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Articles de revues sur le sujet « Zonal pricing »

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Auteur : Grafiati
Publié le 11 mars 2023

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1

Poyrazoglu, Gokturk. « Determination of Price Zones during Transition from Uniform to Zonal Electricity Market : A Case Study for Turkey ». Energies 14, no 4 (15 février 2021) : 1014. http://dx.doi.org/10.3390/en14041014.

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In the electricity market, different pricing models can be applied to increase market competitiveness. Different electricity systems use different market structures. Uniform marginal pricing, zonal marginal pricing, and nodal marginal pricing methods are commonly used market structures. For markets wishing to move from a uniform pricing structure to a more competitive zonal pricing structure, the determination of price zones is critical for achieving a competitive market that generates accurate price signals. Three different pricing zone detection algorithms are analyzed in this paper including the k-means clustering and queen/rook spatially constraint clustering. Finally, the results of a case study for the Turkish electricity system are shared to compare each method.
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MICLEA, Andrei, et Ionut JDERU. « IMPLEMENTATION OF CROSS-ZONAL INTRADAY CAPACITY PRICING ». EMERG - Energy. Environment. Efficiency. Resources. Globalization 6, no 4 (2020) : 65–74. http://dx.doi.org/10.37410/emerg.2020.4.05.

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Aori Mabea, Geoffrey. « Simulating Zonal Pricing in East African Electricity Markets ». International Journal of Economy, Energy and Environment 7, no 1 (2022) : 13. http://dx.doi.org/10.11648/j.ijeee.20220701.12.

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Rouhani, Omid M. « Beyond Standard Zonal Congestion Pricing : A Detailed Impact Analysis ». Journal of Transportation Engineering, Part A : Systems 144, no 9 (septembre 2018) : 04018052. http://dx.doi.org/10.1061/jtepbs.0000151.

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Ding, F., et J. D. Fuller. « Nodal, Uniform, or Zonal Pricing : Distribution of Economic Surplus ». IEEE Transactions on Power Systems 20, no 2 (mai 2005) : 875–82. http://dx.doi.org/10.1109/tpwrs.2005.846042.

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Walton, Steven, et Richard D. Tabors. « Zonal transmission pricing : methodology and preliminary results from the WSCC ». Electricity Journal 9, no 9 (novembre 1996) : 34–41. http://dx.doi.org/10.1016/s1040-6190(96)80456-8.

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Dicorato, M., A. L'Abbate, A. Minoia et M. Trovato. « Pricing criterions in presence of intra- and inter-zonal constraints ». Electric Power Systems Research 66, no 2 (août 2003) : 179–86. http://dx.doi.org/10.1016/s0378-7796(03)00044-0.

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Zhang, Ruiyou, Shui Han, Jinzhu Zhang et Dingwei Wang. « Zone division models and algorithms in zonal pricing power market ». European Transactions on Electrical Power 19, no 1 (janvier 2009) : 140–49. http://dx.doi.org/10.1002/etep.236.

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Dagoumas, Athanasios, et Nikolaos Koltsaklis. « ZONAL PRICING IN KAZAKHSTAN POWER SYSTEM WITH A UNIT COMMITMENT MODEL ». International Journal of Energy Economics and Policy 10, no 3 (18 mars 2020) : 24–36. http://dx.doi.org/10.32479/ijeep.9022.

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Lété, Quentin, Yves Smeers et Anthony Papavasiliou. « An analysis of zonal electricity pricing from a long-term perspective ». Energy Economics 107 (mars 2022) : 105853. http://dx.doi.org/10.1016/j.eneco.2022.105853.

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Sarfati, Mahir, Mohammad Reza Hesamzadeh et Pär Holmberg. « Production efficiency of nodal and zonal pricing in imperfectly competitive electricity markets ». Energy Strategy Reviews 24 (avril 2019) : 193–206. http://dx.doi.org/10.1016/j.esr.2019.02.004.

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Bjørndal, Mette, Kurt Jørnsten et Virginie Pignon. « Congestion Management in the Nordic Power Market — Counter Purchases and Zonal Pricing ». Competition and Regulation in Network Industries 4, no 3 (septembre 2003) : 271–92. http://dx.doi.org/10.1177/178359170300400302.

