Competitive behaviour, design and technical innovation in ... - CiteSeerX

222

Int. J. Biotechnology, Vol. 5, Nos. 3/4, 2003

Competitive behaviour, design and technical innovation in food and beverage multinationals Oscar Alfranca Escola Superior d’Agricultura de Barcelona, Universitat Politecnica de Catalunya, Urgell 187, 08036 Barcelona, Spain E-mail: [email protected]

Ruth Rama Instituto de Economia y Geografia, CSIC (Spanish Council for Scientific Research), Pinar 25, 280006 Madrid, Spain Fax: 34-91-562-55-67 E-mail: [email protected]

Nicholas von Tunzelmann SPRU, Freeman Centre University of Sussex Falmer, Brighton, BN1 9QE, uk E-mail: [email protected] Abstract: The main objective of this paper is to analyse long-term regularities in the pattern of generating technical innovation among global food and beverage multinationals (FBMs). In order to investigate persistent technological practices, we study a panel of 16,698 utility and design patents granted to 103 major FBMs from 1977 to 1994 and present econometric evidence on a joint-product formulation of such companies’ patents. The joint-product hypothesis implies that the production of patented inventions in FBMs is closely associated with both the effect of past research efforts in the multinational itself, and utility and design patents produced by other global F&B companies within the same sector. However, patenting in FBMs pertaining to other agri-food sectors does not induce technical innovation or new designs at the company level. Global food and drink firms show a stable pattern of technological accumulation in which ‘success breeds success’ but are also influenced by technical and design innovation developed within their international agri-food sector. Persistence is apparent not only in innovation intrinsic to foodstuffs and processes but also in packaging aesthetics. The temporary impact of past innovation is about two years in both cases. Technical and design innovations are associated. Technological opportunity seems to be similar across sectors. Keywords: competitive behaviour; design; innovation; patents; multinational enterprises; food and beverage industry. Reference to this paper should be made as follows: Alfranca, O., Rama, R. and von Tunzelmann, N. (2003) ‘Competitive behaviour, design and technical innovation in food and beverage multinationals’, Int. J. Biotechnology, Vol. 5, Nos. 3/4, pp.222–248. Copyright © 2003 Inderscience Enterprises Ltd.

Competitive behaviour, design and technical innovation

223

Biographical notes: Dr Oscar Alfranca has been an associate professor at Universitat Politecnica de Catalunya since 1992, and a researcher at the Institut Universitari d’Estudis Europeus, Universitat Autonoma de Barcelona since 1994. He obtained a PhD in Applied Economics from Universitat Autonoma de Barcelona in 1995. Before coming to the Universitat Politecnica de Catalunya, he was an economist for the Department of Agriculture of the Catalan Government. He has a been a visiting scholar at the Department of Economics of Iowa State University in 1999 and is currently a researcher at Department of Economics and Rural Sociology of INRA and the Université Pierre MendèsFrance in Grenoble, France. His main current interests are in the persistence of innovation, technology spillovers, public and private R&D interaction and research competition in imperfect markets (seed industries). He has published papers on total factor productivity analysis, R&D policy in agriculture and the persistence of innovation in agrifood multinationals in refereed journals such as Agribusiness, Agricultural Economics, Investigacion Agraria and the International Journal of Technology Management. Dr Ruth Rama has been Senior Researcher at the Institute of Economics and Geography of the Spanish Council for Scientific Research (CSIC) since 1988. She was also the Deputy Director of the IEG from 1998 to 2002. Before coming to CSIC, she was a consultant for the Centre on Transnational Corporations of the United Nations, the OECD and FAO. Her main current interests are in the long- run evolution of patenting activities, typologies of innovators and the impact of outsourcing on innovative activities. She has published in the area of food and beverage multinationals, innovation in the food industry and networked innovators in refereed journals such as Environment & Planning A, Agribusiness, Economía Agraria y Recursos Naturales, The Journal of International Food and Agribusiness Marketing and the International Journal of Technology Management. She coordinated a special issue of the IJTM (2002) on networks, innovation and regions in the electronics industry. She is a member of the Editorial Board of the International Journal of Entrepreneurship and Innovation Management. Professor Nick von Tunzelmann is Professor of the Economics of Science and Technology at SPRU, University of Sussex, where he has been located since 1984. He is also Director of Research at SPRU. Before coming to SPRU, he was a lecturer in the Faculty of Economics and Politics at Cambridge University, and a Fellow of St. John’s College, Cambridge. He has a DPhil from Oxford University and an MA in Economics (1st class hons.) from the University of Canterbury, New Zealand. His main current research interests include: the evolution of technological capabilities, complexity and management, governance of micro and macro economic systems, long-term causes of economic growth. He has written two major books on the relationship between technology and the economy, and has numerous publications in refereed journals, chapters in books, and published reports (list available on request). He has published in relation to many areas of technology.

