Collaborative Demand Forecasting: Toward the Design of an Exception-Based Forecasting Mechanism

Abstract

Yan Dong is an assistant professor of supply chain management at the Darla Moore School of Business, university of South Carolina. He also taught at the Robert H. Smith School of Business, university of Maryland, and the Carlson School of Management, university of Minnesota. He was a supply chain management consultant for IBM global Services. His research interests include supply chain contracts, supply chain governance and relationships, and quality management in supply chains. His work has appeared in journals such as Management Science, Production and Operations Management, Journal of Operations Management, Information Technology and Management, and Decision Sciences.Xiaowen Huang is the Endres Associate Professor Fellow and Miami university Distinguished Scholar at the Richard T. Farmer School of Business, Miami university. Her research interest primarily revolves around understanding how companies can effectively deploy their supply chain, technology, and operations strategy to achieve competitive advantage.

Information sharing for sales and operations planning: Contextualized solutions and mechanisms

“…Based on case studies, Alftan et al. (2015) and Dong et al. (2014b) emphasize that collaborative demand forecasting is needed as an exception management mechanism.…”

What modelling research on supply chain collaboration informs us? Identifying key themes and future directions through a literature review

“…CPFR, on the other hand, is relatively new in SCC, issued by the Voluntary Interindustry Commerce Standards (VICS), under which both buyer and seller collaborate by correcting, adjusting, and proposing prices and quantities to agree on a unique forecast, that coincides buyer's purchase forecast and the seller's sales forecast (Caridi, Cigolini, and De Marco 2005). Among the studies, Panahifar, Byrne, and Heavey (2014) have highlighted the benefits and deficiencies of CPFR, while Caridi, Cigolini, and De Marco (2005) and Dong et al (2014b) have emphasised the implementation and development of CPFR model for improving supply chain performance by using intelligent agents or incentive-based contracts. Few studies focused on both VMI and CPFR, e.g.…”

<b>The importance of trust and collaboration between companies to mitigate the bullwhip effect in supply chain management

“…It implies the ability to break old habits and try to put forward new ideas. According to Daugherty et al (2006) and Dong et al (2014), if each partner trusts the other one in inter-organizational collaboration, initiatives and practices of SCM such as CPFR and VMI will bring benefits for the SC (Figure 4). Production, demand forecasting, and replenishment products…”

“…Bray & Mendelson (2012), Trapero, Korentzes, & Fildes (2012), Li (2013), Sari (2015), Barkataki & Zeineddine (2015) 2. Improved demand forecasting Wright & Yuan (2008), Ali, Boylan, & Syntetos (2012), Trapero et al (2012), Dong et al (2014), Sari (2015), Xu, Dong, &Xia (2015), Nagashima et al (2015) 3. Replenishment policy Lee & Wu (2006), Jaksic & Rusjan (2008), Su & Wong (2008), Kelepouris, Miliots, & Pramatari (2008), Dong et al(2014) VMI Disney & Towill (2003) Relationships between trust, collaboration, and BWE Some studies consider trust as a defining characteristic of the presence of collaboration among members of a SC (Vieira et al, 2009).…”

“…According to Dong, Huang, Sinha, & Xu (2014), central to Collaborative Planning, Forecasting, and Replenishment (CPFR) is Collaborative Demand Forecasting (CDF) that allows SC partners to share private demand information, and incorporate the jointly derived demand forecast into production planning and product replenishment decisions. A systematic literature review (SLR), by Almeida, Marins, Pedro, Santos and Silva (2015), has only found isolated studies on BWE, trust and collaboration in SC, and strategic SCM, which leads to the need for these concepts to be addressed in an integrated way.…”