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Article
Publication date: 26 November 2021

Zijun Mao, Jingyi Wu, Yali Qiao and Hong Yao

The present paper constructed a new framework for government data governance based on the concept of a data middle platform to elicit the detailed requirements and…

Abstract

Purpose

The present paper constructed a new framework for government data governance based on the concept of a data middle platform to elicit the detailed requirements and functionalities of a government data governance framework.

Design/methodology/approach

Following a three-cycle activity, the design science research (DSR) paradigm was used to develop design propositions. The design propositions are obtained based on a systematic literature review of government data governance and data governance frameworks. Cases and experts further assessed the effectiveness of the implementation of the artifacts.

Findings

The study developed an effective framework for government data governance that supported the digital service needs of the government. The results demonstrated the advantages of the framework in adapting to organizational operations and data, realized the value of data assets, improved data auditing and oversight and facilitated communication. From the collection of data to the output of government services, the framework adapted to the new characteristics of digital government.

Originality/value

Knowledge of the “data middle platforms” generated in this study provides new knowledge to the design of government data governance frameworks and helps translate design propositions into concrete capabilities. By reviewing earlier literature, the article identified the core needs and challenges of government data governance to help practitioners approach government data governance in a structured manner.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

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Article
Publication date: 3 September 2021

Anca C. Yallop, Oana A. Gică, Ovidiu I. Moisescu, Monica M. Coroș and Hugues Séraphin

Big data and analytics are being increasingly used by tourism and hospitality organisations (THOs) to provide insights and to inform critical business decisions…

Abstract

Purpose

Big data and analytics are being increasingly used by tourism and hospitality organisations (THOs) to provide insights and to inform critical business decisions. Particularly in times of crisis and uncertainty data analytics supports THOs to acquire the knowledge needed to ensure business continuity and the rebuild of tourism and hospitality sectors. Despite being recognised as an important source of value creation, big data and digital technologies raise ethical, privacy and security concerns. This paper aims to suggest a framework for ethical data management in tourism and hospitality designed to facilitate and promote effective data governance practices.

Design/methodology/approach

The paper adopts an organisational and stakeholder perspective through a scoping review of the literature to provide an overview of an under-researched topic and to guide further research in data ethics and data governance.

Findings

The proposed framework integrates an ethical-based approach which expands beyond mere compliance with privacy and protection laws, to include other critical facets regarding privacy and ethics, an equitable exchange of travellers’ data and THOs ability to demonstrate a social license to operate by building trusting relationships with stakeholders.

Originality/value

This study represents one of the first studies to consider the development of an ethical data framework for THOs, as a platform for further refinements in future conceptual and empirical research of such data governance frameworks. It contributes to the advancement of the body of knowledge in data ethics and data governance in tourism and hospitality and other industries and it is also beneficial to practitioners, as organisations may use it as a guide in data governance practices.

Details

Journal of Consumer Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0736-3761

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Article
Publication date: 27 July 2021

Sadra Ahmadi, Mohammad Mahdi Tavana, Sajjad Shokouhyar and Mina Dortaj

The purpose of this paper is to propose an approach for managing relevant factors and activities for implementing data governance in an organization. The process of…

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60

Abstract

Purpose

The purpose of this paper is to propose an approach for managing relevant factors and activities for implementing data governance in an organization. The process of assessing the establishment of data governance in an organization is intrinsically imprecise, due to the characteristics of new problem settings, particularly in relation to newly generated alternatives or vaguely defined qualitative assessment criteria.

Design/methodology/approach

To reject the inherent subjectiveness and imprecision involved in the evaluation process, the authors use the concept of fuzzy logic in this approach for developing the assessment model and analyzing the model for allocating the management efforts in the most efficient way to improve the data governance deployment level.

Findings

This paper identifies relevant factors and activities for implementing data governance in an organization and evaluates the state of data governance based on causal relationships between influential factors. In this study, factors are prioritized for effective allocation of limited management efforts in any improvement plan.

