Adel Ben Youssef
email: adel.ben-youssef@univ-cotedazur.fr

Mounir Dahmani
email: mounir.dahmani@isaeg.u-gafsa.tn

Mohamed Mabrouki
email: mohamed.mabrouki@isaeg.u-gafsa.tn

The impact of

Keywords: Environmentally related taxes, productive capacities, environmental degradation, European Economic Area countries, CS-ARDL, DCCE

published or not. The documents may come

Introduction

In the face of escalating global climate change, the need to bridge the gap between existing climate change mitigation policies and the comprehensive efforts needed to meet the temperature targets of the Paris Agreement is more urgent than ever. The Paris Agreement, signed in 2015, emphasizes the critical need to balance economic growth with environmental sustainability. This need has significantly increased the focus of policymakers and researchers alike on the complex relationship between economic development and environmental protection.

The concept of the environmental Kuznets curve (EKC), an inverted U-shaped relationship between pollution and economic development, was first introduced by [START_REF] Grossman | Environmental Impacts of a North American Free Trade Agreement[END_REF]. This concept has given rise to two different perspectives on the nature of the relationship between the environment and the economy. One perspective argues that environmental regulation increases the cost of pollution control, leading to negative effects on economic growth [START_REF] Metcalf | Carbon Taxes in Theory and Practice[END_REF]. Conversely, another perspective argues that an appropriate level of environmental regulation stimulates technological advancement, drives business growth, and offsets the costs of pollution, thereby promoting economic growth [START_REF] Ward | How global climate policy could affect competitiveness[END_REF]. This latter view is further supported by [START_REF] Porter | Toward a New Conception of the Environment-Competitiveness Relationship[END_REF], who coined the term "innovation offsets" to describe the potential benefits from implementing eco-innovations. UNCTAD (2020) describes productive capacities as comprising three main dimensions: productive resources, entrepreneurial capabilities, and production linkages. These elements together determine a nation's ability to produce goods and services and are influenced by various factors such as education, technology, infrastructure, and institutions. Environmental taxes, which include carbon and pollution taxes, target activities that have a negative impact on the environment. The primary objective of such taxes is to incentivize individuals and firms to adopt more environmentally friendly practices and technologies, while generating revenues that can be reinvested in environmental protection and other public goods [START_REF] Baumol | The Theory of Environmental Policy[END_REF][START_REF] Metcalf | Carbon Taxes in Theory and Practice[END_REF].

While the relationship between Gross Domestic Product (GDP) growth, environmental taxes and environmental degradation has been extensively studied, the role of productive capacities in this relationship has received less attention, especially in the context of the European Economic Area (EEA). This is where our study aims to contribute -by providing evidence that productive capacities play a substantial role in reducing CO2 emissions, even more so than environmental taxes. This finding underscores the need for more research on the effectiveness of policies that promote productive capacities in the context of environmental protection in the EEA.

This study attempts to identify EKC in the economies of the EEA, while also considering the influence of environmental taxes and productive capacities on the quality of the environment. We use advanced econometric techniques, including cross-sectional autoregressive distributive lag (CS-ARDL) and dynamic common correlated effects (DCCE), to analyze a data set for the years 2000 to 2018. We additionally use second-generation panel tests to mitigate the potential spurious results caused by cross-sectional dependence and slope heterogeneity. Based on our findings, we then provide policy recommendations aimed at promoting a more sustainable and inclusive economy in the EEA countries.

The paper is organized as follows: Section 2 presents a literature review focusing on environmental degradation and related control variables. Section 3 provides the theoretical framework of our study and details the methodology and estimation procedures used. Section 4 reports and interprets the results of our analysis. Section 5 concludes our research by discussing the main findings and proposing policy recommendations for improving sustainability in the EEA.

Background and literature review

Environmental taxes and environmental degradation

The relationship between environmental taxes, environmental degradation, and economic development has become an increasingly important focus of recent research. Environmental taxes have emerged as powerful tools with the potential to mitigate the negative externalities that economic activities often generate and to foster a culture of environmental sustainability among firms and individuals alike. They are fiscal instruments that balance and interweave policies that promote economic prosperity while ensuring environmental protection, paving the way for sustainable growth (Eurostat, 2013;OECD, 2019). For a more comprehensive understanding, environmental taxes can be broadly grouped into four areas: energy, transportation, pollution, and natural resources. The origins of these taxes, particularly carbon taxes and emissions trading schemes, including the "tradable pollution permits" introduced in the United States since the 1960s, can be traced back to the seminal work of [START_REF] Pigou | The economics of welfare[END_REF] and [START_REF] Coase | The Problem of Social Cost[END_REF]. These taxes serve multiple purposes: to achieve environmental goals, to incentivize environmentally friendly activities, and to address non-environmental issues. The EEA has demonstrated a remarkable commitment to the application of environmental taxes, with all member states implementing some form of these levies, covering energy, transportation, and pollution. However, the effectiveness of these fiscal instruments in mitigating environmental degradation remains a subject of ongoing debate.

The positive effects of environmental taxes on climate change and pollution reduction have been substantiated in multiple studies. For example, [START_REF] Szasz | Which approaches to climate policy decrease carbon dioxide emissions? Evidence from US states, 1997-2017[END_REF] found that environmental taxes mitigate carbon footprints and environmental damage in the United States. [START_REF] Doğan | How environmental taxes and carbon emissions are related in the G7 economies?[END_REF] demonstrated that a tax on carbon emissions can significantly reduce emissions and encourage the use of renewable energy sources in G7 countries. These findings are supported by multiple studies conducted across different regions and countries. Studies conducted for OECD countries [START_REF] Bashir | The nexus between environmental tax and carbon emissions with the roles of environmental technology and financial development[END_REF][START_REF] He | Will environmental taxes help to mitigate climate change? A comparative study based on OECD countries[END_REF], Colombia [START_REF] Calderón | Achieving CO2 reductions in Colombia: Effects of carbon taxes and abatement targets[END_REF], Asian economies [START_REF] Chien | A step toward reducing air pollution in top Asian economies: The role of green energy, eco-innovation, and environmental taxes[END_REF], Chile [START_REF] Vera | Does a carbon tax make sense in countries with still a high potential for energy efficiency? Comparison between the reducing-emissions effects of carbon tax and energy efficiency measures in the Chilean case[END_REF], China (Wang et al., 2023a), Latin American and Caribbean countries (Wolde-Rufael and Mulat-Weldemeskel, 2022a), and EEA countries [START_REF] Ghazouani | Exploring the Role of Carbon Taxation Policies on CO2 Emissions: Contextual Evidence from Tax Implementation and Non-Implementation European Countries[END_REF][START_REF] Liddle | Age-structure, urbanization, and climate change in developed countries: revisiting STIRPAT for disaggregated population and consumption-related environmental impacts[END_REF][START_REF] Neves | Determinants of CO2 emissions in European Union countries: Does environmental regulation reduce environmental pollution?[END_REF][START_REF] Wang | The role of information and communication technologies in achieving hydropower sustainability: Evidence from European Union economies[END_REF][START_REF] Wolde-Rufael | Effectiveness of environmental taxes and environmental stringent policies on CO2 emissions: the European experience[END_REF]) consistently show the positive impact of environmental tax policies on reducing carbon emissions and improving environmental outcomes.

A strand of literature has highlighted the role of environmental taxes in promoting the adoption of clean technologies and reducing pollutant emissions. For example, [START_REF] Xu | Greenhouse gas emissions of electric vehicles in Europe considering different charging strategies[END_REF] found that the implementation of carbon taxes in European countries promoted the use of electric vehicles, which in turn helped reduce carbon emissions in the automotive sector. In addition, [START_REF] Koval | Environmental Taxation Assessment on Clean Technologies Reducing Carbon Emissions Cost-Effectively[END_REF] found that green taxes in European countries increased the adoption of environmentally friendly technologies, which subsequently reduced environmental impacts. [START_REF] Aydin | Reducing CO2 emissions in the EU member states: Do environmental taxes work[END_REF] examined the effect of total environmental taxes on CO2 emissions in 15 European Union (EU) countries and identified a dual effect of reducing emissions and promoting technological innovation and the development of green technologies.

Another stream of studies has focused on the effects of specific types of environmental taxes. [START_REF] Silajdzic | Do Environmental Taxes Pay Off? The Impact of Energy and Transport Taxes on CO2 Emissions in Transition Economies[END_REF] investigated the impact of energy and transport taxes on CO2 emissions in ten transition economies from 1995 to 2015, using the panel cointegration method. Their results confirmed the validity of the EKC hypothesis, showing that energy taxes had a significant and positive effect on CO2 emissions. However, transport taxes did not have a similar statistically significant effect.

