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Sweidan, D., Johansson, U., Alenljung, B. & Gidenstam, A. (2023). Improved Decision Support for Product Returns using Probabilistic Prediction. In: : . Paper presented at The 19th International Conference on Data Science (ICDATA’23), July 24-27, 2023 - Las Vegas, Nevada, USA.
Open this publication in new window or tab >>Improved Decision Support for Product Returns using Probabilistic Prediction
2023 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Product returns are not only costly for e-tailers, but the unnecessary transports also impact the environment. Consequently, online retailers have started to formulate policies to reduce the number of returns. Determining when and how to act is, however, a delicate matter, since a too harsh approach may lead to not only the order being cancelled, but also the customer leaving the business. Being able to accurately predict which orders that will lead to a return would be a strong tool, guiding which actions to be taken. This paper addresses the problem of data-driven product return prediction, by conducting a case study using a large real-world data set. The main results are that well-calibrated probabilistic predictors are essential for providing predictions with high precision and reasonable recall. This implies that utilizing calibrated models to predict some instances, while rejecting to predict others can be recommended. In practice, this would make it possible for a decision-maker to only act upon a subset of all predicted returns, where the risk of a return is very high.

Keywords
Product Returns, Decision Support, Probabilistic Predictions, Calibration, Predict with Reject Option.
National Category
Computer and Information Sciences Information Systems Probability Theory and Statistics Business Administration
Research subject
INF301 Data Science; Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-23269 (URN)
Conference
The 19th International Conference on Data Science (ICDATA’23), July 24-27, 2023 - Las Vegas, Nevada, USA
Projects
INSiDR
Funder
Knowledge Foundation, 20160035, 20170215
Note

©2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Available from: 2023-09-29 Created: 2023-09-29 Last updated: 2023-10-03
Lindblom, J. & Alenljung, B. (2023). The Quest for Appropriate Human-Robot Interaction Strategies in Industrial Contexts. In: Andrew Thomas; Lyndon Murphy; Wyn Morris; Vincenzo Dispenza; David Jones (Ed.), Advances in Manufacturing Technology XXXVI: Proceedings of the 20th International Conference on Manufacturing Research, Incorporating the 37th National Conference on Manufacturing Research,  6th – 8th September 2023, Aberystwyth University, UK. Paper presented at The 20th International Conference on Manufacturing Research, 6th – 8th September 2023, Aberystwyth University, UK (pp. 87-92). Amsterdam, Netherlands: IOS Press
Open this publication in new window or tab >>The Quest for Appropriate Human-Robot Interaction Strategies in Industrial Contexts
2023 (English)In: Advances in Manufacturing Technology XXXVI: Proceedings of the 20th International Conference on Manufacturing Research, Incorporating the 37th National Conference on Manufacturing Research,  6th – 8th September 2023, Aberystwyth University, UK / [ed] Andrew Thomas; Lyndon Murphy; Wyn Morris; Vincenzo Dispenza; David Jones, Amsterdam, Netherlands: IOS Press, 2023, p. 87-92Conference paper, Published paper (Refereed)
Abstract [en]

The industrial evolutions require robots to be able to share physical and social space with humans in such a way that interaction and coexistence arepositively experienced by human workers. A prerequisite is the possibility for the human and the robot to mutually perceive, interpret and act on each other's actions and intentions. To achieve this, strategies for human-robot interaction are needed that are adapted to operators’ needs and characteristics in the industrial contexts. In this paper, we aim to present various taxonomies of levels of automation, humanrobot interaction, and human-robot collaboration suggested for the envisioned factories of the future. Based on this foundation, we propose a compass direction for continued research efforts which both zooms in and zooms out on how to develop applicable human-robot interaction strategies that are worker-centric in order to obtain effective, efficient, safe, sustainable, and pleasant human-robot collaboration and coexistence.

