and the creative performance of knowledge workers.

The study was carried out on a sample, including a dyad of 398 knowledge workers and their immediate supervisors in four research institutes in southwest China. The authors tested the theoretical model using structural equation modeling (SEM) and Mplus 7.0 software.

The results support the mediation model in which perspective taking was found to significantly and positively mediate the relationship between transformational leadership and boundary spanning. Boundary spanning was found to significantly and positively mediate the relationship between perspective taking and creative performance. Moreover, both perspective taking and boundary spanning were found to mediate the relationship between transformational leadership and creative performance.

The study findings imply that the transformational leadership behaviors of managers or supervisors nurture knowledge workers' perspective taking and their boundary spanning activities leading to creative performance.

The findings contribute new knowledge to the relationship between transformational leadership and creative performance by uncovering the causal chain of a cognitive mechanism (perspective taking) with a behavioral mechanism (boundary spanning).

The representation of Heterogeneous Object (HO) is divided into two categories: Data model (DM) and material evaluation paradigm (MEP). A hybrid methodology with geometry model and volumetric dataset to represent heterogeneous properties is proposed in this paper. Geometry model of an object can guarantee the accuracy of the final HO slices; and volumetric dataset lends the flexible manipulability and other advantages to HO representation. Two MEPs, namely distance field (DF) based and Fixed Reference Features & Active Grading Source(s) (FRF&AGS) are presented to facilitate the process of HO representation according to the designer)s input parameters. The DM can be modified interactively with users until the final satisfactory result is obtained. In this paper, a scheme of HO slicing is described. In this method, we utilize the slices contour of geometrical model as constraint to reconstruct the HO slices, which can theoretically achieve the same accuracy with the geometrical shape. Some examples of Heterogeneous object represented with our scheme are provided.

This study examines intrinsic motivations and antecedents that affect millennial mobile impulsive shopping in markets with the technology acceptance model (TAM) during the COVID-19 pandemic.

The study has been conducted by collecting data from 367 regular mobile shopping millennials, which was analyzed by structural equation modeling.

The findings reported that the perceived ease of use correlates positively with perceived usefulness. Similarly, perceived ease of use, usefulness, perceived utilitarian value and hedonic value significantly impacts shoppers' trust and attitude toward impulsive mobile shopping. Perceived trust was found to exhibit a positive association with mobile shopping. Finally, perceived usefulness, ease of use, utilitarian value, hedonic value, trust and attitude significantly positively impacted millennials' impulsive mobile shopping.

This study's results will help e-retailers establish novel techniques and efforts to enhance market volume and build solid connections with mobile customers by ensuring secure purchase habits. The results would also help companies develop customer satisfaction-focused business strategies.

This study contributes to the body of literature by finding a significant impact of attitude, trust and shopping values on impulsive mobile shopping. These constructs have not been explored as factors impacting mobile impulsive shopping, especially when it comes to a pandemic.

The objective was to investigate the utility of cottonseed oil (CSO) as a raw material for the synthesis of CSO water-based alkyd resin. The synthesis involved the polymerization of CSO, trimethylolpropane, phthalic anhydride (PA) and trimellitic anhydride (TMA). The prepared resin coating material was subsequently applied to the surface of steel structure material.

This study aimed to synthesize water-based alkyd resins using CSO. Therefore, the alkyd resin was introduced with TMA containing carboxyl groups and neutralized with triethylamine (TEA) to form a water-soluble salt. Then, the esterification kinetics of CSO water-based alkyd resin were investigated, and finally, the basic properties of CSO water-based alkyd resin coating were evaluated.

It was demonstrated that CSO water-based alkyd resin exhibited excellent water solubility and that the esterification kinetic of the synthesis reaction could be described by a second-order reaction. The coating properties of the material were investigated and found to have good basic properties, with 40% resin addition having the best corrosion resistance. Consequently, it could be effectively applied to the surface of steel structural materials.

This study not only met the requirement of environmentally friendly development but also expanded the application of CSO through the synthesis of CSO water-based alkyd resin via alcoholysis. Compared to fatty acid process, the alcoholysis reduced the need for fatty acid pre-extraction, simplifying the alkyd resin synthesis process. Thus, economic costs are effectively reduced.

In an emerging market, understanding shoppers' behavior in an online market is essential to developing online retail strategies. This research study examines the effects of intrinsic factors, namely, perceived utilitarian, hedonic value, materialism, fashion interest and enjoyment, on impulsive online shopping with mediating role of trust and online shopping attitude in the Indian emerging market.

Data are collected from 443 Indian respondents, using purposive and snowball sampling. The data were analyzed using the IBM Statistical Product and Service Solutions (SPSS) and Analysis of Moment Structures (AMOS) package using structural equation modeling.

The results showed that perceived utilitarian, hedonic value, materialism and enjoyment factors significantly impacted perceived trust and online shopping attitude, but fashion interest had no effect. Mediating factors positively impacted impulsive online shopping and showed a significant association between intrinsic factors and impulsive online shopping.

