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This paper aims to propose a method for dynamic product perceived quality analysis using social media data and to achieve a macro–micro combination analysis. The method enables the prioritization of perceived quality attributes and provides perception causes.

To rationalize the macro–micro combination, ANOVA and multiple linear regression were used to identify the main factors affecting perceived quality which served as the combination basis; by using the combination basis for consumer segmentation, macro-knowledge (i.e. attribute importance and quality category of the attribute) is achieved by term frequency-inverse document frequency (TF-IDF)-based attribute importance calculation and KANO-based attribute classification, which is combined with micro-quality diagnostic information (i.e. perceived quality, perception causes and quality parameters). Further, dynamic perception Importance-Performance Analysis (IPA) is built to present the attribute priority and perception causes.

The framework was validated by the new energy vehicle (NEV) data of Autohome. The results show that price and purchase purpose are the most influential factors of perceived quality and that dynamic perception IPA can effectively prioritize attributes and mine perception causes.

This is one of the first studies to analyze dynamic perceived quality using social media data, which contributes to the research on perceived quality. The paper also contributes by achieving a combined macro–micro analysis of perceived quality. The method rationalizes the macro–micro combination by identifying the factors influencing perceived quality, which provides ideas for other studies using social media data.

The purpose of this paper is to examine the recent accounting regulations designed to facilitate international harmonization in Vietnam and to show how Vietnam developed an accounting system that harmonizes with international standards while preserving macroeconomic control.

This paper is developed using the theoretical framework on globalisation.

The recent development of accounting aims to implement Vietnam's commitment to harmonize its accounting system with the world. This process has faced some difficulties due to national particularities such as Vietnam's economic system and accounting tradition. This paper shows that the regulators have been careful in their approach to develop and find ways to combine or adapt when pushing for accounting development: a co‐existence of vietnamese accounting standards and a uniform accounting system. This point differs from the Anglo‐Saxon world, but is comparable to China.

The different approach to developing accounting regulation in Vietnam reflects the key role of the State in preserving governmental control while harmonizing with international standards.

This paper studies the influence of globalization on accounting development in Vietnam. It suggests that developing accounting practices in a country in harmony with international standards faces obstacles previously evidenced in the literature, such as economic system and accounting tradition. The study also provides insight into problems encountered by regulators who are incorporating international accounting standards into national accounting regulations. These problems suggest that international accounting standard setters and accounting regulators may face issues similar to those in Vietnam.

This paper contributes to the literature on international accounting harmonisation by illustrating the need for considering national particularities as factors that will affect the rate of harmonisation with international accounting standards.

Drawing on a sensemaking perspective, this study aims to theoretically and empirically investigate the effects of participative corporate political activity (PCPA) on radical innovation and how regulatory uncertainty and technological uncertainty affect firms’ choice of PCPA as well as its effectiveness on radical innovation.

Hierarchical regression analyses were conducted to test the research model based on survey data collected from 227 Chinese manufacturing firms.

The results indicate that PCPA has a significantly positive effect on radical innovation. Both regulatory and technological uncertainty are positively related to PCPA. In addition, regulatory uncertainty strengthens the positive relationship between PCPA and radical innovation, whereas technological uncertainty weakens this relationship.

This study reveals that firm managers should be mindful that PCPA is beneficial to firms’ radical innovation activities in China. Additionally, although regulatory uncertainty and technological uncertainty can drive firms to engage in PCPA to cope with the ambiguity they experienced, managers should also be alert to the complicated role of environment forces in enlarging or discounting the positive effect of PCPA on radical innovation.

The findings offer fresh insights into the use of PCPA to manage the uncertain external environment when pursuing radical innovation activities in China.

The purpose of this paper is to present a novel method to design and manufacture rapid prototyping (RP) lightweight photopolymer‐resin models for wind‐tunnel tests. This method can ensure the structural configuration similarity considering model deformation under aerodynamic loads.

Photopolymer‐resin based on RP technique was used to fabricate DLR‐F4 models. Testing in a subsonic and transonic wind tunnel was carried out and the test results were compared to analyze performance predictions.

