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The purpose of this paper is to propose a three-staged approach to configuration change management that uses a combination of complexity analysis, data visualization, and algorithmic validation to assist in validating configuration changes.

In order to accomplish the above purpose, the authors conducted a review of existing configuration management practices. This was followed by an in-depth case study of the configuration management practices of a major automotive OEM. The primary means of data collection for the case study were interviews, ethnographic study, and document analysis. Based on the results of the case study, a set of support tools is proposed to assist in the configuration management process.

Through the case study, the authors identified that the OEM used a configuration management method that largely represented the rule-based reasoning methods identified in the literature review. In addition, many of the associated challenges are present, primarily, the difficulty in making changes to the rule system and evaluating the changes.

The primary limitation is that the case study was based on a single OEM. However, the results are in line with other practices identified in the literature review. Therefore, it is expected that the findings and recommendations should hold true in other applications.

A set of configuration management tools and associated requirements are identified and defined that could be used to assist companies in the automotive industry, and perhaps others, in managing their option changes as they continue to move towards full mass customization of products.

The proposed approach for configuration management has not been seen in any other organization. The value of this paper is in the effectiveness of the proposed approach in assisting in the configuration change management process.

The purpose of this research paper is to discuss cellular manufacturing is discussed under conditions of changing product demand. Traditional cell formation procedures ignore any changes in demand over time from product redesign and other factors. However given that in today's business environment, product life cycles are short, a framework is proposed that creates a multi‐period cellular layout plan including cell redesign where appropriate.

The framework is illustrated using a two‐stage procedure based on the generalized machine assignment problem and dynamic programming. This framework is conceptually compared to virtual cell manufacturing, which is useful when there is uncertainty in demand rather than anticipated changes in demand. A case study is used to explain how the concept would work in practice.

One major characteristic of the proposed method is that it is flexible enough to incorporate existing cell formation procedures. It is shown through an example problem that the proposed two‐stage method is better than undergoing ad hoc layout changes or ignoring the demand changes when shifting or cell rearrangement costs exist. It also sheds some insight into cellular manufacturing under dynamic conditions.

This paper should be useful to both researchers and practitioners who deal with demand changes in cellular manufacturing.

This research aims to analyze the potential of revenue management in the German car industry. The concept offers the chance for original equipment manufacturers (OEMs) to be more customer‐oriented to reduce costs and increase earnings. To implement revenue management, criteria are required to segment the customers. The car configuration changes and the delivery time look suitable in this context and this paper aims to analyze these.

Survey analysis was conducted with 2974 German buyers of new cars. The respondents recently bought a car or were in the planning process of doing so. A total of 803 data sets could be evaluated statistically using SPSS software. Descriptive statistics and mean test were utilized to test several hypotheses and find out distinctions between the respondents.

The results show that German car buyers could be segmented in to different groups according to the criteria: delivery time and configuration changes. This enables manufacturers to introduce revenue management and realize benefits in better customer orientation and improved supply chain planning.

This research shows that German OEMs, especially the premium OEMs overestimate the value of change flexibility and short delivery times for their customers. The implementation of revenue management could help to reduce complexity and offer each customer the appropriate degree of change flexibility and the optimal delivery time combined with a process‐ and effort‐adequate pricing.

The paper aims to address the question of how and how often companies change their manufacturing strategy in the medium and long run, thus addressing a lack of evidence in the literature.

This paper explores the movements made by companies among four manufacturing strategy configurations drawn from the literature (market‐based, product‐based, capability‐based and price‐based configuration). Analyses are based on three longitudinal samples from the International Manufacturing Strategy Survey (IMSS) database.

Results show that while strategic configurations are rather stable, many companies do indeed change strategy and identifies which patterns of change prevail. Product‐based strategy is the most‐widely spread and most stable strategy. Capability‐based competition is the rising star. The market‐based strategy is struggling and price‐based competition is on its way out.

The main limitation is the small size of longitudinal samples, leading to tentative propositions for further testing.

No strategic configuration appears to be the final “maturity” target for manufacturers. Companies select their configurations according to life cycle of the organization and market competition.

The paper contributes to fill a lack of longitudinal evidence of strategic change and flexibility of manufacturing companies.

The functionality and reliability of an overhauled aero-engine is determined by all configuration changes in the overhaul process. Identifying, recording, auditing, tracking and tracing of configuration modifications are significant and meaningful. Considering the barriers to these goals, this paper aims to put forward an approach to configuration management in the aero-engine overhaul process.

The overhaul configuration management model is proposed to describe an aero-engine’s configuration evolution trajectory in the overhaul process. The controlling and auditing procedures are put forward to control and audit parts’ return-to-zero statuses and overproof statuses. And some searching algorithms are also designed to enable tracking and tracing of the configuration status along the time coordinate, or get a snapshot of an aero-engine’s configuration at a certain time. The above model, procedures and algorithms have been implemented and adopted to fulfill the configuration management requirements in the aero-engine overhaul process.

The approach is effective in identifying, recording, controlling, auditing, tracking and tracing configuration changes in the overhaul process.

The approach’s implementation and adoption present a practical example for aero-engines’ configuration management issue in the overhaul process.

The work proposes an original aero-engine configuration management solution for the overhaul process and enables a reliable and accurate configuration management mode.

