Parameter identification for the decision model of uncertainty price competition in food delivery services
The sharing economy innovation has created a new service industry sector, the ride-hailing industry. Government regulations regarding minimum tariffs change the competition map and uncertainty in that industry. This has led to predatory pricing, switching costs and pre-emptive duopoly. This study ai...
Gespeichert in:
| Veröffentlicht in: | IOP conference series. Earth and environmental science 2021-04, Vol.733 (1), p.12035 |
|---|---|
| Hauptverfasser: | , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 1 |
| container_start_page | 12035 |
| container_title | IOP conference series. Earth and environmental science |
| container_volume | 733 |
| creator | Andriani, D P Kusuma, L T W N Rachman, A B Firdausa, S Z Azzahra, A D Fadhlurrahman, Q A |
| description | The sharing economy innovation has created a new service industry sector, the ride-hailing industry. Government regulations regarding minimum tariffs change the competition map and uncertainty in that industry. This has led to predatory pricing, switching costs and pre-emptive duopoly. This study aims to determine the parameters that can affect the decision model in the uncertainty of price competition through factorial experiments. This study was conducted on two ride-hailing companies, which currently lead market share, thus establishing a duopoly market. There are many services offered by these companies. This study focuses on investigating food delivery services, which are one of the stable services during the Covid-19 pandemic. The approach that will be used in this research is a factorial experiment to determine what parameters can affect price determination with several uncertainty cases. The result is the identification of the optimal decision model, both parameters and levels in pricing. The implication of this study is fair competition for the welfare of society and the country. |
| doi_str_mv | 10.1088/1755-1315/733/1/012035 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2521608795</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2521608795</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2365-c77d1279fb325981efb3c4ee745371f1c153e0b0a7d37c47cec46ad102de1c633</originalsourceid><addsrcrecordid>eNo9kEFLAzEQhYMoWKt_QQKe180km83uUYpaoaAHPYc0mcWU7qYmaaH_3l0rPc1j5r0Z5iPkHtgjsKYpQUlZgABZKiFKKBlwJuQFmZ0Hl2fN1DW5SWnDWK0q0c7I5sNE02PGSL3DIfvOW5N9GGgXIs3fSB1an6ZGHxxuaejofrAYs_FDPtJd9BapDf0Os__L-Ska3Jjb-gPGI00YD6Mp3ZKrzmwT3v3XOfl6ef5cLIvV--vb4mlVWC5qWVilHHDVdmvBZdsAjsJWiKqSQkEHFqRAtmZGOaFspSzaqjYOGHcIthZiTh5Oe3cx_OwxZb0J-ziMJzWXHGrWqFaOrvrksjGkFLHT4yu9iUcNTE9c9YRMT_j0yFWDPnEVv1LCbOk</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2521608795</pqid></control><display><type>article</type><title>Parameter identification for the decision model of uncertainty price competition in food delivery services</title><source>IOP Publishing Free Content</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>IOPscience extra</source><creator>Andriani, D P ; Kusuma, L T W N ; Rachman, A B ; Firdausa, S Z ; Azzahra, A D ; Fadhlurrahman, Q A</creator><creatorcontrib>Andriani, D P ; Kusuma, L T W N ; Rachman, A B ; Firdausa, S Z ; Azzahra, A D ; Fadhlurrahman, Q A</creatorcontrib><description>The sharing economy innovation has created a new service industry sector, the ride-hailing industry. Government regulations regarding minimum tariffs change the competition map and uncertainty in that industry. This has led to predatory pricing, switching costs and pre-emptive duopoly. This study aims to determine the parameters that can affect the decision model in the uncertainty of price competition through factorial experiments. This study was conducted on two ride-hailing companies, which currently lead market share, thus establishing a duopoly market. There are many services offered by these companies. This study focuses on investigating food delivery services, which are one of the stable services during the Covid-19 pandemic. The approach that will be used in this research is a factorial experiment to determine what parameters can affect price determination with several uncertainty cases. The result is the identification of the optimal decision model, both parameters and levels in pricing. The implication of this study is fair competition for the welfare of society and the country.