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This paper aims to better understand the linkage between CO₂ emitters and industrial consumers. The border-crossing frequency is applied to calculate the average number of steps that a country takes in relation to the CO₂ emissions of its construction industry. The maximum border-crossing frequency and declining speed of CO₂ transfer are used to reveal the relationship between the length of production chains and the transfer efficiency of construction products.

This paper maps the CO₂ transfer that accompanies global production chains using the frequency of border crossing in the production processes of construction products. As the basic analysis framework, a multi-regional input–output model is adopted to analyse the average border-crossing frequency of CO₂ transfer. Additionally, indicators including the maximum border-crossing frequency and declining speed of CO₂ transfer are employed. Also, the maximum border-crossing frequency and declining speed of CO₂ transfer are used to reveal the relationship between the length of production chains and the transfer efficiency of construction products.

The results indicate that 85.49% of the CO₂ in construction products needs to be processed in at least one country, reflecting that direct trade is the major pattern of transfer of CO₂ from primary producers in global construction industries. The maximum border-crossing frequency is 4.88 for 15 economies, meaning that construction products cross the international borders up to 4.88 times before they are absorbed by the final users. The scale of the average border-crossing frequency ranged from 1.16 to 1.87 over 2000–2014, indicating that the original construction products crossed the international borders at least 1.16 times to satisfy the final demand of the consuming countries.

The data from the economic MRIO tables in the WIOD are only available until 2014, which is a limitation for conducting this research in recent years.

The fragmentation of production is not only reshaping global trade patterns, but also leading to the separation of CO₂ emitters and final consumers in production chains. A growing number of studies have focussed on the impact of production fragmentation on accounting for regional and national CO₂ emissions, but little research has been done at the scale of a specific industry. The major contribution of this paper lies in mapping the CO₂ emissions that accompany the production chains of construction products from the perspectives of both magnitude and length. Additionally, this paper is the first to propose using maximum border-crossing frequency and declining speed to analyse the characteristics of global production chains induced by the final demand of major economies for construction products.

Tourism is a labor-intensive sector with extensive links to other industries and plays a vital role in creating employment. This study aims to propose a new framework to analyze the intrinsic structure of the employment effects of tourism-related sectors and their drivers.

This study uses input–output and structural decomposition analysis (IO-SDA) to quantify the employment effects of tourism-related sectors and their driving mechanisms based on China’s I-O tables of 2002, 2007, 2012 and 2017.

The results show a declining trend in the intensity of direct or indirect employment effects in tourism-related sectors, indicating a decreasing number of jobs directly or indirectly required to create a unit of tourism output. Among tourism-related sectors, catering has the highest intensity of indirect employment effects over the study period. Catering stimulates the indirect employment of agriculture, forestry, animal husbandry, fishery and food and tobacco manufacturing. The decomposition analysis reveals that final demand is the largest contributor to the increase in tourism employment, while technological progress shifts from an employment-creation effect in 2002–2012 to an employment-destruction effect in 2012–2017.

This study proposes a new analytical framework to investigate the structural proportional relationship between the direct and indirect employment effects of various tourism-related sectors and their dynamic changes. Doing so, it provides valuable references for policymakers to promote tourism employment.

旅游相关部门就业效应的驱动因素：以中国为例

摘要

旅游业是一个劳动密集型部门, 与其他国民经济部门有着广泛的联系, 这在创造就业方面发挥着重要作用。本研究旨在建立一个框架, 分析旅游相关部门就业效应的内在结构及其驱动因素。

本研究基于中国2002年、2007年、2012年和2017年的投入产出表, 引入投入产出和结构分解分析（IO-SDA）法量化了旅游相关行业的就业效应及其变化的驱动机制。

旅游相关部门的直接或间接就业强度呈下降趋势, 可见创造一个单位的旅游产出所需的直接或间接工作数量在减少。在旅游相关部门中, 餐饮部门在研究期内的间接就业效应强度最高, 主要带动了农、林、牧、渔业和食品及烟草制造业的间接就业。旅游就业效应变动的驱动因素中, 最终需求是旅游就业效应增加的最大贡献者, 技术效应从2002-2012年期间的就业创造效应转变为2012-2017年期间的就业破坏效应。

