Intellectual capital in the age of Big Data: establishing a research agenda

2017 ◽  
Vol 18 (2) ◽  
pp. 242-261 ◽  
Author(s):  
Giustina Secundo ◽  
Pasquale Del Vecchio ◽  
John Dumay ◽  
Giuseppina Passiante
Keyword(s):  
Big Data ◽  
Literature Review ◽  
Intellectual Capital ◽  
Economic Value ◽  
Future Research ◽  
Value Drivers ◽  
Content Type ◽  
Data Movement ◽  
Value Propositions ◽  
Emerging Issues

Purpose The purpose of this paper is to contribute to the literature on intellectual capital (IC) in light of the emerging paradigm of Big Data. Through a literature review, this paper provides momentum for researchers and scholars to explore the emerging trends and implications of the Big Data movement in the field of IC. Design/methodology/approach A literature review highlights novel and emerging issues in IC and Big Data research, focussing on: IC for organisational value, the staged evolution of IC research, and Big Data research from the technological to the managerial paradigm. It is expected that identifying these contributions will help establish future research directions. Findings A conceptual multi-level framework demonstrates how Big Data validates the need to shift the focus of IC research from organisations to ecosystems. The framework is organised into four sections: “why” – the managerial reasons for incorporating Big Data into IC; “what” – the Big Data typologies that enhance IC practice; “who” – the stakeholders involved in and impacted by Big Data IC value creation; and “how” – the Big Data processes suitable for IC management. Research limitations/implications The paper provides many avenues for future research in this emerging area of investigation. The key research questions posed aim to advance the contribution of Big Data to research on IC approaches. Practical implications The paper outlines the socio-economic value of Big Data generated by and about organisational ecosystems. It identifies opportunities for existing companies to renew their value propositions through Big Data, and discusses new tools for managing Big Data to support disclosing IC value drivers and creating new intangible assets. Originality/value This paper investigates the effects and implications Big Data offers for IC management, in support of the fourth stage of IC research. Additionally, it provides an original interpretation of IC research through the lens of Big Data.

Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rajesh Kumar Singh ◽  
Saurabh Agrawal ◽  
Abhishek Sahu ◽  
Yigit Kazancoglu
Keyword(s):  
Health Care ◽  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Health Care Sector ◽  
Future Research ◽  
Research Gaps ◽  
Content Type

PurposeThe proposed article is aimed at exploring the opportunities, challenges and possible outcomes of incorporating big data analytics (BDA) into health-care sector. The purpose of this study is to find the research gaps in the literature and to investigate the scope of incorporating new strategies in the health-care sector for increasing the efficiency of the system.Design/methodology/approachFora state-of-the-art literature review, a systematic literature review has been carried out to find out research gaps in the field of healthcare using big data (BD) applications. A detailed research methodology including material collection, descriptive analysis and categorization is utilized to carry out the literature review.FindingsBD analysis is rapidly being adopted in health-care sector for utilizing precious information available in terms of BD. However, it puts forth certain challenges that need to be focused upon. The article identifies and explains the challenges thoroughly.Research limitations/implicationsThe proposed study will provide useful guidance to the health-care sector professionals for managing health-care system. It will help academicians and physicians for evaluating, improving and benchmarking the health-care strategies through BDA in the health-care sector. One of the limitations of the study is that it is based on literature review and more in-depth studies may be carried out for the generalization of results.Originality/valueThere are certain effective tools available in the market today that are currently being used by both small and large businesses and corporations. One of them is BD, which may be very useful for health-care sector. A comprehensive literature review is carried out for research papers published between 1974 and 2021.

Big data-driven strategic orientation in international marketing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shahriar Akter ◽  
Md Afnan Hossain ◽  
Qiang (Steven) Lu ◽  
S.M. Riad Shams
Keyword(s):  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
International Marketing ◽  
Strategic Orientation ◽  
Data Driven ◽  
Future Research ◽  
Content Type ◽  
Strategic Orientations ◽  
Marketing Activities