RP photopolymer‐resin wind‐tunnel models fabricated by the design methods yielded satisfactory aerodynamic performance. The methods can decrease the model's weight and prevent resonance occurrence among the models, wind‐tunnel, and support system, shorten the processing period, and lead to decrease in manufacturing period and cost.

Stiffness shortage of the thin components, such as wing tip, often leads to deformation occurrence under aerodynamic loads in transonic wind‐tunnel tests, which has significant influence on aerodynamic characteristics of the test models. Therefore, model deformation should be taken into account in the design process.

This design and manufacture method, aerodynamic and structural combination design and structural optimization, can obtain RP lightweight photopolymer‐resin wind‐tunnel models for satisfactory aerodynamic performance, which makes RP techniques more practical for manufacturing transonic wind‐tunnel test models, considering deformation induced by aerodynamic forces such as lift force. The methods also present an inexpensive way to test and evaluate preliminary aircraft designs, in both academia and industry.

In view of the strength and stiffness deficiencies of current photopolymer resin models under high aerodynamic loads, the purpose of this paper is to introduce a preliminary design and manufacturing technique for hybrid lightweight high‐speed wind‐tunnel models with internal metal frame and surface photopolymer resin based on rapid prototyping (RP).

Internal metal frame structure was designed to be of regular configurations that can be conveniently fabricated by conventionally mechanical manufacturing methods. Outer resin components were designed to meet configuration fidelity and surface quality, which were fabricated by RP apparatus. Combination of aerodynamics and structure was utilized to accomplish structural design, strength and stiffness calibration and vibration analysis. Structural design optimization and manufacturing method of the validated hybrid AGARD‐B models were studied by analysis of manufacturing precision, surface quality processing and mechanical capability.

The method with internal metal frame and outer resin has dramatically improved the overall strength and stiffness of RP parts of the hybrid AGARD‐B model, and it is suitable to construct the high‐speed wind‐tunnel models with complex internal structure. The method could decrease the model's weight and prevent resonance occurrence among the models, wind‐tunnel and support system, and shorten processing period, and also it leads to decrease in manufacturing period and cost.

Stiffness of thin components for outer resin configuration is somewhat poor under high aerodynamic loads in a high‐speed wind‐tunnel test, and the effect of deformation of the components on the experimental results should be taken into account.

This method can enhance the versatility of using RP technique in the fabrication of high‐speed wind‐tunnel models, especially for experimental models with complex structure. Aerodynamic and structural combination design and structural optimization for hybrid models make RP techniques more practical for manufacturing high‐speed wind‐tunnel models.

Since the initiation of the share split reform by the Chinese Securities Regulatory Commission (CSRC) in 2005, the private placement has become the major source of raising equity after IPO. The purpose of this paper is to investigate why listed firms in China prefer private placements compared to other options of raising capital.

The ordinary least squares regression, the piecewise regression and the cross‐sectional regression analysis were undertaken to investigate the determinants and characteristics of the seasoned‐equity offerings announcement effects. Probit regression analysis was taken to estimate the probability of a firm choosing private placements.

The authors find positive significant announcement abnormal returns for private placement. The findings also indicate that operating performance deteriorates immediately after announcement and poor operating performance is more likely to be contributed by large size portfolios, which suggests size effect.

The paper's evidence contributes to an understanding of the wider implication of the share split reform undertaken by the CSRC.

The paper provides insights for policy makers in China and around the world who have and wish to adopt similar practices within their jurisdictions. Similar research can be conducted in other emerging markets to enable better understanding and implications of seasoned equity offerings on firm financial performance.

The paper is novel in regard to the data and the wider research paradigm used.

The purpose of this paper is to construct an unbiased interval grey number prediction model with new information priority for dealing with the jumping errors from difference equation to the differential equation in the prediction model of interval grey number.

First, this study obtains a set of linear equations about the model parameters by taking the minimum error sum of squares between the accumulative sequence and its simulation values as criterion, and solves them on the basis of the Crammer rule. Then, according to the new information priority principle, it selects the last number of the accumulated generation sequence as the initial value and gives the expression of the time response function by the recursive iteration method to establish the interval grey number prediction model.

