Search results

Under the global climate change, carbon footprint has become a hot issue at home and abroad. However, there is no consensus on the concept, measurement and application of carbon footprint.

In this paper, first, the concept and connotation of carbon footprint are reviewed; then, different methods of carbon footprint measurement are compared, and it is found that “bottom-up” life cycle assessment and “top-down” input–output analysis are applicable to different research scales.

Finally, the problems in the process of carbon footprint assessment in textile industry are analyzed and further research directions are proposed.

Analyzed and further research directions are proposed.

This policy paper compares the performance of state-owned enterprise (SOEs) versus private firms in selected emerging economies in Asia, focusing on a number of performance indicators. The indicators are internationally recognized quality innovation, product and/or service innovation, financing of operations, dealing with government regulations and labor performance. To the best of the authors’ knowledge, there has been no such comparative study for these indicators between SOEs and private firms and across countries. Most studies of SOEs have been national case studies. As such, they give us little knowledge of how a country compares with other countries at similar stages of economic development. A cross-country comparative analysis can help us identify broader trends and patterns.

The authors compare and discuss the performance of SOEs versus private firms in a number of emerging Asian countries, namely China, India, Indonesia, Malaysia and Vietnam. To do so, the authors use data from the 2018 World Bank Enterprise Survey (which is the latest available) for the period 2012–2015. The authors focus on a number of key performance indicators, namely internationally recognized quality innovation, product and/or service innovation, financing of operations, dealing with government regulations and labor performance.

The comparative analysis uncovers some interesting differences between the two types of firms. For example, somewhat surprisingly, SOEs tend to innovate more than private firms. However, the single most significant pattern the authors find is that in middle-income Asia both types of firms face formidable challenges with respect to doing business – e.g. scarcity of relevant training programs for employees. Therefore, the priority of policymakers must be to improve the overall business environment for all firms, regardless of their ownership structure.

The nature of this paper is a policy paper. This is because the data used in this study is survey data, conducted every four–five years (or more) for each country in the study and available for very few countries. As the data are not available for a continuous period of time, The authors could not conduct empirical research for this topic and thus made it a policy paper that presents a comparison across Asian countries as case studies.

The five selected Asian countries are interesting case studies for a comparative analysis since they are middle-income countries where SOEs play a significant role in the economy. Furthermore, state ownership is an important institutional dimension in emerging markets, and strong ties with the government can influence the performance of SOEs through various market and non-market channels. Despite the potential importance of the research theme, there is very little existing research on cross-country comparisons of the performance of SOEs vis-à-vis private firms. This could be explained by scarce data availability. With this in mind, the study attempts to shed some light on SOEs' performance and add to the rather limited literature.

Resilience concepts in integrated urban transport refer to the performance of dealing with external shock and the ability to continue to provide transportation services of all modes. A robust transportation resilience is a goal in pursuing transportation sustainability. Under this specified context, while before the perturbations, robustness refers to the degree of the system’s capability of functioning according to its design specifications on integrated modes and routes, redundancy is the degree of duplication of traffic routes and alternative modes to maintain persistency of service in case of perturbations. While after the perturbations, resourcefulness refers to the capacity to identify operational problems in the system, prioritize interventions and mobilize necessary material/ human resources to recover all the routes and modes, rapidity is the speed of complete recovery of all modes and traffic routes in the urban area. These “4R” are the most critical components of urban integrated resilience.

The trends of transportation resilience's connotation, metrics and strategies are summarized from the literature. A framework is introduced on both qualitative characteristics and quantitative metrics of transportation resilience. Using both model-based and mode-free methodologies that measure resilience in attributes, topology and system performance provides a benchmark for evaluating the mechanism of resilience changes during the perturbation. Correspondingly, different pre-perturbation and post-perturbation strategies for enhancing resilience under multi-mode scenarios are reviewed and summarized.

Cyber-physic transportation system (CPS) is a more targeted solution to resilience issues in transportation. A well-designed CPS can be applied to improve transport resilience facing different perturbations. The CPS ensures the independence and integrity of every child element within each functional zone while reacting rapidly.

This paper provides a more comprehensive understanding of transportation resilience in terms of integrated urban transport. The fundamental characteristics and strategies for resilience are summarized and elaborated. As little research has shed light on the resilience concepts in integrated urban transport, the findings from this paper point out the development trend of a resilient transportation system for digital and data-driven management.

The major marine functional zoning plan (MMFZP) and marine functional zoning (MFZ) are two important kinds of marine spatial planning (MSP) in China. Their developing and implementation are integral to rational marine utilization and sustainable marine development. The purpose of this research is to study how these two kinds of MSP work in coordination in China.

This paper reviewed the present status of MSP research in China and abroad and presented a comparative study of the MMFZP and MFZ from different aspects, analyzing the relationship between the two.

The study found obvious differences between the MMFZP and MFZ, with respect to their concept and connotation, purpose and goal, as well as zoning methods and zoning functions. MFZ provides reference with respect to data, zoning methods and partial zoning results for the MMFZP, which in turn takes measures for addressing issues faced by MFZ and promotes the national MSP work.