Research limitations/implications

The interrelationships among factors are contextual and based on the perceptions of experts who may be biased as per their background and area of expertise. Meanwhile, lack of a data governance plan may cause failure during its implementation in an organization, as the worth of an organization's data will not be determined precisely. The paper has tremendous practical implications for organizations that intend to implement the data governance program and evaluate its state to design an improvement plan.

Originality/value

The paper proposes an approach for implementing data governance in an organization faced with limited resources for improvement.

Details

The TQM Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-2731

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Book part
Publication date: 8 July 2020

Uma Gupta and San Cannon

Abstract

Details

A Practitioner's Guide to Data Governance
Type: Book
ISBN: 978-1-78973-567-3

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Article
Publication date: 5 March 2018

Emily M. Coyne, Joshua G. Coyne and Kenton B. Walker

Big Data has become increasingly important to multiple facets of the accounting profession, but accountants have little understanding of the steps necessary to convert Big…

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4426

Abstract

Purpose

Big Data has become increasingly important to multiple facets of the accounting profession, but accountants have little understanding of the steps necessary to convert Big Data into useful information. This limited understanding creates a gap between what accountants can do and what accountants should do to assist in Big Data information governance. The study aims to bridge this gap in two ways.

Design/methodology/approach

First, the study introduces a model of the Big Data life cycle to explain the process of converting Big Data into information. Knowledge of this life cycle is a first step toward enabling accountants to engage in Big Data information governance. Second, it highlights informational and control risks inherent to this life cycle, and identifies information governance activities and agents that can minimize these risks.

Findings

Because accountants have a strong ability to identify the informational and control needs of internal and external decision-makers, they should play a significant role in Big Data information governance.

Originality/value

This model of the Big Data life cycle and information governance provides a first attempt to formalize knowledge that accountants need in a new field of the accounting profession.

Details

International Journal of Accounting & Information Management, vol. 26 no. 1
Type: Research Article
ISSN: 1834-7649

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Article
Publication date: 12 June 2017

Victor Were and Christopher Moturi

The purpose of this paper is to determine the status, drivers, and barriers to data governance at the health professional regulatory authorities in Kenya. This study aims…

Abstract

Purpose

The purpose of this paper is to determine the status, drivers, and barriers to data governance at the health professional regulatory authorities in Kenya. This study aims to develop a model that can be used to establish a formal data governance program at these regulatory authorities.

Design/methodology/approach

This study used data governance decision areas based on the study of Khatri and Brown (2010). Qualitative and quantitative research methods were used in this study to collect data.

Findings

This paper identified maintenance of quality of data, achieving customer satisfaction, ensuring data security and control, and achieving operational efficiency as the drivers of data governance at the regulatory authorities. The authorities are faced with lack of data governance awareness, lack of management ownership and support, as well as limited funding and resource allocations as barriers to data governance. This study proposed that for the authorities to increase their data governance, they need to identify their data as an asset, initiate more data quality management mechanism, restrict access to their data, create awareness, and increase management, ownership and support.

Practical implications

A data governance program for healthcare workforce data is necessary for healthcare planning which influences national policy in the healthcare and the overall delivery of health services in a country.

Originality/value

The paper proposes a model that health professional regulators in developing countries that are facing limited resources can be used to establish a formal data governance program.

Details

The TQM Journal, vol. 29 no. 4
Type: Research Article
ISSN: 1754-2731

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Article
Publication date: 24 August 2012

Hong‐Linh Truong and Schahram Dustdar

The purpose of this paper is to examine how cloud‐based information systems and services can support emerging and future requirements for sustainability governance of facilities.

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1227

Abstract

Purpose

The purpose of this paper is to examine how cloud‐based information systems and services can support emerging and future requirements for sustainability governance of facilities.

Design/methodology/approach

The authors present basic elements of cloud‐based sustainability governance platforms, conduct a survey of existing industrial platforms and research works, discuss distinguishable and common characteristics of cloud computing platforms for sustainability governance, and give views on future research.

