Outlining new product development research through bibliometrics

Abstract

Purpose New product development (NPD) is a noteworthy field that has attracted the attention of scholars for its relevance for firm success. Based on bibliometric indicators and spatial distance network analysis, the authors outline the general structure overview of NPD research through the last 40 years of scientific production; identify and categorize key articles, authors, journals, institutions, and countries related to NPD research; identify and map the research subareas that have mostly contributed to the construction of NPD intellectual structure. The paper aims to discuss these issues. Design/methodology/approach The work uses the Web of Science Core Collection and the visualization of similarities viewer software. The analysis searches for all the documents connected to NPD available in the database. The graphical visualization maps the bibliographic data in terms of bibliographic coupling and co-citation. Findings The general NPD citation pattern evidences a construction of knowledge and learning, as evidenced in different subjects, such as biology or physics. Relevant contributions and contributors are highlighted as journals, articles, researchers, countries and institutions in overall NPD research and in its constituent subfields. Five subareas related to the NPD field based on journals and authors network are identified: marketing; operations and production; strategy; industrial engineering and operations; and management. Originality/value This paper contributes to the NPD literature by offering a global perspective on the field by using bibliometric data graphical networks, providing insights about the influence of individual actors and its contributions to build bridges between the different subfields of research in NPD.

Bibliometric analysis of entrepreneurial orientation

“…For instance, mapping entire areas of research in full fields of study such as marketing (González-Valiente, 2014), strategic management (Maia et al , 2015) and even in other sciences, such as clinical medicine (Alfonzo et al , 2014; Xing et al , 2018). One of its strengths is that it can map field structures at different levels of analysis such as journals (Van Leeuwen and Wouters, 2017; Merigó et al , 2016; Kolle, 2016; Cancino et al , 2017), geographical spaces, countries or continents (Lu and Wolfram, 2010), and even more detailed subjects or sub fields like new product development (Andrade-Valbuena and Merigo, 2018), green supply chain management (Mishra et al , 2017), technology road mapping (Zhang et al , 2013), fuzzy research (Blanco-Mesa et al , 2016) among others. Moreover, specific constructs at the level of the firm as market orientation (Valenzuela-Fernández et al , 2018), or social value (Fulgencio et al , 2016) have been researched using this technique, highlighting its usefulness for outlining the literature on EO, purpose of this investigation.…”

Recent trends in agile new product development: a systematic review and agenda for future research

“…Later, Galli and Lopez (2018) analyzed articles to identify the implementation risks associated with ANPD projects in manufacturing firms and proposed risk management methodologies. Further, Andrade-Valbuena and Merigo (2018) conducted a bibliometric literature review to analyze journals, research papers and NPD scholars, as well as identify different sub-areas. Also (Borgianni et al, 2018), investigated the selection of design strategies during the product planning stage and discovered that agile and lean strategies appear to be more appropriate, whereas (Voltolini et al, 2019), expanded the use of ontologies for cost estimation.…”

“…Later, Galli and Lopez (2018) analyzed articles to identify the implementation risks associated with ANPD projects in manufacturing firms and proposed risk management methodologies. Further, Andrade-Valbuena and Merigo (2018) conducted a bibliometric literature review to analyze journals, research papers and NPD scholars, as well as identify different sub-areas. Also (Borgianni et al.…”

Biofuels and Nanocatalysts: Python Boosting Visualization of Similarities

“…A search on the Scopus database using the words “Visualization of Similarities” and VOSviewer returned eighty-two documents [ 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 , 186 , 187 , 188 , 189 , 190 , 191 , 192 , …”