scholarly journals How Big Data Analytics Boosts Organizational Performance: The Mediating Role of the Sustainable Product Development

2020 ◽  
Vol 6 (4) ◽  
pp. 190
Author(s):  
Saqib Ali ◽  
Petra Poulova ◽  
Fakhra Yasmin ◽  
Muhammad Danish ◽  
Waheed Akhtar ◽  
...  
Keyword(s):  
Air Pollution ◽  
Big Data ◽  
Product Development ◽  
Organizational Performance ◽  
Data Analytics ◽  
Time Lag ◽  
Big Data Analytics ◽  
Haze Pollution ◽  
Sustainable Product Development ◽  
Sustainable Product

Increasing haze pollution and its adverse effects on human health is pressuring academics and practitioners to search for different solutions for environmental sustainability around the world. Similar to other countries, Pakistan is also affected by air pollution, and smog has become a fifth season. In Pakistan, one of the main reasons of smog and air pollution is hazardous emissions from vehicles. As a result, the booming automobile industry of Pakistan is now affected by two major challenges: sustainable product development and organizational performance. To meet these challenges, the study has developed a conceptual model to find the effect of big data analytics on organizational performance by adopting a sustainable development program. For the elimination of standard method biases, the study has used a time lag approach to collect the data in three waves and receive 372 usable responses. The empirical results of PLS-SEM suggest that big data analytics have a positive effect on a sustainable product development and sustainable product development has a positive and significant impact on organizational performance. Moreover, mediation of a sustainable program development is also confirmed between big data analytics and organizational performance. The managerial and theoretical implications of these results are discussed.

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.

Big data analytics capabilities and organizational performance: the mediating effect of dual innovations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaofeng Su ◽  
Weipeng Zeng ◽  
Manhua Zheng ◽  
Xiaoli Jiang ◽  
Wenhe Lin ◽  
...  
Keyword(s):  
Big Data ◽  
Organizational Performance ◽  
Empirical Analysis ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Mediating Effect ◽  
Content Type ◽  
Mediating Role ◽  
The Relationship

PurposeFollowing the rapid expansion of data volume, velocity and variety, techniques and technologies, big data analytics have achieved substantial development and a surge of companies make investments in big data. Academics and practitioners have been considering the mechanism through which big data analytics capabilities can transform into their improved organizational performance. This paper aims to examine how big data analytics capabilities influence organizational performance through the mediating role of dual innovations.Design/methodology/approachDrawing on the resource-based view and recent literature on big data analytics, this paper aims to examine the direct effects of big data analytics capabilities (BDAC) on organizational performance, as well as the mediating role of dual innovations on the relationship between (BDAC) and organizational performance. The study extends existing research by making a distinction of BDACs' effect on their outcomes and proposing that BDACs help organizations to generate insights that can help strengthen their dual innovations, which in turn have a positive impact on organizational performance. To test our proposed research model, this study conducts empirical analysis based on questionnaire-base survey data collected from 309 respondents working in Chinese manufacturing firms.FindingsThe results support the proposed hypotheses regarding the direct and indirect effect that BDACs have on organizational performance. Specifically, this paper finds that dual innovations positively mediate BDACs' effect on organizational performance.Originality/valueThe conclusions on the relationship between big data analytics capabilities and organizational performance in previous research are controversial due to lack of theoretical foundation and empirical testing. This study resolves the issue by provides empirical analysis, which makes the research conclusions more scientific and credible. In addition, previous literature mainly focused on BDACs' direct impact on organizational performance without making a distinction of BDAC's three dimensions. This study contributes to the literature by thoroughly introducing the notions of BDAC's three core constituents and fully analyzing their relationships with organizational performance. What's more, empirical research on the mechanism of big data analytics' influence on organizational performance is still at a rudimentary stage. The authors address this critical gap by exploring the mediation of dual innovations in the relationship through survey-based research. The research conclusions of this paper provide new perspective for understanding the impact of big data analytics capabilities on organizational performance, and enrich the theoretical research connotation of big data analysis capabilities and dual innovation behavior.

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.

scholarly journals Organizational performance and capabilities to analyze big data: do the ambidexterity and business value of big data analytics matter?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ahmad Ibrahim Aljumah ◽  
Mohammed T. Nuseir ◽  
Md. Mahmudul Alam
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Organizational Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Manufacturing Firms ◽  
Business Value ◽  
Primary Data ◽  
Content Type

PurposeThe aim of the study is to examine the impact of the big data analytics capabilities (BDAC) on the organizational performance. The study also examines the mediating role of ambidexterity and the moderating role of business value of big data (BVBD) analytics in the relationship between the big data analytics capabilities and the organizational performance.Design/methodology/approachThis study collected primary data based on a questionnaire survey among the large manufacturing firms operating in UAE. A total of 650 questionnaires were distributed among the manufacturing firms and 295 samples were used for final data analysis. The survey was conducted from September to November in 2019, and data were analyzed based on partial least squares structural equation modeling (PLS-SEM).FindingsThe big data analysis (BDA) scalability is supported by the findings on the performance of firm and its determinants such as system, value of business and quality of information. The roles of business value as a moderator and ambidexterity as mediator are found significant. The results reveal that there is a need for managers to consider the business value and quality dynamics as crucial strategic objectives to achieve high performance of the firm.Research limitations/implicationsThe study has significant policy implication for practitioners and researchers for understanding the issues related to big data analytics.Originality/valueThis is an original study based on primary data from UAE manufacturing firms.

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