Unlocking the power of big data analytics in new product development: An intelligent product design framework in the furniture industry

2021 ◽  
Author(s):  
Y.P. Tsang ◽  
C.H. Wu ◽  
Kuo-Yi Lin ◽  
Y.K. Tse ◽  
G.T.S. Ho ◽  
...  
Keyword(s):  
Big Data ◽  
Product Development ◽  
Product Design ◽  
New Product Development ◽  
Data Analytics ◽  
Big Data Analytics ◽  
New Product ◽  
Design Framework ◽  
Furniture Industry ◽  
Intelligent Product

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.

Business model designs, big data analytics capabilities and new product development performance: evidence from China

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Biao Sun ◽  
Yu Liu
Keyword(s):  
Big Data ◽  
Product Development ◽  
New Product Development ◽  
Business Model ◽  
Data Analytics ◽  
Big Data Analytics ◽  
New Product ◽  
Moderating Effects ◽  
Content Type ◽  
Npd Performance

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.

scholarly journals A Parametric Product Design Framework for the Development of Mass Customized Head/Face (Eyewear) Products

2021 ◽  
Vol 11 (12) ◽  
pp. 5382
Author(s):  
Xiaobo Bai ◽  
Omar Huerta ◽  
Ertu Unver ◽  
James Allen ◽  
Jane E. Clayton
Keyword(s):  
Product Development ◽  
Product Design ◽  
New Product Development ◽  
Mass Customization ◽  
Parametric Design ◽  
Early Stage ◽  
New Product ◽  
Parametric Modelling ◽  
Design Framework ◽  
Human Face

This study led to the development of a parametric design method for mass-customised head/face products. A systematic review of different approaches for mass customization was conducted, identifying advantages and limitations for their application to new product development. A parametric modelling algorithm of a 3D human face was developed using selected scanned 3D head models. The algorithm was developed from a set of measurable and adjustable parameter points related to the facial geometry. These parameters were defined using planimetry. Using the assigned parameter values as input, the parametric model generated 3D models of a human face that served as a reference for the design of customized eyewear. The current challenges and opportunities of mass customized head/face products are described, along with the possibilities for new parametric product design approaches to enable rapid manufacturing and mass customization. This study also explored whether a new parametric design framework for mass customization could be effectively implemented as an early-stage new product development strategy for head/face products.

scholarly journals Traditional marketing analytics, big data analytics and big data system quality and the success of new product development

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 ◽  
New Product Development ◽  
Data Analytics ◽  
Big Data Analytics ◽  
New Product ◽  
Data System ◽  
System Quality ◽  
Content Type ◽  
Traditional Marketing

PurposeThis study investigates the impact of traditional marketing analytics and big data analytics on the success of a new product. Moreover, it assesses the mediating effects of the quality of big data system.Design/methodology/approachThis study is based on primary data that were collected through an online questionnaire survey from large manufacturing firms operating in UAE. Out of total distributed 421 samples, 327 samples were used for final data analysis. The survey was conducted from March–April 2020, and data analysis was done via Structural Equation Modelling (SEM-PLS).FindingsIt emerges that big data analysis (BDA), traditional marketing analysis (TMA) and big data system quality (BDSQ) are significant determinants of new product development (NPD) success. Meanwhile, the BDA and TMA significantly affect the BDSQ. Results of the mediating role of BDSQ in the relationship between the BDA and NPD, as well as TMA and NPD, are significant.Practical implicationsThere are significant policy implications for practitioners and researchers concerning the role of analytics, particularly big data analytics and big data system quality, when attempting to achieve success in developing new products.Originality/valueThis is an original study based on primary data from UAE.

Application of Rapid Prototyping Technology in Product Design

2014 ◽  
Vol 989-994 ◽  
pp. 3208-3211
Author(s):  
Dan Tong Li ◽  
Zheng Zhang ◽  
Jia Wen Deng ◽  
Ming Yu Huang ◽  
Xiao Feng Wan ◽  
...  
Keyword(s):  
Product Development ◽  
Rapid Prototyping ◽  
Product Design ◽  
New Product Development ◽  
Medical Model ◽  
New Product ◽  
Mechanical Parts

The rapid prototyping technology was introduced, including its definition, principle and characteristics. The advantages of rapid prototyping technology in new product development were analyzed. Application of rapid prototyping technology in design of mechanical parts, industrial model, medical model, ceramic products, automobile model and products based on ergonomics was discussed. The feasibility of rapid prototyping technology in product design and the optimization direction was prospected.

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.

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