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The vehicle development process (VDP) is iterative in nature with numerous interactions and information flows between design groups and between development phases. The VDP has been changed from a sequential‐functional development to a concurrent‐team based approach. Concurrent execution of design activities may reduce the development lead‐time, but it increases the managerial complexity in the VDP. A system dynamics model was developed to understand the transient behavior of parallel, overlap, and sequential processes in the VDP and to determine the optimal level of overlapping considering the development lead‐time and total number of reworks. The simulation results showed that different execution processes should be used, depending upon the intensity of reworks.

Concerns the nature of strategic capabilities from a network (rather than single‐firm) context. Augments what may be termed the predominantly structural and inward‐looking bias of much of the existing literature by integrating issues of network theory and organizational learning into the authors’ conceptual frames. Contends that this is necessary in order to understand more clearly the processes through which strategic development takes place, and especially to appreciate the sources of transformational change.

The purpose of this paper is to propose a methodology that determines vehicle-level specifications for new-car program by balancing market environments and engineering feasibility in the early stages of the vehicle development processes using statistical analysis of historical data.

The proposed methodology effectively captures the interplay among key factors in preliminary vehicle planning: engineering feasibility constraints, market demands, and economic conditions. Engineering design constraints, derived by statistical analysis of historical data, define the strategic feasible space. Within the defined design space, the methodology determines a set of specifications that maximize the customer utility which is built as a function of preferences on each attribute of a vehicle.

The present paper develops an “extrapolation” approach using historical vehicle data, rather than attempt to model a complex system with limited information. In doing so, the proposed approach avoids the difficulties of understanding an entire complex system by determining only the moderate level of specifications. Moreover, its quantification of revealed customer preferences as expressed in sales data resolves the confusions in vehicle planning arising from the translation of customer requirements to engineering specification.

The proposed methodology can provide feasible prediction values with a new, historical-data-based statistical approach that effectively surmounts the difficulty of mechanically understanding complex systems. Moreover, through quantification of the target market's customer requirements as well as effects of market-environmental changes, the methodology enables designers to plan complex products for new concept in objective and reasonable manner.

This paper aims to investigate car manufacturers’ constraints to innovate radically.

Automotive case study.

First, cultural constraints hold them back, for example, reflected in legacy power structures and failure aversion. Second, car manufacturers face cash constraints as they have to exploit their core business while exploring potential future profit pools. Third, talent gaps in digital and some non-digital areas are a challenge for incumbents while competing with digital-native firms such as Tesla.

This paper elevates a fragmented literature strand on constraints to innovate.

Although many knowledge management (KM) initiatives are known to miscarry, there has been relative little critical, in‐depth research into the causes of failure. In this paper, an action research (AR) project is described in a major motor manufacturer (WWM) focusing on one of their key knowledge processes (Design for Manufacturabilty) which was regarded as dysfunctional. The paper has two aims: to explore the substantive factors underlying this malaise, and to demonstrate how the rigour and respectability of AR as a research tool can be strengthened by the use of grounded theory (GT) methodology. Using the latter, a model was produced relating the effectiveness of the DFM process to a set of success factors. These factors resonate with key issues described in previous KM research, namely the need for a shared knowledge repository, a formal KM process, and a culture disposed towards knowledge sharing and re‐use. The model provided a rigorous platform for designing interventions to improve the DFM process. Whilst technical changes (creating infrastructure, defining process) are readily feasible, bringing about cultural change is less tractable and process improvements in WWM have tended to focus more on the former than the latter. As well as providing generalisable insights into KM success and failure, the paper also demonstrates the valuable role that GT can make in informing the design of organisational interventions, in evaluating their impact, and in adding rigour to the theory generation dimension of AR.

Digitalization is changing the assets, competencies, and value creation of the customer insight function. New data sources, methods, and technologies provide an unprecedented wealth of data and opportunity for efficiency. At the same time, it is leading to an evolution in necessary capabilities such as data synthesis, networking, and constant learning. Changes in the means of value creation have included automation of insights, more frequent evaluation of business results, and more emotional inspiration. Customer insights in the machine age drive customer centricity and go beyond the descriptive research function of previous “market research” within companies.

Attempts to answer the question: why are Japanese firms better at managing long‐term supplier relationships? Discusses the results from a three‐year research project that focuses on the way in which Japanese transplants and UK non‐Japanese‐owned vehicle manufacturers manage their relationships. The research attempts to define the concept of trust, by using existing academic models. Using the existing literature examines how Japanese and non‐Japanese‐owned (UK) manufacturers work with their first tier suppliers. The research is primarily qualitative due to the small sample size of non‐Japanese‐owned and Japanese vehicle manufacturers; however, the research does examine five vehicle manufacturers and 19 relationships. Concludes with the development of a conceptual model for mutually advantageous business relationships, which is an attempt to produce a workable inventory of trust for use by both customers and suppliers.

To identify QFD best practices and understand factors that contribute to successful QFD application.

A field research study is presented that summarises the use of QFD in a number of companies operating in Brazil. The paper reports multiple case studies conducted in organizations that have already achieved maturity in QFD implementation.

The study identified areas of QFD best practice such as the development of matrices and voice of customers, interaction with other organizational practices (e.g. TQC system and other methods and techniques), and less traditional QFD applications (concept definition, strategic planning, and developing a global product). The study also identifies QFD implementation success factors related to organizational characteristics (e.g. management support for QFD and cross‐functional involvement in QFD project), data sources (e.g. existing data sources and QFD‐driven data sources), and QFD tools and techniques such as use of advanced phases of quality deployment (e.g. development of different matrices, comprehensive QFD, integration of analytical techniques and QFD).

A useful source to be used by organizations that have been implementing QFD for product development or for those that plan to employ the method.

The paper offers practical and applied information on QFD implementation while identifying areas of best practice within a variety of situations. It will be useful for both academics and practitioners.

By definition, all organizations that survive as their environment evolves are learning, at least to some degree, but proposes that the learning capabilities of most organizations are extremely limited, especially when learning requires that diverse constituencies build shared understanding of dynamically complex business environments. As such, learning capabilities become increasingly needed, and those organizations which possess them will have unique advantages. Discovering how organizations might develop such learning capabilities represents a unique opportunity for partnership between researchers and practitioners. Suggests that to do this will require consensus about the research territory, research methods and goals, and how meaningful field projects can be designed and conducted.

The purpose of this paper is to investigate usage of fused deposition modeling (FDM)-based sheet metal tooling for small lot productions as a real case. FDM-based sheet metal tooling was used for stamping prototype parts for two different materials to evaluate dimensional conformance.

The experimental process of data capture used the following steps: sheet metal parts were stamped and optically scanned at every 10th interval for both DC04 and S355MC material. FDM-based upper and lower dies were optically scanned at 1st, 51st and 101st intervals. Dimensional conformance analyses were carried out by using scanned data to evaluate the behavior of FDM dies against DC04 and S355MC materials in terms of geometric deviation.

Satisfactory results were obtained for DC04 material by using FDM-based tooling, and overall deviation was at an acceptable level in terms of production tolerance. S355MC material is harder than DC04 and results were not convenient in terms of tolerance range. Geometric deviation of FDM dies was slightly increased and after the 50th part, increased drastically due to squeezing of FDM layers. Experiments showed that this method can be used for DC04 material and up to 100 parts can be stamped within the tolerance range. Using FDM-based sheet metal tooling, product development phase can be shortened in terms of leading time.

This paper presents a study to create an alternative tooling method to shorten product cycle and product development phase by integrating rapid tooling methods to low-volume production.