Place, publisher, year, edition, pages
Amsterdam, Netherlands: IOS Press, 2023
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 44
Keywords
Interaction strategies, Human-robot interaction, Human-robot collaboration
National Category
Interaction Technologies
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-23463 (URN)10.3233/ATDE230906 (DOI)2-s2.0-85181137728 (Scopus ID)978-1-64368-466-6 (ISBN)978-1-64368-467-3 (ISBN)
Conference
The 20th International Conference on Manufacturing Research, 6th – 8th September 2023, Aberystwyth University, UK
Funder
Vinnova, 2022-03012
Note

CC BY-NC 4.0

Corresponding Author: jessica.lindblom@his.se

This research was financially supported by AIHURO [2022-03012] which is sponsored by Vinnova, Sweden.

Available from: 2023-12-12 Created: 2023-12-12 Last updated: 2024-01-11Bibliographically approved
Alenljung, B., Lindblom, J., Zaragoza-Sundqvist, M. & Hanna, A. (2023). Towards a Framework of Human-Robot Interaction Strategies from an Operator 5.0 Perspective. In: Andrew Thomas; Lyndon Murphy; Wyn Morris; Vincenzo Dispenza; David Jones (Ed.), Advances in Manufacturing Technology XXXVI: Proceedings of the 20th International Conference on Manufacturing Research, Incorporating the 37th National Conference on Manufacturing Research,  6th – 8th September 2023, Aberystwyth University, UK. Paper presented at The 20th International Conference on Manufacturing Research, 6th – 8th September 2023, Aberystwyth University, UK (pp. 81-86). Amsterdam, Netherlands: IOS Press
Open this publication in new window or tab >>Towards a Framework of Human-Robot Interaction Strategies from an Operator 5.0 Perspective
2023 (English)In: Advances in Manufacturing Technology XXXVI: Proceedings of the 20th International Conference on Manufacturing Research, Incorporating the 37th National Conference on Manufacturing Research,  6th – 8th September 2023, Aberystwyth University, UK / [ed] Andrew Thomas; Lyndon Murphy; Wyn Morris; Vincenzo Dispenza; David Jones, Amsterdam, Netherlands: IOS Press, 2023, p. 81-86Conference paper, Published paper (Refereed)
Abstract [en]

The industrial transition to Industrie 4.0 and subsequently Industrie 5.0 requires robots to be able to share physical and social space with humans in such a way that interaction and coexistence are positively experienced by the humans and where it is possible for the human and the robot to mutually perceive, interpret and act on each other's actions and intentions. To achieve this, strategies for humanrobot interaction are needed that are adapted to operators’ needs and characteristics in an industrial context, i.e., Operator 5.0. This paper presents a research design for the development of a framework for human-robot interaction strategies based on ANEMONE, which is an evaluation framework based on activity theory, the seven stages of action model, and user experience (UX) evaluation methodology. At two companies, ANEMONE is applied in two concrete use cases, collaborative kitting and mobile robot platforms for chemical laboratory assignments. The proposed research approach consists of 1) evaluations of existing demonstrators, 2) development of preliminary strategies that are implemented, 3) re-evaluations and 4) cross-analysis of results to produce an interaction strategy framework. The theoretically and empirically underpinned framework-to-be is expected to, in the long run, contribute to a sustainable work environment for Operator 5.0.

Place, publisher, year, edition, pages
Amsterdam, Netherlands: IOS Press, 2023
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 44
Keywords
Industrie 4.0, Industrie 5.0, user experience, Operator 4.0, Operator 5.0, work engagement, human-robot collaboration, human-robot interaction
National Category
Interaction Technologies
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-23462 (URN)10.3233/ATDE230905 (DOI)2-s2.0-85181075648 (Scopus ID)978-1-64368-466-6 (ISBN)978-1-64368-467-3 (ISBN)
Conference
The 20th International Conference on Manufacturing Research, 6th – 8th September 2023, Aberystwyth University, UK
Funder
Vinnova, 2022-03012AFA Insurance, 220244
Note

CC BY-NC 4.0

Corresponding Author: beatrice.alenljung@his.se

This research was financially supported by AIHURO [2022-03012], sponsored by Vinnova, Sweden, and AROA [220244], sponsored by Afa Försäkringar, Sweden.