本研究建立了一个全新的分析框架, 可以揭示各个旅游相关部门的直接和间接就业效应之间的结构比例关系及其动态变化。对旅游就业效应的驱动因素分析可以为政策制定者提供针对性的建议, 以促进旅游就业。

Factores que impulsan los efectos del empleo en los sectores relacionados con el turismo: El caso de China continental

Resumen

El turismo es un sector intensivo en mano de obra con amplios vínculos con otras industrias y desempeña un papel vital en la creación de empleo. Este estudio propone un nuevo marco para analizar la estructura intrínseca de los efectos en el empleo de los sectores relacionados con el turismo y sus impulsores.

Este estudio utiliza el análisis de entrada-salida (input-output) y de descomposición estructural (structural decomposition) (IO-SDA) para cuantificar los efectos sobre el empleo en los sectores relacionados con el turismo y sus mecanismos impulsores, basándose en las tablas input-output de China de 2002, 2007, 2012 y 2017.

Los resultados muestran una tendencia a la baja en la intensidad de los efectos directos o indirectos del empleo en los sectores relacionados con el turismo, lo que indica un número cada vez menor de puestos de trabajo directos o indirectos necesarios para crear una unidad de producción turística. Entre los sectores relacionados con el turismo, la restauración tiene la mayor intensidad de efectos indirectos sobre el empleo durante el periodo de estudio. La restauración estimula el empleo indirecto de la agricultura, la silvicultura, la ganadería, la pesca y la fabricación de alimentos y tabaco. El análisis de descomposición revela que la demanda final es la que más contribuye al aumento del empleo turístico, mientras que el progreso tecnológico pasa de ser un efecto de creación de empleo en 2002-2012 a un efecto de destrucción de empleo en 2012-2017.

Este estudio propone un nuevo marco analítico para investigar la relación estructural proporcional entre los efectos directos e indirectos del empleo de varios sectores relacionados con el turismo y sus cambios dinámicos. De este modo, proporciona valiosas referencias para que los responsables políticos promuevan el empleo en el sector turístico.

This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.

The input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.

The data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.

The metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.

Comparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.

The purpose of this paper is to investigate regional impact of macroeconomic and regional policy impulses, using our newly developed multi-regional computable general equilibrium (CGE) model for three, structurally distinctive Polish macro-regions.

In this study, we build an interregional social accounting matrix for Poland and use it to develop a small scale, three-region CGE model, reflecting the size of regional economies and cross-regional differences in industrial structures, while also explicitly accounting for the dynamics of main economic relationships across regions, such as interregional flows in commodities, labor and capital. The model is subsequently use to simulate regional effects of various policy impulses.

We demonstrate important cross-regional differences in the transmission mechanism of macro-level policies, which either affect regional output and its individual components (as in the case of imposing shocks to VAT or PIT rates) or are limited to the components, while preserving a rather uniform impact on output (as in the case of imposing shocks to wages). Furthermore, we contribute to the regional policy equity-efficiency trade-off debate, by illustrating quantitatively how, due to structural differences, spatially targeted expenditure measures might promote either regional convergence or aggregate output growth at the country-level.

Prior to our study, regional CGE models have not been used to simulate spatial distribution of aggregate shocks in Poland or in any other CEE country. Another originality of our study lies in comprehensive evaluation of various policy impulses, from the perspective of their impact on the respective region, spillovers to the other regions and its overall, country-level effect.

The Spain–Portugal Cross-Border Cooperation Program launched the “Espomar” project in 2017, with the aim of designing a sustainable and transboundary maritime transport system in the Gulf of Cádiz, which includes the Spanish provinces of Cádiz (its Atlantic coast) and Huelva, together with the Portuguese region of the Algarve. This chapter limits the scope to the Algarve-Huelva connection and the resident population demand. The findings suggest a maritime connection defined and marketed as part of leisure activities. The demand for potential tourism packages created around boat trips appears to be promising. The sun beach, gastronomy wine and culture landscape vectors are the main attractors.

