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1

Hollmann, Roberto Luis, Luiz Felipe Scavarda, and Antônio Márcio Tavares Thomé. "Collaborative planning, forecasting and replenishment: a literature review." International Journal of Productivity and Performance Management 64, no. 7 (September 14, 2015): 971–93. http://dx.doi.org/10.1108/ijppm-03-2014-0039.

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Purpose – The purpose of this paper is to provide a systematic review of the literature on Collaborative Planning, Forecasting and Replenishment (CPFR). The review emphasises the descriptors of CPFR implementation and models, as well as the impact of CPFR and other supply chain collaboration (SCC) initiatives on supply chain (SC) performance. Design/methodology/approach – The systematic review includes 50 full-text papers retrieved from four databases: Emerald, EBSCO, ScienceDirect and Wiley. Rigorous and verifiable keywords, review steps and selection criteria were applied to the database and inter-coders agreement was systematically checked. Findings – There is no consensus regarding the breadth and scope of CPFR configurations. CPFR is context-dependent and varies according to the configuration of the SC. Trust, information-communication technology and the quality of information sharing are main enablers and inhibitors of implementation. Practical implications – Practitioners will benefit from insights related to the choice of SCC configurations (e.g. number of partners, nature of products and spatial complexity), the importance of trust and empowerment for SCC and the need to outweigh carefully the costs and benefits of specific SCC before implementation. Originality/value – CPFR, which is considered by many to be the most advanced and the most comprehensive SCC process and has a direct impact upon SC performance. Nonetheless, efforts to synthesise the overall state of the art in CPFR have been rather limited to date. As an effort to fill this gap, this paper provides a better understanding of the role of CPFR as a determinant of SC performance. As an effort to contribute to complete the cycle of theory building based on the literature review, seven propositions for CPFR research are put forward.
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Panahifar, Farhad, Cathal Heavey, PJ Byrne, and Hamed Fazlollahtabar. "A framework for Collaborative Planning, Forecasting and Replenishment (CPFR)." Journal of Enterprise Information Management 28, no. 6 (October 12, 2015): 838–71. http://dx.doi.org/10.1108/jeim-09-2014-0092.

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Purpose – Although many papers purport the significant value attributable to supply chain performance from the use of Collaborative Planning, Forecasting and Replenishment (CPFR), the question of “what are the main constructs and efficient framework for successful implementation of CPFR?” remains largely unanswered. This question will be addressed by identifying and analysing the main constructs for successful implementation of CPFR. The purpose of this paper is to attempt first to seek answers to this question. Second, to review the scope and value of CPFR using a devised state-of-the-art taxonomy for the classification of selected bibliographical references and third, to develop a conceptual framework by identifying areas which need more research. Design/methodology/approach – The method underlying this paper followed the steps of a systematic literature review process outlined by Soni and Kodali (2011). The review is based on a total of 93 papers published from 1998 to 2013 on CPFR. Findings – Four main constructs for successful implementation of CPFR have been identified: CPFR enablers, CPFR barriers, trading partner selection and IA. The findings indicate that there is a need for better understanding of the amount and level of information sharing as an important function of CPFR implementation. The paper also illustrates a number of shortcomings in the current literature and provides suggestions to guide future research on implementing CPFR in different industries. Practical implications – This paper is of interest to both academicians and practitioners as it helps to better understand the concept and role of CPFR in supply chain integration and its implementation results, enablers and inhibitors. The proposed framework in this paper can be used to give insight for future research and practice. Originality/value – The paper offers a framework for the review of previous research on CPFR and identifies the most important shortcomings that need to be addressed in future research. In addition, this review is both greater in scope than previous reviews and is broader in its subject focus.
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Singhry, Hassan Barau, and Azmawani Abd Rahman. "Enhancing supply chain performance through collaborative planning, forecasting, and replenishment." Business Process Management Journal 25, no. 4 (July 3, 2019): 625–46. http://dx.doi.org/10.1108/bpmj-03-2017-0052.

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Purpose Despite the importance of collaborative planning, forecasting, and replenishment (CPFR), its influence on supply chain innovation capability (SCIC) and supply chain performance (SCP) has not been sufficiently examined. The purpose of this paper is to examine the antecedence of SCP through CPFR and SCIC. Design/methodology/approach Through cluster and stratified random sampling, 286 responses from top managers of 1,574 Nigerian manufacturing companies were analyzed. Data analysis was performed using structural equation modeling with AMOS graphics. Findings The results show that SCIC has a full mediating effect on the relationship between CPFR and SCP. Specifically, CPFR has a significant relationship with both SCP and SCIC, and SCIC also relates significantly to SCP. Practical implications This study offers implications for manufacturers in developing countries in general, and in Nigeria in particular, by providing a guideline on how to improve SCP through CPFR. Originality/value The paper contributes to the limited studies on CPFR and SCP by extending this line of study into the realm of innovation capability and innovation. It integrates the social exchange theory and the dynamic capabilities theory to examine the collaborative processes of CPFR in the supply chain context. This study stressed the importance of boundary theoretical spanning by extending CPFR and SCP into the domain of innovation capability.
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Panaihfar, Farhad, Cathal Heavey, and PJ Byrne. "Developing retailer selection factors for collaborative planning, forecasting and replenishment." Industrial Management & Data Systems 115, no. 7 (August 10, 2015): 1292–324. http://dx.doi.org/10.1108/imds-01-2015-0009.