Despite the broad consensus on the effectiveness of environmental taxes in reducing environmental degradation, concerns have been raised about their potential negative impact on economic growth. For example, [START_REF] Tu | The Effect of Carbon Emission Taxes on Environmental and Economic Systems[END_REF] found that the introduction of a tax on carbon emissions significantly improved environmental quality but resulted in substantial reductions in most economic variables. Nevertheless, [START_REF] Depren | Heterogeneous impact of environmental taxes on environmental quality: Tax domain based evidence from the nordic countries by nonparametric quantile approaches[END_REF] argue that the effectiveness of environmental taxes in achieving their intended goals may vary due to several factors. Their study reveals the heterogeneous effects of environmental taxes on CO2 emissions and concludes that the effectiveness of the European carbon tax system varies across countries, despite overall positive results. Similarly, [START_REF] Delgado | Environmental taxation in the European Union: Are there common trends?[END_REF] point to the complex, contextspecific nature of the relationship between environmental taxes and economic growth.

Building on [START_REF] Pearce | The Role of Carbon Taxes in Adjusting to Global Warming[END_REF] theory of the "double dividend" effect of environmental taxes, environmental tax revenues could be channeled to reduce existing tax rates. This tax shift suggests that environmental taxes could generate a double benefit, known as the "green" and "blue" dividends. The "green dividend" refers to the environmental benefits, while the "blue dividend" refers to the reduction in the impact of the existing tax system on factors of production such as capital and labor, thereby stimulating job creation and economic growth [START_REF] Shayanmehr | How do environmental tax and renewable energy contribute to ecological sustainability? New evidence from top renewable energy countries[END_REF]. However, the potential of these taxes to promote renewable energy has yet to be fully explored. As highlighted by [START_REF] Rafique | Exploring the heterogenous impacts of environmental taxes on environmental footprints: An empirical assessment from developed economies[END_REF], [START_REF] Alola | Analysing the co-benefit of environmental tax amidst clean energy development in Europe's largest agrarian economies[END_REF], [START_REF] Gyamfi | Colligating ecological footprint and economic globalization after COP21: Insights from agricultural value-added and natural resources rents in the E7 economies[END_REF]Shayanmehret et al. (2023), revenue from environmental taxes could be strategically allocated to renewable energy investments, countering the phenomenon of the "green paradox," where the prospect of reduced demand may lead to increased production of non-renewable energy sources, thereby exacerbating pollution [START_REF] Sinn | Public policies against global warming: a supply side approach[END_REF]. For example, studies by [START_REF] Dogan | Do energy and environmental taxes stimulate or inhibit renewable energy deployment in the European Union?[END_REF] argue for the allocation of environmental tax revenues to renewable energy development. They argue that renewable energy sources can significantly reduce emissions and promote sustainable growth, underscoring the need for a deliberate redirection of environmental tax revenues to the renewable energy sector. In addition, an analysis of G7 countries by [START_REF] Wang | Revisiting the environmental kuznets curve hypothesis in 208 counties: The roles of trade openness, human capital, renewable energy and natural resource rent[END_REF] found that environmental tax revenues, if properly allocated, contribute significantly to renewable energy development.

However, the effectiveness of environmental taxes in achieving environmental and economic goals largely depends on their design and implementation. A study by [START_REF] Li | Assessing the impacts of China's environmental tax using a dynamic computable general equilibrium model[END_REF] found that while environmental taxes help reduce emissions of most pollutants, they may have a negative impact on economic growth. This negative outcome could result from increased production costs and damage to international competitiveness associated with these taxes [START_REF] Mulatu | Environmental regulation and international competitiveness: a critical review[END_REF]. Further research by [START_REF] Aydin | Reducing CO2 emissions in the EU member states: Do environmental taxes work[END_REF] suggests that the economic outcomes of environmental taxes in the EU depend on the specific tax design. They found that beyond a certain threshold, the effectiveness of these taxes may deteriorate. Similarly, [START_REF] Chang | Exploring the economic impacts of carbon tax in China using a dynamic computable general equilibrium model under a perspective of technological progress[END_REF] found that poorly designed environmental taxes may lead to negative economic outcomes, such as economic contraction or even bankruptcy of firms, ultimately leading to job losses.

Given the dual effects of environmental taxes -both improving environmental quality and potentially contributing to environmental degradation -their impact on ecological footprints in countries with significant renewable energy consumption warrants further study. A comprehensive understanding of the role of environmental taxes requires a nuanced examination of their purpose; whether they serve primarily as genuine environmental interventions or are designed primarily as revenue raising instruments [START_REF] Karmaker | The role of environmental taxes on technological innovation[END_REF]. The conceptualization of environmental taxes as a new resource for the EU further amplifies their potential role in sustainable development [START_REF] Palenik | Concept of Environmental Taxes as EU's Own Resource and CGE Modelling of its Effects on Slovakia[END_REF]). [START_REF] Parry | Reforming the tax system to promote environmental objectives: An application to Mauritius[END_REF] suggestion that environmental taxes can increase government revenues, thereby providing critical funds for investments in clean technologies, underscores this point. Thus, green taxes not only act as a deterrent to environmentally harmful practices, but also generate resources that can be channeled into sustainable innovation. In addition, the management of the revenues generated by environmental taxes plays a key role in their effectiveness as a tool for environmental protection. In general, revenue from environmental taxes is earmarked for specific purposes, following the principle of special funds for special uses. This ensures that the funds raised by taxing environmentally harmful activities are reinvested in initiatives that mitigate environmental damage and support ecological restoration. This perspective is supported by Kombat and Wätzold (2019), who argue that environmental taxes have been successful in mitigating environmental problems in part because a portion of the tax revenue has been specifically earmarked for environmental protection measures. Thus, the true value of environmental taxes lies not only in their ability to discourage harmful environmental practices, but also in their potential as a source of funding for environmental protection and sustainable development initiatives. However, their effectiveness depends on the purpose of these taxes and how their revenues are managed. Therefore, an in-depth analysis of the role, implementation, and management of environmental taxes is needed to better understand their impact on ecological footprints and their potential role in promoting renewable energy consumption.

Environmental taxes therefore play an important role in promoting environmental sustainability and economic growth. However, their effectiveness is influenced by several factors, including the design of the tax, the expected response of non-renewable energy producers, and the strategic use of tax revenues. This complexity underscores the need for policymakers to take these factors into account when designing and implementing environmental tax policies. Continued empirical research is needed to refine these policies and increase their effectiveness in achieving desired environmental and economic outcomes.

Productive capacities and environmental degradation

It is now recognized that pursuit of both economic growth and environmental protection is feasible due to the relationship between productive capacities, environmental degradation, and economic development in the context of climate change. Pursuit of these objectives relies on types of productive capacities, including human capital, natural capital, energy, transport, information and communication technology (ICT), institutions, private sector, and structural change. The United Nations Conference on Trade and Development (UNCTAD) Productive Capacity Index (PCI) provides a framework for comprehensive evaluation and assessment of national productive capacity, including the country's its capacity to achieve sustainable economic growth while mitigating climate change. This framework captures the various factors that contribute to economic development while taking account also of environmental sustainability.

Human capital, which encompasses a country's cumulative knowledge, education, health, skills, and training, is widely recognized as the primary input to inclusive production [START_REF] Ashraf | Food security and environmental degradation: Do institutional quality and human capital make a difference[END_REF][START_REF] Wang | Unleashing the influence of natural resources, sustainable energy and human capital on consumption-based carbon emissions in G-7 Countries[END_REF]. Studies conducted across different methodologies, time periods, and geographical contexts consistently emphasize the central role of human capital, particularly its educational component, in promoting sustainable practices and mitigating environmental degradation. [START_REF] Saqib | Pollution Haven or Halo? How European countries leverage FDI, energy, and human capital to alleviate their ecological footprint[END_REF] found a significant relationship between human capital enhancement through education and reduced ecological footprint in 16 European countries from 1990 to 2020, while [START_REF] Meyer | Does education increase pro-environmental behavior? Evidence from Europe[END_REF] and [START_REF] Baiardi | Climate change awareness: Empirical evidence for the European Union[END_REF] highlighted the indispensable role of education in cultivating environmental awareness in Europe. [START_REF] Özbay | Exploring the role of education on environmental quality and renewable energy: Do education levels really matter[END_REF] and [START_REF] Ahmad | Is achieving environmental sustainability dependent on information communication technology and globalization? Evidence from selected OECD countries[END_REF] demonstrated the significant contribution of higher education to CO2 emission reduction in OECD countries from 1997 to 2019 and 1990 to 2018, respectively. Caglar and Askin (2023) examined the impact of economic globalization, human capital, gross capital formation, and total factor productivity on the ecological footprint in the top 10 competitive industrial performance economies for the period 1990-2018, acknowledging potential negative environmental impacts but emphasizing the positive role of renewable energy consumption and human capital. [START_REF] Mehmood | Environmental degradation and financial development: do institutional quality and human capital make a difference in G11 nations?[END_REF], using annual data from 1984-2017 for a group of 11 countries, noted the potential negative effects of financial development, but suggested that these effects could be mitigated by human capital and institutional quality. Çamkaya et al. (2022) showed that human capital has a negative effect on carbon emissions and ecological footprint in Turkey from 1980 to 2018. [START_REF] Liu | An analysis of the effects of human capital on green growth: effects and transmission channels[END_REF] highlighted the positive effects of educational attainment, renewable energy consumption, internet use, and financial development on green growth in China from 1991 to 2019. [START_REF] Wang | Revisiting the environmental kuznets curve hypothesis in 208 counties: The roles of trade openness, human capital, renewable energy and natural resource rent[END_REF] tested the EKC hypothesis based on an aggregate dataset of 208 countries from 1990 to 2018, highlighting the importance of trade openness, human capital, renewable energy consumption, and natural resource rent in achieving carbon neutrality globally. They also found that renewable energy consumption has a better emission reduction effect for countries before the EKC inflection point, while human capital has a better emission reduction effect for countries after the inflection point. [START_REF] Wang | Unleashing the influence of natural resources, sustainable energy and human capital on consumption-based carbon emissions in G-7 Countries[END_REF] demonstrated the nexus between natural resources, sustainable energy, human capital, and consumption-based carbon emissions in G-7 economies from 1976 to 2020, emphasizing the role of natural resources, clean energy, and human capital in preserving environmental quality. [START_REF] Karaduman | The effects of economic globalization and productivity on environmental quality: evidence from newly industrialized countries[END_REF] highlighted the negative correlation between economic globalization and human capital with ecological footprint, while emphasizing the positive relationship between GDP per capita and ecological footprint in emerging economies from 1975 to 2017. Despite the differences, these studies collectively confirm the significant and multifaceted role of human capital in achieving environmental sustainability and solidify its position as a vital asset in shaping the inclusive production of our world.

