Search results

Six Sigma is a well-established powerful business strategy for achieving operational excellence (OPEX). However, previous studies have suggested that the Six Sigma may negatively impact organizational creativity and innovation. The C-K theory is one of the most widely used technique for design reasoning which promotes the creativity and innovation. The purpose of this paper is to integrate the Six Sigma methodology and C-K theory for enhancing innovative capacity of Six Sigma for achieving OPEX.

The paper proposes an integration methodology of C-K theory and Six Sigma using the extant literature. Also, a case study is conducted based on the proposed integration model.

The paper suggests a step-by-step integration methodology for integrating Six Sigma with C-K theory for both (DMAIC and DMADV). The methodology when applied to a live case in mining logistics the results are very encouraging. The solution was cost effective and also technically superior compared to previous solutions.

The paper proposes a step-by-step methodology for the integration of Six Sigma with C-K tools. The methodology is practically applied in a live case. Organizations can use findings from this paper to implement an integration model of Six Sigma with C-K theory.

This is the first paper that proposes an integration methodology of Six Sigma with C-K theory to enhance the innovation capability to achieve the OPEX.

Despite an increasingly explicit professional nature, the futures studies field has suffered an increasing constraining to a collection of specific techniques. The purpose of this paper is to harness the foundational shortcomings of current futures studies methods, namely the lack of a well‐defined underpinning theory and of rigorous, rational, systematic, repeatable, traceable, documentable, and transferable method. It proposes a rigorous theory for futures studies whereby futures can be logically designed.

This paper envisages the futures design activity as an extension and a generalization of decision theories and problem solving. The process is made comprehensible and interpretable thanks to a co‐generation referencing between two spaces named Concepts and Knowledge. It works by undertaking a formal mathematical approach on undecidable root concepts, bearing no logical status, by logically expanding them until a validable proposition in the knowledge space is reached. The paper is based on the concept‐knowledge theory (C‐K theory) from Ecole des Mines ParisTech, explains why it is needed, illustrates it and uses it on two illustrative futures studies examples.

The proposed research opens a new method for designing futures based on the C‐K theory that has the intrinsic capacity of constructing radical innovations for futures scenarios. While setting clear departure from, for example, brainstorming techniques or Delphi‐based methods, it offers a systematic method for designing futures that rests upon solid theoretical foundation that explains the nonsense or contradictions in producing futures.

While the C‐K theory is fully supported by a scientific basis founded on mathematics and is in widening use in domain‐specific industrial sectors at large, it is still being expanded both theoretically and epistemologically. The theory is not aimed at choosing or formulating suitable or appropriate root concepts, this being the role of domain professionals. Its implementation, however coherent, is only as extensive and covering the problematic at hand as the implementers are congruous to the application domain.

The proposed research can help futurists to develop new breakthrough plans, solutions and alternatives with essential and novel benefits: to help control the rationale of a futures scenario development, to control the degree of innovation (e.g. change, reform, progress, create …) to reach, and to bring to decision makers and policy‐makers the traced explanation of different design paths.

The benefits of the C‐K approach are detailed and elements founding further theoretical research are provided, including possible developments of C‐K theory specifically helpful for futurists. The research offers a collective design method for revisiting futures sciences by defining, understanding and developing creative futures alternatives that can collectively mobilize stakeholders. Workshops with stakeholders remain necessary, with experienced coaches catalyzing its field implementation.

The paper pushes the edge of the discussion on philosophical, ontological and epistemological grounds and supplies a theoretical underpinning for futures studies at large. The research is inherited from the creative power of modern mathematics as developed and proven by the C‐K theory, a powerful approach for discussing design phenomena. The author argues that it constitutes a suitable and useful asset for futures scientists insofar as to imagine, understand, develop, manipulate, and assess creative futures alternatives. The paper introduces and discusses the notion of futuron, which can be seen as a “logical quantum particle of future”.

Scholars and practitioners have both emphasized the importance of collaboration in an innovation context. They have also largely acknowledged that the definition of common purpose is a major driver of successful collaboration, but surprisingly, researchers have put little effort into investigating the process whereby the partners define the common purpose. The purpose of this paper is to explore the generation of common purpose (GCP) in innovation partnerships.

