Search

Abstract Species composition of forests is a very important component from the point of view of nature conservation and forestry. We aimed to identify 10 tree species in a hilly forest stand using a hyperspectral aerial image with a particular focus on two invasive species, namely Ailanthus tree and black locust. Deep learning‐based training data augmentation (TDA) and post‐classification techniques were tested with Random Forest and Support Vector Machine (SVM) classifiers. SVM had better performance with 81.6% overall accuracy (OA). TDA increased the OA to 82.5% and post‐classification with segmentation improved the total accuracy to 86.2%. The class‐level performance was more convincing: the invasive Ailanthus trees were identified with 40% higher producer's and user's accuracies (PA and UA) to 70% related to the common technique (using a training dataset and classifying the trees). The PA and UA did not change in the case of the other invasive species, black locust. Accordingly, this new method identifies well Ailanthus, a sparsely distributed species in the area; while it was less efficient with black locust that dominates larger patches in the stand. The combination of the two ancillary steps of hyperspectral image classification proved to be reasonable and can support forest management planning and nature conservation in the future.

A legjobb-rosszabb skálázás (BWS) az adatgyűjtés egyik módszere és/vagy annak elmélete, hogy a válaszadók miként adják meg a lista első és legrosszabb rangsorolását. Cikkemben azt vizsgálom meg, hogy mi az a best-worst scaling (BWS), milyen területeken használják előszeretettel, illetve mi maga a módszer. Ezután rátérek a BWS metódusára, ezen belül is megvizsgálom elemét: a BWS objektum esetet (1. eset), a BWS profil esetet (2. eset) és BWS többprofil esetet (3. eset). Részletezem a BWS használatát a marketingkutatásban, ezután pedig összehasonlítom a Likert-skálás módszert és a BWS-t. Konklúzióimat cikkem végén összegzem.

Buildings worldwide use a large amount of energy and, hence, contribute to increasing the level of greenhouse gases emission (GHG). It was realized that most electrical energy is used in buildings for heating, cooling, and ventilation purposes. To deal with environmental issues, the concepts of renewable energies and clean or green energy sources have been a part of academic discussions. A review of the literature unveils that most of the prior research in the GHG domain focused on the production side of producing renewable energy by opting for different cleaner energy sources (for example, solar energy). Although such studies have contributed significantly to advancing the field, it is also important to change the energy consumption behavior at the level of individuals for decarbonization. However, such a debate to promote the pro-environmental behavior (PEB) of employees from the perspective of energy consumption remains an understudied area. Against this backdrop, this research was carried out to promote PEB at the level of employees through corporate social responsibility (CSR) and green organizational practices in the healthcare sector of an emerging economy. The current research also focused on personal employee values, especially altruistic values, to spur their PEB. The data for the current work was collected from employees of different hospitals by employing a survey strategy (n = 441). To analyze the data, structural equation modeling was considered. The results showed that CSR directly and indirectly (via green organizational practices) influences employees’ PEB, whereas the altruistic values of employees produce a significant conditional indirect effect on the above relationship. The current research offers different implications for theory and practice, which are discussed in detail.

In view of scarcity of traditional energy resources and environmental issues, renewable energy resources (RERs) are introduced to fulfill the electricity requirement of growing world. Moreover, the effective utilization of RERs to fulfill the varying electricity demands of customers can be achieved via demand response (DR). Furthermore, control techniques, decision variables and offered motivations are the ways to introduce DR into distribution network (DN). This categorization needs to be optimized to balance the supply and demand in DN. Therefore, intelligent algorithms are employed to achieve optimized DR. However, these algorithms are computationally restrained to handle the parametric load of uncertainty involved with RERs and power system. Henceforth, this paper focuses on the limitations of intelligent algorithms for DR. Furthermore, a comparative study of different intelligent algorithms for DR is discussed. Based on conclusions, quantum algorithms are recommended to optimize the computational burden for DR in future smart grid.

The green innovations in the energy sector are smart solutions to meet the excessive power requirements through renewable energy resources (RERs). These resources have forwarded the revolutionary relief in control of carbon dioxide gaseous emissions from traditional energy resources. The use of RERs in a heuristic manner is necessary to meet the demand side management in microgrids (MGs). The pricing scheme limitations hinder the profit maximization of MG and their customers. In addition, recent pricing schemes lack mechanistic underpinning. Therefore, a dynamic electricity pricing scheme through linear regression is designed for RERs to maximize the profit of load customers (changeable and unchangeable) in MG. The demand response optimization problem is solved through the particle swarm optimization (PSO) technique. The proposed dynamic electricity pricing scheme is evaluated under two different scenarios. The simulation results verified that the proposed dynamic electricity pricing scheme sustained the profit margins and comforts for changeable and unchangeable load customers as compared to fixed electricity pricing schemes in both scenarios. Hence, the proposed dynamic electricity pricing scheme can readily be used for real microgrids (MGs) to grasp the goal for cleaner energy production.