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Purpose – Selecting an appropriate partner is a vital and strategic decision-making process in any supply chain collaboration initiative. The purpose of this paper is to introduce and explore the key factors considered by manufacturers in the selection of an appropriate retailer(s) for collaboration and collaborative planning, forecasting and replenishment (CPFR) implementation and the relationships between these factors. Design/methodology/approach – A comprehensive literature review and experts’ views are applied to identify the main retailer selection and evaluation factors for CPFR implementation. A fuzzy decision-making trial and evaluation laboratory approach is then used to rank and analysis the interaction among identified factors. The findings are finally evaluated using a case study from a high-tech industry. Findings – The most important partner selection factors comprising of five dimensions and 24 factors are introduced. Of the identified criteria, three factors: manufacturer’s familiarity with the retailer, workforce skills and training and customer service orientation and capability have been identified as critical when selecting retailers for CPFR implementation. The technological capabilities dimensions are identified as the only net cause dimension which affects all other dimensions and its importance and role in simplifying and enhancing the speed and flexibility of CPFR implementation. Practical implications – The paper identifies practical retailer selection factors for CPFR implementation and the causal relationships between factors. Developed retailer selection dimensions and criteria will assist manufacturers and retailers in understanding the role these factors play in CPFR implementation. This will also assist in appropriate retailer(s) selection by manufacturers. Originality/value – This paper contributes to the literature on CPFR and tackles the important issue of selecting appropriate partners by developing retailer selection dimensions and criteria in CPFR implementation.
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Berezinets, Irina, Natalia Nikolchenko, and Nikolay Zenkevich. "Is Collaborative Planning a Determinant of Financial Performance in Supply Chain?" International Journal of Information Systems and Supply Chain Management 13, no. 3 (July 2020): 38–53. http://dx.doi.org/10.4018/ijisscm.2020070103.

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As both the practice and the results of the contemporary studies show, collaborative planning, forecasting and replenishment (CPFR) improves the financial performance of supply chain members. The study investigated how Russian companies - the supply chain members, implement the process of CPFR in practice, and how implementation of the concept of collaborative planning affects the financial performance of the companies. The analysis of the obtained results revealed that collaborative planning drives the revenue of companies participating in the supply chain.
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Sherer, Susan A., Rajiv Kohli, Yuliang Yao, and Jerold Cederlund. "Do Cultural Differences Matter in IT Implementation?" Journal of Global Information Management 19, no. 4 (October 2011): 1–17. http://dx.doi.org/10.4018/jgim.2011100101.

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As multinational firms increasingly adopt collaborative technology with supply chain partners in other countries, their implementation strategies need to accommodate cultural differences. This paper draws upon Hofstede’s framework for understanding national cultural characteristics to propose differences in implementation timing and strategy. These propositions are tested with a case study involving a large U.S. based multinational’s implementation of Collaborative Planning, Forecasting and Replenishment (CPFR) with partners in four different countries: U.S., Germany, China, and Poland. This research suggests that cultural differences impact the rollout life cycle for CPFR. The authors recommend that (1) implementation strategies should match national culture, (2) implementation timing can be a function of national culture, and finally (3) customer readiness assessments for CPFR rollout should include an assessment of national cultural differences.
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Wei, Ling Yun, Ming Xiang Wen, and Xiao Guang Zhou. "A Comparative Simulation Study about Supply Chain Inventory Management Strategies Based on System Dynamics." Applied Mechanics and Materials 701-702 (December 2014): 1280–85. http://dx.doi.org/10.4028/www.scientific.net/amm.701-702.1280.

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This paper aims to compare benefits of Vendor Managed Inventory (VMI) system and Collaborative Planning, Forecasting, and Replenishment (CPFR) system based on (R,Q) inventory strategy. Four-stage supply chain models that are simulated by system dynamics (SD) methods will be used to support the comparison. In addition, factors of total cost for the whole supply chain (TSC) and product fill rate (fr) can assist to evaluate simulation models. The results of this study indicate that benefits and flexibility of CPFR appear to be higher than VMI under (R, Q) strategy, and key parameters have significant impacts on TSC of the two systems.
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Vivaldini, Mauro, Sílvio R. I. Pires, and Fernando Bernardi de Souza. "Importância dos fatores não-tecnológicos na implementação do CPFR." Revista de Administração Contemporânea 14, no. 2 (April 2010): 289–309. http://dx.doi.org/10.1590/s1415-65552010000200007.

