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Collaborative Planning with Biclustering

Year 2024, EARLY VIEW, 1 - 1
https://doi.org/10.2339/politeknik.1461222

Abstract

For companies, improving and streamlining their supply chains is crucial for survival in the global competitive environment. Collaborative Planning, Forecasting, and Replenishment (CPFR) is a process management strategy that promotes collaboration among supply chain participants and aims to achieve mutual benefits between parties. CPFR enables effective collaboration between manufacturers, suppliers, and customers. If there are many customers and suppliers in a company's supply chain, the process of establishing collaboration can be achieved faster and at a lower cost by using biclustering, a business analytics method. Biclustering can reduce the need for multiple collaborations by grouping customers in the supply chain according to their common characteristics. Therefore, biclustering and CPFR are valuable tools that can be used together to improve efficiency in the supply chain. Combining these techniques can help increasing competitive advantage and managing supply chain operations more successfully. In this study, a company operating in the automotive supply industry used a biclustering strategy to collaborate with multiple customers. The findings revealed the potential benefits of biclustering, which enables the company to work with multiple customers simultaneously. It is evident that this strategy can benefit businesses in various ways, such as facilitating inventory control and increasing supply chain effectiveness.

References

  • [1] Ireland, R. K. and Crum, C., "Supply chain collaboration: How to implement CPFR and other best collaborative practices." U.S.A.: J. Ross Publishing, (2005).
  • [2] Seifert, D., "Collaborative planning, forecasting, and replenishment: How to create a supply chain advantage," 1 ed. U.S.A.: Amacom, (2003).
  • [3] Christopher, M. and Jüttner, U., "Developing strategic partnerships in the supply chain: A practitioner perspective," European Journal of Purchasing and Supply Management, 6, 117-127, (2000).
  • [4] Danese, P., Romano, P., and Vinelli, A., "Managing business processes across supply networks: the role of coordination mechanisms," Journal of Purchasing and Supply Management, 10,165-177, (2004).
  • [5] Arsawan, W. E., Koval, V., Suhartanto, D., Babachenko, L., Kapranova, L., and Suryantini, N. P. S., "Invigorating supply chain performance in small medium enterprises: exploring knowledge sharing as moderator," Business, Management and Economics Engineering, 21,1-18, (2023).
  • [6] Torgul, B. and Paksoy, T., "Multi-level competitive closed loop supply chain network design," Journal of Polytechnic-Politeknik Dergisi, 27, (2024).
  • [7] Gürdere, A., İlbaş, A., and Boran, F. E., "Türk Silahlı Kuvvetleri ve Özel Sektör Lojistiğinin Entegrasyonu İçin SWOT ve Bulanık Tercih İlişkileri Analizi," Politeknik Dergisi, 27, 653-664, (2024).
  • [8] Daugherty, P. J., Richey, R. G., Roath, A. S., Min, S., Chen, H., Arndt, A. D., and Genchev, S. E., "Is collaboration paying off for firms?," Business Horizons, 49, 61-70, (2006).
  • [9] Holweg, M., Disney, S., Holmström, J., and Småros, J., "Supply chain collaboration: Making sense of the strategy continuum," European Management Journal, 23, 170-181, (2005).
  • [10] Cao, M. and Zhang, Q., "Supply chain collaboration: Impact on collaborative advantage and firm performance," Journal of Operations Management, 29, 163-180, (2011).
  • [11] Vickery, S. K., Jayaram, J., Droge, C., and Calantone, R., "The effects of an integrative supply chain strategy on customer service and financial performance: an analysis of direct versus indirect relationships," Journal of Operations Management, 21, 523-539, (2003).
  • [12] Raghunathan, S., "Interorganizational collaborative forecasting and replenishment systems and supply chain implications," Decision Sciences, 30, 1053-1071, (1999).
  • [13] Kulp, S. C., Lee, H. L., and Ofek, E., "Manufacturer Benefits from Information Integration with Retail Customers," Management Science, 50, 431-444, (2004).
  • [14] Petersen, K. J., Ragatz, G. L., and Monczka, R. M., "An examination of collaborative planning effectiveness and supply chain performance," Journal of Supply Chain Management, 41, 14-25, (2005).
