Int. Journal of Business Science and Applied Management, Volume 10, Issue 1, 2015

Designing an AHP methodology to prioritize critical elements for

product innovation: an intellectual capital perspective

Ana Paula Ramos

University Institute of Maia (ISMAI)

Av. Carlos Oliveira Campos – Castelo da Maia, 4475-690 Maia, Portugal

Phone: +351 229 866 000

Email: anapaula.ramos9@gmail.com

Abstract

relative importance for product innovation performance at the firm level. The main goal of this research is to

build a diagnosis and action tool that helps business managers incorporate an intellectual capital perspective into

their product innovation initiatives. This framework will help managers to better understand which intellectual

capital elements are more critical to their product innovation efforts, and thereby systematize actions and clarify

resource allocation priorities to improve their product innovation capabilities. In order to validate the

practicability of this proposal, the methodology was empirically applied to a Portuguese innovative company.

Keywords: intellectual capital, product innovation, Analytic Hierarchy Process, Portugal, AHP, SMEs

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technological evolution, accelerated product cycles and rapid changes in consumers’ needs and expectations

(Daneels, 2002).

Against this backdrop, two critical factors for the competitiveness of firms assume particular relevance:

intellectual capital (IC) and innovation.

In fact, as the “resource-based view of the firm” stream of research began to highlight (Barney, 1991;

Wernerfelt, 1984), resources and competencies of intangible characteristics, as opposed to the traditional “land,

labour and financial capital”, have gradually emerged as critical success factors to corporations. Intangible

assets comply particularly well with the assumption that only valuable, rare, inimitable and non-substitutable

resources are potential sources of sustainable competitive advantages (Barney, 1991; Itami, 1987). It is now

abundantly clear that intangible assets are driving value creation in today’s global economy (Dumay and

Verde et al., 2011).

As we will argue in our literature review section, several studies have linked intangible assets, and IC in

particular, to the firms’ ability to innovate. It thus seems especially relevant for managers to be able to analyse

and manage this relationship, so that actions can be taken and strategies corrected in order to develop and

improve the firm’s innovation capabilities. The main goal of this article is thus to try to address this need.

Specifically, we will design and test a model to allow the prioritization of IC elements according to their relative

importance to product innovation success at the firm level.

The structure of the paper is as follows: the following section proposes a brief review of the literature

regarding IC, product innovation, the relationships between those concepts, and the benefits of measuring IC.

The next section presents our proposed methodology to prioritize critical IC indicators for product innovation,

of corporations, through the analysis of the intangible assets’ contribution to an organization (Roos et al., 2001).

As stated by Petty and Guthrie (2000), the IC perspective surfaced as a means to better understand what

constitutes the value of the business and to manage more successfully those elements that effectively generate

value.

Descriptions of IC abound in the literature, although there isn’t yet a clear, internationally accepted single

definition. For the purpose of this study, we will thus define IC as “the stocks or funds of knowledge, intangible

assets, and ultimately intangible resources and capabilities, which allow for the development of basic business

processes of organizations, enabling the achievement of competitive advantages” (Martín-de-Castro et al., 2011,

p. 650). IC is thus a multidimensional concept. It is nowadays generally accepted that the main components of

IC can be structured into three dimensions: human capital, structural capital and relational capital (Guthrie et al.,

human capital elements include skills and competencies of employees, their know-how in certain fields that are

important to the success of the enterprise, and their aptitudes and attitudes.

Structural capital is the knowledge that the company has managed to internalize and that remains in the

organisation, either in its structure, its processes or its culture, even when the employees leave. Martín-de-Castro

et al. (2011) subdivide structural capital into technological and organizational capital. The first one refers to the

development of the activities and functions of the technical system of the organization, responsible for obtaining

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products and services; the second one can be seen as the combination of explicit and implicit, formal and

informal knowledge which structure and develop the organizational activity of the firm. This includes culture,

structure and organizational learning. Bueno & Salmador (2000) refer to structural capital as the systematized

and explicit knowledge that has been internalized by the organisation, such as its values, culture, routines,

more important impact on how firms are managed. Brand image, corporate reputation, and product/service

reputation, which reflect the relationships between organizations and their (current and potential) customers,

also fall into this category. Bueno & Salmador (2000) state that relational capital represents the firm’s

“competitive and social intelligence”, while Martin-de-Castro (2011) adds that relational capital provides a

useful external guide for the firm to improve and develop new knowledge.

