The rapid expansion of transport infrastructure during economic development has led to significant increases in carbon emissions, particularly in developing countries. However, the relationship between different transport modes and carbon emissions across development stages remains unclear. This study examines the relationship between the relative improvement of railways to roads (RPR), economic growth, and transport carbon emissions, aiming to verify the Environmental Kuznets Curve (EKC) hypothesis in China's transport sector. Using an ARDL model and bounds testing approach, we analyze Chinese data from 1978 to 2021. The bounds test confirms a long-term cointegration relationship among RPR, GDP per capita, and transport carbon emissions. Both long-term and short-term analyses support the EKC hypothesis, indicating an inverted U-shaped relationship between economic growth and per capita transport carbon emissions. The impact of RPR on per capita transport carbon emissions is significantly positive in both the long and short term. The error correction term shows that approximately 41 % of short-term disequilibrium is corrected within a year, further confirming the long-term relationship between variables. Diagnostic tests and stability analysis ensure the reliability of the model results. The study reveals that the impacts of transport demand, infrastructure investment, and technological progress on carbon emissions vary across different stages of economic development. These findings suggest that developing economies should adopt a dynamic approach to transport infrastructure planning, with early preparation for railway development to avoid carbon emission lock-in effects. For sustainable development, policymakers should align infrastructure investment priorities with economic development stages while promoting cross-regional coordination in transport planning.
The rapid growth of the low-altitude economy has driven the widespread adoption of unmanned aerial vehicles (UAVs). This growing deployment presents new challenges for UAV trajectory planning in complex urban environments. However, existing studies often overlook key factors, such as urban airspace constraints and economic efficiency, which are essential in low-altitude economy contexts. Deep reinforcement learning (DRL) is regarded as a promising solution to these issues, while its practical adoption remains limited by low learning efficiency. To overcome this limitation, we propose a novel UAV trajectory planning framework that combines DRL with large language model (LLM) reasoning to enable safe, compliant, and economically viable path planning. Experimental results demonstrate that our method significantly outperforms existing baselines across multiple metrics, including data collection rate, collision avoidance, successful landing, regulatory compliance, and energy efficiency. These results validate the effectiveness of our approach in addressing UAV trajectory planning key challenges under constraints of the low-altitude economy networking.
Inclusiveness and economic development have been slowed by the pandemics and military conflicts. This study investigates the main determinants of inclusiveness at the European level. A multi-method approach is used, with Principal Component Analysis (PCA) applied to create the Inclusiveness Index and Generalised Method of Moments (GMM) analysis used to investigate the determinants of inclusiveness. The data comprises a range of 22 years, from 2000 to 2021, for 32 European countries. The determinants of inclusiveness and their effects were identified. First, economic growth, industrial upgrading, electricity consumption, digitalisation, and the quantitative aspect of governance, all have a positive impact on inclusive growth in Europe. Second, the level of CO2 emissions and inflation have a negative impact on inclusiveness. Tomorrow's inclusive and sustainable growth must include investments in renewable energy, digital infrastructure, inequality policies, sustainable governance, human capital, and inflation management. These findings can help decision makers design inclusive growth policies.
Sudden attention on social media, and how users navigate these contextual shifts, has been a focus of much recent work in social media research. Even when this attention is not harassing, some users experience this sudden growth as overwhelming. In this workshop paper, I outline how growth infuses the design of much of the modern social media platform landscape, and then explore why applying a post-growth lens to platform design could be productive.
Cuong Le Van, Ngoc-Sang Pham, Thi Kim Cuong Pham
et al.
This paper explores the interplay between transfer policies, R\&D, corruption, and economic development using a general equilibrium model with heterogeneous agents and a government. The government collects taxes, redistributes fiscal revenues, and undertakes public investment (in R\&D, infrastructure, etc.). Corruption is modeled as a fraction of tax revenues that is siphoned off and removed from the economy. We first establish the existence of a political-economic equilibrium. Then, using an analytically tractable framework with two private agents, we examine the effects of corruption and evaluate the impact of various policies, including redistribution and innovation-led strategies.