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De acordo com o Voluntary Interindustry Commerce Standards [VICS], o Collaborative Planning, Forecasting, and Replenishment [CPFR] se baseia na padronização, registro e sincronização de dados eletronicamente, apoiado pela gestão colaborativa existente entre as empresas (VICS, 2004). A partir desta definição, pode-se concluir que existem dois fatores preponderantes na implementação do CPFR: um essencialmente tecnológico e outro não-tecnológico. Nesse contexto, o propósito principal deste estudo é identificar na literatura os chamados fatores não tecnológicos que envolvem o CPFR e analisá-los em situações reais. A importância desses fatores é analisada, então, por meio do estudo de dois casos reais de implementação do CPFR, respectivamente, em uma grande rede de fast food e em um grande distribuidor de alimentos, que operam no Brasil. Os resultados destacam, principalmente, que a previsão da demanda realizada pela empresa coordenadora do CPFR é preponderante sobre o entendimento da demanda por todos os elos da cadeia de suprimentos, que a cultura colaborativa é considerada muito importante no relacionamento ao longo da cadeia (embora não seja determinante para a implementação dos processos) e que o monitoramento das atividades é fundamental para o alinhamento das empresas na gestão do CPFR.
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Chen, Xiang, Xue Feng Zhou, and Wei Hou. "Application of Improved Safety Inventory Quantity in Building Construction." Applied Mechanics and Materials 99-100 (September 2011): 250–53. http://dx.doi.org/10.4028/www.scientific.net/amm.99-100.250.

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Safety inventory quantity computation based on Collaborative Planning Forecasting & Replenishment (CPFR) can avoid uncertainty of material supply in building construction, which can also coordinate relationship between supplier and construction side to reduce inventory cost and to ensure the progress of construction. The paper analyzed systematically on relationship between lead time and safety inventory. Combining with application of CPFR and based on establishing good relation between material supplier and construction contractors, safety inventory level was reduced with management of lead time. Supply of material supplier was also coordinated to reduce uncertainty of inventory quantity. Construction application example based on improved safety inventory quantity method also proves the feasibility of the proposed method.
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CHEN, MU-CHEN, HSU-HWA CHANG, SHUEN-CHIEH CHANG, and SHIH-MING CHEN. "DEVELOPMENT OF MANUFACTURER-RETAILER RELATIONSHIPS THROUGH COLLABORATIVE MANAGEMENT: A CASE STUDY." International Journal of Innovation and Technology Management 01, no. 03 (September 2004): 307–23. http://dx.doi.org/10.1142/s0219877004000210.

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Nowadays enterprises are facing many challenges such as global competition and thin profits. Consequently, enterprises have changed their focus from cost reduction and quality improvement to quick customer response and innovative services. In recent decades, enterprises have developed advanced industry initiatives to improve efficiency by supply chain management. Effective supply chain management is not achievable by any single enterprise, but instead requires a virtual entity of integrated supply chain partners. They have the insightful commitment of real-time information sharing and collaborative management. Under such a circumstance, an initiative of collaborative management, Collaborative Planning, Forecasting, and Replenishment (CPFR), has recently been developed and implemented in the industry. In this paper, a case study of CPFR implementation in Rexon, Taiwan is conducted to provide a reference to other enterprises. Rexon's primary purpose of implementing CPFR is to strengthen its retail partnership, improve the accuracy of demand forecasts, and reduce inventory cost and other related operational costs.
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Saptaria, Lina. "ANALISIS PERAMALAN PERMINTAAN PRODUK NATA DE COCO UNTUK MENDUKUNG PERENCANAAN DAN PENGENDALIAN PRODUKSI DALAM SUPPLY CHAIN DENGAN MODEL CPFR (COLLABORATIVE PLANNING, FORECASTING, AND REPLENISHMENT)." JURNAL NUSANTARA APLIKASI MANAJEMEN BISNIS 2, no. 2 (October 31, 2017): 130. http://dx.doi.org/10.29407/nusamba.v2i2.924.

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Strategi proses bisnis yang dinilai efektif dalam penerapan SCM (Supply Chain Management) adalah penggunaan metode perencanaan kolaboratif, peramalan dan pengisian ulang atau CPFR (Collaborative Planning, Forecasting, And Replenishment) dimana produsen, distributor, dan pengecer bekerjasama untuk merencanakan, meramalkan, dan mengisi kembali produk yang dijual di pasar. Tujuan penelitian ini adalah untuk mendeskripsikan proses penyusunan peramalan kolaboratif antara mitra rantai pasok (Supply Chain) dengan mengacu pada alur kerja model CPFR dalam bisnis manufaktur skala mikro dan menemukan metode peramalan yang dinilai paling efektif dan efisien yang dapat digunakan sebagai dasar pembuatan keputusan dalam perencanaan dan pengendalian produksi sepanjang rantai pasok. Analisis peramalan menggunakan model time series dengan 3 metode yaitu Moving Averages dengan periode waktu 4 bulanan, Trend Projection metode exponential smooting dengan α = 0.1, α = 0.5, α = 0.9 dan Linier Regression (Least Squares). Hasil analisis menunjukkan bahwa metode Linier Regression (Least Squares) merupakan metode yang paling efektif yang dapat digunakan sebagai dasar pembuatan keputusan dalam perencanaan dan pengendalian produksi sepanjang rantai pasok. Kata Kunci: Peramalan Permintaan, Perencanaan dan Pengendalian Produksi, Metode Time Series, Model CPFR
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Skjoett‐Larsen, Tage, Christian Thernøe, and Claus Andresen. "Supply chain collaboration." International Journal of Physical Distribution & Logistics Management 33, no. 6 (August 1, 2003): 531–49. http://dx.doi.org/10.1108/09600030310492788.

