{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/104549"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/104549","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Clovette : predicting preferences for flowers","abstract":"Flowers are often gifted for major holidays and personal holidays, for both personal and corporate purposes. Today's solutions in the market are abundant but scattered, with many players offering products of varying quality at a range of price points. To command higher prices and stay relevant in the market, florists need to distinguish themselves through high quality and/or niche product and ease of service. The goal for this project is to map the current competitive landscape and supply chain of the flower industry, and to determine whether predictive modeling in the floral industry is feasible as a point of difference for new gifting company Clovette. Data collection through distribution of a survey called \"Discovering Floral Preference\" assessed the potential for prediction. Furthermore, the project explores Clovette's brand identity and potential \"good\" business development through sustainability initiatives and supply chain optimization. Keywords: random forest, predictive modeling, flowers, gifting, sustainability.","abstract_html":"Flowers are often gifted for major holidays and personal holidays, for both personal and corporate purposes. Today's solutions in the market are abundant but scattered, with many players offering products of varying quality at a range of price points. To command higher prices and stay relevant in the market, florists need to distinguish themselves through high quality and/or niche product and ease of service. The goal for this project is to map the current competitive landscape and supply chain of the flower industry, and to determine whether predictive modeling in the floral industry is feasible as a point of difference for new gifting company Clovette. Data collection through distribution of a survey called "Discovering Floral Preference" assessed the potential for prediction. Furthermore, the project explores Clovette's brand identity and potential "good" business development through sustainability initiatives and supply chain optimization. Keywords: random forest, predictive modeling, flowers, gifting, sustainability.","abstract_has_math":false,"creators":["Lee, Jeeyun Jennifer"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Sloan School of Management.","school":null,"contributors":[],"advisors":["Tauhid Zaman."],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016","date_published":"2016","updated_at":"2026-07-22T22:21:54Z","subjects":["Sloan School of Management."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/104549","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Tauhid Zaman."]},{"key":"dc:contributor.department","label":"Department","values":["Sloan School of Management."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Sloan School of Management."]},{"key":"dc:creator","label":"Author","values":["Lee, Jeeyun Jennifer"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2016-09-30T19:35:05Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2016-09-30T19:35:05Z"]},{"key":"dc:date.issued","label":"Date","values":["2016"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Sloan School of Management."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/104549"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2016.","Cataloged from PDF version of thesis.","Includes bibliographical references (pages 69-73)."]},{"key":"dc:description.abstract","label":"Abstract","values":["Flowers are often gifted for major holidays and personal holidays, for both personal and corporate purposes. Today's solutions in the market are abundant but scattered, with many players offering products of varying quality at a range of price points. To command higher prices and stay relevant in the market, florists need to distinguish themselves through high quality and/or niche product and ease of service. The goal for this project is to map the current competitive landscape and supply chain of the flower industry, and to determine whether predictive modeling in the floral industry is feasible as a point of difference for new gifting company Clovette. Data collection through distribution of a survey called \"Discovering Floral Preference\" assessed the potential for prediction. Furthermore, the project explores Clovette's brand identity and potential \"good\" business development through sustainability initiatives and supply chain optimization. Keywords: random forest, predictive modeling, flowers, gifting, sustainability."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.B.A."]},{"key":"dc:title","label":"Title","values":["Clovette : predicting preferences for flowers"]}]}],"canonical_facts":{"dc:contributor.advisor":["Tauhid Zaman."],"dc:contributor.department":["Sloan School of Management."],"dc:contributor.other":["Sloan School of Management."],"dc:creator":["Lee, Jeeyun Jennifer"],"dc:date.accessioned":["2016-09-30T19:35:05Z"],"dc:date.available":["2016-09-30T19:35:05Z"],"dc:date.issued":["2016"],"dc:description":["Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2016.","Cataloged from PDF version of thesis.","Includes bibliographical references (pages 69-73)."],"dc:description.abstract":["Flowers are often gifted for major holidays and personal holidays, for both personal and corporate purposes. Today's solutions in the market are abundant but scattered, with many players offering products of varying quality at a range of price points. To command higher prices and stay relevant in the market, florists need to distinguish themselves through high quality and/or niche product and ease of service. The goal for this project is to map the current competitive landscape and supply chain of the flower industry, and to determine whether predictive modeling in the floral industry is feasible as a point of difference for new gifting company Clovette. Data collection through distribution of a survey called \"Discovering Floral Preference\" assessed the potential for prediction. Furthermore, the project explores Clovette's brand identity and potential \"good\" business development through sustainability initiatives and supply chain optimization. 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