Natural capital includes natural resources and ecosystems and is crucial for sustaining economic growth and human well-being while also providing a wide range of ecosystem services that support human societies. In the EEAs, the depletion and deterioration of natural capital have been identified as among the main causes of environmental degradation [START_REF] Abbasi | Does natural resources depletion and economic growth achieve the carbon neutrality target of the UK? A way forward towards sustainable development[END_REF][START_REF] Du | Impact of financial inclusion and human capital on environmental quality: evidence from emerging economies[END_REF][START_REF] Farrell | Natural capital approaches: shifting the UN Decade on Ecosystem Restoration from aspiration to reality[END_REF][START_REF] Pascual | Valuing nature's contributions to people: the IPBES approach[END_REF][START_REF] Schlaepfer | Conserving biodiversity in the face of rapid climate change requires a shift in priorities[END_REF]. Areas such as energy and transport play a crucial role in promoting sustainable development.

Numerous studies indicate that utilizing renewable energy sources and developing more efficient transportation systems can result in reduced greenhouse gas emissions [START_REF] Chu | Determinants of ecological footprint in OCED countries: do environmentalrelated technologies reduce environmental degradation?[END_REF][START_REF] Dahmani | Decoupling Analysis of Greenhouse Gas Emissions from Economic Growth: A Case Study of Tunisia[END_REF][START_REF] Dogan | The impact of renewable energy consumption to economic growth: A replication and extension of[END_REF]Khan et al., 2022a[START_REF] Khan | The nexus between CO2 emissions, human capital, technology transfer, and renewable energy: evidence from Belt and Road countries[END_REF][START_REF] Saqib | Integration of renewable energy and technological innovation in realizing environmental sustainability: the role of human capital in EKC framework[END_REF]. In many economic sectors, ICTs have the power to reduce environmental impact and improve resources efficiency [START_REF] Ahmad | Is achieving environmental sustainability dependent on information communication technology and globalization? Evidence from selected OECD countries[END_REF][START_REF] Dahmani | The ICT, financial development, energy consumption and economic growth nexus in MENA countries: dynamic panel CS-ARDL evidence[END_REF][START_REF] Dahmani | The Information and Communication Technologies-Economic Growth Nexus in Tunisia: A Cross-Section Dynamic Panel Approach[END_REF][START_REF] Park | The effect of ICT, financial development, growth, and trade openness on CO2 emissions: an empirical analysis[END_REF][START_REF] Wang | The role of information and communication technologies in achieving hydropower sustainability: Evidence from European Union economies[END_REF]Xie et al., 2023). This strand of work highlights how ICTs contribute by reducing CO2 emissions through more efficient use of resources and sustainable consumption and production practices. ICT applications can increase resource use efficiency, reduce waste and emissions, and support the development of sustainable business models. The involvement of the private sector has been identified as important in several studies that highlight the role of corporate social responsibility and environmental management systems for promoting sustainable development (Biró and Szalmáné Csete, 2021;[START_REF] Puig | Insights on the environmental management system of the European port sector[END_REF]. Private sector innovation can contribute to the development of eco-friendly technologies and processes which reduce the effects of production and consumption on the environment. The productive capacity of private sector industries contributes significantly to environmental degradation (e.g., through the substantial greenhouse gas emissions by the transportation sector, [START_REF] Alkhani | Understanding Private-Sector Engagement in Sustainable Urban Development and Delivering the Climate Agenda in Northwestern Europe-A Case Study of London and Copenhagen[END_REF]. Policies that encourage low-carbon transport options have been shown to be effective in reducing these emissions. The manufacturing sector' also causes environmental degradation; sustainable manufacturing practices have been found to be effective for reducing the impact on the environment [START_REF] Quintás | Are small and medium enterprises defining their business models to reach a symbolic or substantive environmental legitimacy[END_REF][START_REF] Renukappa | Carbon emission reduction strategies in the UK industrial sectors: an empirical study[END_REF]. In addition, institutions and structural change are important for promoting sustainable development and reducing environmental degradation; several studies show that effective policy and regulatory frameworks can promote green investment and sustainable business practices [START_REF] Glass | Governance for achieving the Sustainable Development Goals: How important are participation, policy coherence, reflexivity, adaptation and democratic institutions?[END_REF][START_REF] Le | The impacts of globalization, financial development, government expenditures, and institutional quality on CO2 emissions in the presence of environmental Kuznets curve[END_REF][START_REF] Wurzel | The European Union in International Climate Change Politics[END_REF]. Institutional frameworks can also play a crucial role in facilitating the transition to low-carbon and resource-efficient economies [START_REF] Bradley | An exploration of institutional approaches in pursuing sustainable development[END_REF][START_REF] Cifuentes-Faura | European Union policies and their role in combating climate change over the years. Air Quality[END_REF]. Finally, structural change and particularly the shift towards a circular economy can reduce environmental impacts and promote sustainable growth significantly [START_REF] Calisto Friant | Analysing European Union circular economy policies: words versus actions[END_REF][START_REF] Moberg | Mobility, food and housing: responsibility, individual consumption and demand-side policies in European deep decarbonisation pathways[END_REF][START_REF] Zhao | Does structural transformation in economy impact inequality in renewable energy productivity? Implications for sustainable development[END_REF].

Overall, the literature demonstrates the need for transformative changes to productive capacities including both decarbonization and sustainable production and consumption practices, to mitigate the environmental impacts of these systems on climate change. While there is evidence to suggest that some types of productive capacity promote sustainable development, more research is needed to understand their specific effects in the context of the EEA countries.

Data and methodology

Data specification

We use a balanced annual panel dataset covering all EEA countries over the period 2000 to 2018 (see table 1). The sample countries are Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, and Sweden. The World Development Indicators (2023) provided data for CO2 emissions per capita (CO2_PC) measured in metric tons, and real GDP per capita (GDPC_PC) measured in constant 2015 US dollars, while the UNCTAD (2023) Productive Capacities Index (CPI) was used to measure productive capacities. We obtained the environmentally related tax revenue from the OECD (2023) database, which was defined as a percentage of GDP. The period of analysis was selected based on the availability of complete data for all variables considered.

Model specification and estimation strategy

The objective of this study is to investigate the impact of environmental-related taxes and productive capacities on climate change. The validity of the relationship is tested using the cointegration panel method based on the long-run relationship between the variables of interest and CO2 emissions. The data used for the study come from a relatively heterogeneous region which underlines the need to consider cross-section dependence and heterogeneity. The functional form of the model can be written as follows:

( ) ( ) ( ) ( ) 0 1 2 3 4 2 _ _ 2 _ it it it it it it LCO PC LGDP PC LGDP PC LERT LPCI       = + + + + +
where LCO2_PC is climate change, LERT is environmental-related tax, LPCI is productive capacity index, LGDP_PC is real GDP per capita, GDP2_PC is GDP per capita squared, and ε is the error term.

The econometric methodology consists of five stages. First, we determine the cross-section dependence of the variables using the Pesaran (2015) test for weak cross-section dependence. Second, we test the slope homogeneity of the cointegration coefficients using the delta test developed by [START_REF] Pesaran | Testing slope homogeneity in large panels[END_REF]. Third, we use the cross-section augmented Im, Pesaran and Shin (CIPS) and cross-section augmented Dickey-Fuller (CADF) developed by [START_REF] Pesaran | A simple panel unit root test in the presence of cross-section dependence[END_REF] to ascertain the level of integration of the variables. Fourth, having established the presence of cointegration relationships using the error-correction-based panel cointegration tests developed by [START_REF] Westerlund | Testing for Error Correction in Panel Data[END_REF], to estimate the long-run cointegration coefficients we apply CS-ARDL and DCCE techniques developed by [START_REF] Chudik | Long-Run Effects in Large Heterogeneous Panel Data Models with Cross-Sectionally Correlated Errors[END_REF] and [START_REF] Chudik | Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors[END_REF]. Finally, based on the estimation results we test the validity of the EKC hypothesis. The estimation approaches are well-suited to a panel data setting and allow for estimation of both long-and short-run relationships between the variables. The CS-ARDL method accounts for cross-sectional dependence and yields more efficient coefficient estimates; the DCCE approach enables simultaneous estimation of common and individual effects. We compare the results of both approaches to ensure robust results. Both methods account for crosssection dependence and endogeneity which makes them suitable for dynamic panel data models with small numbers of cross-sectional units and relatively short time periods.

