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Book part
Publication date: 11 April 2019

Ann Langley and Davide Ravasi

In this chapter, the authors discuss how visual artifacts may support the analysis and interpretation of qualitative data in organization studies. They draws on their own…

Abstract

In this chapter, the authors discuss how visual artifacts may support the analysis and interpretation of qualitative data in organization studies. They draws on their own experience as well as other scholars’ published work to explore the distinctive affordances of visual forms. In particular, the authors identify four roles – namely “mapping,” “analyzing,” “conceptualizing,” and “communicating” – that visual artifacts play to help us move from raw qualitative data to a compelling conceptual product.

Specifically, the use of visuals for “mapping” involves directly coding data into visual forms such as cognitive maps, flow charts or relational diagrams, an approach that may offer a useful complement to traditional verbal coding. Using visuals for “analyzing” implies either comparing, aggregating or decomposing previously constructed visual maps, or drawing directly on verbal data to develop visuals such as analytical flow charts, process replication maps, and trend charts. Using visuals for “conceptualizing” involves rising above the data to develop more abstract representations of concepts and relationships, while maintaining recognizable connections to empirical phenomena. While conceptual models can take a wide variety of forms, the authors illustrate, in particular, the use of visuals to represent linear, dialectic and multi-level process theories. Finally, the authors consider the importance of visualizations for “communicating” insights as well as for developing them, and the inextricable linkages between the two.

The authors conclude by discussing some of the strengths and weaknesses of visualization and by considering how new technologies may offer further possibilities for useful and insightful visual representations of qualitative data that can enhance theory-building.

Details

The Production of Managerial Knowledge and Organizational Theory: New Approaches to Writing, Producing and Consuming Theory
Type: Book
ISBN: 978-1-78769-183-4

Keywords

Article
Publication date: 15 July 2014

Victoria Louise Lemieux, Brianna Gormly and Lyse Rowledge

This paper aims to explore the role of records management in supporting the effective use of information visualisation and visual analytics (VA) to meet the challenges…

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Abstract

Purpose

This paper aims to explore the role of records management in supporting the effective use of information visualisation and visual analytics (VA) to meet the challenges associated with the analysis of Big Data.

Design/methodology/approach

This exploratory research entailed conducting and analysing interviews with a convenience sample of visual analysts and VA tool developers, affiliated with a major VA institute, to gain a deeper understanding of data-related issues that constrain or prevent effective visual analysis of large data sets or the use of VA tools, and analysing key emergent themes related to data challenges to map them to records management controls that may be used to address them.

Findings

The authors identify key data-related issues that constrain or prevent effective visual analysis of large data sets or the use of VA tools, and identify records management controls that may be used to address these data-related issues.

Originality/value

This paper discusses a relatively new field, VA, which has emerged in response to meeting the challenge of analysing big, open data. It contributes a small exploratory research study aimed at helping records professionals understand the data challenges faced by visual analysts and, by extension, data scientists for the analysis of large and heterogeneous data sets. It further aims to help records professionals identify how records management controls may be used to address data issues in the context of VA.

Details

Records Management Journal, vol. 24 no. 2
Type: Research Article
ISSN: 0956-5698

Keywords

Book part
Publication date: 13 June 2013

Li Xiao, Hye-jin Kim and Min Ding

Purpose – The advancement of multimedia technology has spurred the use of multimedia in business practice. The adoption of audio and visual data will accelerate as…

Abstract

Purpose – The advancement of multimedia technology has spurred the use of multimedia in business practice. The adoption of audio and visual data will accelerate as marketing scholars become more aware of the value of audio and visual data and the technologies required to reveal insights into marketing problems. This chapter aims to introduce marketing scholars into this field of research.Design/methodology/approach – This chapter reviews the current technology in audio and visual data analysis and discusses rewarding research opportunities in marketing using these data.Findings – Compared with traditional data like survey and scanner data, audio and visual data provides richer information and is easier to collect. Given these superiority, data availability, feasibility of storage, and increasing computational power, we believe that these data will contribute to better marketing practices with the help of marketing scholars in the near future.Practical implications: The adoption of audio and visual data in marketing practices will help practitioners to get better insights into marketing problems and thus make better decisions.Value/originality – This chapter makes first attempt in the marketing literature to review the current technology in audio and visual data analysis and proposes promising applications of such technology. We hope it will inspire scholars to utilize audio and visual data in marketing research.

Details

Review of Marketing Research
Type: Book
ISBN: 978-1-78190-761-0

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Article
Publication date: 10 August 2018

Mohammad Kamel Daradkeh

Visual analytics is increasingly becoming a prominent technology for organizations seeking to gain knowledge and actionable insights from heterogeneous and big data to…

1252

Abstract

Purpose

Visual analytics is increasingly becoming a prominent technology for organizations seeking to gain knowledge and actionable insights from heterogeneous and big data to support decision-making. Whilst a broad range of visual analytics platforms exists, limited research has been conducted to explore the specific factors that influence their adoption in organizations. The purpose of this paper is to develop a framework for visual analytics adoption that synthesizes the factors related to the specific nature and characteristics of visual analytics technology.

