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The purpose of this paper is to develop a coiling robot in the production of coated elevator compensation chains to replace the manual coiling operations and improve the quality of compensation chains.

This paper introduces both mechanical and servo control system designs of the coiling robot. The structure of two friction wheels stabilizes the conveying speed of compensation chain, so the chain speed matches with the car speed. A centering mechanism pushes the chain to its original position. Seven servo motors are integrated into the system, and they are controlled by a servo control system based on programmable logic controller, positioning controller, analog output block and touch screen.

The results of the project show that the coiling robot can both greatly reduce the number of workers and the intensity of the work and improve the quality of the chain. The chain lid by the robot is not only neat, but also uniform in its inner stress.

When the output speed of the compensation chain from the rear friction wheel does not match the coiling speed, the coiling operation has to be halted. Then, the operator adjusts the chain speed and restarts the coiling operation.

The coiling robot is proven working. It has been adopted by a leading company manufacturing compensation chains.

This is the first coiling robot which is practically used in a production line of compensation chains. Its design, mechanism and control systems are of great reference values to people.

This study aims to explore the most salient contributors to residents' support for tourism. As such, the authors measure residents' fear and risk of coronavirus disease 2019 (COVID-19) and residents' animosity towards tourists as predictors of attitudinal, intentional and behavioural support for tourism in China, Malaysia, Kazakhstan and Iran.

An online survey of 1,318 respondents across four countries was conducted, with data analysed using structural equation modelling.

This study shows that residents' perceptions about tourism development vary in different countries based on the impact of COVID-19, even though some factors, such as perceived risk and fear of COVID-19, have a similar effect on residents' attitudes and intentions to support tourism.

Only residents from four countries participated due to the collaborative effort of researchers from these specific countries.

Insight into residents' perceptions and responses to COVID-19 can aid policymakers and managers in developing effective crisis recovery strategies.

The data from this study can serve as a foundation for future research to examine residents' attitudes and support towards tourism during the post-COVID-19 period.

Unlocking the unrevealing of residents' perceptions and coping mechanisms towards tourists during the pandemic, this research shines a light on their crucial role in the revival of the tourism industry. With an exclusive focus on residents' attitudes and behaviours, this study stands out amongst the few that delve into this crucial aspect of post-pandemic recovery.

The purpose of this study was to empirically investigate the characteristics of good hospitality managers and the core causes that lead to developing such characteristics.

Using a qualitative inquiry approach, 93 line-level hospitality employees were surveyed online regarding their experiences about the characteristics of good managers.

The research findings revealed five key themes of good managerial characteristics, including interpersonal skills, communication skills, supervisory skills, leadership skills, and positive personality and professionalism. Additionally, the root causes of these managerial characteristics were also analyzed. The good managerial characteristics were perceived to have developed from having worked under either a great manager or a terrible manager.

This study advanced the literature on managerial characteristics by confirming several existing categories from the viewpoint of hospitality industry employees.

Human resource managers should be considerate of these findings in terms of recruitment, hiring, and training, development, and promotion of employees in their companies.

This is one of the first studies to analyze the perceived reasons behind the development of these characteristics.

The purpose of this study is to integrate research on competitive and cooperative repertoires and to simultaneously assess the direct, indirect and curvilinear effects of competitive and cooperative action repertoires in relation to firm performance.

The analyses are conducted using a longitudinal dual-industry sample of publicly traded firms, including over 6,500 competitive actions and 750 cooperative actions. The authors use fixed effects (FE) regression models to test the diminishing returns of action volume on firm performance as well as the moderating effects of action diversity.

The results suggest that increasing competitive and cooperative actions yields diminishing returns in relation to firm performance. Furthermore, in the context of competitive action repertoire diversity, increased diversity magnifies the diminishing returns of competitive action volume on firm performance.

The study provides a firm-level conceptualization of overall competitive and cooperative repertoires to extend the literature on competition and cooperation beyond dyadic interactions or structural determinants of competitive and cooperative actions.

This study attempts to identify and explicate the unique segmentation of the increasingly growing virtual reality (VR) user market based on the user experience. Consequently, it collects five hundred forty-five online survey questionnaires through the Prolific platform and deploys cluster analysis to identify mutually exclusive groups of VR users. The research variable, user experience, contains 16 indicators explained by four dimensions. As a result, this study is able to unveil three mutually exclusive markets which are labeled as (1) beginner, (2) aficionado, and (3) utilitarian. The unique features of these three groups are further compared based on their VR tour behaviors. In the conclusion section, it offers managerial implications for devising novel marketing strategies.

This paper examines the impact of dividend policy on stock market liquidity, and whether the dividend payouts has an asymmetric effect on stock liquidity.