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Presents a theoretical framework for analysing interorganizational collaboration. Argues that Collaborative Planning, Forecasting and Replenishment (CPFR) should be viewed as a general approach to coordination of processes between participants in a supply chain, rather than following a slavish step‐by‐step model, as suggested by the organization Voluntary Inter‐Industry Commerce Standards (VICS). This approach demands a deeper analysis of both integration depth and scope of various collaboration forms. This is done primarily from a theoretical perspective, but supported by an empirical study of Danish companies’ attitudes towards interorganizational collaboration.
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Vivaldini, Mauro, Fernando Bernardi de Souza, and Silvio Roberto Ignácio Pires. "Implementação de um sistema Collaborative Planning, Forecasting, and Replenishment em uma grande rede de fast food por meio de um prestador de serviços logísticos." Gestão & Produção 15, no. 3 (December 2008): 477–89. http://dx.doi.org/10.1590/s0104-530x2008000300005.

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A gestão colaborativa é, atualmente, um elemento-chave no contexto da gestão da cadeia de suprimentos. Neste artigo, o tema é abordado mediante a análise de um caso real, em que uma grande rede mundial de fast-food e seu prestador de serviço logístico (PSL) trabalharam conjuntamente no Brasil em um projeto-piloto para a implementação de um collaborative planning, forecasting, and replenishment (CPFR). O trabalho faz uso de uma metodologia de pesquisa-ação e apresenta as principais variáveis que influenciaram o projeto, abordando os processos necessários para a implementação e os pontos que favorecem o CPFR. Com base no caso estudado, o trabalho apresenta um conjunto de propostas sobre o papel dos agentes da cadeia em projetos dessa natureza. A gestão da cadeia de suprimentos por intermédio da coordenação direta de um PSL também permite demonstrar as possibilidades e dificuldades desse sistema, contribuindo com a visão colaborativa na cadeia de suprimentos a partir da relação entre seus agentes.
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Fu, Hsin-Pin. "Comparing the factors that influence the adoption of CPFR by retailers and suppliers." International Journal of Logistics Management 27, no. 3 (November 14, 2016): 931–46. http://dx.doi.org/10.1108/ijlm-10-2014-0168.

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Purpose The purpose of this paper is to compare the factors that influenced the adoption of a Collaborative Planning, Forecasting, and Replenishment (CPFR) model by a retailer that is a lifestyle accessories chain, and a supplier that is a food manufacturer. Design/methodology/approach The study started with the construction of a questionnaire based on the factors of the theoretical framework of a Technology-Organization-Environment that were discovered through a literature review and distribution of the questionnaire to experts. The fuzzy analytical hierarchy process method was used to determine the weights (importance) of these factors. Findings The study found that among the top ten factors, two are the same for both the retailer and the supplier – “partner trust and communication,” and “support of top managers” – while the other factors differ. In addition, it was found that the supplier pays more attention to the environmental issues, while the retailer focuses on organizational issues when introducing a CPFR model. Practical implications This study offers five practical implications for the successful adoption of a CPFR model: first, top management support and trusting relationship building are important factors for both the retailer and the supplier; second, adoption of CPFR is a management issue, rather than a technological issue; third, retailers lead more successfully; fourth, a careful selection of collaborative partners is essential; and finally, an innovative model should be constructed. Originality/value The results can serve as a reference to help enterprises to better allocate their resources, according to the weights of the important adoption factors when they are formulating their strategies for the adoption of CPFR. Decisions based upon this guideline can increase the success rate of CPFR adoptions and can ensure better allocation of resources.
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Vivaldini, M., F. B. Souza, and S. R. I. Pires. "Processos Componentes no CPFR (Collaborative Planning, Forecasting, and Replenishment) – Um Estudo de Caso." Revista Eletrônica Gestão e Serviços 6, no. 2 (December 30, 2015): 1231–59. http://dx.doi.org/10.15603/2177-7284/regs.v6n2p1231-1259.

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Putu, Ni Luh, and Elia Fardiya. "Supply Chain Analysis Using Distribution Requirement Planning (DRP) Based On Bullwhip Effect Parameter (Case Study: Ud. Narwastu, Surabaya)." Jurnal IPTEK 24, no. 2 (December 31, 2020): 95–104. http://dx.doi.org/10.31284/j.iptek.2020.v24i2.914.

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Narwastu Firm is a company in Surabaya which produces traditional body care and aromatherapy. During the product distribution, this company encounters many mistakes such as inappropriateness between Purcashing Order (PO) from distributors/consumers and the goods delivered due to bullwhip effects. Therefore, this research aimed at reducing the bullwhip effects by implementing Collaborative, Planning, Forecasting, and Replenishment (CPFR) method and investigating a lot sizing technique for producing minimum distribution cost by Distribution Requirement Planning (DRP) method in order to regulate order and plan a certain distribution activity. The research results demonstrated that the bullwhip effect values after CPFR improvement of two products that could be repaired were 1.0 for Body Scrub Goats Milk Balibloom (BSC GM BB) 200 gr and 0.96 for Body Mist Sparkling White (BM SW) 60 ml. Meanwhile, the calculations by Distribution Requirement Planning (DRP) method with Economic Order Quantity (EOQ) method got the plans for ordering Body Scrub Lightening (BSC LIGHT) 200 gr by 182 times with total cost IDR 96,886,476 and Body Lotion Lightening (BL LIGHT) 250 ml by 235 times with total cost IDR 125,873,816.
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Putu, Ni Luh, and Elia Fardiya. "Supply Chain Analysis Using Distribution Requirement Planning (DRP) Based On Bullwhip Effect Parameter (Case Study: Ud. Narwastu, Surabaya)." Jurnal IPTEK 24, no. 2 (December 31, 2020): 95–104. http://dx.doi.org/10.31284/j.iptek.2020.v24i2.914.