According to some authors (for example Dumay, 2014; Guthrie et al., 2012), IC research is nowadays

going through a new, emerging stage, characterised by growing calls for a more practice-based IC research,

supported on a critical and more interventionist analysis of IC practices in action.

2.2 Product Innovation

Innovation is in the core of economic change, and its role as the main driver of long term development is

improved product (good or service) or process, a new marketing method, or a new organisational method in

business practices, workplace organisation or external relations. Different types of innovations are also

distinguished: product innovations, process innovations, marketing innovations and organisational innovations.

Among these distinct types of innovations, product innovation stands out as an element of particular importance

to any business. Companies must develop new products, at least on occasion, to maintain or gain competitive

advantages, and their ability to create new products has been linked to performance and even long-term survival

(De Jong and Vermeulen, 2006; Linzalone, 2008). This study will therefore focus on product innovation,

defined in the Oslo Manual (OECD, 2005) as the introduction of a good or service that is new or significantly

improved with respect to its characteristics or intended uses.

The way firms approach product innovation, and particularly the process of new product development

some important trends: the increasing specialization in the production of knowledge, the increasing complexity

of physical products and the technology they use, and the need to accommodate new technological opportunities

with market needs and organizational practices. In this context, two central features of product innovation have

been emphasized: first, that the innovative process includes the coordination and integration of increasingly

specialized knowledge; second, that this process requires continuous learning, in conditions of great uncertainty

(Bullinger et al., 2004; Castellacci et al., 2005).

The increasing strategic importance of new products for companies and the awareness of the high

percentage of failures in their introduction led to the gradual development of formally structured NPD

processes. These are typically defined as a sequence of steps or activities that a company develops in order to

conceive, design, test and market a new product. The literature offers many different proposals and

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Lerro et al. (2014) argue that the resource-based view of the firm helped establish a very clear link between

intangible assets and innovation. Within this body of work, knowledge has emerged as a strategically significant

resource for the firm and has been asserted to play a significant role in the innovation process, as well as in

recognize and exploit opportunities abroad (an external perspective), and also on their "transformation" ability,

meaning the aptitude to continuously redefine their product portfolios based on the opportunities created within

the company (an internal perspective). The European Commission (2006) contends that there are strong links

and contingencies between research and development, innovation, human capital and relational capital. Other

studies state that firm-level knowledge is associated with a higher degree of innovation (Thornhill, 2006; Bueno

et al., 2010), and that knowledge assets can play a critical role in the different phases of the NPD process

(Linzalone, 2008).

The specific analysis of the relationship between IC and product innovation is scarcer. However, some

According to Marr (2004), organizations measure IC for different reasons: to formulate and assess strategy;

to influence people’s behaviour; and to externally validate performance, which includes reporting and

benchmarking. The European Commission (2006) argues that as the future potential of an enterprise lies not

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assessment and management of knowledge assets support the governance of an organization, not only by

improving strategy planning, but most importantly by affecting organizational behaviour.

According to Sveiby (2010), the most interesting reason for measuring intangibles is the learning motive.

The increasing awareness of the benefits of measuring and managing IC is reflected in the growing number

competitive and profitable. Yet, most companies do not identify core IC indicators in many areas that directly

influence business value, and those that do frequently use them in an inefficient manner (Kim and Kumar,

2009). The remaining of this article tries to address this issue, by offering some clues regarding the possibilities

of modelling and prioritizing IC indicators within a product innovation context.

hierarchy is built where at the top is the problem to be taken into consideration. The next layer consists in the

criteria or strategies to be considered; and the last layer resides in several alternative activities or actions (for

each of the criteria from the second level).

