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The purpose of this study is to analyze the environmental efficiency level and trend of the transportation sector in the upper–mid–downstream of the Yangtze River Economic Belt and the JingJinJi region in China and assess the effectiveness of policies for protecting the low-carbon environment.

This study uses the meta-frontier slack-based measure (SBM) approach to evaluate environmental efficiency, which targets and classifies specific regions into regional groups. First, this study employs the SBM with the undesirable outputs to construct the environmental efficiency measurement models of the four regions under the meta-frontier and group frontiers, respectively. Then, this study uses the technology gap ratio to evaluate the gap between the group frontier and the meta-frontier.

The analysis reveals several key findings: (1) the JingJinJi region and the downstream of the YEB had achieved the overall optimal production technology in transportation than the other two regions; (2) significant technology gaps in environmental efficiency were observed among these four regions in China; and (3) the downstream region of the YEB exhibited the lowest levels of energy consumption and excessive CO₂ emissions.

To evaluate the differences in environmental efficiency resulting from regions and technological gaps in transportation, this study employs the meta-frontier model, which overcomes the limitation of traditional environmental efficiency methods. Furthermore, in the practical, the study provides the advantage of observing the disparities in transportation efficiency performed by the Yangtze River Economic Belt and the Beijing–Tianjin–Hebei regions.

Do luxury consumers negatively evaluate digital interactions (website and social media) by international luxury brands? The topic has received much debate. The authors argue that luxury brand personality (modern vs. traditional), which encompasses a more stable form of brand identity in global markets, affects evaluations of digital interactions. They further investigate the role of self-brand connection in this process.

Three experiments on Prolific use a European sample and manipulate a single factor between subjects (modernity: less vs. more; traditionality: less vs. more) of French luxury brands and measure evaluations as the dependent variable. Two studies assesses self-brand connection (continuous) as a moderator (studies 2a, 2b). Study 2b rules out some alternative explanations, with culture (independent vs. collectivist) as an independent variable. A fourth study, using a North American sample on CloudResearch, assesses the effect of personality manipulation (more modernity vs. more traditionality) on consumer evaluations of an Italian brand, and assesses ubiquity perceptions as a mediator.

Consumers evaluate digital interactions of international luxury brands less favorably when luxury brand personality exhibits more (vs. less) modernity or less (vs. more) traditionality. Perceptions of ubiquity mediate these relationships. When self-brand connection is high, this effect is attenuated.

The research sheds light on the debate on whether luxury brands should create digital interactions in international markets, given that these global brands operate in multiple channels. Findings show that luxury brands can develop strategies based on aspects of their brand identity, a less malleable feature of brand identity within global markets. Additionally, the research contributes to the conversation about a global luxury market. In short, the findings offer evidence in favor of brand identity (personality) influencing the digital channel strategy a brand should undertake in international markets, first, followed by consumer needs.

Industry 4.0 or I4.0 has transformed the manufacturing landscape by integrating social and technical factors by means of the sociotechnical framework. However, the sociotechnical aspects of digitalization of total quality management (TQM 4.0), especially in small and medium enterprises (SMEs) remain largely unexplored. This groundbreaking research endeavors to delve into the pivotal role played by social (soft) and technical (hard) TQM 4.0 in driving I4.0 readiness among SMEs.

A research framework has been developed by harnessing the principles of Socio-technical systems (STS) theory. Data collection from a sample of 310 randomly selected SMEs manufacturing in Malaysia through an online survey approach. The collected data is then subjected to analysis using Partial Least Square-Structural Equation Modeling (PLS-SEM) through SmartPLS.

The study findings indicate that both hard and soft TQM 4.0 factors are vital to promoting I4.0 readiness (R² = 0.677) and actual implementation (R² = 0.216). Surprisingly, the findings highlight that customer-related construct has no impact on hard TQM 4.0 attributes. Furthermore, hard TQM 4.0 factors have played a partial mediating role on the relationship of soft TQM 4.0 and I4.0 attributes (20% = VAF = 80%).

This is a novel research as it explores the underexplored domain of sociotechnical aspects of TQM 4.0 within SMEs amid I4.0 transformation. The study distinctive contributes include revealing the pivotal role of both soft and hard TQM 4.0 factors in driving I4.0 readiness, emphasizing the primacy of people-related dimensions for successful implementation in manufacturing SMEs.

This paper aims to investigate the impact of political stability on corruption by drawing upon a sample encompassing both developed and developing European and Asian countries.

The dataset, sourced from the Refinitiv database, spans from July 2014 to May 2022. Panel data techniques, specifically pooled estimation and dynamic panel data [generalized method of moments (GMM)] are employed. The analysis encompasses both fixed and random effects models to capture country-specific cross-sectional effects. To validate our findings, we perform a robustness test by including in the investigation four control variables, namely poverty, type of governance, economic freedom and inflation. To test heterogeneity, the dataset is further divided into two distinct subsamples based on the countries’ locations.