Empirical results

Cross-section dependence tests

The initial step in this analysis is to investigate the potential presence of cross-section dependence in the data. Cross-section dependence can arise from various factors such as common shocks, unobserved factors, or spatial dependence which violate the assumption of independence of observations necessary for standard panel data models. To test for crosssection dependence, we apply the [START_REF] Pesaran | Testing Weak Cross-Sectional Dependence in Large Panels[END_REF] test for weak cross-section dependence. This test is based on correlation among the ordinary least square residuals and evaluates the null hypothesis of no cross-section dependence. Rejection of the null hypothesis indicates presence of cross-section dependence in the data which requires more advanced econometric techniques to account for this dependence.

Table 2 presents the results of the [START_REF] Pesaran | Testing Weak Cross-Sectional Dependence in Large Panels[END_REF] test for weak cross-sectional dependence for all the variables included in the panel data model. The results show the existence of crosssection dependence for all variables which implies that the model error terms are correlated across countries. This means that we need to account for cross-section dependence in the estimation process. The nature of cross-section dependency and the degree to which it affects the estimations must be considered when employing panel data models.

Slope homogeneity tests

The second step tests for slope homogeneity of the explanatory variables across different panel dataset units. We employ the [START_REF] Pesaran | Testing slope homogeneity in large panels[END_REF] delta test which examines whether the coefficients of the explanatory variables are homogeneous across different panel dataset units. This test is designed to determine whether the impacts of the explanatory variables on the different dependent variable units such as countries are consistent. The null hypothesis of the test is that the coefficients are homogeneous, with the alternative hypothesis being that they are heterogeneous. Rejection of the null hypothesis implies that across different countries the explanatory variables have different impacts on the dependent variable, indicating presence of slope heterogeneity.

Table 3 presents the results of the slope homogeneity test for the variables included in the model. In all cases, the probability values of the variables are less than 0.01 which rejects the null hypothesis of slope homogeneity. Thus, the model coefficients are heterogeneous, and the slopes vary from country to country which calls for heterogeneous panel techniques to account for these data differences.

Second-generation unit root test

In the third step of our study, we conducted unit root tests to examine the stationarity of individual series in the panel. Since our selected series suffers from both cross-section dependence and slope heterogeneity, we use a second-generation unit root test whose robustness and validity are well-known. Specifically, we employ second-generation stationary techniques which allow for identification and correction of the unit root problem while accounting also for cross-section dependence and slope heterogeneity. We conducted the CIPS and CADF tests developed by [START_REF] Pesaran | A simple panel unit root test in the presence of cross-section dependence[END_REF]; table 4 reports the results for levels and first differences. Our findings show that LnPCI is a stationary time series at level I(0), while LnCO2_PC, LnGDP_PC, LnGDP2_PC, and LnERT are non-stationary at their levels but become stationary at the first difference I(1).

Panel cointegration tests

The fourth step of the study investigates long run cointegration between variables. Table 5 presents the results of the [START_REF] Westerlund | Testing for Error Correction in Panel Data[END_REF] cointegration tests, which are particularly useful in the presence of heterogeneous slope coefficients and dependence among individual panel data. The null hypothesis assumes no long-term cointegration among variables, while the alternative hypothesis assumes the opposite. The [START_REF] Westerlund | Testing for Error Correction in Panel Data[END_REF] tests revealed that the null hypothesis of non-cointegration can be rejected at both the individual cross-section and panel level, allowing for the estimation of long-term equilibrium relationships between variables. Notes: The Gτ and Gα statistics examine co-integration for each cross-section, while Pτ and Pα test for cointegration in the panel when the null hypothesis assumes no cointegration.

Panel regression results

Having confirmed the existence of cointegration relationships among the variables, we employ the CS-ARDL and DCCE estimators developed respectively by [START_REF] Chudik | Long-Run Effects in Large Heterogeneous Panel Data Models with Cross-Sectionally Correlated Errors[END_REF] and [START_REF] Chudik | Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors[END_REF], to estimate the long-run cointegration coefficients. These estimators account for cross-section dependence and slope heterogeneity. The CS-ARDL method provides more efficient coefficient estimates while the DCCE approach allows for simultaneous estimation of common and individual effects. Both methods are suited to dynamic panel data models with small numbers of cross-section units and relatively short time periods which makes them appropriate for our study which uses panel data for EEA countries.

The short-term and long-term results of the CS-ARDL and DCCE models have similar signs and significance but differ slightly in their magnitude (see table 6). In both models, the error correction term (ECT) ranges from -0.652 to -0.609 indicating that approximately 65.2% and 60.9% of the disequilibrium observed in the previous year was corrected in the current year.

Based on the CS-ARDL estimates, the long-run results show that a 1% increase in real GDP per capita leads to a 0.628% increase in CO2 emissions, and that a 1% increase in real GDP per capita squared results in a 0.026% decrease in CO2 emissions. Similarly, in the DCCE model, a 1% increase in real GDP per capita leads to a 0.22% increase in CO2 emissions, while a 1% increase in real GDP per capita squared results in a 0.009% decrease in CO2 emissions. These findings confirm the existence of an EKC in the EEA countries which is consistent with recent research conducted by [START_REF] Bao | Applicability of the environmental Kuznets curve to construction waste management: A panel analysis of 27 European economies[END_REF] and [START_REF] Simionescu | Could quality of governance influence pollution? Evidence from the revised Environmental Kuznets Curve in Central and Eastern European countries[END_REF]. [START_REF] Chen | The role of environmental taxes and stringent environmental policies in attaining the environmental quality: Evidence from OECD and non-OECD countries[END_REF] also found a positive long-term relationship between economic growth and CO2 emissions for the EEA countries. This relationship is confirmed in [START_REF] Destek | Analyzing the environmental Kuznets curve for the EU countries: the role of ecological footprint[END_REF] who use a dynamic panel data model to examine the relationship between real income and ecological footprint in 27 EU countries. However, the positive correlation between GDP growth and ecological footprint in EAA countries suggests that the negative impacts of economic growth on the environment might be eased through the implementation of environmental-related taxes and incentives to promote development of productive capacity that responds to environmental issues while also promoting economic growth.

Our analysis, utilizing the CS-ARDL model and DCCE estimator, has revealed a significant negative correlation between productive capacities and CO2 emissions in both short and longterm periods within EEA countries. Specifically, our findings indicate that a 1% rise in productive capacities corresponds with a 0.357% and a 0.308% decrease in overall and per capita CO2 emissions, respectively. This correlation underscores the crucial role of robust productive capacities -characterized by strategic investments in education, renewable energy sources, sustainable transportation infrastructure, digital technologies, and sustainable business practices -in mitigating environmental degradation. In addition, our study revealed a notable inverse relationship between environmental taxes and CO2 emissions. According to the CS-ARDL model, a 1% increment in environmental taxes is associated with a 0.057% reduction in the environmental footprint. This correlation is reinforced by the DCCE model, which shows a 0.048% decrease in CO2 emissions for the same 1% increase in environmental taxes. Interestingly, the coefficient of the productive capacities index exceeds that of environmentally related tax revenue, implying that productive capacities have a more substantial influence on reducing CO2 emissions. This discrepancy could stem from variations in the design and implementation of environmental protection policies and the efficiency of institutions across different EEA economies. These findings not only align with existing research in the field but also underscore the imperative for robust productive capacities and effective environmental policies in reducing CO2 emissions and enhancing environmental quality (as demonstrated in works by [START_REF] Alkhani | Understanding Private-Sector Engagement in Sustainable Urban Development and Delivering the Climate Agenda in Northwestern Europe-A Case Study of London and Copenhagen[END_REF]Biró and Szalmáné Csete, 2021;[START_REF] Bradley | An exploration of institutional approaches in pursuing sustainable development[END_REF][START_REF] Calisto Friant | Analysing European Union circular economy policies: words versus actions[END_REF][START_REF] Chu | Determinants of ecological footprint in OCED countries: do environmentalrelated technologies reduce environmental degradation?[END_REF][START_REF] Cifuentes-Faura | European Union policies and their role in combating climate change over the years. Air Quality[END_REF][START_REF] Doğan | How environmental taxes and carbon emissions are related in the G7 economies?[END_REF][START_REF] Du | Impact of financial inclusion and human capital on environmental quality: evidence from emerging economies[END_REF][START_REF] Ghazouani | Exploring the Role of Carbon Taxation Policies on CO2 Emissions: Contextual Evidence from Tax Implementation and Non-Implementation European Countries[END_REF][START_REF] Glass | Governance for achieving the Sustainable Development Goals: How important are participation, policy coherence, reflexivity, adaptation and democratic institutions?[END_REF][START_REF] Le | The impacts of globalization, financial development, government expenditures, and institutional quality on CO2 emissions in the presence of environmental Kuznets curve[END_REF][START_REF] Moberg | Mobility, food and housing: responsibility, individual consumption and demand-side policies in European deep decarbonisation pathways[END_REF][START_REF] Neves | Determinants of CO2 emissions in European Union countries: Does environmental regulation reduce environmental pollution?[END_REF][START_REF] Oluc | The productive capacity and environment: evidence from OECD countries[END_REF][START_REF] Puig | Insights on the environmental management system of the European port sector[END_REF][START_REF] Quintás | Are small and medium enterprises defining their business models to reach a symbolic or substantive environmental legitimacy[END_REF][START_REF] Simionescu | Could quality of governance influence pollution? Evidence from the revised Environmental Kuznets Curve in Central and Eastern European countries[END_REF][START_REF] Wang | The role of information and communication technologies in achieving hydropower sustainability: Evidence from European Union economies[END_REF][START_REF] Wolde-Rufael | Effectiveness of environmental taxes and environmental stringent policies on CO2 emissions: the European experience[END_REF][START_REF] Zhao | Does structural transformation in economy impact inequality in renewable energy productivity? Implications for sustainable development[END_REF].

