scholarly journals Converged Reality: A Data Management Research Agenda for a Service-, Cloud-, and Data-Driven Era

2016 ◽  
Author(s):  
Michael Smit
Keyword(s):  
Data Management ◽  
Research Agenda ◽  
Data Driven ◽  
Management Research ◽  
Service Cloud

Intellectual Capital: Who Counts, Controls?

2004 ◽  
Vol 4 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Robin Roslender ◽  
Robin Fincham
Keyword(s):  
Intellectual Capital ◽  
Value Creation ◽  
Business Strategy ◽  
Research Agenda ◽  
Effective Means ◽  
Management Research ◽  
Successful Management

Intellectual capital and related topics including intangibles, innovation, and knowledge have rapidly climbed the management research agenda. Their significance lies in the contribution these assets make to sustained value creation, a central mantra within contemporary business strategy. A premium has been placed on the successful management of such assets, and within this program, the accountancy profession has found itself challenged to devise effective means of counting and controlling them. Driven by a distinctly managerial agenda, the majority of developments within intellectual capital accounting to date have exhibited the negative characteristics that critical accounting researchers associate with the extension of the prevailing accounting calculus into new fields. Nevertheless, in some recent contributions there are indications of how an alternative, more progressive approach, that of intellectual capital self-accounts, might be fashioned. As a consequence, the emergence of intellectual capital may yet provide an opportunity to return to the task of accounting for labor. This aspect of the critical accounting project has become less evident as researchers seeking to promote enabling accounting have directed their focus on a range of “other voices” to be encouraged to tell their own stories “from below.”

scholarly journals DaLiF: a data lifecycle framework for data-driven governments

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Syed Iftikhar Hussain Shah ◽  
Vassilios Peristeras ◽  
Ioannis Magnisalis
Keyword(s):  
Big Data ◽  
Data Management ◽  
Good Governance ◽  
Business Community ◽  
Data Driven ◽  
Governmental Organizations ◽  
Data Lifecycle ◽  
The Government ◽  
Data Ecosystem ◽  
Governance Transparency

AbstractThe public sector, private firms, business community, and civil society are generating data that is high in volume, veracity, velocity and comes from a diversity of sources. This kind of data is known as big data. Public Administrations (PAs) pursue big data as “new oil” and implement data-centric policies to transform data into knowledge, to promote good governance, transparency, innovative digital services, and citizens’ engagement in public policy. From the above, the Government Big Data Ecosystem (GBDE) emerges. Managing big data throughout its lifecycle becomes a challenging task for governmental organizations. Despite the vast interest in this ecosystem, appropriate big data management is still a challenge. This study intends to fill the above-mentioned gap by proposing a data lifecycle framework for data-driven governments. Through a Systematic Literature Review, we identified and analysed 76 data lifecycles models to propose a data lifecycle framework for data-driven governments (DaliF). In this way, we contribute to the ongoing discussion around big data management, which attracts researchers’ and practitioners’ interest.

scholarly journals Progress towards the Development of Research Agenda and the Launch of Knowledge Hub: The WHO Thematic Platform for Health Emergency and Disaster Risk Management Research Network (Health EDRM RN)

2021 ◽  
Vol 18 (9) ◽  
pp. 4959
Author(s):  
Ryoma Kayano ◽  
Shuhei Nomura ◽  
Jonathan Abrahams ◽  
Qudsia Huda ◽  
Emily Y. Y. Chan ◽  
...  
Keyword(s):  
Risk Management ◽  
Research Agenda ◽  
Strong Support ◽  
Disaster Risk ◽  
Disaster Risk Management ◽  
Research Network ◽  
World Health ◽  
Management Research ◽  
Research Activities ◽  
Global Research

In response to the increasing burden of recent health emergencies and disasters, the World Health Organization (WHO) and its partners established the WHO thematic platform for health emergency and disaster risk management research network (health EDRM RN) in 2016, with the purposes of promoting global research collaboration among various stakeholders and enhancing research activities that generate evidence to manage health risks associated with all types of emergencies and disasters. With the strong support and involvement of all WHO regional offices, the health EDRM RN now works with more than 200 global experts and partners to implement its purposes. The 1st and 2nd Core Group Meetings of the health EDRM RN were held on 17–18 October 2019 and 27 November 2020, respectively, to discuss the development of a global research agenda that the health EDRM RN will focus on facilitating, promoting, synthesizing and implementing, taking into account the emergence of the coronavirus disease 2019 (COVID-19) (health EDRM RN research agenda). A focus of the meetings was the establishment of an online platform to share information and knowledge, including the databases that the health EDRM RN accumulates (WHO health EDRM knowledge hub). This paper presents a summary of the discussion results of the meetings.

scholarly journals Opportunities for data management research in the era of horizontal AI/ML

2019 ◽  
Vol 12 (12) ◽  
pp. 2323-2323
Author(s):  
Theodoras Rekatsinas ◽  
Sudeepa Roy ◽  
Manasi Vartak ◽  
Ce Zhang ◽  
Neoklis Polyzotis
Keyword(s):  
Data Management ◽  
Management Research

Multichannel Data-Driven Attribution Models: A Review and Research Agenda

2021 ◽  
pp. 153-189
Author(s):  
Ben B. Beck ◽  
J. Andrew Petersen ◽  
Rajkumar Venkatesan
Keyword(s):  
Research Agenda ◽  
Data Driven ◽  
Multichannel Data

Beyond Micro-Tasks

2018 ◽  
Vol 29 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Roman Lukyanenko ◽  
Jeffrey Parsons
Keyword(s):  
Data Acquisition ◽  
Data Management ◽  
Future Research ◽  
Information Production ◽  
Management Research ◽  
Research Attention ◽  
Important Type ◽  
Sensory Ability ◽  
Term Data

The emergence of crowdsourcing as an important mode of information production has attracted increasing research attention. In this article, the authors review crowdsourcing research in the data management field. Most research in this domain can be termed tasked-based, focusing on micro-tasks that exploit scale and redundancy in crowds. The authors' review points to another important type of crowdsourcing – which they term observational – that can expand the scope of extant crowdsourcing data management research. Observational crowdsourcing consists of projects that harness human sensory ability to support long-term data acquisition. The authors consider the challenges in this domain, review approaches to data management for crowdsourcing, and suggest directions for future research that bridges the gaps between the two research streams.

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