  • [15] Chung, W. W. C. and Leung, S. W. F., "Collaborative planning, forecasting and replenishment: a case study in copper clad laminate industry," Production Planning & Control, 16, 563-574, (2005).
  • [16] Kim, D., "Process chain: A new paradigm of collaborative commerce and synchronized supply chain," Business Horizons, 49, 359-367, (2006).
  • [17] Rivera, L., Wan, H.-d., Chen, F. F., and Lee, W. M., "Beyond partnerships: The power of lean supply chains," in Trends in supply chain design and management: Technologies and methodologies, 1 ed London: Springer, 241-268, (2007).
  • [18] Sari, K., "On the benefits of CPFR and VMI: A comparative simulation study," International Journal of Production Economics, vol. 113, pp. 575-586, (2008).
  • [19] Nyaga, G. N., Whipple, J. M., and Lynch, D. F., "Examining supply chain relationships: do buyer and supplier perspectives on collaborative relationships differ?," Journal of operations management, 28, 101-114, (2010).
  • [20] Kamalapurkar, D., "Benefits of CPFR and VMI collaboration strategies in a variable demand environment," Doctor of Philosophy Doctoral dissertation, Department of Industrial and Manufacturing Engineering, Western Michigan University, Michigan, (2011).
  • [21] Ramanathan, U. and Gunasekaran, A., "Supply chain collaboration: Impact of success in long-term partnerships," International Journal of Production Economics, 147, 252-259, (2012).
  • [22] Boddy, D., Macbeth, D., and Wagner, B., "Implementing collaboration between organizations: An empirical study of supply chain partnering," Journal of Management Studies, 37, 1003-1017, (2000).
  • [23] Hendijani, R. and Norouzi, M., "Supply chain integration and firm performance in the COVID-19 era: the mediating role of resilience and robustness," Journal of Global Operations and Strategic Sourcing, 16, 337-367, (2023).
  • [24] Kotzab, H., Bäumler, I., and Gerken, P., "The big picture on supply chain integration – insights from a bibliometric analysis," Supply Chain Management, 28, 25-54, (2023).
  • [25] Xu, X., Choi, T.-M., Chung, S.-H., and Guo, S., "Collaborative-commerce in supply chains: A review and classification of analytical models," International Journal of Production Economics, 263, 108922, 2023/09/01/ (2023).
  • [26] Daghar, A., Alinaghian, L., and Turner, N., "The role of collaborative interorganizational relationships in supply chain risks: a systematic review using a social capital perspective," Supply Chain Management, 26, 279-296, (2021).
  • [27] Zhang, X. and Song, H., "An integrative framework for collaborative forecasting in tourism supply chains," International Journal of Tourism Research, 20, 158-171, (2018).
  • [28] Ryu, C. S., "Simulation study of two supply chain collaboration programs: Consignment and VMI," Journal of Distribution Science, 14, 21-31, (2016).
  • [29] Panahifar, F., Heavey, C., Byrne, P. J., and Fazlollahtabar, H., "A framework for Collaborative Planning, Forecasting and Replenishment (CPFR): State of the Art," Journal of Enterprise Information Management, 28, 838-871, (2015).
  • [30] Hollmann, R. L., Scavarda, L. F., and Thomé, A. M. T., "Collaborative planning, forecasting and replenishment: a literature review," International Journal of Productivity and Performance Management, 64, 971-993, (2015).
  • [31] J.S, N., Chilkapure, A., and Pillai, V. M., "Literature review on supply chain collaboration: comparison of various collaborative techniques," Journal of Advances in Management Research, 16, 537-562, (2019).
  • [32] Bailey, K. and Francis, M., "Managing information flows for improved value chain performance," International Journal of Production Economics, 111, 2-12, (2008).
  • [33] Cachon, G. P. and Fisher, M., "Supply chain inventory management and the value of shared information," Management science, 46, 1032-1048, (2000).
  • [34] Aviv, Y., "The effect of collaborative forecasting on supply chain performance," Management science, 47, 1326-1343, (2001).
  • [35] Byrne, P. and Heavey, C., "The impact of information sharing and forecasting in capacitated industrial supply chains: A case study," International Journal of Production Economics, 103, 420-437, (2006).
  • [36] Pan, J. C.-H. and Yang, J.-S., "A study of an integrated inventory with controllable lead time," International Journal of Production Research, 40, 1263-1273, (2002).
  • [37] Yao, Y., Evers, P. T., and Dresner, M. E., "Supply chain integration in vendor-managed inventory," Decision support systems, 43, 663-674, (2007).