</description><identifier>ISSN: 1755-1307</identifier><identifier>EISSN: 1755-1315</identifier><identifier>DOI: 10.1088/1755-1315/733/1/012035</identifier><language>eng</language><publisher>Bristol: IOP Publishing</publisher><subject>Car sharing ; Competition ; COVID-19 ; Delivery services ; Factorial experiments ; Food ; Government regulations ; Markets ; Mathematical models ; Pandemics ; Parameter identification ; Postal & delivery services ; Predatory pricing ; Pricing ; Sharing economy ; Uncertainty</subject><ispartof>IOP conference series. Earth and environmental science, 2021-04, Vol.733 (1), p.12035</ispartof><rights>2021. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2365-c77d1279fb325981efb3c4ee745371f1c153e0b0a7d37c47cec46ad102de1c633</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Andriani, D P</creatorcontrib><creatorcontrib>Kusuma, L T W N</creatorcontrib><creatorcontrib>Rachman, A B</creatorcontrib><creatorcontrib>Firdausa, S Z</creatorcontrib><creatorcontrib>Azzahra, A D</creatorcontrib><creatorcontrib>Fadhlurrahman, Q A</creatorcontrib><title>Parameter identification for the decision model of uncertainty price competition in food delivery services</title><title>IOP conference series. Earth and environmental science</title><description>The sharing economy innovation has created a new service industry sector, the ride-hailing industry. Government regulations regarding minimum tariffs change the competition map and uncertainty in that industry. This has led to predatory pricing, switching costs and pre-emptive duopoly. This study aims to determine the parameters that can affect the decision model in the uncertainty of price competition through factorial experiments. This study was conducted on two ride-hailing companies, which currently lead market share, thus establishing a duopoly market. There are many services offered by these companies. This study focuses on investigating food delivery services, which are one of the stable services during the Covid-19 pandemic. The approach that will be used in this research is a factorial experiment to determine what parameters can affect price determination with several uncertainty cases. The result is the identification of the optimal decision model, both parameters and levels in pricing. The implication of this study is fair competition for the welfare of society and the country.</description><subject>Car sharing</subject><subject>Competition</subject><subject>COVID-19</subject><subject>Delivery services</subject><subject>Factorial experiments</subject><subject>Food</subject><subject>Government regulations</subject><subject>Markets</subject><subject>Mathematical models</subject><subject>Pandemics</subject><subject>Parameter identification</subject><subject>Postal & delivery services</subject><subject>Predatory pricing</subject><subject>Pricing</subject><subject>Sharing economy</subject><subject>Uncertainty</subject><issn>1755-1307</issn><issn>1755-1315</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNo9kEFLAzEQhYMoWKt_QQKe180km83uUYpaoaAHPYc0mcWU7qYmaaH_3l0rPc1j5r0Z5iPkHtgjsKYpQUlZgABZKiFKKBlwJuQFmZ0Hl2fN1DW5SWnDWK0q0c7I5sNE02PGSL3DIfvOW5N9GGgXIs3fSB1an6ZGHxxuaejofrAYs_FDPtJd9BapDf0Os__L-Ska3Jjb-gPGI00YD6Mp3ZKrzmwT3v3XOfl6ef5cLIvV--vb4mlVWC5qWVilHHDVdmvBZdsAjsJWiKqSQkEHFqRAtmZGOaFspSzaqjYOGHcIthZiTh5Oe3cx_OwxZb0J-ziMJzWXHGrWqFaOrvrksjGkFLHT4yu9iUcNTE9c9YRMT_j0yFWDPnEVv1LCbOk</recordid><startdate>20210401</startdate><enddate>20210401</enddate><creator>Andriani, D P</creator><creator>Kusuma, L T W N</creator><creator>Rachman, A B</creator><creator>Firdausa, S Z</creator><creator>Azzahra, A D</creator><creator>Fadhlurrahman, Q A</creator><general>IOP Publishing</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope></search><sort><creationdate>20210401</creationdate><title>Parameter identification for the decision model of uncertainty price competition in food delivery services</title><author>Andriani, D P ; Kusuma, L T W N ; Rachman, A B ; Firdausa, S Z ; Azzahra, A D ; Fadhlurrahman, Q