Open Access
| Issue |
MATEC Web Conf.
Volume 215, 2018
The 2nd International Conference on Technology, Innovation, Society and Science-to-Business (ICTIS 2018)
|
|
|---|---|---|
| Article Number | 02004 | |
| Number of page(s) | 7 | |
| Section | Science to Business | |
| DOI | https://doi.org/10.1051/matecconf/201821502004 | |
| Published online | 16 October 2018 | |
- Ali, A. H. M., (2003). Poultry Industry in Malaysia: Issues and Challenges. Knowledge Transfer Programme (KTP) Workshop on Business Model for Broiler Industry in Malaysia. Penang. [Google Scholar]
- Ariffin, Ahmad Shabudin Bin, Hendrik Lamsali, and Shahimi Mohtar, (2013). ‘Linkages between Integrator, Grower Involvement and Business Performance: An Excerpt from Preliminary Findings’, International Journal of Supply Chain Management, 2.3: 47–52. [Google Scholar]
- Ariffin, Ahmad Shabudin, Hendrik Lamsali, and Shahimi Mohtar, (2012). ‘Linkages between supplier, customer involvement and business performance: A green supply chain investigation in the poultry industry’, 2012 International Conference on Green and Ubiquitous Technology (GUT), IEEE, Bandung, 41–44. [CrossRef] [Google Scholar]
- Febransyah, A., and Simangunsong, E., (2015). ‘Supply chain competitiveness in food industry: An Indonesian case, Supply Chain Design and Management for Emerging Markets’, Springer International Publishing, 147–175. [Google Scholar]
- Garcia, R. G., Almeida Paz, I. C. L., Caldara, F. R., Nääs, I. A., Pereira, D. F., and Ferreira, V. M. O. S., (2012). ‘Selecting the most adequate bedding material for broiler production in Brazil’, RevistaBrasileira de CiênciaAvícola, 14.2: 121–127. [Google Scholar]
- Korpela, J., and Tuominen, M., (1996). ‘A decision support system for strategic issues management of logistics’, International journal of production economics, 46: 605–620. [CrossRef] [Google Scholar]
- Opasanon, Sathaporn, and Pattarakamol Lertsanti, (2013). ‘Impact analysis of logistics facility relocation using the analytic hierarchy process (AHP)’, International Transactions in Operational Research, 20.3: 325–339. [CrossRef] [Google Scholar]
- Saaty, T. L., (1979). Mathematical modeling of dynamic decisions; priorities and hierarchies with time dependence, Mathematics and computers in Simulation, 21.4: 352–358. [CrossRef] [Google Scholar]
- Saaty, T. L., (1990). ‘How to make a decision: the analytic hierarchy process’, European journal of operational research, 48.1: 9–26. [CrossRef] [Google Scholar]
- Saaty, T. L., (1994). ‘Highlights and critical points in the theory and application of the analytic hierarchy process’, European journal of operational research, 74.3: 426–447. [Google Scholar]
- Saaty, T. L., (2008). ‘Decision making with the analytic hierarchy process’, International journal of services sciences, 1.1: 83–98. [Google Scholar]
- Saaty, T.L., (2000). ‘Fundamentals of decision making and priority theory with the analytic hierarchy process’, Rws Publications, 6. [Google Scholar]
- Sipahi, Seyhan, and Mehpare Timor, (2010). ‘The analytic hierarchy process and analytic network process: an overview of applications’, Management Decision, 48.5: 775–808. [CrossRef] [Google Scholar]
- Siqueira, K. B., da Silva, C. A. B., and Aguiar, D. R., (2008). ‘Viability of introducing milk futures contracts in Brazil: a multiple criteria decision analysis’, Agribusiness, 24.4: 491–509. [CrossRef] [Google Scholar]
- Vaidya, Omkarprasad S., and Sushil Kumar, (2006). ‘Analytic hierarchy process: An overview of applications’, European Journal of operational research, 169.1: 1–29. [Google Scholar]
- Yakovleva, N., Sarkis, J., and Sloan, T., (2012). ‘Sustainable benchmarking of supply chains: the case of the food industry’, International Journal of Production Research, 50.5: 1297–1317. [CrossRef] [Google Scholar]
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