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Narwastu Firm is a company in Surabaya which produces traditional body care and aromatherapy. During the product distribution, this company encounters many mistakes such as inappropriateness between Purcashing Order (PO) from distributors/consumers and the goods delivered due to bullwhip effects. Therefore, this research aimed at reducing the bullwhip effects by implementing Collaborative, Planning, Forecasting, and Replenishment (CPFR) method and investigating a lot sizing technique for producing minimum distribution cost by Distribution Requirement Planning (DRP) method in order to regulate order and plan a certain distribution activity. The research results demonstrated that the bullwhip effect values after CPFR improvement of two products that could be repaired were 1.0 for Body Scrub Goats Milk Balibloom (BSC GM BB) 200 gr and 0.96 for Body Mist Sparkling White (BM SW) 60 ml. Meanwhile, the calculations by Distribution Requirement Planning (DRP) method with Economic Order Quantity (EOQ) method got the plans for ordering Body Scrub Lightening (BSC LIGHT) 200 gr by 182 times with total cost IDR 96,886,476 and Body Lotion Lightening (BL LIGHT) 250 ml by 235 times with total cost IDR 125,873,816.
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Hohmann, Susanne, and Stephan Zelewski. "Effects of Vendor-Managed Inventory on the Bullwhip Effect." International Journal of Information Systems and Supply Chain Management 4, no. 3 (July 2011): 1–17. http://dx.doi.org/10.4018/jisscm.2011070101.

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The bullwhip effect means that demand variability increases as one moves up the supply chain. In the following article the bullwhip effect is quantified for each part of the supply chain which is presupposed to consist of a producer, a wholesaler, a retailer, and a consumer. After considering the causes of the bullwhip effect, it will be shown with the help of a nonlinear optimization model to what extent the bullwhip effect can be reduced using vendor-managed inventory (VMI) as one concept of Collaborative Planning, Forecasting and Replenishment (CPFR). In contrast to other studies in this field the reduction of the bullwhip effect will be accurately quantified for each part of the supply chain.
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Kim, Sung Min, and Joseph T. Mahoney. "Collaborative planning, forecasting and replenishment (CPFR) as a relational contract: an incomplete contracting perspective." International Journal of Learning and Intellectual Capital 7, no. 3/4 (2010): 403. http://dx.doi.org/10.1504/ijlic.2010.034377.

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Vitorino Filho, Valdir Antonio, João Batista de Camargo Júnior, Silvio Roberto Ignácio Pires, and Ana Rita Tiradentes Terra Argoud. "A produção acadêmica internacional em práticas e iniciativas na gestão colaborativa em cadeias de suprimentos: um estudo bibliométrico." Revista Produção Online 17, no. 2 (June 14, 2017): 567. http://dx.doi.org/10.14488/1676-1901.v17i2.2462.

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Este artigo tem como objetivo analisar a produção acadêmica internacional sobre as principais práticas e iniciativas na gestão colaborativa em cadeias de suprimentos em artigos publicados em periódicos internacionais indexados no Scopus. A pesquisa avaliou publicações no período de 2005 a 2014, utilizando-se de técnicas bibliométricas para identificar ano de publicação, país e periódicos em que esses artigos foram publicados e predominância de temas. No total, a pesquisa investigou 331 artigos com as seguintes práticas e iniciativas colaborativas: Electronic Data Interchange (EDI), Vendor Managed Inventory (VMI), Continuous Replenishment (CR), Efficient Customer Response (ECR) e Collaborative Planning, Forecasting and Replenishment (CPFR). Os resultados da pesquisa demonstram que (a) não existe concentração de publicações em poucos periódicos; (b) existe concentração de publicação sobre os temas em poucos países, destacando-se os Estados Unidos; (c) não existe uma concentração de autores com vários artigos publicados sobre alguma das práticas ou iniciativas; (d) o EDI e VMI são as práticas mais investigadas nos artigos analisados e (e) não há concentração das publicações em algum ano específico, mantendo-se equilibradas as publicações durante o período investigado pela pesquisa.
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Sherman, Richard J. "Collaborative Planning, Forecasting & Replenishment (CPFR): Realizing the Promise of Efficient Consumer Response through Collaborative Technology." Journal of Marketing Theory and Practice 6, no. 4 (October 1998): 6–9. http://dx.doi.org/10.1080/10696679.1998.11501806.

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GOMES, LEONARDO DE CARVALHO, and FRANCISCO JOSÉ KLIEMANN NETO. "MÉTODOS COLABORATIVOS NA GESTÃO DE CADEIAS DE SUPRIMENTOS: DESAFIOS DE IMPLEMENTAÇÃO." Revista de Administração de Empresas 55, no. 5 (October 2015): 563–77. http://dx.doi.org/10.1590/s0034-759020150508.