Large language models (LLMs), when guided by explicit textual plans, can perform reliable step-by-step reasoning during problem-solving. However, generating accurate and effective textual plans remains challenging due to LLM hallucinations and the high diversity of task-specific questions. To address this, we draw inspiration from human Implicit Cognition (IC), the subconscious process by which decisions are guided by compact, generalized patterns learned from past experiences without requiring explicit verbalization. We propose iCLP, a novel framework that enables LLMs to adaptively generate latent plans (LPs), which are compact encodings of effective reasoning instructions. iCLP first distills explicit plans from existing step-by-step reasoning trajectories. It then learns discrete representations of these plans via a vector-quantized autoencoder coupled with a codebook. Finally, by fine-tuning LLMs on paired latent plans and corresponding reasoning steps, the models learn to perform implicit planning during reasoning. Experimental results on mathematical reasoning and code generation tasks demonstrate that, with iCLP, LLMs can plan in latent space while reasoning in language space. This approach yields significant improvements in both accuracy and efficiency and, crucially, demonstrates strong cross-domain generalization while preserving the interpretability of chain-of-thought reasoning.
This article explores how smart leadership contributes to developing inclusive, equitable, and sustainable smart cities amidst the backdrop of rapid urbanization and technological advancement. Smart leadership, as articulated in this article, embodies a holistic and forward-looking approach that prioritizes the well-being and inclusion of residents as a primary concern. In line with this approach, technological innovation is harmoniously embodied alongside an unwavering commitment to social justice, sustainability, and long-term planning, enabling cities that are not only technologically advanced, but also more sustainable, equitable and enriched for all residents. Central to this visionary leadership is a profound recognition of equality and representation in city governance. The principles of inclusive leadership require a leadership structure that reflects the diversity of the population, ensuring that the voices of all communities are integral to decision-making processes. Smart leaders actively advocate for the problems and aspirations of each segment of society, promoting a sense of belonging and empowerment among residents, thereby strengthening the city’s commitment to the principles of social cohesion and equal opportunities. In addition, sound leadership recognizes the key challenge of the digital divide, which can exacerbate disparities in urban landscapes. This article highlights the fundamental importance of digital access in ensuring all residents’ full participation in modern society, economics, and governance. Smart leaders introduce policies and initiatives to bridge the digital divide and ensure equal access to digital tools and information for every resident, regardless of socioeconomic background. This proactive approach promotes digital inclusion and lays the foundation for seamless smart technology integration in the city, ultimately improving its residents’ overall quality of life. Through a systematic analysis of articles, this inquiry observes the metamorphosis of cities into centers of advanced technological implementation and economic dynamism. The article proposes the author’s Smart City Leadership Activity Model, which contains several key principles of smart leadership in the context of equitable, sensible, and strategic smart city growth, development, and innovation.
O presente trabalho busca identificar a ocorrência, duração e probabilidades de transição de diferentes regimes de inflação na economia brasileira pós-Real. A teoria de inflação utilizada é a de inflação por conflito distributivo, cujas tipificações de inflação são regime de inflação de equilíbrio e estrato-inflação. A investigação empírica é feita através de um modelo de Markov Switching Autorregressivo e utiliza o índice de inflação brasileiro IPCA (Índice de Preços ao Consumidor Amplo) mensal, desde janeiro de 1995 até maio de 2023. Os resultados obtidos indicam a ocorrência de dois regimes de inflação, onde o mais persistente é o regime de estrato-inflação. As probabilidades de transição mostram que dado que se está no regime de estrato-inflação, a probabilidade de transitar de regime é relativamente pequena, porém, a probabilidade de continuar nele é de 98%. O tempo de duração de regime de estrato-inflação é de cinquenta e um períodos. A memória inflacionária como variável explicativa da inflação presente é estatisticamente significante e corrobora a existência de um fator mantenedor da inflação.
Economic growth, development, planning, Economics as a science
Arda Sarp Yenicesu, Sepehr Nourmohammadi, Berk Cicek
et al.