Findings

Cloud computing emerges as a potential candidate for supporting sustainability governance. However, several techniques must be provided in order to support multiple stakeholders, complex analysis and compliance processes.

Research limitations/implications

The number of industrial platforms and research works in the survey is limited, as is information about industrial platforms. Furthermore, industrial platforms are continuously updated, thus some information might be outdated.

Originality/value

There exists no survey for understanding how cloud computing could be used for sustainability governance. The paper not only helps to understand state‐of‐the‐art in using cloud computing for sustainability governance but also discusses main components, stakeholders and requirements for cloud‐based sustainability governance platforms.

Details

International Journal of Web Information Systems, vol. 8 no. 3
Type: Research Article
ISSN: 1744-0084

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Article
Publication date: 5 March 2018

Ibrahim Alhassan, David Sammon and Mary Daly

The purpose of this paper is to explore the current literature on data governance in scientific and practice-oriented publications, and to provide a comparative analysis…

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1886

Abstract

Purpose

The purpose of this paper is to explore the current literature on data governance in scientific and practice-oriented publications, and to provide a comparative analysis of the activities reported for data governance. Data have become a key organisational asset and data governance both a necessary and critical activity.

Design/methodology/approach

A comprehensive literature review is conducted in order to identify the published material that reflects the current state of knowledge. A systematic procedure was followed that identified 61 publications that explicitly mention data governance activities. Open coding techniques were applied to conduct content analysis, resulting in the identification of 591 concepts. A critical analysis also identified gaps in the literature.

Findings

The analysis identified 120 data governance activities which are understood as: “action” plus “area of governance” plus “decision domain” (e.g. define data policies for data quality). The authors define and present a data governance activities model based on the analysis. The analysis also shows a higher volume of data governance activities reported by practice-oriented publications that are associated with the “implement” and “monitor” actions of the areas of governance across the decision domains compared with scientific publications, whereas The authors found that the scientific publications focus more on defining activities. The results contribute to identifying research gaps and concerns on which ongoing and future research efforts can be focused.

Research limitations/implications

This paper is of interest to both academics and practitioners, as it helps them understand the activities associated with a data governance programme. Current literature fails to provide a comprehensive understanding of the data governance activities that are required when considering a data governance programme. Therefore, the proposed model for data governance activities can be used to give insights into these activities.

Originality/value

To the knowledge of the authors, this study is the first to explicitly consider data governance activities from both an academic and practice-oriented perspective.

Details

Journal of Enterprise Information Management, vol. 31 no. 2
Type: Research Article
ISSN: 1741-0398

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Book part
Publication date: 8 July 2020

Uma Gupta and San Cannon

Abstract

Details

A Practitioner's Guide to Data Governance
Type: Book
ISBN: 978-1-78973-567-3

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Book part
Publication date: 25 November 2019

Tavis D. Jules

With the advent of the fourth industrial revolution and the intelligent economy, this conceptual chapter explores the evolution of educational governance from one based on…

Abstract

With the advent of the fourth industrial revolution and the intelligent economy, this conceptual chapter explores the evolution of educational governance from one based on governing by numbers and evidence-based governance to one constituted around governance by data or data-based educational governance. With the rise of markets and networks in education, Big Data, machine data, high-dimension data, open data, and dark data have consequences for the governance of national educational systems. In doing so, it draws attention to the rise of the algorithmization and computerization of educational policy-making. The author uses the concept of “blitzscaling”, aided by the conceptual framing of assemblage theory, to suggest that we are witnessing the rise of a fragmented model of educational governance. I call this governance with a “big G” and governance with a “small g.” In short, I suggest that while globalization has led to the deterritorializing of the national state, data educational governance, an assemblage, is bringing about the reterritorialization of things as new material projects are being reconstituted.

Details

The Educational Intelligent Economy: Big Data, Artificial Intelligence, Machine Learning and the Internet of Things in Education
Type: Book
ISBN: 978-1-78754-853-4

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