This paper provides an unbiased interval grey number prediction model with new information priority, and the example analysis shows that the method proposed in this paper has higher prediction precision and practicality.

If there is a better method to whiten the interval grey number, so as to fully tap the grey information contained in it, the accuracy of the model will be higher.

The model proposed in this paper can avoid the error caused by jumping from difference equation to differential equation and make full use of new information. It can be better used in a problem where new information has a great influence on prediction results.

This paper selects the last number of the accumulated generation sequence as the initial value and gives the expression of the time response function by the recursive iteration method. Then, it constructs an unbiased interval grey number prediction model with new information priority.

This study aims to conduct an exploratory research to find out the evolving constructs and variables of digital literacy, as seen by researchers since its inception. This research also includes an empirical study to identify and further analyze the digital literacy dimensions of university students studying fashion design program in Kolkata, India.

The exploratory study is based on a review of extant literature, whereas the empirical study is carried out through a self-assessment survey based on UNESCOs Digital Literacy Global Framework competences after validating their relevance with respect to the fashion and apparel industry. A total of 120 university students studying four years Bachelor of Design (Fashion Design) program were asked to rate their digital literacy competences on a five-point Likert scale, with a self-reported truth response against each statement. The results were analyzed using multivariate statistical tools.

Based on UNESCO competences, it came out that there are eight digital literacy dimensions. ANOVA further confirms that the dimensions requiring higher-order cognition, such as “software management competence” and “digital citizenship competence,” increase with progress in the graduate program. However, lower-order competence dimensions remained unchanged over time.

The research instrument used for this empirical study, its identified dimensions and the fact that higher-order competence dimensions are enhanced with progression in university education may be helpful for similar research in other fashion-related programs.

Internet emergence has evolved the business of tourism companies, and every tourism company is available online and provides abundant choices, which causes consumers' confusion. The current study aims to investigate the interaction effect of demographic variables on confusion, decision postponement as a negative consequence of confusion and self-efficacy as a moderator in light of the stimulus organism response (SOR) model. Also, an attempt has been made to integrate the smart technology-based solution to deal with consumers' confusion.

Three-way ANOVA, Andrew Hayes process, structural equation modelling and random forest algorithm were used to assess the 507 self-filled questionnaire responses for examining consumers' confusion.

The results reveal that confusion decreases with increased education levels for each gender and age group. Also, for every gender and education level, consumer confusion increases and then decreases. Further, it was observed that self-efficacy effectively moderates the influence of different confusions on decision postponement. An artificial intelligence-enabled predictive model with an accuracy of 71.49% was established, which forecasts the possibility of consumers' decision postponement.

This study offers the comprehension of how the travel site administrators and stakeholders have used artificial intelligence-enabled solution for consumers' confusion and to reduce decision postponement.

To the best of the authors' awareness, this is one of the first studies to unveil the interaction effect of demographic factors on confusion, assess the role of self-efficacy as a moderator and provide artificial intelligence-enabled solutions for consumers' confusion.

This paper aims to extract the Cr from chrome containing leather waste (CCLW) in order to develop composite at optimum casting parameters using RSM technique. Chrome containing leather wastes (CCLW) is one of the significant cause of pollution that is exhaled by the leather industries. One of the technique to address the problem of pollution that is created by CCLW is to recycle it and produce some fruitful results from it. This will not only minimize the levels of harmful emissions to some extent but also give some befitting results.

The current work is all about exploring the ways by which CCLW could be used as a reinforcing material with aluminum. In this work, alumina has been used as a secondary reinforcement particle together with CCLW as with the help of stir casting process. The parameters of stir casting have been optimized by using “Response Surface Methodology.”

To maximize the hardness and tensile strength the values of optimal input casting parameters as found by the experimental results (response surface methodology) are as follows: the pre-heating temperature of collagen and alumina must be 166 °C and 300 °C, respectively, while the wt.% of collagen and alumina present in the matrix must be 2.45% and 5% sequentially 180 s of stirring time.

The hardness of the finally tested composite is 67.12 BHN (approx) which has been enhanced by 52.54% as compared to the base material. Tensile strength of composite also enhanced about 18% with respect to base material developed at the optimum combination of casting parameters.