1

Introduction

Competition in the food and beverage (F&B) industry of industrial countries is currently conducted more in terms of quality, variety, diversification and safety of processed foodstuffs than in terms of price, as in the past [1]. These desirable characteristics are largely the result of efforts in design and technical innovation at the company level.

224

O. Alfranca, R. Rama and N. von Tunzelmann

As in other large firms [2], in large F&B companies such efforts are probably developed as systematic habits and behaviours persisting through time. Companies implement decision rules, including those concerned with new technology, as a matter of ‘routine’ [3]. We know very little about the specific technological strategies that food and beverage multinationals (FBMs) maintain through time. For instance, the effect of technological competition has not been analysed, to our knowledge, let alone investigated over long periods of time. The relationship of technical and design innovation, a major source of differentiation of products in this industry [4], has seldom been investigated with statistical data. Innovation in packaging is especially important in F&B given the need to transform undifferentiated, low-profit commodities into differentiated, branded, high-value, profitable food products [5]. Many foodstuffs are ‘bought with the eye’ [6] so that even very large food processors are keen to take into account innovation in aesthetic aspects of packaging that may influence merchandising [7,8,4,9]. To understand persistent technological traits of firms, a long-run analysis of continuing companies is necessary. The timing of R&D may actually be as important as the amounts devoted to it. For instance, ‘crash’ R&D programmes seem to be less effective than programmes developed over a period of time, even if the amounts devoted to R&D are lower in the latter case [10]. Brands have similar cumulative properties since they ‘need maintenance’ including periodical new improvements in design of packaging [11]. A dynamic approach is lacking in most previous research on innovation in F&B firms, probably owing to insufficient information on technological variables at the company level over long periods of time. This paper explores regularities in the pattern of generating technical innovation among global F&B firms. In order to investigate the technological practices and long-run behaviour of such companies, we analyse panel data of 16,698 patents pertaining to 103 major FBMs from 1977 to 1994. Technological evolution has received a great deal of attention in the literature. Whilst a large part of the literature since Schumpeter has emphasised competition as a factor of technological dynamism, other authors have focused on the cumulative and self-generating nature of innovation [12]. Here, we investigate empirically whether the rise of in-house patented innovation in the FBM is related to innovative activities in other FBMs operating in the same agri-food sector or to past own R&D operations of the multinational itself. A reason for studying world leaders is that they are very influential because of their high share of world food sales [13,14] and innovation. Patel and Pavitt [15] found that, between 1981 and 1986, global companies patented nearly half of the world’s innovations produced in food and tobacco. According to estimations based on US patenting, the largest global firms hold around 52% of the world’s patented innovations in FB&T (tobacco included) between 1977 and 1994 [16]. The importance of the largest firms in F&B technology is not only quantitative: an OECD report [17] emphasises the capacity of such firms for controlling the adoption of technology and directing the innovation process in the F&B industry. Another motive for studying such companies is their long-run involvement in innovative activities [18], which enables us to follow their innovative activities over a long period of time. To anticipate our results, we find that very large food companies show specificities concerning their long-run innovation strategy. Firstly, FBMs build chiefly on their own past innovation and their design experience but they also seem to react, within a short lag, to the innovative activities of other FBMs in the same sector (agribusinesses and basic food, processed food, and beverages). However, they are not responsive to technical or


225

design innovations patented by FBMs operating in other agri-food sectors. Secondly, the technological base, as measured by patenting in different technological fields (food, chemistry, bioengineering, etc.), is relatively similar across sectors of the international agri-food industry. Therefore, differences in the production of patents among FBMs operating in different sectors are not likely to depend on different technological opportunities but on the dynamism induced by technological competition (and probably also spillovers). Thirdly, FBMs develop bundles of different sorts of innovations, with a common pattern of persistent association of technical and design inventions.

2

Theoretical background and hypotheses

In order to formulate our hypotheses, here we analyse the literature on technological competition, technological opportunity, and the effect of past own innovation and technical/design innovation.

