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An automated sheet‐metal manufacturing systems for low‐volume production utilises an industrial robot to move blanks from a store to a press brake.

The purpose of this paper is to explore the entrepreneurial and policy consequences of the structural changes associated with postindustrialization.

The approach uses Schumpeterian and institutional theories to predict the consequences of postindustrialization on four types of innovative markets: global mass markets; global niche markets; local mass markets and local niche markets.

The paper makes two key predictions. First, global mass markets will account for most cost-cutting process innovations. Second, niche markets, whether global or local, will provide the bulk of product innovations. Opportunities for product innovations in niche markets multiply both as the result of a more complex economy and as the result of heterogeneous preferences of consumers with divergent learning trajectories.

The key implication of the theoretical pattern prediction of this paper is that there are increasing opportunities for entrepreneurs to introduce novelties that cater to niche demands, and this includes new lifestyle communities. The increasing diversity of values and preferences implies that one-size-fit-all policies are becoming increasingly inimical to the entrepreneurial discovery of higher-valued resource uses.

This paper takes a standard prediction of entrepreneurial theories – that innovations become more common with an increase in economy-wide product complexity – and extends this to increasing complexity on the consumption side. With increases in opportunities for learning, consumers diverge and develop disparate lifestyles. The resultant super-diversity, which multiplies consumption niches to a much greater extent than what ethnicity-based diversity indices would imply, makes it more difficult to achieve consensus about the desirability of public policies.

Examines the potential for introducing automation processes including robots into the construction industry. Outlines some of the problems to be tackled including the technical and organisational problems of site layouts and the role of automation and robotics in construction. Looks at the advantages of using task‐specific robots and the development of mechatronics. Emphasizes the need for the development of CAD in architecture and construction as autonomous robotic machines require appropriate design description of a building to make available the necessary information about the developing building geometry on the construction site.

Many bike rental organizations permit customers to pick-up bikes from one bike station and return them at a different one. However, this service may result in bike imbalance, as bikes may accumulate in stations with low demand. To overcome the imbalance problem, this paper aims to develop a decision model to minimize the total costs of unmet demand and empty bike transport by determining bike fleet size, deployments and the vehicle routing schedule for bike transports.

This paper developed a constrained mixed-integer programming model to deal with this bike imbalance problem. The proposed model belongs to the non-deterministic polynomial-time (NP)-hard problem. This paper developed a two-phase heuristic approach to solve the model. In Phase 1, the approach determines fleet size, deployment level and the number of satisfied demands. In Phase 2, the approach determines the routing schedule for bike transfers.

Computational results show the following results that the proposed approach performs better than General Algebraic Modeling System (GAMS) in terms of solution quality, regardless of problem size. The objective values and the fleet size of rental bikes allocated increase as the number of rental stations increases. The cost of transportation is not directly proportional to the number of bike stations.

The authors provide an integrated model to simultaneously deal with the problems of fleet sizing, empty-resource repositioning and vehicle routing for bike transfer in multiple-station systems, and they also present an algorithm that can be applied to large-scale problems which cannot be solved by the well-known commercial software, GAMS/CPLEX.

Engineer-to-order (ETO) supply chains involve multiple companies for performing complex projects. The ability to effectively coordinate cross-business activities is essential to avoid delays, cost overruns and quality problems. Coordination is related to a number of contingent factors that need to be better comprehended. The purpose of this paper is to highlight such contingent factors and to analyse their effect on the occurrence of project delays.

A multiple case study is used to investigate the moderating factors affecting coordination in projects carried out in an ETO supply chain. Such factors are examined through a cross-analysis of six shipbuilding projects based on data from interviews, project documentation and clips from the media press.

In ETO supply chains, the engineering and production activities involve mutual interdependences that need to be coordinated. The findings suggest that both the integration of engineering and production and the production capability are the most critical factors influencing coordination in an ETO supply chain.

The study was carried out within shipbuilding projects as a setting to represent the ETO domain. To extend the findings, further research can examine other types of projects, such as: oil and gas, construction, military and aerospace.

In practice, there is no “one-fits-all” solution for coordination. Each project represents a unique context which has specific objectives, actors and constraints. From that perspective, this study provides a basis to comprehend coordination in a complex setting.

This study builds knowledge upon coordination by generating a number of propositions regarding the effectiveness of coordination on avoiding delays in complex projects carried out in ETO supply chains. Focusing on the engineering and production activities, the authors extend the existing theory by demonstrating that coordination can vary according to the level of several moderating factors.

The customer enquiry management (CEM) process is of strategic importance in engineer‐to‐order contexts but existing literature does not adequately describe how firms support delivery date setting and order acceptance decisions in practice. This paper seeks to explore how and why the CEM process varies between companies in the capital goods sector, thereby taking a contingency theory approach.

Multi‐case study research involving 18 Italian capital goods manufacturers in four industrial sectors. Face‐to‐face interviews with senior representatives have been conducted. Companies have been grouped into five clusters, based on similarities in their CEM decision‐making modes, to aid analysis.

