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Based on student responses to a set of customized questionnaires, this study aims to present evidence that while student evaluations of instructors and courses remain consistent, a designated mobile app enhances perceived online learning experience.

This study addresses quality assurance issues in accelerated online graduate-level education by identifying factors that influence nontraditional adult student preferences for using mobile applications (apps).

It is evident that affordability and functionality are the two most important determinants of nontraditional student preferences for app-based learning, followed by mobility and ease of purchase.

These findings underscore the potential of app learning to bolster positive perceptions of online education. Findings of this study imply that integrating additional app learning tools can be used as a quality assurance mechanism and enhance nontraditional students’ satisfaction through improving their perceived online learning experience.

This study aims to examine student perceptions regarding the mid-semester transition from face-to-face to online delivery in an accounting course during spring 2020.

Due to the COVID-19 pandemic, numerous universities and colleges worldwide transitioned from face-to-face instruction to online delivery during spring 2020. We find some evidence in line with prior literature that COVID-19 affected student learning experience from various aspects.

Thanks in part to effective teaching techniques implemented by the instructor during the transition, including online lecture videos recorded by the instructor, online class materials, early posting of answer keys, frequent communication through emails and bonus points for watching lecture videos, students still perceived their learning outcomes positively in general.

These teaching techniques can be used to enhance student learning experience and satisfaction during class modality transitions in unforeseen circumstances, for both hybrid and online business courses.

Built upon three components (attitudes, subjective norms, and perceived behavioral control) of the theory of planned behavior (TPB), the purpose of this paper is to analyze the factors that influenced accounting students’ intention to pursue public accounting instead of private accounting as their career choice in China.

The TPB is used to predict the rational intention of accounting students in this study. A binary logistic regression analysis was applied to test all hypotheses because of its suitability.

The authors find that the variety and marketability of public accounting experiences, high turnover plus, low firm cohesion in the workplace, and perceived difficulties in traveling extensively affected students’ intentions to pursue the public accounting profession significantly. By highlighting these factors that affect students’ intention to pursue public accounting, this paper has important implications for the accounting educators and other stakeholders in China and other emerging economies.

By understanding the factors influencing the accounting students’ interests in pursuing public accounting, accounting educators and accounting firms could make some changes, redesign accounting curriculum, and enhance internship experience and recruiting process in order to increase more interests in public accounting. Professional organizations and policy makers might learn some lessons to take some actions to encourage young accounting professionals to work for public accounting firms. Moreover, this study has provided a valuable perspective to accounting educators, practitioners, and policy makers in other emerging economies with the same shortage of qualified public accountants.

The paper makes a significant contribution to the accounting education literature by examining the impact of using online meetings with an academic coach on student-perceived learning outcomes, course and instructor evaluations in an online graduate-level accounting course.

A quasi-experimental design is adopted by the author to compare the students' evaluations in fall 2018 and in spring 2019 in an online graduate-level accounting course taught by the same instructor and assisted by the same academic coach.

The study finds that the use of online meetings with an academic coach helps students have a much positive view about the course and a better perception about the instructor's teaching effectiveness for the course. The offering of online meetings by an academic coach also improves students' evaluation about the academic coach in an online graduate-level accounting course.

The paper provides a new perspective to investigate students' perception with the use of online meetings with an academic coach.

This paper aims to explore the interplay between industrial diversity and sustainable economic development in US counties.

Among other popularly used measures, this study uses an underused measure, Hachman index, to gauge the degree of industrial diversity in the models. To capture the impact of industrial diversity on the local community, this study estimates the relationship of two diversity measures to four traditional socioeconomic indicators: per capita personal income growth, gross domestic product per worker, income inequality ratio and poverty rate.

Statistical results suggest that industrial diversity, which is measured by Hachman index, is significantly related to the four socio-economic indicators. Industrial diversity can positively contribute to regional per capita personal income growth and mitigate income inequality and poverty stress; however, it is negatively related to the gross domestic product (GDP) per worker, which means industrial specialization may contribute to GDP per worker growth.

The findings of this study show that there is a nonlinear relationship between industrial diversity and all socioeconomic indicators. Most of the control variables, human capital variables and business and industry profile variables also display significant and positive impacts on economic development.

Climate change has aroused widespread concern around the world, which is one of the most complex challenges encountered by human beings. The underlying cause of climate change is the increase of carbon emissions. To reduce carbon emissions, the analysis of the factors affecting this type of emission is of practical significance.

This paper identified five factors affecting carbon emissions using the logarithmic mean Divisia index (LMDI) decomposition model (e.g. per capita carbon emissions, industrial structure, energy intensity, energy structure and per capita GDP). Besides, based on the projection pursuit method, this paper obtained the optimal projection directions of five influencing factors in 30 provinces (except for Tibet). Based on the data from 2000 to 2014, the authors predicted the optimal projection directions in the next six years under the Markov transfer matrix.

The results indicated that per capita GDP was the critical factor for reducing carbon emissions. The industrial structure and population intensified carbon emissions. The energy structure had seldom impacted on carbon emissions. The energy intensity obviously inhibited carbon emissions. The best optimal projection direction of each index in the next six years remained stable. Finally, this paper proposed the policy implications.

This paper provides an insight into the current state and the future changes in carbon emissions.

This paper aims to investigate the relationships between several macro‐economic indicators and real estate investment in China.

This study proposes the “investment preference theory” to explain that bank deposits, stock investment and real estate investment are three important investment vehicles to Chinese households.