Design/methodology/approach

This study applies a directed content analysis approach to online evaluation reviews of visual analytics platforms to identify the salient determinants of visual analytics adoption in organizations from the standpoint of practitioners. The online reviews were gathered from Gartner.com, and included a sample of 1,320 reviews for six widely adopted visual analytics platforms.

Findings

Based on the content analysis of online reviews, 34 factors emerged as key predictors of visual analytics adoption in organizations. These factors were synthesized into a conceptual framework of visual analytics adoption based on the diffusion of innovations theory and technology–organization–environment framework. The findings of this study demonstrated that the decision to adopt visual analytics technologies is not merely based on the technological factors. Various organizational and environmental factors have also significant influences on visual analytics adoption in organizations.

Research limitations/implications

This study extends the previous work on technology adoption by developing an adoption framework that is aligned with the specific nature and characteristics of visual analytics technology and the factors involved to increase the utilization and business value of visual analytics in organizations.

Practical implications

This study highlights several factors that organizations should consider to facilitate the broad adoption of visual analytics technologies among IT and business professionals.

Originality/value

This study is among the first to use the online evaluation reviews to systematically explore the main factors involved in the acceptance and adoption of visual analytics technologies in organizations. Thus, it has potential to provide theoretical foundations for further research in this important and emerging field. The development of an integrative model synthesizing the salient determinants of visual analytics adoption in enterprises should ultimately allow both information systems researchers and practitioners to better understand how and why users form perceptions to accept and engage in the adoption of visual analytics tools and applications.

Details

Information Technology & People, vol. 32 no. 3
Type: Research Article
ISSN: 0959-3845

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Article
Publication date: 1 September 2004

A.D. Songer, B. Hays and C. North

The construction industry produces voluminous quantitative data. Much of this data is created during the controls phase of projects and relates to cost, schedule, and…

Abstract

The construction industry produces voluminous quantitative data. Much of this data is created during the controls phase of projects and relates to cost, schedule, and administrative information. Recent storage and processing advances in computers as well as display capabilities afforded by computer graphics increase the opportunity to monitor projects fundamentally different from existing project control systems. However, changes in project control methods have been slow to evolve. The lack of a fundamental model of project control data representation contributes to the inadequate application and implementation of visual tools in project control methods. Difficulties associated with the graphical representation of data can be traced to the diversity of skills required in creating visual information displays. Owing to the reality that not all engineers/constructors possess these attributes in great strength, streamlining the process of how to best visualize data is important. Visual representations of data hold great potential for reducing communication difficulties fostered by industry fragmentation. However, without information structure, organization, and visual explanations, the massive amount of data available to project managers results in information overload. Therefore, improved information displays are needed to overcome the possibility of information overload with the capability of human perception. This paper discusses research to create a framework for visual representation of construction project data. Underlying visualization theory, the visual framework, and a detailed implementation are provided.

Details

Construction Innovation, vol. 4 no. 3
Type: Research Article
ISSN: 1471-4175

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Article
Publication date: 15 June 2020

Abdelhak Belhi, Abdelaziz Bouras, Abdulaziz Khalid Al-Ali and Sebti Foufou

Digital tools have been used to document cultural heritage with high-quality imaging and metadata. However, some of the historical assets are totally or partially…

Abstract

Purpose

Digital tools have been used to document cultural heritage with high-quality imaging and metadata. However, some of the historical assets are totally or partially unlabeled and some are physically damaged, which decreases their attractiveness and induces loss of value. This paper introduces a new framework that aims at tackling the cultural data enrichment challenge using machine learning.

Design/methodology/approach

This framework focuses on the automatic annotation and metadata completion through new deep learning classification and annotation methods. It also addresses issues related to physically damaged heritage objects through a new image reconstruction approach based on supervised and unsupervised learning.

Findings

The authors evaluate approaches on a data set of cultural objects collected from various cultural institutions around the world. For annotation and classification part of this study, the authors proposed and implemented a hierarchical multimodal classifier that improves the quality of annotation and increases the accuracy of the model, thanks to the introduction of multitask multimodal learning. Regarding cultural data visual reconstruction, the proposed clustering-based method, which combines supervised and unsupervised learning is found to yield better quality completion than existing inpainting frameworks.

Originality/value

This research work is original in sense that it proposes new approaches for the cultural data enrichment, and to the authors’ knowledge, none of the existing enrichment approaches focus on providing an integrated framework based on machine learning to solve current challenges in cultural heritage. These challenges, which are identified by the authors are related to metadata annotation and visual reconstruction.

