Unfolding the impact of leadership and management on sustainability performance: Green and lean practices and guanxi as the dual mediators

This study aims to empirically evaluate the predictors that influence sustainability performance among manufacturing firms. Leadership and management, green and lean practices, and guanxi were examined to determine whether these predictors are directly and/or indirectly affecting sustainability performance; 160 valid responses were collected and partial-least-squares-structural-equation-modeling (PLS-SEM) was used to analyze the data. The results showed that leadership and management positively influenced green and lean practices and green and lean practices positively influenced sustainability performance. Leadership and management also positively influenced guanxi. Interestingly, leadership and management and guanxi do not exert a significant direct influence on sustainability performance. The findings contributed to the development of the resource-based-view theory further by empirically exploring the significance of leadership and management coupled with green and lean practices as competencies and capability to drive sustainability performance. The testing of the dual mediators' effects further added value to this study.     

An alternative bivariate zero-inflated negative binomial regression model using a copula

We propose an alternative bivariate zero-inflated negative binomial (BZINB) regression model based on a copula. The empirical result shows that the proposed model performs better than the existing BZINB models in terms of the maximum log-likelihood and the AIC.     

Tourists and traditional divers in a common fishing ground

We study socio-ecological models for a fishing ground open to tourists. On Jeju Island, Korea, women traditional divers called “Haenyeo” harvest resources in a common fishing ground. To investigate the impact of introducing tourists on the benefit to the fishing association and the resource level, we examine two models that differ in the way the number of tourists is controlled. In the first model, the fishing association charges an entrance fee to tourists and the level of the fee is chosen to regulate tourist number. In the second, only a part of the fishing ground is made open to tourists, and the fraction of the ground open is chosen to control the tourist number. In both models, the fishing association seeks to maximize its total benefit. Analysis shows that the way the number of tourists increases with the availability of resources strongly influences the distribution of benefits among the fishing ground stakeholders. Finally, we discuss policy implications of our results and how local government can reduce the risk of introducing tourism.     

Roles played by financial development in economic growth: application of the flexible regression model

This study presents the nonlinear relationship that exists between financial development and economic growth. This study applies the flexible nonlinear regression model of Hamilton (Econometrica 69(3):537–573, 2001) because it imposes no specification restrictions. Two empirical results are obtained. First, an inverted U-shaped relation between banking sector development and economic growth is identified. Namely, the two variables are positively linked before the turning point, but negatively linked after it. Second, a positive relationship with asymmetric √-shape between stock market development and economic growth is found.     

Restricted maximum likelihood estimation under Eisenhart model Ill

For a balanced two-way mixed model, the maximum likelihood (ML) and restricted ML (REML) estimators of the variance components were obtained and compared under the non-negativity requirements of the variance components by L ee and K apadia (1984). In this note, for a mixed (random blocks) incomplete block model, explicit forms for the REML estimators of variance components are obtained. They are always non-negative and have smaller mean squared error (MSE) than the analysis of variance (AOV) estimators. The asymptotic sampling variances of the maximum likelihood (ML) estimators and the REML estimators are compared and the balanced incomplete block design (BIBD) is considered as a special case. The ML estimators are shown to have smaller asymptotic variances than the REML estimators, but a numerical result in the randomized complete block design (RCBD) demonstrated that the performances of the REML and ML estimators are not much different in the MSE sense.     

Performance lies are hazardous to organizational health

Performance lies arise both from individual and from situational causes, but in this article, the attention is on situational causes. These are generally triggered by loyalty to the coalition, which is expressed through the continued use of performance lies. Because performance lies help create a boundary around the coalition that insulates its activities from top management, performance lies enable members of the coalition to exercise a greater degree of internal control. Naturally, such lies are dysfunctional, resulting in the avoidance of difficult issues and problems and compromising the organization's ability to adapt to a changing environment based on accurate information.     

Mean squared error efficient estimators of the variance components

Summary Pseudo Bayesian estimators for the variance components based on Jeffrey’s Rule are derived for the mixed balanced incomplete block design and are compared with the usual analysis of variance estimators in terms of mean squared error (MSE) efficiency. Numerical results show that Pseudo-Bayesian estimators are more efficient in numerical results.     

Economic Development Indicators as Determinants of Medal Winning at the Sydney Olympics: An Extreme Bounds Analysis

This paper examines the variables that determine the performance of countries at the Olympic Games as measured by a weighted sum of the medals won at the Sydney 2000 Games. While previous studies have identified the importance of a country's economic size and the resources available to sport, this paper examines nine more variables including the number of athletes representing each nation and some development indicators. Based on 2310 regressions, both traditional and restricted extreme bounds analysis show that only two variables are robust: the number of athletes and national expenditure on health. Thus, the final model recognises four explanatory variables that include these two as well as GDP and population.