This article introduces a novel heuristic for Task and Motion Planning (TAMP) named Interpretable Responsibility Sharing (IRS), which enhances planning efficiency in domestic robots by leveraging human-constructed environments and inherent biases. Utilizing auxiliary objects (e.g., trays and pitchers), which are commonly found in household settings, IRS systematically incorporates these elements to simplify and optimize task execution. The heuristic is rooted in the novel concept of Responsibility Sharing (RS), where auxiliary objects share the task's responsibility with the embodied agent, dividing complex tasks into manageable sub-problems. This division not only reflects human usage patterns but also aids robots in navigating and manipulating within human spaces more effectively. By integrating Optimized Rule Synthesis (ORS) for decision-making, IRS ensures that the use of auxiliary objects is both strategic and context-aware, thereby improving the interpretability and effectiveness of robotic planning. Experiments conducted across various household tasks demonstrate that IRS significantly outperforms traditional methods by reducing the effort required in task execution and enhancing the overall decision-making process. This approach not only aligns with human intuitive methods but also offers a scalable solution adaptable to diverse domestic environments. Code is available at https://github.com/asyncs/IRS.
Economic growth prioritizes building and strengthening sectors in the economic field by developing, improving and maximizing resources. West Java Province is one of the provinces that has a large economic contribution to the national Gross Domestic Product (GDP). West Java Province has a diverse economic base. The indicator used to see the macroeconomic conditions in a region is by looking at the Gross Domestic Product (GRDP) in the region. The purpose of this study was to determine the agricultural sub-sector included in the leading sector (base) and to determine the shift of the agricultural sub-sector in West Java Province and the classification of Klassen typology in the economic sector in West Java Province. This study uses secondary data in the form of the value of the Gross Regional Domestic Product of West Java Province and the Indonesian Gross Domestic Product at constant 2010 prices by business field from 2019 to 2023. The data is processed using location quentient (LQ) analysis tools, shift share analysis (SSA) and Klassen typology analysis. The results of the location quentient (LQ) analysis show that the Agriculture, Forestry and Fisheries sector is a non-base sector in West Java Province. The results of shift share analysis (SSA) show that the Agriculture, Forestry and Fisheries Sector has a positive influence on regional economic growth (Nij) of Rp. 12,925 billion, Industry Mix (Mij) of Rp. -5,183 billion and competitive advantage (Cij) of Rp. 910,074 billion. The results of the Klassen typology analysis show that the Agriculture, Forestry and Fisheries Sector is a developed but depressed sector, so it is hoped that the West Java Provincial Government will accelerate growth by increasing output and absorbing more labor.
Each stage of the fashion clothing lifecycle exerts multitudinous negative impacts on the planet. To date, research and policy interventions toward sustainable clothing consumption have largely concentrated on the initial and final life-stages of clothing production, and garment disposal. However, such efforts, even alongside industry technological advances, have failed to balance ever-expanding fashion consumption demand. More recently, alongside wider sustainability debates on sufficiency and consumption corridors, the active use phase of clothing lifecycle is emerging as a vital piece of the sustainability puzzle. An in-depth exploration of users’ real-life everyday interactions with clothing can facilitate a more comprehensive and holistic understanding of wearer garment interactions and use practices with implications for sustainable consumption. This paper presents the findings of an empirical, qualitative research study on the active use phase of clothing consumption in Ireland drawing on a complex intergenerational dataset gathered using in-depth problem-based interviews and wardrobe studies. Findings reveal that participants were largely unaware of both the positive impacts of prolonging wear and the adverse impact of frequent washing on clothing longevity and sustainability. A range of other barriers and enablers to sustainable clothing consumption also emerged, such as the impact of social media on repeat garment wear, the widespread disregard of garment care labels and the considerable acceptability of second-hand clothing wear. In providing such a snapshot into actual everyday clothing wear and care practices, we argue that it is possible to unlock insights into the various ways sustainable maximum use of clothing can be supported and we present implications for future sustainable policy development. We advocate that existing good practice in anti-consumption and sustainable maximum use must be recognised, understood, and promoted to become increasingly more widely culturally and socially acceptable and therefore, impactful in supporting sustainability transitions.
