<?xml version="1.0"?><rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:edm="http://www.europeana.eu/schemas/edm/" xmlns:wgs84_pos="http://www.w3.org/2003/01/geo/wgs84_pos" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:rdaGr2="http://rdvocab.info/ElementsGr2" xmlns:oai="http://www.openarchives.org/OAI/2.0/" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:ore="http://www.openarchives.org/ore/terms/" xmlns:skos="http://www.w3.org/2004/02/skos/core#" xmlns:dcterms="http://purl.org/dc/terms/"><edm:WebResource rdf:about="http://www.dlib.si/stream/URN:NBN:SI:DOC-KQZBCSOJ/87993b74-c3d3-4b6e-8608-f56e6fa94343/PDF"><dcterms:extent>1185 KB</dcterms:extent></edm:WebResource><edm:WebResource rdf:about="http://www.dlib.si/stream/URN:NBN:SI:DOC-KQZBCSOJ/df357dc7-f9f9-4dca-b7c9-b9e51642dadd/TEXT"><dcterms:extent>0 KB</dcterms:extent></edm:WebResource><edm:TimeSpan rdf:about="2014-2026"><edm:begin xml:lang="en">2014</edm:begin><edm:end xml:lang="en">2026</edm:end></edm:TimeSpan><edm:ProvidedCHO rdf:about="URN:NBN:SI:DOC-KQZBCSOJ"><dcterms:isPartOf rdf:resource="https://www.dlib.si/details/URN:NBN:SI:spr-QCV9XF2O" /><dcterms:issued>2023</dcterms:issued><dc:creator>Deng, G. F.</dc:creator><dc:format xml:lang="sl">letnik:18</dc:format><dc:format xml:lang="sl">številka:4</dc:format><dc:format xml:lang="sl">str. 434-446</dc:format><dc:identifier>DOI:10.14743/apem2023.4.483</dc:identifier><dc:identifier>ISSN:1854-6250</dc:identifier><dc:identifier>COBISSID_HOST:268960771</dc:identifier><dc:identifier>URN:URN:NBN:SI:doc-KQZBCSOJ</dc:identifier><dc:language>en</dc:language><dc:publisher xml:lang="sl">Fakulteta za strojništvo, Inštitut za proizvodno strojništvo</dc:publisher><dcterms:isPartOf xml:lang="sl">Advances in production engineering and management</dcterms:isPartOf><dc:subject xml:lang="en">agent-based modeling and simulation (ABMS)</dc:subject><dc:subject xml:lang="sl">agentni modeli</dc:subject><dc:subject xml:lang="en">complex adaptive system (CAS)</dc:subject><dc:subject xml:lang="en">consumer learning behavior</dc:subject><dc:subject xml:lang="en">fuzzy logic (FL)</dc:subject><dc:subject xml:lang="en">genetic algorithms (GA)</dc:subject><dc:subject xml:lang="sl">genetski algoritem</dc:subject><dc:subject xml:lang="sl">kompleksni prilagodljivi sistemi</dc:subject><dc:subject xml:lang="en">machine learning (ML)</dc:subject><dc:subject xml:lang="sl">mehka logika</dc:subject><dc:subject xml:lang="en">pricing competitive model</dc:subject><dc:subject xml:lang="en">reinforcement learning (RL)</dc:subject><dc:subject xml:lang="sl">simulacija</dc:subject><dc:subject xml:lang="sl">spodbujevano učenje</dc:subject><dc:subject xml:lang="sl">strojno učenje</dc:subject><dc:subject xml:lang="en">swarm intelligence (SW)</dc:subject><dc:subject xml:lang="sl">vedenje potrošnikov</dc:subject><dcterms:temporal rdf:resource="2014-2026" /><dc:title xml:lang="sl">Dynamic price competition market for retailers in the context of consumer learning behavior and supplier competition: machine learning-enhanced agent-based modeling and simulation|</dc:title><dc:description xml:lang="sl">This study analyzes the impact of consumer learning behavior and supplier price competition on retailer price competition in a complex adaptive system. Using machine Learning-enhanced agent-based modeling and simulation, the study applies fuzzy logic and genetic algorithms to model price decisions, and reinforcement learning and swarm intelligence to model consumer behavior. Simulations reveal that different learning behaviors result in different retailer competition patterns, and that supplier price competition affects the strength of retailer price competition. Simulation results demonstrate that consumer learning behavior influences retailer competition, with self-learning consumers leading to higher-priced partnerships, and collective-learning consumers leading to a shift in price competition among retailers. In contrast, perfect rationality consumers result in low-price competition and the lowest average margin and profit. Additionally, the competitive price behavior of suppliers impacts retailers' price competition patterns, with supplier price competition reducing retailer price competition in the perfect rationality consumer market and enhancing it in the self-learning and collective-learning consumer markets, leading to lower average prices and profits for retailers. This study presents a simulated market for price competition among suppliers, retailers, and consumers that can be expanded by subsequent scholars to test related hypotheses</dc:description><edm:type>TEXT</edm:type><dc:type xml:lang="sl">znanstveno časopisje</dc:type><dc:type xml:lang="en">journals</dc:type><dc:type rdf:resource="http://www.wikidata.org/entity/Q361785" /></edm:ProvidedCHO><ore:Aggregation rdf:about="http://www.dlib.si/?URN=URN:NBN:SI:DOC-KQZBCSOJ"><edm:aggregatedCHO rdf:resource="URN:NBN:SI:DOC-KQZBCSOJ" /><edm:isShownBy rdf:resource="http://www.dlib.si/stream/URN:NBN:SI:DOC-KQZBCSOJ/87993b74-c3d3-4b6e-8608-f56e6fa94343/PDF" /><edm:rights rdf:resource="http://creativecommons.org/licenses/by/4.0/" /><edm:provider>Slovenian National E-content Aggregator</edm:provider><edm:intermediateProvider xml:lang="en">National and University Library of Slovenia</edm:intermediateProvider><edm:dataProvider xml:lang="sl">Univerza v Mariboru, Fakulteta za strojništvo</edm:dataProvider><edm:object rdf:resource="http://www.dlib.si/streamdb/URN:NBN:SI:DOC-KQZBCSOJ/maxi/edm" /><edm:isShownAt rdf:resource="http://www.dlib.si/details/URN:NBN:SI:DOC-KQZBCSOJ" /></ore:Aggregation></rdf:RDF>