The authors find that interest rate, an important monetary aggregate indicator – M2 – and the size of new equity offering are negatively related to real estate investment, which may imply that Chinese investors would prefer to channel their funds to stock market and high‐interest‐rate‐bearing bank deposits to keep a good balance between risk and high return on investment while higher interest rate also increases the cost of borrowing for the property buyers.

This is one of the first studies which investigated the connections behind Chinese consumers' real estate investment and empirically tested the choices among bank deposit, stock and property investment. This study hopefully deepens the understanding towards the consumer investment behaviors in housing investment decisions.

The purpose of this paper is to study the behavior of smoke flow in a typical high-rise residential building fire in six common smoke control systems.

The pressure, temperature and CO₂ concentration were used to trace the motion of turbulent smoke flow through CFD.

It is found that the hot smoke could rise up and spread into the indoor space on the upper floors through the staircase. When the pressure in the evacuation staircase is higher, it would be more difficult for the smoke to enter the staircase and transport vertically. On the other hand, the smoke would soon transport to the indoor space on the upper floors horizontally. During this process, the smoke shows a more disorder horizontal transport under the sole effect of thermal buoyancy than the co-existence of thermal buoyancy and the air inlet.

Because of the chosen research approach, the research results may need to be tested by further experiments.

The paper includes implications for the design of smoke control systems and evacuation in a building fire.

This paper fulfils an identified need to study the behavior of smoke in a fire and optimize the design of smoke control systems.

The aim of this study was to investigate the impact of low-carbon city pilots (LCCPs) policy using Chinese city-level data from 2009 to 2018 and examine the mechanisms of LCCP policy using a mediation effect model.

The authors measured carbon emissions by high-resolution carbon emission data and used difference-in-difference (DID) and propensity matching score-difference-in-difference (PSM-DID) model to investigate the relationship between LCCP policy and urban carbon intensity. The complex relationship between policy and carbon intensity was evaluated through a mediation model.

The results show that LCCP policy can reduce urban carbon intensity (−0.287), but its effects are different in different sectors. The impact of LCCP policy is greater in the industrial enterprise sector than in the transport sector than in the agricultural sector. Second, the authors find that LCCP policy under market-driven is more effective than government intervention. Third, there is a spillover effect of LCCP policy, which is decreasing with distance. Finally, the authors explore the mechanisms of LCCP policy from multiple perspectives, such as optimizing industrial structure, green areas, promoting public transport travel, population migration and innovation. In addition, the flow of these factors can also explain the spillover effects of LCCP policy.

This study confirms that LCCP policy is an effective tool for achieving urban sustainable development. Government policy-makers should consider the differences in the impacts of LCCP policy in different sectors and the spillover effects of LCCP policy. And, it shows that the effects of LCCP policy are larger by market-driven. These findings imply that the government should take full account of city characteristics and marketisation processes when formulating carbon reduction policies.

This study analyzed the relationship between LCCP policy and urban carbon intensity based on high-resolution carbon emission data. Urban panel data are used to discuss the impacts of LCCP policy under government intervention and market-driven and the mechanisms at play. The study reveals that LCCP policy mainly acts on the industrial enterprise sector, the spillover effects and the market-driven effects.

The purpose of this paper is to apply the theory of perceptual image to clothing, study the effect of bra components on the perceptual image of Chinese female consumers aged 18 to 27, explore the relationship between them, promote the computer-aided bra design to be more rapid and accurate and meet consumer's needs better.

In this paper, cognitive psychology and mathematical analysis methods were used, and two experiments were conducted. A reaction time experiment was conducted based on 3D virtual bra samples, proving that bra components have an effect on the consumer's perceptual image and obtaining a revised bra component design indicator system by multi-dimensional Scaling (MDS). A projection experiment was conducted to study what kind of relationship exists between the two, and a prediction model was constructed by the quantitative I-class theory.

It is found that bra components have an effect on perceptual image of Chinese female consumers aged 18 to 27. A total of five important components (cup area, center front height, torso width, side wing width and center back shape) that affect the consumer's perceptual image were identified by MDS and references analysis, and then a bra perceptual image space composed of five pairs of words was constructed by subjective evaluation and cluster analysis. What is more, a prediction model was obtained by the quantitative I-class theory; after testing, the model can visually and effectively predict consumer's perceptual image according to bra components indicators, which provide a convenience for the positive design of bras.

In this article, the authors just studied bra components, but did not take fabric, color and other factors that also affect the perceptual image into consideration. Further research can use this method to study other important influential factors as well as their comprehensive impact. Also, the subjects are Chinese young women; consumers of other age or from other countries are not involved, and more extensive research can be done in the future.

The bra component indicator system can help to build a more systematic and clearer bra design library, which provides convenience for designers to search and use them quickly, improving the efficiency of bra design. The prediction model is also helpful to bra designers and companies. When they already design a bra, they can use this model to predict consumer's perceptual image, thus carry out more accurate market positioning and promotion. When they want to satisfy consumers or design a specific effect, they can also refer to this model to reverse design of components. In general, the outcomes of this paper can help companies to quickly establish a computer-aided bra design system, which is conducive to designers to accurately design and better meet market's needs, and the method is also a good attempt to apply the theory of perceptual image in psychology to clothing and can be extended to other relevant fields in the future.

Based on cognitive psychology, this paper attempts to apply the theory of perceptual image in psychology into clothing and takes bra as an example to study the relationship between bra components and consumer's perceptual image. The prediction model constructed here is conducive to the development of bra design and to meet personalized needs of consumers. This method can also be extended to other fields in the future.