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Article
Publication date: 17 August 2021

One-Ki Daniel Lee, Ramakrishna Ayyagari, Farzaneh Nasirian and Mohsen Ahmadian

The rapid growth of artificial intelligence (AI)-based voice-assistant systems (VASs) has created many opportunities for individuals to use VASs for various purposes in…

Abstract

Purpose

The rapid growth of artificial intelligence (AI)-based voice-assistant systems (VASs) has created many opportunities for individuals to use VASs for various purposes in their daily lives. However, traditional quality success factors, such as information quality and system quality, may not be sufficient in explaining the adoption and use of AI-based VASs. This study aims to propose interaction quality as an additional, yet more important quality measure that leads to trust in an AI-based VAS and its adoption.

Design/methodology/approach

The authors propose a research model that highlights the importance of interaction quality and trust as underlying mechanisms in the adoption of AI-based VASs. Based on survey methodology and data from 221 respondents, the proposed research model is tested with a partial least squares approach.

Findings

The results suggest that interaction quality and trust are critical factors influencing the adoption of AI-based VASs. The findings also indicate that the impacts of traditional quality factors (i.e. information quality and system quality) occur through interaction quality in the context of AI-based VASs.

Originality/value

This research adds interaction quality as a new quality factor to the traditional quality factors in the information systems success model. Further, given the interactive nature of VASs, the authors use social response theory to explain the importance of the trust mechanism when individuals interact with AI-based VASs.

Contribution to Impact

Details

Journal of Systems and Information Technology, vol. 23 no. 2
Type: Research Article
ISSN: 1328-7265

Keywords

Article
Publication date: 30 December 2020

Luís Sanhudo, João Poças Martins, Nuno M.M. Ramos, Ricardo M.S.F. Almeida, Ana Rocha, Débora Pinto, Eva Barreira and M. Lurdes Simões

This paper aims to further the discussion on Building Information Modelling (BIM) legal requirements, providing a framework with key energy parameters capable of…

Abstract

Purpose

This paper aims to further the discussion on Building Information Modelling (BIM) legal requirements, providing a framework with key energy parameters capable of supporting the Appointing Party in the definition of the Exchange Information Requirements (EIR) for a BIM project appointment. The EIR is described in ISO-19650–1:2018 as a fundamental step in the information delivery cycle.

Design/methodology/approach

A literature review on the topic of BIM energy analysis was completed to identify current knowledge gaps and support the need for the proposed framework. Afterwards, the framework was established based on the review findings and the authors’ domain knowledge. The applicability of the proposed framework was assessed through a case study, where several energy simulations were performed in three different design stages of the same BIM model.

Findings

This study identified a lack of standards and legislation capable of supporting the Appointing Party in the definition of energy-related BIM requirements. To this end, a new framework is proposed to mediate existing practices, linking prior knowledge with BIM’s new reality. The study showcases the applicability of the framework, identifying that the performance of different energy studies involves distinct Level of Development (LOD) requirements, which in turn have an impact on the modelling time and cost.

Originality/value

A BIM framework for the specification of information requirements in energy-related projects was developed to support the Appointing Party. The framework presents appropriate parameters for energy analysis in each design stage, as well as the suitable LOD for the BIM model.

Details

Engineering, Construction and Architectural Management, vol. 28 no. 10
Type: Research Article
ISSN: 0969-9988

Keywords

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