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The purpose of this paper is to provide a survey of the empirical literature on environmental Kuznets curve (EKC) estimation of carbon dioxide (CO₂) emissions over the period of 1991–2017.

This survey categorizes the studies on the basis of power of income in empirical models of EKC. It has been hypothesized that the EKC shows an inverted U-shaped association between economic growth and CO₂ emissions.

For all the contexts, the results of EKC estimation for CO₂ emissions are inconclusive in nature. The reasons behind this discrepancy can be attributed to the choice of contexts, time period, explanatory variables, and methodological adaptation.

The future studies in this context should not only consider new set of variables (e.g. corruption index, social indicators, political scenario, energy research and development expenditures, foreign capital inflows, happiness, population education structure, public investment toward alternate energy exploration, etc.), but also the data set should be refined, so that the EKC estimation issues raised by Stern (2004) can be addressed.

By far, no study in the literature of ecological economics has focused on the empirical estimation of EKC for CO₂ emissions. This particular context has been used for this study, as CO₂ is one of the highest studied pollutants in the ecological economics, and especially within the EKC hypothesis framework.

The purpose of this paper is to study the influence of financial flexibility (FF) on enterprise performance (EP) within Taiwan’s hospitality industry during the COVID-19 shock and explore whether EP varies with hospitality industry characteristics.

Secondary data of 39 Taiwan Stock Exchange-listed hospitality firms were collected from the Taiwan Economic Journal databases. Quantile regression analysis was applied to examine the FF-EP relationship

The results evidence that there is a U-shaped (convex) FF-EP relationship for hospitality firms in the 10th, 25th and 50th Tobin’s Q quantiles and in asset-heavy firms. For asset-light firms, FF has an inverted U-shaped (concave) effect on EP in the 90th Tobin’s Q quantile

The empirical results highlight the need for Taiwan’s hospitality industry as a whole to take rolling adjustment and optimization of FF and concentrate on liquidity risk management after the COVID-19 pandemic and for long-term sustainability.

To the best of the authors’ knowledge, this study is one of the first to examine the nonlinear FF-EP relationship in the hospitality industry of Taiwan, particularly amid the COVID-19 shock. Moreover, this study extends current literature by revealing the hospitality industry’s FF-EP relationship and highlights the importance of the pandemic crisis context.

The relationship between multinationality and firm performance is a central issue in the international marketing and business literatures. Predominantly, this body of research has tried to identify a single, generalized pattern for this relationship. However, despite the vast number of studies, results have been characterized as mixed or inconsistent. In this study, we take a fresh look at this relationship.

We focus on a key inducement to expand firm multinationality – the search for a more efficient way to exploit firm resources, and also on a specific operationalization of multinationality – firm geographic scope. We use a formal analytical model analyzing the trade-off between benefits and costs arising from expanding firm geographic scope and emphasizing the role of lumpy costs emanating from resource indivisibility.

The relationship between geographic scope and performance cannot be confined to a single pattern, but instead, may have any one of a set of patterns: negatively monotonic shape, inverted U-shape, S-shape, M-shape or, multiple-wave inverted U-shape.

The current study offers managers some guidelines to identify which of the above patterns fits their firm's specific case, and to identify the optimal level of geographic scope for their firm.

We conclude that the search for a single, generalized pattern for multinationality-performance is largely futile, whereas the focus on specific inducements and operationalizations for multinationality allows us to explain when and why specific patterns are more likely to occur.

Previous empirical results on the relationship between internationalization and firm performance have been mixed. Both monotonic and curvilinear relationships have been reported. Most recent studies have focused on different types of curvilinear relationships, such as inverted Ushaped, standard U‐shaped, and multiple waves. This paper utilizes a more current sample of firms than prior studies have used and decomposes traditional financial performance measures, applying two different measures of degree of internationalization, country scope and foreign sales as a percent of total sales (FSTS), to measure the effects on financial performance of different degrees of internationalization. Several financial performance measures, including traditional indexes (ROE and ROA) and a decomposition of traditional ones (Profit Margin, Total Asset Turnover), are examined.

This paper aims to link location choice and ownership structure to the debate on the multinationality–performance relationship.

This paper draws on a panel data set that covers 1,321 emerging economy multinational enterprises (EMNEs) and includes 4,227 observations from 44 emerging economies between 2004 and, 2013.

The empirical results find that multinationality has a positive effect on EMNEs’ performance, and that this positive effect is larger for their investments in developed countries than in developing countries. The study also finds that this positive effect of foreign operation in developed countries switch to negative at higher levels of multinationality for privately owned EMNEs than for state-owned EMNEs.

This paper provides new empirical evidence to support an institutional perspective of the internationalisation of EMNEs that are investing in developed countries, contributing to the multinationality-performance literature, highlighting the importance of foreign direct investment location decision and ownership structure.

Misconduct allegations have been found to not only affect the alleged firm but also other, unalleged firms in form of reputational and financial spillover effects. It has remained unexplored, however, how the number of prior allegations against other firms matters for an individual firm currently facing an allegation. Building on behavioral decision theory, we argue that the relationship between allegation prevalence among other firms and investor reaction to a focal allegation is inverted U-shaped. The inverted U-shaped effect is theorized to emerge from the combination of two effects: In the absence of prior allegations against other firms, investors fail to anticipate the focal allegation, and hence react particularly negatively (“anticipation effect”). In the case of many prior allegations against other firms, investors also react particularly negatively because investors perceive the focal allegation as more warranted (“evaluation effect”). The multi-industry, empirical analysis of 8,802 misconduct allegations against US firms between 2007 and 2017 provides support for our predicted, inverted U-shaped effect. Our study complements recent misconduct research on spillover effects by highlighting that not only a current allegation against an individual firm can “contaminate” other, unalleged firms but that also prior allegations against other firms can “contaminate” investor reaction to a focal allegation against an individual firm.