The optimization of the energy portfolio for a small, open, landlocked economy with rather limited fossil resources is a complex task because it must find a long-range, sustainable balance between the various goals of society under the constant pressure of different interest groups. The opinions of independent, informed experts could be an essential input in the decision-making process. The goal of this research was to determine the relative importance of the values and goals potentially accompanying projects, based on the utilization of bioenergy. The current research is based on a wide-ranging survey of 65 non-partisan experts, applying the Pareto analytic hierarchy process to ensure the unbiased prioritization of project segments. The results of the survey put a spotlight on the importance of the economic role of bioenergy projects. Contrary to previous expectations and considerations, the social functions of these projects have hitherto been given relatively little importance. The results highlight the importance of bioenergy in increasing the income-generating capacity of agricultural producers by optimal utilization of natural resources for agricultural production. This can be achieved without considerable deterioration of the natural environment. Modern agricultural production is characterized by high levels of mechanization and automatization. Under these conditions, the social role of bioenergy projects (job creation) is rather limited.

Az erősödő verseny és a globalizáció következtében megváltozott a vállalatok mikro- és makrokörnyezete. Az Ipar 4.0 a negyedik ipari forradalmat jelenti, amely során szorosabban fonódik össze az információs technológia és az automatizálás, ezáltal alapvetően megváltoznak a gyártási módszerek. Nem csupán a technológia térhódításáról van szó, hanem az üzleti folyamatok paradigmaváltásáról is. Az Ipar 4.0 a hazai vállalatok számára is egyre inkább napi valósággá válik, egy új szintre fogja emelni a gyártásban felhasznált erőforrások és szereplők közötti interakciókat. Véleményem szerint az Ipari 4.0 át fogja alakítani a termelés szerkezetét – és meg fogja változtatni a globális versenyképességet – új lehetőségeket ad a vállalatoknak az értékteremtéshez. Kutatásomban bemutattam az Ipar 4.0 fogalmát, az újszerű technológiáit, keretrendszerét és a kapcsolódó technológiákat, feltártam az intelligens logisztikai megoldásokat és az Ipar 4.0 legfontosabb előnyeit. A fenti eszközök használatakor lényegében nem csak az ipar robbanásszerű fejlődéséről van szó, hanem a teljes gazdaság digitalizációjáról, mely az egész társadalmat érinti. Fontos, hogy a kis- és középvállalkozások is reagáljanak az új technológiai lehetőségekre, egyébként jelentős mértékben lemaradnak.

A lovas szolgáltatások megjelennek a rekreációban, sportban és a turisztikai kínálatban egyaránt. Hazánk kedvező természeti és kulturális értékei, valamint lovas hagyományaira építő lovas nemzet imázsa kedvező hátteret biztosít a kínálati elemek fejlesztésére. Az Észak-alföldi régió alföldi karakterű tája és lovas-kultúrája, az itt található lovas szolgáltatások folyamatos fejlesztése erősíti a lovas kínálati elemet a sport és szabadidőgazdaság területén. Mélyinterjús kutatásunkat az Észak - alföldi régióban működő patkós minősítettséggel rendelkező és nem rendelkező szolgáltatók (N=11) körében végeztük. Az eredmények azt igazolják, hogy valamennyi szolgáltató fontosnak véli és tervezi a lóállomány, az infrastruktúra és a humánerőforrás fejlesztését, bár ennek finanszírozásának forrása eltérő (állami, más sikeres vállalkozásból, lovas vállalkozás realizált üzleti eredményéből). A patkós minősítéssel nem rendelkező lovas szolgáltatók a minőség fejlesztését, a 3, 4, 5 patkós minősítéssel rendelkező szolgáltatók a komplex programkínálat bővítését, a termékdiverzifikációt jelölték meg.

