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As a problem-solving tool, the kaizen event (KE) is underutilised in practice. Assuming this is due to a lack of group process quality during those events, the authors aimed to grasp what is needed during high-quality KE meetings. Guided by the phased approach for structured problem-solving, the authors built and explored a measure for enriching future KE research.

Six phases were used to code all verbal contributions (N = 5,442) in 21 diverse, videotaped KE meetings. Resembling state space grids, the authors visualised the course of each meeting with line graphs which were shown to ten individual kaizen experts as well as to the filmed kaizen groups.

From their reactions to the graphs the authors extracted high-quality KE process characteristics. At the end of each phase, that should be enacted sequentially, explicit group consensus appeared to be crucial. Some of the groups spent too little time on a group-shared understanding of the problem and its root causes. Surprisingly, the mixed-methods data suggested that small and infrequent deviations (“jumps”) to another phase might be necessary for a high-quality process. According to the newly developed quantitative process measure, when groups often jump from one phase to a distant, previous or next phase, this relates to low KE process quality.

A refined conceptual model and research agenda are offered for generating better solutions during KEs, and the authors urge examinations of the effects of well-crafted KE training.

Firms increasingly rely on both external and internal crowdsourcing to capture ideas more broadly and enhance innovative problem-solving. Especially in internal crowdsourcing, knowledge sharing that contributes to develop or further the understanding of the problem the idea is focused on solving can take place between critical employees, and in that way improve ideas generated by others. This far, most crowdsourcing practices have focused on identifying solutions to proposed problems, whereas much less is known about how crowds can be used to share problem-related knowledge. There is thus an untapped potential in leveraging crowds not just to generate solution-oriented ideas but also to share knowledge to improve ideas and even to reframe problems. This paper aims to explore the effect of problem- and solution-related knowledge sharing in internal crowdsourcing for idea development.

Data on ideas and comments were collected from an idea management system in a Swedish multinational company. The investigation captures the influences of the problem- and solution-related knowledge sharing on ideas based on content analysis and logistic regression analysis.

The results from this study show that sharing knowledge related to solutions in idea development impacts idea acceptance positively, whereas sharing knowledge related to problems in idea development has a negative effect on the likelihood of idea acceptance and these effects of knowledge sharing are moderated by the active author responses.

This research provides managerial implications for firms to deliberately manage knowledge sharing in peer communities in internal crowdsourcing, especially by providing suggestions on problem reframing and solution refining for ideas.

The results contribute to existing theory in terms of extending the view of crowdsourcing in ideation to include how crowds contribute to the development of the problem and the solution during the development of ideas and providing new insights on knowledge sharing in internal crowdsourcing based on problem-solving theory.

Teachers of primary education experience high levels of stress but lack rational coping strategies to reduce their work stress. The paper develops a value stream mapping for education approach and examines its use as a rational coping strategy for teams of teachers and other employees to overcome work-related stressors.

The research process consists of two phases. First, a value stream mapping approach for education is developed, based on literature research. Next, the approach is validated in an action research study to reduce work stress of teachers in educational services. The processes that have been selected by the teachers relate to coping with increased variety, long and uncertain throughput times and unclear specifications.

Value stream mapping for education (VSM4EDU) is a well-structured improvement method based on principles of visualization, participation and process thinking, which helps teachers without background in lean thinking to analyse their processes. Using this method has enabled the team to develop rational coping strategies to reduce their work-related stress.

VSM4EDU has been validated using action research at a single school, which implicates deep insight, but further testing at other schools is welcome. Moreover, VSM4EDU has not been used to develop a future state map.

Value stream mapping is useful in educational settings as long as the educational context is respected in the approach.

VSM4EDU empowers teachers and helps to develop co-operation in teams.

The validation of value stream mapping for education is well-documented and original.

This study aims to aid theory building, the use of decision theory (DT) concepts in sustainable supply chain management (SSCM) research is examined.

An abductive approach considers two DT concepts, Snowden’s Cynefin framework for sense-making and Keeney’s value-focussed decision analysis, in a systematic literature review of 160 peer-reviewed papers in English.

