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Knowledge sharing has entered the stage of knowledge payment with the typical models of paid Q&A, live session, paid subscription, course column and community service. Numerous knowledge suppliers have begun to pour into the knowledge payment market, and users' willingness to pay for premium content has increased. However, the academic research on knowledge payment has just begun.

In this paper, the authors searched several bibliographic databases using keywords such as “knowledge payment”, “paid Q&A”, “pay for answer”, “social Q&A”, “paywall” and “online health consultation” and selected papers from aspects of research scenes, research topics, etc. Finally, a total of 116 articles were identified for combing studies.

This study found that in the early research, scholars paid attention to the definition of knowledge payment concept and the discrimination of typical models. With the continuous enrichment of research literature, the research direction has gradually been refined into three main branches from the perspective of research objects, i.e. knowledge provider, knowledge demander and knowledge payment platform.

This paper focuses on discussing and sorting out the key research issues from these three research genres. Finally, the authors found out conflicting and contradictory research results and research gaps in the existing research and then put forward the urgent research topics.

This paper aims to review the studies on intersection control with connected and automated vehicles (CAVs).

The most seminal and recent research in this area is reviewed. This study specifically focuses on two categories: CAV trajectory planning and joint intersection and CAV control.

It is found that there is a lack of widely recognized benchmarks in this area, which hinders the validation and demonstration of new studies.

In this review, the authors focus on the methodological approaches taken to empower intersection control with CAVs. The authors hope the present review could shed light on the state-of-the-art methods, research gaps and future research directions.

Considering the relationship between the central bank balance sheet and unconventional monetary policy after the 2008 financial crisis, it is crucial to see how the unconventional monetary policy, given near-zero interest rates, affects future stock market performance. This paper analyzes the impact of the Fed's balance sheet size on stock market performance.

To analyze the Fed's balance sheet size's long-term stock market implications, this paper uses the asset pricing framework of market return predictability such as Ordinary least squares (OLS) and Generalized method of moments (GMM) analysis.

Findings in this paper suggest that the Fed's balance sheet size, deflated by asset market wealth, presents evidence of return predictability during 1926–2015 that is robust against standard controls. These results can be explained through the redistribution of risk and the wealth channels of monetary policy transmission. The changing balance sheet size of a central bank (1) affects systemic risk, yields and expectations and (2) signals the future direction of monetary policy and thus economic outlook.

The main implication of these findings is that policymakers should avoid a severe imbalance between a central bank's balance sheet size and assets market wealth.

The empirical evidence in this paper documents a century-old relation between the Fed's balance sheet size and US stock market return using the Fed's balance sheet data for the last 100 years and stock market returns from the Center for research in security prices (CRSP) database.

The impending demographic shift in the United States (Vespa et al., 2020) will require leadership educators to reexamine the relationship between diversity and inclusive leadership. Our literature review revealed inclusive leadership has historically not been viewed with a diversity perspective. To better understand the link between diversity and inclusive leadership, we reviewed how leadership scholars, researchers, and authors have described the attributes and impacts of inclusive leaders. Through inductive coding, we identified seven attributes (i.e., characteristics and actions) of inclusive leaders. When these attributes are acted upon, inclusive leaders create various impacts on followers. These impacts are applied to Shore et al.’s (2011) inclusion framework. Both the attributes and impacts are presented to provide information and tools to better equip leadership educators with the knowledge to foster classroom inclusion in diverse classroom environments.

The underrepresentation of women in engineering has important consequences for meeting the need for a larger, talented scientific and technological labor force. Increasing the proportion of women faculty in engineering will help increase the persistence probabilities of women undergraduate and graduate students in engineering, as well as contribute to the range and diversity of ideas toward innovations and solutions to the greatest engineering challenges. This study aims to examine the association among gender, family formation and post-PhD employment patterns of a cohort of engineering doctorates.

Using the National Science Foundation’s Survey of Doctorate Recipients data, 2001–2010, descriptive and multinomial logit regression analyses are conducted to illustrate the career trajectories of engineering PhDs over a ten-year period.

The career trajectories of engineering PhDs are nonlinear, and transitions between employment sectors commonly occur over the ten-year time period studied. Although women engineering PhDs with young dependents are less likely to be employed initially after PhD completion, they tend to enter the workforce in the academic sector as time progresses. Early post-PhD employment as a postdoctoral researcher or in the academic sector contributes to the pursuit of the professoriate downstream.

While previous studies tend to focus on the early career outcomes of science and engineering students, this study contributes to the literature by focusing on the long-term career outcomes of engineering doctorates. Research findings provide engineering PhD students and PhDs with more information regarding potential post-PhD career trajectories, highlighting the multitude of career options and transitions that occur over time. Research findings also provide higher education administrators and doctoral program stakeholders with foundational information toward designing and revitalizing professional development programs to help PhD students prepare for the workforce. The findings have the potential to be applied toward helping increase diversity by shaping policies and programs to encourage multiple alternative career pathways to the professoriate.

Digital voice assistants use wake word engines (WWEs) to monitor surrounding audio for detection of the voice assistant's name. There are two failed conditions for a WWE, false negative and false positive. Wake word false positives threaten a loss of personal privacy because, upon activation, the digital assistant records audio to the voice cloud service for processing.

