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Available. Open Access. Open Access
Article
Publication date: 14 March 2022

Luke McCully, Hung Cao, Monica Wachowicz, Stephanie Champion and Patricia A.H. Williams

A new research domain known as the Quantified Self has recently emerged and is described as gaining self-knowledge through using wearable technology to acquire information on…

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Abstract

Purpose

A new research domain known as the Quantified Self has recently emerged and is described as gaining self-knowledge through using wearable technology to acquire information on self-monitoring activities and physical health related problems. However, very little is known about the impact of time window models on discovering self-quantified patterns that can yield new self-knowledge insights. This paper aims to discover the self-quantified patterns using multi-time window models.

Design/methodology/approach

This paper proposes a multi-time window analytical workflow developed to support the streaming k-means clustering algorithm, based on an online/offline approach that combines both sliding and damped time window models. An intervention experiment with 15 participants is used to gather Fitbit data logs and implement the proposed analytical workflow.

Findings

The clustering results reveal the impact of a time window model has on exploring the evolution of micro-clusters and the labelling of macro-clusters to accurately explain regular and irregular individual physical behaviour.

Originality/value

The preliminary results demonstrate the impact they have on finding meaningful patterns.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

Available. Open Access. Open Access
Article
Publication date: 10 March 2022

Luigi Corvo, Lavinia Pastore, Marco Mastrodascio and Denita Cepiku

Social return on investment (SROI) has received increasing attention, both academically and professionally, since it was initially developed by the Roberts Enterprise Development…

13565

Abstract

Purpose

Social return on investment (SROI) has received increasing attention, both academically and professionally, since it was initially developed by the Roberts Enterprise Development Fund in the USA in the mid-1990s. Based on a systematic review of the literature that highlights the potential and limitations related to the academic and professional development of the SROI model, the purpose of this study is to systematize the academic debate and contribute to the future research agenda of blended value accounting.

Design/methodology/approach

Relying on the preferred reporting items for systematic reviews and meta-analyses approach, this study endeavors to provide reliable academic insights into the factors driving the usage of the SROI model and its further development.

Findings

A systematic literature review produced a final data set of 284 studies. The results reveal that despite the procedural accuracy characterizing the description of the model, bias-driven methodological implications, availability of resources and sector specificities can influence the type of approach taken by scholars and practitioners.

Research limitations/implications

To dispel the conceptual and practical haze, this study discusses the results found, especially regarding the potential solutions offered to overcome the SROI limitations presented, as well as offers suggestions for future research.

Originality/value

This study aims to fill a gap in the literature and enhance a conceptual debate on the future of accounting when it concerns a blended value proposition.

Details

Meditari Accountancy Research, vol. 30 no. 7
Type: Research Article
ISSN: 2049-372X

Keywords

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