Details

Journal of Enterprise Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0398

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Book part
Publication date: 9 July 2018

Janine Pierce

The purpose of this paper was to examine and reflect on the visual social research method of photovoice, which is a qualitative research process increasingly being used by…

Abstract

The purpose of this paper was to examine and reflect on the visual social research method of photovoice, which is a qualitative research process increasingly being used by government and nongovernment organizations to enable participants who are often from disadvantaged groups, to capture their lives, experiences, and issues through photos and associated written stories. Visual methods such as photovoice provide both opportunities and risks with ethical considerations and concerns that are both ethical in nature for those taking the photographs, and for those in the photographs. There are also associated ethical challenges for researchers to conform to ethical guidelines, while conveying stories that are in the public interest. Ascertaining why visual information should be considered in relation to ethics can be argued as important, as the receiver processing the visual information will process, perceive, and respond in a variety of ways, and possibly in different ways to what the sender aimed to convey. It was argued here that due to the strong ethical guidelines for photovoice projects, it is more of a deontological-based research approach. A key ethical concern associated with photovoice is that it is touted to participants as a vehicle to achieve social change, yet there is no guarantee that this change will occur, as ultimate power rests in the hands of decision makers. Photovoice ethical processes were discussed, with reflections by the author on ethical issues that have occurred in her own research, and suggestions to organizations on what to consider to ensure a photovoice project proceeds with ethical consideration to ensure an empowering experience as an influencer for social change.

Details

Visual Ethics
Type: Book
ISBN: 978-1-78756-165-6

Keywords

Book part
Publication date: 10 April 2019

Eric Knight and Sotirios Paroutis

Visuals are a crucial part of strategizing, whether it be through the use of body gesture, the crafting of strategy presentations, or the use of new media technologies…

Abstract

Visuals are a crucial part of strategizing, whether it be through the use of body gesture, the crafting of strategy presentations, or the use of new media technologies from videoconferencing through to data visualization. Yet studying these aspects of the strategy process is methodologically challenging and requires careful attention to how the data is collected and what questions the data analysis can address. In this chapter, we lay out choices for scholars and the opportunities these afford to new and promising agendas in strategy and management research.

Details

Standing on the Shoulders of Giants
Type: Book
ISBN: 978-1-78756-336-0

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Article
Publication date: 5 September 2017

Catherine P. Killen

The purpose of this paper is to improve decision quality, and therefore project and portfolio success, by testing the influence of different visual representations of…

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Abstract

Purpose

The purpose of this paper is to improve decision quality, and therefore project and portfolio success, by testing the influence of different visual representations of interdependency data in a simulated decision experiment. A network mapping approach to visualize project interdependencies is introduced and compared with matrix and tabular displays.

Design/methodology/approach

A simulated decision task in a controlled classroom setting tested five hypotheses though a sample of 480 experiments.

Findings

The type of data representation used is associated with differing levels of decision quality, and the use of network mapping displays is aligned with the best results.

Research limitations/implications

The findings are limited as this experiment-based study presented a simplified decision scenario and involved students rather than practicing managers. The findings are best interpreted in combination with organization-based research.

Practical implications

The findings of this study suggest that visual data displays, particularly network mapping displays, can provide benefits and improve project portfolio decision quality. Managers may draw upon this study to design ways to include visual data representations in their project portfolio management decision processes.

Originality/value

This study uses experimentation to complement organization-based studies to better understand the influence of different methods of visualizing data and managing interdependencies between projects. This research provides an important contribution to meet the acknowledged need for better tools to understand and manage project interdependencies.

Details

International Journal of Managing Projects in Business, vol. 10 no. 4
Type: Research Article
ISSN: 1753-8378

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Book part
Publication date: 5 June 2020

Alice Neeson

Participatory research approaches often involve visual methods. However, when it comes to data analysis, the opportunities and challenges of participatory visual methods…

Abstract

Participatory research approaches often involve visual methods. However, when it comes to data analysis, the opportunities and challenges of participatory visual methods remain underexplored. A focus on the process of data collection, rather than the data itself, may lead to the omission of a formal analysis stage. In action-orientated research, analysis is often discussion-based and undocumented. As a result, the intended ‘meaning’ behind visual data may not be explicitly communicated to audiences. This chapter explores the ethical considerations of sharing raw visual data. It considers the significance of inter-textual meanings in the digital age, where pathways to accessing that data are highly individualised, and consequently constructed meanings may radically diverge from intended meanings. It also suggests how participatory research facilitators can minimise radical divergence between intention and interpretation.

Details

Ethics and Integrity in Visual Research Methods
Type: Book
ISBN: 978-1-78769-420-0

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