This observational study attempted to identify which Amazon Alexa wake word and Amazon Echo smart speaker resulted in the fewest number of human voice false positives. During an eight-week period, false-positive data were collected from four different Amazon Echo smart speakers located in a small apartment with three female roommates.

Results from this study suggest the number of human voice false positives are related to wake word selection and Amazon Echo hardware. Results from this observational study determined that the wake word Alexa resulted in the fewest number of false positives.

This study suggests Amazon Alexa users can better protect their privacy by selecting Alexa as their wake word and selecting smart speakers with the highest number of microphones in the far-field array with 360-degree geometry.

A key factor adversely affecting contractor social networking performance is the improper handling and information management of contractor’s services delivery on websites. Contractor social networking is particularly problematic on industrialised building system (IBS) infrastructure maintenance projects where contractor’s certified quality product and firms are not matched with maintenance specialisation services. The paper aims to discuss this issue.

This paper reports on the early stages of research which is developing a new information and communications technology (ICT)-based approach to managing contractor social networking on IBS infrastructure maintenance schemes. As a precursor to this work, the paper reviews current contractor social networking websites practices on IBS infrastructure maintenance projects and explores the ICT tools and techniques currently being employed on such projects.

The findings reveal the need for more sophisticated contractor social networking websites solutions which accord with the needs of IBS infrastructure maintenance schemes.

The paper concludes by presenting a research framework for developing such a system in the future.

Carbon trading mechanism has been adopted to foster the green transformation of the economy on a global scale, but its effectiveness for the power industry remains controversial. Given that energy-related greenhouse gas emissions account for most of all anthropogenic emissions, this paper aims to evaluate the effectiveness of this trading mechanism at the plant level to support relevant decision-making and mechanism design.

This paper constructs a novel spatiotemporal data set by matching satellite-based high-resolution (1 × 1 km) CO₂ and PM_2.5 emission data with accurate geolocation of power plants. It then applies a difference-in-differences model to analyse the impact of carbon trading mechanism on emission reduction for the power industry in China from 2007 to 2016.

Results suggest that the carbon trading mechanism induces 2.7% of CO₂ emission reduction and 6.7% of PM_2.5 emission reduction in power plants in pilot areas on average. However, the reduction effect is significant only in coal-fired power plants but not in gas-fired power plants. Besides, the reduction effect is significant for power plants operated with different technologies and is more pronounced for those with outdated production technology, indicating the strong potential for green development of backward power plants. The reduction effect is also more intense for power plants without affiliation relationships than those affiliated with particular manufacturers.

This paper identifies the causal relationship between the carbon trading mechanism and emission reduction in the power industry by providing an innovative methodology for identifying plant-level emissions based on high-resolution satellite data, which has been practically absent in previous studies. It serves as a reference for stakeholders involved in detailed policy formulation and execution, including policymakers, power plant managers and green investors.

The purpose of this study is to analyze the relationship between dynamic service innovation capabilities (DSICs) and startup growth in an emerging country.

This paper used a theoretical DSIC model to process data on 137 Brazilian startups, using a stepwise regression.

Service startup growth is related to the capability of enterprises to understand market signals, learn from customers and design a scalable, repetitive and profitable business model.

Despite the innovative nature of startups, this paper found that technological and networking capacities are not a determinant of growth.

Managers should commit themselves to improve their competence in terms of understanding market signals, even when they already have a consolidated business model, products and service offerings. The findings also function as a warning about the dangers of an excessive focus on technological capabilities.

Innovative startups, which achieve high growth create a disproportionate number of new jobs. Hence, by indicating the dynamic capabilities that are more conducive to firm growth, this paper contributes to society and the economy at large.

The findings challenge the myth of technological capacity and networking skills as the main sources of startup growth. This paper shows that founders and managers of service startups who want to achieve rapid growth should concentrate more effort on other skills. Marketing competence and building scalable business models – abilities that are common to successful traditional firms – are more relevant for short-term growth than technological innovation.

Many studies have analysed the impact of various variables on the ability of companies to raise capital. While most of these studies are sector-agnostic, literature on the effects of macroeconomic variables on sectors that established over the last 20 years like property technology and financial technology, is scarce. This study aims to identify macroeconomic factors that influence the ability of both sectors and is extended by real estate variables.

The impact of macroeconomic and real estate related factors is analysed using multiple linear regression and quantile regression. The sample covers 338 observations for PropTech and 595 for FinTech across 18 European countries and 5 deal types between 2000–2001 with each observation representing the capital invested per year for each deal type and country.

Besides confirming a significant impact of macroeconomic variables on the amount of capital invested, this study finds that additionally the real estate transaction volume positively impacts PropTech while the real estate yield-bond-gap negatively impacts FinTech.

For PropTech and FinTech companies and their investors it is critical to understand the dynamic with mac-ro variables and also the real estate industry. The direct connection identified in this paper is critical for a holistic understanding of the effects of measurable real estate variables on capital investments into both sectors.

The analysis fills the gap in the literature between variables affecting investment into firms and effects of the real estate industry on the investment activity into PropTech and FinTech.