Forecasting movie demand using total and split exponential smoothing
In the motion picture industry, the movie market players always rely on accurate demand forecasts. Distributors require the demand forecasts to decide the best release date of the new movies that arguably the most difficult decision. Thus, forecasting methods which are able to capture historical p...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2018
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| Online Access: | http://journalarticle.ukm.my/19795/ http://journalarticle.ukm.my/19795/1/jeko_522-7.pdf |
| _version_ | 1848814933520678912 |
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| author | Mak, Kit Mun Choo, Wei Chong |
| author_facet | Mak, Kit Mun Choo, Wei Chong |
| author_sort | Mak, Kit Mun |
| building | UKM Institutional Repository |
| collection | Online Access |
| description | In the motion picture industry, the movie market players always rely on accurate demand forecasts. Distributors require
the demand forecasts to decide the best release date of the new movies that arguably the most difficult decision. Thus,
forecasting methods which are able to capture historical patterns can be relied on to produce an accurate prediction.
Exponential smoothing methods are the common methods, but there is limited study using this technique in movie
demand forecasting. In this paper, we study the performance of a newly proposed seasonal exponential smoothing
method that previously has been considered for forecasting daily supermarket sales. It is known as total and split
exponential smoothing, and apply it to daily box office from the United States market. The resulting forecasts are
compared against other exponential smoothing methods, seasonal adjustment, non-seasonal, and seasonal exponential
smoothing methods. Overall, total and split exponential smoothing with optimised parameters separately for each lead
time is performing good, followed by seasonal (damped trend) exponential smoothing method (DA-A). The identification
of the best performing method assists distributors to make a decision on the best release date for their new movies
earlier than the competitors. |
| first_indexed | 2025-11-15T00:41:57Z |
| format | Article |
| id | oai:generic.eprints.org:19795 |
| institution | Universiti Kebangasaan Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T00:41:57Z |
| publishDate | 2018 |
| publisher | Penerbit Universiti Kebangsaan Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:generic.eprints.org:197952022-09-21T06:47:31Z http://journalarticle.ukm.my/19795/ Forecasting movie demand using total and split exponential smoothing Mak, Kit Mun Choo, Wei Chong In the motion picture industry, the movie market players always rely on accurate demand forecasts. Distributors require the demand forecasts to decide the best release date of the new movies that arguably the most difficult decision. Thus, forecasting methods which are able to capture historical patterns can be relied on to produce an accurate prediction. Exponential smoothing methods are the common methods, but there is limited study using this technique in movie demand forecasting. In this paper, we study the performance of a newly proposed seasonal exponential smoothing method that previously has been considered for forecasting daily supermarket sales. It is known as total and split exponential smoothing, and apply it to daily box office from the United States market. The resulting forecasts are compared against other exponential smoothing methods, seasonal adjustment, non-seasonal, and seasonal exponential smoothing methods. Overall, total and split exponential smoothing with optimised parameters separately for each lead time is performing good, followed by seasonal (damped trend) exponential smoothing method (DA-A). The identification of the best performing method assists distributors to make a decision on the best release date for their new movies earlier than the competitors. Penerbit Universiti Kebangsaan Malaysia 2018 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/19795/1/jeko_522-7.pdf Mak, Kit Mun and Choo, Wei Chong (2018) Forecasting movie demand using total and split exponential smoothing. Jurnal Ekonomi Malaysia, 52 (2). pp. 81-94. ISSN 0127-1962 https://www.ukm.my/jem/issue/v52i2/ |
| spellingShingle | Mak, Kit Mun Choo, Wei Chong Forecasting movie demand using total and split exponential smoothing |
| title | Forecasting movie demand using total and split exponential smoothing |
| title_full | Forecasting movie demand using total and split exponential smoothing |
| title_fullStr | Forecasting movie demand using total and split exponential smoothing |
| title_full_unstemmed | Forecasting movie demand using total and split exponential smoothing |
| title_short | Forecasting movie demand using total and split exponential smoothing |
| title_sort | forecasting movie demand using total and split exponential smoothing |
| url | http://journalarticle.ukm.my/19795/ http://journalarticle.ukm.my/19795/ http://journalarticle.ukm.my/19795/1/jeko_522-7.pdf |