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To improve the position tracking efficiency of the upper-limb rehabilitation robot for stroke hemiplegia patients, the optimization Learning rate of the membership function based on the fuzzy impedance controller of the rehabilitation robot is propose.

First, the impaired limb’s damping and stiffness parameters for evaluating its physical recovery condition are online estimated by using weighted least squares method based on recursive algorithm. Second, the fuzzy impedance control with the rule has been designed with the optimal impedance parameters. Finally, the membership function learning rate online optimization strategy based on Takagi-Sugeno (TS) fuzzy impedance model was proposed to improve the position tracking speed of fuzzy impedance control.

This method provides a solution for improving the membership function learning rate of the fuzzy impedance controller of the upper limb rehabilitation robot. Compared with traditional TS fuzzy impedance controller in position control, the improved TS fuzzy impedance controller has reduced the overshoot stability time by 0.025 s, and the position error caused by simulating the thrust interference of the impaired limb has been reduced by 8.4%. This fact is verified by simulation and test.

The TS fuzzy impedance controller based on membership function online optimization learning strategy can effectively optimize control parameters and improve the position tracking speed of upper limb rehabilitation robots. This controller improves the auxiliary rehabilitation efficiency of the upper limb rehabilitation robot and ensures the stability of auxiliary rehabilitation training.

Using cross-country data on the 1,000 largest global banks for 2019, the paper aims to examine the response of bank risk and returns to the pandemic.

The author employs weighted least squares (WLS) techniques for the purposes of analysis.

The findings suggest that banks with Islamic windows increased their riskiness in response to the pandemic, although there was not much impact on profitability. Additionally, the author categorizes banks based on certain major characteristics and find that these findings are manifest primarily for well-capitalized and less liquid banks.

Research as to the impact of the pandemic on banks' balance sheets has been an unaddressed area of research. By focusing on a large sample of banks across countries with both Islamic and conventional banking presence, the analysis sheds light on the balance sheet response of banks to the pandemic, an aspect that has not been addressed earlier.

Land value varies at a micro level depending on the location’s economic, geographical and political determinants. The purpose of this study is to present a comprehensive assessment of the determinants affecting land value in the Indian city of Thiruvananthapuram in the state of Kerala.

The global influence of the identified 20 explanatory variables on land value is measured using the traditional hedonic price modeling approach. The localized spatial variations of the influencing parameters are examined using the non-parametric regression method, geographically weighted regression. This study used advertised land value prices collected from Web sources and screened through field surveys.

Global regression results indicate that access to transportation facilities, commercial establishments, crime sources, wetland classification and disaster history has the strongest influence on land value in the study area. Local regression results demonstrate that the factors influencing land value are not stationary in the study area. Most variables have a different influence in Kazhakootam and the residential areas than in the central business district region.

This study confirms findings from previous studies and provides additional evidence in the spatial dynamics of land value creation. It is to be noted that advanced modeling approaches used in the research have not received much attention in Indian property valuation studies. The outcomes of this study have important implications for the property value fixation of urban Kerala. The regional variation of land value within an urban agglomeration shows the need for a localized method for land value calculation.

Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

This paper examines the relationship between the extent and quality of the four dimensions of corporate social responsibility disclosure (CSRD) namely community, environment, workplace and marketplace with the long-run share price performance of Malaysian initial public offering (IPO) companies.

This study utilised secondary data by the content analysis of the annual reports and Datastream of 115 IPOs listed from 2007 to 2015 in Malaysia. The IPO’s performance was determined by calculating the return measures under the equally weighted and value-weighted schemes of the mean abnormal returns and buy-and-hold abnormal returns covering the three years post-listing using the event-time approach.

The findings demonstrate that Malaysian IPOs experience substantial overperformance and underperformance when both the IPO performance measures are benchmarked against the matched companies and market. The results indicated that the extent and quality of the community and environment CSRD dimensions are positively and significantly correlated to the IPO’s performance. On the other hand, the extent and quality of the workplace and marketplace CSRD dimensions are negatively and significantly correlated to the IPO performance.

Malaysian regulators could benefit from these findings in their endeavour to carry out a reform process on CSRD to improve its quality. The results of this study are important to investors, regulators, non-government organisations, communities and policymakers. They also enhance the understanding of companies about the importance of disclosing greater CSR information to improve their performance and profitability.

To the researchers' best knowledge, this study provides new insights into the association between CSRD and the performance of Malaysian IPO companies, which is considered important.

This paper aims to examine the effect of family control on corporate anticorruption disclosures of UK publicly listed firms and whether female board directors moderate the latter relationship.