  • [38] Tekerek, A. and Dörterler, M., "The Adaptation of Gray Wolf Optimizer to Data Clustering," Journal of Polytechnic-Politeknik Dergisi, 25, 1761-1767, (2022).
  • [39] Busygin, S., Prokopyev, O., and Pardalos, P. M., "Biclustering in data mining," Computers and Operations Research, 35, 2964-2987, (2008).
  • [40] Boutsinas, B., "Machine-part cell formation using biclustering," European Journal of Operational Research, 230, 563-572, (2013).
  • [41] Pinheiro, R. G. S., Martins, I. C., Protti, F., Ochi, L. S., Simonetti, L. G., and Subramanian, A., "On solving manufacturing cell formation via Bicluster Editing," European Journal of Operational Research, 254, 769-779, (2016).
  • [42] Batsyn, M. V., Batsyna, E. K., and Bychkov, I. S., "NP-completeness of cell formation problem with grouping efficacy objective," International Journal of Production Research, 58, 6159-6169, (2020).
  • [43] Panteli, A., Boutsinas, B., and Giannikos, I., "On solving the multiple p-median problem based on biclustering," Operational Research, 21, 775-799, (2021).
  • [44] Sabherwal, R. and Becerra-Fernandez, I., "Business Intelligence: Practices, Technologies, and Management," Wiley, (2010).
  • [45] Turban, E., Sharda, R., Delen, D., King, D., and Aronson, J. E., "Business Intelligence: A Managerial Approach," Prentice Hall, (2010).
  • [46] Trkman, P., McCormack, K., de Oliveira, M. P. V., and Ladeira, M. B., "The impact of business analytics on supply chain performance," Decision Support Systems, 49, 318-327, (2010).
  • [47] Oliveira, M. P. V. d., McCormack, K., and Trkman, P., "Business analytics in supply chains – The contingent effect of business process maturity," Expert Systems with Applications, 39, 5488-5498, (2012).
  • [48] Kohavi, R., Rothleder, N. J., and Simoudis, E., "Emerging trends in business analytics," Communications of the ACM, 45, 45-48, (2002).
  • [49] Chae, B. K., Olson, D., and Sheu, C., "The impact of supply chain analytics on operational performance: A resource-based view," International Journal of Production Research, 52, 4695-4710, (2014).
  • [50] Madeira, S. C. and Oliveira, A. L., "Biclustering algorithms for biological data analysis: A survey," IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1, 24-45, (2004).
  • [51] Hartigan, J. A., "Direct Clustering of a Data Matrix," Journal of the American Statistical Association, 67, 123-129, 1972/03/01 (1972).
  • [52] Cheng, Y. and Church, G. M., "Biclustering of expression data," in Ismb, 93-103, (2000).
  • [53] Getz, G., Levine, E., and Domany, E., "Coupled two-way clustering analysis of gene microarray data," Proceedings of the National Academy of Sciences, 97, 12079-12084, (2000).
  • [54] Califano, A., Stolovitzky, G., and Tu, Y., "Analysis of gene expression microarrays for phenotype classification," in Ismb, 75-85, (2000).
  • [55] Lazzeroni, L. and Owen, A., "Plaid models for gene expression data," Statistica sinica, 61-86, (2002).
  • [56] Segal, E., Taskar, B., Gasch, A., Friedman, N., and Koller, D., "Rich probabilistic models for gene expression," Bioinformatics-Oxford-, 17, S243-S252, (2001).
  • [57] Tang, C., Zhang, L., Zhang, A., and Ramanathan, M., "Interrelated two-way clustering: an unsupervised approach for gene expression data analysis," in Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001), 41-48, (2001).
  • [58] Tanay, A., Sharan, R., and Shamir, R., "Discovering statistically significant biclusters in gene expression data," Bioinformatics-Oxford-, 18, S136-S144, (2002).
  • [59] Yang, J., Wang, H., Wang, W., and Yu, P., "Enhanced biclustering on expression data," in Third IEEE Symposium on Bioinformatics and Bioengineering, 2003. Proceedings., 321-327, (2003).
  • [60] Prelić, A., Bleuler, S., Zimmermann, P., Wille, A., Bühlmann, P., Gruissem, W., Hennig, L., et al., "A systematic comparison and evaluation of biclustering methods for gene expression data," Bioinformatics, 22, 1122-1129, (2006).
  • [61] Wu, C. and Barnes, D., "A literature review of decision-making models and approaches for partner selection in agile supply chains," Journal of Purchasing and Supply Management, 17, 256-274, (2011).
  • [62] Hitt, M. A., Dacin, M. T., Levitas, E., Arregle, J.-L., and Borza, A., "Partner selection in emerging and developed market contexts: Resource-based and organizational learning perspectives," Academy of Management journal, 43, 449-467, (2000).