An action‐research approach combined with modeling has been followed. The authors’ research is based on an in‐depth qualitative case study of a cross‐industry exploratory partnership through which four partners, from very different arenas, aim to collectively define innovation projects based on micro‐nanotechnologies. Based on a design reasoning framework, the mechanisms of GCP mechanism are depicted.

Regarding GCP, two main interdependent facets are identified: the determination of existing intersections between the parties’ concept and knowledge spaces (“Matching”); and an introspective learning process that allows the parties to transforms those spaces (“Building”).

The better understanding of the GCP and the specific notion of “C‐K profiles”, which is an original way to characterize each partner involved in a partnership, should improve the capabilities of organizations to efficiently define collaborative innovation projects.

The paper explores one of the cornerstones of successful collaboration in innovation: the process whereby several parties define the common purpose of their partnership.

There is a widespread agreement in the managerial literature that projects produce much more than what they deliver. However, most of the literature focuses on what project delivers (new products, processes, services …). This can be misleading, especially for highly innovative projects for which neither the goals, nor the means to reach them, are clearly defined at the beginning. Thus, contemporary research argues for a model in which project management is, first and foremost, a way to organize the exploration process. The question becomes the definition of a framework to evaluate the project results (success or failures). The purpose of this paper is to study this question by bridging project management and design literature. Indeed research on design processes propose tools that could help managers to better understand what has been delivered and learned during the exploration journey. The paper relies on the Manhattan case to illustrate the fruitfulness of this approach.

The paper opted for an exploratory study using an historical case study: the Manhattan project. The author was able to draw on a large amount of historical material which has not yet been used to study the management of exploration projects. The paper focuses on a specific set of events likely to reveal the problems raised by the evaluation of exploration projects. Given the information available, it was considered that the point of “theoretical saturation”, which Glaser and Strauss proposed as the criterion to stop collecting data, had been attained.

The paper shows how recent development in design theory may provide a fruitful theoretical framework to develop a new evaluation framework to assess the results of exploratory projects in terms of both products designed and knowledge developed.

Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to explore this question further.

The paper includes implications for the development of new evaluation tools for exploratory projects.

The question of project evaluation is of the greatest importance to enhance the management of exploration processes. The paper's bridging of design theory and project management constitutes an original approach.

Product configurators are expert systems that support product customization by defining how predefined entities and their properties may be combined. Developers of configuration systems act as designers, although they do not often recognize that they are performing as such. Moreover, exploring solution spaces is typically not integral to configuration projects, as this task is typically perceived as mapping existing knowledge to the configurator. This article argues that developing configurators may be understood by distinguishing between the problem and solution spaces using design thinking (DT).

A multiple-case-study approach with four configuration projects is adopted to study two projects involving DT and compare them to two similar projects not involving DT. Data collection depended on multiple data sources via workshops and semi-structured interviews.

First, DT methods and concept–knowledge (C-K) theory are integrated into configuration projects. Second, the application of DT during configurator development is presented through workshops and interviews, which demonstrates the benefits of DT in overcoming existing challenges.

The case studies demonstrate the successful implementation of DT in developing configurators. However, a limited number of cases in only one company limits the generalizability of the results.

The framework's individual steps create a structured approach to supporting industrial companies with a toolbox of DT techniques and methods for configuration projects.

The results show that the application of DT to configuration projects can improve user motivation, stakeholder satisfaction and knowledge acquisition.

We develop a discourse of strategic management as design, using a conceptual base drawing upon the work of Michel Foucault, as an alternative to the prevailing strategy discourse (strategy as “economizing”). We then use contemporary design theory to theorize strategic management as a design activity in which the focus is on innovation, with the emphasis on future strategies based on the creation of desirable unknowns.

The purpose of this paper is to present a framework of ideation pathways that organically extend the current stock of knowledge to generate new and useful knowledge. Although detailed, granular guidance is available in the strategy literature on all aspects of empirically testing theory, the other key aspect of theory development – theory generation – remains relatively neglected. The framework developed in this paper addresses this gap by proposing pathways for how new theory can be generated.

Grounded in two foundational principles in epistemology, the Genetic Argument and the open-endedness of knowledge, I offer a framework of distinct pathways that systematically lead to the creation of new knowledge.

Existing knowledge can be deepened (through introspection), broadened (through leverage) and rejuvenated (through innovation). These ideation pathways can unlock the vast, hidden potential of current knowledge in strategy.

