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The aim of this paper is to study the impact of the questions and answers (Q&A) between investors and enterprises from the China stock exchange investor interactive platforms on the total factor productivity (TFP) of enterprises.

To show how the interaction influences the TFP of enterprises, the authors select Q&A records from the interactive platforms related to production, R&D and technology through the Latent Dirichlet Allocation (LDA) topic model and choose A-share listed companies from 2010 to 2019 in China as a sample. To treat the data and test the proposed hypothesis, the authors applied OLS regression and endogeneity testing methods, such as the entropy balance test, Heckman two-stage model and the two-stage least squares regression.

This paper finds that interaction between investors and enterprises is positively correlated with TFP, and that improvements in content length and the timeliness of response can promote TFP. Interactive behavior mainly improves the TFP of enterprises by alleviating financing constraints and encouraging enterprises to increase R&D investment. This positive effect is more pronounced in companies with higher agency costs, non-high-tech companies and companies not supported by industrial policy.

The novelty of the research stands in the application of Python's LDA topic model to screen out Q&A records that are directly related to TFP, such as production, R&D, technology, etc., and measures the degree of information interaction between investors and enterprises from multiple dimensions, such as interaction frequency, content length and the timeliness of response.

This study aims to investigate which stock characteristics and corporate governance variables affect stock price overreaction and volatility during the COVID-19 pandemic period.

A set of stock characteristics and corporate governance variables which may affect price overreaction and volatility were identified following a review of the literature. A dummy variable was created for the cross-sectional analysis to take into account the unique sector effect in the consumer staples sector. Out of sample analysis was conducted to confirm the robustness of the main results.

The empirical results consistently show that size, dividend and trading volume determine the stock price reactions when the market is in turmoil during the pandemic period. Board size and average board tenure exhibit moderate effects on reducing the stock price reactions, but the effects become insignificant while controlling for the firm characteristics in the regressions. The results remain robust when tested out of the sample. More interestingly, a consumer staples sector effect is identified and tested. The test results show that the consumer staples sector effect mitigates the stock price reactions.

The results have practical implications for investors who aim to manage desired levels of risk in their portfolios during the pandemic. The results also provide meaningful insights to stock market speculators regarding pandemic-related speculation opportunities.

This study makes a meaningful connection between the irrational stock market anomalies and the COVID-19 pandemic.

This paper aims to explore the consumer insights and ethical concerns surrounding the online payday loan services available in the Google Play Store. This research was conducted to compare whether the presence or absence of debt collection protection acts in a country creates differences in consumer experiences regarding the ethics of payday loan collection. Specifically, the study compares customers’ experiences in both the Indonesian and US markets.

Indonesia and the USA were chosen because they have very different regulatory structures for the payday loan industry. The data was scraped using Python from 27 payday loan apps on the Indonesian Play Store, resulting in a total of 244,697 reviews extracted from the Indonesian market. For the US market, 446,010 reviews were extracted from 14 payday loan apps. The data was further analyzed using NVIVO.

The results suggest that consumers of payday loans in Indonesia and the USA hold positive views about the benefits of payday loan apps, as revealed by the word frequency and word cloud analysis. Notably, customers in both countries did not express any negative sentiments regarding the unethical interest rate charged by the payday loan, contradicting what is commonly reported in academic literature. However, a distinct pattern of unethical conduct was observed in both countries concerning marketing communication and debt collection practices. In the Indonesian market, payday loan companies were found to engage in unethical debt collection activities. In the US market, payday lenders exhibited unethical behavior in their marketing communication, particularly through deceptive advertising that makes promises to consumers that are not delivered.

The study aims to provide evidence on the various experiences of customers in the presence and absence of debt collection regulations using a novel methodology and a large sample, which strengthens the results and conclusions of the study. The study also intends to inform policymakers, particularly the Indonesian government, about the need for specific laws to regulate the debt collection process and prevent unethical practices. Ultimately, the study is expected to protect the rights of consumers from a deceptive marketing communication or unethical debt collection practices in both the Indonesian and US markets.

Independent directors are important corporate decision participants and makers. Based on the Chinese cultural background, this paper interprets the listing order of independent directors as independent directors’ status, exploring their influence on the corporate research and development (R&D) behavior.

This paper studies A-share listed firms in China from 2008 to 2018 as the sample. The main method is ordinary least square (OLS) regression. We also use other methods to deal with endogenous problems, such as the firm fixed effect method, change model method, two-stage instrumental variable method, and Heckman two-stage method.

(1) Higher independent directors’ status attribute to more effective exertion of supervision and consultation function, and positively enhance the corporate R&D investment. The increase of the independent director’ status by one standard deviation will increase the R&D investment by 4.6%. (2) The above effect is more influential in firms with stronger traditional culture atmosphere, higher information opacity and higher performance volatility. (3) High-status independent directors promote R&D investment by improving the scientificity of R&D evaluation and reducing information asymmetry. (4) The enhancing effect of independent director’ status on R&D investment is positively associated with the firm’s patent output and market value.