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RESUMOO tema gestão colaborativa vem sendo abordado como forma de gerar vantagem competitiva. Iniciativas colaborativas em cadeias de suprimentos (CS) proporcionaram o surgimento de métodos e práticas que corroboram a ideia de que a competitividade não se dá mais entre empresas isoladas, e sim entre cadeias. Na literatura, além de métodos colaborativos para a gestão da cadeia de suprimentos (GCS), é possível encontrar iniciativas para projeto, configuração, otimização, entre outras. Porém, observa-se baixa adesão de métodos colaborativos para a GCS, assim como dificuldades de implementação. O objetivo do artigo é investigar os métodos colaborativos referentes à coordenação de CS e analisar suas características e dificuldades de implementação. Uma revisão sistemática apontou o Collaborative Planning, Forecasting and Replenishment (CPFR) como o método colaborativo mais abordado e, posteriormente, um estudo de caso identificou dificuldades na implementação que colaboraram com o que foi pesquisado na literatura.
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Vivaldini, Mauro, and Silvio Pires. "Gestão da Demanda, Colaboração e CPFR (Collaborative Planning, Forecasting, and Replenishment): Um Estudo em Empresas de Alimentação." Sistemas & Gestão 7, no. 3 (2012): 312–24. http://dx.doi.org/10.7177/sg.2012.v7.n3.a2.

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Mu-Chen Chen, Kai-Ying Chen, Ming-Fu Hsu, and Cheng-Ta Yeh. "A Web Services-Based Collaborative Planning, Forecasting, and Replenishment (CPFR) Framework for Managing Spare Parts of Semiconductor Equipment." IEEE Transactions on Semiconductor Manufacturing 22, no. 4 (November 2009): 596–600. http://dx.doi.org/10.1109/tsm.2009.2028217.

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Yao, Yuliang, Rajiv Kohli, Susan A. Sherer, and Jerold Cederlund. "Learning curves in collaborative planning, forecasting, and replenishment (CPFR) information systems: An empirical analysis from a mobile phone manufacturer." Journal of Operations Management 31, no. 6 (August 6, 2013): 285–97. http://dx.doi.org/10.1016/j.jom.2013.07.004.

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Márcio Tavares Thomé, Antonio, Roberto Luis Hollmann, and L. F. R. R. Scavarda do Carmo. "Research synthesis in collaborative planning forecast and replenishment." Industrial Management & Data Systems 114, no. 6 (June 3, 2014): 949–65. http://dx.doi.org/10.1108/imds-03-2014-0085.

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Purpose – The purpose of this research synthesis is to gather and integrate findings on Collaborative Planning Forecast and Replenishment (CPFR) as a business process and as a management practice; and to assemble quantitative evidence of its impact on supply chain (SC) performance. Design/methodology/approach – The researchers independently conducted a systematic review of 629 abstracts and 47 full-text papers. Original keywords were applied to four key electronic databases for operations management and information systems. Rigorous and verifiable selection criteria governed inter-coders reliability, review of steps and exclusion of papers. Resource and dependency-based view of the firm, contingency research and maturity models informed the analysis. Findings – There is not a single “blueprint” for CPFR. Competing models emphasize the need for “trust and confidence” and reliable data systems. The type of products, scope, spatial diversity and number of partners in the network are important contextual variables. Firm resources that are unique and advantages from multiple and reciprocal dependencies are powerful levers. There is no consensus on maturity model and on required investment in data and communication systems. Practical implications – Practical implications are implementation related: cost-benefit analysis and simulations should precede full-scale collaboration. There is a consensus on starting CPFR small and expanding gradually. Originality/value – This synthesis applies a rigorous review method and attempts to assemble the dispersed literature in one study, utilizing explanatory operations management and information systems theories.
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Zhang, Pei, and A. Qian Yuan. "A Study on CPFR Inventory Management Technology." Applied Mechanics and Materials 599-601 (August 2014): 2079–82. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.2079.

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CPFR is a collaborative supply chain inventory management technique, it is very important for supply chain partners to improve cooperative relationship, reduce inventory, improve the forecasting accuracy and supply chain efficiency. This paper identifies what CPFR is, explains the CPFR process, cites benefits that have been achieved, identifies obstacles to implementation, and discusses the necessary measures for CPFR to running succesfully.
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Gao, Jin Dong, Yong Zhang, Fang Jun Zhou, and Hong Long Mao. "Research on Control Model for Spare Parts Inventory Based on the Optimal Replenishment Cycle." Applied Mechanics and Materials 519-520 (February 2014): 1390–94. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.1390.

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Control model for spare parts inventory is established based on the optimal replenishment cycle. The replenishment cycle impact on the spare parts inventory control is analyzed as well as the demand forecasting. First, the optimal replenishment cycle is given by using the method of the lowest cost of inventory. Then according to the demand characteristic of the spare parts, the safety stock can be calculated. Finally on the basis of the demand forecasting, the calculation method of spare parts replenishment quantity is given. A numerical example is presented to verify the validity and practicability of the model.
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Alftan, Annika, Riikka Kaipia, Lauri Loikkanen, and Karen Spens. "Centralised grocery supply chain planning: improved exception management." International Journal of Physical Distribution & Logistics Management 45, no. 3 (April 7, 2015): 237–59. http://dx.doi.org/10.1108/ijpdlm-02-2014-0017.