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Weibelzahl, Martin. « Nodal, zonal, or uniform electricity pricing : how to deal with network congestion ». Frontiers in Energy 11, no 2 (30 mars 2017) : 210–32. http://dx.doi.org/10.1007/s11708-017-0460-z.

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14

Jansen, Luca Lena, Georg Thomaßen, Georgios Antonopoulos et Ľuboš Buzna. « An Efficient Framework to Estimate the State of Charge Profiles of Hydro Units for Large-Scale Zonal and Nodal Pricing Models ». Energies 15, no 12 (8 juin 2022) : 4233. http://dx.doi.org/10.3390/en15124233.

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The power system is undergoing significant changes so as to accommodate an increasing amount of renewably generated electricity. In order to facilitate these changes, a shift from the currently employed zonal pricing to nodal pricing is a topic that is receiving increasing interest. To explore alternative pricing mechanisms for the European electricity market, one needs to solve large-scale nodal optimization problems. These are computationally intensive to solve, and a parallelization or sequencing of the models can become necessary. The seasonality of hydro inflows and the issue of myopic foresight that does not display the value in storing water today and utilizing it in the future is a known problem in power system modeling. This work proposes a heuristic step-wise methodology to obtain state of charge profiles for hydro storage units for large-scale nodal and zonal models. Profiles obtained from solving an aggregated model serve as guidance for a nodal model with high spatial and temporal resolution that is solved in sequences. The sequenced problem is guided through soft constraints that are enforced with different sets of penalty factors. The proposed methodology allows for adjustments to congestions on short timescales and proves to perform well in comparison to other approaches to this issue suggested in the literature. Following the input profile closely on a long timescale renders good results for the nodal model.
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Zhang, Ruiyou, Dingwei Wang et Won Young Yun. « Power-Grid-Partitioning Model and its Tabu-Search-Embedded Algorithm for Zonal Pricing ». IFAC Proceedings Volumes 41, no 2 (2008) : 15927–32. http://dx.doi.org/10.3182/20080706-5-kr-1001.02692.

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Weibelzahl, Martin, et Alexandra Märtz. « On the effects of storage facilities on optimal zonal pricing in electricity markets ». Energy Policy 113 (février 2018) : 778–94. http://dx.doi.org/10.1016/j.enpol.2017.11.018.

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Kang, C. Q., Q. X. Chen, W. M. Lin, Y. R. Hong, Q. Xia, Z. X. Chen, Y. Wu et J. B. Xin. « Zonal marginal pricing approach based on sequential network partition and congestion contribution identification ». International Journal of Electrical Power & ; Energy Systems 51 (octobre 2013) : 321–28. http://dx.doi.org/10.1016/j.ijepes.2013.02.033.

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18

Tongxin Zheng et E. Litvinov. « Contingency-Based Zonal Reserve Modeling and Pricing in a Co-Optimized Energy and Reserve Market ». IEEE Transactions on Power Systems 23, no 2 (mai 2008) : 277–86. http://dx.doi.org/10.1109/tpwrs.2008.919314.

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Xu, Xiaomin, Dongxiao Niu, Yan Li et Lijie Sun. « Optimal Pricing Strategy of Electric Vehicle Charging Station for Promoting Green Behavior Based on Time and Space Dimensions ». Journal of Advanced Transportation 2020 (11 août 2020) : 1–16. http://dx.doi.org/10.1155/2020/8890233.

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Considering that the charging behaviors of users of electric vehicles (EVs) (including charging time and charging location) are random and uncertain and that the disorderly charging of EVs brings new challenges to the power grid, this paper proposes an optimal electricity pricing strategy for EVs based on region division and time division. Firstly, by comparing the number of EVs and charging stations in different districts of a city, the demand ratio of charging stations per unit is calculated. Secondly, according to the demand price function and the principle of profit maximization, the charging price between different districts of a city is optimized to guide users to charge in districts with more abundant charging stations. Then, based on the results of the zonal pricing strategy, the time-of-use (TOU) pricing strategy in different districts is discussed. In the TOU pricing model, consumer satisfaction, the profit of power grid enterprises, and the load variance of the power grid are considered comprehensively. Taking the optimization of the comprehensive index as the objective function, the TOU pricing optimization model of EVs is constructed. Finally, the nondominated sorting genetic algorithm (NSGA-II) is introduced to solve the above optimization problems. The specific data of EVs in a municipality directly under the Central Government are taken as examples for this analysis. The empirical results demonstrate that the peak-to-valley ratio of a certain day in the city is reduced from 56.8% to 43% by using the optimal pricing strategy, which further smooth the load curve and alleviates the impact of load fluctuation. To a certain extent, the problem caused by the uneven distribution of electric vehicles and charging stations has been optimized. An orderly and reasonable electricity pricing strategy can guide users to adjust charging habits, to ensure grid security, and to ensure the economic benefits of all parties.
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20

