Understanding Designers Behavior in Parameter Design Activities

2017 ◽  
Author(s):  
Turki Alelyani ◽  
Ye Yang ◽  
Paul T. Grogan
Keyword(s):  
Parameter Design ◽  
Future Research ◽  
Design Experiment ◽  
Problem Complexity ◽  
Design Problems ◽  
Complex Design ◽  
Design Activities ◽  
Successful Design ◽  
And Performance ◽  
The Individual

Successful design processes and tools are vital for the success of any design project, particularly when developing aerospace, automotive and other complex systems that can entail imposing design constraints to meet desired objectives. These constraints, coupled with a lack of uniform strategies to define, acquire and process the interaction between designers and tools, add new challenges to the design process. So appropriate processes and tools that allow problem designers to assist in framing and resolving complex design problems can extend the power of the individual working memory, according to previous research. This current research investigates the behavior of engineers working on a parameter design experiment. In the study, 30 subjects solved parameter design problems with both coupled and uncoupled variables. Results showed a relationship among designers’ actions and other features such as gender, recorded error, problem complexity, and performance. These findings can guide future research into engineering design and can inform ideas for better strategies for various aspects of parameter designing.

The role of compliance for organisational change

2018 ◽  
Vol 31 (2) ◽  
pp. 334-351 ◽  
Author(s):  
Ronald Busse ◽  
Ufuk Doganer
Keyword(s):  
Qualitative Methodology ◽  
Qualitative Content Analysis ◽  
Organisational Change ◽  
Future Research ◽  
Content Type ◽  
Lively Debate ◽  
And Performance ◽  
The Individual ◽  
Depth Interviews

Purpose Fuelled by the latest scandals at Siemens, VW or Walmart, there is a lively debate on the role of compliance and ethics programmes. Unlike large corporations, small and medium-sized enterprises (SMEs) arguably tend to underestimate their significance and lag behind. Hence, the purpose of this paper is to shed light on the process of introducing compliance codes and its effects on employee acceptance and performance. Design/methodology/approach In line with the qualitative methodology, the authors conducted 12 in-depth interviews with German SME employees which the authors evaluated with the qualitative content analysis. Findings As for the major contribution, results indicate the emergence of a lack of understanding, anger, anxiety and operational performance losses – both at the individual and the corporate level – especially when employees feel uninvolved in the initial introduction stadium. Originality/value Practicing managers may benefit from the recommendation to facilitate staff involvement at earlier stages. As for theory advancement, the authors draw on Kotter’s (2007) long surviving “Eight Steps Change Management Model” and find significant support for shifting the spotlight of attention towards the first four phases. The authors discuss the original value of the research, admit limitations and illuminate some promising future research trajectories.

scholarly journals Impacts of knowledge sharing: a review and directions for future research

2019 ◽  
Vol 31 (3) ◽  
pp. 207-230 ◽  
Author(s):  
Farhan Ahmad ◽  
Muhaimin Karim
Keyword(s):  
Knowledge Sharing ◽  
Past Research ◽  
Future Research ◽  
Content Type ◽  
Work Related ◽  
Review Protocol ◽  
Negative Impacts ◽  
And Performance ◽  
The Individual ◽  
Methodological Aspects

PurposeKnowledge sharing contributes to the success of an organization in various ways. This paper aims to summarize the findings from past research on knowledge-sharing outcomes in organizations and to suggest promising directions for future research.Design/methodology/approachThere was a conduction of a systematic literature review that consisted of three main phases: defining a review protocol, conducting the review and reporting the review. The thematic analysis was conducted on 61 studies, based on which a framework for understanding the impacts of knowledge sharing was developed.FindingsPrevious research has investigated knowledge-sharing outcomes at three levels: the individual, team and organization; specific impacts are summarized for each level. The most commonly studied factors affected by knowledge sharing are creativity, learning and performance. Knowledge sharing is also found to have some beyond-convention work-related impacts, such as those on team climate and employees’ life satisfaction. Research on the outcomes of knowledge sharing is dominated by quantitative studies, as we found only one qualitative study in this review. Based on the discussion of the results, promising avenues for further research were identified and a research agenda was proposed. More research on differential, psychological and negative impacts, as well as interactional and methodological aspects of knowledge-sharing, is suggested.Originality/valueTo date, no systematic review has been conducted on the impacts of knowledge-sharing. This paper makes an important contribution to knowledge-sharing research, as it consolidates previous research and identifies a number of useful research topics that can be explored to advance the field, as well as to establish the evidence-based importance of knowledge sharing.

