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Supply chains can improve their performance by developing competitive priorities in a specified sequence: quality, reliability, flexibility, agility, and finally, cost efficiency. This paper extends Ferdows and De Meyer's (1990) sand cone model and Vokurka and Fliedner's (1998) sand cone model extension incorporating agility to supply chain management priorities. This work provides a framework for a cumulative and sustainable improvement process by which supply chains can build a strategic competitive advantage.

Today, to improve productivity in manufacturing, one has a large variety of improvement programmes at one′s disposal. Zero defects, value analysis, just‐in‐time, manufacturing lead time reduction are just a few of a long list of potential action programmes. Their real impact is not always clearly described, and manufacturing managers often have to start implementation on a basis of belief. In this article we use the database of the European Manufacturing Futures Survey to explore some of the medium‐term effects of these improvement programmes on manufacturing performance. The conclusions show that there are no simple cause‐effect relationships between single improvement programmes and manufacturing performance. Tenacity in implementation is required since some programmes have negative effects in the short term, but can have positive effects in the long term.

The purpose of using an adaptive meshing strategy is to define the problem well with as few nodes as possible. The extent to which the discrete system adequately represents the problem being solved depends on the positioning of the grid points. It is the intention to show here that adding badly placed nodes to the region of interest in a mesh can reduce the accuracy of the resulting solution. A practical refinement strategy is presented where such problems are avoided.

In the Numerical Analysis of Semiconductor Devices a lot of problems arise in the fields of numerical analysis, semiconductor physics, technology and device electronics. Indicating what the problems are and which tools could be used was the main objective of the Short Course held in association with the NASECODE II Conference. The Lecture Notes of this Short Course are contained in and the Proceedings of the NASECODE II Conference in.

The purpose of this paper is to test the cumulative capabilities theory of manufacturing strategy against the capabilities tradeoffs theory in a less‐developed economy. It also aims to test whether the sequential development of capabilities follows the same order prescribed in the sand cone model.

Specific hypotheses on the relationships among the four manufacturing strategy components of cost, delivery, flexibility, and quality were stated. Data were collected from 126 manufacturing firms in Ghana. Statistical analyses included correlation, factor analysis, and multiple regression analysis.

As with previous studies, the evidence here supports the cumulative capabilities theory. However, tradeoffs between the capabilities of quality, cost, delivery, and flexibility were not found. In addition, the sequence of capability development was found to be different from that in developed economies, with cost being second in importance after quality. This is postulated to be due to the substantially different economic conditions in Ghana.

The findings of this research provide guidelines to managers, particularly in developing economies, on the sequence of manufacturing capability development that is most likely to occur as they seek lasting improvements in manufacturing performance.

This paper provides findings from a less‐developed economic environment that is typically not included in manufacturing strategy research – Ghana. The consistency of the results with those obtained in more advanced economies provides additional evidence for the cumulative capability model.

Historically, US firms have increased production volumes to gain economies of scale and operating efficiencies. Quality, dependability, and flexibility have more recently become competitive weapons. In today’s dynamic, global marketplace, some have suggested that the next competitive dimension will be agility. Current research suggests cumulative and lasting improvements of strategic capabilities can be achieved if they are developed in a specific sequence. This paper reviews the historical competitive environment and changes in strategic responses; reviews relevant research on competitive capabilities and suggested trade‐offs in these capabilities; and offers a model which suggests how firms may build cumulative and lasting improvements in strategic competitive capabilities including agility.

This paper presents a new discretization technique of the hydrodynamic energy balance model based on a finite‐element formulation. The concept of heat source lumping is introduced, and the thermal conductivity model includes the effect of varying both carrier concentrations and temperatures. The energy balance equation is formulated to account for kinetic energy as a convective flow. The new discretization method has the advantage that it allows for assembling the functions out of elementary variables available over elements instead of along element links. Therefore, theoretically, calculation of the Jacobian should be three times faster than by the classic method. Results are given for three examples. The method suffers from mathematical instabilities, but provides a good basis for future work to solve these problems.

The purpose of this paper is to test the integrated model of operations strategy as proposed by Schmenner and Swink to explain whether firms trade‐off or accumulate capabilities, taking into account their positions relative to their asset and operating frontiers.

The four major airlines based in Australia were studied. The paper is based on longitudinal data obtained from secondary sources. The four operations capabilities cost, quality, delivery and flexibility, and asset and operating frontiers, were all measured with proxy variables.

The study provides some support for the integrated model. Firms do appear to trade‐off capabilities when their asset and operating frontiers are close to each other. Firms show signs of accumulation when the asset frontiers are expanding significantly over time. There is indirect evidence that firms could be accumulating capabilities when the gap between the two frontiers is large.

The study provides insights into when firms trade‐off or accumulate capabilities. A good understanding of asset and operating frontiers is important in this regard. Managers need to better identify, establish and combine their firms' capabilities in response to varying internal and external contingencies.

The paper provides an original and detailed empirical validation of Schmenner and Swink's integrated model. In doing so, this study contributes to informing and clarifying the debate in the operations strategy area relating to the circumstances in which firms trade‐off and/or accumulate capabilities.

The purpose of this paper is to present and test a new model for competitive capabilities. Traditionally, a cumulative model has been viewed as having one sequence of building competitive capabilities in a firm in support of market needs, including quality, delivery, cost efficiency and flexibility. Although appealing as a conceptual model, empirical testing has not been able to fully support the cumulative model. This paper acknowledges the need for a hybrid approach to managing capability progression. It brings together the literature on trade‐offs, cumulative capabilities, and order winners and qualifiers.

A new hybrid approach for modelling competitive capabilities is tested empirically using data from the high performance manufacturing (HPM) study, round 3, including three industries and seven countries – a total of 211 plants.

The hybrid model shows significantly better fit with the data from the sample than the cumulative models suggested by previous literature. Empirical support is found for the traditional perception that a high level of quality is a prerequisite for a high level of delivery performance. However, cost efficiency and flexibility do not exhibit a cumulative pattern. Instead, the results show that they are developed in parallel. The findings suggest that a balance between cost efficiency and flexibility is built upon high levels of quality and delivery performance.

Since we limit the empirical investigation to three industries and seven countries, it would be interesting to extend the testing of this model to more industries and countries. This research shows that combining perspectives and insights from different research streams – in this case, trade‐off theory and the concepts of cumulative capabilities, and order winners and qualifiers – can be fruitful.

The results of this paper provides managers with guidelines concerning the configuration of competitive capabilities. First, a qualifying level of quality needs to be attained, followed by a qualifying level of delivery. Then, a balance between potential order winners, i.e. cost efficiency and flexibility, needs to be attained.

This paper presents a new approach to modelling competitive capabilities that synthesises previous research streams and perspectives from cumulative capabilities, contesting capabilities (trade‐offs), and order winners and qualifiers.