Moreover, our analysis validates the effectiveness of the European Union's ongoing efforts to minimize pollution transfer and implement carbon tariffs as part of the European Green Deal. Under this initiative, the EU is proactively implementing comprehensive measures, such as the "Fit for 55" package and the Emissions Trading System, to achieve climate neutrality by 2050 (European Parliament, 2023). A central element of these efforts is the Carbon Border Adjustment Mechanism, which imposes a carbon levy on imports from countries with less stringent climate regulations, thereby mitigating the risk of carbon leakage.

As a result, it is crucial to consider the economic capacity of nations when designing environmental policies. Countries with robust productive capacities, typically high-income countries, are in a better position to reduce CO2 emissions. At the same time, environmental tax policies can be powerful tools for reducing emissions, although their effectiveness depends on the economic capacity of the countries implementing them. The case of the EU illustrates how such policies can be used, adapted, and strengthened to achieve ambitious environmental goals. Our findings therefore underscore the critical role of environmental taxes and productive capacities in fostering sustainable and inclusive economic transitions, and the need for judicious design and implementation of environmental policies.

Conclusions and policy recommendations

Conclusions

This study aimed to investigate the complex relationships between GDP growth, productive capacities and environmental taxes and their combined effect on environmental quality. To address the methodological challenges, advanced second-generation CS-ARDL and DCCE methods were employed to effectively deal with cross-sectional dependence, slope homogeneity, and endogeneity issues. This robust approach enabled a comprehensive global assessment of the EKC across all 30 EEA countries from 2000 to 2018.

The results confirm the existence of the EKC relationship, suggesting that environmental quality improves once GDP growth reaches a certain threshold. Moreover, a significant negative correlation between environmental taxes and CO2 emissions was observed in both specifications, highlighting the effectiveness of fiscal policy in promoting environmental sustainability. The results also emphasize the crucial role of robust productive capacities in mitigating environmental degradation.

Policy recommendations

Based on these findings, several policy recommendations emerge to balance economic development and environmental sustainability:

First, fostering productive capacities in strategic sectors such as education, renewable energy, sustainable transportation, digital technologies, and sustainable business practices is critical for industrial decarbonization. By incentivizing investment in these sectors, countries can support the development of sustainable infrastructure and encourage the adoption of green technologies.

Second, there is a need to refine environmental tax policies to provide stronger incentives for industries to transition to greener practices while minimizing regressive effects on low-income households. This includes basing minimum tax rates on the actual energy content and environmental performance of fuels and electricity, continuously updating rates based on consumer prices, and broadening the tax base by eliminating exemptions and rebates.

In addition, policymakers should institutionalize and clarify initiatives such as the proposed revision of the Energy Tax Directive as part of the European "Fit for 55" package. The objectives and purpose of this revision should be clearly defined, with a particular focus on encouraging investment in new and innovative green industries and securing green tax revenues. This will facilitate the creation of a green financial system that will drive the transition to a sustainable and inclusive low-carbon economy.

Strengthening institutional capacities is an essential prerequisite for the successful implementation of environmental policies. Policymakers should improve enforcement mechanisms, promote transparency and accountability, and facilitate the sharing of best practices among countries. Improving institutional capacities will enable effective enforcement of environmental regulations and promote the adoption of sustainable practices.

Fostering regional and global cooperation is crucial to addressing the transboundary nature of climate change. Policymakers should encourage cooperation among nations, drawing inspiration from successful initiatives such as the European Green Deal. Refining mechanisms such as the Carbon Border Adjustment Mechanism will help prevent carbon leakage and promote global environmental justice.

Ensuring inclusive and sustainable transitions is paramount. Policymakers should design policies that prevent socio-economic inequalities and protect vulnerable groups during the transition to a low-carbon economy. Providing support, implementing retraining programs and establishing social safety nets for communities heavily dependent on high-carbon industries are critical aspects of this effort.

Promoting green growth through the adoption of green technologies, renewable energy and strong environmental regulations is essential. Policymakers should prioritize investments in sustainable infrastructure, encourage the use of renewable energy sources, and enforce environmentally friendly practices in industry.

Finally, citizen engagement should be strengthened to ensure effective implementation of these policy recommendations. Active citizen participation in energy and environmental development strategies, coupled with increased transparency in energy systems, will foster environmental awareness and promote sustainable practices.

Research limitations and future directions

Despite the significant contributions of this study, it is important to note that the geographical scope of our research is limited to the EEA countries. While this focus provides in-depth insights into the EKC within these countries, it limits the broader applicability of our findings to non-EEA countries with different socio-economic and environmental contexts. In addition, data availability for the variable of productive capacities was restricted to the period 2000-2018, which limits the time span of our analysis.

Future research could broaden the scope by including additional variables such as energy prices, institutional quality, and R&D expenditures to gain a more comprehensive understanding of the dynamics of environmental quality. Studies could also examine variations in environmental degradation and response strategies across countries and time periods. Understanding the gap between policy design and implementation could prove particularly insightful, as this gap can have a significant impact on policy effectiveness.

Table 1 .

 1 Variables' definition and descriptive statistics

	Variable	Description	Obs. Mean	Std. Dev. Min.	Max.	Source
	LnCO2_PC	CO2 emissions (metric tons)	570	7.584	3.431	2.927	25.604	WDI
		GDP per capita
	LnGDP_PC	(constant 2015	570	34349.660 28906.200 3717.677 178864.900 WDI
		US$)
		Environmentally
	LnERT	related tax revenue	570	2.580	0.688	0.471	5.000	OECD
		(% of the GDP)
	LnPCI	Productive Capacities Index	570	39.663	4.146	28.450	48.371	UNCTAD

Table 2 .

 2 [START_REF] Pesaran | Testing Weak Cross-Sectional Dependence in Large Panels[END_REF] test for weak cross-sectional dependence

	Variables (in log)

Note: The CD statistic is normally distributed under the null hypothesis of no cross-sectional dependence.

Table 3 .

 3 Slope Homogeneity Test[START_REF] Pesaran | Testing slope homogeneity in large panels[END_REF]

	Slope Homogeneity Tests	 statistic	P-value
	 test	16.949	0.000
	adj  test	20.490	0.000

Note: The null hypothesis for slope heterogeneity test is slope coefficients are homogenous.

Table 4 .

 4 Results of panel unit-root

	Variables (in log)	Level Without trend With trend	First-difference Without trend With trend	Order
	Cross-Sectionally Augmented IPS (CIPS)
	LnCO2_PC	-1.989	-2.525	-4.222***	-4.262***	I(1)
	LnGDP_PC	-1.721	-1.842	-2.911***	-3.169***	I(1)
	LnGDP2_PC	-1.763	-2.603	-3.149***	-3.165***	I(1)
	LnERT	-1.415	-2.394	-3.863***	-3.995***	I(1)
	LnPCI	-2.227**	-2.624*	-4.882***	-4.897***	I(0)
	Cross

-Sectionally Augmented Dicky-Fuller (CADF)

  The panel unit-root test was performed under the null hypothesis wherein the variables are homogeneous non-stationary. ***, **, and * denote statistical significance level at 1%, 5%, and 10%, respectively.

	LnCO2_PC	-1.550	-2.320	-3.570***	-3.820***	I(1)
	LnGDP_PC	-1.817	-1.801	-2.948***	-3.112***	I(1)
	LnGDP2_PC	-1.775	-1.771	-2.905***	-3.154***	I(1)
	LnERT	-1.185	-2.347	-3.930***	-3.995***	I(1)
	LnPCI	-2.130*	-2.781**	-4.695***	-4.742***	I(0)

Notes:

Table 5 .