Available from: 2023-12-12 Created: 2023-12-12 Last updated: 2024-01-11Bibliographically approved
Sweidan, D., Johansson, U., Gidenstam, A. & Alenljung, B. (2022). Predicting Customer Churn in Retailing. In: M. Arif Wani; Mehmed Kantardzic; Vasile Palade; Daniel Neagu; Longzhi Yang; Kit-Yan Chan (Ed.), Proceedings 21st IEEE International Conference on Machine Learning and Applications ICMLA 2022: 12–14 December 2022 Nassau, The Bahamas. Paper presented at 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 12-14 December 2022, Nassau, Bahamas (pp. 635-640). IEEE
Open this publication in new window or tab >>Predicting Customer Churn in Retailing
2022 (English)In: Proceedings 21st IEEE International Conference on Machine Learning and Applications ICMLA 2022: 12–14 December 2022 Nassau, The Bahamas / [ed] M. Arif Wani; Mehmed Kantardzic; Vasile Palade; Daniel Neagu; Longzhi Yang; Kit-Yan Chan, IEEE, 2022, p. 635-640Conference paper, Published paper (Refereed)
Abstract [en]

Customer churn is one of the most challenging problems for digital retailers. With significantly higher costs for acquiring new customers than retaining existing ones, knowledge about which customers are likely to churn becomes essential. This paper reports a case study where a data-driven approach to churn prediction is used for predicting churners and gaining insights about the problem domain. The real-world data set used contains approximately 200 000 customers, describing each customer using more than 50 features. In the pre-processing, exploration, modeling and analysis, attributes related to recency, frequency, and monetary concepts are identified and utilized. In addition, correlations and feature importance are used to discover and understand churn indicators. One important finding is that the churn rate highly depends on the number of previous purchases. In the segment consisting of customers with only one previous purchase, more than 75% will churn, i.e., not make another purchase in the coming year. For customers with at least four previous purchases, the corresponding churn rate is around 25%. Further analysis shows that churning customers in general, and as expected, make smaller purchases and visit the online store less often. In the experimentation, three modeling techniques are evaluated, and the results show that, in particular, Gradient Boosting models can predict churners with relatively high accuracy while obtaining a good balance between precision and recall. 

Place, publisher, year, edition, pages
IEEE, 2022
Keywords
Sales, Case-studies, Churn rates, Correlation, Customer churn prediction, Customer churns, Digital retailing, Feature importance, High costs, RFM analysis, Top probability, Forecasting, correlations, top probabilities
National Category
Software Engineering Business Administration Computer Sciences
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-22430 (URN)10.1109/ICMLA55696.2022.00105 (DOI)000980994900094 ()2-s2.0-85152214345 (Scopus ID)978-1-6654-6283-9 (ISBN)978-1-6654-6284-6 (ISBN)
Conference
2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 12-14 December 2022, Nassau, Bahamas
Funder
Knowledge Foundation, 20160035, 20170215
Note

© 2022 IEEE.

The current research is a part of the Industrial Graduate School in Digital Retailing (INSiDR) at the University of Borås, funded by the Swedish Knowledge Foundation, grants nr. 20160035, 20170215.

Available from: 2023-04-20 Created: 2023-04-20 Last updated: 2023-10-03Bibliographically approved
Alenljung, B., Nalin, K. & Rambusch, J. (2022). The User Experience Design Program: Applying Situated and Embodied Cognition Together With Reflective Teaching. Frontiers in Computer Science, 4, 1-9, Article ID 794400.
Open this publication in new window or tab >>The User Experience Design Program: Applying Situated and Embodied Cognition Together With Reflective Teaching
2022 (English)In: Frontiers in Computer Science, E-ISSN 2624-9898, Vol. 4, p. 1-9, article id 794400Article in journal (Refereed) Published
Abstract [en]