The sustainable environment has been a desired situation around the world for the last few decades. Environmental contaminations can be a consequence of various economic activities. Different socio-economic factors influence the environment positively or negatively. Many previous studies have resulted in the efficient allocation of inputs as an environment-friendly component. This paper investigates the effects of energy efficiency on ecological footprint in the ASEAN region using balanced panel data from 2001 to 2019. First, this paper technically derives the energy efficiency, using the stochastic frontier analysis (SFA) of the translog production type of single output and multiple inputs. Findings of the SFA show that the Philippines and Singapore have the highest energy efficiency (94%) and Laos has the lowest energy efficiency (85%) in the ASEAN region. The estimated average efficiency score of the ASEAN region was around 90%, ranging from 85% to 96%, indicating that there is still 10% room for improvement in energy efficiency. Second, this study employed the panel autoregressive distributed lag (ARDL) model to explore the short run and long run impact of technically derived energy efficiency on ecological footprint in the ASEAN region. Results of the panel ARDL model show that energy efficiency is a reducing factor of ecological footprint in the long run. Moreover, energy efficiency plays a significant role to control the environmental contaminations. In addition, results of this study also explored that urbanization is an increasing factor of ecological footprint, and investment in agriculture is also beneficial for the environment. Moreover, to obtain the directional nature of the associations between the ecological footprint and its independent variables, this paper has employed the paired-panel Granger causality test. The results of the paired wise panel Granger causality test also confirm that the energy efficiency, urbanization, and investment in agriculture cause ecological footprint. Finally, this study recommends that efficient utilization of energy resources as well as investment in agriculture are necessary for sustainable environment.

The increase in domestic transportation in developing countries may adversely affect the energy efficiency of road transportation due to effective productivity and carbon dioxide emissions (CO2). When evaluating quantitatively the countries on the efficiency frontier, poor efficiency can still be seen sometimes due to the slack available in undesirable output measures. This paper uses desirable and undesirable output variables, such as passenger-kilometers (PKM), tones-kilometers (TKM), and carbon dioxide (CO2), to compute the weakly efficient decision-making units (DMUs). The data envelopment analysis (DEA) technology is used to assess the efficiencies of the decision-making units (DMUs), which are countries in our case. Then, the trade-off method with efficient binding surfaces is used to attain the optimal efficiencies of the weakly efficient DMUs. The marginal rates aid this trade-off analysis. Resultantly, such marginal trade-offs do not deteriorate the efficiency of the DMUs below the frontier line. We calculate the maximum change (margin) in a specific variable amount when another variable’s amount is changed. Thus, such a computation gives us different margins, with which each output variable can be a traded off to bring a DMU further toward the closest optimal point possible. The marginal trade-off can help the managers and policymakers in effective decision-making, and it is further recommended to address efficiency damages (by the undesired outputs).

The bioethanol sector is an extremely complex set of actors, technologies and market structures, influenced simultaneously by different natural, economic, social and political processes. That is why it lends itself to the application of system dynamics modelling. In last five years a relatively high level of experience and knowledge has accumulated related to the application of computer-aided system modelling for the analysis and forecasting of the bioethanol sector. The goal of the current paper is to offer a systematic review of the application of system dynamics models in order to better understand the structure, conduct and performance of the bioethanol sector. Our method has been the preferred reporting items for systematic reviews and meta-analyses (PRISMA), based on English-language materials published between 2015 and 2020. The results highlight that system dynamic models have become more and more complex, but as a consequence of the improvement in information technology and statistical systems, as well as the increasing experience gained they offer an efficient tool for decision makers in the business and political spheres. In the future, the combination of traditional system dynamics modelling and agent-based models will offer new perspectives for the preparation of more sophisticated description and forecasting.

China’s huge investment in the “belt and road initiative” (BRI) may have helped improve the economic level of participating countries, but it may also be accompanied by a substantial increase in greenhouse gas (GHG) emissions. The BRI corridors aim to bring regional stability and prosperity. In such efforts, energy efficiency due to increased transport has been overlooked in the recent literature. This paper employed a data envelopment analysis of the slack-based measurement (SBM) for bad output to assess the transport energy efficiency of 19 countries under the BRI economic corridors. By using the most cited transport-related input variables, such as vehicles, labor, motor oil, jet fuel, and natural gas, this study first analyzes the transport energy efficiency by first assuming the output variables individually and then takes two years as a pre- and post-BRI case by considering the aggregated output model. The results show an increase in economic activity but a decline in transport energy efficiency in terms of consumption and emissions.