A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2365-c77d1279fb325981efb3c4ee745371f1c153e0b0a7d37c47cec46ad102de1c633</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Car sharing</topic><topic>Competition</topic><topic>COVID-19</topic><topic>Delivery services</topic><topic>Factorial experiments</topic><topic>Food</topic><topic>Government regulations</topic><topic>Markets</topic><topic>Mathematical models</topic><topic>Pandemics</topic><topic>Parameter identification</topic><topic>Postal & delivery services</topic><topic>Predatory pricing</topic><topic>Pricing</topic><topic>Sharing economy</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Andriani, D P</creatorcontrib><creatorcontrib>Kusuma, L T W N</creatorcontrib><creatorcontrib>Rachman, A B</creatorcontrib><creatorcontrib>Firdausa, S Z</creatorcontrib><creatorcontrib>Azzahra, A D</creatorcontrib><creatorcontrib>Fadhlurrahman, Q A</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Environmental Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Environmental Science Collection</collection><jtitle>IOP conference series. Earth and environmental science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Andriani, D P</au><au>Kusuma, L T W N</au><au>Rachman, A B</au><au>Firdausa, S Z</au><au>Azzahra, A D</au><au>Fadhlurrahman, Q A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Parameter identification for the decision model of uncertainty price competition in food delivery services</atitle><jtitle>IOP conference series. Earth and environmental science</jtitle><date>2021-04-01</date><risdate>2021</risdate><volume>733</volume><issue>1</issue><spage>12035</spage><pages>12035-</pages><issn>1755-1307</issn><eissn>1755-1315</eissn><abstract>The sharing economy innovation has created a new service industry sector, the ride-hailing industry. Government regulations regarding minimum tariffs change the competition map and uncertainty in that industry. This has led to predatory pricing, switching costs and pre-emptive duopoly. This study aims to determine the parameters that can affect the decision model in the uncertainty of price competition through factorial experiments. This study was conducted on two ride-hailing companies, which currently lead market share, thus establishing a duopoly market. There are many services offered by these companies. This study focuses on investigating food delivery services, which are one of the stable services during the Covid-19 pandemic. The approach that will be used in this research is a factorial experiment to determine what parameters can affect price determination with several uncertainty cases. The result is the identification of the optimal decision model, both parameters and levels in pricing. The implication of this study is fair competition for the welfare of society and the country.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1755-1315/733/1/012035</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1755-1307 |
| ispartof | IOP conference series. Earth and environmental science, 2021-04, Vol.733 (1), p.12035 |
| issn | 1755-1307 1755-1315 |
| language | eng |
| recordid | cdi_proquest_journals_2521608795 |
| source | IOP Publishing Free Content; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; IOPscience extra |
| subjects | Car sharing Competition COVID-19 Delivery services Factorial experiments Food Government regulations Markets Mathematical models Pandemics Parameter identification Postal & delivery services Predatory pricing Pricing Sharing economy Uncertainty |
| title | Parameter identification for the decision model of uncertainty price competition in food delivery services |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T22%3A56%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Parameter%20identification%20for%20the%20decision%20model%20of%20uncertainty%20price%20competition%20in%20food%20delivery%20services&rft.jtitle=IOP%20conference%20series.%20Earth%20and%20environmental%20science&rft.au=Andriani,%20D%20P&rft.date=2021-04-01&rft.volume=733&rft.issue=1&rft.spage=12035&rft.pages=12035-&rft.issn=1755-1307&rft.eissn=1755-1315&rft_id=info:doi/10.1088/1755-1315/733/1/012035&rft_dat=%3Cproquest_cross%3E2521608795%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2521608795&rft_id=info:pmid/&rfr_iscdi=true |