Open for business: The impact of creative team environment and innovative behaviour in technology-based start-ups

2020 ◽  
Vol 38 (4) ◽  
pp. 318-336 ◽  
Author(s):  
Zhao Zhou ◽  
Robert Verburg
Keyword(s):  
Individual Characteristics ◽  
Future Research ◽  
High Tech ◽  
Mediating Role ◽  
Team Environment ◽  
Innovative Behaviour ◽  
And Performance ◽  
The Individual ◽  
The Impact ◽  
Creative Team

Rather than the view of the entrepreneur as a ‘lone ranger’, recent work has focused on the importance of teams in bringing a start-up to growth and success. Here, we aim to bridge the gap between the individual characteristics of entrepreneurs and the characteristics of their teams by examining openness of founders in relation to creative team environment (CTE), innovative work behaviour (IWB) and performance. On the basis of upper echelon theory and integrating other complementary theories such as the attention-based view, we develop a theoretical framework and test this using a survey of 322 high-tech entrepreneurs. Our findings suggest a mediating role of CTE and IWB in the relation between openness of entrepreneurs and performance. The implications of the results for managerial practices and future research directions are discussed.

Revisiting Behavioral Integrity: Progress and New Directions After 20 Years

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Tony Simons ◽  
Hannes Leroy ◽  
Lisa Nishii
Keyword(s):  
Organizational Behavior ◽  
Future Research ◽  
Annual Review ◽  
Publication Date ◽  
Behavioral Integrity ◽  
Positive Behaviors ◽  
Positive Attitudes ◽  
Leadership Initiatives ◽  
And Performance ◽  
The Individual

Behavioral integrity (BI) describes the extent to which an observer believes that an actor's words tend to align with their actions. It considers whether the actor is seen as keeping promises and enacting the same values they espouse. Although the construct of BI was introduced in 1999 and developed more fully in 2002, it builds on the work of earlier scholars that discussed related notions of hypocrisy, credibility, and gaps between espousal and enactment. Since the 2002 paper, a growing literature has established the BI construct, largely but not exclusively in the leadership realm, as a critical antecedent to positive attitudes such as trust and commitment, positive behaviors such as turnover and performance, and as a moderator of the effectiveness of leadership initiatives. BI is by definition subjectively assessed, and perceptions of BI are susceptible to various forms of perceptual biases. A variety of factors appear to affect whether observers interpret a particular word-action alignment or gap as an indication of the actor's high or low BI. In this article, we examine and synthesize this literature and suggest directions for future research. We discuss the early history of BI research and then examine contemporary research at the individual, group, and organizational levels of analysis. We assess what we have learned and what methodological challenges and theoretical questions remain to be addressed. We hope in this way to stimulate further research on this consequential construct. Expected final online publication date for the Annual Review of Organizational Psychology and Organizational Behavior, Volume 9 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Addressing Challenges to Problem Complexity: Effectiveness of AI Assistance During the Design Process

2021 ◽  
Author(s):  
Binyang Song ◽  
Nicolás F. Soria Zurita ◽  
Hannah Nolte ◽  
Harshika Singh ◽  
Jonathan Cagan ◽  
...  
Keyword(s):  
Design Process ◽  
Quantitative Methods ◽  
Search Strategy ◽  
Design Research ◽  
Markov Models ◽  
Parameter Design ◽  
Problem Complexity ◽  
Research Platform ◽  
Design Effectiveness ◽  
The Individual