Interest in the rapid growth of CO2 emissions, together with the economic performance of various countries continues to attract researchers and practitioners’ interest. Alongside, concerns regarding global warming and its effects on human and animal health, and thus sustainable development, escalate. The present study employs the nonlinear autoregressive distributed lag to identify short- and long-run dynamics and the asymmetric nexus between absorptive capacity, and CO2 emissions intensity from 1970 to 2018 in the case of the USA and China. In the short-run, an increase in technology transfer based on human resources increases CO2 emissions in China. Contrarily, the decrease in technology transfer based on infrastructure has an emissions-decreasing effect in China. In the long-run, the effects of an increase in absorptive capacity based on innovation and infrastructure developments provide positive and significant impetus to mitigate the carbon intensity in China and the USA. The results are robust using GHG intensity. Thus, policymakers and researchers have to consider the pivotal role of absorptive capacity in facilitating sustainable development.

A mezőgazdaság számára a precíziós gazdálkodás jelentheti a jövőt, hiszen egyszerre járhat a jövedelmek növelésével és a környezetterhelés mérséklésével. A precíziós gazdálkodás statisztikailag igazolható többletet termel hozamban, bevételben, eredményben, de nem azonnal. A többletjövedelem potenciál 20-50% között várható. A precíziós gazdálkodásra főként azért térnek át a gazdaságok, hogy tehermentesítsék a dolgozókat. Sok gazdálkodó azonban még mindig tart az új technológiával működő eszközök használatától, pedig a mezőgazdaságban is megkerülhetetlen lesz az informatika alkalmazása. A technológia alapvetően drága, még nem elterjedt, sőt a gazdák a fokozatosság elvét követve csupán néhány technológiai elemet használnak, ráadásul az óvatosság jegyében a technológia mezőgazdasági területük csak egy részére terjed ki. A gazdaságoknak tehát meg kell tanulni a korábbinál precízebben gazdálkodni, nem csak a termőföldön, hanem fejben is.

A technológiai fejlődésnek köszönhetően egyre fokozódó, felgyorsuló piaci verseny alakult ki a vállalatok között. Ezen verseny nemcsak a logisztikai folyamatokban, hanem a termeléssel kapcsolatos kérdésekben is jelentősnek tűnik, hiszen a termelővállalatok középpontját jelentik az értékesítésnek, és nélkülük nem teremthetők meg a logisztika folyamataiban fellelhető értékesítési cikkek. A termelés optimalizálásának, hatékonyságának a szerepe az ellátási láncban folyamatosan nő, ugyanis a vállalat költségeinek jelentős része itt képződik. Kutatási célkitűzésünk egy különböző gyártási, szerelési technológiákat alkalmazó vállalat eszközeinek hatékonyság vizsgálata az SAP Business One, illetve a svájci eredetű, napjainkban megjelent PPS One rendszerrel. Ezen alkalmazások segítségével a kifejezetten gyártással és termelésirányítással foglalkozó vállalatok számára adtunk megoldást a munkafolyamataik optimalizálására, tevékenységeik, műveleteik megszervezésére, alapanyagaik felügyelésére és ellenőrzésére. Megfigyeltük a termeléstechnológia elemek közül a kapacitástervezést, gyártási utasításokat, ütemezéseket, gyártás nyomonkövetést és költségszámítást. Az elemzés során olyan javaslatokat tettünk, amelyek a stratégia javításával a vállalkozás versenyképességét, valamint üzleti tevékenységének eredményességét növelik, mindemellett megkönnyítik a vállalat készletgazdálkodási és árazási tevékenységét.

Az erdőgazdálkodás és a fafeldolgozás gazdasági jelentőségét nagymértékben a fa értékteremtési lánca határozza meg. A fa, mint megújuló nyersanyag, termelésével és feldolgozásával egyidejűleg az erdőgazdálkodás és a fafeldolgozás alapvetően hozzájárul a fenntartható fejlődés céljainak megvalósításához. A multifunkcionális erdőgazdálkodás különböző áruk és szolgáltatások előállításában megnyilvánuló kapcsolatrendszere szükségszerűen azt eredményezi, hogy egy kapcsolati ág megváltozása az erdészeti üzemi értékteremtés teljes hálózatának változásához vezet. A kíméletes és tartamos erőgazdálkodás értékteremtésének speciális területei az infrastrukturális, rekreációs és turisztikai jellegű szolgáltatások.

