Application of Statistical Analysis Tools and Concepts to Big Data and Predictive Analytics to New Product Development

2020 ◽  
Vol 3 (1) ◽  
pp. 17-35
Author(s):  
Brian J. Galli
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Product Development ◽  
Competitive Advantage ◽  
New Product Development ◽  
New Product ◽  
Big Data Analysis ◽  
Life Cycles ◽  
The Impact

In today's fiercely competitive environment, most companies face the pressure of shorter product life cycles. Therefore, if companies want to maintain a competitive advantage in the market, they need to keep innovating and developing new products. If not, then they will face difficulties in developing and expanding markets and may go out of business. New product development is the key content of enterprise research and development, and it is also one of the strategic cores for enterprise survival and development. The success of new product development plays a decisive role both in the development of the company and in maintaining a competitive advantage in the industry. Since the beginning of the 21st century, with the continuous innovation and development of Internet technology, the era of big data has arrived. In the era of big data, enterprises' decision-making for new product development no longer solely relies on the experience of decision-makers; it is based on the results of big data analysis for more accurate and effective decisions. In this thesis, the case analysis is mainly carried out with Company A as an example. Also, it mainly introduces the decision made by Company A in the actual operation of new product development, which is based on the results of big data analysis from decision-making to decision-making innovation. The choice of decision-making is described in detail. Through the introduction of the case, the impact of big data on the decision-making process for new product development was explored. In the era of big data, it provides a new theoretical approach to new product development decision-making.

scholarly journals A multi-dimensional approach for managing open innovation in NPD

2017 ◽  
Vol 37 (10) ◽  
pp. 1366-1385 ◽  
Author(s):  
Hanna Bahemia ◽  
Brian Squire ◽  
Paul Cousins
Keyword(s):  
Product Development ◽  
Competitive Advantage ◽  
New Product Development ◽  
New Product ◽  
Three Dimensions ◽  
Longitudinal Impact ◽  
Product Innovativeness ◽  
Content Type ◽  
The Impact ◽  
Positive Effect

Purpose This paper explores openness within new product development (NPD) projects. The purpose of this paper is to examine the impact of breadth, depth and partner newness on product innovativeness and product competitive advantage. The authors also seek to examine the contingent effects of the appropriability regime. The authors make suggestions to academics and practitioners based on the findings. Design/methodology/approach The authors use a structured survey instrument producing an empirical analysis of 205 NPD projects in the manufacturing sector in the UK. The authors use an ordinary least squares regression model to test hypothesised relationships between openness (breadth, depth and partner newness), product innovativeness, product competitive advantage and the appropriability regime. Findings The authors find that each of the three dimensions of openness, depth, breadth and partner newness, have a significant but differing impact on product innovativeness. Specifically, the study indicates that breadth has a positive effect but only in the presence of a strong appropriability regime, partner newness has a direct positive effect, and depth a direct negative effect. The authors also find that product innovativeness has a positive impact on product competitive advantage. Research limitations/implications Further research should focus on replicating the findings in other countries, search for further moderating factors, such as the stage of the NPD process, and analyse the longitudinal impact of openness within NPD projects. Practical implications Organisations are encouraging managers to be more open in their approach to NPD. The authors’ findings suggest that managers need to think about the three dimensions of openness, breadth, depth and partner newness. Their engagement with each of these dimensions depends on the desired outcomes of the innovation project and the strength of patents. Originality/value The research extends the extant supplier involvement in new product development literature to examine the effect of up to 11 types of external actor in NPD projects. The authors test a new multi-dimensional measurement scale for the openness construct. The authors show that each dimension has a different relationship with product innovativeness.

scholarly journals The impact of big data analysis on competitive advantage support (Field study on industrial companies listed on the Palestine Stock Exchange)

2021 ◽  
Vol 10 (3) ◽  
pp. 630-646
Author(s):  
Abd El Rahman Mohammed Rashwan ◽  
Mohammed Atef Madi
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Competitive Advantage ◽  
Stock Exchange ◽  
Big Data Analysis ◽  
Quality Of Data ◽  
Industrial Companies ◽  
General Managers ◽  
Leadership Strategy ◽  
The Impact

The study was aimed at identifying the impact of big data analysis on supporting the competitive advantage of industrial companies listed on the Palestine Stock Exchange, the study used the descriptive analytical approach, and conducted the study on a sample of (49) general managers, financial and administrative in the industrial companies listed on the Palestine Stock Exchange, and concluded the study there is a significant impact of the analysis of big data on (strengthening competitive position, cost leadership strategy, strategy of excellence, strategy of focus) in the industrial companies listed on the Palestine Stock Exchange, and recommended that companies listed industrial in Palestine work on Do more big data analysis to support and enhance investors' decision-making ability by improving the quality of data obtained, and you need to have correct information about customers, products and the environment around the company in the fastest and least time to access the competitive advantage that big data analysis can provide.

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.

scholarly journals The Impact of Structural Capital on New Product Development Performance Effectiveness- The Mediating Role of New Product Vision and Competitive Advantage

2014 ◽  
Vol 3 (4) ◽  
pp. 281 ◽  
Author(s):  
Mohammad Hossein Khasmafkan Nezam ◽  
Ali Ataffar ◽  
Ali Nasr Isfahani ◽  
Arash Shahin
Keyword(s):  
Product Development ◽  
Competitive Advantage ◽  
New Product Development ◽  
New Product ◽  
Structural Equations ◽  
Mediating Role ◽  
Structural Capital ◽  
Study Results ◽  
The Impact

For organizations mostly, changes are faster than their speed in responsibility and the ability for adjustment. In this space, organizations face with opportunities and threats. Therefore each invention and innovation causes change that may create opportunity for organization. So having proper structural capital is very important. Organizations should develop their new products and share clear vision in order to improve the effectiveness of their new product development performance. Therefore, this research wants to investigate and model the relationship between structural capital (SC) and new product development performance (NPDP) effectiveness with regard to the mediating role of new product competitive advantage and vision. Automobile industry in Iran is elected as statistical society. In this study, results are obtained by structural equations and path model. Also for better description of results, we use other deducible statistic such as binamial test and one-Sample Kolmogorov-Smirnov Test. The results of this study bode that structural capital can improve NPDP effectiveness by obtaining competitive advantage and providing clear and comprehensive vision. Also the provided model in this research is supported by data.

The impact of business analytics capability on data-driven culture and exploration: achieving a competitive advantage

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Najah Almazmomi ◽  
Aboobucker Ilmudeen ◽  
Alaa A. Qaffas
Keyword(s):  
Product Development ◽  
Competitive Advantage ◽  
New Product Development ◽  
Structural Equation ◽  
New Product ◽  
Data Driven ◽  
Business Analytics ◽  
Content Type ◽  
The Impact ◽  
Analytics Capability

PurposeIn today's business setting, the business analytic capability, data-driven culture and product development features are highly pronounced in light of the firm's competitive advantage. Though widespread attention has been given to the above concepts, there hasn't been much research done on how it could support achieving competitive advantage.Design/methodology/approachThis research strongly lies on the theoretical background and empirically tests the hypothesized relationships. The primary survey of 272 responses was analysed by using the partial least squares structural equation modelling (PLS-SEM).FindingsThe findings of this study show a significant relationship for the constructs in the research model except for the third hypothesis. Accordingly, the firm's data-driven culture does not have a significant impact on new product newness.Originality/valueThis study empirically tests the business analytics capability, data-driven culture, and new product development features in the context of a firm's competitive advantage. The findings of this study contribute to the theoretical, practical and managerial aspects of this field.

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