PurposeBig data is one of the most demanding topics in contemporary marketing research. Despite its importance, the big data-based strategic orientation in international marketing is yet to be formed conceptually. Thus, the purpose of this study is to systematically review and propose a holistic framework on big data-based strategic orientation for firms in international markets to attain a sustained firm performance.Design/methodology/approachThe study employed a systematic literature review to synthesize research rigorously. Initially, 2,242 articles were identified from the selective databases, and 45 papers were finally reported as most relevant to propose an integrative conceptual framework.FindingsThe findings of the systematic literature review revealed data-evolving, and data-driven strategic orientations are essential for performing international marketing activities that contain three primary orientations such as (1) international digital platform orientation, (2) international market orientation and (3) international innovation and entrepreneurial orientation. Eleven distinct sub-dimensions reflect these three primary orientations. These strategic orientations of international firms may lead to advanced analytics orientation to attain sustained firm performance by generating and capturing value from the marketplace.Research limitations/implicationsThe study minimizes the literature gap by forming knowledge on big data-based strategic orientation and framing a multidimensional framework for guiding managers in the context of strategic orientation for international business and international marketing activities. The current study was conducted by following only a systematic literature review exclusively in firms' overall big data-based strategic orientation concept in international marketing. Future research may extend the domain by introducing firms' category wise systematic literature review.Originality/valueThe study has proposed a holistic conceptual framework for big data-driven strategic orientation in international marketing literature through a systematic review for the first time. It has also illuminated a future research agenda that raises questions for the scholars to develop or extend theory in this area or other related disciplines.

scholarly journals Transforming the stakeholders’ Big Data for intellectual capital management

2018 ◽  
Vol 26 (3) ◽  
pp. 420-442 ◽  
Author(s):  
Lorna Uden ◽  
Pasquale Del Vecchio
Keyword(s):  
Big Data ◽  
Conceptual Framework ◽  
Activity Theory ◽  
Intellectual Capital ◽  
Value Creation ◽  
Organizational Values ◽  
Service Science ◽  
Future Research ◽  
Content Type ◽  
Service Ecosystems

PurposeThis paper aims to define a conceptual framework for transforming Big Data into organizational value by focussing on the perspectives of service science and activity theory. In coherence with the agenda on evolutionary research on intellectual capital (IC), the study also provides momentum for researchers and scholars to explore emerging trends and implications of Big Data for IC management.Design/methodology/approachThe paper adopts a qualitative and integrated research method based on a constructive review of existing literature related to IC management, Big Data, service science and activity theory to identify features and processes of a conceptual framework emerging at the intersection of previously identified research topics.FindingsThe proposed framework harnesses the power of Big Data, collectively created by the engagement of multiple stakeholders based on the concepts of service ecosystems, by using activity theory. The transformation of Big Data for IC management addresses the process of value creation based on a set of critical dimensions useful to identify goals, main actors and stakeholders, processes and motivations.Research limitations/implicationsThe paper indicates how organizational values can be created from Big Data through the co-creation of value in service ecosystems. Activity theory is used as theoretical lens to support IC ecosystem development. This research is exploratory; the framework offers opportunities for refinement and can be used to spearhead directions for future research.Practical implicationsThe paper proposes a framework for transforming Big Data into organizational values for IC management in the context of entrepreneurial universities as pivotal contexts of observation that can be replicated in different fields. The framework provides guidelines that can be used to help organizations intending to embark on the emerging paradigm of Big Data for IC management for their competitive advantages.Originality/valueThe paper’s originality is in bringing together research from Big Data, value co-creation from service ecosystems and activity theory to address the complex issues involved in IC management. A further element of originality offered involves integrating such multidisciplinary perspectives as a lens for shaping the complex process of value creation from Big Data in relationship to IC management. The concept of how IC ecosystems can be designed is also introduced.

scholarly journals Big data as a value generator in decision support systems: a literature review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gustavo Grander ◽  
Luciano Ferreira da Silva ◽  
Ernesto Del Rosário Santibañez Gonzalez
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Literature Review ◽  
Decision Support Systems ◽  
Support Systems ◽  
Big Data Analytics ◽  
Machine Learning Algorithms ◽  
Future Research ◽  
Content Type ◽  
Theoretical Contribution

PurposeThis paper aims to analyze how decision support systems manage Big data to obtain value.Design/methodology/approachA systematic literature review was performed with screening and analysis of 72 articles published between 2012 and 2019.FindingsThe findings reveal that techniques of big data analytics, machine learning algorithms and technologies predominantly related to computer science and cloud computing are used on decision support systems. Another finding was that the main areas that these techniques and technologies are been applied are logistic, traffic, health, business and market. This article also allows authors to understand the relationship in which descriptive, predictive and prescriptive analyses are used according to an inverse relationship of complexity in data analysis and the need for human decision-making.Originality/valueAs it is an emerging theme, this study seeks to present an overview of the techniques and technologies that are being discussed in the literature to solve problems in their respective areas, as a form of theoretical contribution. The authors also understand that there is a practical contribution to the maturity of the discussion and with reflections even presented as suggestions for future research, such as the ethical discussion. This study’s descriptive classification can also serve as a guide for new researchers who seek to understand the research involving decision support systems and big data to gain value in our society.

scholarly journals Big data and analytics in hospitality and tourism: a systematic literature review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marcello Mariani ◽  
Rodolfo Baggio
Keyword(s):  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Data Science ◽  
The Body ◽  
Future Research ◽  
Content Type ◽  
Tourism Management ◽  
Scientific Outputs ◽  
Hospitality And Tourism