Around 60 per cent of the papers on decision-making in SSCM come from operational research (OR), which makes explicit use of DT. These are almost all normative and rationalist and focussed on structured decision contexts. Some exceptions seek to address unstructured decision contexts via Complex Adaptive Systems or Soft Systems Methodology. Meanwhile, a second set, around 16 per cent, comes from business ethics and are empirical, behavioural decision research. Although this set does not explicitly refer to DT, the empirical evidence here supports Keeney’s value-focussed analysis.

There is potential for theory building in SSCM using DT, but the research only addresses SSCM research (including corporate responsibility and ethics) and not DT in SCM or wider sustainable development research.

Use of particular decision analysis methods for SSCM may be improved by better understanding different decision contexts.

The research shows potential synthesis with ethical DT absent from DT and SCM research.

Empirical behavioural decision analysis for SSCM is considered alongside normative, rational analysis for the first time. Value-focussed DT appears useful for unstructured decision contexts found in SSCM.

Empirical, behavioural decision analysis for SSCM is considered alongside normative rational analysis for the first time. Value-focussed DT appears useful for unstructured decision contexts found in SSCM.

Soft systems methodology (SSM) is well documented in the academic and management literature. Over the last 40 years, the methodology has come to be adapted depending on the tool users’ skills and experience in order to fit the problem. The purpose of this paper is to demonstrate good teaching and learning practice from a pedagogical perspective.

Dr Ian Yeoman of Victoria University of Wellington provides a personal reflection of how the methodology is used in the teaching and learning of TOUR301 Tourism Policy and Planning as a policy and scenario analysis method.

The paper articulates the seven stages of SSM from problem situation unstructured, through to Rich Pictures, vision and guiding principles, policy solutions, comparisons, feasibility and implementation stages. The paper uses a series of teaching tasks to breakdown the complexity of the methodology thus guiding students and teachers in how to deploy the methodology in the classroom.

The value of the paper demonstrates the reflective practice of SSM in action as an exemplar of good practice. The paper clearly articulates the stages of the methodology so students and teachers can adopt this approach in classroom environments following a scaffolding learning approach. The use of teaching tasks throughout the paper helps bring clarity and order thus enabling the teacher to effectively teach the subject and the students to learn. The most significant contribution of this paper is the articulation of good teaching practice in policy and scenario analysis which articulated through four learning lessons: facilitating a learning environment; the impact of visual thinking; political theory; the importance of incremental learning; and problem-based learning and international students.

This paper aims to review recent research in design for additive manufacturing (DfAM), including additive manufacturing (AM) terminology, trends, methods, classification of DfAM methods and software. The focus is on the design engineer’s role in the DfAM process and includes which design methods and tools exist to aid the design process. This includes methods, guidelines and software to achieve design optimization and in further steps to increase the level of design automation for metal AM techniques. The research has a special interest in structural optimization and the coupling between topology optimization and AM.

The method used in the review consists of six rounds in which literature was sequentially collected, sorted and removed. Full presentation of the method used could be found in the paper.

Existing DfAM research has been divided into three main groups – component, part and process design – and based on the review of existing DfAM methods, a proposal for a DfAM process has been compiled. Design support suitable for use by design engineers is linked to each step in the compiled DfAM process. Finally, the review suggests a possible new DfAM process that allows a higher degree of design automation than today’s process. Furthermore, research areas that need to be further developed to achieve this framework are pointed out.

The review maps existing research in design for additive manufacturing and compiles a proposed design method. For each step in the proposed method, existing methods and software are coupled. This type of overall methodology with connecting methods and software did not exist before. The work also contributes with a discussion regarding future design process and automation.

The purpose of this paper is to conduct research with children, who have different abilities from adults, in terms of language understanding and level of attention, is a challenging task, especially concerning novel interactive systems such as social robots. Consequently, self-reporting methods are often replaced or supplemented by observational methods that are usually carried out taking advantage of video recordings. However, some limitations make this approach challenging for studies conducted with groups of children in real-world environments, whose relevance is being addressed more and more frequently in human-robot interaction (HRI) research. Thus, there is a growing need for rigorous observation approaches in unstructured test environments.