Abstract As Artificial Intelligence (AI) assistance tools become more ubiquitous in engineering design, it becomes increasingly necessary to understand the influence of AI assistance on the design process and design effectiveness. Previous work has shown the advantages of incorporating AI design agents to assist human designers. However, the influence of AI assistance on the behavior of designers during the design process is still unknown. This study examines the differences in participants’ design process and effectiveness with and without AI assistance during a complex drone design task using the HyForm design research platform. Data collected from this study is analyzed to assess the design process and effectiveness using quantitative methods, such as Hidden Markov Models and network analysis. The results indicate that AI assistance is most beneficial when addressing moderately complex objectives but exhibits a reduced advantage in addressing highly complex objectives. During the design process, the individual designers working with AI assistance employ a relatively explorative search strategy, while the individual designers working without AI assistance devote more effort to parameter design.

scholarly journals Group Positive Affect and Beyond: An Integrative Review and Future Research Agenda

2020 ◽  
Vol 17 (20) ◽  
pp. 7499
Author(s):  
Jonathan Peñalver ◽  
Marisa Salanova ◽  
Isabel M. Martínez
Keyword(s):  
Positive Affect ◽  
Research Agenda ◽  
Group Processes ◽  
Integrative Review ◽  
Future Research ◽  
Future Research Agenda ◽  
Similarity Group ◽  
Working Together ◽  
And Performance ◽  
The Individual

Group positive affect is defined as homogeneous positive affect among group members that emerges when working together. Considering that previous research has shown a significant relationship between group positive affect and a wide variety of group outcomes (e.g., behaviors, wellbeing, and performance), it is crucial to boost our knowledge about this construct in the work context. The main purpose is to review empirical research, to synthesize the findings and to provide research agenda about group positive affect, in order to better understand this construct. Through the PsycNET and Proquest Central databases, an integrative review was conducted to identify articles about group positive affect published between January 1990 and March 2019. A total of 44 articles were included and analyzed. Finding suggests that scholars have been more interested in understanding the outcomes of group positive affect and how to improve the productivity of groups than in knowing what the antecedents are. A summary conclusion is that group positive affect is related to leadership, job demands, job resources, diversity/similarity, group processes, and contextual factors, all of which influence the development of several outcomes and different types of wellbeing at the individual and group levels. However, with specific combinations of other conditions (e.g., group trust, negative affect, and interaction), high levels of group positive affect could cause harmful results. Conclusions shed light on group positive affect research and practice and might help Human Resources professionals to initiate empirically-based strategies related to recruitment, group design and leadership training.

scholarly journals Beyond brood: the potential impacts of insect growth disruptors on the long-term health and performance of honey bee colonies

Apidologie ◽  
2021 ◽  
Author(s):  
Julia D. Fine ◽  
Vanessa Corby-Harris
Keyword(s):  
Honey Bees ◽  
Future Research ◽  
Insect Development ◽  
Insect Growth ◽  
And Performance ◽  
The Individual ◽  
And Behavior ◽  
Bee Colonies ◽  
Critical Aspects

AbstractHoney bees are valued pollinators of agricultural crops, and heavy losses reported by beekeepers have spurred efforts to identify causes. As social insects, threats to honey bees should be assessed by evaluating the effects of stress on the long-term health and productivity of the entire colony. Insect growth disruptors are a class of pesticides encountered by honey bees that target pathways involved in insect development, reproduction, and behavior, and they have been shown to affect critical aspects of all three in honey bees. Therefore, it is imperative that their risks to honey bees be thoroughly evaluated. This review describes the effects of insect growth disruptors on honey bees at the individual and colony levels, highlighting hazards associated with different chemistries, and addresses their potential impacts on the longevity of colonies. Finally, recommendations for the direction of future research to identify strategies to mitigate effects are prescribed.

Interdisciplinary Graduate Design Programs: Results and Recommendations From a NSF Workshop

2009 ◽  
Author(s):  
Timothy W. Simpson ◽  
Samuel T. Hunter ◽  
Cari Bryant-Arnold ◽  
Matthew Parkinson ◽  
Russell R. Barton ◽  
...  
Keyword(s):  
Design Research ◽  
Well Being ◽  
Design Problems ◽  
Future Directions ◽  
Research And Teaching ◽  
Interdisciplinary Design ◽  
National Competitiveness ◽  
Complex Design ◽  
Design Activities ◽  
The Common

