Study on the Influence of Organizational Innovation on Organizational Performance under the Circumstances of Big Data : —Intermediary Role of Dynamic Capability

Author(s):  
Li Xiaoran ◽  
Shi Chunsheng ◽  
Wang Chenggang
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaofeng Su ◽  
Weipeng Zeng ◽  
Manhua Zheng ◽  
Xiaoli Jiang ◽  
Wenhe Lin ◽  
...  

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.


2019 ◽  
Vol 31 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Ly Minh Thi Pham ◽  
Lobel Trong Thuy Tran ◽  
Phanee Thipwong ◽  
Wan Tran Huang

Given the growing importance of organizational capabilities due to the dynamic nature of most markets, dynamic capability has been increasingly considered a key element of superior organizational performance. This article extends this link by the mediational role of social networking site integration (SNS) to develop a competitive advantage. Drawing from the resource-based view (RBV) and social capital theory, this article empirically examines the ability of recognizing and capitalizing opportunities of dynamic capability and SNS mechanisms (technical and administrative) affecting organizational performance. Using a sample of 124 hotel managers, the article successfully identifies the mediator role of SNS in the dynamic capability-organizational performance link.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ginevra Gravili ◽  
Francesco Manta ◽  
Concetta Lucia Cristofaro ◽  
Rocco Reina ◽  
Pierluigi Toma

PurposeThe aim of this paper is to analyze and measure the effects of intellectual capital (IC), i.e. human capital (HC), relational capital (RC) and structural capital (SC), on healthcare industry organizational performance and understanding the role of data analytics and big data (BD) in healthcare value creation (Wang et al., 2018). Through the assessment of determined variables specific for each component of IC, the paper identifies the guidelines and suggests propositions for a more efficient response in terms of services provided to citizens and, specifically, patients, as well as predicting effective strategies to improve the care management efficiency in terms of cost reduction.Design/methodology/approachThe study has a twofold approach: in the first part, the authors operated a systematic review of the academic literature aiming to enquire the relationship between IC, big data analytics (BDA) and healthcare system, which were also the descriptors employed. In the second part, the authors built an econometric model analyzed through panel data analysis, studying the relationship between IC, namely human, relational and structural capital indicators, and the performance of healthcare system in terms of performance. The study has been conducted on a sample of 28 European countries, notwithstanding the belonging to specific international or supranational bodies, between 2011 and 2016.FindingsThe paper proposes a data-driven model that presents new approach to IC assessment, extendable to other economic sectors beyond healthcare. It shows the existence of a positive impact (turning into a mathematical inverse relationship) of the human, relational and structural capital on the performance indicator, while the physical assets (i.e. the available beds in hospitals on total population) positively mediates the relationship, turning into a negative impact of non-IC related inputs on healthcare performance. The result is relevant in terms of managerial implications, enhancing the opportunity to highlight the crucial role of IC in the healthcare sector.Research limitations/implicationsThe relationship between IC indicators and performance could be employed in other sectors, disseminating new approaches in academic research. Through the establishment of a relationship between IC factors and performance, the authors implemented an approach in which healthcare organizations are active participants in their economic and social value creation. This challenges the views of knowledge sharing deeply held inside organizations by creating “new value” developed through a more collaborative and permeated approach in terms of knowledge spillovers. A limitation is given by a fragmented policymaking process which carries out different results in each country.Practical implicationsThe analysis provides interesting implications on multiple perspectives. The novelty of the study provides interesting implications for managers, practitioners and governmental bodies. A more efficient healthcare system could provide better results in terms of cost minimization and reduction of hospitalization period. Moreover, dissemination of new scientific knowledge and drivers of specialization enhances best practices sharing in the healthcare sector. On the other hand, an improvement in preventive medicine practices could help in reducing the overload of demand for curative treatments, on the perspective of sharply decreasing the avoidable deaths rate and improving societal standards.Originality/valueThe authors provide a new holistic framework on the relationship between IC, BDA and organizational performance in healthcare organizations through a systematic review approach and an empirical panel analysis at a multinational level, which is quite a novelty regarding the healthcare. There is little research focussed on healthcare industries' organizational performance, and, specifically, most of the research on IC in healthcare delivered results in terms of theoretical contribution and qualitative analyzes. The authors even contributed to analyze the healthcare industry in the light of the possible existence of synergies and networks among countries.


2021 ◽  
pp. 1111-1120 ◽  
Author(s):  
Nazlina Zakaria ◽  
Francis Chuah Chin Wei ◽  
Nor Azimah Chew Abdullah ◽  
Rushami Zien Yusoff

Many studies have focused on direct link between HRM practices and organizational performance. There is a strong relationship between these two variables that driven further research to identify the mechanism through which such relationship exists. Following resource-based view (RBV), the aim of this research was to investigate the indirect effect of organizational innovation on HRM practices-performance linkage. Data was collected from owners/managers of manufacturing SMEs in West Malaysia. 331 (60.5%) distributed questionnaires were received and analyzed through PLS-SEM. Out of six hypotheses on mediation, only one hypothesis was rejected. The findings strongly supported the RBV theory when organizational innovation significantly mediated the relationship. These results clearly indicate that organizational innovation plays an intermediate role between HRM practices (i.e. communication and information sharing, compensation, selection, performance appraisal, and training and development) and organizational performance of SMEs.


2020 ◽  
Vol 90 ◽  
pp. 581-592 ◽  
Author(s):  
Shivam Gupta ◽  
Vinayak A. Drave ◽  
Yogesh K. Dwivedi ◽  
Abdullah M. Baabdullah ◽  
Elvira Ismagilova

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ahmad Ibrahim Aljumah ◽  
Mohammed T. Nuseir ◽  
Md. Mahmudul Alam

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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