 5 [START_REF] Westerlund | Testing for Error Correction in Panel Data[END_REF] Panel cointegration tests

	Statistic	Value	Z-value	P-value
	Gτ	-5.053	-17.880	0.000
	Gα	-11.344	-3.099	0.001
	Pτ	-24.236	-12.989	0.000
	Pα	-11.049	-5.880	0.000

Table 6 .

 6 Short-run and long-run estimates using the CS-ARDL and DCCE methods

CS-ARDL DCCE Variables Coefficient Std. Err. P-value Coefficient Std. Err. P-value Short-run results

	LnGDP_PC	0.987***	0.278	0.000	1,109***	0,411	0,000
	LnGDP2_PC -0.052***	0.013	0.000	-0,046***	0,019	0,000
	LnERT	-0.017*	0.009	0.074	-0.001*	0.004	0.068
	LnPCI	-0.138**	0.042	0.047	-0.113*	0.022	0.094
	ECT(-1)	-0.652***	0.085	0.000	-0.609***	0.091	0,000
				Long-run results
	LnGDP_PC	0.628***	0.175	0.000	0,821***	0,220	0.000
	LnGDP2_PC -0.026***	0.013	0.000	-0,031**	0,009	0.001
	LnERT	-0.057**	0.038	0.028	-0.048**	0.018	0.035
	LnPCI	-0.357**	0.322	0.002	-0.308***	0.277	0.000
	CD Statistic	-0.790		0.427	-1.040		0.298

Note:

The CD statistic test is standard normally distributed under the null of hypothesis of weak cross-section dependence. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.


Jesus Gonzalez-Feliu

Javier Feizar

Rueda-Velasco

Joëlle Morana

Amir Hasnaoui

Wilson Adarme-Jaimes

PRO-ACTION RESEARCH FOR PERFORMANCE IMPROVEMENT OF SUPPLY CHAINS: FROM A SOCIAL IMPROVEMENT CASE TO A GENERALIZED FRAMEWORK

Keywords: Supply Chain Traceability, Social Improvement, Digitalization, Performance, Food assistance programs PRO-ACTION RESEARCH

This paper aims to address how interactive research (via the adaptation of the PrOACT view of thought) can support the improvement of social improvement supply chains, via the case study of Bienestarina in Colombia. To do that, an interactive research case study is developed and proposed. First, the main issues of social improvement logistics are presented. Then, the proposed methodology is defined from the four theories and methodologies: the PrOACT way of though, the group decision theory, the social systems theory and the Supply Chain Processes Management methodology. After that, the case study is presented, then, as results, the main characteristics of the Bienestarina supply chain will be presented and analysed, to identify the main information disruptions. After that, two proposed improvement solutions are analyzed and compared, identifying the levers and limits of their respective deployment, to understand on which bases the final implementation choice has been made and which trade-offs were needed.

INTRODUCTION

The performance of a supply chain is crucial for its daily execution, but also for its technical, economic, and social continuity. This is the case of not only commercial supply chains, but also those of humanitarian nature. Indeed, although goals and objectives are not the same (Holguin-Veras et al., 2012), the efficiency and efficacity of humanitarian supply chains results on reaching those goals, which are mainly the decrease of suffering and diseases. In humanitarian supply chains, different categories can be established (Gonzalez-Feliu et al., 2019), related to the type of crisis they deal with: long-term crises, exceptional crises, recurrent crises, or social improvement needs. Indeed, social improvement systems are those issued to bring inclusive growth and welfare to populations in difficulties (Maldonado and Moyá, 2013;[START_REF] Thomas | Inclusive growth: The global challenges of social inequality and financial inclusion[END_REF], via economic and financial support, nutritional improvement or resource/logistics help, among others (Gonzalez-Feliu et al., 2018). In this last category, less studied, we find many schemes having important lacks that affect performance. This is the case of food assistance programs (Rueda- [START_REF] Velasco | El sistema de distribución y la eficacia en programas de asistencia nutricional infantil[END_REF], which are often seen as governmental humanitarian projects aiming to support the fight against malnutrition via the supply of complementary food products to sensible populations. However, those programs have little knowledge of supply chain management, relying mainly on service providers without a central, integrated monitoring of the supply operations by the program's promotion institution. Indeed, few studies can be found (either in scientific or practice literature) about the assessment of food assistance programs efficiency on a supply chain management perspective, mainly in those countries having a high number of families facing malnutrition (Information Resources Management Association, 2021).

To improve those programs' supply chains, digitalization can play an important role (Rueda- [START_REF] Rueda-Velasco | Methodology for the Design of Traceability System in Food Assistance Supply Chains: Case Bienestarina, Colombia[END_REF]. Indeed, recent works showed that the main problems those supply chains face are related to the lack of information tracking, traceability and synchronization/integration, issues that can be improved by digitalization and ICT tools [START_REF] Betancur Betancur | Diseño de una metolodología de gestión de tecnología e innovación para grupos de investigación[END_REF]Cruz Castelblanco, 2019;[START_REF] Knoops | Adoption of a Trackability Tool among Humanitarian Practitioners in Local Units: A Field Study on a Food Assistance Program in Colombia[END_REF][START_REF] Rueda-Velasco | Methodology for the Design of Traceability System in Food Assistance Supply Chains: Case Bienestarina, Colombia[END_REF], 2021), since main dysfunctions are related to the lack of tracking and exchanging information concerning the efficiency of the whole supply chain process and its components (Gonzalez-Feliu et al., 2018). In any case, the adoption of digital technologies and traceability is not always easy, and although traceability is a popular subject in food supply chains, it is not the case in distribution systems related to food assistance programs [START_REF] Velasco | El sistema de distribución y la eficacia en programas de asistencia nutricional infantil[END_REF]. For those reasons, the analysis and implementation of traceability tools in those types of supply chains require a good comprehension of the context of application, and a contextual or interactive planning approach (Ackoff, 1994[START_REF] Ackoff | A brief guide to interactive planning and idealized design[END_REF]. Thus, research needs to be re-defined and adapted to catch the reality of the context, and results obtained need at their time to be compared to that reality and more precisely the main objective the involved stakeholders fixed with respect to the research. A pure "observational research" approach seems having their limits, and action research needs to include the main issues of interactive planning to lead to applicable decision-making issues.

For those reasons, this paper aims to propose a methodology to carry out action research from the PrOACT way of thought (Raifa et al., 2001) and the interactive planning issues of [START_REF] Ackoff | A brief guide to interactive planning and idealized design[END_REF] adapting it to a social improvement supply chain case, that of the Bienestarina production and distribution in Colombia. First, the main issues of social improvement logistics are presented. Then, the proposed methodology is defined from the four theories and methodologies: the PrOACT way of though, the group decision theory, the social systems theory and the Supply Chain Processes Management methodology. After that, the case study is presented, then, as results, the main characteristics of the Bienestarina supply chain will be presented and analysed, to identify the main information disruptions. After that, two proposed improvement solutions are analyzed and compared, identifying the levers and limits of their respective deployment, to understand on which bases the final implementation choice has been made and which trade-offs were needed.

AN OVERVIEW ON SOCIAL IMPROVEMENT LOGISTICS

As seen above, the aim of food assistance programs is to fight hunger and malnutrition. It can then be considered as a case of social improvement logistics (Orwell and Dawes, 1993), a subset (often under-studied) of humanitarian logistics (Gonzalez-Feliu et al., 2019). In humanitarian support organizations and actions, we find three main types of logistics problems:

(1) supply chain issues related to long-term crises (which can be planned in advance), (2) humanitarian logistics relief facing exceptional crises, those that are difficult to anticipate (such as terrorist acts or the recent sanitary crisis of COVID-19, among others), (3) humanitarian logistics facing recurrent crisis, similar to that above but in cases where the causes and impacts of a future crises, although not forecasteable precisely, can be anticipated from previous events, and (4) social improvement logistics, related to distributing products to support everyday needs of poor and sensible populations and improve their social status. Although humanitarian logistics (both for disasters or post-disaster) is nowadays a popular research subject [START_REF] Kovács | Identifying challenges in humanitarian logistics[END_REF][START_REF] Apte | Humanitarian logistics: A new field of research and action[END_REF][START_REF] Chandes | Investigating humanitarian logistics issues: from operations management to strategic action[END_REF][START_REF] Holguín-Veras | Disaster Response Logistics: Chief Findings of Fieldwork Research[END_REF], we find a lower scientific interest for social improvement logistics. Indeed, we find a first statement on the importance of logistics in supporting the social welfare, or social improvement, made by Orwell and Dawes (2007), after what we observe only three works related explicitly to the logistics of social improvement: [START_REF] Stock | Logistics thought and practice: a perspective[END_REF] is the fist, to the best of our knowledge, that states the poor contribution of logistics research to evidence its contribution to social welfare; [START_REF] Adivar | Improving social welfare chain using optimal planning model[END_REF] focus on the notion of value chain for social improvement and welfare; finally, [START_REF] Maldonado | The Challenge of Implementing Reverse Logistics in Social Improvement: The Possibility of Expanding Sovereignty Food in Developing Communities[END_REF] show the importance of combining social improvement policies with reverse logistics in developing and improving food banks actions and logistics schemes. Finally, recent works focusing on the distribution processes of food assistance programs address some questions of social improvement logistics but without an explicit definition of this notion [START_REF] Clark | Innovations in international food assistance strategies and therapeutic food supply chains[END_REF]Cruz Castelblanco, 2019;[START_REF] Knoops | Adoption of a Trackability Tool among Humanitarian Practitioners in Local Units: A Field Study on a Food Assistance Program in Colombia[END_REF][START_REF] Rueda-Velasco | Methodology for the Design of Traceability System in Food Assistance Supply Chains: Case Bienestarina, Colombia[END_REF][START_REF] Peters | The nutritious supply chain: optimizing humanitarian food assistance[END_REF].

