scholarly journals Big data and dynamic capabilities: a bibliometric analysis and systematic literature review

2019 ◽  
Vol 57 (8) ◽  
pp. 2052-2068 ◽  
Author(s):  
Riccardo Rialti ◽  
Giacomo Marzi ◽  
Cristiano Ciappei ◽  
Donatella Busso
Keyword(s):  
Big Data ◽  
Literature Review ◽  
Bibliometric Analysis ◽  
Systematic Literature Review ◽  
Dynamic Capabilities ◽  
Process Management ◽  
Big Data Analytics ◽  
Management Decision ◽  
Content Type ◽  
Management Decision Making

Purpose Recently, several manuscripts about the effects of big data on organizations used dynamic capabilities as their main theoretical approach. However, these manuscripts still lack systematization. Consequently, the purpose of this paper is to systematize the literature on big data and dynamic capabilities. Design/methodology/approach A bibliometric analysis was performed on 170 manuscripts extracted from the Clarivate Analytics Web of Science Core Collection database. The bibliometric analysis was integrated with a literature review. Findings The bibliometric analysis revealed four clusters of papers on big data and dynamic capabilities: big data and supply chain management, knowledge management, decision making, business process management and big data analytics. The systematic literature review helped to clarify each clusters’ content. Originality/value To the authors’ best knowledge, minimal attention has been paid to systematizing the literature on big data and dynamic capabilities.

A systematic literature review with bibliometric analysis of big data analytics adoption from period 2014 to 2018

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zeeshan Inamdar ◽  
Rakesh Raut ◽  
Vaibhav S. Narwane ◽  
Bhaskar Gardas ◽  
Balkrishna Narkhede ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Literature Review ◽  
Bibliometric Analysis ◽  
Systematic Literature Review ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Sustainable Supply Chain ◽  
Content Type ◽  
Future Direction

PurposeThe volume of data being generated by various sectors in recent years has increased exponentially. Consequently, professionals struggle to process essential data in the current competitive world. The purpose of the study is to explore and provide insights into the Big Data Analytics (BDA) studies in different sectors.Design/methodology/approachThis study performs a systematic literature review (SLR) with bibliometric analysis of BDA adoption (BDAA) in the supply chain and its applications in various sectors from 2014 to 2018. This paper focuses on BDAA studies have been carried out across different countries and sectors. Also, the paper explores different tools and techniques used in BDAA studies.FindingsThe benefits of adopting BDA, coupled with a lack of adequate research in the field, have motivated this study. This literature review categorizes paper into seven main areas and found that most of the studies were carried out in manufacturing and service.Practical implicationsThis research insight and observations can provide practitioners and academia with guidance on implementing BDA in different sustainable supply chain sectors. The article indicates a few remarkable gaps in the future direction and trends regarding the integration of BDA and sustainable supply chain development.Originality/valueThe study derives a new categorization of BDA, which investigates how data is generated, organized, captured, interpreted and evaluated to give valuable insights to manage the sustainable supply chain.

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 Manager perceptions of big data reliability in hotel revenue management decision making

2019 ◽  
Vol 36 (1) ◽  
pp. 25-39 ◽  
Author(s):  
David Egan ◽  
Natalie Claire Haynes
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Revenue Management ◽  
Management Decision ◽  
Local Market ◽  
Data Systems ◽  
Local Data ◽  
Content Type ◽  
User Input ◽  
Management Decision Making

PurposeThe purpose of this paper is to investigate the perceptions that managers have of the value and reliability of using big data to make hotel revenue management and pricing decisions.Design/methodology/approachA three-stage iterative thematic analysis technique based on the approaches of Braun and Clarke (2006) and Nowell et al. (2017) and using different research instruments to collect and analyse qualitative data at each stage was used to develop an explanatory framework.FindingsWhilst big data-driven automated revenue systems are technically capable of making pricing and inventory decisions without user input, the findings here show that the reality is that managers still interact with every stage of the revenue and pricing process from data collection to the implementation of price changes. They believe that their personal insights are as valid as big data in increasing the reliability of the decision-making process. This is driven primarily by a lack of trust on the behalf of managers in the ability of the big data systems to understand and interpret local market and customer dynamics.Practical implicationsThe less a manager believes in the ability of those systems to interpret these data, the more they perceive gut instinct to increase the reliability of their decision making and the less they conduct an analysis of the statistical data provided by the systems. This provides a clear message that there appears to be a need for automated revenue systems to be flexible enough for managers to import the local data, information and knowledge that they believe leads to revenue growth.Originality/valueThere is currently little research explicitly investigating the role of big data in decision making within hotel revenue management and certainly even less focussing on decision making at property level and the perceptions of managers of the value of big data in increasing the reliability of revenue and pricing decision making.

Rural women entrepreneurship: a systematic literature review and beyond

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Monika Aggarwal ◽  
Ramanjit Kaur Johal
Keyword(s):  
Literature Review ◽  
Bibliometric Analysis ◽  
Systematic Literature Review ◽  
Rural Women ◽  
Future Research ◽  
Female Entrepreneurs ◽  
Role Of Government ◽  
Women Entrepreneurship ◽  
Content Type ◽  
The United Kingdom

PurposeRural women entrepreneurship has been a domain attracting academicians and governments. This paper aims to to annotate existing literature in order to find a nexus between rural women and entrepreneurship using a systematic literature review and bibliometric analysis. Further, it has a certain scope and direction of existing research by critically analysing the work published in the domain of rural women entrepreneurship.Design/methodology/approachOut of 213 documents, 192 were published during last 20 years till October 2020 in Scopus journals that were downloaded using the keywords “Women Entrepreneurship” OR “Female Entrepreneurs” OR “Women Entrepreneurs” OR “Female Entrepreneurship” AND rural were accepted for further processing. VOS-Viewer software has been used to present bibliometric analysis. A thematic analysis of top 10 papers and 26 open access papers has also been done.FindingsIt was found that research interest in the said domain gained momentum in the last decade only. India is the top country that is publishing maximum papers; the United Kingdom has the maximum citations. The existing studies have focussed on factors influencing entrepreneurship, impact of gender and role of government schemes in fostering entrepreneurship. It is recommended that future studies may explore few inadequately explored grey areas including impact of entrepreneurial education, microcredit and information technology on rural women entrepreneurship.Originality/valueThis literature review article contributes to the existing literature by identifying the scope and direction of the existing literature. Further, it helps in identifying the least explored areas that can be taken up for the conduct of future research.