Empirical findings substantiate that political stability (viewed as the risk of government destabilization) has a positive and significant impact on corruption in all analyzed samples of European and Asian countries, though some differences are observed in various subsamples. When we take into account the control variables, these analysis results are robust.

This research provided a panel data analysis with GMM, while other empirical methodologies could also be used, like the difference-in-difference approach. However, our results should be validated by extending the time and the sample to a worldwide sample and using alternative measures of corruption and political stability. Moreover, our focus was on a linear and unidirectional relationship between the considered variables, but it would be interesting to test in our further research a non-linear and bidirectional correlation between them. Furthermore, we have introduced in the robustness test only four economic variables, but to consolidate our findings, we plan to include socioeconomic and demographic variables in future studies.

These outcomes imply that authorities should be aware of the necessity of implementing anti-corruption policies designed to establish effective agencies and enforcement structures for combating systemic corruption, to improve the political environment and the quality of institutions and to apply coherent economic strategies to accelerate economic growth because higher political stability and sustainable development determine a decrease in levels of corruption.

At the microeconomic level, the survival of organizations may be in danger from new types of corruption and money laundering. Therefore, in order to prevent financial harm, the top businesses worldwide should respond to instances of corruption through strengthened supervisory procedures. This calls for the creation of a mechanism inside the code of conduct where correct reporting of suspected situations of corruption would have a prompt procedure to be notified of. To avoid corruption in operational procedures, national plans and policies should be developed by government officials, executives and legislators on a national level, as well as by senior management and the board of directors on an organizational level. This might lower organizations' extra corruption-related expenses, assure economic growth and improve global welfare.

A novel feature of our research resides in its broad examination of a sizable sample of European and Asian countries regarding the nexus between corruption and political stability. The paper also investigates a less explored topic in economic literature, namely the impact of political stability on corruption. Furthermore, the study depicts policy recommendations, outlining effective and reasonable measures aimed at improving the political landscape and combating corruption.

The purpose of this research is to empirically analyze the influence of the financial crisis on the investment behavior of sovereign wealth funds (SWFs).

Using 615 deals from 20 SWFs, a series of research are designed and conducted to compare the SWFs' governance, external environment, investment strategy and financial markets' feedback around the crisis.

The paper finds that the recent financial crisis did not only bring SWFs heavy losses and the pressure to improve its image and governance structure, but also a precious opportunity of a better external environment by easing the nerves of the recipient country's government. Their investment strategies will be more positive, diversified and complementary to their own real economy. The event studies illustrate that financial markets turn to be more effective after the crisis. The market reaction to SWF's investment tends to mitigate speculative trading to a larger extent, which is shown by the lower cumulative abnormal return and turnover volatility.

This paper tries to test the change of SWFs' behavior pro‐ and post‐crisis. It reveals that SWFs have changed their effects on SWF's home country, SWF's host country, the financial market and the real economy after the financial crisis, which is helpful for government and institutions to maintain the stability of the national economy and security market.

Although the concept of branding has been considered extensively in products and services, branding in Chinese is a relatively emerging phenomenon. This paper aims to present the enlivenment of branding in Chinese within the cross‐strait markets of Taiwan and Mainland China, which underlies various ideologies.

This study primarily reviews literatures of brand and brand name translation, defines the essentiality of brand naming, and outlines the branding strategies for entering cross‐strait markets. Furthermore, this study validates the using of substantially interpreted brands that support the authors' four developed propositions.

This study compares substantially interpreted brands in cross‐strait markets with a reference to commonly used translation methods. The results illustrate interesting ideologies among cross‐strait markets and can help managers achieve global brand recognition.

Since China and Taiwan share the same Chinese culture, the qualitative method proposed by the present authors is more applicable to practitioners who are eager to pursue branding in cross‐strait markets. Thus, the relevant techniques may not be applicable to people less familiar with Chinese culture.

The qualitative case study provides an advisable method for branding in Chinese. The results of this study can provide greater understanding of the various ideologies in cross‐strait markets, as well as help managers achieve global brand recognition.

The various ideologies from branding is complex, especially for those involved with linguistic essentials. Previous research has mainly focused on managerial‐based branding and customer‐based branding. This paper extends the interest into enlivening inspirations.

The objective of this paper is to explore the critical success factors (CSFs) for Lean Six Sigma (LSS) in the Malaysian automotive industry.

Structural equation modeling (SEM) was employed to test the model drawing on a sample of 252 Malaysian automotive organisations. Exploratory factor analyses (EFA), confirmatory factor analysis (CFA), and reliability analysis empirically verified and validated the underlying items of CSFs of LSS.

The results of EFA, CFA, and reliability analysis show that two items for supplier relationship are recommended to be excluded from the analysis. The result indicates that LSS has identified 40 items as compared to the original questionnaire which had 42 items. Based on the survey of empirical data, the two factors of leadership and customer focus have been shown to be the extremely important factors for LSS implementation in the Malaysian automotive industry.

Firstly, this survey is based only on the automotive industry in Malaysia, and therefore it is not generalisable to other industries. Secondly, there may be other CSFs for LSS such as culture change, project management skill, and employee involvement, which were not included in this study. Finally, for future research agenda, the authors are looking at the structural relationship between LSS practices and organizational performance in the Malaysian automotive industry.

