The variety of ICT adopters in the intra-firm diffusion process: Theoretical arguments and empirical evidence

Abstract

This paper proposes to analyse intra-firm ICT diffusion with a specific focus on the differentiation of the types of ICTs adopted. Its theoretical foundations rest on three sources: (i) models of technology diffusion, (ii) Milgrom's and Roberts’ complementarity hypothesis (1990), and (iii) the neo-Schumpeterian theory of technological choices. Cluster analyses and a multinomial logit model are used to show the coexistence of four ICT adoption modes characterized by different ICT choices, as well as by different strategic, organizational and environmental patterns. The dataset is based on a cross-sectional survey of French firms, which was conducted in 2002.

Introduction

The diffusion of information and communication technologies (ICTs) has recently been the subject of numerous empirical analyses (see for example the review of Hollenstein, 2004). The issue is indeed essential in that ICTs are probably one of the most important technological tools in the so-called “knowledge-based economy”. It is widely admitted that the adoption and command of these technologies is likely to accelerate the growth of the firms and countries which are able to exploit them. Understanding the ICT diffusion process therefore constitutes a fundamental issue.

Some contributions have, however, emphasized the complexity of the technological diffusion process (e.g. Gold, 1981, Leseure et al., 2004), by more particularly underlining the differences between inter- and intra-firm diffusion (Battisti and Stoneman, 2003, Battisti and Stoneman, 2005). Inter-firm diffusion relates to the time evolution of the percentage of firms having adopted a given technology, while intra-firm diffusion deals with the intensity of use of this technology at a certain point in time. The inter-firm phenomenon may therefore be more important in the early stages of diffusion, whereas the intra-firm effect may become more relevant at the later stages of diffusion. Given that we observe ICT diffusion on the basis of a cross-sectional survey of French firms, which was carried out in 2002, we are in no position to address empirically the inter-firm issue appropriately. We therefore mean to focus on the intra-firm diffusion process here.

Although some determinants of technology adoption are common to intra- and inter-firm diffusion processes, Battisti and Stoneman have recently stressed that the usual stock-order and epidemic effects are probably less significant in the former. The spread of information about the new technology is indeed not enough to trigger an intra-firm diffusion process if the firm has not developed an adequate knowledge absorption capacity first. Moreover, these researchers’ empirical results reveal that rank and profitability effects are significant determinants of the intra-firm diffusion process of computer-numerically controlled (CNC) machine tools in the U.K., while epidemic effects are not.

In this paper, we mean to build an empirical model with a view to uncovering the determinants of intra-firm ICT diffusion by choosing a specific approach to deal with this type of technologies. The “ICT” label actually refers to a wide range of rather different tools such as EDI systems, ERP software, Intranet/Extranet networks, tracking software, Web marketplaces, and so on. Firms do not necessarily adopt all these components, nor do they adopt them all at the same time. It is therefore difficult to define precisely the notion of intra-firm intensity of ICT use: should this notion be captured by counting the number of different kinds of ICTs used in the firm, or should it be measured by calculating the share of “new” ICT capital in total capital? In the latter case, it would be necessary to choose a specific type of ICT capital (e.g. ERP). This would lead to results specific to the type of ICTs adopted. Furthermore, this approach would require a suitable database to compute the shares of “new” ICT capital. Given that we do not have such a database and that our focus is on the possible diversity of intra-firm diffusion patterns, we propose an alternative empirical methodology whereby the measurement of intra-firm ICT diffusion is twofold: (i) firms are classified into ICT use intensity categories on the basis of a count of the different kinds of ICTs they have adopted, and (ii) these categories account as well for the specific types of ICTs adopted. Applying only the first criterion would lead a firm with EDI and ERP to be classified in the same category as a firm with a tracking software and Web marketplace. This will not necessarily be the case in our study.

The methodology we intend to use here allows us to assess the variety of intra-firm diffusion patterns in the case of ICTs.¹

Concerning the determinants of intra-firm ICT diffusion, we may derive strong arguments from two well-known approaches. The first is a literature dealing mainly with inter-firm technological diffusion, which emphasizes the importance of rank, stock-order and epidemic effects. As shown by Battisti and Stoneman, 2003, Battisti and Stoneman, 2005, it is possible to apply this “diffusion view”² to the intra-firm context after some adaptation. The latter researchers have more particularly observed that order effects are no longer conceptually relevant in this context, and that epidemic effects are not empirically significant. Our data will allow us to test the significance of rank effects.

The second approach is the “complementarity hypothesis” (Milgrom and Roberts, 1990, Milgrom and Roberts, 1995, Milgrom et al., 1995), which states that firms adopt a particular technology when it optimally fits their organizational design. More precisely, ICTs are considered to be complementary with certain flexibility-oriented practices in the field of strategic and organizational choices. This approach holds that ICT adoption is correlated with the adoption of these “flexibility-oriented” practices, and that this joint adoption generates productivity gains. Our database contains information on both strategic choices and organizational practices, which will allow us to control such effects in the empirical analysis of the determinants of ICT adoption.

By merging these two approaches into adoption equations, the empirical literature has provided evidence that rank, stock(-order), epidemic and complementarity effects do affect ICT or Advanced Manufacturing Technology (AMT)³ adoption (see for example Colombo and Mosconi, 1995, Arvanitis and Hollenstein, 2001). However, as shown in recent studies, the adoption sequence is still not clear (Grenadier and Weiss, 1997, Hollenstein, 2004, Battisti and Stoneman, 2003, Battisti and Stoneman, 2005), and partial adoption remains a complex phenomenon, which may indeed be partly explained by factors proposed by the diffusion and the complementarity views. In particular, some firms are low or average ICT users because their organizational practices are not complementary enough with these technologies. In this case, the complementarity approach and the diffusion view provide very similar explanations: partial adoption is an equilibrium outcome resulting from exogenous factors such as adjustment costs (rank and stock effects), insufficient managerial capabilities, or lack of relevant information. Partial adoption is the best choice within a constrained environment. In the same way, Battisti and Stoneman use the option-theoretic framework to show that delayed adoption can be regarded as an optimal use of the “option to wait” within an uncertain environment.

However, as once suggested by Gold (1981) and more recently pointed out by Leseure et al. (2004), profit maximisation is not the only rationale for the adoption decision. The ability to learn, the capacity to clearly identify the needs covered by the new technology, and the environment's stability are good candidates as well. Since our database allows us to construct measures of such determinants, we adopt a neo-Schumpeterian conception of the firm's technological choices, and take these determinants into account to explain the plurality of adoption modes in the intra-firm diffusion process.

The descriptive analysis outlines the plurality of adoption modes through a specially designed survey of French firms located in Haute-Savoie. Cluster analysis is used to detect the presence of archetypes of ICT adopters, as well as a multinomial logit model to test whether intra-firm diffusion is explained by factors stemming from the diffusion, the complementarity, and the neo-Schumpeterian views.

The present paper is organized as follows: Section 2 presents the theoretical foundations, which it extends by introducing elements of the neo-Schumpeterian approach; Section 3 reviews the related empirical literature; Section 4 sets out the empirical procedure and describes the dataset; Section 5 expounds the empirical results; and finally, Section 6 presents the conclusions.