The first categorizations of social improvement logistics are found in Gonzalez-Feliu et al. (2018[START_REF] Knoops | Adoption of a Trackability Tool among Humanitarian Practitioners in Local Units: A Field Study on a Food Assistance Program in Colombia[END_REF], in a comparison to other humanitarian logistics visions. Social improvement logistics aim to deploy logistics systems to bring vulnerable populations with the goods and services they need for improving their daily life conditions. With respect to other categories of humanitarian logistics, most issues can be planned, since they are acting with daily life improvement, but are of particular importance since the consequences of those logistics systems' efficiency have a direct impact on populations' growth [START_REF] Anand | Inclusive growth: Measurement and determinants[END_REF].

According to Gonzalez-Feliu et al. (2018), there are 5 sub-categories of social improvement initiatives:

1. Primary economic improvements (mainly by subsidies and income transfer actions to beneficiaries).

2. Cost reduction to improve nutrition and welfaire (mainly by subsidies to retailers and distribution companies).

3. Food access initiatives (by bringing beneficiaries, hospitals, nurseries and schools foods).

4. Education and monitoring initiatives (by promoting good habits and/or monitoring the risk of families and sensible groups of the population regarding malnutrition).

Promotion and development of self-production.

In this research, we deal with food access initiatives, and more precisely with nutrition improvement programs. Making such foods arriving to destination (i.e. beneficiaries) need the deployment of supply chains that are not commercial and cannot be monitored on the basis of classical SCM KPIs, and remain, in many countries, not always integrated (Gonzalez-Feliu et al., 2018). Main works in this field (i.e. the distribution processes and supply chains of food assistance programs and food access initiatives) remain mainly related to supply chain or transport optimization (Cruz Calstelblanco, 2019;[START_REF] Peters | The nutritious supply chain: optimizing humanitarian food assistance[END_REF][START_REF] Velasco | El sistema de distribución y la eficacia en programas de asistencia nutricional infantil[END_REF], ICT/ITS design-development [START_REF] Rueda-Velasco | Methodology for the Design of Traceability System in Food Assistance Supply Chains: Case Bienestarina, Colombia[END_REF] or supply chain design [START_REF] Clark | Innovations in international food assistance strategies and therapeutic food supply chains[END_REF]. In all cases, the problems addressed are a lack of efficiency of supply chains and to solve them, top-down, engineering approaches are used (as on many operations research and management science applications), with the conviction that current systems are inefficient by organizational gaps that can be solved via optimization. But as showed by Ackoff (1994),

those methods are a way to deal with problems but not the only one to solve them. Indeed, all those methods result into what Ackoff (1994) call "problem resolution", i.e. the use of known methods and techniques, in a quasi-replicational viewpoint, to deal with a problem, sometimes adapting the problem to the existing models and methods and not the opposite. However, there are other two ways to deal with a problem (that for sure start by resolution, but complete it):

problem solution (i.e. the definition of unexisting methods to make the problem disappear, at least currently) and problem dissolution (i.e. the identification of variables and issues that can be change in a way that the problem has none reason to exist anymore, making it disappearing permanently, or in Ackoff's words, dissolving it). To extend and evolve problem resolution techniques leading then to more long-term consequences on the capability to make the problem disappear, it is important to address problems in a more interactive way. To do that: to main, complementary visions can be addressed: that of Raiffa ( 2007) related to finding the roots of a problem and defining various solutions to finally make tradeoffs and consensus, and that of [START_REF] Ackoff | Optimization+objectivity=optout[END_REF] aiming to start by a first modeling and problem solving approach which is compared to the decision needs and the problem's reality and modified iteratively until a satisficing solution (for the decision makers) is found. Both approaches are complementary and have similarities. For those reasons, this paper aims to apply an interactive planning and research approach based on both frameworks to deal with a real problem of food access supply chains: that of the Bienestarina distribution processes in Colombia.

THEORETICAL AND METHODOLOGICAL FRAMEWORK

Since the main problem addressed in this research is of applicative nature, it is important to examine it on an applicative way, and the "observation" viewpoint or the "theoretical optimization" one both remain little adapted to the field of application: that of food assistance programs. Indeed, the aim of such programs is to provide vulnerable population with dietary complements to improve their daily nutrition conditions. This research is aimed at improving such programs and supporting institutions and NGOs on the deployment of social improvement logistics policies. For that reason, action-research seem the most adapted category of research methods that can be used. More precisely, theory of practice in social systems [START_REF] Ackoff | A theory of practice in the social systems sciences[END_REF] is followed here. Indeed, supply chains, as well as organizations and societies, among others, can be seen as social systems. Social systems can be defined as "open systems that (1) have purposes of their own, (2) at least some of whose essential parts have purposes of their own, and (3) are parts of larger (containing) systems that have purposes of their own" (Ackoff, 1994).

The author states also that systems where people play an essential role cannot be completely understood, and then managed, if viewed in other ways than as social systems. Seeing the considered field as a social system raises also the questions of how identifying the problems to be solved in order to correspond to the organization's aims, that of the method and models proposed to deal with the problem and that of how addressing eventual changes the research will identify as necessary for improvement [START_REF] Ackoff | A theory of practice in the social systems sciences[END_REF], among others.

To address all three of them, four frameworks are called here, which are:

• The PrOACT way of thought [START_REF] Keeney | Foundations for making smart decisions[END_REF]Raiffa et al., 2002), since it allows to address a problem in an interactive way, relating it directly to practice. The PrOACT methodology identifies 5 stages: 1) Defining Problems; 2) Setting Objectives; 3)

Generating Alternatives; 4) Assessing Consequences; 5) Making Tradeoffs.

•

The Optimization cycle [START_REF] Ackoff | Optimization+objectivity=optout[END_REF]Gonzalez-Feliu, 2019), which sees the problem solving as a cyclical procedure that starts from the observation of a reality, the definition of a decision problem, the modelling of the problem, the resolution of that problem (by proposing solving methods), and the validation of the solution with respect to the model, the problem and the reality represented. If one of the three validations is unsatisfactory, the cycle in re-iterated until all three validation conditions are verified.

•

The Group Decision Analysis Theory [START_REF] Keeney | Foundations for group decision analysis[END_REF], which defines the decision processes on a group and their relationships to individual decisions. That theory is completed by the decision distance issues of Gonzalez-Feliu et al. ( 2013), mainly those guiding and orienting consensus searching.

•

The Supply Chain Business Process Management Components (Lambert, 2008), which can be divided into physical and technical (the physical, financial, work and information flow structures of a supply chain, the company's organizational structure, which are of different types, the optimization/organization methods), and human and behavioural (the structures of culture and attitude, rewards and risks, and power and leadership, plus the management methods).

Those four frameworks have been mixed to propose a pro-action research method. The conceptual and methodological framework proposed here can be summarized in the following schema (Figure 1): The methodology proposed here is that of case study research (Eisenhardt, 1989). In other words, we will start by presenting the case of Bienestarina supply chain in Colombia (managed and organized by a centralized stakeholder&r), then we tried to identify the main traceability issues and generalize it mainly for transferability issues.

To do this, we propose the following methodological frameworks organized as follows:

• Characterization of the Bienestarina supply chain.

• Identification of the main problems and dysfunctions due to lack of traceability.

• Definition of traceability needs.

• Proposal of two solutions: a combined and an integrated traceability alternatives.

• Suitability assessment and deployment issues.

The Bienestarina supply chain characterization will be made via an adapted framework issued from [START_REF] Cooper | Supply chain management: more than a new name for logistics[END_REF] but extended to social improvement supply chains. It will combine a supply chain process modelling, an analysis of social improvement management components and an assessment of the resulting network structure, in the sense of Lambert (2001). Then, a 24 month research period has led to the observation of the Bienestarina Supply Chain, various exchanges with the different stakeholders involved, a set of quantitative surveys, an analysis of the current traceability tools, the identification of current problems and the proposal of solutions to improve the current lacks, some of which have been implemented and followed.

FIRST RESULTS

Case study presentation

Bienestarina is a public program launched in 1976 led by the Colombian Institute of Family Welfare (ICBF) that manages direct transfers of food to the vulnerable population to fight malnutrition, especially in children and teenagers. With an annual budget of 40 USD million, the ICBF and the Colombian government projected 22 thousand tons/ year to produce and deliver to reach around six million of beneficiaries annually [START_REF] Dnp | Conpes[END_REF].

