A Linguistic Approach to Measuring the Attractiveness of New Products in Portfolio Selection
Ching-Torng Lin
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Yuan-Shan Yang
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Y.-S. Yang Ph. D Program in Management, Dayeh University, 168 University Rd.
, Dacun, Changhua 51591,
Taiwan
To gain a competitive edge, companies must continually invest in new product development (NPD), and must decide how to strategically allocate limited resources. The most critical NPD activity is the accurate assessment of the attractiveness of new products, simultaneously considering favorable factors (project value and strategic fit) and unfavorable factors (project risks), especially in robust companies in developing countries. In the NPD development process, the attractiveness of products is often evaluated using information that is imprecise or ambiguous. Fuzzy logic is well-suited to inform NPD decision-making. Thus, a comprehensive method considering both favorable and unfavorable factors, and using a fuzzy weighted average to devise a fuzzy possible-attractiveness rating (FPAR) of an NPD project for portfolio selection, is proposed in this paper. FPAR is a measurement of information, which is able to retain the multiplicity of that information. The proposed evaluation technique was demonstrated using a Taiwanese company as an example. The results indicated that this method provided an accurate assessment of overall product attractiveness, necessary for obtaining organizational buy-in, and can effectively aid managers to conduct sensitive analyses, balance the impact of changes in strategy, and receive quick feedback on the results of such changes.
1 Introduction
Technological innovations and new business practices, as well as mounting market
competition worldwide, have forced many firms, such as Google, Apple, Alexion
Pharmaceuticals, and Tesla Motors, to accelerate new product development (NPD)
to maintain long-term growth and sustainability (Hammond et al. 2006; Oke et al.
2007). New product portfolio selection is crucial and vital for successful innovation.
However, portfolio decisions are difficult because of the combinatorial complexity
involved in allocating limited resources to develop a multiplicity of new products;
moreover, necessary information is often incomplete or ambiguous, and selection
criteria are interdependent and often conflict (Loch and Kavadiaa 2002; Zapata et al. 2008).
To assist managers in new product portfolio selection, numerous decision-enhancing
tools, such as mathematical programming, economic models, option pricing theory,
scoring models, and analytical hierarchy approaches, have been developed. However,
most of these techniques have both practical and theoretical limitations (Griffin 1997;
Henriksen and Traynor 1999; Hans et al. 2007); these approaches are unable to take
holistic views, provide limited information on financial results, and offer dubious
probabilities of completion (Kornfeld and Kara 2011; Griffin 1997; Kornfeld and
Kara 2011). Furthermore, mathematical portfolio approaches have tended to provide
inadequate understandings of risk and information, and are unable to handle multiple
interrelated criteria (Lin and Chen 2004). They generally fail to recognize
interrelationships with respect to the payoffs of combined utilization of resources (Griffin
1997; Lin and Chen 2004; Ghasemzadeh and Archer 2000), and address only some of
the aforementioned issues (Zapata et al. 2008). Finally, managers typically perceive
such techniques to be too difficult to use and understand (Griffin 1997; Kornfeld and
Kara 2011).
Portfolio management is a complex, dynamic process involving substantial
decision-making. Managers must allocate a limited set of resources to projects in
a manner that balances risk and reward, and aligns with their strategies, which
may not be easily expressed in numerical values. Conventional crisp
evaluation approaches are inadequate to suitably or effectively inform such decisions.
People are capable of understanding and analyzing obscure and imprecise events,
but this level of comprehension is difficult to incorporate into existing analytical
methods. Therefore, NPD decisions are executed primarily on the basis of expert
opinions expressed not in numbers, but in linguistic terms, which are inherently
vague. One way to objectively capture the meaning of linguistic terms is to use
the fuzzy logic approach to associate each term with a possibility distribution
(Dubois and Prade 1988). By using the concepts of multicriteria decision-making
(MCDM), and a fuzzy-weighted average technique, a fuzzy possible-attractiveness
rating (FPAR) was devised to conduct for new product portfolio selection. The
proposed fuzzy logic new product portfolio selection model (FLNPPSM), integrating
strategic fit and both product value and risk into a flexible formulation, can
effectively aid managers dealing with ambiguity and complexity in the portfolio selection
process. The development of FPAR and FLNPPSM is the main contribution of this
paper.
2 Literature Review
Portfolio management is critical, yet complex, and a wide (...truncated)