Article S12.5 Business Performance of New Products: Literature Review and Research Focus Md Washim Raja, Alok Pattanayak, Solomon James, Prajwalita A. Veronica Masih, Monalisha Ghosh Doctoral Candidates, Xavier University, Bhubaneswar, INDIA washim[at]stu.ximb.ac.in Suggested Citation: Washim Raja, M., Pattanayak, A., James, S., Masih, P. A .V., & Ghosh, M. (2015). Business performance of new products: Literature review and research focus. Research World, 12, Article S12.5. Retrieved from http://www1.ximb.ac.in/RW.nsf/pages/S12.5 Note. This report is based on the “Topic Registration Seminar” delivered by Shashisekhar M. S., Doctoral Candidate, Xavier Institute of Management, Xavier University, Bhubaneswar, India, on August 22, 2015. Doctoral scholar Shashishekhar M. S. discussed new product introduction (NPI) by business organisations. NPI is a strategic activity for development and commercialisation of new products. NPI affects business performance while influencing organisational capability. It has an influence on the profitability of a firm and it is recognised as a key to business success (Cooper, 2001). NPI includes all activities related to product development such as idea generation, idea screening, new product development, product launch, and monetisation. Interestingly, a majority of new products never make it to the market and, among those which are launched eventually, up to 45 per cent fail commercially (Cooper, 2001; Mendes & Ganga, 2013). 1. Influencers of NPI Performance Factors that influence NPI performance are spread over the entire product life cycle, including new product development as well as the process stages prior to and subsequent to new product development. The pre-development and post-development phases are rather nebulous and chaotic. Shashishekhar’s research aims to identify the most critical variables influencing NPI performance. Some of the variables considered relevant in this research are: market orientation, product advantage, degree of innovation, product development timeliness, and technology adoption. Mendes and Ganga (2013) have provided a framework to predict NPI performance (using principal component analysis and binomial logistic regression). Marketing orientation and market intelligence are considered critically important for NPI performance. Marketing orientation arises from the implementation of the marketing concept (Houston, 1986; McCarthy & Perreault, 1984). Marketing concept is essentially a business philosophy—an ideal or a policy with regard to the centrality of customer needs in all business decisions (Barksdale & Darden, 1971). Gathering reliable information on the current and future needs of customers is called market intelligence (Kohli & Jaworksi, 1990). Marketing literature suggests that long-term business performance is related to the above two concepts: marketing orientation and market intelligence. These require customer orientation, competitor orientation, and interfunctional coordination. These involve activities for acquiring information about customers and competitors in the target market and using the information for decision making in all areas of a business (Kohli & Jaworski, 1990; Narver & Slater, 1990). 2. NPI Performance Measures and Analytical Techniques NPI performance is a multidimensional concept. Therefore measuring NPI performance involves combining various aspects in order to get a comprehensive picture. It include efficiency measures (e.g., time to market, cycle time, and timeliness), product-level measure (e.g., degree of innovation, performance characteristics, and product advantages), market-level measures (e.g., technology adoption, customer satisfaction, competition, and sales volume), and financial measures (e.g., return on investment). Time to market is the elapsed time between product definition and product availability (Vesey, 1991). Cycle time is a similar concept which focuses on the product development cycle, starting from target identification, idea generation, up to the first sale (Griffin, 1993). Timeliness is the actual availability of the new product in comparison with the planned time frame (Chryssochoidis & Wong, 1998). Degree of innovation refers to the degree to which its new products are new to the world. It reflects the degree of firm’s acceptance and adoption of new ideas and concepts (Deshpandé, Grinstein, Kim, & Ofek, 2013; Hurley & Hult, 1998). Product advantage is the perceived superiority of a product (Song & Montoya-Weiss, 2001) and the benefits customers derive from it, compared to any competitive products (Calantone & di Benedetto, 1988; Cooper, 1979; Hua & Wemmerlöv, 2006; Slater & Narver, 1993). However, sometimes excessive focus on customer needs may result in a less competitive product (Christensen & Bower, 1996). Technology adoption can refer to the spread in the number of producers engaged in manufacturing a new product or the spread in the number of customers already using it. It is not easy to forecast the degree of adoption of a technologically innovative product. Various models exist to explain the diffusion and adoption process (Calantone & Gentry, 2007). Various analytical techniques are used in the study of NPI performance. These are often multivariate statistical techniques using artificial neural networks, fuzzy logic, and classification trees (Mendes & Ganga, 2013). 3. Potential Research Gaps Shashisekhar identifies the following gaps based on a review of the research literature in this area: (a) Effect of marketing orientation, degree of innovation, timeliness, product advantage, and technology adoption on NPI performance (b) Effect of various dimensions of product advantage and degree of innovation on NPI performance under specific market characteristics, such as alternative combinations of customer differentiation and product differentiation (Sheth, 1985) (c) Effect of various dimensions of product advantage on technology adoption (d) Effect of various dimensions of the degree of innovation on technology adoption and imitation, especially when NPI leads to the creation of a “blue ocean” (i.e., an uncontested market space). (e) Relationship between subjective and objective measures of NPI performance (f) Effective prediction of NPI performance using multivariate statistical techniques Shashisekhar stressed that further research is needed to study the longitudinal performance of new products. This could include the effects of marketing orientation, degree of innovation, technology adoption, and competition (especially the role of imitators). He would fine-tune his research focus by selecting the research gaps to be addressed, with an eye on uniqueness and relevance of the research. References Barksdale, H. C., & Darden, B. (1971). Marketers’ attitudes toward the marketing concept. Journal of Marketing, 35(4), 29-36. Calantone, R. J., & di Benedetto, C. A. (1988). An integrative model of the new product development process: An empirical validation. Journal of Product Innovation Management, 5(3), 201-215. Calantone, R. J., & Gentry, L. (2007). 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