A recipe for big data value creation

2019 ◽  
Vol 25 (5) ◽  
pp. 1085-1100 ◽  
Author(s):  
Ossi Ylijoki ◽  
Jari Porras
Keyword(s):  
Big Data ◽  
Value Creation ◽  
Success Factors ◽  
Process Theory ◽  
Performance Impact ◽  
Holistic Model ◽  
Content Type ◽  
Business Context ◽  
Data Value ◽  
Probabilistic Processes

PurposeThe purpose of this paper is to present a process-theory-based model of big data value creation in a business context. The authors approach the topic from the viewpoint of a single firm.Design/methodology/approachThe authors reflect current big data literature in two widely used value creation frameworks and arrange the results according to a process theory perspective.FindingsThe model, consisting of four probabilistic processes, provides a “recipe” for converting big data investments into firm performance. The provided recipe helps practitioners to understand the ingredients and complexities that may promote or demote the performance impact of big data in a business context.Practical implicationsThe model acts as a framework which helps to understand the necessary conditions and their relationships in the conversion process. This helps to focus on success factors which promote positive performance.Originality/valueUsing well-established frameworks and process components, the authors synthetize big data value creation-related papers into a holistic model which explains how big data investments translate into economic performance, and why the conversion sometimes fails. While the authors rely on existing theories and frameworks, the authors claim that the arrangement and application of the elements to the big data context is novel.

Creating multiple value streams from big data

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Keyword(s):  
Big Data ◽  
Value Creation ◽  
Content Type ◽  
It Alignment ◽  
Process Creation ◽  
Data Value ◽  
Value Streams ◽  
Pertinent Information ◽  
Multiple Value ◽  
Process Alignment

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings This research paper determines how service supply chains can create value with big data, by building cross-departmental processes. Based on the study’s results, the critical alignment capabilities for successful big data value creation are: IT-process alignment; IT-performance alignment; performance-process alignment; human-IT alignment; and human-process alignment. Additionally, overarching and underlying strategic and organizational alignment capabilities also impacted this value creation. The human impact on employees of big data-led process creation shouldn’t be underestimated. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

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 in the Danish industry: application and value creation

2017 ◽  
Vol 23 (3) ◽  
pp. 645-670 ◽  
Author(s):  
Sune Dueholm Müller ◽  
Preben Jensen
Keyword(s):  
Big Data ◽  
Value Creation ◽  
Online Survey ◽  
Organizational Context ◽  
Business Processes ◽  
Research Question ◽  
Business Strategies ◽  
Processing Technologies ◽  
Content Type ◽  
Analytical Skills

Purpose The development within storage and processing technologies combined with the growing collection of data has created opportunities for companies to create value through the application of big data. The purpose of this paper is to focus on how small and medium-sized companies in Denmark are using big data to create value. Design/methodology/approach The research is based on a literature review and on data collected from 457 Danish companies through an online survey. The paper looks at big data from the perspective of SMEs in order to answer the following research question: to what extent does the application of big data create value for small and medium-sized companies. Findings The findings show clear links between the application of big data and value creation. The analysis also shows that the value created through big data does not arise from data or technology alone but is dependent on the organizational context and managerial action. A holistic perspective on big data is advocated, not only focusing on the capture, storage, and analysis of data, but also leadership through goal setting and alignment of business strategies and goals, IT capabilities, and analytical skills. Managers are advised to communicate the business value of big data, adapt business processes to data-driven business opportunities, and in general act on the basis of data. Originality/value The paper provides researchers and practitioners with empirically based insights into how the application of big data creates value for SMEs.

scholarly journals Beyond reciprocal: the role of platforms in diffusing data value across multiple stakeholders

2019 ◽  
Vol 30 (4) ◽  
pp. 507-518 ◽  
Author(s):  
Edward C. Malthouse ◽  
Alexander Buoye ◽  
Nathaniel Line ◽  
Dahlia El-Manstrly ◽  
Tarik Dogru ◽  
...  
Keyword(s):  
Value Creation ◽  
Future Research ◽  
Multiple Stakeholders ◽  
Content Type ◽  
Data Value ◽  
Data Ecosystem ◽  
Hospitality Managers ◽  
Value Creation Process ◽  
Practical Implications

Purpose The purpose of this paper is to assess the role of platforms in diffusing data value across multiple stakeholders. Design/methodology/approach Seminal theoretical and managerial work has been critically examined in order to justify the need for improving/extending the contemporary understanding of the data value creation process. Findings The results suggest that existing frameworks and conceptualizations of reciprocal data value provide incomplete understanding of the role of platforms in data value diffusion. Research limitations/implications This paper provides service researchers with a better understanding of the role of platforms in data value diffusion. Future research can develop and validate new frameworks that reflect the proposed extended/improved view of data value creation. Practical implications Service and hospitality managers will be able to more effectively manage the role of platforms in data value diffusion. Specifically, this paper proposes that, in order for data to become a source of competitive advantage, there must be a symbiotic relationship among all the stakeholders of the data ecosystem. Originality/value The authors discuss how data creates value for different stakeholders in the hospitality industry.