Jiang, Xufeng, Zelu Jia, Lefei Li et Tianhong Zhao. « Understanding Housing Prices Using Geographic Big Data : A Case Study in Shenzhen ». Sustainability 14, no 9 (28 avril 2022) : 5307. http://dx.doi.org/10.3390/su14095307.

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Understanding the spatial pattern of urban house prices and its association with the built environment is of great significance to housing policymaking and urban planning. However, many studies on the influencing factors of urban housing prices conduct qualitative analyses using statistical data and manual survey data. In addition, traditional housing price models are mostly linear models that cannot explain the distribution of housing prices in urban areas. In this paper, we propose using geographic big data and zonal nonlinear feature machine learning models to understand housing prices. First, the housing price influencing factor system is built based on the hedonic pricing model and geographic big data, and it includes commercial development, transportation, infrastructure, location, education, environment, and residents’ consumption level. Second, a spatial exploratory analysis framework for house price data was constructed using Moran’s I tools and geographic detectors. Finally, the XGBoost model is developed to assess the importance of the variables influencing housing prices, and the zonal nonlinear feature model is built to predict housing prices based on spatial exploration results. Taking Shenzhen as an example, this paper explored the distribution law of housing prices, analyzed the influencing factors of housing prices, and compared the different housing price models. The results show that the zonal nonlinear feature model has higher accuracy than the linear model and the global model.
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21

dos Santos, Priscila Duarte, Antonio Carlos Zambroni Souza et Benedito Donizeti Bonatto. « Assessment of the impacts of distributed generation and electric vehicles as mobile sources through a nodal and zonal pricing methodology ». IET Generation, Transmission & ; Distribution 15, no 14 (8 mars 2021) : 2137–51. http://dx.doi.org/10.1049/gtd2.12163.

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22

Bompard, Ettore, Shaghayegh Zalzar, Tao Huang, Arturs Purvins et Marcelo Masera. « Baltic Power Systems’ Integration into the EU Market Coupling under Different Desynchronization Schemes : A Comparative Market Analysis ». Energies 11, no 8 (26 juillet 2018) : 1945. http://dx.doi.org/10.3390/en11081945.

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Currently, the power transmission system of the Baltic states is synchronized with the Integrated/Unified Power System (IPS/UPS), which includes the Russian grid, and the IPS/UPS provides frequency regulation and system security within the Baltic states. Since joining the European Union (EU) in 2004, the Baltic states have been following the EU’s energy policy targets. The Baltics are presently participating in a European electricity market, i.e., the NordPool market, while they are expected to join the pan-European electricity market—the European target model for power market integration. Moreover, from a power grid perspective, EU energy policies intend to desynchronize the power grid of the Baltic states from the IPS/UPS over the coming years. This paper evaluates these policy trends through market impacts, and it complements existing studies on Baltic-IPS/UPS desynchronization in terms of wholesale electricity prices, generation surpluses, primary reserve adequacy, and redispatch costs. Participation of the Baltic states in the integrated pan-European day-ahead electricity market with zonal pricing was modeled for 2030, followed by a national redispatch, with detailed power grid modeling of Baltic states to solve potential intrazonal congestion. The simulation results imply the superiority of the Baltics’ synchronization to continental Europe, compared to the other schemes.
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23

Satyanarayana, K. « Credit Risk and Capital Adequacy of Banks ». Vision : The Journal of Business Perspective 4, no 2 (juillet 2000) : 42–49. http://dx.doi.org/10.1177/097226290000400206.