İkili Kümeleme ile İş Birlikçi Planlama

Year 2024, EARLY VIEW, 1 - 1
https://doi.org/10.2339/politeknik.1461222

Abstract

Firmalar için yer aldıkları tedarik zincirlerini geliştirmek ve daha etkili kılmak, küresel rekabet ortamında hayatta kalmak adına önemlidir. İş birlikçi Planlama, Tahmin ve İkmal (İPTİ) tedarik zinciri katılımcıları arasında iş birliğini teşvik eden ve taraflar arasında ortak fayda sağlamayı amaçlayan bir süreç yönetim stratejisidir. İPTİ ile üreticiler ile tedarikçileri ve müşterileri arasında etkin iş birlikleri mümkündür. Bir firmanın tedarik zincirinde çok sayıda müşteri ve tedarikçi yer alıyorsa her bir iş birliği için ayrı çaba sarf etmek yerine bir iş analitiği yöntemi olan ikili kümeleme kullanılarak iş birliği kurma süreci daha hızlı ve daha düşük maliyetle gerçekleştirilebilir. İkili kümeleme, çok sayıda iş birliği kurma ihtiyacını tedarik zincirindeki müşterilerin ortak özelliklerine göre gruplandırarak azaltabilir. Bu nedenle, ikili kümeleme ve İPTİ, tedarik zincirinde verimliliğini artırmak için beraber kullanılabilecek değerli araçlardır. Bu tekniklerin birleştirilmesi, rekabet avantajının artırılmasına ve tedarik zinciri operasyonlarının daha başarılı bir şekilde yönetilmesine yardımcı olabilir. Bu çalışmada otomotiv yan sanayi sektöründe faaliyet gösteren bir firma, ikili kümeleme stratejisini kullanarak birden fazla müşteriyle tek bir iş birliği gerçekleştirmiştir. Bulgular, firmanın birden fazla müşterisiyle beraber çalışmasına olanak tanıyan ikili kümelemenin potansiyel faydalarını ortaya koymuştur. Bu stratejinin işletmelere müşteri odaklı girişimler oluşturma, envanter kontrolünü kolaylaştırma ve tedarik zinciri etkinliğini artırma gibi faydalar sağlayabileceği açıktır.

