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This paper proposes the combination of rapid prototyping and physical modelling as a set-based concept evaluation method in the early stage of new product development.

The concept evaluation method is applied in a case study of a new metal additive manufacturing process for aluminium, where a set of four extruder concepts has been modelled and evaluated. Rapid prototyping was used to produce plastic models of the different designs, and plasticine feedstock material was used to physically model the metal flow during operation. Finally, the selected concept has been verified in full-scale for processing of aluminium feedstock material.

The proposed method led to several valuable insights on critical factors that were unknown at the outset of the development project. Overall, these insights enabled concept exploration and concept selection that led to a substantially better solution than the original design.

This method can be applied for other projects where numerical approaches are not applicable or capable, and where the costs or time required for producing full-scale prototypes are high.

Employing this method can enable a more thorough exploration of the design space, allowing new solutions to be discovered.

The proposed method allows a design team to test and evaluate multiple concepts at lower cost and time than what is usually required to produce full-scale prototypes. It is, therefore, concluded to be a valuable design strategy for the early development stages of complex products or technologies.

The purpose of this paper is to identify the areas and logic of integration of different stakeholders using different methods and to analyse their applicability and challenges in practical projects. The main aim is to describe how these different methods impact value creation.

Action design research was carried out in a large hospital construction project where the first author acted as an “involved researcher” and the second author acted as an “outside researcher”. Two workshops were organised to evaluate the direct and indirect challenges and benefits of the applied four methods and to explain how different methods enable value creation.

All the studied methods provide good results in terms of usability and commitment to the aims of the project, thus delivering the direct benefits expected. Process, people and tools logic works well in this case project when applying the methods properly. Significant evidence was provided on secondary deliverables of the methods, and all analysed methods had a significant impact in the area of leading people, clarifying what “focus on people” means and how it is enabled.

Focus on people can be achieved through different operative methods if applied in the right way. It is necessary to select the most suitable methods based on all the direct and indirect deliverables.

This case project offered a platform to analyse integration methods in a real-life project using the collaborative contract method. The authors were able to participate in the analysis by taking action from the very beginning of the project in terms of training, learning, continuous development and coaching of these methods and evaluating the applicability.

The emergence of collaborative delivery models and working practices in construction industry has created a potential area for project success research. Previous studies have addressed success factors of various collaborative delivery models (e.g. alliance and partnering). However, there is currently very limited research-based knowledge concerning core success factors for different collaborative delivery models, exploring the commonalities. Thus, this study aims to conceptualize a success model for collaborative construction projects by identifying and structuring their core success factors through the lens of project delivery elements.

A systematic literature review was conducted, and thematic as well as content analysis of the relevant studies led to the identification of mentioned success factors in the literature for different collaborative delivery models. Then, those common success factors were structured in a model based on factors' relation to project delivery elements.

The obtained results present eight core success factors (e.g. equality, mutual trust and commitment to win–win philosophy) for collaborative construction projects, structured in a model based on their contribution toward project organization, contractual relationships, and operational system in construction project delivery. Moreover, the differences between success factors for traditional and collaborative construction projects are discussed.

This study's findings provide insightful theoretical contributions on collaborative construction project success and providing a departure point for future studies based on the discussed differences between success factors of collaborative and traditional construction projects. The findings can be also practically insightful for the project professionals in collaborative construction projects to succeed in managing project organization, contractual relationships, and operational system.

The purpose of this paper is to investigate the factors contributing to the competencies and capabilities of Family Development Center (FDC) staff in order to promote pre-school language developmental support amongst parents.

A cross-sectional study was conducted amongst 260 FDC staff under the supervision of Thai local authorities in the rural province of Suphanburi in Thailand from July to September 2016. Self-administered questionnaires were used. Eligible participants with at least a year’s experience on the FDC committee were purposively selected. Analyses were performed by descriptive statistics, Pearson’s correlation, Spearman’s correlation, χ² test and stepwise multiple regression.

Only 23.5 percent of staff had a high level of capability. The respondents’ perceptions of their self-capability were influenced by motivation, attitudes toward promoting language learning amongst parents, self-efficacy, sufficient budget and receiving constructive appraisal support (r=0.387, 0.328, 0.366, 0.106 and 0.104, respectively). Marital status was negatively associated with FDC staff capability (r=−0.172). The multivariate analysis showed that 23.9 percent of the variability of FDC staff’s self-capability could be explained by their motivation for working, attitude, self-efficacy and marital status (p<0.001).

Research findings could be used to improve motivation for working, positive attitudes and self-efficacy regarding parenting promotion for pre-school language development to achieve standardized quality performance. Results of this study could also form the basis for designing effective training programs for FDC staff in the context of the specific organization and community.

Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively.

The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process.

To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages.

This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.

This paper aims to develop and apply a service design method that allows for stronger recognition and integration of human activities into the front-end stages of the service design process.

Following a discussion of different service design perspectives and activity theory, the paper develops a method called activity-set mapping (ActS). ActS is applied to an exploratory service design project to demonstrate its use.

Three broad perspectives on service design are suggested: (1) the dyadic interaction, (2) the systemic interaction and (3) the customer activity perspectives. The ActS method draws on the latter perspective and focuses on the study of human activity sets. The application of ActS shows that the method can help identify and visualize sets of activities.

The ActS method opens new avenues for service design by zooming in on the micro level and capturing the set of activities linked to a desired goal achievement. However, the method is limited to activities reported by research participants and may exclude unconscious activities. Further research is needed to validate and refine the method.

The ActS method will help service designers explore activities in which humans engage to achieve a desired goal/end state.

