Big data analytics as a roadmap towards green innovation, competitive advantage and environmental performance

2021 ◽  
pp. 128998
Author(s):  
Muhammad Waqas ◽  
Xue Honggang ◽  
Naveed Ahmad ◽  
Syed Abdul Rehman Khan ◽  
Muzzafar Iqbal
Keyword(s):  
Big Data ◽  
Competitive Advantage ◽  
Environmental Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Green Innovation

scholarly journals Decision Framework for Engaging Cloud-Based Big Data Analytics Vendors

2020 ◽  
Vol 22 (4) ◽  
pp. 60-74
Author(s):  
Emmanuel Wusuhon Yanibo Ayaburi ◽  
Michele Maasberg ◽  
Jaeung Lee
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Competitive Advantage ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Unique Contribution ◽  
Data Services ◽  
Business Environments ◽  
Digital Era ◽  
Service Oriented

Organizations face both opportunities and risks with big data analytics vendors, and the risks are now profound, as data has been likened to the oil of the digital era. The growing body of research at the nexus of big data analytics and cloud computing is examined from the economic perspective, based on agency theory (AT). A conceptual framework is developed for analyzing these opportunities and challenges regarding the use of big data analytics and cloud computing in e-business environments. This framework allows organizations to engage in contracts that target competitive parity with their service-oriented decision support system (SODSS) to achieve a competitive advantage related to their core business model. A unique contribution of this paper is its perspective on how to engage a vendor contractually to achieve this competitive advantage. The framework provides insights for a manager in selecting a vendor for cloud-based big data services.

scholarly journals Strategies to Implement Big Data Analytics in Telecommunication Organizations

2021 ◽  
Vol 10 (04) ◽  
pp. 064-076
Author(s):  
Dr. Delton Aneato ◽  
Dr. Cesar Castellanos
Keyword(s):  
Big Data ◽  
Competitive Advantage ◽  
Organizational Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
The United States ◽  
Communication Strategy ◽  
Analysis Process ◽  
Successful Communication ◽  
Multiple Case

Information technology (IT) leaders who do not invest in big data projects may struggle to gain a competitive advantage and business insights to improve performance. Grounded in Kotter’s change and Six Sigma models, the purpose of this qualitative multiple case study was to explore strategies IT leaders use to implement big data analytics successfully. The participants comprised 4 IT leaders from 2 telecommunication organizations in the United States of America, who expertly used big data analytics strategies to promote and maximize competitive advantage. Data were collected from semistructured interviews, company documents, and project-related documents. The collected information was examined by utilizing a thematic analysis approach. Four themes emerged from the data analysis process communication, training, employee involvement in decisions, and teamwork strategy. A key recommendation from these findings is for IT leaders to use successful communication strategies to convey the vision and objectives to all organizational levels. The successful communication-strategy can help evaluate business trends, forecasts, improve overall organizational performance and competitive advantage. The implications for positive social change include the potential for job creation, thus catalysing economic growth within communities.

Decision Framework for Engaging Cloud-Based Big Data Analytics Vendors

2022 ◽  
pp. 245-261
Author(s):  
Emmanuel Wusuhon Yanibo Ayaburi ◽  
Michele Maasberg ◽  
Jaeung Lee
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Competitive Advantage ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Unique Contribution ◽  
Data Services ◽  
Business Environments ◽  
Digital Era ◽  
Service Oriented

Organizations face both opportunities and risks with big data analytics vendors, and the risks are now profound, as data has been likened to the oil of the digital era. The growing body of research at the nexus of big data analytics and cloud computing is examined from the economic perspective, based on agency theory (AT). A conceptual framework is developed for analyzing these opportunities and challenges regarding the use of big data analytics and cloud computing in e-business environments. This framework allows organizations to engage in contracts that target competitive parity with their service-oriented decision support system (SODSS) to achieve a competitive advantage related to their core business model. A unique contribution of this paper is its perspective on how to engage a vendor contractually to achieve this competitive advantage. The framework provides insights for a manager in selecting a vendor for cloud-based big data services.

Big data analytics and competitive advantage: the strategic role of firm-specific knowledge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rajiv Dahiya ◽  
Son Le ◽  
John Kirk Ring ◽  
Kevin Watson
Keyword(s):  
Big Data ◽  
Competitive Advantage ◽  
Data Analytics ◽  
Management Strategies ◽  
Big Data Analytics ◽  
Specific Knowledge ◽  
Content Type ◽  
Absorptive Capacities ◽  
Strategic Role

PurposeWhile advances in big data analytics (BDA) provide valuable business insights and immense business value, many firms find it difficult to gain advantage from their BDA initiatives. Noting the strategic role of firm-specific knowledge, we develop a framework examining the relation between firm specificity of BDA knowledge and competitive advantage. We also examine the dynamic evolution of BDA capabilities and the associated knowledge management strategies.Design/methodology/approachWe review the resource-based view (RBV), capabilities life cycles and absorptive capacity perspectives along with the literature on BDA competitive advantage. Identifying two key BDA factors, application customization and data proprietorship, we develop a BDA competitive advantage framework. We also investigate the absorptive capacities employed by firms to advance their BDA capabilities. We use anecdotal cases to support our theoretical arguments.FindingsWe propose that BDA solutions with vendor-based applications (noncustomized) and public data will not generate firm-specific knowledge and therefore not provide competitive advantage. In contrast, BDA solutions with custom applications and proprietary data will provide high-level firm-specific knowledge and potentially result in sustained competitive advantage. We further suggest the relevant absorptive capacities and the knowledge management strategies for BDA capability development.Practical implicationsOur framework provides managers with insights into how to develop and enhance firm-specific knowledge from their BDA solutions to gain competitive advantage.Originality/valueOur study offers a new BDA firm-specific knowledge framework for competitive advantage.