References

  • [1] Ireland, R. K. and Crum, C., "Supply chain collaboration: How to implement CPFR and other best collaborative practices." U.S.A.: J. Ross Publishing, (2005).
  • [2] Seifert, D., "Collaborative planning, forecasting, and replenishment: How to create a supply chain advantage," 1 ed. U.S.A.: Amacom, (2003).
  • [3] Christopher, M. and Jüttner, U., "Developing strategic partnerships in the supply chain: A practitioner perspective," European Journal of Purchasing and Supply Management, 6, 117-127, (2000).
  • [4] Danese, P., Romano, P., and Vinelli, A., "Managing business processes across supply networks: the role of coordination mechanisms," Journal of Purchasing and Supply Management, 10,165-177, (2004).
  • [5] Arsawan, W. E., Koval, V., Suhartanto, D., Babachenko, L., Kapranova, L., and Suryantini, N. P. S., "Invigorating supply chain performance in small medium enterprises: exploring knowledge sharing as moderator," Business, Management and Economics Engineering, 21,1-18, (2023).
  • [6] Torgul, B. and Paksoy, T., "Multi-level competitive closed loop supply chain network design," Journal of Polytechnic-Politeknik Dergisi, 27, (2024).
  • [7] Gürdere, A., İlbaş, A., and Boran, F. E., "Türk Silahlı Kuvvetleri ve Özel Sektör Lojistiğinin Entegrasyonu İçin SWOT ve Bulanık Tercih İlişkileri Analizi," Politeknik Dergisi, 27, 653-664, (2024).
  • [8] Daugherty, P. J., Richey, R. G., Roath, A. S., Min, S., Chen, H., Arndt, A. D., and Genchev, S. E., "Is collaboration paying off for firms?," Business Horizons, 49, 61-70, (2006).
  • [9] Holweg, M., Disney, S., Holmström, J., and Småros, J., "Supply chain collaboration: Making sense of the strategy continuum," European Management Journal, 23, 170-181, (2005).
  • [10] Cao, M. and Zhang, Q., "Supply chain collaboration: Impact on collaborative advantage and firm performance," Journal of Operations Management, 29, 163-180, (2011).
  • [11] Vickery, S. K., Jayaram, J., Droge, C., and Calantone, R., "The effects of an integrative supply chain strategy on customer service and financial performance: an analysis of direct versus indirect relationships," Journal of Operations Management, 21, 523-539, (2003).
  • [12] Raghunathan, S., "Interorganizational collaborative forecasting and replenishment systems and supply chain implications," Decision Sciences, 30, 1053-1071, (1999).
  • [13] Kulp, S. C., Lee, H. L., and Ofek, E., "Manufacturer Benefits from Information Integration with Retail Customers," Management Science, 50, 431-444, (2004).
  • [14] Petersen, K. J., Ragatz, G. L., and Monczka, R. M., "An examination of collaborative planning effectiveness and supply chain performance," Journal of Supply Chain Management, 41, 14-25, (2005).
  • [15] Chung, W. W. C. and Leung, S. W. F., "Collaborative planning, forecasting and replenishment: a case study in copper clad laminate industry," Production Planning & Control, 16, 563-574, (2005).
  • [16] Kim, D., "Process chain: A new paradigm of collaborative commerce and synchronized supply chain," Business Horizons, 49, 359-367, (2006).
  • [17] Rivera, L., Wan, H.-d., Chen, F. F., and Lee, W. M., "Beyond partnerships: The power of lean supply chains," in Trends in supply chain design and management: Technologies and methodologies, 1 ed London: Springer, 241-268, (2007).
  • [18] Sari, K., "On the benefits of CPFR and VMI: A comparative simulation study," International Journal of Production Economics, vol. 113, pp. 575-586, (2008).
  • [19] Nyaga, G. N., Whipple, J. M., and Lynch, D. F., "Examining supply chain relationships: do buyer and supplier perspectives on collaborative relationships differ?," Journal of operations management, 28, 101-114, (2010).
  • [20] Kamalapurkar, D., "Benefits of CPFR and VMI collaboration strategies in a variable demand environment," Doctor of Philosophy Doctoral dissertation, Department of Industrial and Manufacturing Engineering, Western Michigan University, Michigan, (2011).
  • [21] Ramanathan, U. and Gunasekaran, A., "Supply chain collaboration: Impact of success in long-term partnerships," International Journal of Production Economics, 147, 252-259, (2012).
  • [22] Boddy, D., Macbeth, D., and Wagner, B., "Implementing collaboration between organizations: An empirical study of supply chain partnering," Journal of Management Studies, 37, 1003-1017, (2000).
  • [23] Hendijani, R. and Norouzi, M., "Supply chain integration and firm performance in the COVID-19 era: the mediating role of resilience and robustness," Journal of Global Operations and Strategic Sourcing, 16, 337-367, (2023).
  • [24] Kotzab, H., Bäumler, I., and Gerken, P., "The big picture on supply chain integration – insights from a bibliometric analysis," Supply Chain Management, 28, 25-54, (2023).
  • [25] Xu, X., Choi, T.-M., Chung, S.-H., and Guo, S., "Collaborative-commerce in supply chains: A review and classification of analytical models," International Journal of Production Economics, 263, 108922, 2023/09/01/ (2023).
  • [26] Daghar, A., Alinaghian, L., and Turner, N., "The role of collaborative interorganizational relationships in supply chain risks: a systematic review using a social capital perspective," Supply Chain Management, 26, 279-296, (2021).
  • [27] Zhang, X. and Song, H., "An integrative framework for collaborative forecasting in tourism supply chains," International Journal of Tourism Research, 20, 158-171, (2018).
  • [28] Ryu, C. S., "Simulation study of two supply chain collaboration programs: Consignment and VMI," Journal of Distribution Science, 14, 21-31, (2016).
  • [29] Panahifar, F., Heavey, C., Byrne, P. J., and Fazlollahtabar, H., "A framework for Collaborative Planning, Forecasting and Replenishment (CPFR): State of the Art," Journal of Enterprise Information Management, 28, 838-871, (2015).