Purpose The purpose of this work is to survey the body of research revolving around big data (BD) and analytics in hospitality and tourism, by detecting macro topical areas, research streams and gaps and to develop an agenda for future research. Design/methodology/approach This research is based on a systematic literature review of academic papers indexed in the Scopus and Web of Science databases published up to 31 December 2020. The outputs were analyzed using bibliometric techniques, network analysis and topic modeling. Findings The number of scientific outputs in research with hospitality and tourism settings has been expanding over the period 2015–2020, with a substantial stability of the areas examined. The vast majority are published in academic journals where the main reference area is neither hospitality nor tourism. The body of research is rather fragmented and studies on relevant aspects, such as BD analytics capabilities, are virtually missing. Most of the outputs are empirical. Moreover, many of the articles collected relatively small quantities of records and, regardless of the time period considered, only a handful of articles mix a number of different techniques. Originality/value This work sheds new light on the emergence of a body of research at the intersection of hospitality and tourism management and data science. It enriches and complements extant literature reviews on BD and analytics, combining these two interconnected topics.

The big data regime shift in real estate

2020 ◽  
Vol 38 (4) ◽  
pp. 363-395 ◽  
Author(s):  
James R. DeLisle ◽  
Brent Never ◽  
Terry V. Grissom
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Real Estate ◽  
Urban Areas ◽  
Regime Shift ◽  
Design Thinking ◽  
Future Research ◽  
Content Type ◽  
Data Movement ◽  
Support Decision Making

PurposeThe paper explores the emergence of the “big data regime” and the disruption that it is causing for the real estate industry. The paper defines big data and illustrates how an inductive, big data approach can help improve decision-making.Design/methodology/approachThe paper demonstrates how big data can support inductive reasoning that can lead to enhanced real estate decisions. To help readers understand the dynamics and drivers of the big data regime shift, an extensive list of hyperlinks is included.FindingsThe paper concludes that it is possible to blend traditional and non-traditional data into a unified data environment to support enhanced decision-making. Through the application of design thinking, the paper illustrates how socially responsible development can be targeted to under-served urban areas and helps serve residents and the communities in which they live.Research limitations/implicationsThe paper demonstrates how big data can be harnessed to support decision-making using a hypothetical project. The paper does not present advanced analytics but focuses aggregating disparate longitudinal data that could support such analysis in future research.Practical implicationsThe paper focuses on the US market, but the methodology can be extended to other markets where big data is increasingly available.Social implicationsThe paper illustrates how big data analytics can be used to help serve the needs of marginalized residents and tenants, as well as blighted areas.Originality/valueThis paper documents the big data movement and demonstrates how non-traditional data can support decision-making.

scholarly journals Journal of Intellectual Capital: a review of emerging themes and future trends

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marco Bellucci ◽  
Giacomo Marzi ◽  
Beatrice Orlando ◽  
Francesco Ciampi
Keyword(s):  
Literature Review ◽  
Intellectual Capital ◽  
Design Methodology ◽  
Future Research ◽  
Future Trends ◽  
Content Type ◽  
Main Research ◽  
Literature Reviews ◽  
Emerging Themes ◽  
Research Domain

PurposeThis article aims to provide a bibliometric and systematic literature analysis of studies published in the Journal of Intellectual Capital (JIC) from 2014 to 2018 in order to highlight emerging themes and future trends.Design/methodology/approachThe analysis focused on 187 papers published on JIC over a period of five years. A scientometric approach to data mining enabled the detection of patterns in the dataset. Precisely, the investigation was conducted by integrating a bibliometric analysis on VOSviewer with a systematic literature review.FindingsFour main streams of research on JIC emerged in the years of the analysis: reporting and disclosure of intellectual capital; intellectual capital research in universities, education and public sector; knowledge management; intellectual capital, financial performance, and market value.Research limitations/implicationsThe study offers valid insights to the topics covered by the Journal of Intellectual Capital by identifying the main research gaps and trends, along with future research avenues.Originality/valuePrior scholars mostly focused on systematic literature reviews, whilst the use of bibliometric methods generally seems to be a missing tile in the research domain. Also, none of the extant studies has focused on the Journal of Intellectual Capital with reference to the 2014–2018 period. The use of both bibliometric and systematic approaches to literature review delivered extremely fine-tuned results in terms of factors such as citations, contents and evolution of clusters over time.