2.1 Competition and technological opportunity As Porter [19] states, “active pressure from rivals stimulates innovation as much from fear of falling behind as the inducement of getting ahead”. Both neo-classical and evolutionary theorists have modelled technological rivalry (for surveys, see [20–23]), although the empirical literature has devoted little attention to the question. The pressure from rivals and its stimulating effects at the company level are also evident concerning the instruments of product differentiation (brands, product design, etc). A number of authors have provided evidence on brand rivalry by market category [24]. Moreover, Tirole [20] lists product design among the instruments used by firms in strategic interaction. Owing to the stability of the demand volume and the pressures from powerful retailers that have often become global companies [25], the drive to stay away, anticipating the customer’s needs and desires, is very strong among food manufacturers. Largely as a result of the new features of demand (more intermediate and pre-cooked food, more foodstuffs adapted to new household technology, etc.), value-added has grown steadily in the F&B industry [26,27]. Manufacturers have encouraged these trends in demand by marketing high value-added products that obviously provide more opportunity for profit. Packaging design is a powerful means for companies to differentiate themselves from others. The most important protagonists of the recent wave of international mergers and acquisitions in the F&B industry of OECD countries [28,29] have been the FBMs analysed in this article; their objective is to become the world’s number one in specific food industries. This strategy has often promoted cut-throat competition and hostile bids. Over the last two decades, retaliatory foreign direct investment across different geographic markets has not been uncommon within the top group. As a result, levels of concentration are high. The ten most important multinationals accounted for 41% of the total sales of the world’s 100 largest FBMs by the mid-1990s [29]. FBMs compete with each other on a worldwide scale. In recent years, an outstanding characteristic of foreign direct investment trends in the F&B industry has been the multiplication of cross-investments within the OECD area [28]. Therefore, FBMs usually coincide in the same geographic markets. For instance, in 1996, the world’s 100 largest

226


FBMs analysed in this article all operated in the North American market (USA and Canada), with a total of 1,719 affiliates (North American multinationals included). By the same token, the EU hosted the 2,953 affiliates of 89 top FBMs (European firms included) [30,14]. Thus, opportunities for FBMs interacting strategically are very frequent. The web of competitive relations among them is often very complex. As shown by Sutton [31] in his case studies of 20 F&B industries across six developed countries, rivals in specific product markets can show symmetry across countries, i.e. some FBMs hold the same ranking in different geographic markets. In other product markets, however, FBMs show asymmetric positions; a company that ranks number one in one country ranks second in another nation, while the position of its multinational rival is inverted. In short, among the companies analysed in this article, the FBMs belonging to the same agri-food sector are likely to be competitors at least in the two largest markets for F&B (North America and the EU), although the relative position of such firms could vary from one area to another [32]. Since innovation and design are sources of competitive advantage, the FBM is likely to scan the latest innovative developments in other FBMs in order to assess the evolution of its own relative position. Firstly, motivation arises from the fact that the international agri-food sector is the most important source of patented innovation in this industry [15,16]. Secondly, opportunities for scanning such developments could originate because global firms’ R&D units are often geographically close to one another in a few of the world’s centres of excellence for food and food-related technology. FBMs are especially inclined to locate their innovative activities abroad [33,15], especially in countries that are also strong in the company’s fields of strength [34]. The specialised technological subsidiaries of the world’s largest F&B multinationals concentrate in a few industrialised countries [35]. At some point, awareness of such developments in other FBMs could obviously turn into imitation. As shown empirically by Mansfield [36], not even patented innovation is free from imitation. The literature reports some examples of both voluntary [37] and involuntary transmissions of knowledge (spillovers) among FBMs and, more broadly, among F&B firms in industrialised countries. In the available cross-sectional studies, the role of spillovers as a source of information to F&B firms is controversial [38–43], although standard accounts assume that food products are easily imitated [44]. Theoretical models of technological rivalry, which are based on game theory, focus chiefly on market structure, the aggregate non-cooperative investment in R&D, the choice of technology under rivalry, etc. Here we recognise the basic behavioural insight underlying such models and assume that competitive pressures faced from other FBMs could be a stimulus to innovate and launch new designs at the company level. However, our scope is limited since we do not intend to test a theoretical model in all its complexity. This would be a difficult task given that the number of ‘games’ in which the world’s 103 largest FBMs are involved with one another and the position of the players in such ‘games’ are, as mentioned above, extremely complex. Instead, we merely test empirically whether the FBM’s level of research is associated, over long periods of time, with the level of innovations and new designs launched by FBMs in its same sector (agribusinesses and basic products, processed foods, and beverages). In the F&B industry of OECD countries, the technological and design activities of competitors could induce firms to launch new products, new processes and new packaging. In a sample of 1,662 product innovations recorded in the German F&B industry between 1993 and 1994, Hermann [45] demonstrates that existing product


