The focus of this empirical investigation is twofold. First, an examination of formal hierarchical forecasting system structural parameters is reported. Four formal experimental factors used to define the hierarchical forecasting system are examined. These factors are evaluated in a controlled comparison by means of parametric statistical analysis. Second, a comparative analysis of formal hierarchical forecasting system performance with (1) an informal hierarchical strategy, and (2) a traditional forecasting approach is presented. The best performing combination of factor level settings identified in the examination of formal hierarchical forecast strategies is subsequently evaluated in the second part of this analysis by means of paired difference comparisons with (1) a randomized, informal approach, and (2) a common forecast strategy over the same time series data. Traditional measures of forecast accuracy are used as dependent performance criteria. 0272-6963/95/$09.50

Coordinated replenishment problems are common in manufacturing and distribution when a family of items shares a common production line, supplier, or a mode of transportation. In these situations the coordination of shared, and often limited, resources across items is economically attractive. This paper describes a mixed-integer programming formulation and Lagrangian relaxation solution procedure for the single-family coordinated capacitated lot-sizing problem with dynamic demand. The problem extends both the multi-item capacitated dynamic demand lot-sizing problem and the uncapacitated coordinated dynamic demand lot-sizing problem. We provide the results of computational experiments investigating the mathematical properties of the formulation and the performance of the Lagrangian procedures. The results indicate the superiority of the dual-based heuristic over linear programming-based approaches to the problem. The quality of the Lagrangian heuristic solution improved in most instances with increases in problem size. Heuristic solutions averaged 2.52% above optimal. The procedures were applied to an industry test problem yielding a 22.5% reduction in total costs.

The Problem The gap between research and practice has been recognized and analyzed across multiple fields. Various solutions have been proposed but the gap persists. Although there are consistent calls for joint actions through collaborations between scholars and practitioners, not many in either party have taken it as their primary responsibilities. Thus, incremental or suboptimal efforts have been made to bridge the great divide. The Solution In this article, we propose forming a new entity—intermediary—as an effective approach to transforming research into practice. Also, we share a real-world case to illustrate how this approach and its outcome can contribute to closing the research-practice divide. The Stakeholders Three stakeholders will benefit from this research—scholars, practitioners, and intermediaries. Both scholars and practitioners will better understand the transformation process and various ways to close research-practice divide. Intermediaries will have a better knowledge about how their contributions, skills and motivations are different from other two stakeholders.

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