Three contingency factors were found to be particularly relevant in determining CEM modes: degree of product customization, flexibility of the production system, and uncertainty of the context. These factors affect the choice of specific CEM decision‐making modes. However, a high level of cross‐functional coordination and formalization of the process were found to constitute best practices whatever the contingency factors.

The research focuses on companies belonging to the Italian capital goods sector – findings may differ in other countries and sectors.

The results indicate that all firms, including small and medium‐sized companies, should implement high levels of cross‐functional coordination and formalization in their CEM practices, in order to improve their performance. For other aspects of the CEM process, including supplier and subcontractor monitoring, the company context will indicate whether these aspects are required, according to a need of matching the approach to CEM with specific sets of contingency factors.

This paper provides a rare insight into the CEM processes found in practice.

Generative Production Systems are generative design computation that is linked to optimal physical production. They can improve the design and production of products which have unique geometries. The purpose of this paper is to introduce a preliminary methodology for Generative Production Systems.

The paper takes the form of a literature review investigating the structures and formats of successful methodologies. The literature review also investigates Generative Production Systems' theoretical foundations, development and implementations.

The potential of Generative Production Systems is restricted because enabling information is fragmented and difficult to access. In other fields, such barriers have been overcome through the introduction of methodologies that provide guiding principles, rules and strategies (P‐R‐S). The P‐R‐S type of methodology structure is suitable for Generative Production Systems.

The use of Generative Production Systems requires more upfront investment than the use of CAD/CAM software packages. However, they require little, or no, human input after they are set‐up. The preliminary methodology provides structured guidance about how to set up a Generative Production System. Further, the explanatory text enables wider understanding of Generative Production Systems, and how they can improve design and production.

An analysis is provided for the structure and format of successful methodologies in general. A preliminary methodology for Generative Production Systems is introduced. Further, the paper provides an overview of the disadvantages and advantages of Generative Production Systems compared to typical CAD/CAM software packages.

This paper seeks to examine the way quality management practices (QMPs) impact quality outcome, R&D process, and business performance, using investigation data from Chinese firms. The possible moderating effects of industrial types and competition on the above influencing relationships were investigated as well.

A two‐round questionnaire survey was conducted to 196 manufacturing and service firms in West China, and hypotheses were verified using a structural equation model with LISREL software.

The results suggest that quality management practices do not have a positive impact on firms' business performance directly, but have an indirect impact on business performance mediated by quality performance and R&D performance. Furthermore, the authors find that industrial type can moderate the relationships between quality management practices and business performance, while competition does not.

The findings make a significant contribution to understanding how QMPs impact firms' performance. In addition, the authors' research provides empirical evidence for the fact that QMPs' contribution to firms' financial and marketing performance is greater in service firms, which partly reflects the actual situation in China and other similar developing countries.

Drum-Buffer-Rope (DBR) is a method to adjust production flows, synchronize the release of materials and enable a process of focused improvement in production systems. Literature on DBR applications in engineer-to-order (ETO) production systems, where customers participate in product design decisions and, consequently, in the way production is planned and executed, is rare. However, the interest in improving production management in ETO systems has received attention from the scientific and business communities. The goal of this research was to evaluate the implementation of DBR in an ETO productive system, critically analyzing the necessary adaptations for its use.

This research was conducted through a case study in a company that manufactures electronic equipment, known as avionics, in the aerospace sector.

In this context, the contribution of this study consists of evaluation of the implementation of DBR in an ETO productive system, describing the implementation and the necessary adaptations of the DBR to the ETO productive system explored, comparing it with the DBR theoretical proposals and Simplified Drum-Buffer-Rope (S-DBR) methods.

The study contributes to knowledge by expanding the field of the DBR application to make it more precise, and by applying the theory of constraints, in a general manner, to this type of productive environment.

The purpose of this paper is to demonstrate the application of vendor rationalization strategy for streamlining the supplies and manufacturing cycle time reduction in an Indian engineer-to-order (ETO) company. ETO firms are known for a large number of vendors, co-ordination hassles, rework problems and its impact on cycle time and operational excellence.

The research demonstrates the case-based application of Kraljic’s matrix for supply and leverages items, on-the-job observations, field visits, discussions and analysis of supplies reports.

The study guides on the rationalization of supplies and the necessary strategic alignments that can significantly reduce supply risk, costs, manufacturing and delivery cycle time along with co-ordination hassles. The study depicts the challenges of ETO environment with respect to supplies, and demonstrates the effectiveness of vendor rationalization application for the case company and weaknesses of commonly practiced vendor management approaches.

To be competitive, companies should rationalize supply items and vendors based on the nature of items and their subsequent usage by applying Kraljic’s matrix-based classification. The immediate implication of vendor rationalization is misunderstood as reducing supply base, but it does much more and includes review of supplies, nature of items and strategic alignments, leading to win-win situation for company and suppliers.

For the rationalization of supplies, while procuring and dealing with vendors, executives should envisage engineering nature of components, considering cross-functional requirements and integration of components in context to ETO products/projects environments. There is a dearth of studies focusing on vendor rationalization aspects in ETO setups in fast-developing country context.