The education of students to become competent user experience designers is a delicate matter as students need to obtain a multitude of knowledge, skills, and judgmental abilities. In this paper, our effort to manage this multiplicity in a bachelor’s program in user experience design is shared along with our experiences and teaching practices influenced by theories of situated and embodied cognition together with reflective teaching. The program was followed up through interviews with eight alumni and a company representative that employs user experience designers. The results show that the program overall works well, although some of the identified issues need to be addressed in the future. The interpretation is that our program curricula and teaching practices are fruitful, which hopefully can contribute to thoughts and discussions for other teachers in the field of user experience design and human-computer interaction.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2022
Keywords
situated cognition, embodied cognition, reflective teaching, user experience design, higher education, human-computer interaction
National Category
Human Computer Interaction Computer and Information Sciences
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-21019 (URN)10.3389/fcomp.2022.794400 (DOI)000804765400001 ()2-s2.0-85128088470 (Scopus ID)
Note

CC BY 4.0

Correspondence: Beatrice Alenljung beatrice.alenljung@his.se

Available from: 2022-03-30 Created: 2022-03-30 Last updated: 2022-06-17Bibliographically approved
Alenljung, B. & Lindblom, J. (2021). Analysing Action and Intention Recognition in Human-Robot Interaction with ANEMONE. In: Masaaki Kurosu (Ed.), Human-Computer Interaction. Interaction Techniques and Novel Applications: Thematic Area, HCI 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings, Part II. Paper presented at 23rd International Conference on Human-Computer Interaction, HCII 2021, Virtual Event, July 24–29, 2021 (pp. 181-200). Cham: Springer, 12763
Open this publication in new window or tab >>Analysing Action and Intention Recognition in Human-Robot Interaction with ANEMONE
2021 (English)In: Human-Computer Interaction. Interaction Techniques and Novel Applications: Thematic Area, HCI 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtual Event, July 24–29, 2021, Proceedings, Part II / [ed] Masaaki Kurosu, Cham: Springer, 2021, Vol. 12763, p. 181-200Conference paper, Published paper (Refereed)
Abstract [en]

The ANEMONE is a methodological approach for user experience (UX) evaluation of action and intention recognition in human-robot interaction that has activity theory as its theoretical lens in combination with the seven stages of action model and UX evaluation methodology. ANEMONE has been applied in a case where a prototype has been evaluated. The prototype was a workstation in assembly in manufacturing consisting of a collaborative robot, a pallet, a tablet, and a workbench, where one operator is working in the same physical space as one robot. The purpose of this paper is to provide guidance on how to use ANEMONE, with a particular focus on the data analysis part, through describing a real example together with lessons learned and recommendations.

Place, publisher, year, edition, pages
Cham: Springer, 2021
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 12763
Keywords
Human-Robot Interaction, Human-Robot Collaboration, User-centered Evaluation, Action Recognition, Intention Recognition, Activity Theory, Seven Stages of Action Model, User Experience (UX)
National Category
Human Computer Interaction
Research subject
INF302 Autonomous Intelligent Systems; Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-20248 (URN)10.1007/978-3-030-78465-2_14 (DOI)000766308400014 ()2-s2.0-85120694190 (Scopus ID)978-3-030-78464-5 (ISBN)978-3-030-78465-2 (ISBN)
Conference
23rd International Conference on Human-Computer Interaction, HCII 2021, Virtual Event, July 24–29, 2021
Projects
AIRSYMBIO-TIC
Funder
Knowledge Foundation, 20140220EU, Horizon 2020
Note

Also part of the Information Systems and Applications, incl. Internet/Web, and HCI book sub series (LNISA, volume 12763)

Available from: 2021-07-27 Created: 2021-07-27 Last updated: 2022-03-31Bibliographically approved
Lindblom, J., Alenljung, B. & Billing, E. (2020). Evaluating the User Experience of Human-Robot Interaction. In: Céline Jost, Brigitte Le Pévédic, Tony Belpaeme, Cindy Bethel, Dimitrios Chrysostomou, Nigel Crook, Marine Grandgeorge, Nicole Mirnig (Ed.), Human-Robot Interaction: Evaluation Methods and Their Standardization (pp. 231-256). Cham: Springer
Open this publication in new window or tab >>Evaluating the User Experience of Human-Robot Interaction
2020 (English)In: Human-Robot Interaction: Evaluation Methods and Their Standardization / [ed] Céline Jost, Brigitte Le Pévédic, Tony Belpaeme, Cindy Bethel, Dimitrios Chrysostomou, Nigel Crook, Marine Grandgeorge, Nicole Mirnig, Cham: Springer, 2020, p. 231-256Chapter in book (Refereed)
Abstract [en]