This paper contributes to understanding the relationship between the independent directors’ status and their duty execution from an embedded cultural background perspective. The findings of the study enlighten the improvement of corporate governance efficiency and the healthy development of the capital market.

This study aims to make full use of the advantages of connected and autonomous vehicles (CAVs) and dedicated CAV lanes to ensure all CAVs can pass intersections without stopping.

The authors developed a signal coordination model for arteries with dedicated CAV lanes by using mixed integer linear programming. CAV non-stop constraints are proposed to adapt to the characteristics of CAVs. As it is a continuous problem, various situations that CAVs arrive at intersections are analyzed. The rules are discovered to simplify the problem by discretization method.

A case study is conducted via SUMO traffic simulation program. The results show that the efficiency of CAVs can be improved significantly both in high-volume scenario and medium-volume scenario with the plan optimized by the model proposed in this paper. At the same time, the progression efficiency of regular vehicles is not affected significantly. It is indicated that full-scale benefits of dedicated CAV lanes can only be achieved with signal coordination plans considering CAV characteristics.

To the best of the authors’ knowledge, this is the first research that develops a signal coordination model for arteries with dedicated CAV lanes.

This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane (CLL) intersections.

The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness. The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique.

The proposed model has a promising control effect under different geometric controlled conditions. Moreover, the proposed model performs robustly under various safety time headways, lengths of the CLL and green times of the main signal.

This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections. The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness

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.

This study aims to estimate the greenest helicopters and the emission amount based on the helicopter movement within the London Heathrow and London city control zone.

The helicopter flight data recorded by the UK’s specialist aviation regulator Civil Aviation Authority and the helicopter type with engine emission data from the Federal Office of Civil Aviation (FOCA) were used for calculation. Based on the approach adopted, the greenest and the most environmentally friendly helicopters were identified for a light-duty helicopter with single-engine, a light-duty helicopter with twin-engine and a heavy-duty helicopter with twin-engine.

Comparing a flight consisting of landing and take-off cycle, and 1-h phase based on helicopters emissions in the FOCA database, B06 with DDA250-C20R single-engine in the light utility, A109 with PT6B-37 twin-engine in the light utility, and the A139 helicopter with the PT6C-67C twin-engine in the high utility has been identified as the most environmentally friendly helicopter.

This study provides the opportunity to compare between the best and the worst helicopter with engine type according to the emission values released to the environment.

This study raises awareness of the emission levels caused by helicopter in urban air transport in developed countries in terms of environmental and human health. It also provides justification for the authorities to encourage the development and use of green engines and technologies.

The authors examine the contemporaneous and causal association between tweet features (bullishness, message volume and investor agreement) and market features (stock returns, trading volume and volatility) using 140 South African companies and a dataset of firm-level Twitter messages extracted from Bloomberg for the period 1 January 2015 to 31 March 2020.

Panel regressions with ticker fixed-effects are used to examine the contemporaneous link between tweet features and market features. To examine the link between the magnitude of tweet features and stock market features, the study uses quantile regression.

No monotonic relationship is found between the magnitude of tweet features and the magnitude of market features. The authors find no evidence that past values of tweet features can predict forthcoming stock returns using daily data while weekly and monthly data shows that past values of tweet features contain useful information that can predict the future values of stock returns.

The study is among the earlier to examine the association between textual sentiment from social media and market features in a South African context. The exploration of the relationship across the distribution of the stock market features gives new insights away from the traditional approaches which investigate the relationship at the mean.

This study aims to examine the impact of managerial use of motivating language on employee absenteeism, turnover intention, job satisfaction and job performance for employees from three nations: India, the USA and Vietnam.

Data is collected from 614 employees working in India, the USA and Vietnam. A variance-based partial least squares structural equation modeling technique is used to test the hypotheses. In addition, a statistical test is used to examine the statistical differences in the results across the three nations.

The findings are consistent with the motivating language theory, in that managerial use of motivating language can be an effective strategy in motivating employees. Specifically, motivating language is found to significantly decrease employee absenteeism and turnover intention, as well as significantly increase job satisfaction and performance across the three nations. The effect sizes indicate that, across all samples, motivating language has a medium effect for all employee outcomes, except absenteeism, which is shown to have a small effect size. Moreover, the results indicate that employees in different cultures perceive and interpret the leader’s use of motivating language in different ways. Whereas motivating language may receive greater success in promoting workers’ job performance in eastern cultures, it is also more effective in retaining employees in western cultures.

The study adds to the literature in three major ways. First, it provides evidence for two understudied relationships: motivating language and absenteeism and motivating language and turnover intention. Second, it assesses the generalizability of the motivating language theory by investigating data from India, the USA and Vietnam. Finally, this paper offers a statistical comparison of the three samples to analyze how the relationship between motivating language and worker outcomes differ among the three samples.