The physical supply chain structure includes public and private actors. Among these actors is the public entity in charge of leading the program, a private logistics service provider who manage food assistance's production and distribution, about 15 private companies work as raw materials suppliers, beneficiaries (individuals, associations, public institutions like hospitals, schools, etc.) and volunteers.

The design of the structure of the distribution system is fundamental to guarantee access in a context of national demand to a geographically dispersed population as shown in Figure 3

Analysis of the system

The distribution system has been configured with two production plants that send the food supplement freight to 25 warehouses (Figure 3 (a)). From there, the product is distributed to around 5000 delivery points at the national level. The production plants can also fulfill the role of distribution centers and could send the product directly to the delivery points. As can be seen, the structure of the system covers a large part of the national territory because of the maintenance and financing of the program for over 40 years. Figure 4 shows a Bienestarina supply chain scheme with its main longitudinal structure (stakeholders) and both physical and information flows. The PrOACT interactive analysis led to the following main issues.

• Agreed Identified Problems: There is a high difficulty to track a part of the information (mainly at the final echelons of the supply chains, i.e. between the executing units and the beneficiaries), which results on high product losses.

Moreover, processes seem integrated in the majority of the supply chain (i.e. until executing units) by the current contractual issues with Ingredion, but that integration is cut at the last echelon. Finally, all stakeholders agree that cost is not a major issue, and product losses and families not accessing to products are more important questions to address.

• Objectives: the main objectives that have been defined are the need of improving service rates (to feed better populations) and that of a higher information transparency.

• Alternatives: various alternatives have been analyzed and compared. Supply chain optimization seems little relevant at inbound level, and production, as the supply chain is entirely planned in advance, does not need further optimization.

Optimisaiton is very difficult at distribution level, mainly in the last echelon, made of volunteers. This lase echelon is critical and the main alternatives seen as improving it are related to process integration and information transparency. For that reason, traceability seems the most suitable issue in terms of cost and acceptability.

Two traceability tools have been analyzed and proposed: the first is an integrated solution and the second the combination of two non-integrated tools, the existing one (that does not cover the last echelon) and a second one to cover it.

• Consequences: after examining the two solutions, the integrated one seems to present high risks (continuity, culture mainly). The non-integrated solution (2 tools)

presents decoupling points but is more accepted than the first one.

• Tradeoffs: it seems that an information system is currently available until local points. A second solution (social network-based) seems easily accepted by volunteers. For that reason, the second traceability approach (2 combined tools, with a decoupling point at executing units) has been accepted by ICBF.

The results allowed to identify a set of dysfunctions, which main causes are:

• Registered Beneficiaries' accuracy.

• Disintegration between supply chain processes and lack of integral information traceability.

• Lack of coordination between social scope and the scope of supply chain informational, functional, and physical structures.

• One single supply chain structure for heterogeneous population groups (e.g. rural, urban, or ethnical) and heterogeneous territory features ( urban concentred and rural dispersed population)

• Public contracts for 4PL-5PL operators do not cover the full program scope.

• Disfunctions related to the different ways of consumption.

• Lack of last mile tracking.

• Lack of primary data about efficiency of the Bienestarina program in fighting malnutrition.

• Loss of product because of improper storage or packaging • High levels of unclaimed product.

• Important levels of distributed product for improper use.

Those causes highlight the importance of having robust traceability and transparency of information, and the main disjointing point of the information low continuity seems to be the link between regional distributors and executing units (i.e. the volunteers that finally bring Bienestarina to beneficiaries). Those units are composed of volunteers and the current tracking tools stop at the regional point level, the last part of the supply chain relying only on paperbased registers, most of them being difficult to verify its accuracy. For that reason, an analysis of traceability solutions to improve the continuity and transparency of that information have been assessed.

Two main solutions are proposed. The comparison of such solutions shows some important concerns. In technical terms, the information applications must be synchronized to an address where the server is located; it could be an issue for the update process of all devices. The server as a central entity may have defaults; all devices must be pointing to a specific URL or address, if it is changed, it is necessary to update each application by tracking. The system proposed may allow after few testes to be an example to implement similar systems on a different first need products that are distributed to vulnerable populations.

In consequence, it is important to a comprehensive development logistics for this case, the implementation of ICT strategies, methods and techniques of various kinds, according to each region's nature of the Colombian territory to bring Bienestarina just in time and make compliance with the fundamental rights of the vulnerable population. More in depth studies of supply chain operators and logistics information technology allows to strengthen the Bienestarina logistics system and to get more sustainability efficient results.

A recent interview with J.P. Cruz, program director at ICBF and former researcher in the Bienestarina improvement team revealed that the acceptability of the chosen system was high, and the qualitative appreciation of both volunteers and beneficiaries has strongly increased. Due to recent events of sanitary importance, a quantitative evaluation of the improvements is not still available but the improvement of the Bienestarina distribution system can be highlighted by the fact the supply chain was used to support logistics operations of sanitary importance during the COVID-19 crises, showing that some of the deficiencies have been reduced and the system increased its robustness.

Other evidence on the improvements of the system can be read in a recent work trying to propose an automatized system to register the last-echelon issues (and then to replace the current system), proposed by Marquez-Diaz and Perilla-Benitez (2020). Authors base their work on the observation that the main issue nowadays arise on the fact volunteers and operators have orthograph and grammar difficulties, having a difficulty to standardize information, but no explicit mention to freight losses or service quality difficulties as stated before the proposed pro-action research approach is made in their work. It is clear that improvements on the system are still needed but one of the major limitations of the system seems to be reduced by an interactive research approach aiming to understand the causes of the problem and then trying to solve/dissolve it. Moreover, the proposed solution seems having been easily implemented and accepted, and even if it can obviously be still improved it has its positive effects.

However, traceability issues are not the only ones to be considered. The human factor, the regional disparities and the lack of accessibility of some regions (which need specific transport modes, such as barges or helicopters since roads are sometimes absent) need to be taken into account in the proposal of efficiency management tools. The case study shows the complexity of the problem, the strengths of action-research and the central place of traceability issues that go beyond the only technical issues to consider also social and human factors. All those elements play an important role in assessing the efficiency and ensuring a good functioning of food assistance programs based on the distribution of dietary complements.

CONCLUSION

This paper proposed an interactive, proactive methodology allowed to exchange with stakeholders and identify the real problems to solve, and was applied to solve an information and integration problem at ICBF, Colombia, for the Bienestarina distribution food improvement program. After examining, in a PrOACT way, the problem, traceability was identified as the most suitable issue to address to improve the Bienestarina supply chain in a cost-speedacceptability equilibrium. A first traceability solution, which was more integrated and allowed a better improvement, had little acceptance, for both cost issues and the lack of integration culture in the Bienestarina supply chain (mainly at the last echelon, made of non-logistics volunteers). Also functionality and education issues constituted a limit for implementing this solution. Exchanging with ICBF and SC stakeholders allowed to implement a more suitable solution, that integrates the information system of the logistics provider (Ingredion) of the supply chain (from producers to executing units) with a social network information system able to be used by volunteers. This solution is working since 2017 and the SC efficiency and sustainability increased highly, although a quantitative evaluation would reinforce the already observed qualitative feelings and is being planned for a moment the sanitary conditions would be more stable. Finally, further works will try to generalize the proposed framework to problemsolving and decision support in other SC fields.

Figure 1 :

 1 Figure 1: The theoretical-methodological framework proposed here

Figure 2 :

 2 Figure 2: Framework to characterize the supply chain in social improvement systems and identify the main lacks (authors' elaboration, adapted from Cooper et al., 1997) As a second step, we propose the description of the main logistics problems regarding the product traceability. This is done as a conclusion of the interviews' analysis and the application the AFNOR (2014) framework, to identify which dysfunctions in the four base activities (plan, program, execute and control) are observed at each stage of the supply chain integration level.As a third step, there is an analysis about the needs of the stakeholders involved in the Bienestarina Supply Chain, also on the basis of the interviews results. Finally, the fourth and fifth step consist on the comparison of two tools: an integrated one, issued from[START_REF] Rueda-Velasco | Methodology for the Design of Traceability System in Food Assistance Supply Chains: Case Bienestarina, Colombia[END_REF], and the combination of a commercial traceability tool for B2B commercial logistics and the implementation of an ad hoc traceability solution for final deliveries[START_REF] Rueda-Velasco | Methodology for the Design of Traceability System in Food Assistance Supply Chains: Case Bienestarina, Colombia[END_REF]. Those two tools are assessed and compared using a framework that combines risk assessment, adoption issues and functional ICT assessment. Finally, a discussion about the proposal is presented, as well as the main generalization issues.

Figure 3 .

 3 Figure 3. Facilities Location in the Bienestarina distribution system. (a) Factories and warehouses location; (b) Delivery Point location.

Figure 4 .

 4 Figure 4. Bienestarina supply chain scheme.