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[{"key": "dc.contributor.advisor", "value": "Vuorinen, Jukka", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Salo, Eetu", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2024-06-10T12:12:21Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2024-06-10T12:12:21Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2024", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/95711", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Teknologian kehittyess\u00e4 v\u00e4hitt\u00e4iskaupan sektori siirtyy monikanavaiseen l\u00e4hestymistapaan miss\u00e4 fyysinen ja digitaalinen kaupank\u00e4ynti sulautuu yhteen. T\u00e4t\u00e4 siirtym\u00e4\u00e4 korostaa kest\u00e4vyyden merkityksen kasvu, mit\u00e4 ohjataan usein jopa lains\u00e4\u00e4d\u00e4nn\u00f6ll\u00e4. Tutkimus toteutettiin kuvailevana kirjallisuuskatsauksena, jossa tutkittiin mit\u00e4 olemassaoleva kirjallisuus sanoo ennakoivan analytiikan kyvyst\u00e4 parantaa v\u00e4hitt\u00e4iskaupan toimitusketjun operationaalista tehokkuutta ja kest\u00e4vyyytt\u00e4. Tutkimus toteutettiin k\u00e4ytt\u00e4en vertaisarvioituja tieteellisi\u00e4 julkaisuja, jotka k\u00e4sittelev\u00e4t ennakoivaa analytiikkaa, kest\u00e4vyytt\u00e4 ja v\u00e4hitt\u00e4iskaupan toimitusketjuja. Valitut tutkimukset suodatettiin niiden merkityksellisyyden, laadun ja julkaisujen ajankohtaisuuden perusteella. Tutkielmassa havaituista hy\u00f6dyist\u00e4 sek\u00e4 haasteista tehtiin yhteenveto, joka tarjoaa selke\u00e4n n\u00e4kym\u00e4n t\u00e4m\u00e4n katsauksen tuloksista. Tutkimuksessa havaittiin, ett\u00e4 ennakoiva analytiikka parantaa merkitt\u00e4v\u00e4sti toimitusketjun tehokkuutta ennustamalla kysynn\u00e4n tarkasti ja optimoimalla resurssien kohdentamisen. Lis\u00e4ksi ennakoiva analytiikka vahvistaa p\u00e4\u00e4t\u00f6ksentekoa, mahdollistaen nopeamman sopeutumisen kehittyviin markkinatrendeihin. Tutkielma tunnistaa my\u00f6s haasteita, kuten tietojen eheys, analyysimallien monimutkaisuus ja tarpeen datavetoiselle kulttuurille. Organisaatioiden tulee huomioida n\u00e4m\u00e4 haasteet ja puuttua niihin hy\u00f6dynt\u00e4\u00e4kseen ennakoivaa analytiikkaa tehokkaasti kest\u00e4v\u00e4n kilpailuedun saavuttamiseksi v\u00e4hitt\u00e4iskaupan alalla.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "As technology advances and digital options gain popularity, the retail sector is shifting towards a multichannel approach where digital and physical retail channels are merging. This shift is emphasized by an increasing focus on sustainability, now a critical requirement often reinforced by legislation. This thesis conducts a descriptive literature review to explore current literature insights into the capabilities of Predictive Analytics for enhancing both operational efficiency and sustainability within retail supply chains. The literature review was conducted using peer-reviewed scientific publications related to predictive analytics, sustainability, and retail supply chains. The selected studies were then filtered based on the recentness of the publication, relevance, and quality. The findings were organized to highlight both the benefits and challenges, providing a clear view of the results of this review. These findings demonstrate that Predictive Analytics substantially improves supply chain efficiency by forecasting demands accurately and optimizing resource allocation. Moreover, Predictive Analytics provides strong decision-making, allowing retail businesses to adapt swiftly to evolving market trends. The thesis also identifies challenges such as data integrity, the complexity of analytical models, and the need for data-driven culture. Organizations need to note these challenges and address them to leverage Predictive Analytics effectively for achieving a sustainable competitive advantage in the retail sector.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Miia Hakanen (mihakane@jyu.fi) on 2024-06-10T12:12:21Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2024-06-10T12:12:21Z (GMT). No. of bitstreams: 0\n Previous issue date: 2024", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "37", "language": "", "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.subject.other", "value": "predictive analytics", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "sustainability", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "demand forecasting", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "retail supply chain", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "resource efficiency", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "The Role of Predictive Analytics in Streamlining Retail Supply Chains for Enhanced Sustainability and Efficiency", "language": "", "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "bachelor thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-202406104482", "language": "", "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Bachelor's thesis", "language": "en", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Kandidaatinty\u00f6", "language": "fi", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Informaatioteknologian tiedekunta", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Faculty of Information Technology", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Informaatioteknologia", "language": "fi", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Information Technology", "language": "en", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Tietoj\u00e4rjestelm\u00e4tiede", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Information Systems Science", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "yvv.contractresearch.funding", "value": "0", "language": "", "element": "contractresearch", "qualifier": "funding", "schema": "yvv"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_7a1f", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": null, "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "bachelorThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.subject.oppiainekoodi", "value": "601", "language": "", "element": "subject", "qualifier": "oppiainekoodi", "schema": "dc"}, {"key": "dc.subject.yso", "value": "toimitusketjut", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "v\u00e4hitt\u00e4iskauppa", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "optimointi", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "supply chains", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "retail trade", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "optimisation", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://rightsstatements.org/page/InC/1.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}]
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