The tourism multiplier effect (TME) is the total economic impact of tourism demand, representing the linkages between tourism and other businesses in an area. However, study about it is limited in Indonesia, especially at the provincial level and after the COVID-19 crisis. This study aims to estimate the TME in all provinces of Indonesia, test its differences in priority and non-priority areas before and after the COVID-19 crisis, analyze its spatial distribution and examine the determinant factor of TME

This study applies an input-output model to measure the TME of all provinces in Indonesia, an independent sample t-test to examine the similarity of TME in priority and nonpriority areas, a paired sample t-test to examine the similarity of it before and after the COVID-19 crisis, and spatial analysis to check its spatial relationship.

The result shows that regional TME ranges from 1.25 to 2.05 in 2019, which changed slightly over time. The empirical result shows the TME difference before and after the COVID-19 crisis, and there is a spatial correlation in terms of TME with the hot spots are clustered in the eastern region of Indonesia, However, there was a slight change in the position of hot spots during the COVID-19 crisis. Moreover, the spatial model shows that value-added and employment in agriculture, manufacturing, trade and transportation affect the size of TME.

This study contributes to the academic literature by providing the first estimate of the TME at the provincial level in Indonesia, comparing the it in priority and non-priority areas before and after the COVID-19 crisis, and mapping its spatial distribution.

This paper proposes an intact framework for building life cycle energy estimation (LCEE), which includes three major energy sources: embodied, operational and mobile.

A systematic review is conducted to summarize the selected 109 studies published during 2012–2021 related to quantifying building energy consumption and its major estimation methodologies, tools and key influence parameters of three energy sources.

Results show that the method limitations and the variety of potential parameters lead to significant energy estimation errors. An in-depth qualitative discussion is conducted to identify research knowledge gaps and future directions.

With societies and economies developing rapidly across the world, a large amount of energy is consumed at an alarming rate. Unfortunately, its huge environmental impacts have forced many countries to take energy issues as urgent social problems to be solved. Even though the construction industry, as the one of most important carbon contributors, has been constantly and academically active, researchers still have not arrived at a clear consensus for system boundaries of life cycle energy. Besides, there is a significant difference between the actual and estimated values in countless current and advanced energy estimation approaches in the literature.

This chapter has aimed to indicate some new important emerging policy problems, which have characterised the Covid crisis in the European economy during 2020 and then the bounce-back in 2021. The chapter has illustrated an economic theoretical framework focussed on innovation and structural changes, according to a Schumpeterian and evolutionary or neo-institutional approach, which seems more appropriate than the traditional neoclassical and macroeconomic models, as the basis for a ‘new industrial strategy’ in the European Union. The mainstream economic models are static and point-like, as they do not consider the role of time and of space, such as the existence of asymmetric information and external economies and also the interdependence between the companies and the other ‘stakeholders’ in the process of economic development. On the contrary, the theoretical framework of this chapter considers the factors that act on the structural changes according to four different and interdependent dimensions: the final demand, the intermediate productions and also the supply of labour and the endowment of natural resources. Finally, some preliminary indications on the organisation of a new industrial strategy at the European scale are discussed, different from the focus on just the digital and green technologies, as indicated by the NGEU program by the European Commission.

The purpose of this paper is to settle the methodological debate on the decomposition of value added in gross exports, proposing a standard, exposing the drawbacks of the alternatives and quantifying the differences.

This paper systematizes the analytical framework and assesses and quantifies the various methodologies and its main differences.

The decomposition method of Borin and Mancini (2023), using a source-based approach and an exporting country perspective, should be considered as the standard for decomposing the value added in gross exports. This study finds that alternative approaches and perspectives are methodologically inferior, and that tailored perspectives do not provide an increase in accuracy that compensates their drawbacks.

This paper’s contribution is fourfold: it rejects the alleged equivalence between approaches and perspectives, defending the superiority of a particular method, approach and perspective; it gives quantitative examples of the differences between them; it proves that the drawbacks of tailored perspectives do not compensate their alleged accuracy (as they do not result in big quantitative differences with the standard perspective); and it argues that no valid standard decomposition can forego the calculation of value added exported, which requires the expression of exports in terms of final demand.

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.