Environmental effects of industries and plants, Economic growth, development, planning
Dustin Tahisin Gómez Rodríguez, Miguel Arturo Aguirre Nieto
The Department of Caquetá is located in the Amazon region of the Colombian state. Since its creation in the 19th century, it has been neglected by institutions, which has contributed, among other variables, to socio-economic and socio-environmental problems that have increased with the incursion of coca cultivation. Quantitative data on competitiveness and poverty reduction are among the lowest among the other departments of the South American country. Therefore, the general objective of the article was to characterize the results of the intervention of a pro-ject carried out by Pastoral Social Caritas Colombia and Caritas Norway in 5 municipalities of the department in the period 2018-2022 to develop food sovereignty and security in 400 farming families. The methodology, methods, and instruments are based on the Theory of Change and MEAL: Monitoring, Evaluating, All Counts and Learning used by Pastoral Social Caritas Colombia. The main conclusion is that the project's contribution to civil society focuses on strengthening organizations to enable them to move forward in spaces that can transform productivity and the recognition of rights by the department's population.
Economic growth, development, planning, Human settlements. Communities
The Information and Communication sector has undoubtedly played a pivotal role in changing the way people live nowadays. Almost every area of our lives is affected by the presence and the use of the new information and communication technologies. In this regard, many researchers' attention has been attracted by the influence or the significant impact of these technologies on economic growth and development. Although the history of South Africa has had some drawbacks that could constitute a big obstacle to the emergence of a successful economic environment, the actual status of the country regarding its economy and the role that it plays in Africa towards the rest of the African countries is a vital example of an emerging economic force in Africa. This paper examines the crucial role that ICT has played and is still playing in the South African economy growth and more specifically the significance of the economic effects of the software industry. It makes use of the framework used by Heavin et al. (2003) to investigate the Irish software industry in order to analyze the impact of endogenous factors -- national, enterprise and individual -- on the software industry and its implication on the economic growth in South Africa.
Planning for sequential robotics tasks often requires integrated symbolic and geometric reasoning. TAMP algorithms typically solve these problems by performing a tree search over high-level task sequences while checking for kinematic and dynamic feasibility. This can be inefficient because, typically, candidate task plans resulting from the tree search ignore geometric information. This often leads to motion planning failures that require expensive backtracking steps to find alternative task plans. We propose a novel approach to TAMP called Stein Task and Motion Planning (STAMP) that relaxes the hybrid optimization problem into a continuous domain. This allows us to leverage gradients from differentiable physics simulation to fully optimize discrete and continuous plan parameters for TAMP. In particular, we solve the optimization problem using a gradient-based variational inference algorithm called Stein Variational Gradient Descent. This allows us to find a distribution of solutions within a single optimization run. Furthermore, we use an off-the-shelf differentiable physics simulator that is parallelized on the GPU to run parallelized inference over diverse plan parameters. We demonstrate our method on a variety of problems and show that it can find multiple diverse plans in a single optimization run while also being significantly faster than existing approaches.
The relevance of the study is determined by the significant and steady decline in the level of citizen participation in political and public life in recent decades in so-called liberal democracies, which cannot guarantee a fair value of political freedoms for all their members. In this light, the purpose of our study is to identify and reveal the problem areas of the study of "political absenteeism" in so-called liberal democracies. The study is based on a systemic and interdisciplinary approach, as well as on a critical approach, the use of which allowed to determine the relevance and originality of our research. Special scientific methods were also used: content analysis and the method of reconstruction. They allowed us to critically rethink the existing approaches to the study of "political absenteeism" and "electoral absenteeism". It turns out that so-called liberal democracies do not currently guarantee a fair price for political freedoms for their poorest (and usually less enlightened and younger) members. "Liberal democracies" may no longer be able (or, indeed, willing) to provide the necessary conditions for citizens to articulate their demands in a way that others can understand and accept and feel as citizens united in one coherent political team. There is not only a concentration of power and influence among the newest associations, but also a strengthening of the ruling "political" class, whose members tend to have a higher socio-economic status, participate more actively in various formal and informal political activities, and have higher levels of political knowledge and influence, along with an "apolitical" class whose members have lower socio-economic status, participate less actively in politics and have lower levels of political knowledge and influence.