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Purpose – The purpose of this paper is to present an operations model for retail replenishment collaboration and identifies its expected benefits and limitations for the members of a grocery supply chain. Design/methodology/approach – A case study is conducted on a development project between a grocery wholesaler and two grocery product suppliers. Data are collected through semi-structured interviews with key respondents from four different companies. Findings – Despite advances in collaborative practices in grocery supply chains, retail store replenishment management faces challenges. In particular, demand exceptions management is a challenge in the grocery industry. A replenishment model called Collaborative Buyer-Managed Forecasting (CBMF) creates a proactive planning approach and a platform for close collaboration in the supply chain. The centralised forecasting transforms retailer sales data into a plan which serves the whole supply chain by creating one-order forecast. The CBMF model facilitates efficient demand management, improves demand responsiveness and promotes better availability of products in retail stores. Research limitations/implications – CBMF provides a replenishment planning model for the whole supply chain. It is tested to a limited extent in one supply chain. Practical implications – The study provides managers with a better understanding of the benefits of centralised forecasting and closer replenishment collaboration, especially during periods of exceptional demand. Originality/value – A new approach for managing demand in grocery supply chains with centralised forecasting is provided.
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Molet, Hugues. "Collaborative planning, forecasting and replenishment. edition Jouwen - 2000." Revue Française de Gestion Industrielle 22, no. 1 (March 1, 2003): 95–98. http://dx.doi.org/10.53102/2003.22.01.398.

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Gurgul, Henryk, and Marcin Suder. "Forecasting withdrawals from ATMs." Wiadomości Statystyczne. The Polish Statistician 60, no. 8 (August 28, 2015): 25–48. http://dx.doi.org/10.5604/01.3001.0014.8305.

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The authors explain links between strategy of replenishment of ATMs and costs of ATMs holders. Cost minimalization depends on accuracy of forecasts of withdrawals from ATMs. In the paper the several forecasting methods of withdrawals from ATMs in Euronet network installed in Małopolskie and Podkarpackie voivodships are applied. The used forecasting models are compared based on quality of ex post and ex ante forecasts. The model used in forecasting process depends on many factors e.g. location of ATM or calendar effects. The importance and role of these factors are analyzed in the paper. The authors supplied evidence, that suggested forecasts based on weighted averages are more accurate than forecasts based on methods applied by other authors.
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Briseño-Oliveros, Hugo, Luis Antonio Guzmán-García, Patricia Cano-Olivos, and Diana Sánchez-Partida. "FORECASTING DEMAND IMPROVEMENT FOR REPLENISHMENT IN A RETAIL PAINTING COMPANY." Acta logistica 6, no. 4 (December 31, 2019): 155–64. http://dx.doi.org/10.22306/al.v6i4.143.

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Kubde, R. A., and S. V. Bansod. "Collaborative Planning Forecasting and Replenishment Initiatives: A State of Art." Asian Journal of Industrial Engineering 2, no. 3 (August 15, 2010): 89–104. http://dx.doi.org/10.3923/ajie.2010.89.104.

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34

Raghunathan, Srinivasan. "Interorganizational Collaborative Forecasting and Replenishment Systems and Supply Chain Implications." Decision Sciences 30, no. 4 (September 1999): 1053–71. http://dx.doi.org/10.1111/j.1540-5915.1999.tb00918.x.

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Özer, Fazilet, Ismail Hakki Toroslu, and Pinar Karagoz. "Comparison of Integer Linear Programming and Dynamic Programming Approaches for ATM Cash Replenishment Optimization Problem." International Journal of Applied Metaheuristic Computing 11, no. 3 (July 2020): 120–32. http://dx.doi.org/10.4018/ijamc.2020070107.

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With the automated teller machine (ATM) cash replenishment problem, banks aim to reduce the number of out-of-cash ATMs and duration of out-of-cash status. On the other hand, they want to reduce the cost of cash replenishment, as well. The problem conventionally involves forecasting ATM cash withdrawals, and then cash replenishment optimization based on the forecast. The authors assume that reliable forecasts are already obtained for the amount of cash needed in ATMs. The focus of the article is cash replenishment optimization. After introducing linear programming-based solutions, the authors propose a solution based on dynamic programming. Experiments conducted on real data reveal that the proposed approach can find the optimal solution more efficiently than linear programming.
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Bala, Pradip Kumar. "Purchase-driven Classification for Improved Forecasting in Spare Parts Inventory Replenishment." International Journal of Computer Applications 10, no. 9 (November 10, 2010): 40–45. http://dx.doi.org/10.5120/1507-2025.

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37

Disney, Stephen M., and Marc R. Lambrecht. "On Replenishment Rules, Forecasting, and the Bullwhip Effect in Supply Chains." Foundations and Trends® in Technology, Information and Operations Management 2, no. 1 (2005): 1–80. http://dx.doi.org/10.1561/0200000010.