The developed and tested content of this study fills the research gap by providing reliable and useful reference material on the CSFs of LSS. On top of that, the contribution for academic researchers and practitioners is to provide important guidelines for automotive and related companies to implement LSS strategic practices to improve organizational performance.

A firm’s ethical behavior is commonly perceived beneficial to the firm and its investors in the literature. However, activities of corporate social responsibility (CSR) are often delivered with multiple purposes, and their expenses are aggregated with other expenditures in financial statements. These two features motivate the authors to hypothesize and find that investors’ ability to predict future earnings of ethical firms may not be improved through observing the CSR activities. The study aims to suggest that CSR spending should be expressed separately from other expenses in financial reports to help investors predict the future performance of CSR firms.

The authors use future (forward) earnings response coefficients (FERC) to testing whether current stock returns reflect correct information about future earnings. The basic specification of FERC framework, initially developed by Collins et al. (1994), is a regression of current-year stock returns on past, concurrent and future reported earnings with future stock returns as a control variable. A significantly positive FERC provides evidence that investors have rich and correct information about future earnings.

The authors find less future earnings information contained in current stock returns for firms with higher intensity of CSR activities. The association is also negative between current stock returns and future earnings reported by firms with a higher degree of CSR spending aggregated with selling, general and administrative expenses (SG&A). In additional analyses, the intensity of CSR activities is positively associated the uncertainty of benefits, measured by the standard deviation of future earnings over the next five years. This future earnings variability does not exist, even though CSR spending is aggregated with SG&A, consistent with the basic principle that accounting expenses create no future economic impacts.

The authors contribute to the current debate over consequences of CSR activities and accounting for CSR spending from a different angle. A common belief is that voluntary disclosure on CSR activities would aid in reducing costs of equity capital and financial reporting errors. These studies provide corporate managers with good reasons and motivations to expect beneficial consequences of voluntary disclosure. The results show that general investors are less capable of predicting future earnings when there is a higher degree of CSR spending aggregated with SG&A. It also highlights potential problems in the disclosure of general-purpose financial reporting to accounting standard setters.

Renewable energy infrastructure is an important asset class in the context of reducing global carbon emissions going forward. This includes solar power, wind farms, hydro, battery storage and hydrogen. This paper examines the risk-adjusted performance and diversification benefits of listed renewable energy infrastructure globally over Q1:2009–Q4:2022 to examine the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio. The performance of renewable energy infrastructure is compared with the other major infrastructure sectors and other major asset classes. The strategic investment implications for institutional investors and renewable energy infrastructure in their portfolios going forward are also highlighted. This includes identifying effective pathways for renewable energy infrastructure exposure by institutional investors.

Using quarterly total returns, the risk-adjusted performance and portfolio diversification benefits of global listed renewable energy infrastructure over Q1:2009–Q4:2022 is assessed. Asset allocation diagrams are used to assess the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio.

Listed renewable energy infrastructure was seen to underperform the other infrastructure sectors and other major asset classes over 2009–2022. While delivering portfolio diversification benefits, no renewable energy infrastructure was seen in the optimal infrastructure portfolio or mixed-asset portfolio. More impressive performance characteristics were seen by nonlisted infrastructure funds over this period. Practical reasons for these results are provided as well as effective pathways going forward are identified for the fuller inclusion of renewable energy infrastructure in institutional investor portfolios.

Institutional investors have an important role in supporting reduced global carbon emissions via their investment mandates and asset allocations. Renewable energy infrastructure will be a key asset to assist in the delivery of this important agenda for a greener economy and addressing global warming. Based on this performance analysis, effective pathways are identified for institutional investors of different size assets under management (AUM) to access renewable energy infrastructure. This will see institutional investors embracing critical investment issues as well as environmental and social issues in their investment strategies going forward.

This paper is the first published empirical research analysis on the performance of renewable energy infrastructure at a global level. This research enables empirically validated, more informed and practical decision-making by institutional investors in the renewable energy infrastructure space. The ultimate aim of this paper is to articulate the potential strategic role of renewable energy infrastructure as an important infrastructure sector in the institutional real asset investment space and to identify effective pathways to achieve this renewable energy infrastructure exposure, as institutional investors focus on the strategic issues in reducing global carbon emissions in the context of increased global warming.

This paper is to present a new failure model that can be applied to single‐sample failure data of a single system under testing.

The Bayesian method is used for the reliability evaluation. The weighted least squares method is used for determining the parameters of the reliability function.

The authors have observed the operation of a special computer numerical control (CNC) system for a period of over two years, and maintained a reliability database will all the collected failure data, from which the main source of failures can be identified.

Preliminary research results are very encouraging. However, more work will be necessary to validate the new failure model.

The determination of the parameters of the reliability function of a system under testing helps to identify its failure characteristics and potential quality problems.

It is hoped that the paper can help understand some of the challenges in modeling the failure behavior of special CNC systems.