  • [30] Hollmann, R. L., Scavarda, L. F., and Thomé, A. M. T., "Collaborative planning, forecasting and replenishment: a literature review," International Journal of Productivity and Performance Management, 64, 971-993, (2015).
  • [31] J.S, N., Chilkapure, A., and Pillai, V. M., "Literature review on supply chain collaboration: comparison of various collaborative techniques," Journal of Advances in Management Research, 16, 537-562, (2019).
  • [32] Bailey, K. and Francis, M., "Managing information flows for improved value chain performance," International Journal of Production Economics, 111, 2-12, (2008).
  • [33] Cachon, G. P. and Fisher, M., "Supply chain inventory management and the value of shared information," Management science, 46, 1032-1048, (2000).
  • [34] Aviv, Y., "The effect of collaborative forecasting on supply chain performance," Management science, 47, 1326-1343, (2001).
  • [35] Byrne, P. and Heavey, C., "The impact of information sharing and forecasting in capacitated industrial supply chains: A case study," International Journal of Production Economics, 103, 420-437, (2006).
  • [36] Pan, J. C.-H. and Yang, J.-S., "A study of an integrated inventory with controllable lead time," International Journal of Production Research, 40, 1263-1273, (2002).
  • [37] Yao, Y., Evers, P. T., and Dresner, M. E., "Supply chain integration in vendor-managed inventory," Decision support systems, 43, 663-674, (2007).
  • [38] Tekerek, A. and Dörterler, M., "The Adaptation of Gray Wolf Optimizer to Data Clustering," Journal of Polytechnic-Politeknik Dergisi, 25, 1761-1767, (2022).
  • [39] Busygin, S., Prokopyev, O., and Pardalos, P. M., "Biclustering in data mining," Computers and Operations Research, 35, 2964-2987, (2008).
  • [40] Boutsinas, B., "Machine-part cell formation using biclustering," European Journal of Operational Research, 230, 563-572, (2013).
  • [41] Pinheiro, R. G. S., Martins, I. C., Protti, F., Ochi, L. S., Simonetti, L. G., and Subramanian, A., "On solving manufacturing cell formation via Bicluster Editing," European Journal of Operational Research, 254, 769-779, (2016).
  • [42] Batsyn, M. V., Batsyna, E. K., and Bychkov, I. S., "NP-completeness of cell formation problem with grouping efficacy objective," International Journal of Production Research, 58, 6159-6169, (2020).
  • [43] Panteli, A., Boutsinas, B., and Giannikos, I., "On solving the multiple p-median problem based on biclustering," Operational Research, 21, 775-799, (2021).
  • [44] Sabherwal, R. and Becerra-Fernandez, I., "Business Intelligence: Practices, Technologies, and Management," Wiley, (2010).
  • [45] Turban, E., Sharda, R., Delen, D., King, D., and Aronson, J. E., "Business Intelligence: A Managerial Approach," Prentice Hall, (2010).
  • [46] Trkman, P., McCormack, K., de Oliveira, M. P. V., and Ladeira, M. B., "The impact of business analytics on supply chain performance," Decision Support Systems, 49, 318-327, (2010).
  • [47] Oliveira, M. P. V. d., McCormack, K., and Trkman, P., "Business analytics in supply chains – The contingent effect of business process maturity," Expert Systems with Applications, 39, 5488-5498, (2012).
  • [48] Kohavi, R., Rothleder, N. J., and Simoudis, E., "Emerging trends in business analytics," Communications of the ACM, 45, 45-48, (2002).
  • [49] Chae, B. K., Olson, D., and Sheu, C., "The impact of supply chain analytics on operational performance: A resource-based view," International Journal of Production Research, 52, 4695-4710, (2014).
  • [50] Madeira, S. C. and Oliveira, A. L., "Biclustering algorithms for biological data analysis: A survey," IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1, 24-45, (2004).
  • [51] Hartigan, J. A., "Direct Clustering of a Data Matrix," Journal of the American Statistical Association, 67, 123-129, 1972/03/01 (1972).
  • [52] Cheng, Y. and Church, G. M., "Biclustering of expression data," in Ismb, 93-103, (2000).
  • [53] Getz, G., Levine, E., and Domany, E., "Coupled two-way clustering analysis of gene microarray data," Proceedings of the National Academy of Sciences, 97, 12079-12084, (2000).
  • [54] Califano, A., Stolovitzky, G., and Tu, Y., "Analysis of gene expression microarrays for phenotype classification," in Ismb, 75-85, (2000).
  • [55] Lazzeroni, L. and Owen, A., "Plaid models for gene expression data," Statistica sinica, 61-86, (2002).
  • [56] Segal, E., Taskar, B., Gasch, A., Friedman, N., and Koller, D., "Rich probabilistic models for gene expression," Bioinformatics-Oxford-, 17, S243-S252, (2001).
  • [57] Tang, C., Zhang, L., Zhang, A., and Ramanathan, M., "Interrelated two-way clustering: an unsupervised approach for gene expression data analysis," in Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001), 41-48, (2001).
  • [58] Tanay, A., Sharan, R., and Shamir, R., "Discovering statistically significant biclusters in gene expression data," Bioinformatics-Oxford-, 18, S136-S144, (2002).
  • [59] Yang, J., Wang, H., Wang, W., and Yu, P., "Enhanced biclustering on expression data," in Third IEEE Symposium on Bioinformatics and Bioengineering, 2003. Proceedings., 321-327, (2003).
  • [60] Prelić, A., Bleuler, S., Zimmermann, P., Wille, A., Bühlmann, P., Gruissem, W., Hennig, L., et al., "A systematic comparison and evaluation of biclustering methods for gene expression data," Bioinformatics, 22, 1122-1129, (2006).
  • [61] Wu, C. and Barnes, D., "A literature review of decision-making models and approaches for partner selection in agile supply chains," Journal of Purchasing and Supply Management, 17, 256-274, (2011).
  • [62] Hitt, M. A., Dacin, M. T., Levitas, E., Arregle, J.-L., and Borza, A., "Partner selection in emerging and developed market contexts: Resource-based and organizational learning perspectives," Academy of Management journal, 43, 449-467, (2000).
There are 62 citations in total.

