Advanced search
Publication Cover
International Journal of Production Research Volume 53, 2015 - Issue 17
Submit an article Journal homepage
290
Views
14
CrossRef citations to date
0
Altmetric
Articles

Practical information diffusion techniques to accelerate new product pilot runs

Der-Chiang LiDepartment of Industrial and Information Management, National Cheng Kung University, Tainan, TaiwanCorrespondence[email protected]
,
Wen-Chih ChenDepartment of Industrial and Information Management, National Cheng Kung University, Tainan, Taiwan
,
Che-Jung ChangDepartment of Industrial and Information Management, National Cheng Kung University, Tainan, Taiwan
,
Chien-Chih ChenDepartment of Industrial and Information Management, National Cheng Kung University, Tainan, Taiwan
&
I-Hsiang WenDepartment of Industrial and Information Management, National Cheng Kung University, Tainan, Taiwan
Pages 5310-5319 | Received 06 Jun 2014, Accepted 28 Feb 2015, Published online: 17 Apr 2015

Citations (14)

Keep up to date with the latest research on this topic with citation updates for this article.

Subscribe to citation updates

Read on this site (6)

Abdulrahman Al-Surmi, Mahdi Bashiri & Ioannis Koliousis. (2022) AI based decision making: combining strategies to improve operational performance. International Journal of Production Research 60:14, pages 4464-4486.
Read now
Yong-Hong Kuo & Andrew Kusiak. (2019) From data to big data in production research: the past and future trends. International Journal of Production Research 57:15-16, pages 4828-4853.
Read now
Dongliang Cui, Guoqi Feng, Ping Zhou & Yajun Zhang. (2017) Parametric design-based multi-objective optimisation for high-pressure turbine disc. International Journal of Production Research 55:17, pages 4847-4861.
Read now
Der-Chiang Li, Wu-Kuo Lin, Liang-Sian Lin, Chien-Chih Chen & Wen-Ting Huang. (2017) The attribute-trend-similarity method to improve learning performance for small datasets. International Journal of Production Research 55:7, pages 1898-1913.
Read now
Der-Chiang Li, I-Hsiang Wen & Wen-Chih Chen. (2016) A novel data transformation model for small data-set learning. International Journal of Production Research 54:24, pages 7453-7463.
Read now
Che-Jung Chang, Liping Yu & Peng Jin. (2016) A mega-trend-diffusion grey forecasting model for short-term manufacturing demand. Journal of the Operational Research Society 67:12, pages 1439-1445.
Read now

Articles from other publishers (8)

Der-Chiang Li, Wen-Kuei Huang & Yao-San Lin. (2022) New Product Short-Term Demands Forecasting with Boxplot-Based Fractional Grey Prediction Model. Applied Sciences 12:10, pages 5131.
Crossref
Chathura Wanigasekara, Ebrahim Oromiehie, Akshya Swain, B. Gangadhara Prusty & Sing Kiong Nguang. (2021) Machine learning-based inverse predictive model for AFP based thermoplastic composites. Journal of Industrial Information Integration 22, pages 100197.
Crossref
Chathura Wanigasekara, Ebrahim Oromiehie, Akshya Swain, B. Gangadhara Prusty & Sing Kiong Nguang. (2020) Machine Learning Based Predictive Model for AFP-Based Unidirectional Composite Laminates. IEEE Transactions on Industrial Informatics 16:4, pages 2315-2324.
Crossref
Chathura Wanigasekara, Akshya Swain, Sing Kiong Nguang & B. Gangadhara Prusty. (2019) Neural Network Based Inverse System Identification from Small Data Sets. Neural Network Based Inverse System Identification from Small Data Sets.
Pattarin Chumnumpan & Xiaohui Shi. (2021) Understanding New Products’ Market Performance Using Google Trends. Australasian Marketing Journal 27:2, pages 91-103.
Crossref
Yigit Kazancoglu, Yesim Deniz Ozkan-Ozen & Melisa Ozbiltekin. (2018) Minimizing losses in milk supply chain with sustainability: An example from an emerging economy. Resources, Conservation and Recycling 139, pages 270-279.
Crossref
Chathura Wanigasekara, Akshya Swain, Sing Kiong Nguang & B Gangadhara Prusty. (2018) Improved Learning from Small Data Sets Through Effective Combination of Machine Learning Tools with VSG Techniques. Improved Learning from Small Data Sets Through Effective Combination of Machine Learning Tools with VSG Techniques.
Yao-San Lin, Yaofeng Zhang, I-Ching Lin & Che-Jung Chang. (2018) Predicting logistics delivery demand with deep neural networks. Predicting logistics delivery demand with deep neural networks.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Order Reprints Request Corporate Permissions

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

Request Academic Permissions

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.