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Prudential regulation of banks and financial institutions, especially the stipulation of risk weighted capital adequacy ratio, has brought into sharp focus their inherent weaknesses. The real licence to expand banking is no more a nod from the regulator than the adequacy of capital backup. The situation is getting complex with deregulation and globalisation wherein the inherent risks especially the credit risk and market risk, need to be covered by proper capital adequacy ratio. Asset managers have to be always alert about the inherent risk and return embedded in any proposed asset accretion. Even before stabilising with an adequate CAR, banks are required to gear up with the proposed and more rigorous new capital adequacy framework of Basle Committee. Instead of confining to centralised approach, the banks can plan and monitor continuously asset expansion at zonal/regional and branch levels with a notional concept of capital adequacy. While pricing the assets, especially in a decentralised process of decision making in the form of both fund based and non-fund based exposures, cost of capital for any additional exposure needs to be taken care in the relevant computations. Ultimately the scope for healthy and sustainable growth of any bank depends upon its competitiveness to attract capital which in turn depends upon the economic value added, i.e., return on capital net of opportunity cost of such capital. Now that the government has almost stopped further infusion of capital into (public sector) banks, are the banks capital market fit?
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24

Trofymenko, P., T. Tretyak, Yu Bezgodkova, N. Trofimenko et V. Zatserkovnyi. « Development and use of gis database for tasks of normative monetary evaluation of land of settlements ». Zemleustrìj, kadastr ì monìtorìng zemelʹ, no 4 (27 octobre 2021) : 6. http://dx.doi.org/10.31548/zemleustriy2021.04.06.

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The paper presents the results of research on the development of a GIS database for the tasks of normative monetary valuation of lands of settlements and highlights the applied aspects of its use on the example of Lychanka village, Dmytriv territorial community, Bucha district, Kyiv region. An algorithm for developing a GIS database for normative monetary valuation of settlement lands is presented. The presented estimation algorithm allows to carry out with high accuracy normative monetary estimation of settlements, to carry out its automated updating on a certain date, to receive necessary information on request, to carry out analytical operations and construction of specialized estimation maps. The development of the GIS database involved the implementation of two stages. At the first stage of formation of the initial land assessment base, the attribute table included data from the Public Cadastral Map of Ukraine on land plots within the settlement by the following items: cadastral number of land plot, area, form of ownership, purpose and functional use of land plot , the number of the cadastral zone in which each land is located, the number of the land assessment area of the settlement, the value of the base value of land, the value of the zonal coefficient (Km2), the coefficient characterizing the functional purpose of the land (Kf), information on the location (street name). The second stage involved the calculation of the value of the normative monetary valuation of each of the 1279 land plots and was performed using the built-in Arc Map function "Calculation of numerical values". After the development of the GIS database, the testing stage of the developed land assessment database was performed, which involved the use of various query execution, geospatial analysis, the use of buffering functions, topological overlay (intersection). As a result of the analysis, the following maps were constructed: "Influence of local factors on the distance of land from the center of the settlement", "Influence of local factors on the distance of land from highways", "Influence of local factors on the environmental situation", "Influence of local factors on security electricity", "Influence of local factors on the distance from paved roads", "Influence of local factors on the provision of centralized water supply", "Influence of local factors on the provision of centralized sewerage", "Influence of local factors on the provision of centralized gas supply", "Map plots according to the results of normative monetary assessment" , "Map of the establishment of buffer zones by the value of local coefficients" , "Map of coastal protection strips around water bodies with the allocation of zones of their intersection with land". Due to the application of special functions of geospatial analysis available in the GIS environment, examples of development of highly informative cartographic materials in the form of special pricing zoning of the territory of the settlement are shown. The expediency of the application of the GIS database for the tasks of monitoring the quality of land, compliance with their legal regime and the possibility of monitoring the implementation of fiscal obligations by landowners and users.
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Muriel-Torrado, Enrique, et Adilson Luiz Pinto. « Editorial ». Encontros Bibli : revista eletrônica de biblioteconomia e ciência da informação 23, no 52 (15 mai 2018) : i. http://dx.doi.org/10.5007/1518-2924.2017v23n52pi.

