Creation of demand forecasting models based on public information
Statistic data are reported by government and organizations, and these data are considered to be important for forecasting future demand in the industry. In addition, patens and papers are issued and published all over the world, covering a wide range of technologies, and it would be powerful if thi...
Gespeichert in:
| Veröffentlicht in: | The Journal of Information Science and Technology Association 2023/06/01, Vol.73(6), pp.242-245 |
|---|---|
| 1. Verfasser: | |
| Format: | Artikel |
| Sprache: | chi ; eng ; jpn |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 245 |
|---|---|
| container_issue | 6 |
| container_start_page | 242 |
| container_title | The Journal of Information Science and Technology Association |
| container_volume | 73 |
| creator | TAKEI, Yoshiyuki |
| description | Statistic data are reported by government and organizations, and these data are considered to be important for forecasting future demand in the industry. In addition, patens and papers are issued and published all over the world, covering a wide range of technologies, and it would be powerful if this information could be applied to a forecasting model for demand forecasting. In this paper, we developed a demand forecasting model using the number of patent applications, the number of patent applicants, the value evaluation index of patens, and information on citations of papers, and examined the applicability of the model and which factors are related to demand in fields of photocatalyst and Li-ion batteries. |
| doi_str_mv | 10.18919/jkg.73.6_242 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_jstag</sourceid><recordid>TN_cdi_proquest_reports_2871884437</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2871884437</sourcerecordid><originalsourceid>FETCH-LOGICAL-j1107-ce3d8d58e15b4cd037130dff3a210936b6fe0a203185b78bb92639d39417241c3</originalsourceid><addsrcrecordid>eNo9kLtPwzAYxC0EElXpyG6xJ9j-nNgZGKqKl1SJBWbLjy8lIS_sdOC_J1DEciedfnfDEXLNWc51xavb9uOQK8hLI6Q4IyuxpJkWSp-TFas4ZKAZvySblFrGmChYIQuxIttdRDs340DHmgbs7RBoPUb0Ns3NcKD9GLBL1NmEgS7UdHRd42kzLFD_W7wiF7XtEm7-fE3eHu5fd0_Z_uXxebfdZy3nTGUeIehQaOSFkz4wUBxYqGuwgrMKSlfWyKxgwHXhlHauEiVUASrJlZDcw5rcnHanOH4eMc0m4jTGORmhFddaSlALdHeC2jTbA5opNr2NX8bGufEdmuUko8CUP7L89J_7dxsNDvANFy9hhw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2871884437</pqid></control><display><type>article</type><title>Creation of demand forecasting models based on public information</title><source>J-STAGE Free</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>TAKEI, Yoshiyuki</creator><creatorcontrib>TAKEI, Yoshiyuki</creatorcontrib><description>Statistic data are reported by government and organizations, and these data are considered to be important for forecasting future demand in the industry. In addition, patens and papers are issued and published all over the world, covering a wide range of technologies, and it would be powerful if this information could be applied to a forecasting model for demand forecasting. In this paper, we developed a demand forecasting model using the number of patent applications, the number of patent applicants, the value evaluation index of patens, and information on citations of papers, and examined the applicability of the model and which factors are related to demand in fields of photocatalyst and Li-ion batteries.</description><identifier>ISSN: 0913-3801</identifier><identifier>EISSN: 2189-8278</identifier><identifier>DOI: 10.18919/jkg.73.6_242</identifier><language>chi ; eng ; jpn</language><publisher>Tokyo: Information Science and Technology Association, Japan</publisher><subject>Demand ; demand forecasting ; Forecasting ; Li-ion battery ; Multiple regression analysis ; patent valuation ; photocatalyst ; RMSE ; Statistical data</subject><ispartof>The Journal of Information Science and Technology Association, 2023/06/01, Vol.73(6), pp.242-245</ispartof><rights>2023 Author(s)</rights><rights>Copyright Information Science and Technology Assn Jun 2023</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,1877,27901,27902</link.rule.ids></links><search><creatorcontrib>TAKEI, Yoshiyuki</creatorcontrib><title>Creation of demand forecasting models based on public information</title><title>The Journal of Information Science and Technology Association</title><addtitle>JOHO NO KAGAKU TO GIJUTSU</addtitle><description>Statistic data are reported by government and organizations, and these data are considered to be important for forecasting future demand in the industry. In addition, patens and papers are issued and published all over the world, covering a wide range of technologies, and it would be powerful if this information could be applied to a forecasting model for demand forecasting. In this paper, we developed a demand forecasting model using the number of patent applications, the number of patent applicants, the value evaluation index of patens, and information on citations of papers, and examined the applicability of the model and which factors are related to demand in fields of photocatalyst and Li-ion batteries.