Journal of Engineering Design Call for Papers

Special Issue: Affective Design using Big Data

Journal of Engineering Design

Overview

The Journal of Engineering Design is inviting high-quality submissions for an upcoming special issue.

Bringing together both academia and industry to report the latest technologies/techniques on using big data for affective design, this special issue presents an opportunity for authors to publish research in a prominent and well-established journal in its field.

Context for the special issue

Rapid increase of consumer expectations and demands in the business environment have elicited an urgent need of competitive strategy to develop a successful product. Consumers not only consider the functionality and reliability of products, but are also concerned with affective aspects of products such as affective elements, texture, form, colour, and style. Successful products nowadays need to demonstrate their competitive edge with affective features, in addition to the basic functions. As an example, smartphones are generally developed with similar functions1. In the market place, some are equipped with more attractive interfaces while others with less attractive ones. Surveys have indicated that attractive features could help promote product success. It clearly demonstrates the importance of affective design: products with good affective design excite psychological feelings and can help improve consumer satisfaction in terms of emotional aspects. Therefore, it is essential to consider affective design when developing products with pleasurable features.  

Affective features can be acquired via analysis of “big data” which may engage 2.5 quintillion bytes of data on a daily basis2. Such data can be captured from a wide range of sources such as pervasive sensor networks, internet services, and social media. Over the past few years, “big data” has raised growing interest in capturing useful information for developing company strategies, marketing campaigns and product preferences. By collecting and processing this data, affective design can be defined as a function of various affective features/elements/dimensions, and such functions can be optimised via analysis and modelling of the relationship between affective dimensions and design attributes.

However, “big data” is generally high volume, multi-dimensional, multi-sourced, highly varied, and highly uncertain3. There are still significant challenges to capture, store, process, visualise, query, and manipulate “big data” to extract useful information for affective design. Distilling information through “big data” from web pages, blogs or social media remains a difficult task, as such data often consists of images, content and videos that are often unstructured as well as dynamic in nature. While such data can be readily understood by humans, it is difficult, if not impossible, to achieve the same using digital technologies such as computers. Therefore, state-of-the-art technologies/techniques that are intelligent and accessible are required to support the identification and optimisation of affective design. 

Details of the special issue

This special issue aims to address the above challenges and solicit original papers describing innovative technologies/techniques to conjunct affective design with big data. Consequently, topics of interest include (but are not limited to):

a) Data collection and knowledge management for affective design based on social media, online product communities, multimedia-based groups, and cloud computing;

b) Capturing affective intention and conducting affective survey through big data; alternatives to traditional survey-based questionnaires, conducting physiological assessment from human through internet, collecting affective data through sensor networks;

c) Transforming unstructured affective data using text mining and ontology;

d) Analysing, capturing and evaluating consumer affective requirements and concepts through big data;

e) Identification of affective features/elements from big data;

f) Impact of uncertainty on generation and evaluation of affective design when using big data; uncertainty analysis with vague concepts or parameters such as Kansei words or psychophysical elements when using big data;

g) Big data mining for Kansei engineering, cognitive-affective modeling, affective quality improvement;

h) Modelling of consumer affective preference / satisfaction using big data;

i) Using big data for correlating consumer satisfaction, engineering characteristics and design attributes on affective design;

j) Using big data to defining affective design specifications from marketing perspective;

k) Using big data to develop smart systems which combine emotionally designed and affective aspects for product development;

l) Development of machine learning/artificial intelligence techniques for affective design based on big data;

m) Development of computer-aided design systems for affective products using big data; incorporating decision-making within the development process of affective products using big data. 

Topics should all be clearly related/integrated within affective design activity or processes.

Why should you submit?

With an Impact Factor of 1.946 and listed in a multitude of indices including EBSCO Databases, British Library Inside, ISI Science Citation Index and Scopus, the Journal of Engineering Design is a well-established and well-recognised journal in its field. As such, you can be assured that research published within this journal and its special issues will be widely read across academia and industry alike.

The potential audience for this special issue includes:

Research students, researchers and scientists from academia or research institutes who are involved in the development of affective design technologies using big data mining,  and solving difficult and complex problems relating to affective design and big data; and, engineers and product designers from manufacturing industries who use big data for affective design.

How to submit

Be sure to submit your papers now for consideration.

Publication Schedule:

Full Papers Due for Review: 30 September, 2017
Notification of Review Decision: 30 November 2017
Revised Manuscript Submission: 31 January 2018
Final Decision: 15 April, 2018  
Final Manuscripts: 15 May, 2018  
Expected Date of Publication: June 2018 (vol. 31, no.2) 

Please prepare your paper following the “Instructions for Authors

Please submit your paper directly to the journal. Once logged in, select “Author Centre”, and then "Click here to submit a new manuscript".

(NOTE: Once logged in, select "Author Centre", and then "Click here to submit a new manuscript". In Step 1, check “Special Issue Article” for the type of article. In Step 5, check “Yes” for the last question, “Is the manuscript a candidate for a Special Issue?” and enter “Special Issue on Affective Design using Big Data” in the accompanying text box.)

Footnotes

 1 S.H. Kim and Y.J. Lee, The User Experience of Smart-Phone Information Hierarchy and Screen Transition Patterns, International Journal of Multimedia and Ubiquitous Engineering, vol.11, no.4, pp. 293-302, 2016.

2 IBM 2015, Big Data and Analytics, http://www-01.ibm.com/software/data/bigdata/what-is-big-data.html 3 P. Hitzler and K. Janowicz, Linked data, big data, and the 4th paradigm, Semantic Web vol. 4, no. 3, pp. 233-235, 2013. 

3 P. Hitzler and K. Janowicz, Linked data, big data, and the 4th paradigm, Semantic Web vol. 4, no. 3, pp. 233-235, 2013. 

Editorial information

  • Guest Editor: Kit Yan Chan, Department of Electrical and Computer Engineering, Curtin University, Australia (kit.chan@curtin.edu.au)
  • Guest Editor: C.K Kwong, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong (c.k.kwong@polyu.edu.hk)
  • Guest Editor: T.C. Wong, Department of Design, Manufacture, and Engineering Management, University of Strathclyde, United Kingdom (andy.wong@strath.ac.uk)