Improving the creativity and innovativeness of U.S. graduate students is a mandate for national competitiveness and social well-being. Despite this imperative, many are uncertain about how to best prepare students for tackling the complex design problems of the future, some that we know about and others yet to be uncovered. With this in mind, we convened a two-day workshop at the National Science Foundation (NSF) in Arlington, VA to discuss the challenges, successes, and future directions for interdisciplinary graduate design programs that have recently emerged or are being established to address this critical need. Not including NSF personnel, 42 people from academia and industry gathered to learn about nine existing interdisciplinary design programs. Three panels were also held to discuss: (1) overcoming interdisciplinary differences in research and teaching, (2) industry perspectives on interdisciplinary design programs, and (3) future directions and program developments. A number of common themes emerged from the workshop, including the disciplinary characteristics of interdisciplinary design, the varying perspectives on the design process, pedagogical approaches toward teaching interdisciplinary design, structuring interdisciplinary design degrees, and sustainability of an interdisciplinary design discipline. Based on the dialogue at the workshop and our analysis of the common themes, we offer ten recommendations divided into three areas: (1) advance interdisciplinary design activities, (2) enhance interdisciplinary design programs, and (3) support interdisciplinary design research.

Identification of Subproblems in Complex Design Problems: A Study of Facility Design

2016 ◽  
Author(s):  
Azrah Azhar ◽  
Erica L. Gralla ◽  
Connor Tobias ◽  
Jeffrey W. Herrmann
Keyword(s):  
Standard Method ◽  
Association Rule ◽  
Rule Learning ◽  
Problem Decomposition ◽  
Design Teams ◽  
Design Problems ◽  
Manufacturing Facility ◽  
Qualitative And Quantitative ◽  
Complex Design ◽  
Design Activities

Many design problems are too difficult to solve all at once; therefore, design teams often decompose these problems into more manageable subproblems. While there has been much interest in engineering design teams, no standard method has been developed to understand how teams solve design problems. This paper describes a method for analyzing a team’s design activities and identifying the subproblems that they considered. This method uses both qualitative and quantitative techniques; in particular, it uses association rule learning to group variables into subproblems. We used the method on data from ten teams who redesigned a manufacturing facility. This approach provides researchers with a clear structure for using observational data to identify the problem decomposition patterns of human designers.

scholarly journals Extended-Range Prediction Model Using NSGA-III Optimized RNN-GRU-LSTM for Driver Stress and Drowsiness

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6412
Author(s):  
Kwok Tai Chui ◽  
Brij B. Gupta ◽  
Ryan Wen Liu ◽  
Xinyu Zhang ◽  
Pandian Vasant ◽  
...  
Keyword(s):  
Traffic Accidents ◽  
Performance Enhancement ◽  
Short Term Memory ◽  
Road Traffic ◽  
Prediction Algorithm ◽  
Future Research ◽  
And Performance ◽  
The Individual ◽  
Gated Recurrent Units ◽  
Driver Stress

Road traffic accidents have been listed in the top 10 global causes of death for many decades. Traditional measures such as education and legislation have contributed to limited improvements in terms of reducing accidents due to people driving in undesirable statuses, such as when suffering from stress or drowsiness. Attention is drawn to predicting drivers’ future status so that precautions can be taken in advance as effective preventative measures. Common prediction algorithms include recurrent neural networks (RNNs), gated recurrent units (GRUs), and long short-term memory (LSTM) networks. To benefit from the advantages of each algorithm, nondominated sorting genetic algorithm-III (NSGA-III) can be applied to merge the three algorithms. This is named NSGA-III-optimized RNN-GRU-LSTM. An analysis can be made to compare the proposed prediction algorithm with the individual RNN, GRU, and LSTM algorithms. Our proposed model improves the overall accuracy by 11.2–13.6% and 10.2–12.2% in driver stress prediction and driver drowsiness prediction, respectively. Likewise, it improves the overall accuracy by 6.9–12.7% and 6.9–8.9%, respectively, compared with boosting learning with multiple RNNs, multiple GRUs, and multiple LSTMs algorithms. Compared with existing works, this proposal offers to enhance performance by taking some key factors into account—namely, using a real-world driving dataset, a greater sample size, hybrid algorithms, and cross-validation. Future research directions have been suggested for further exploration and performance enhancement.

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