This paper uses Poisson regression analysis for a sample of 1,546 FTSE 350 firm-year observations. Weighted least squares and propensity score matching are then used to assess the robustness of the findings.

The results show that family ownership and involvement are negatively associated with anticorruption disclosures. The tests of moderation indicate that female directors decrease the negative effect of family control on anticorruption disclosures.

To the best of the researcher’s knowledge, this paper is the first to investigate the impact of family control on anticorruption disclosures while taking into consideration the moderating effect of female directors.

This study aims to examine the effects of product market competition (PMC) on analysts’ earnings forecast attributes, particularly forecast accuracy and dispersion. The authors also investigate whether investor protection moderates the relationship between PMC and forecast attributes.

The sample covers 49,578 firm-year observations from 38 countries. This study uses an ordinary least squares regression, a Heckman two-stage regression and an instrumental two-stage least squares regression.

This study finds that PMC is associated with higher forecast accuracy and lower dispersion. The results also show that investor protection enhances the effect of PMC on forecast accuracy and dispersion. These findings imply that countries with strong investor protection have a better information environment, as exhibited by the stronger relationship between PMC and analysts’ forecast properties.

The findings highlight the importance of strong governance mechanisms in both the country and industry environments. Policymakers, including government agencies and financial regulators, can leverage these insights to formulate regulations that promote competition, ensure investor protection and facilitate informed investment decisions.

This study advances our understanding of how PMC affects analysts’ earnings forecast attributes. In addition, it pioneers evidence of the moderating role of investor protection in the relationship between PMC and forecast attributes.

Evolved from Toyota’s shop floor in Japan, lean bundles are universally accepted for boosting manufacturing performance. However, extant literature shows mixed findings on the effectiveness of lean bundles in non-Japanese settings. This meta-analysis is aimed at understanding the influence of national culture (NC) differences on the lean bundles-performance relationships.

A total of 224 effects from 12,569 observations across 48 empirical studies from 14 countries are meta-analyzed. Also, weighted least squares (WLS) meta-regression using NC scores from the Global Leadership and Organizational Behavior Effectiveness (GLOBE) study are conducted to test the moderating effect of NC dimensions.

The meta-analysis reveals a positive association between the lean bundles and firm performance; though, the strength of the association varies across the individual lean bundles. The meta-regression results show that lean practices are more effective in countries that value high future orientation, high collectivism, low-performance orientation and high assertiveness.

The results contribute to the literature on the role of local cultural influence on strategies and decisions related to the implementation of continuous improvement (CI) programs in cross-cultural settings.

When customers make their purchase decisions, they use all the available information from all the initiatives and behaviors that companies carry out with their stakeholders. This research aims to identify whether a company's financial performance and reputation determine the customer's perception of the company, which affects their engagement. This study is based on the theories of engagement, stakeholder and signalling. Are customers engaged solely based on their feeling of satisfaction, or do employees and brand value play a role in this engagement?

Secondary data was collected from 14 automotive companies and empirically tested through a longitudinal study over the period 2010–2018. For panel data analysis this study used weighted least squares.

The variables proposed in this research, firm value and corporate reputation, were significant for the analysed panel sample. Furthermore, employee satisfaction influences customer engagement as an independent and moderating variable, just like brand value.

This research contributes to the emerging stream of customer engagement research by combining insight as a company-initiated resource, with the sheer transaction, integrating data obtained from employees and customers in an international context.

Key performance indicators (KPIs) play a pivotal role in evaluating the level of success of an organization in achieving its business objectives. The objective of the current research is to identify and prioritize effective KPIs in branding products and construction projects, which contribute to the success of construction companies in a competitive environment.

The present research is of an inferential, descriptive and survey nature. In this study, we identified the influential key performance indicators of construction companies in branding products and construction projects for success in a competitive environment through a literature review and expert opinions. The data were collected using a questionnaire, and a combination of the one-sample t-test method with a 95% confidence level and the fuzzy multiple attribute decision-making (FMADM) method was employed for analysis.

The results indicate that the most influential key performance indicators for construction companies in branding products and construction projects for success in a competitive environment are, in order of significance, the following indices: “Marketing and Advertising,” “Financial,” “Creativity,” “Technical and Operational” and “Social and Political.”

The present research examines the importance of branding construction products and projects for the success of construction companies by improving their business objectives and utilizing key performance indicators throughout the product lifecycle (production and construction). This study provides solutions on how construction companies can increase their competitive advantage through branding and achieve long-term success in the global construction industry.