Deep Data Analytics for New Product Development

Author(s):  
Walter R. Paczkowski
Author(s):  
Rameshwar Dubey ◽  
David J. Bryde ◽  
Gary Graham ◽  
Cyril Foropon ◽  
Sushma Kumari ◽  
...  

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.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Biao Sun ◽  
Yu Liu

PurposeAlthough the business model (BM) has become a top priority in management research, existing literature still offers a confusing and partial picture about how to leverage BM designs for new product development (NPD) because of two limitations. First, research has paid little attention to different BM designs' effects on NPD performance. Second, few empirical studies have examined the moderating roles of firms' learning capabilities, such as big data analytics capabilities (BDA capabilities). This study aims to investigate the effects of BM novelty design and BM efficiency design on NPD performance and the ways in which BDA capabilities moderate these effects.Design/methodology/approachA literature review provides the model and hypotheses. Using a sample of 208 Chinese firms, the authors conducted an empirical test following multiple regression analysis.FindingsThe results demonstrate that BM novelty design has a positive effect on NPD performance while BM efficiency design takes the form of an inverted U-shape. Moreover, BDA capabilities (i.e. BDA technology capability and BDA management capability) have complicated moderating effects on BM novelty design- and BM efficiency design-NPD performance relationships.Research limitations/implicationsThe results may be affected by both the context (solely in China) and type (cross-sectional) of the data set. This study has explored the moderating effects of BDA capabilities, further studies considering other significant practices such as social media usage, could yield richer insights that would help validate the results of this study.Practical implicationsFirst, we suggest that managers should be explicitly aware of the different impacts of BM novelty design and BM efficiency design on NPD performance. Second, this study encourages managers to build relevant BDA capabilities to work with BM designs to improve NPD performance.Originality/valueThis is one of the first studies to investigate BM designs' complicated influences on NPD success and explore BDA capabilities' moderating effects on the BM design-NPD performance linkage.


Author(s):  
Dundusid Porananond ◽  
◽  
Natcha Thawesaengskulthai ◽  

2017 ◽  
Vol 2017 ◽  
pp. 24-28
Author(s):  
Fabio Shimabukuro Sandes ◽  
◽  
Fundacao Getulio Vargas

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