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Min, Hokey, and Wen Bin 'Vincent' Yu. "Collaborative planning, forecasting and replenishment: demand planning in supply chain management." International Journal of Information Technology and Management 7, no. 1 (2008): 4. http://dx.doi.org/10.1504/ijitm.2008.015886.

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Kumar, Ashwani. "Implications Of Collaborative Planning, Forecasting, And Replenishment In Supply Chain Management." Paradigm 10, no. 1 (January 2006): 21–25. http://dx.doi.org/10.1177/0971890720060104.

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Holmström, Jan, Kary Främling, Riikka Kaipia, and Juha Saranen. "Collaborative planning forecasting and replenishment: new solutions needed for mass collaboration." Supply Chain Management: An International Journal 7, no. 3 (August 2002): 136–45. http://dx.doi.org/10.1108/13598540210436595.

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Hill, Craig A., G. Peter Zhang, and Keith E. Miller. "Collaborative planning, forecasting, and replenishment & firm performance: An empirical evaluation." International Journal of Production Economics 196 (February 2018): 12–23. http://dx.doi.org/10.1016/j.ijpe.2017.11.012.

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42

ChunTa Lin, and ChihYao Lo. "Apply 3C Theory in Collaborative Planning, Forecasting, and Replenishment Expert System Formulation." International Journal of Advancements in Computing Technology 3, no. 7 (August 31, 2011): 38–45. http://dx.doi.org/10.4156/ijact.vol3.issue7.6.

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43

Zhang, Hao, and Jia-Hui Mu. "A Back Propagation Neural Network-Based Method for Intelligent Decision-Making." Complexity 2021 (February 4, 2021): 1–11. http://dx.doi.org/10.1155/2021/6610797.

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A shortage or backlog of inventory can easily occur due to the backward forecasting method typically used, which will affect the normal flow of funds in pharmacies. This paper proposes a replenishment decision model with back propagation neural network multivariate regression analysis methods. With the regular pattern between sales and individual variables, supplemented with the safety stock empirical formula, an accurate replenishment quantity can be obtained. In the case analysis, this paper takes the sales situation of a pharmacy as an example and tests the accuracy and stability of the model. The results show that the model has good prediction accuracy which can be introduced into the intelligent pharmacy system and used in the replenishment of the intelligent pharmacy to prevent overstocking or a shortage of stock, thus improving the financial situation, reducing the manpower burden of typical retail pharmacy, and helping residents buy medicines.
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Chungsuk Ryu. "Review of Collaborative Planning, Forecasting, and Replenishment as a Supply Chain Collaboration Program." Journal of Distribution Science 12, no. 3 (March 2014): 85–98. http://dx.doi.org/10.15722/jds.12.3.201403.85.

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A. Kubde, Rajesh. "Collaborative Planning, Forecasting and Replenishment: Determinants of Joint Action in Buyer-supplier Relationships." Research Journal of Business Management 6, no. 1 (December 15, 2011): 12–18. http://dx.doi.org/10.3923/rjbm.2012.12.18.

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Chung *, W. W. C., and S. W. F. Leung. "Collaborative planning, forecasting and replenishment: a case study in copper clad laminate industry." Production Planning & Control 16, no. 6 (September 2005): 563–74. http://dx.doi.org/10.1080/09537280500112488.

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47

Bukhori, Saiful, and Windi Eka Yulia Retnani. "Development of Supply Chain Management Agribusiness Using Collaborative, Planning, Forecasting and Replenishment Concept." Advanced Science Letters 23, no. 3 (March 1, 2017): 2340–43. http://dx.doi.org/10.1166/asl.2017.8757.

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48

Wang, S. J., C. T. Huang, W. L. Wang, and Y. H. Chen. "Incorporating ARIMA forecasting and service-level based replenishment in RFID-enabled supply chain." International Journal of Production Research 48, no. 9 (March 18, 2010): 2655–77. http://dx.doi.org/10.1080/00207540903564983.

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Ryu, Chung-Suk. "Review of Collaborative Planning, Forecasting, and Replenishment as a Supply Chain Collaboration Program*." Journal of Distribution Science 12, no. 3 (March 30, 2014): 85–98. http://dx.doi.org/10.13106/jds.2014.vol12.no3.85.

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Mayur, R., and Baibhav Kumar. "Demand Forecasting of Spare Parts of Automobiles using Gaussian Support Vector Machine." IJOSTHE 6, no. 1 (February 10, 2019): 4. http://dx.doi.org/10.24113/ojssports.v7i1.114.

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Reordering motor vehicle spare parts for the purposes of stock replenishment is an important function of the parts manager in the typical motor dealership. Meaningful reordering requires a reliable forecast of the future demand for items. Production planning and control in remanufacturing are more complex than those in traditional manufacturing. Developing a reliable forecasting process is the first step for optimization of the overall planning process. In remanufacturing, forecasting the timing of demands is one of the critical issues. The current article presents the result of examining the effectiveness of demand forecasting by time series analysis in auto parts remanufacturing. A variety of alternative forecasting techniques were evaluated for this purpose with the aim of selecting one optimal technique to be implemented in an automatic reordering module of a real time computerized inventory management system.
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