scholarly journals The role of alliance management, big data analytics and information visibility on new-product development capability

2021 ◽  
Author(s):  
Rameshwar Dubey ◽  
David J. Bryde ◽  
Gary Graham ◽  
Cyril Foropon ◽  
Sushma Kumari ◽  
...  
Keyword(s):  
Big Data ◽  
Product Development ◽  
Competitive Advantage ◽  
Organizational Performance ◽  
New Product Development ◽  
Data Analytics ◽  
Dynamic Capabilities ◽  
Big Data Analytics ◽  
New Product ◽  
Alliance Management

AbstractMany organizations are increasingly investing in building dynamic capabilities to gain competitive advantage. New products play an important role in gaining competitive advantage and can significantly boost organizational performance. Although new product development (NPD) is widely recognized as a potentially vital source of competitive advantage, organizations face challenges in terms of developing the right antecedents or capabilities to influence NPD performance. Our research suggests that organizations should invest in building alliance management capability (AMC), big data analytics capability (BDAC) and information visibility (IV) to achieve their desired NPD success. Informed by the dynamic capabilities view of the firm (DCV) we have stated seven research hypotheses. We further tested our hypotheses using 219 usable respondents gathered using a pre-tested instrument. The hypotheses were tested using variance based structural equation modelling (PLS-SEM). The results of our study paint an interesting picture. Our study makes some significant contribution to the DCV and offers some useful directions to practitioners engaged in NPD in the big data analytics era. We demonstrate that AMC and BDAC are lower-order dynamic capabilities and that AMC has a positive and significant influence on BDAC. In turn, AMC and BDAC influence NPD under the moderating influence of IV. Ours is one of the first studies to empirically establish an association among three distinct dynamic capabilities which are often considered in isolation: AMC, BDAC and NPD. Our findings support emergent views on dynamic capabilities and their classification into various orders. Lastly, we provide empirical evidence that information visibility acts as a contingent variable to both AMC and BDAC effects on NPD. We end our paper by outlining some limitations of our study and by offering useful future research directions.

Antecedents to firm performance and competitiveness using the lens of big data analytics: a cross-cultural study

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abhishek Behl
Keyword(s):  
Big Data ◽  
Firm Performance ◽  
Competitive Advantage ◽  
Data Analytics ◽  
Positive Impact ◽  
Country Of Origin ◽  
Big Data Analytics ◽  
Content Type ◽  
Common Method Bias ◽  
India And China

PurposeThe study aims to understand how big data analytics capabilities of tech startups help them gain competitive advantage and improve their firm performance. The study is performed for two countries: India and China. A comparative analysis is also discussed in the study.Design/methodology/approachThe study collected responses from tech startups from both India and China. A total of 502 responses were collected with 269 from India and 233 from China. The results were analyzed using Warp PLS 6.0 after testing for common method bias, endogeneity and reliability of data. The study tested five primary hypotheses and also tested the effect of two control variables: country of origin of startup and age of the startup.FindingsWe found that big data analytics capabilities have a positive and significant impact on the firm performance and competitive advantage of tech startups. While organizational culture proved to have a positive impact as a moderator, innovation was found to have non-significant effect. The results also found to have non-significant effect of age of the firm while its country of origin does play an important role in defining its success.Originality/valueThe study offer key insights for the tech startups operating in two countries which are geographically neighbors but differ in the tech expertise from each other. Moreover, the study offers key insights on how does the origin of the country contributes significantly to explaining the success and competitiveness of the firm.

scholarly journals Sustainable Competitive Advantage Driven by Big Data Analytics and Innovation

2020 ◽  
Vol 10 (19) ◽  
pp. 6784
Author(s):  
Muawia Ramadan ◽  
Hana Shuqqo ◽  
Layalee Qtaishat ◽  
Hebaa Asmar ◽  
Bashir Salah
Keyword(s):  
Big Data ◽  
Competitive Advantage ◽  
Direct Effect ◽  
Data Analytics ◽  
Structural Equation ◽  
Big Data Analytics ◽  
Manufacturing Firms ◽  
Data Availability ◽  
Equation Modeling ◽  
Sustainable Competitive Advantage

Big data analytics (BDA) is one of the main pillars of Industry 4.0. It has become a promising tool for supporting the competitive advantages of firms by enhancing data-driven performance. Meanwhile, the scarcity of resources on a worldwide level has forced firms to consider sustainable-based performance as a critical issue. Additionally, the literature confirms that BDA and innovation can enhance firms’ performance, leading to competitive advantage. However, there is a lack of studies that examine whether or not BDA and innovation alone can sustain a firm’s competitive advantage. Drawing on previous studies and dynamic capability theory, this study proposes that big data analytics capabilities (BDAC), supported by a high level of data availability (DA), can improve innovation capabilities (IC) and, hence, lead to the development of a sustainable competitive advantage (SCA). This study examines the proposed hypotheses by surveying 117 manufacturing firms and analyzing responses via partial least squares–structural equation modeling (PLS-SEM) statistical software. Findings reveal that BDAC relies significantly on the degree of DA and has a significant role in increasing IC. Furthermore, the analysis confirms that IC has a significant and direct effect on a firm’s SCA, while BDAC has no direct effect on SCA. This study provides valuable insights for manufacturing firms to improve their sustainable business performance and theoretical and practical insights into BDA implementation issues in attaining sustainability in processes.

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