A multivariate panel-data regression analysis is conducted for a sample of the largest 411 nonfinancial US firms. Three main hypothesis are tested: (1) whether dividend payouts impact affect stock liquidity, (2) whether low and high dividend payments can asymmetrically effect on stock liquidity and (3) whether the presence of the GFC has an impact the relationship between dividend payments and stock liquidity.

The study finds that dividend policy is adversely associated with stock liquidity. This supports the prediction of the liquidity-dividend hypothesis. The authors also report that stock liquidity asymmetrically responds to changes in dividend payouts, confirming the prediction of the dividend-signaling approach. More specifically, higher dividend payments decrease stock liquidity by a lower magnitude than the increase in stock liquidity resulting from lower dividend payments. Finally, the presence of the GFC weakened the relationship between dividend payments and stock liquidity.

The paper can help in performing future research by using different dataset covering the COVID-19 crisis.

The paper allows market participants to better understand the impact of dividend policy and its asymmetric effects on stock liquidity. The authors’ analyses can direct investors and regulators to adopt new supervisory devices to create an appropriate level of dividend payouts that helps to effectively support the level of stock liquidity.

The paper intends to support the business community and to make strong contributions to the economic development and the welfare of the community.

The originality comes from its new evidence as it can help in assessing the importance of dividend policy and its asymmetric impact on stock liquidity in the full sample and during the GFC. The paper is helpful in performing future analyses using a new sample period for another set of data as well as accounting for COVID-19 pandemic crisis.

Behavioral finance literature has long claimed that internet stock message boards can move markets. In this chapter, the authors study more than 2,000 internet board messages posted across finance message boards in India (Chittorgarh, etc.) for 110 companies that went for initial public offering (IPO) in the last one year. This study has multi-fold objectives. First, the authors try to identify the factors which lead to a discussion on an IPO stock in the message board. Second, the authors identify the factors which differentiate a widely discussed stock from the less discussed one. Next, the authors apply advanced machine learning technique to identify the topics which are discussed in the message board through automatic topic modeling. The methodology used includes a logistic regression model for identifying firm characteristics which leads to a probability of getting stakeholders’ attention and hence more discussion. The authors also use advanced topic modeling techniques to identify topics of discussion on the message boards through machine learning. The authors find that larger sized firms, younger firms, firms with low leverage, and non-manufacturing firms get discussed more and the topics of discussion relate to their financial statements, trading strategies, stock behavior, and performance.

The purpose of this paper is to introduce and test a portfolio view of a firm’s corporate social responsibility (CSR) activities. Drawing from stakeholder theory and the dynamic capabilities literature, the authors introduce CSR portfolio diversity and dynamism as key portfolio characteristics that have differential impacts across short- and long-term performance contexts.

The study draws from the Kinder, Lydenberg and Domini database to examine CSR portfolio diversity and dynamism across seven dimensions of CSR activities. The authors test the direct and indirect relationships between CSR portfolio characteristics and both short- and long-term performance outcomes to assess the opportunities and challenges associated with managing a diverse and dynamic CSR portfolio.

The findings suggest that a diverse portfolio of CSR activities positively impacts long-term performance; however, CSR portfolio diversity yields negative performance outcomes in the short-term. The authors also find that CSR portfolio dynamism moderates the relationship between CSR level and firm performance, such that a dynamic portfolio of CSR positively moderates the relationship between a firm’s CSR level and long-term performance; however, it negatively moderates the relationship between CSR level and short-term performance.

This study integrates insights from the literature that examine the independent effects of individual CSR activities and the broader perspective that assesses the aggregated summation of CSR activities in relation to firm performance. By taking a portfolio perspective, the present study provides a unique integration of these two research streams to examine the performance implications of engaging in a diverse and dynamic range of CSR activities.

This paper aims to provide evidence that market efficiency varies greatly across individual stock, and across market exchanges.

Three approaches, partial adjustment model, Dimson beta model and variance ratio test, are used on a large sample of US stocks.

This paper finds prices are closer to random walk benchmarks (i.e. more efficient) for stocks with better liquidity provision, frequent trading, greater return volatility, higher prices, larger market capitalizations and smaller trade sizes. These findings suggest that liquidity stimulates arbitrage activity, which, in turn, enhances market efficiency. Market efficiency also varies with information environment. The results show that stocks with greater information-based trading exhibit higher level of efficiency. Finally, market structure influences market efficiency. New York Stock Exchange stocks achieve higher level of efficiency than NASDAQ stocks do. The empirical results are robust and not driven by differences in stock attributes between the two markets.

Overall, these results indicate that liquidity provision, stock attributes and market structure exert a significant impact on the realization of market efficiency.

In addition, this paper is also relevant to both stock exchanges facing increased competition and to market regulators.

Prior studies offer little evidence on the speed at which new information is impounded into the price. There is also limited evidence regarding how liquidity provision and market structure affect market efficiency. Using a transformation of the speed of price adjustment and other measurements as proxies for individual stock efficiency, this study may shed further lights on our understanding of market efficiency.