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Prezados leitores.É com muita alegria e satisfação que publicamos o segundo número de 2018 (v. 23, n. 52) da Encontros Bibli: Revista Eletrônica de Biblioteconomia e Ciência da Informação.Para a presente edição contamos com uma imagem de Santo Antônio de Lisboa, Florianópolis (UFSC).Em relação à parte científica da revista, temos o prazer de contar com sete artigos científicos:(1) Dos direitos sociais ao prazer: itinerários discursivos em Biblioteconomia & Ciência Informação - Rachel de Melo Vellozo Pereira e Gustavo Silva Saldanha;(2) O comportamento informacional e a competência em informação: uma abordagem para geração de inovação em micro e pequenas empresas - Selma Leticia Capinzaiki Ottonicar, Clemilton Luis Bassetto e Natália Marinho do Nascimento;(3) Aprendizagem móvel, competência em informação e mediação: interlocução sob a ótica do paradigma social da Ciência da Informação - Bárbara Luisa Ferreira Carneiro, Jefferson Veras Nunes, Lidia Eugenia Cavalcante e Maria Giovanna Guedes Farias;(4) Exclusão e inclusão digitais em bibliotecas públicas municipais da Região Metropolitana de Belo Horizonte: análise do serviço de acesso à internet disponibilizado pelas instituições para o exercício da cidadania - Luciana Gonçalves Silva Souza e Lígia Maria Moreira Dumont;(5) Construção Colaborativa de Representações para a Disseminação de Dados Agrícolas: Um Estudo do Portal CoDAF - Fabio Mosso Moreira, Diana Vilas Boas Souto Aleixo, Pedro Henrique Santos Bisi, Leonardo Felipe Franchi e Ricardo César Gonçalves Sant'ana;(6) Gestão do conhecimento no setor público: um estudo sobre os artigos publicados em periódicos nacionais no período 2005-2015 - Ana Paula Nogueira e Silva e Angélica Conceição Dias Miranda;(7) Aplicação do modelo Servqual na bienal do livro da Zona da Mata: o olhar dos interagentes abrindo novas páginas para melhoria da qualidade- Ana Claudia Borges Campos, Marcelo Calderari Miguel e Sandra Maria Souza De Carvalho;E um ensaio, (1) INFORMAÇÃO E MEMÓRIA: aproximações teóricas e conceituais de Ana Pricila Celedonio da Silva, Lidia Eugenia Cavalcante e Jefferson Veras Nunes.Boa leitura.
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Blazquez de Paz, Mario. « Redispatch in Zonal Pricing Electricity Markets ». SSRN Electronic Journal, 2020. http://dx.doi.org/10.2139/ssrn.3644217.

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Bjorndal, Mette, et Kurt Jornsten. « Zonal Pricing in a Deregulated Electricity Market ». Energy Journal 22, no 1 (1 janvier 2001). http://dx.doi.org/10.5547/issn0195-6574-ej-vol22-no1-3.

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Holmberg, P�r, et Ewa Lazarczyk. « Comparison of congestion management techniques : Nodal, zonal and discriminatory pricing ». Energy Journal 36, no 2 (1 avril 2015). http://dx.doi.org/10.5547/01956574.36.2.7.

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Holmberg, Par, et Ewa Lazarczyk. « Congestion Management in Electricity Networks : Nodal, Zonal and Discriminatory Pricing ». SSRN Electronic Journal, 2012. http://dx.doi.org/10.2139/ssrn.2055655.

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Sarfati, Mahir, Mohammad Reza Hesamzadeh et Par Holmberg. « Production Efficiency of Nodal and Zonal Pricing in Imperfectly Competitive Electricity Markets ». SSRN Electronic Journal, 2019. http://dx.doi.org/10.2139/ssrn.3644259.

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« 04/01348 Pricing criterions in presence of intra- and inter-zonal constraints ». Fuel and Energy Abstracts 45, no 3 (mai 2004) : 184. http://dx.doi.org/10.1016/s0140-6701(04)90174-9.

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Moon, Sedong, Dong-Kyu Kim et Shin-Hyung Cho. « Design of Zonal Express Bus Services to Reduce User Travel Time and Transfers Considering Demand Diversion ». Transportation Research Record : Journal of the Transportation Research Board, 22 juillet 2021, 036119812110184. http://dx.doi.org/10.1177/03611981211018463.