Bank financing is an important external financing source for firm research and development (R&D) investment. This study aims to use an exponential quadratic specification to investigate the effect of bank competition on firm R&D investment and its underlying mechanisms. Moreover, this study checks bank competition’s heterogeneous effects on firm R&D investment.

Based on data of Chinese manufacturing firms and bank branches, this study uses the Tobit estimator, instrumental variable method and Heckman two-step approach to test the relationship between bank competition and firm R&D investment.

The results show robustness evidence of an inverted-U relationship between bank competition and firm R&D investment. Specifically, increases in bank competition promote firm R&D investment until bank competition reaches the turning point and reduce firm R&D investment after crossing the turning point. Financing costs and financial constraints can explain the inverted-U relationship between bank competition and firm R&D investment. Heterogeneity examinations reveal that R&D investment is more sensitive to bank competition in non-state-owned enterprises, small firms and high-tech firms.

This study contributes to the literature on the relationship between bank competition and firm innovation. The authors investigate the heterogeneity of R&D investment influenced by bank competition and depict the economic effects brought by bank competition. This study sheds light on the real effects of bank competition and the determinants of firm R&D investment in transition economies. The conclusions provide empirical evidence for reducing credit discrimination and improving capital allocation efficiency in developing countries.

In this paper, the authors investigate that the increasing level of fossil fuel combustion in the industrial sector has been considered the prime cause for the emissions of greenhouse gas. Meanwhile, the research focusing on the impact of fossil fuel consumption on the emission of CO₂ is limited for the developing countries containing Vietnam. This study applied the autoregressive distributed lag (ARDL) approach with structural breaks presence, and the Bayer–Hanck combined cointegration method to observe the rationality of the environmental Kuznets curve (EKC) hypothesis in the dynamic relationship between the industrialization and carbon dioxide (CO₂) emission in Vietnam, capturing the role of foreign direct investment (FDI) inflows and the fossil fuel consumption over the period of 1975–2019. The outcomes revealed the confirmation of cointegration among the variables and both short and long-run regression parameters indicated the evidence for the presence of a U-shaped association between the level of industrial growth and CO₂ emission that is further confirmed by employing the Lind and Mehlum U-test for robustness purpose. The results of Granger causality discovered a unidirectional causality from FDI and fossil fuel consumption to CO₂ emission in the short run. For the policy points, this study suggests the use of efficient and low carbon-emitting technologies.

In order to test for consistency and robustness of the cointegration analysis, this study also applied the ARDL bound testing method to find out long-run association among variables with the existence of the structural break in the dataset. The ARDL method was preferred to other traditional cointegration models; because of the smaller dataset, the results obtained from the ARDL method are efficient and consistent and equally appropriate for I(1) and I(0) variables.

The short-run and long-run causal associations among variables have been observed by employing the error correction term (ECT) augmented Granger-causality test that revealed the presence of the long-run causality among variables only when the CO₂ emission is employed as a dependent variable. The outcomes for short-run causality indicated the presence of unidirectional causality between consumption of fossil fuel and CO₂ emission, where the fossil fuel consumptions Granger-cause CO₂ emission. Industrial growth has also been found to have an impact on fossil fuel consumptions, however not the opposite. This advocates that the policies aimed at reducing the fossil fuel consumptions would not be harmful to industrial growth as other energy efficient and cleaner technology could be implemented by the firms to substitute the fossil fuel usage.

The study explored the dynamic relationship among FDI, consumption of fossil fuel, industrial growth and the CO₂ emission in Vietnam for the time period 1975–2019. The newly established Bayer–Hanck joint cointegration method and the ARDL bound testing were employed by taking into account the structural breaks in the dataset.

Based on a strategic group concept, the purpose of this paper is to examine the effects of resource employments on persistent performance in the pharmaceutical industry.

In departing from previous research, this paper takes an inverted approach to mapping firms into heterogeneous groups with distinct long-term performance trajectories, given that strategic profiles and characteristics were unknown. The methodology used is latent class growth analysis, a person-centred approach focussing on the relationships among individuals. Regression models were subsequently used to examine the strategy variables-performance relationship between groups and within groups.

First, firms were grouped into upper-performance and lower-performance trajectory subpopulations. Second, the effects of marketing and R&D on performance significantly differed within subpopulations and presented a U shape or an inverse U shape relation. Third, the employment of R&D resources was more effective in the lower-performance trajectory group, the average scale of which is smaller than in the upper-performance trajectory group. On the contrary, the employment of marketing resources had a greater benefited in the upper-performance trajectory group.

Intangible strategy features are ignored due to measure problem in the long period.

Strategic competition is more significant among intragroup members than inter groups. That the U-shape or invert U-shape effects of resource employments on performance among intragroup members reminds the researchers that the law of diminishing return or increasing return should not be ignored when test the group-performance relationship in future research.

The current study introduces an effective approach to investigate the strategic group concept.

As a field, we should put more emphasis on interpreting the magnitude of coefficient estimates rather than only assessing statistical significance. To support this claim, I demonstrate how focusing only on statistical significance can lead to incorrect and incomplete conclusions in many common applications of the linear regression model. Moreover, I demonstrate why interpreting coefficient estimates in common non-linear estimators (e.g., probit, logit, Poisson, and negative binomial estimators) requires additional care compared to the linear regression model.