The geographical area of study was limited to only India. Consequently, the findings and conclusions of the study had their limits. The research used the information continuum with a purposive and snowball approach that does not necessarily generalize the findings of the analysis. This work looked at factors stimulating the impulsive online shopping pattern of Indian shoppers in an emerging market.

This research would help e-retailers develop new strategies and plans to increase sales volume and create strong relationships with online customers by providing trustworthiness and security in buying practices.

This study helps to understand the consumer impulsive buying during coronavirus disease 2019 (COVID-19), and it helps e-retailers to adopt a new online store to draw the attention of the consumers and enhance their online sales.

In this COVID-19 situation, this study explores the inherent factors influencing impulsive online shopping in the emerging Indian market. As a result, it contributes to visual identity literature by expanding the field of impulsive online shopping behavior.

This study aims to assess the effects of risk perception and management subject satisfaction on consumers' online meal food safety self-protection behavior during the COVID-19 pandemic.

This study uses 742 questionnaires collected via a two-stage online survey conducted during the COVID-19 pandemic, between December 2021 and January 2022. The entropy method, descriptive statistics, ordered logit model, stepwise regression models, interaction terms and decentralization method were used in the quantitative analysis. Respondents’ written responses to self-protection behavior were categorized into five groups.

Less than half of consumers were aware that online food products carry the risk of SARS-COV-2 (44.48%). Between 30 and 40% of consumers took insufficient or no self-protection measures. Risk perception significantly and positively affected self-protection behavior during the COVID-19 pandemic. Consumers' management subject satisfaction has a positive moderating effect on risk perception, with the moderating effect of the satisfaction of online retailers being significant at the 5% level. Risk perception significantly and positively influences consumer self-protection behavior in provinces not affected by the pandemic.

The findings stress the benefits of synergistic interventions by consumers and management subject to food safety measures and the inclusion of tailored interventions during events threatening public health to effectively address food safety. The study offers valuable insights contributing to the improvement of public health outcomes, customer trust and service quality within the online food delivery industry.

The purpose of this paper is to use artificial intelligence to evaluate the risks of urban power network planning.

A fuzzy Bayesian least squares support vector machine (LS_SVM) model is established in this paper, which can learn the risk information of urban power network planning through artificial intelligence and acquire expert knowledge for its risk evaluation. With the advantage of possessing learning analog simulation precision and speed, the proposed model can be effectively applied in conducting a risk evaluation of an urban network planning system. First, fuzzy theory is applied to quantify qualitative risk factors of the planning to determine the fuzzy comprehensive evaluation value of the risk factors. Then, Bayesian evidence framework is utilized in LS_SVM model parameter optimization to automatically adjust the LS_SVM regularization parameters and nuclear parameters to obtain the best parameter values. Based on this, a risk comprehensive evaluation of urban network planning based on artificial intelligence is established.

The fuzzy Bayesian LS_SVM model established in this paper is an effective artificial intelligence method for risk comprehensive evaluation in urban network planning through empirical study.

The paper breaks new ground in using artificial intelligence to evaluate urban power network planning risks.

Fused deposit modeling (FDM) additive manufacturing technology is widely applied in recent years. However, there are many defects that may affect the surface quality, accuracy, or even cause the collapse of the parts. This paper presents a solution to the problem of detecting defects on the outer surface in the additive process of FDM.

A multi-view and all-round vision detection method is introduced where the detection field of view is changing with the vector of the outer surface during the printing process on the six degrees of freedom robot FDM printer.

After the image is preprocessed, this paper can identify the defects effectively according to its laminate structure, and introduces a mathematical matrix to represent the defects which will be classified into three typical types according to the geometry shape and area distribution.

This research only focuses on the feasibility of the defects detection method. To create the object of high quality, more research is needed to account for the process parameters which significantly cause the defects.

This work will help to detect the defects online, monitor the printing quality of the outer surface, reduce the waste of printed filaments, etc.

This study is among the first to present a multi-view and all-round vision detection method to detect defects on the outer surface in the additive process of FDM; proposes a means of identifying defects according to its laminate structure; and introduces a mathematical matrix to represent the defects which may be used in quality assessment.

The purpose of this paper is to examine the effects of perceived benefits, i.e. utilitarian value, hedonic value and social value, as well as perceived risk, on purchase intention in social commerce context.

To cast light on the factors motivating users’ intention to purchase in the context of social commerce, data of 277 users of social commerce in China were collected via an online survey.

Results show that satisfaction significantly and positively affects users’ purchase intention in social commerce context. In addition, utilitarian, hedonic and social values have significant and positive impacts on satisfaction and purchase intention; and utilitarian value is found to be the most salient factor influencing purchase intention, while hedonic value has the greatest effect on satisfaction. Moreover, perceived risk significantly and negatively affects satisfaction.

Extant research on social commerce has mainly focused on investigating how the general perceived value affects user behavior, but has less considered different dimensions of perceived value. Moreover, prior studies have explored the roles of utilitarian and hedonic values on user behavior; however, there is a lack of research on the effect of social value. The current study attempts to fill these research gaps.