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Zonal express is an operational strategy for express transit service that only stops in the initial and final zones of its route while skipping stops in-between. Zonal express provides a service with less travel and transfer time by aggregating trip demands with similar origins, destinations, and departure times. In this study, new zonal express routes are designed to reduce the travel and transfer times of transit users efficiently. This study develops a methodology that considers demand diversion. To meet the purpose, the following are conducted: (1) estimation of zonal express demand; (2) clustering of demand with similar origins, destinations, and departure times; (3) selection of candidate clusters; (4) optimization of stops and routes of zonal express; and (5) determining zonal express routes in which the benefit from reduced time and transfers outweighs the cost. The methodology is applied to an actual transportation network in Seoul, South Korea, using smartcard, car navigation, and spatial information data. The result shows that zonal express can reduce users’ travel time and the number of transfers effectively. This study proposes that it is desirable to introduce the zonal express sequentially from the route with the highest net benefit under a budget constraint. This study also presents the results when fares change to provide implications for pricing strategies of the zonal express. Future studies can consider incorporating various objective functions or utilizing vehicles in different time slots.
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Katzen, Matthew, et Gordon Leslie. « Revisiting Optimal Pricing in Electrical Networks over Space and Time : Mispricing in Australia’s Zonal Market ». SSRN Electronic Journal, 2019. http://dx.doi.org/10.2139/ssrn.3501336.

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Jeihani, Mansoureh, et Anam Ardeshiri. « TRANSIMS Implementation for a Small Network and Comparison with Enhanced Four-Step Model ». Journal of the Transportation Research Forum, 1 mars 2014. http://dx.doi.org/10.5399/osu/jtrf.53.1.4216.

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Travel demand forecasting is a major tool to assist decision makers in transportation planning. While the conventional four-step trip-based approach is the dominant method to perform travel demand analysis, behavioral advances have been made in the past decade. This paper proposes and applies an enhancemnt to the four-step travel demand analysis model called Sub-TAZ. Furthermore, as an initial step toward activity-based models, a TRANSIMS Track-1 approach is implemented utilizing a detailed network developed in Sub-TAZ approach. The conventional four-step, Sub-TAZ, and TRANSIMS models were estimated in a small case study for Fort Meade, Maryland, with zonal trip tables. The models were calibrated and validated for the base year (2005), and the forecasted results for the year (2010) were compared to actual ground counts of traffic volume and speed. The study evaluated the forecasting ability of TRANSIMS versus the conventional and enhanced four-step models and provided critical observations concerning strategies for the further implementation of TRANSIMS.BACKGROUND Traffic pattern prediction is necessary for infrastructure improvement, and travel demand modeling provides tools to forecast travel patterns under various conditions. This modeling involves a series of mathematical equations that represent how people make travel choices. Traditional travel demand models use the four-step method, which was introduced in the 1950s and has been used widely in transportation planning. Although the four-step method has been practical in producing aggregate forecasts, it has some shortcomings. For example, in short-range planning networks, existing and newly constructed roads become congested much faster than forecasted (TRB 2007) and the performance of current four-step models is not always satisfactory. Additionally, these models are not behavioral in nature and as a result they are unable to represent the time chosen for travel, travelers’ responses to demand policies (e.g., toll roads, road pricing, and transit vouchers), non-motorized
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Simões, Andre Rozemberg Peixoto, Charles Frederick Nicholson, Janderson Damaceno dos Reis, Roberto Max Protil, André Luiz Julien Ferraz et Dalton Mendes de Oliveira. « Determinants of farmers’ loyalty to dairy processors in Minas Gerais, Brazil ». Ciência Rural 51, no 5 (2021). http://dx.doi.org/10.1590/0103-8478cr20200340.

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ABSTRACT: The current study explores variables associated with the loyalty of dairy farmers to dairy processors in the Brazilian context. A multivariate discrete choice (Logit) model and alternative formulations assess the associations between loyalty metrics and farm and processor characteristics for a sample of 32 dairy farmers in 16 municipalities at the Zona da Mata in Minas Gerais. Twenty-two dairy processors were identified as milk buyers in the area studied, but each farmer indicated that they could sell to an average of five alternative buyers of milk. Farmers’ attributes such as production scale or the technological level are not statistically significantly associated with loyalty in this sample. The current milk price paid to farmers in our sample is not associated with increased loyalty (sales to a single processor for 6 or more years) in all estimated models; although, further research on this impact is merited to inform buyer-pricing policy. Variables associated with increased loyalty include payment of premiums for quality, farmer years of experience and cooperation among farmers in the purchase of inputs. Delayed payment is associated with reduced loyalty. We could not determine the effect of participation in technical assistance programs offered by processors on loyalty, because in our sample all farmers received free university-provided technical assistance. The payment of a premium based on milk volume was also unassociated with loyalty determination. The small size of our sample limits the ability to generalize our results but provides exploratory results that facilitate future investigation.
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