A systematic literature review of data science, data analytics and machine learning applied to healthcare engineering systems

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Roberto Salazar-Reyna ◽  
Fernando Gonzalez-Aleu ◽  
Edgar M.A. Granda-Gutierrez ◽  
Jenny Diaz-Ramirez ◽  
Jose Arturo Garza-Reyes ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Data Analytics ◽  
Research Area ◽  
Engineering Systems ◽  
Content Type ◽  
Healthcare Engineering

PurposeThe objective of this paper is to assess and synthesize the published literature related to the application of data analytics, big data, data mining and machine learning to healthcare engineering systems.Design/methodology/approachA systematic literature review (SLR) was conducted to obtain the most relevant papers related to the research study from three different platforms: EBSCOhost, ProQuest and Scopus. The literature was assessed and synthesized, conducting analysis associated with the publications, authors and content.FindingsFrom the SLR, 576 publications were identified and analyzed. The research area seems to show the characteristics of a growing field with new research areas evolving and applications being explored. In addition, the main authors and collaboration groups publishing in this research area were identified throughout a social network analysis. This could lead new and current authors to identify researchers with common interests on the field.Research limitations/implicationsThe use of the SLR methodology does not guarantee that all relevant publications related to the research are covered and analyzed. However, the authors' previous knowledge and the nature of the publications were used to select different platforms.Originality/valueTo the best of the authors' knowledge, this paper represents the most comprehensive literature-based study on the fields of data analytics, big data, data mining and machine learning applied to healthcare engineering systems.

scholarly journals Seeking competitive advantage with service infusion: a systematic literature review

2015 ◽  
Vol 26 (3) ◽  
pp. 394-425 ◽  
Author(s):  
Ville Eloranta ◽  
Taija Turunen
Keyword(s):  
Literature Review ◽  
Strategic Management ◽  
Competitive Advantage ◽  
Systematic Literature Review ◽  
Dynamic Capabilities ◽  
Business Models ◽  
Content Type ◽  
Management Concepts ◽  
Service Infusion ◽  
Management Theories

Purpose – The purpose of this paper is to analyze how the service infusion literature explains competitive advantage through services. The four strategic management theories – competitive forces, the resource-based view, dynamic capabilities, and relational view – are applied in the analysis. Design/methodology/approach – A systematic literature review analyzes the links between the service infusion and strategy literature. Findings – The review reveals that although discussion of service infusion applies strategic management concepts, the stream lacks rigor with respect to construct definition and justification. Additionally, contextual variables are often missing. The result is an over-emphasis of contextually bound measures, such as technology, and focal actors. Research limitations/implications – The growing trends toward social networks, co-specialization, actor dependency and shared resources encourage service infusion scholars to focus on network-related and relational capabilities, co-opetition, open business models, and relational rent extraction. Furthermore, service infusion research would benefit from considering strategy-based theoretical discussions, constructs, and constraints that would improve the scientific rigor, impact and contribution. Originality/value – This paper represents a systematic attempt to link the service infusion literature with strategic management theories and thoroughly analyzes the knowledge gaps and possible misconceptions.

Dynamic capabilities in humanitarian supply chain management: a systematic literature review

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdussamet Polater
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Dynamic Capabilities ◽  
Future Research ◽  
Chain Management ◽  
Content Type ◽  
Humanitarian Supply Chain ◽  
Humanitarian Supply Chain Management

PurposeThe main purpose of this paper is to examine the extant literature of humanitarian supply chain management (HSCM) which specifically use dynamic capabilities (DCs) view. By this means, the objectives of this study are to identify and assess the DCs used in the HSCM context, the factors positively and negatively affecting the DCs and how the DCs affect humanitarian supply chain (HSC) operations. Furthermore, this research aims to give directions for future research in the field of HSCM.Design/methodology/approachThis study adopts systematic literature review (SLR) approach proposed by Denyer and Tranfield (2009). Based on a SLR, this study synthesizes and compares the evidence, has a specific focus and research questions, has certain inclusion and exclusion criteria and provides evidence-based implications to the researchers and practitioners. This is a method which is replicable, transparent and auditable. The SLR methodology provides scholars and practitioners a basis for comprehending the current situation of relevant topic and taking correct steps in their future actions.FindingsThis SLR deduces that applying DCs view is still in its infancy in the HSCM literature. The result of this SLR reveals that supply chain agility (SCA), supply chain resilience (SCR), reconfiguration/transformation, integration, (short-term) collaboration, sustaining, sensing, seizing and knowledge access DCs have been used in the HSCM literature. In addition, it is determined that only one paper analyzed the influence of DCs on predisaster performance while rest of the papers focused on the postdisaster performance.Originality/valueThe result of the exhaustive literature search indicates that this is the first SLR that specifically analyzes the application of DCs view in the HSCM domain. This investigation determined the DCs used in HSCM and revealed the relations between the dependent and independent variables through the comprehensive model. In this way, this review provides a guidance to researchers in conduct their future investigations and practitioners to carry out supply chain (SC) operations by considering the factors affecting their operations.

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