The novelty and doability of the framework can potentially inspire research on a broad, community-wide basis, engaging PhD students and management faculty, improving knowledge, democratizing scholarship and deepening the societal footprint of strategy research.

Knowledge is open-ended. The more we know, the more we appreciate how much we don’t know. But the lack of clear guidance on rigorous pathways along which new knowledge that advances both theory and practice can be created from prior knowledge has stymied strategy research. The paper’s framework systematically pulls together for the first time the disparate elements of transforming past learning into new knowledge in a coherent epistemological whole.

In further conceptualizing a novel generative knowledge management system (KM/KMS), this paper aims to focus on identifying and mitigating the risks related to its envisaged scaling from a prototype to an application with a rapidly growing user base.

It follows up on prior publications using design science research (DSR) methodologies in compliance with theory effectiveness, a principle expecting system designs to be purposeful in terms of utility and communication. The KMS perspective taken prioritizes a decentralizing agenda benefiting knowledge workers while also aiming to foster a fruitful co-evolution with conventional organizational KM approaches.

The utilization and further extension of the CKDT and a “scalable innovation” heuristic are assisting the detecting of potential scaling risks related to the logics and logistics, generative interoperability, technological capacitating, knowledge dynamics and value chain which further validates the viability of the proposed KM concept and system.

Although the prototype development is still in progress, the paper conforms to the DSR practice to report on early visions of technology impact on users, organizations and society but also reflects on expectations of viability, desirability and commitment, as well as the system’s prospect as a general-purpose-technology or disruptive innovation.

In addition to the novel KM-related perspectives, the paper’s practical emphasis on the scaling of more complex systems is rarely dealt with in the literature due to the respective projects’ often large-scale collaborative nature, broad methodological scope and diverse stakeholders’ interests. In this case, the task is eased as prior DSR outputs can be referred to.

Often, it is assumed that teams are better at solving problems than individuals working independently. However, recent work in engineering, design and psychology contradicts this assumption. This study aims to examine the behavior of teams engaged in data science competitions. Crowdsourced competitions have seen increased use for software development and data science, and platforms often encourage teamwork between participants.

We specifically examine the teams participating in data science competitions hosted by Kaggle. We analyze the data provided by Kaggle to compare the effect of team size and interaction frequency on team performance. We also contextualize these results through a semantic analysis.

This work demonstrates that groups of individuals working independently may outperform interacting teams on average, but that small, interacting teams are more likely to win competitions. The semantic analysis revealed differences in forum participation, verb usage and pronoun usage when comparing top- and bottom-performing teams.

These results reveal a perplexing tension that must be explored further: true teams may experience better performance with higher cohesion, but nominal teams may perform even better on average with essentially no cohesion. Limitations of this research include not factoring in team member experience level and reliance on extant data.

These results are potentially of use to designers of crowdsourced data science competitions as well as managers and contributors to distributed software development projects.

The purpose of this paper is to present a reflective assessment on a research project aimed at applying design research methodologies to understand the benefits of building information modelling (BIM) in infrastructure design projects, a context where design research has not been applied adequately.

The findings reported in this paper are based on a reflective diary and reporting by the researchers on the challenges and barriers they faced in a research project that involved four case studies. The data in the case studies were collected from project documentation, questionnaire surveys, interviews and workshops. Sentiment analysis was conducted to assess the research participants’ perceptions.

Several challenges faced during the research study forced changes to the research process as well as adjustments to the research objectives. From the original objective of quantitatively measuring the benefits of BIM in the design process, the objective was shifted to measuring qualitatively how the designers’ perceived the benefits. There was evident lack of shared understanding between the researchers and industry partners about the scope of design research and design in infrastructure projects.

The findings are based on the studies in one country, and the reflective assessment could have researchers’ bias in terms of their interpretation and experience.

The presented findings and the lessons learnt from the research will be useful for others planning to conduct similar studies, because they are likely to encounter similar problems. The recommendations will benefit both the industry as well as the academia in bridging the gap between design theory and practice.

This paper primarily focusses on the challenges and barriers to conducting empirical research, especially from the viewpoints of a young researcher aiming to adopt design research methodology in infrastructure design projects. While the reported challenges may be widespread in similar research projects, they have not been the focus of research themselves, and are often sidelined. The primary contribution of this research is to identify and bring the key barriers and challenges to the forefront.