Toward a theory of project interdependencies in high tech R&D environments

Abstract

In today’s intensely competitive market place, high technology firms are challenged with the task of managing multiple‐concurrent research and development (R&D) projects with constrained resources. As success in the business world depends on the ability to do more with less, it is important for these high technology firms to understand why certain projects consume less monetary resources but still achieve superior product development outcomes. To address this question, we develop a theoretical framework for understanding the interdependencies between projects and their relationship to project performance in a multiple‐concurrent R&D environment. The framework is developed through multiple‐case studies of projects undertaken by a Fortune 500 high technology manufacturing firm. The seven projects that comprised the sample for the multiple‐case study were chosen from a larger portfolio of projects belonging to a technology group at the firm’s corporate R&D center. The choice of the seven projects was guided by a data envelopment analysis (DEA)‐based project performance metric, also proposed in this paper.

Managing portfolio interdependencies

“…However, projects are often interdependent, and the literature highlights a range of types of interdependencies, such as resource and technical dependencies, and dependencies based on learning and organizational structures (Jerbrant, 2013, Parker et al, 2015, Verma and Sinha, 2002, Eilat et al, 2006, Blau et al, 2004, Killen and Kjaer, 2012, Bathallath et al, 2016. Understanding these interdependencies is important because they can result in flow-on effects throughout the portfolio, stemming from decisions or problems related to individual projects (Aritua et al, 2009, Collyer andWarren, 2009).…”

Project, Program and Portfolio Risk Perceptions

“…Interdependencies may be classified in different ways. For instance, [53] mentioned three origins of interdependencies including: resources shared by different Projects, a single technology developed by different Projects and market conditions having an effect on objectives and specifications of different Projects.…”

Using DEA and Malmquist Productivity Index to Analyze the Operational Efficiency of Taiwan Biotechnological Industry

“…They found that there is a technology push factor related to the development of biotechnology and, the demand pull related to the growing R&D performance required by the market. Verma and Sinha (2002) developed a theoretical framework for understanding the interdependencies between project and their relationship to project performance, based on the Fortune 500 high-tech manufacturing firm, in a multiple-concurrent R&D environment. Niosi and Banik (2005) work was based on 90 Canadian-based publicly quoted biotechnology companies.…”

“…The price of assets is a proxy and is obtained by the interest level. Dividing the sum of R&D expenses into net business revenues derives the price of R&D expenses Verma and Sinha (2002). Literature affirms the assumption that most firms operate with variable returns to scale rather than constant returns to scale, hence it is considered practical to present CRS as well as VRS results to add richness of the analysis.…”