The concept of “human activity set” is new to service research and opens analytical opportunities for service design. The ActS method contributes a visualization tool for identifying activity sets and uncovering the benefits, sacrifices and frequency of activities.

The scalability of similarity joins is threatened by the unexpected data characteristic of data skewness. This is a pervasive problem in scientific data. Due to skewness, the uneven distribution of attributes occurs, and it can cause a severe load imbalance problem. When database join operations are applied to these datasets, skewness occurs exponentially. All the algorithms developed to date for the implementation of database joins are highly skew sensitive. This paper presents a new approach for handling data-skewness in a character- based string similarity join using the MapReduce framework. In the literature, no such work exists to handle data skewness in character-based string similarity join, although work for set based string similarity joins exists. Proposed work has been divided into three stages, and every stage is further divided into mapper and reducer phases, which are dedicated to a specific task. The first stage is dedicated to finding the length of strings from a dataset. For valid candidate pair generation, MR-Pass Join framework has been suggested in the second stage. MRFA concepts are incorporated for string similarity join, which is named as “MRFA-SSJ” (MapReduce Frequency Adaptive – String Similarity Join) in the third stage which is further divided into four MapReduce phases. Hence, MRFA-SSJ has been proposed to handle skewness in the string similarity join. The experiments have been implemented on three different datasets namely: DBLP, Query log and a real dataset of IP addresses & Cookies by deploying Hadoop framework. The proposed algorithm has been compared with three known algorithms and it has been noticed that all these algorithms fail when data is highly skewed, whereas our proposed method handles highly skewed data without any problem. A set-up of the 15-node cluster has been used in this experiment, and we are following the Zipf distribution law for the analysis of skewness factor. Also, a comparison among existing and proposed techniques has been shown. Existing techniques survived till Zipf factor 0.5 whereas the proposed algorithm survives up to Zipf factor 1. Hence the proposed algorithm is skew insensitive and ensures scalability with a reasonable query processing time for string similarity database join. It also ensures the even distribution of attributes.

To address requirements and specifications of construction project, academics need to build a project classification model. In recent years, project success concept, particularly on large-scale construction projects, has been a controversial issue, especially in developing countries. Hence, in this paper, after introducing a sustainable success index (SSI), a novel method called “rough set approach” had been adopted to induce decision rules and to classify construction projects. The paper aims to discuss these issues.

At first, 20 effective success factors and 15 success criteria based on three pillars of sustainability of economy, society and environment had been categorized. The research data used for analysis had been collected from 26 large-scale construction projects in Iran and five other countries. After collecting data collection, observations had been analyzed and 51 decision rules were generated, and the projects were classified. Eventually, in order to evaluate the performance of the generated rules, confusion matrix was applied, and the model was validated.

The results of the present study show that rough set theory (RST) can be an effective and valuable tool for building expert systems. Practical applications of these results along with limitations and future research are described.

Perhaps for the first time, in the present study, a number of large-scale construction projects are classified based on SSI. Applying RST for building rule-based system and classifying projects in construction project area are novel attempts undertaken in this paper. The rules induced in this study can be applied to develop a sustainable success prediction model in the future studies.

The study aims to promote independent mobility for persons with visual impairment or legal blindness (VIB) by developing a Web-based wayfinding application using geographic information systems (GIS). While the literature mainly focuses on technical devices presenting results for wayfinding, a lack of integration of user needs is identified. The inclusive, participative developed application offers step-by-step directions for pre-trip planning through an accessible user interface.

The paper presents a semi-automated approach to extract a pedestrian routing network data set based on open government data and field survey. User profiles calculate different routes using a weighting scheme for landmarks, orientation hints, infrastructure of crossings and sidewalks. The adoption of ArcGIS Web AppBuilder widgets allows access of the user interface additionally through keyboard-only navigation and therefore screen-reader capability.

GIS offers a powerful tool to design network analysis for persons with VIB. The routing algorithm accesses different user profiles, returning individualized turn-by-turn directions. The complex set of attributes, including shorelines, landmarks and barriers, can be integrated by semi-automated processes.

The paper illustrates the benefit of GIS applications for wayfinding of persons with VIB to raise self-determination and independence.

A ubiquitous pedestrian sidewalk network for a medium-size city comprises a novelty, as research has mainly focused on small areas. The integration of shorelines next to a various number of hints, landmarks and potential barriers through semi-automated processes allows reproducibility and transferability of the model to other cities.

The small Brazilian companies are responsible for a large part of national GDP and formal jobs in the country. This expressiveness is contrasted with the specificities of companies of this size possess, including the need to innovate to survive. Research shows that 83 percent of Brazilian SMEs have launched new products and services, obtaining positive results through this innovative process. This competitive advantage is weighted by a great feature of the small organization: resource constraint. The paper aims to discuss this issue.

Research was carried out in three stages: one qualitative research (by using focal groups) and another two quantitative research works (descriptive and cross-sectional).

The author identified three factors that are important for teenagers when influencing the purchase of the family car: safety, sportiness and comfort. The identification of these factors shows that the millennial generation tends to emphasize aspects of individual interest, such as status and performance, and family context, such as safety and comfort, rather than social aspects, such as the type of fuel and environmental impact.

The authors recommend the development of automobiles that prioritize the three factors mentioned herein in order to reverse the trend of declining car purchase.

The authors presented the relevant attributes in buying decisions of family cars according to teenagers. The authors also indicated which automobile attributes are relevant for a more informed, connected, and with an increasing purchase power generation in contrast with previous generations, whose social context was prior to the emergence of social media.