Details

Primary Language Turkish
Subjects Industrial Engineering, Packaging, Storage and Transportation (Excl. Food and Agricultural Products)
Journal Section Research Article
Authors

Alptekin Demiray 0009-0000-7667-7796

Fatma Ateş 0000-0001-6512-0685

Sena Aydoğan 0000-0003-1267-1779

Diyar Akay 0000-0002-3215-0236

Early Pub Date June 27, 2024
Publication Date
Submission Date March 29, 2024
Acceptance Date May 27, 2024
Published in Issue Year 2024 EARLY VIEW

Cite

APA Demiray, A., Ateş, F., Aydoğan, S., Akay, D. (2024). İkili Kümeleme ile İş Birlikçi Planlama. Politeknik Dergisi1-1. https://doi.org/10.2339/politeknik.1461222
AMA Demiray A, Ateş F, Aydoğan S, Akay D. İkili Kümeleme ile İş Birlikçi Planlama. Politeknik Dergisi. Published online June 1, 2024:1-1. doi:10.2339/politeknik.1461222
Chicago Demiray, Alptekin, Fatma Ateş, Sena Aydoğan, and Diyar Akay. “İkili Kümeleme Ile İş Birlikçi Planlama”. Politeknik Dergisi, June (June 2024), 1-1. https://doi.org/10.2339/politeknik.1461222.
EndNote Demiray A, Ateş F, Aydoğan S, Akay D (June 1, 2024) İkili Kümeleme ile İş Birlikçi Planlama. Politeknik Dergisi 1–1.
IEEE A. Demiray, F. Ateş, S. Aydoğan, and D. Akay, “İkili Kümeleme ile İş Birlikçi Planlama”, Politeknik Dergisi, pp. 1–1, June 2024, doi: 10.2339/politeknik.1461222.
ISNAD Demiray, Alptekin et al. “İkili Kümeleme Ile İş Birlikçi Planlama”. Politeknik Dergisi. June 2024. 1-1. https://doi.org/10.2339/politeknik.1461222.
JAMA Demiray A, Ateş F, Aydoğan S, Akay D. İkili Kümeleme ile İş Birlikçi Planlama. Politeknik Dergisi. 2024;:1–1.
MLA Demiray, Alptekin et al. “İkili Kümeleme Ile İş Birlikçi Planlama”. Politeknik Dergisi, 2024, pp. 1-1, doi:10.2339/politeknik.1461222.
Vancouver Demiray A, Ateş F, Aydoğan S, Akay D. İkili Kümeleme ile İş Birlikçi Planlama. Politeknik Dergisi. 2024:1-.