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The purpose of this study is twofold. First, the author posits and finds a significant positive relation between environmental performance (i.e., environmental efficiency) and firm performance (i.e., firm efficiency) by using a large panel sample from 1987 to 2015. The results are consistent with the notion in prior research (e.g., Porter, 1991; Porter & van der Linde, 1995) that pollution indicates a form of resource inefficiency and reducing pollution can increase firm performance. Second, managerial ability has recently received tremendous research attention. The author investigates the impact of managerial ability on the relation between environmental efficiency and firm efficiency and finds that the results are mainly driven by firms with low managerial ability.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

The purpose of this paper is to examine the effects of environmental regulation on green R&D, as well as to characterize the conditions under which the Porter hypothesis, both the weak as well as the strict version, may or may not hold.

The authors use a simple two‐stage model with environmental R&D and endogenously determined abatement costs to address these issues.

In a monopoly framework, the authors identify a channel arising out of the replacement effect that may increase R&D incentives following stricter regulation. It was found that the Porter hypothesis, both the weak as well as the strong version, is likely to hold if the new technology is relatively efficient in production, but not otherwise.

The paper makes a contribution towards the debate on the relationship between environmental regulation and green R&D, in particular the extremely influential Porter hypothesis.

This study aims to use Porter’s hypothesis (PH), which tests whether corporates’ green investment has an impact on their economic performance (EP). The study argues that corporates’ environmental strategy should allow for a “win-win” situation concerning regulatory compliance.

The quantitative methodology used PH to test empirically the economic consequences of corporates’ green investment in China.

This study indicates that there is a U-shaped relationship between green/environmental investment (EI) and EP. When EI is less, corporates’ EP follows a downward sloping curve until the scale of EI increases and exceeds the “threshold.” From this turning point, EP follows an upward-sloping curve as EI increase. This relationship is more significant in high-polluting companies and state-owned companies.

The empirical results extend the research field of EI and EP for listed companies in China and cover 1,324 observations over the period 2008–2017.

First, the authors expand the research on green/EI and EP using firm-level data. Second, the study empirically tests the economic consequences of corporates’ green investment. Third, this study finds a non-linear relationship between green investment and EP due to the heterogeneity of industry attributes and property rights. These findings provide better explanations for the different research conclusions regarding the economic consequences of green investment.

Compared to global research, China’s research on EI has mainly focused on the macro and industry levels. There is still a lack of micro-level research. The paper addresses this research gap as the authors use firm-level EI data to capture companies’ green investment efforts in environmentally sustainable development and its subsequent impact on EP.

We contribute to the emerging literature on strategic corporate social responsibility (CSR) and its antecedents by undertaking a systematic analysis of the effect of rivalry on firm and industry CSR. We deal with the codetermination of competition and CSR by using instrumental variables in the firm-level analysis and by modeling it directly in the industry-level analysis. We find that higher intensity of rivalry and CSR of competitors increase firm CSR, ceteris paribus; however, in a more dynamic setting when firms can change their production output, more competition in fact decreases aggregate industry CSR. While seemingly contradictory, these findings suggest interesting implications for both managers and public policy makers.

Port performance and port choice have been treated as separate streams of research. This hampers the efforts of ports to anticipate on and respond to possible future changes in port choice by shippers, freight forwarders and carriers. The purpose of this paper is to develop and demonstrate a port performance measurement methodology, extended from the perspective of port choice, which includes hinterland performance and a weighting of attributes from a port choice perspective.

A review of literature is used to extend the scope of port performance indicators. Multi-criteria decision analysis is used to operationalize the context of port choice, presenting a weighted approach using the Best-Worst Method (BWM). An empirical model is built based on an extensive port stakeholder survey.

Transport costs and times along the transport chain are the dominant factors for port competitiveness. Satisfaction, reputation and flexibility criteria are the other important decision criteria. The results also show how the availability of different modal alternatives impact on the position of a port. A ranking of routes for hinterland regions is done.

The paper focuses on two extensions of port performance measurement. So far, not all factors that determine port choice have been included in port performance studies. Here, first, factors related to hinterland services are included. Second, a weighting of port performance measures is proposed. The importance of factors is assessed using BWM. The approach is demonstrated empirically for a case of the European contestable hinterland regions, which so far have lacked quantitative analysis.

Vector Autoregression (VAR) has been a standard empirical tool used in macroeconomics and finance. In this paper we discuss how to compare alternative VAR models after they are estimated by Bayesian MCMC methods. In particular we apply a robust version of deviance information criterion (RDIC) recently developed in Li, Zeng, and Yu (2014b) to determine the best candidate model. RDIC is a better information criterion than the widely used deviance information criterion (DIC) when latent variables are involved in candidate models. Empirical analysis using US data shows that the optimal model selected by RDIC can be different from that by DIC.

Copula modeling enables the analysis of multivariate count data that has previously required imposition of potentially undesirable correlation restrictions or has limited attention to models with only a few outcomes. This article presents a method for analyzing correlated counts that is appealing because it retains well-known marginal distributions for each response while simultaneously allowing for flexible correlations among the outcomes. The proposed framework extends the applicability of the method to settings with high-dimensional outcomes and provides an efficient simulation method to generate the correlation matrix in a single step. Another open problem that is tackled is that of model comparison. In particular, the article presents techniques for estimating marginal likelihoods and Bayes factors in copula models. The methodology is implemented in a study of the joint behavior of four categories of US technology patents. The results reveal that patent counts exhibit high levels of correlation among categories and that joint modeling is crucial for eliciting the interactions among these variables.

This study examined how proactive environmental management affects firm performance and whether a controlling family moderates this effect. The paper aims to discuss these issues.

The study adopted content analysis to collect data on listed Taiwanese firms and used cross-sectional regression analysis to examine the relationship between proactive environmental management and firm performance as well as the moderating role of a controlling family.

The results indicated that not all types of proactive environmental management are positively associated with firm performance and that a controlling family might be more effective in low-risk proactive environmental management practices.

The focus was on the impact of proactive environmental management from the perspective of stockholders. Future research could investigate its impact on other stakeholders as well.

The findings might convince managers that the stereotype of an environment-friendly firm – that the more its green initiatives, the less competitive it becomes – may not necessarily be true. Investing in product-focused pollution prevention could increase revenues and improve performance. Even though process-focused pollution prevention is negatively associated with firm performance, companies are not expected to reduce investment in green processes since they are required for the production of environment-friendly products.

This study adopted a multi-dimensional approach to reveal how different types of proactive environmental management affect firm performance. The authors used the controlling family as a moderating variable to determine whether it moderates the relationship between proactive environmental management and firm performance.