Breaching intellectual capital: critical reflections on Big Data security

2018 ◽  
Vol 26 (3) ◽  
pp. 463-482 ◽  
Author(s):  
Matteo La Torre ◽  
John Dumay ◽  
Michele Antonio Rea
Keyword(s):  
Big Data ◽  
Intellectual Capital ◽  
Data Security ◽  
Economic Value ◽  
Public Information ◽  
Dark Side ◽  
Content Type ◽  
Security Breaches ◽  
Managerial Implications ◽  
New Research

PurposeReflecting on Big Data’s assumed benefits, this study aims to identify the risks and challenges of data security underpinning Big Data’s socio-economic value and intellectual capital (IC).Design/methodology/approachThe study reviews academic literature, professional documents and public information to provide insights, critique and projections for IC and Big Data research and practice.FindingsThe “voracity” for data represents a further “V” of Big Data, which results in a continuous hunt for data beyond legal and ethical boundaries. Cybercrimes, data security breaches and privacy violations reflect voracity and represent the dark side of the Big Data ecosystem. Losing the confidentiality, integrity or availability of data because of a data security breach poses threat to IC and value creation. Thus, cyberthreats compromise the social value of Big Data, impacting on stakeholders’ and society’s interests.Research limitations/implicationsBecause of the interpretative nature of this study, other researchers may not draw the same conclusions from the evidence provided. It leaves some open questions for a wide research agenda about the societal, ethical and managerial implications of Big Data.Originality/valueThis paper introduces the risks of data security and the challenges of Big Data to stimulate new research paths for IC and accounting research.

scholarly journals Structured literature review about intellectual capital and innovation

2017 ◽  
Vol 18 (2) ◽  
pp. 262-285 ◽  
Author(s):  
Marta Buenechea-Elberdin
Keyword(s):  
Literature Review ◽  
Intellectual Capital ◽  
Business Environment ◽  
Research Field ◽  
Future Research ◽  
Journal Articles ◽  
Content Type ◽  
The Relationship ◽  
Research Domain ◽  
Structured Literature Review

Purpose The purpose of this paper is to review and critique the literature dealing with the relationship between intellectual capital (IC) and innovation, and to outline the future of this research field. Design/methodology/approach Structured literature review (SLR). Findings The relationship between IC and innovation has been examined in great detail; however, much remains to be understood regarding the way of approaching and conceptualising both IC and innovation according to the current business environment. Moreover, academic literature on the IC-innovation relationship shows a disconnection between academia, and both business practice and policy-making, in this research domain. Research limitations/implications Since the study was developed by one person, the results could be influenced by her subjective interpretation. In addition, only journal articles published between 2006 and 2015 have been examined. Originality/value This paper contributes to IC literature by providing a unique SLR of the IC-innovation field of research. The paper points to pathways for future research in the IC-innovation domain.

Intellectual capital disclosure: a structured literature review

2017 ◽  
Vol 18 (1) ◽  
pp. 9-28 ◽  
Author(s):  
Benedetta Cuozzo ◽  
John Dumay ◽  
Matteo Palmaccio ◽  
Rosa Lombardi
Keyword(s):  
Literature Review ◽  
Intellectual Capital ◽  
Listed Companies ◽  
Future Research ◽  
Data Set ◽  
Content Type ◽  
General Decline ◽  
The Usa ◽  
Research Stream ◽  
Structured Literature Review

Purpose The purpose of this paper is to provide an up-to-the-minute literature review of intellectual capital disclosure (ICD) to: identify the major themes developed within this research stream; investigate the evolution of the theory; and derive insights to guide future research agendas for the benefit of researchers and ICD users. Design/methodology/approach Research articles from ten relevant journals for the 17-year period between 2000 and 2017 are categorised and analysed in a structured literature review (Massaro et al., 2016) to answer these three research questions. This study adds to a data set established by Guthrie et al. (2012) and presents the results in a consistent and comparable manner across the studies. Findings A lack of significant innovation in the evolution of ICD indicates that this research stream may have been a victim of its own success (Dumay and Guthrie, 2017). Stuck in overview mode, studies continue to fixate on general issues, largely drawing their analysis from the corporate reports of publicly listed companies in Europe. Very few studies examine ICD in the USA and beyond, nor do they drill down to organisational level to examine ICD in practice. Practical implications We academics need to leave our ivory towers and base future research on how organisations, in different contexts, using different languages, harness intangible assets to create value. Without discouraging content analysis from corporate reports, we need to be more innovative in searching for IC from the rich variety of media resources modern corporate communication channels offer, and recognise that, while we are all working towards the same thing, we may not be using the same language to get there. Originality/value Despite extending previous work, this study highlights some of the new insights revealed from ICD research, especially over the last two years. The findings regarding differing use of terminology across continents, a general decline in published research due to lack of interest or new ground to cover, and zero evidence for a “groundswell” of IC disclosures by listed companies should motivate further reading in many researchers.

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