A raktárgazdálkodás az elmúlt években széleskörű és gyors fejlődésnek indult. Ez az egyre komplexebb logisztikai folyamatok mellett a raktár kialakításával és működtetésével kapcsolatos erőteljes és látványos fejlődésnek köszönhető. Kutatásomban a raktár-technológiai rendszerrel szemben elvárt teljesítmény meghatározásának összetett problémakörét vizsgáltam. Ez a döntés magában foglalja a teljesítmény mérésére alkalmas kulcsfontosságú teljesítménymutatók kiválasztását és az emutatók mentén specifikált elvárt teljesítményszint meghatározását egy vizsgált vállalat példáján. Kutatásom során megállapítottam, hogy a raktári folyamatok logisztikai teljesítmény mérése nagyon nehéz feladat, mert minden vállalatnak olyan mutatókat kell meghatározni és alkalmazni, amelyek a vállalat profiljához jól illeszkednek, és hűen tükrözik a mérni kívánt teljesítményt. E döntés nagy fontosságú, hiszen ehhez a teljesítmény-elváráshoz kell majd igazítanunk raktári rendszerünket és annak működési elveit.

No consensus has been reached on the problem of solving resource depletion. A recognition of the fact that resources are not endless and the Earth is a finite globe reinforces the idea that the vision of continuous economic growth is not sustainable over time. The aim of this paper is to examine the efficacy of real prices as an indicator of metals and oil in consideration of growth tendencies in the Consumer Price Indexes. In addition, enhancing the current literature on commodity price interrelationships, the main contribution of this study is the substitution of different proxies in order to justify the effect of scarcity and crude oil changes on the examined metal group prices. In order to demonstrate the usefulness of scarcity as an indicator of real price deviations, the study has been conducted involving various non-renewable metals, i.e., copper, molybdenum, zinc, gold and platinum group metals. The real price indices and metal prices of the US market are constructed between 1913 and 2015. Moreover, additional econometric analyses are also carried out to discover whether prices of various metals associate with oil prices and scarcity, as the proxy of reserves-to-production ratio. The linear regression results seem to suggest that the effects of the R/P ratios are negatively correlated with each of the examined precious (gold, PGMs), mass consumable (copper, zinc) and doping agent (molybdenum) metals from 1991 to 2015. An increase in oil-prices is positively associated with the price levels of each non-renewable resource in the short-run. The findings of multivariate co-integration and Granger causality tests also suggest that pairwise and direct relationships among these variables seem to arise in the long-run. These findings indicate essential questions that must be addressed by future generations in order to appropriately solve scarcity problems.

In our paper we examine the economics of a technological process which utilizes the separated biogas plant digestate as the primary material and, as auxiliary material, the waste heat produced by the cogeneration process, to produce a marketable pellet which can be used in two ways (to supply soil nutrients and heat energy). Using multivariate linear regression model we developed an equation for the biogas yield from the modelled production recipe and expected nutrient pellet prices, and sensitivity analysis were also performed for the substrate dry matter content. We found that pellets can be produced at a cost of 88–90 EUR/ton with a 6 to 10% dry matter substrate content and that, primarily, sales of pellets for heating justify pelleting; producer’s own use and use for nutrient purposes can only be justified in exceptional cases. In the case of dry solid content above 5%, the process does not require the total amount of waste heat; some of this can be used to cover other heat requirements.

The bioeconomy is a highly complex, cross-sectorial concept covering all sectors and systems that rely on biomass. Based on the analysis of the size of bioeconomy in the V4 countries it can be concluded that the sustainable transition is a great challenge and can be achieved by developing national circular bioeconomy strategies. It is extremely difficult to analyse the contribution of different sectors to the performance of the circular bioeconomy. Currently, the contribution of different sectors to the biomass-based economy is very complex, therefore a strategic socio-economic planning and optimal resource allocation is necessary to achieve the goals of the bioeconomy. This paper aims to determine the place and role of the bioeconomy in the structural change of the linear economy, based on detailed matrices of in- and output relations between different sectors. Based on the input-output matrices, as well as centrality and flow metrics of network analysis, the role of the bioeconomy in the linear economy, its multiplicative effects and future research implications are analysed.

Archaeal lipids have a high biotechnological potential, caused by their high resistance to oxidative stress, extreme pH values and temperatures, as well as their ability to withstand phospholipases. Further, methanogens, a specific group of archaea, are already well-established in the field of biotechnology because of their ability to use carbon dioxide and molecular hydrogen or organic substrates. In this study, we show the potential of the model organism Methanothermobacter marburgensis to act both as a carbon dioxide based biological methane producer and as a potential supplier of archaeal lipids. Different cultivation settings were tested to gain an insight into the optimal conditions to produce specific core lipids. The study shows that up-scaling at a constant particle number (n/n = const.) seems to be a promising approach. Further optimizations regarding the length and number of the incubation periods and the ratio of the interaction area to the total liquid volume are necessary for scaling these settings for industrial purposes.