Purpose -To propose and test an augmented collaborative planning, forecasting, and replenishment (A-CPFR) model in a retailer-supplier context with a view to improving forecasting accuracy and then reducing the "bullwhip effect" in the supply chain. Design/methodology/approach -After a literature review, the paper presents a real case in which the present authors provided assistance. The description of the case includes: case company background; an "as-is" model analysis; a "to-be" (CPFR) model analysis; and a description of the results and potential benefits. The paper then proposes an A-CPFR model for the case and performs a simulation of the new model for comparison with the existing CPFR model. Findings -The results show that the mean absolute deviation of forecasting and the inventory variance are both better in the proposed model than in the existing CPFR model. The proposed model can thus improve the accuracy of sales forecasting, reduce inventory levels, and reduce the "bullwhip effect". Practical implications -In addition to information provided by the retailer, a logistics supplier should also obtain competitors' promotional information from the market as another factor for forecasting -thus enabling timely responses to demand fluctuations. Originality/value -The proposed model is an original and useful development on the existing CPFR model. It could become a reference model for the retail industry in implementing CPFR in the future.
PurposeTo present a three‐layer hierarchical structure of the factors involved in adopting an electronic marketplace (EM) model and to examine the relative weightings given to various strategic factors by the securities industry (SI) and the heavy electric machinery industry in Taiwan.Design/methodology/approachA literature review and a review of nine Taiwanese industries allow the formulation of a three‐layer hierarchical structure of adoption factors. A fuzzy analytic hierarchical process (AHP) is then undertaken to ascertain the relative weightings of factors that affect entry to an EM in two of these industries which are studied in more detail.FindingsThe weights of “proactive” factors are found to be greater than those of “defensive” factors. For example, contrary to previous findings in this area, the “risk of adopting new technology” is not found to be the major factor influencing decision making. Various factors are found to have different routes of influence in determining decision making in different industries.Practical implicationsEnterprises that appreciate the weightings of factors to be considered will be able to facilitate the adoption of an EM model with lower costs and greater efficiency.Originality/valueThe study provides novel and reliable information about strategic factors that are involved in corporate decisions about entering an EM.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.