</description><subject>Demand</subject><subject>demand forecasting</subject><subject>Forecasting</subject><subject>Li-ion battery</subject><subject>Multiple regression analysis</subject><subject>patent valuation</subject><subject>photocatalyst</subject><subject>RMSE</subject><subject>Statistical data</subject><issn>0913-3801</issn><issn>2189-8278</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNo9kLtPwzAYxC0EElXpyG6xJ9j-nNgZGKqKl1SJBWbLjy8lIS_sdOC_J1DEciedfnfDEXLNWc51xavb9uOQK8hLI6Q4IyuxpJkWSp-TFas4ZKAZvySblFrGmChYIQuxIttdRDs340DHmgbs7RBoPUb0Ns3NcKD9GLBL1NmEgS7UdHRd42kzLFD_W7wiF7XtEm7-fE3eHu5fd0_Z_uXxebfdZy3nTGUeIehQaOSFkz4wUBxYqGuwgrMKSlfWyKxgwHXhlHauEiVUASrJlZDcw5rcnHanOH4eMc0m4jTGORmhFddaSlALdHeC2jTbA5opNr2NX8bGufEdmuUko8CUP7L89J_7dxsNDvANFy9hhw</recordid><startdate>20230601</startdate><enddate>20230601</enddate><creator>TAKEI, Yoshiyuki</creator><general>Information Science and Technology Association, Japan</general><general>Information Science and Technology Assn</general><scope>E3H</scope><scope>F2A</scope></search><sort><creationdate>20230601</creationdate><title>Creation of demand forecasting models based on public information</title><author>TAKEI, Yoshiyuki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-j1107-ce3d8d58e15b4cd037130dff3a210936b6fe0a203185b78bb92639d39417241c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>chi ; eng ; jpn</language><creationdate>2023</creationdate><topic>Demand</topic><topic>demand forecasting</topic><topic>Forecasting</topic><topic>Li-ion battery</topic><topic>Multiple regression analysis</topic><topic>patent valuation</topic><topic>photocatalyst</topic><topic>RMSE</topic><topic>Statistical data</topic><toplevel>online_resources</toplevel><creatorcontrib>TAKEI, Yoshiyuki</creatorcontrib><collection>Library & Information Sciences Abstracts (LISA)</collection><collection>Library & Information Science Abstracts (LISA)</collection><jtitle>The Journal of Information Science and Technology Association</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>TAKEI, Yoshiyuki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Creation of demand forecasting models based on public information</atitle><jtitle>The Journal of Information Science and Technology Association</jtitle><addtitle>JOHO NO KAGAKU TO GIJUTSU</addtitle><date>2023-06-01</date><risdate>2023</risdate><volume>73</volume><issue>6</issue><spage>242</spage><epage>245</epage><pages>242-245</pages><issn>0913-3801</issn><eissn>2189-8278</eissn><abstract>Statistic data are reported by government and organizations, and these data are considered to be important for forecasting future demand in the industry. In addition, patens and papers are issued and published all over the world, covering a wide range of technologies, and it would be powerful if this information could be applied to a forecasting model for demand forecasting. In this paper, we developed a demand forecasting model using the number of patent applications, the number of patent applicants, the value evaluation index of patens, and information on citations of papers, and examined the applicability of the model and which factors are related to demand in fields of photocatalyst and Li-ion batteries.</abstract><cop>Tokyo</cop><pub>Information Science and Technology Association, Japan</pub><doi>10.18919/jkg.73.6_242</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0913-3801 |
| ispartof | The Journal of Information Science and Technology Association, 2023/06/01, Vol.73(6), pp.242-245 |
| issn | 0913-3801 2189-8278 |
| language | chi ; eng ; jpn |
| recordid | cdi_proquest_reports_2871884437 |
| source | J-STAGE Free; EZB-FREE-00999 freely available EZB journals |
| subjects | Demand demand forecasting Forecasting Li-ion battery Multiple regression analysis patent valuation photocatalyst RMSE Statistical data |
| title | Creation of demand forecasting models based on public information |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-05T15%3A46%3A09IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_jstag&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Creation%20of%20demand%20forecasting%20models%20based%20on%20public%20information&rft.jtitle=The%20Journal%20of%20Information%20Science%20and%20Technology%20Association&rft.au=TAKEI,%20Yoshiyuki&rft.date=2023-06-01&rft.volume=73&rft.issue=6&rft.spage=242&rft.epage=245&rft.pages=242-245&rft.issn=0913-3801&rft.eissn=2189-8278&rft_id=info:doi/10.18919/jkg.73.6_242&rft_dat=%3Cproquest_jstag%3E2871884437%3C/proquest_jstag%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2871884437&rft_id=info:pmid/&rfr_iscdi=true |