scholarly journals Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation

2021 ◽  
Vol 123 ◽  
pp. 1-13
Author(s):  
Francesco Ciampi ◽  
Stefano Demi ◽  
Alessandro Magrini ◽  
Giacomo Marzi ◽  
Armando Papa
Keyword(s):  
Big Data ◽  
Business Model ◽  
Entrepreneurial Orientation ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Business Model Innovation ◽  
Mediating Role ◽  
The Impact

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.

Social capital and business model innovation in SMEs: do organizational learning capabilities and entrepreneurial orientation really matter?

2020 ◽  
Vol 24 (1) ◽  
pp. 191-212
Author(s):  
Samar Hayat Khan ◽  
Abdul Majid ◽  
Muhammad Yasir ◽  
Asad Javed
Keyword(s):  
Social Capital ◽  
Organizational Learning ◽  
Business Model ◽  
Entrepreneurial Orientation ◽  
Business Model Innovation ◽  
Content Type ◽  
Mediating Role ◽  
Learning Capabilities ◽  
The Relationship

PurposeThis research aims to concentrate on the important concern that how social capital (SC) influences business model innovation (BMI) in the course of the mediating role of organizational learning capabilities (OLC) and the moderating role of entrepreneurial orientation (EO). In the context of small and medium enterprises (SMEs), this study empirically tested a theoretical model of BMI to advocate a mechanism for the analysis of its significant determinants.Design/methodology/approachIn order to achieve the objective of the research, survey method was utilized, and data were collected from 521 CEOs, MDs and the owners of ICT sector SMEs. Correlation, causal step approach and regression analysis were used to test the proposed model.FindingsFinding of the research advocates that OLC mediate the relationship between SC and BMI. In addition, stronger EO augments the association between OLC and BMI.Practical implicationsThe study adds to the literature by providing insights regarding the impact of SC, OLC and EO on BMI of small firms.Originality/valueThis research enriches the existing knowledge by testing a mediating role of OLC between SC-BMI link and, therefore, makes an important addition to the existing knowledge in the context of SMEs by concentrating on the relationship between SC, OLC, BMI and EO.

scholarly journals Operationalizing Business Model Innovation through Big Data Analytics for Sustainable Organizations

2019 ◽  
Vol 12 (1) ◽  
pp. 277 ◽  
Author(s):  
Vinicius Luiz Ferraz Minatogawa ◽  
Matheus Munhoz Vieira Franco ◽  
Izabela Simon Rampasso ◽  
Rosley Anholon ◽  
Ruy Quadros ◽  
...  
Keyword(s):  
Big Data ◽  
Performance Management ◽  
Business Model ◽  
Small Businesses ◽  
Data Analytics ◽  
Design Science ◽  
Big Data Analytics ◽  
Business Model Innovation ◽  
Raw Material ◽  
Animal Origin

Business model innovation is considered key for organizations to achieve sustainability. However, there are many problems involving the operationalization of business model innovation. We used a design science methodology to develop an artifact to assist business model innovation efforts. The artifact uses performance measurement indicators of the company’s business model, which are powered by Big Data analytics to endow customer-driven business model innovation. Then, we applied the artifact in a critical case study. The selected company is a fashion ecommerce that proposes a vegan and sustainable value using recycled plastic bottle yarn as raw material, and ensures that no material with animal origin is used. Our findings show that the artifact successfully assists a proactive and continuous effort towards business model innovation. Although based on technical concepts, the artifact is accessible to the context of small businesses, which helps to democratize the practices of business model innovation and Big Data analytics beyond large organizations. We contribute to the business model innovation literature by connecting it to performance management and Big Data and providing paths for its operationalization. Consequently, in practice, the proposed artifact can assist managers dealing with business model as a dynamic element towards a sustainable company.

scholarly journals The role of big data for Supply Chain 4.0 in manufacturing organisations of developing countries

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vaibhav S. Narwane ◽  
Rakesh D. Raut ◽  
Vinay Surendra Yadav ◽  
Naoufel Cheikhrouhou ◽  
Balkrishna E. Narkhede ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Business Performance ◽  
Big Data Analytics ◽  
Content Type ◽  
Performance Factors ◽  
Mediating Role ◽  
Sustainable Procurement

PurposeBig data is relevant to the supply chain, as it provides analytics tools for decision-making and business intelligence. Supply Chain 4.0 and big data are necessary for organisations to handle volatile, dynamic and global value networks. This paper aims to investigate the mediating role of “big data analytics” between Supply Chain 4.0 business performance and nine performance factors.Design/methodology/approachA two-stage hybrid model of statistical analysis and artificial neural network analysis is used for analysing the data. Data gathered from 321 responses from 40 Indian manufacturing organisations are collected for the analysis.FindingsStatistical analysis results show that performance factors of organisational and top management, sustainable procurement and sourcing, environmental, information and product delivery, operational, technical and knowledge, and collaborative planning have a significant effect on big data adoption. Furthermore, the results were given to the artificial neural network model as input and results show “information and product delivery” and “sustainable procurement and sourcing” as the two most vital predictors of big data adoption.Research limitations/implicationsThis study confirms the mediating role of big data for Supply Chain 4.0 in manufacturing organisations of developing countries. This study guides to formulate management policies and organisation vision about big data analytics.Originality/valueFor the first time, the impact of big data on Supply Chain 4.0 is discussed in the context of Indian manufacturing organisations. The proposed hybrid model intends to evaluate the mediating role of big data analytics to enhance Supply Chain 4.0 business performance.

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