This paper uses a biform game model to study firms’ trade-offs between corporate social responsibility (CSR) and competitive advantage. We focus on the context in which a competitive advantage may lead to a non-profitable scenario. It is possible that the first mover’s investment in competitive strength may deter itself from the market, which encourages firms’ investment in CSR over competitive strength. As a result, in some circumstances, firms may actively choose a CSR strategy over a competitive strategy. Our results show that (1) technological characteristics, (2) industrial structure, and (3) institutional environments are factors that influence the rational equilibrium of our model and the balance between competitive advantage and CSR. The mechanism and boundary on how firms make trade-offs between CSR activities and competitive strength are exhibited by our model, which provides a framework for decision-making and adds new insights into the strategic balance between market and non-market strategies.
First published online 10 February 2022
Since Reform and Opening-up 40 years ago, China has made remarkable achievements in economic fields. And consumption activities, including household consumption, have played an important role in it. Consumer activity is the end of economic activity, because the ultimate aim of other economic activities is to meet consumer demand; consumer activity is the starting point of economic activity, because consumption can drive economic and social development. This paper selects the economic data of more than 40 years since Reform and Opening-up, and establishes the Vector Autoregressive (VAR) model and Vector Error Correction (VEC) model, analyzing the influence of consumption level and total consumption of urban and rural residents on economic growth. The conclusion is that the increase of urban consumption and rural consumption can lead to the increase of GDP, and in the long run, urban consumption can promote economic growth more than rural consumption. According to this conclusion, we analyze the reasons and puts forward some policy suggestions.
Economic Policy Uncertainty (EPU) is a critical indicator in economic studies, while it can be used to forecast a recession. Under higher levels of uncertainty, firms' owners cut their investment, which leads to a longer post-recession recovery. EPU index is computed by counting news articles containing pre-defined keywords related to policy-making and economy and convey uncertainty. Unfortunately, this method is sensitive to the original keyword set, its richness, and the news coverage. Thus, reproducing its results for different countries is challenging. In this paper, we propose an unsupervised text mining method that uses word-embedding representation space to select relevant keywords. This method is not strictly sensitive to the semantic similarity threshold applied to the word embedding vectors and does not require a pre-defined dictionary. Our experiments using a massive repository of Persian news show that the EPU series computed by the proposed method precisely follows major events affecting Iran's economy and is compatible with the World Uncertainty Index (WUI) of Iran.
Foreign Direct Investment (FDI) is an essential source of economic development. It has a broad relationship with different dimensions of the mixed economies. Like other development assistance, FDI also needs the best economic environment. This investigation aims to find the impact of Covid -19 on FDI inflow and other barriers to receiving FDI commitment in Nepal. This study is descriptive and analytical. Secondary data are used in the study. Foreign direct investment can be obtained as the government prioritized agriculture, tourism, energy, IT, infrastructure, etc., considering rapid economic Development. The government of Nepal is accepting and implementing foreign investment proposals of donor commitments. However, the Covid -19 pandemic has reduced FDI commitments funds as envisioned. Pandemic is not the only barrier of investment commitment. Still, there are also investment barriers are like, Business environment, poor infrastructure, lack of human resource skills, political transitions, weak governance, natural calamities, diverse and complex geography, tax slab, red tape, and climate change are critical in Nepal. Though the FDI in Nepal till 2019 was an upward trajectory, the 2020 pandemic has reduced it as Nepal's primary economic development source. South Asian environment can create FDI friendly environment in Nepal. Finally, this paper is a new one and full authority for future researchers.
Keywords: Covid-19 pandemic, Foreign Direct Investment, Commitment, Business Environment, Nepal
JEL: F23, I1, M0
Economics as a science, Economic growth, development, planning
Let $\mathrm{TC}_r(X)$ denote the $r$-th topological complexity of a space $X$. In many cases, the generating function $\sum_{r\ge 1}\mathrm{TC}_{r+1}(X)x^r$ is a rational function $\frac{P(x)}{(1-x)^2}$ where $P(x)$ is a polynomial with $P(1)=\mathrm{cat}(X)$, that is, the asymptotic growth of $\mathrm{TC}_r(X)$ with respect to $r$ is $\mathrm{cat}(X)$. In this paper, we introduce a lower bound $\mathrm{MTC}_r(X)$ of $\mathrm{TC}_r(X)$ for a rational space $X$, and estimate the growth of $\mathrm{MTC}_r(X)$.