Success of Multi Criteria Decision Support Systems: The Relevance of Trust

Maida, Martina; Maier, Konradin; Obwegeser, Nikolaus; Stix, Volker

doi:10.1109/hicss.2013.503

Cited by 3 publications

(3 citation statements)

References 22 publications

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“…Their findings indicate that perceived ease of use, compatibility and trustworthiness are significant predictors of citizens' intention to adopt technology. Similarly, other studies highlight trust as the key success factor in technology acceptance of multi criteria decision support systems in the case of high impact decisions [20]. We advance this argument and argue decision support can help promote judgment and dialogue with citizens thus providing rich material.…”

Section: Implications Of Researchmentioning

confidence: 53%

Assessing Policy Making for ICT Innovation: A Decision Support Research Agenda

Fitzgerald

Adam

2014

Lecture Notes in Computer Science

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Section: Implications Of Researchmentioning

confidence: 53%

Assessing Policy Making for ICT Innovation: A Decision Support Research Agenda

Fitzgerald

Adam

2014

Lecture Notes in Computer Science

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“…Similarly, other studies highlight trust as the key success factor in technology acceptance of multi-criteria decision-support systems in the case of high impact decisions (Maida et al 2013). We advance this argument and argue decision support can help promote judgment and dialogue with citizens thus providing rich material.…”

Section: Implications Of Researchmentioning

confidence: 53%

Ageing and Technology

2016

Science Studies

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Our present society can be characterized by expectations of reaching old age and thus having a long life: life expectancy has constantly risen for the last 150 years in industrialised countries -mainly due to better living conditions, higher hygienic standards and improved medical care (Schwentker/Vaupel 2011; Hülsken-Giesler/Krings 2015). The high life expectancy we face today is indeed a success for our present ageing society, although it is very often negatively connoted and mainly discussed in the context of a "crisis" in demographic change. Among many similar statistical overviews, the EU Ageing Report 2012 states that "one in three Europeans will be over 65 by 2060. The ratio of working people to the 'inactive' others is shifting from 4 to 1 today to 2 to 1 by 2060" (European Commission 2012: online). The "challenge" of coping with this growing share of "inactive" population has fostered many initiatives by political, social and research institutions (see also Mantovani/Turnheim in this volume) 1 . In the last decades, the field of ageing studies has also driven the attention of scholars from many disciplines in an effort to respond to this alteration in the social structure and in an attempt to reflect and also improve the quality of life for elderly people (e.g. Kriebernegg/Maierhofer 2013; Twigg/Martin 2015). Technological advances have undoubtedly contributed to improve the lives of elderly citizens in numerous aspects and are prominently included in political ambitions to RefeRences

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“…Analysis is often utilized in Card Sorting to analyze card clusters through dendrograms (Baxter et al, 2015;Kaufman & Rousseeuw, 2005). In addition, other advanced statistical techniques can be found in the literature to quantitatively analyze Card Sorting data, such as distance analysis (Katsanos et al, 2019) using similarity matrices (Maida & Obwegeser, 2012). Some of them are represented by heatmaps (Schmettow & Sommer, 2016) to analyze relationships among cards visually.…”

Section: Systematic Literature Reviewmentioning

confidence: 99%

A Supporting Tool for Enhancing User’s Mental Model Elicitation and Decision-Making in User Experience Research

Martín

Macías

2022

International Journal of Human–Computer Interaction

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User Experience (UX) research is intended to find insights and elicit applicable requirements to guide usable designs. Card Sorting is one of the most utilized methods. It is used to uncover the user's mental model and increase the usability of existing products. However, although Card Sorting has been widely utilized, most applications are based on spreadsheets. Furthermore, existing tools are principally intended to obtain qualitative information or customized quantitative outcomes to improve the information architecture. In this paper, a supporting tool based on the Card Sorting method is presented and detailed, including a comprehensive use case showing the main features. The tool implements predictive analysis of results through advanced statistics and machine learning techniques, providing comprehensive reports that enable evaluators and UX researchers to obtain high-level knowledge and important quantitative clues to enhance decision-making. The tool has been evaluated with participants and evaluators, obtaining relevant usability results and feedback.

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Success of Multi Criteria Decision Support Systems: The Relevance of Trust

Cited by 3 publications

References 22 publications

Assessing Policy Making for ICT Innovation: A Decision Support Research Agenda

Assessing Policy Making for ICT Innovation: A Decision Support Research Agenda

Ageing and Technology

A Supporting Tool for Enhancing User’s Mental Model Elicitation and Decision-Making in User Experience Research

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