For social robots, like in all other digitally interactive systems, products, services, and devices, positive user experience (UX) is necessary in order to achieve the intended benefits and societal relevance of human–robot interaction (HRI). The experiences that humans have when interacting with robots have the power to enable, or disable, the robots’ acceptance rate and utilization in society. For a commercial robot product, it is the achieved UX in the natural context when fulfilling its intended purpose that will determine its success. The increased number of socially interactive robots in human environments and their level of participation in everyday activities obviously highlights the importance of systematically evaluating the quality of the interaction from a human-centered perspective. There is also a need for robot developers to acquire knowledge about proper UX evaluation, both in theory and in practice. In this chapter we are asking: What is UX evaluation? Why should UX evaluation be performed? When is it appropriate to conduct a UX evaluation? How could a UX evaluation be carried out? Where could UX evaluation take place? Who should perform the UX evaluation and for whom? The aim is to briefly answer these questions in the context of doing UX evaluation in HRI, highlighting evaluation processes and methods that have methodological validity and reliability as well as practical applicability. We argue that each specific HRI project needs to take the UX perspective into account during the whole development process. We suggest that a more diverse use of methods in HRI will benefit the field, and the future users of social robots will benefit even more.

Place, publisher, year, edition, pages
Cham: Springer, 2020
Series
Springer Series on Bio- and Neurosystems, ISSN 2520-8535, E-ISSN 2520-8543 ; 12
Keywords
User experience, Evaluation, Methods
National Category
Human Computer Interaction
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-18450 (URN)10.1007/978-3-030-42307-0_9 (DOI)978-3-030-42306-3 (ISBN)978-3-030-42307-0 (ISBN)
Projects
SIDUS AIR, Action and intention recognition in human interaction with autonomous systems, funded by the Knowledge Foundation, Stockholm, under SIDUS grant agreement no. 20140220.
Funder
Knowledge Foundation, 20140220
Note

Evaluating the User Experience of Human–Robot Interaction

Available from: 2020-05-14 Created: 2020-05-14 Last updated: 2020-08-27Bibliographically approved
Lindblom, J. & Alenljung, B. (2020). The ANEMONE: Theoretical Foundations for UX Evaluation of Action and Intention Recognitionin Human-Robot Interaction. Sensors, 20(15), Article ID 4284.
Open this publication in new window or tab >>The ANEMONE: Theoretical Foundations for UX Evaluation of Action and Intention Recognitionin Human-Robot Interaction
2020 (English)In: Sensors, E-ISSN 1424-8220, Vol. 20, no 15, article id 4284Article in journal (Refereed) Published
Abstract [en]

The coexistence of robots and humans in shared physical and social spaces is expected toincrease. A key enabler of high-quality interaction is a mutual understanding of each other’s actionsand intentions. In this paper, we motivate and present a systematic user experience (UX) evaluationframework of action and intention recognition between humans and robots from a UX perspective,because there is an identified lack of this kind of evaluation methodology. The evaluationframework is packaged into a methodological approach called ANEMONE (action and intentionrecognition in human robot interaction). ANEMONE has its foundation in cultural-historicalactivity theory (AT) as the theoretical lens, the seven stages of action model, and user experience(UX) evaluation methodology, which together are useful in motivating and framing the workpresented in this paper. The proposed methodological approach of ANEMONE provides guidanceon how to measure, assess, and evaluate the mutual recognition of actions and intentions betweenhumans and robots for investigators of UX evaluation. The paper ends with a discussion, addressesfuture work, and some concluding remarks.

Place, publisher, year, edition, pages
MDPI, 2020
Keywords
human-robot interaction, human-robot collaboration, user-centered, evaluation, action recognition, intention recognition, activity theory, seven stages of action, user experience (UX)
National Category
Human Computer Interaction
Research subject
INF302 Autonomous Intelligent Systems; Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-18862 (URN)10.3390/s20154284 (DOI)000559213800001 ()32752008 (PubMedID)2-s2.0-85088948958 (Scopus ID)
Funder
Knowledge Foundation, 20140220EU, Horizon 2020, 637107
Note

CC BY 4.0 This article belongs to the Special Issue Human-Robot Interaction and Sensors for Social Robotics

Available from: 2020-07-31 Created: 2020-07-31 Last updated: 2022-02-10Bibliographically approved
Andreasson, R., Alenljung, B., Billing, E. & Lowe, R. (2018). Affective Touch in Human–Robot Interaction: Conveying Emotion to the Nao Robot. International Journal of Social Robotics, 10(4), 473-491
Open this publication in new window or tab >>Affective Touch in Human–Robot Interaction: Conveying Emotion to the Nao Robot
2018 (English)In: International Journal of Social Robotics, ISSN 1875-4791, E-ISSN 1875-4805, Vol. 10, no 4, p. 473-491Article in journal (Refereed) Published
Abstract [en]

Affective touch has a fundamental role in human development, social bonding, and for providing emotional support in interpersonal relationships. We present, what is to our knowledge, the first HRI study of tactile conveyance of both positive and negative emotions (affective touch) on the Nao robot, and based on an experimental set-up from a study of human–human tactile communication. In the present work, participants conveyed eight emotions to a small humanoid robot via touch. We found that female participants conveyed emotions for a longer time, using more varied interaction and touching more regions on the robot’s body, compared to male participants. Several differences between emotions were found such that emotions could be classified by the valence of the emotion conveyed, by combining touch amount and duration. Overall, these results show high agreement with those reported for human–human affective tactile communication and could also have impact on the design and placement of tactile sensors on humanoid robots.

Place, publisher, year, edition, pages
Springer, 2018
Keywords
Tactile interaction, Affective touch, Human–robot interaction, Emotion encoding, Emotion decoding, Social emotions, Nao robot
National Category
Human Computer Interaction
Research subject
Interaction Lab (ILAB); INF302 Autonomous Intelligent Systems
Identifiers
urn:nbn:se:his:diva-14563 (URN)10.1007/s12369-017-0446-3 (DOI)000445226600007 ()2-s2.0-85053554592 (Scopus ID)
Projects
Design, textil och hållbar utveckling
Funder
Region Västra Götaland
Available from: 2017-12-07 Created: 2017-12-07 Last updated: 2018-11-16Bibliographically approved
Alenljung, B., Andreasson, R., Lowe, R., Billing, E. & Lindblom, J. (2018). Conveying Emotions by Touch to the Nao Robot: A User Experience Perspective. Multimodal Technologies and Interaction, 2(4), Article ID 82.
Open this publication in new window or tab >>Conveying Emotions by Touch to the Nao Robot: A User Experience Perspective
Show others...
2018 (English)In: Multimodal Technologies and Interaction, ISSN 2414-4088, Vol. 2, no 4, article id 82Article in journal (Refereed) Published
Abstract [en]

Social robots are expected gradually to be used by more and more people in a widerrange of settings, domestic as well as professional. As a consequence, the features and qualityrequirements on human–robot interaction will increase, comprising possibilities to communicateemotions, establishing a positive user experience, e.g., using touch. In this paper, the focus is ondepicting how humans, as the users of robots, experience tactile emotional communication with theNao Robot, as well as identifying aspects affecting the experience and touch behavior. A qualitativeinvestigation was conducted as part of a larger experiment. The major findings consist of 15 differentaspects that vary along one or more dimensions and how those influence the four dimensions ofuser experience that are present in the study, as well as the different parts of touch behavior ofconveying emotions.

Place, publisher, year, edition, pages
MDPI, 2018
National Category
Interaction Technologies
Research subject
Interaction Lab (ILAB); INF302 Autonomous Intelligent Systems
Identifiers
urn:nbn:se:his:diva-16507 (URN)10.3390/mti2040082 (DOI)2-s2.0-85075609001 (Scopus ID)
Funder
Region Västra GötalandKnowledge Foundation, 20140220
Available from: 2018-12-18 Created: 2018-12-18 Last updated: 2022-09-14Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-7554-2301

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