The Effect of Collaborative Forecasting on Supply Chain Performance

By Yossi Aviv. Management Sciences, 2001

588 citations recorded by the source corpus.

Subfields: Management Information Systems, Management Science and Operations Research, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/67794d1a8ab88a2e5e647ef621f78bf5c8ef44d6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Information Systems

In Management Science and Operations Research

In Strategy and Management

Citations in the corpus

Trust and Information Sharing in Supply Chains (2012, background): “Aviv (2001) compared a " local forecasting " supply chain, in which the manufacturer and the retailer maintain separate forecasts, with a " collaborative forecasting " supply chain, in which the manufacturer and the retailer join their forecasting efforts.”
Information Sharing, Buyer-Supplier Relationships and Firm Performance: A Multi-Region Analysis (2008, background): “This in turn facilitates improvements in quality, and other measures of performance ( Aviv, 2001”
In Search of the Bullwhip Effect (2007, background): “Additional work on the impact of correlated demand on supply chain variability is found in Aviv (2001,2002,2003), Guar, Giloni and Seshadri (2005) and Raghunathan (2001).”
Retailer Information Sharing with Supplier Encroachment (2018, unknown): “Our study belongs to the vast literature on information sharing in supply chains (see, e.g., Aviv 2001, Cachon and Fisher 2000, Guo 2009, Jiang et al. 2016, Kong et al. 2013, Li and Zhang 2008, Shamir and Shin 2016, Shang et al. 2016).”
Models for Supply Chains in E-Business (2003, background): “Aviv (2001) studies a two-stage two-player cooperative supply chain.”
A Trade Credit Model with Asymmetric Competing Retailers (2018, methodology): “Following Aviv (2001), we assume each demand follows a normal distribution, with l i = 100 and r i = 30.”
Trust in Forecast Information Sharing (2011, background): “2000, Aviv 2003), or have no trust and do not cooperate at all (e.g., Cachon and Lariviere 2001, Özer and Wei 2006). Rejecting Theorem 1 in favor of Hypotheses 1–3 suggests that people show some level of trust and cooperate to some extent when sharing forecast information. However, supporting these ”
Demand Forecast Sharing in Supply Chains (2009, background): “…sharing by assuming price and demand to be exogenous, and, consequently, it did not address the strategic role forecasts play in pricing (e.g., Aviv 2001, 2002a, Bourland et al. 1996, Cachon and Fisher 2000, Gaur et al. 2005, Gavirneni 2002, Gavirneni et al. 1999, Lee et al. 2000, Raghunathan…”
All You Need Is Trust? An Examination of Inter‐organizational Supply Chain Projects (2015, methodology): “Under such an agreement, a retailer shares his point of sales information with an upstream supply chain member who optimizes her own production and replenishment decisions using the retailer’s point of sales data (Aviv 2001, Lee et al. 1997).”
Customer‐Base Concentration and Inventory Efficiencies: Evidence from the Manufacturing Sector (2016, background): “One such practice is collaborative planning, forecasting, and replenishment (CPFR), which is a set of technology-enabled standards that provides a roadmap for enabling collaborative demand and supply planning and execution processes (e.g., Aviv 2001).”
Impact of eBusiness technologies on operational performance: The role of production information integration in the supply chain (2007, background): “Examples include jointly developing demand forecasting (Koloczyc, 1998; Aviv, 2001) and vendor-managed inventory (VMI), also referred to as direct shipment or automatic replenishment (Buzzell and Ortmeyer, 1995; Cetinkaya and Lee, 2000; Kulp et al.”