Based on comparative judgments, a positive matrix of choices is derived from these criteria. A ranking

structure is achieved afterwards as a vector of priorities, based on the theory of eigenvectors. The same

procedure is applied for the alternatives considered with respect to every criterion. Then, weights beard by the

criteria are applied to the considered alternatives and lastly, the corresponding totals for each alternative are

calculated. Within the very abstract and fuzzy framework of IC, the step by step approach provided by AHP,

breaking down the problem into smaller parts that can be more easily handled, represents an important

advantage.

established. Although the main goal of this research is not to develop a standardized IC model, but to propose a

methodology to prioritize critical IC elements as perceived by each company, we will materialize our

hierarchical structure with concrete IC elements and indicators, as a way to better explain and exemplify this

proposal. For that purpose, we will resort to the exact same structure and indicators suggested by the

aforementioned work of Costa et al. (2011), Dorrego et al. (2013) and Fernandez-Jardón et al. (2014) when

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studying the influence of intellectual capital elements on product innovation. Table 1 presents our suggested

hierarchical structure.

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The next step is to compare the relative importance of all variables. For that purpose a questionnaire must

be built, pairing components, elements and indicators, questioning which of each pair is more important with

regards to the objective, and how much more important. In order to help the respondent to assess the pair-wise

comparisons, Saaty created a nine point intensity scale of importance between two elements (Saaty, 2008).

Table 2 The fundamental scale for pair-wise comparisons (Saaty, 2008)

Level 2 – IC Components:

Level 3 - Human capital elements:

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The next step, the calculation of relative weights based on the answers to the questionnaire, can be

conducted using Microsoft Excel. As previous research suggested (Saaty, 2008), three steps are employed. They

are:

(a) Using questionnaire results to insert the data in Excel, building binary comparison matrices for each

level of the hierarchical structure;

(b) Calculating relative weights:

(b.1) Sum of each column of the matrix;

obtaining a new vector (consistency measure);

(c.2) If the matrix is consistent, the vector calculated in step c.1 will have values ideally equal to 1.

3.2 Testing the AHP methodology: empirical results

Once the conceptual structure of this methodology was completed, an empirical test of its functionality was

in order. More than any kind of frequency count or statistical generalization, our aim was to make sure that the

intended users of this tool (business managers) would understand its purpose and modus operandi, and to get

feedback on those issues as well as on the overall usefulness of the methodology. Considering these goals, an

“action research” approach seemed the most adequate way to fully apprehend how the framework would work

in practice. This methodological choice seeks to bring together action and reflection, theory and practice. The

researcher acts in concert with the host organisation, observes process and outcome, and analyses findings in

characterised by critically studying IC in practice, in search for the managerial implications of how to use IC in

managing a company. According to this perspective, “for IC research to remain relevant, researchers need to

concentrate on research based on managing IC at the operating level of case/field study/interviews rather than

taking a top-down approach to research.” (Dumay, 2014, p. 16).

Hence, in this section the implementation of our proposed model is demonstrated on a real firm, a

Portuguese innovative SME, as part of a larger case-study. The firm is located in northern Portugal and operates

in the chemical industry. Creating innovative products is one of its core strategic aims. It has around 100

employees and an annual turnover estimated at €72 million, thus complying with the European Commission

Recommendation 2003/361/EC from May 6th 2003 in what concerns its SME status. It operates both in the

domestic and international market, with the latter corresponding to 85% of its sales. The research was conducted

with the firm’s CEO, as suggested by the Oslo Manual (OECD, 2005), since he represents the key informant

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However, the company had never conducted any kind of structured initiative in order to systematise or measure

in any way the intangible resources that could impact product innovation. This study was therefore labelled as

very pertinent, as the respondent recognized the relevance of building a model that in an intuitive way depicts

the relative importance of each IC element to the firm’s innovation strategy.

weights and the resulting hierarchy. Recapping those steps, we started by building the binary comparison

matrices for each level of the hierarchical structure, based on the questionnaire results; then a new standardized

matrix was built from each original matrix, through dividing each cell by the sum of its corresponding column,

so that relative weights were calculated; next, the average of each line of the standardized matrix was calculated,

obtaining the column vector “w” (relative weight).

Some examples of this procedure will be depicted next, including level 2 IC components, level 3 elements

for human capital and level 4 indicators for the human capital element “Competencies”:

Level 3 - Human capital elements: