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The Knowledge Factory is a metaphor to describe an accelerated learning organization. World‐class manufacturers are gearing every aspect of their business, from the shop floor to administrative offices, toward the rapid acquisition and deployment of knowledge. This article, based on an extensive research project to identify and interview best‐in‐class operations, provides conceptual guidelines and action steps for organizations striving to practice knowledge‐based competitiveness.

One strategic design parameter in capacity management is the setting of a planned level of capacity utilization at which the manufacturing operation will operate long term. Seeks to examine systematically the implications of varying levels of capacity utilization within an assemble‐to‐order firm through experiments with a simulation model. Four performance measures and a total weekly cost measure are analysed under nine capacity utilization levels, two demand patterns, and 11 ratios of the costs of idle capacity to the costs of late orders. The prescribed capacity utilization level is a function of the firm′s competitive goals, demand pattern, and cost structures.

Assessing the impact of a quality improvement intervention on an organization is particularly difficult in a high contact service operation where the intangible service encounter is the unit of output. Frequently, accounting or financial data must be used to evaluate the effectiveness of the intervention; however, these data may be problematic with respect to sample size and masking effects due to aggregation. Presents a systems model which describes metaphorically how an unstable process can continue to show no performance gains despite continued input of resources into improvement initiatives. A special type of Shewart control chart, known as the X‐chart, is developed as a methodology for assessing process performance after an improvement programme has been implemented. An X‐chart is used to analyse performance data collected in a real service setting where service quality standards were deployed in the front line phase of the operation. Although traditional analysis of variance concluded that there was no significant improvement in performance, the X‐chart indicates that real performance gains were occurring. The X‐chart provides management with an easy‐to‐use decision tool which can help assess the effectiveness of many different types of organizational change initiatives.

Manufacturers are in the midst of one of the most significant transformations in history. The kaleidoscopic nature of the global economy has created an environment of unprecedented hyper‐complexity and dynamic change. So much so that the rules of the competitive game are shifting faster than managers can react to them. Moreover, these dynamics bode continuous sea changes in work and sources of value‐added. Looking to past solutions for rationing resources and controlling costs is not an option. The drivers of change indicate one point: Successful manufacturers tomorrow will not look much like those of today.

This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities.

The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance.

The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs.

This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities.

The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings.

This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended.

Optimizing both qualitative and quantitative factors is a key challenge in solving construction finance decisions. The semi‐structured nature of construction finance optimization problems precludes conventional optimization techniques. With a desire to improve the performance of the canonical genetic algorithm (CGA) which is characterized by static crossover and mutation probability, and to provide contractors with a profit‐risk trade‐off curve and cash flow prediction, an adaptive genetic algorithm (AGA) model is developed. Ten projects being undertaken by a major construction firm in Hong Kong were used as case studies to evaluate the performance of the genetic algorithm (GA). The results of case study reveal that the AGA outperformed the CGA both in terms of its quality of solutions and the computational time required for a certain level of accuracy. The results also indicate that there is a potential for using the GA for modelling financial decisions should both quantitative and qualitative factors be optimized simultaneously.

The purpose of this paper is to examine how the location of a firm’s headquarters and component sourcing impact a firm’s responsiveness in a product-harm crisis in local market.

The authors collected data on 1,251 vehicle recalls from 12 manufacturers, six in the USA, three in Germany, and three in Japan. All of the recalls occurred in the USA between 2002 and 2010. The time the product was first released into the marketplace was used as the starting point while the time the recall was initiated (if at all) was used to record the probability of the product recall over time. Specifically, a survival analysis with an accelerated failure time model was employed to examine the speed with which a product is recalled. The authors examined the impact of foreign composition using information provided by the American Automobile Labeling Act, which lists the proportion of each vehicle that is composed of domestic parts (USA/Canada) and foreign parts. Organizational characteristics (i.e. size, market share, assets, net income, and reputation) and recall size (i.e. number of affected vehicles) that might have an effect on time to recall were controlled for.

The authors found that firms headquartered outside the local market would take longer to issue a product recall than firms that were headquartered in the local market. Firm headquartered outside the local market can reduce the time taken to recall by sourcing parts from the local marketplace, rather than from abroad. Interestingly, even local firms are affected by the location of component sourcing, such that they take longer to issue a recall if they sourced parts from abroad.

Research in international marketing has examined the benefits of integration to firms, but has not studied the risks of integration. By highlighting the challenges of managing institutional differences and integration difficulties, the authors show that location of headquarters and the location from where components are sourced have an effect on firm responsiveness in product-harm crises. Further, the authors build on the global supply chain management literature that has shown the effect of upstream activities (i.e. foreign production) on downstream activities (i.e. product quality). Specifically, the authors show that upstream activities can not only affect product quality, but also the ability of firms to respond to those product qualities in a timely fashion.

This paper outlines, using evidence from several case studies, the use of alternative forms of manufacturing strategy processes. Our investigation shows that the manufacturing strategy development practices of manufacturers are evolving in many directions; we found several alternatives to the formal top‐down planning process. Manufacturers use one or more of the following alternatives with or without the top‐down manufacturing strategy process: a coherent pattern of actions; manufacturing/process improvement programs; or the pursuit of core manufacturing capabilities. It appears that the various manufacturing strategy development processes may be tied to the strategic role of manufacturing in a company. This paper offers a framework that captures the relationship between the strategic role of manufacturing and the process of manufacturing strategy development. An in‐depth case from a UK company illustrates the evolving forms of manufacturing strategy development processes.

The paper's purpose is to investigate the direct and indirect effects of industry competitive forces on strategy‐making and performance in small‐to‐medium‐sized manufacturing companies.

The paper's approach is a survey design with structural equation modeling used for hypotheses testing.

The findings provide strong support for the mitigating role of managerial action through the strategy‐making process and indications that this is true regardless of small‐to‐medium‐sized enterprise (SME) size. Also, automotive‐manufacturing SMEs seem to exhibit higher levels of competitive factors compared with non‐automotive manufacturing SMEs.

The major limitation of this research is that the survey was taken in the Mid‐western USA and involved only SME manufacturing organizations. The research should be extended to other geographic regions, industry types, and larger organizations.

Many small company managers feel that they have little impact on industry‐wide macro‐economic and industry‐specific forces. This research indicates that managers in SMEs can mitigate some of the negative effects of industry competitive factors through strategy‐making activities.

This research is unique in several ways. It is the only research that has clearly identified and successfully measured the impact of managerial action in SMEs. It demonstrates that managerial action can be measured by comparing the direct and indirect effects of industry competitive forces on performance. It further identifies the need for a self‐assessment tool to measure the effectiveness of managerial action of top managers in SMEs.