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Speed is now a key competitive factor in industry. Responsiveness is a significant component, which can create speed in a system. In the author's previous research four groups of industries were identified with respect to responsiveness characteristics – off‐the‐shelf, safety stock, assembler and customizer. This paper focuses on one industrial sector within the off‐the‐shelf class – the food industry in Thailand – to study responsiveness in depth. A survey was conducted investigating critical areas for performance measurement with respect to responsiveness. A more precise set of critical areas for responsiveness were obtained. The results highlight the importance of planning, sourcing and inventory areas in this sector. Then an in‐depth interview was conducted in 11 case studies. Those three areas identified in the survey were investigated. It was found that there are three methods of creating responsiveness responding by production plan adjustment to customer; responding by production plan adjustment to raw material available level; and responding by providing raw material. Thus, according to the three responding methods, a framework for responsiveness assessment was developed. It also implies that nature of industry, types of stimuli and raw material significantly influence the areas for creating ability to respond.

Identifies the need for a formal procedure to generate a reference state when conducting qualitative simulation studies. A procedure for generating a reference state is presented and justified. The procedure considers output performance indicators, steady state conditions, system capacity and model validity. Its application is illustrated using a simulation model for an order fulfillment process. The calibration process is necessarily iterative and subjective to some degree and in general does not generate a unique reference state. The impact of using different reference states in a simulation experiment is illustrated. In general the results are consistent when interpreted qualitatively in terms of direction, trend and order of magnitude. The approach is most applicable for qualitative simulation studies where comparative performance is being investigated and where precise numerical estimation is not required. However the procedure is also applicable to the study of real systems where data is not available.

In transportation and distribution systems, the shipment decisions, fleet capacity, and storage capacity are interrelated in a complex way, especially when the authors take into account uncertainty of the demand rate and shipment lead time. While shipment planning is tactical or operational in nature, increasing storage capacity often requires top management’s authority. The purpose of this paper is to present a new method to integrate both operational and strategic decision parameters, namely shipment planning and storage capacity decision under uncertainty. The ultimate goal is to provide a near optimal solution that leads to a striking balance between the total logistics costs and product availability, critical in maritime logistics of bulk shipment of commodity items.

The authors use simulation as research method. The authors develop a simulation model to investigate the effects of various factors on costs and service levels of a distribution system. The model mimics the transportation and distribution problems of bulk cement in a major cement company in Indonesia consisting of a silo at the port of origin, two silos at two ports of destination, and a number of ships that transport the bulk cement. The authors develop a number of “what-if” scenarios by varying the storage capacity at the port of origin as well as at the ports of destinations, number of ships operated, operating hours of ports, and dispatching rules for the ships. Each scenario is evaluated in terms of costs and service level. A full factorial experiment has been conducted and analysis of variance has been used to analyze the results.

The results suggest that the number of ships deployed, silo capacity, working hours of ports, and the dispatching rules of ships significantly affect both total costs and service level. Interestingly, operating fewer ships enables the company to achieve almost the same service level and gaining substantial cost savings if constraints in other part of the system are alleviated, i.e., storage capacities and working hours of ports are extended.

Cost is a competitive factor for bulk items like cement, and thus the proposed scenarios could be implemented by the company to substantially reduce the transportation and distribution costs. Alleviating storage capacity constraint is obviously an idea that needs to be considered when optimizing shipment planning alone could not give significant improvements.

Existing research has so far focussed on the optimization of shipment planning/scheduling, and considers shipment planning/scheduling as the objective function while treating the storage capacity as constraints. The simulation model enables “what-if” analyses to be performed and has overcome the difficulties and impracticalities of analytical methods especially when the system incorporates stochastic variables exhibited in the case example. The use of efficient frontier analysis for analyzing the simulation results is a novel idea which has been proven to be effective in screening non-dominated solutions. This has provided the authors with near optimal solutions to trade-off logistics costs and service levels (availability), with minimal experimentation times.

This paper discusses evidence from field studies undertaken to investigate the responsiveness of the order fulfilment process in a number of companies. The evidence is analysed in the context of the literature on responsiveness and related areas such as time‐based competition. Similarities and differences are analysed across a number of industrial sectors with respect to order fulfilment processes and the interpretation and significance of responsiveness. Generic factors that influence different types of companies are identified. Four components of responsiveness – stimuli, awareness, capabilities and goals – emerge from an analysis of the literature. The field and case study evidence allows the development of more precise definitions and descriptions of each of these components. The study also allows a generic responsiveness framework to be developed that incorporates both strategic and operational viewpoints. The need for more field studies on responsiveness is noted. More work is advocated on the assessment and measurement of responsiveness and on developing appropriate responsiveness interventions, particularly with respect to the order fulfilment process.