The purpose of this paper is to describe a shape‐shifting robot with diverse configurations, named “AMOEBA‐I”, which has been developed for search and rescue operations. The accessibility of this robot to unstructured environment is efficiently enhanced by changing its configuration. So the shape and reconfiguration of the robot should be considered in AMOEBA‐I path planning to improve work ability of the robot in complex environment. The unique accessibility of AMOEBA‐I is thus fully displayed.

An auto‐adapted path‐planning method is presented for AMOEBA‐I by introducing the reconfigurable ability of the robot into the modified potential field method. The modified potential field method solves the local minimum problem and goal‐unreachable with nearby obstacles (GUWNO) effectively. A method of the shape‐shifting robot's passing through the narrow space is studied by combining the corner detection with the modified potential field method.

The ability of the robot to automatically change configuration to pass through a narrow space is proven through the experiment. Simulation results show that the robot can change its own configurations to perform auto‐adapted path planning corresponding to the environmental variation. Therefore, the proposed method can improve the probability of completing the path planning. As a result, this method will shorten the path length and complete the rescue operation more effectively.

The paper presents an effective auto‐adapted path‐planning method that integrates the reconfigurable ability of the robot into the modified potential field method in order to realize the auto‐adapted path planning.

This paper aims to report findings from an exploratory empirical study focusing on an application of mass customization in financial services. Based on the study of configurations and usage data, the authors evaluate a series of hypotheses relating to the interplay of adoption and usage by customers.

The study is based on quantitative analysis of data from a Turkish bank which offers customizable credit cards, encompassing both configurations as well as credit card usage.

The results confirm that trial-and-error learning will not end with product definition, but will continue afterwards and lead to changes in customization. Especially active usage length shows a significant positive effect on the number of changes. The effect of base category usage could only partly be confirmed for changes, but was significant for adoption. It was also found that a series of smaller changes in a limited number of attributes has a higher likelihood than a smaller number of changes in a large number of aspects.

The study uses data from a single financial service provider, from a specific country. In addition, anonymized data on adoption and usage were used, thus demographic data as well as subjective measures from customers were not available.

The results highlight the importance of specifying the correct solution space, as the authors could at least partially confirm the negative effect of both a large number of options, as well as basing on alternatives rather than attributes on several levels. Although overall mass customization seems less interesting than traditional credit cards, the authors discuss several positive implications for financial sector companies from offering this option.

The paper extends current literature in focusing for the first time on mass customization for financial services. In addition, this is the first study using longitudinal data on adoption and modification of mass-customized solutions to analyze the long-term behavior of usage.

The purpose of this paper is to describe different ways in which a buyer and supplier can be embedded in a dyadic relationship and how these differences influence patterns of inter-firm innovation activities and outcomes. Specifically, to address the relative paucity of theoretical work on how dyadic configurations influence parties’ joint innovation behavior, this study examines how different buyer-supplier embeddedness (BSE) configurations change the four choices that pertain to the levels of involvement buyers and suppliers exhibit in inter-firm innovation activities. These choices concern the processes buyers use to engage suppliers; the scope of efforts in each party; the locus of effects determining the beneficiaries; and the extent to which parties disclose private innovations within the relationship.

Drawing on social embeddedness literature, the authors conceptualize dyad level, BSE in two dimensions: relational and structural. The relational dimension describes the quality of relationship, while the structural dimension describes the intensity of exchanges between the parties. Together these dimensions allow the authors to map the differences in BSE configurations and provide a basis for exploring their links to inter-firm innovation patterns.

The authors demonstrate the configurational approach to the innovation patterns in inter-organizational setting. That is, the authors conclude that different configurations of BSE are likely to produce distinctive patterns of choices for inter-firm innovation activities.

This study applies social embeddedness perspective to conceptualize dyadic BSE. Adoption of this concept allows dimensionalizing the dyadic relationships into two distinct dyadic elements, relational, and structural dimensions. Also, the concept has rich implications for how partner firms interact and share information. The dyad’s innovation potential and patterns are considered based on the configurations of dyadic embeddedness.

The purpose of this paper is to describe how to measure workplace configuration, show its application in, and the results of, a field experiment aimed at improving collaborative knowledge work and identify and discuss larger problems involved with research on workplace configuration.

The paper reviews recent thought on density, proximity and problems with evaluating configuration. It then describes a method of spatial network analysis used in a field experiment involving the reconfiguration of a workplace. This is followed with a discussion of recent research on knowledge work from economic geography.

It was found that, instead of increasing it, the reconfigured workplace decreased collaborative activity. The spatial network analysis shows how this occurred.

This method of spatial network analysis, when used carefully, is a robust technique for analyzing and comparing spatial configuration. Further research needs to address the links between spatial proximity and information and communications technologies as well as the relation of types of knowledge bases and associated forms of proximity that can stimulate collaboration.

While spatial network analysis methods are not do‐it‐yourself tools, corporate real estate managers should employ them, especially in larger‐scale projects, before committing to final workplace designs. They can also use them to identify and map best spatial patterns (like best practices) to identify strategic spatial patterns.

This appears to be the first rigorous application of spatial network methods in a field experiment involving a real workplace. The paper shows the method can clearly extract and discriminate spatial network patterns underlying configurations and relate them both quantitatively and graphically to employee evaluations of collaborative performance. It introduces concepts of comparative knowledge bases that need to be understood in determining the types of collaboration needed in a workplace.