In the process of developing and implementing the two zoning plans, this paper emphasizes the necessity to strengthen data sharing, reference of zoning techniques and coordination in zoning work, which will help to improve China's marine spatial management.

The major objective of the study is to investigate the effect of selected customer retention strategies (fair pricing, online marketing and frequent communication) on perceived service quality and organisational performance within the retail sector in Zimbabwe. Also, the study sought to understand the moderating role of ICT on the effect of customer retention strategies on perceived service quality and organisational performance.

A cross-sectional survey of 280 employees within Zimbabwe's retail sector was adopted and respondents were selected using simple random sampling method. A structured questionnaire with Likert type questions was used to gather data.

The study findings indicate that the performance of organisations within the retail sector is influenced by superior service quality, selected customer retention strategies and also moderated by the use of ICT.

The study contributes to the business management body of knowledge by assessing the effect of selected customer retention strategies (fair pricing, online marketing and frequent communication) on perceived service quality and organisational performance within the retail industry of an emerging economy. The study is also unique in that it used ICT to moderate the effect of selected customer retention strategies on perceived service quality and organisational performance.

This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane (CLL) intersections.

The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness. The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique.

The proposed model has a promising control effect under different geometric controlled conditions. Moreover, the proposed model performs robustly under various safety time headways, lengths of the CLL and green times of the main signal.

This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections. The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness

The aggregate index and per capita index have different meanings for some countries or regions. CO₂ emissions per capita matters for China because of its huge population. Therefore, this study aims to deepen the understanding of Kuznets curve from the perspective of CO₂ emissions per capita. In this study, mathematical formulas will be derived and verified.

First, this study verified the existing problems with the environmental Kuznets curve (EKC) through multiple regression. Second, this study developed a theoretical derivation with the Solow model and balanced growth and explained the underlying principles of the EKC’s shape. Finally, this study quantitatively analyzed the influencing factors.

The CO₂ emission per capita is related to the per capita GDP, nonfossil energy and total factor productivity (TFP). Empirical results support the EKC hypothesis. When the proportion of nonfossil and TFP increase by 1%, the per capita CO₂ decrease by 0.041 t and 1.79 t, respectively. The growth rate of CO₂ emissions per capita is determined by the difference between the growth rate of output per capita and the sum of efficiency and structural growth rates. To achieve the CO₂ emission intensity target and economic growth target, the growth rate of per capita CO₂ emissions must fall within the range of [−0.92%, 6.1%].

Inspired by the EKC and balanced growth, this study investigated the relationships between China’s environmental variables (empirical analysis) and developed a theoretical background (macro-theoretical derivation) through formula-based derivation, the results of which are universally valuable and provide policymakers with a newly integrated view of emission reduction and balanced development to address the challenges associated with climate change caused by energy.

This paper aims to improve the delimitation of plant growth stages in the context of weather index insurance design. We propose a data-driven phase division that minimizes estimation errors in the weather-yield relationship and investigate whether it can substitute an expert-based determination of plant growth phases. We combine this procedure with various statistical and machine learning estimation methods and compare their performance.

Using the example of winter barley, we divide the complete growth cycle into four sub-phases based on phenology reports and expert instructions and evaluate all combinations of start and end points of the various growth stages by their estimation errors of the respective yield models. Some of the most commonly used statistical and machine learning methods are employed to model the weather-yield relationship with each selected method we applied.

Our results confirm that the fit of crop-yield models can be improved by disaggregation of the vegetation period. Moreover, we find that the data-driven approach leads to similar division points as the expert-based approach. Regarding the statistical model, in terms of yield model prediction accuracy, Support Vector Machine ranks first and Polynomial Regression last; however, the performance across different methods exhibits only minor differences.

This research addresses the challenge of separating plant growth stages when phenology information is unavailable. Moreover, it evaluates the performance of statistical and machine learning methods in the context of crop yield prediction. The suggested phase-division in conjunction with advanced statistical methods offers promising avenues for improving weather index insurance design.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

The operation safety of the high-speed railway has been widely concerned. Due to the joint influence of the environment, equipment, personnel and other factors, accidents are inevitable in the operation process. However, few studies focused on identifying contributing factors affecting the severity of high-speed railway accidents because of the difficulty in obtaining field data. This study aims to investigate the impact factors affecting the severity of the general high-speed railway.

A total of 14 potential factors were examined from 475 data. The severity level is categorized into four levels by delay time and the number of subsequent trains that are affected by the accident. The partial proportional odds model was constructed to relax the constraint of the parallel line assumption.

The results show that 10 factors are found to significantly affect accident severity. Moreover, the factors including automation train protection (ATP) system fault, platform screen door and train door fault, traction converter fault and railway clearance intrusion by objects have an effect on reducing the severity level. On the contrary, the accidents caused by objects hanging on the catenary, pantograph fault, passenger misconducting or sudden illness, personnel intrusion of railway clearance, driving on heavy rain or snow and train collision against objects tend to be more severe.

The research results are very useful for mitigating the consequences of high-speed rail accidents.