This paper presents an alternative analysis approach, in relation to an experimental child-robot interaction (CRI) application, which was developed at the Academy of Arts and Design, Tsinghua University, China. The proposed methodology is based on the analysis of video recordings of in-wild activities of children with a robot. The methodology has the aim of providing a framework to facilitate knowledge identification and structuring. It was implemented for experiment evaluation and validation purposes and to propose a reference structure for the organization of new experiments and the stimulation of new ideas and activities in the design process.

This methodology provides a logical structure, which can be used to identify the effectiveness or limits of design choices, pertaining to such aspects as the morphology or movement of robots or the choice of their specific role in education, all of which play crucial roles in the design process and could be improved to achieve better results. This structured identification is a practical implication for the design process, above all when it is oriented toward social robots and their interaction with children or elderly senile people. In this case, the outcomes were the identification of important elements of an experiment (psychological profiles of the involved children and possible problems or risks) and their impact on the design process.

The methodological approach, which structures and uses cognitive maps to elaborate multicriteria evaluation models, is not new to the operations research field (where it is defined as a multimethodology application of Soft OR), but it has not yet been applied in the field of HRI studies, to analyze children’s perception of a robot and to identify the factors that can affect a good CRI or to structure knowledge that can be shared to guide the design process of robots for the experience of children playing.

This study aims to analyze the complexities of the Brazilian soybean supply chain (SSC) and develop strategic interventions to improve the origin system’s performance.

This study used stakeholder interviews to identify the SSC bottlenecks and determine and assess drivers of competitiveness. A methodological framework based on the systems thinking approach for developing long-term structural changes was used. The problem was structured using behavior over time graph and causal loop modeling to propose three investment strategies to solve the logistics problem in SSC.

This study highlights the gaps in coordination between stakeholders and the public sector regarding the public policy for infrastructure investment. Three strategic interventions were developed to address the agro-industrial logistical problem, namely, investment in storage, multimodal transport systems and improvements in existing transport infrastructure. To overcome transport and storage logistics limitations, the authors suggest different forms of partnerships, including public-private partnerships.

This research is limited to evaluating an agricultural commodity (soybean) and does not include its by-products. The sample of stakeholders was limited and the boundary of analysis was Brazil. Nevertheless, the study showed how strategic interventions could be developed following a holistic analysis.

The proposed integrated approach illustrates the development of three strategic initiatives. It can be implemented by stakeholders, including the public sector, which is the basis for providing assertive long-term investments in Brazilian logistics.

The SSC analysis could promote the implementation of systemically determined interventions and strategies. It could significantly improve the performance of agricultural systems and help the formulation of public policies aimed at rural development.

The use of system dynamics to identify intervention points is an essential contribution to mitigating the SSC’s hindrances. Moreover, the combining methodologies resulted in comprehensive intervention strategies.

We read and hear frequently about the role of vision in leadership. Standards for leadership education programs typically emphasize vision as a core component of leadership education and published accounts of successful leadership usually extol the leader’s vision. Given the prevalence of this term in discourse on leadership, it is surprising how little literature exists with specific discussions of how to teach it. In this article I discuss the potential of problem-based pedagogy for teaching the concept of vision. This paper draws on literature, theory, and my professional experience as a faculty member for 20 years in a graduate-level education leadership program.

This paper presents an information technology based instructional model for effective learning in management information systems programs and modules for students in undergraduate education. This model is primarily centered on the traditional in-class learning model. Information technology is used in a unique and novel way in order to create a learning environment which not only engages students in the learning process but also enhances their problems solving skills, analysis and decision making abilities. The model embeds information technology in projects in order to hide complexities but without compromising achievement of learning objectives. It also uses information technology in a simulation mode in order to demonstrate key concepts or learning themes, to simulate main themes presented in case studies and to simulate problems behaviors. The model employs other creative techniques in order to deliver its overall goals.