Detecting customers knowledge from social media big data: toward an integrated methodological framework based on netnography and business analytics

2020 ◽  
Vol 24 (4) ◽  
pp. 799-821 ◽  
Author(s):  
Pasquale Del Vecchio ◽  
Gioconda Mele ◽  
Giuseppina Passiante ◽  
Demetris Vrontis ◽  
Cosimo Fanuli
Keyword(s):  
Social Media ◽  
Big Data ◽  
Customer Relationship Management ◽  
Value Creation ◽  
Relationship Management ◽  
Customer Relationship ◽  
Business Analytics ◽  
Content Type ◽  
Social Big Data ◽  
Practical Implications

Purpose This paper aims to demonstrate how the integration of netnography and business analytics can support companies in the process of value creation from social big data by leveraging on customer relationship management and customer knowledge management (CKM). Design/methodology/approach This paper adopts the methodology of a single case study by using desk analysis, netnography and business analytics. The context of analysis has been identified into the case of Aurora Company, a well-known producer of fountain pens. Findings The case demonstrates how the integration of big data analytics and netnography is relevant for the development of a customer relationship management strategy. The results obtained have been categorized according to the three main categories of customer knowledge, such as knowledge for, from and about customer. Research limitations/implications This paper presents implications for the advancement of the theory on CKM by demonstrating, as the acquisition, storage and management of data generated by customers on social media require the adoption of a cross-disciplinary approach resulting from the integration of qualitative and quantitative approaches. The framework is structured as methodological tool to detect knowledge in virtual community. Practical implications Practical implications arise for managers and entrepreneurs in terms of value creation from knowledge assets generated on social big data through the management of the customers’ relationship and data-driven innovation patterns. Originality/value This paper offers an original contribution of integration of well-established research streams. The focus on the knowledge under the perspectives of information assets for, from and about customers in the debate on value creation and management of big data is an element of value offered by this study in addition to the comprehension of strategies of social customer relationship management as actual initiative embraced by a company in the leveraging of innovation and tradition.

How big data alters value creation: through the lens of big data competency

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaobo Wu ◽  
Liping Liang ◽  
Siyuan Chen
Keyword(s):  
Big Data ◽  
Value Creation ◽  
Value Chain ◽  
Current Knowledge ◽  
Two Dimensions ◽  
Future Research ◽  
Firm Capabilities ◽  
Content Type ◽  
Rigorous Approach ◽  
Future Research Agenda

PurposeAs various different and even contradictory concepts are proposed to depict a firm's capabilities related to big data, and extant relevant research is fragmented and scattered in several disciplines, there is currently a lack of holistic and comprehensive understanding of how big data alters value creation by facilitating firm capabilities. To narrow this gap, this study aims to synthesize current knowledge on the firm capabilities and transformation of value creation facilitated by big data.Design/methodology/approachThe authors adopt an inductive and rigorous approach to conduct a systematic review of 185 works, following the “Grounded Theory Literature-Review Method”.FindingsThe authors introduce and develop the concept of big data competency, present an inductive framework to open the black box of big data competency following the logic of virtual value chain, provide a structure of big data competency that consists of two dimensions, namely, big data capitalization and big data exploitation, and further explain the evolution of value creation structure from value chain to value network by connecting the attributes of big data competency (i.e. connectivity and complementarity) with the transformation of value creation (i.e. optimizing and pioneering).Originality/valueThe big data competency, an inclusive concept of firm capabilities to deal with big data, is proposed. Based on this concept, the authors highlight the significant contributions that extant research has made toward our understanding of how big data alters value creation by facilitating firm capabilities. Besides, the authors provide a future research agenda that academics can rely on to study the strategic management of big data.

The relationship between intellectual capital and big data: a review

2018 ◽  
Vol 26 (3) ◽  
pp. 361-380 ◽  
Author(s):  
Federica De Santis ◽  
Claudia Presti
Keyword(s):  
Big Data ◽  
Intellectual Capital ◽  
Value Creation ◽  
Design Methodology ◽  
Content Type ◽  
A Value ◽  
Starting Point ◽  
The Relationship ◽  
Practical Implications ◽  
Decision Making Tool

PurposeThis paper aims to give an integrated framework for analysing the main opportunities and threats related to the exploitation of Big Data (BD) technologies within intellectual capital (IC) management.Design/methodology/approachBy means of a structured literature review (SLR) of the extant literature on BD and IC, the study identified distinctive opportunities and challenges of BD technologies and related them to the traditional dimensions of IC.FindingsThe advent of BD has not radically changed the risks and opportunities of IC management already highlighted in previous literature. However, it has significantly amplified their magnitude and the speed with which they manifest themselves. Thus, a revision of the traditional managerial solutions needed to face them is required.Research limitations/implicationsThe developed framework can contribute to academic discourse on BD and IC as a starting point to understanding how BD can be turned into intangible assets from a value creation perspective.Practical implicationsThe framework can also represent a useful decision-making tool for practitioners in identifying and evaluating the main opportunities and threats of an investment in BD technologies for IC management.Originality/valueThe paper responds to the call for more research on the integration of BD discourse in the fourth stage of IC research. It intends to improve this understanding of how BD technologies can be exploited to create value from an IC perspective, focussing not only on the potential of BD for creating value but also on the challenges that it poses to organizations.

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