227

variety is the major driver of future product innovation in an industry (market growth and concentration checked). The author also shows that company-level innovations were particularly sensitive to lagged product variety in the health and ethno-foodstuffs markets [46,47]. Inducements to innovate can also come indirectly from the capital market. In a large sample of US food firms traded in US capital markets between 1973 and 1991, Wu and Bjornson [48] find that advertisement – a way of differentiating foodstuffs comparable to packaging design – and R&D activity, are related to the market value of firms (capital reinvestment, performance and risk checked). The study shows that during recessions, for instance, capital markets appeared to especially value R&D activity in F&B companies as an investment in future cash flows. In our view, this situation could induce food firms to compete with each other in terms of patenting activity and investment in intangible capital oriented toward product differentiation, such as packaging. Here we assume that the FBM will feel some pressure to compete with the innovative activities of other global companies who market most of their sales in the same product market. The company will respond to such inducements by launching innovations itself. By contrast, the FBM will not feel under pressure to compete in terms of new products/processes (or in packaging design) with FBMs conducting businesses in other agri-food sectors because such companies market different products [49]. Thus, the innovative activities of companies operating in other food and drink markets will not induce the FBM to innovate itself. However, given that part of the inducement to innovate could be attributable to spillovers, i.e. involuntary transmissions of knowledge from innovators to followers, our results should be considered a crude beginning in the analysis of competition as a factor of technological dynamism in this international industry. Hence, we test the following hypothesis: Hypothesis 1: Innovation at the company level is induced by innovation originating in other FBMs operating in the same sector. Before testing this hypothesis, however, we need to verify whether the technological base for the three sectors within the multinational agri-food industry (basic food and agribusinesses, processed food, and beverages) is comparable. If the technological base is different across sectors, then the influence of other FBMs’ innovative activities on the company could be attributable to different technological opportunity in specific sectors, not to competitive pressure. Nevertheless, if the technological base is comparable across sectors, the association between the innovative activities of other FBMs in the same sector and the company level of technical and design innovation could be a symptom of technological (and marketing) rivalry among multinationals engaged in similar businesses. In general, authors believe that technology available to the F&B industry is superabundant or easily accessible from external sources. Building on Paldberg and Westgren [50], Galizzi and Venturini [51] define the notion of ‘redundant technology’ according to which “technology and food science offer relevant opportunities to altering characteristics of foodstuffs (taste, nutritive content, preparation)”. According to this view, and given that F&B firms are aware of the reluctance of consumers to accept radically new foodstuffs (‘consumer inertia’), “at any point in time, the introduction of new products is not constrained by the availability of technological opportunities but by the existence of particular demand conditions”. Although technology is probably far from

228


‘redundant’ in the solution of some specific problems faced by food manufacturers [52,41], it is true that this industry often adapts solutions provided by a diversified body of sciences, techniques and upstream industries [41]. A study of 4,572 foreign patents usable in 14 four-digit level F&B industries found that both food and non-food technology (new chemical additives, new packaging, etc.) are used in all these industries [53]. Beer, canned fruits and vegetables, meat, sugar, animal feed and grain milling manufacturers tend to utilise even greater amounts of non-food innovation (as opposed to food innovation). Though part of the food-related technology is produced by the F&B industry itself (see below), these results could suggest that part of the technological ‘corpus’ available to food and drink manufacturers is similar in a variety of F&B industries, given that it could come from external sources accessible to all. The lags in the empirical model incorporate the probably slower transmission of information when it must cross national boundaries [54]. In the model, we will test whether the existence of patenting activities in other FBMs within the same sector is a positive influence on firms’ patent production. This hypothesis is tested in the technical area (utility patents). We also explore whether the launching of new designs in other FBMs operating in the same sector induces the production of new design at the company level. As will be seen below, FBMs innovate persistently in design. One reason could be that elements of product differentiation, such as packaging aesthetics, are subject to a decay effect. Some authors view advertisement, for instance, as affecting the demand for food through a psychological stock variable. Current advertising, claim Brown and Lee [55], “adds to the stock and memory loss results in depreciation of the stock over time”. They report on research results calculating that, on average, 80% of the stock of advertisements for different types of foodstuffs wears off annually. It may well be that FBMs launch new designs periodically because packaging designs experience a similar decay over time (consumers do not ‘see’ it anymore). It is more difficult to explain why FBMs would race against each other concerning new packaging design. Fashion theory currently offers a number of principles for understanding consumers’ acceptance of products not only in clothing – the classic product in fashion oriented behaviour – but also in aesthetic choices concerning cars, housing or food [56]. One reason why, in this international industry, innovators would launch new types of designs, different from those used by other FBMs, could be – as in fashion cycles – the perception of social saturation (overuse) and of the customers’ desire for novelty. Fashion is accompanied by “a process of continuous innovation in which new designs are developed … only to be replaced by other designs” [56]. The innovative designer introduces a new signalling device, and hence destroys the ‘value’ of the previous fashionable type of design currently predominant in the industry [57]. In the international agri-food industry, this strategy could stimulate, in turn, the production of new designs in other FBMs operating in the same sector. Conversely, imitation is considered as a powerful force behind the creation of new designs because it stimulates innovators to create new designs periodically in order to differentiate the company/brand from its rivals. Given that elements of product differentiation seem to experience a considerable annual decay and that fashion cycles are short – sometimes only a few months – in these types of products [57] we assume that the reaction of firms to new design packaging in other FBMs will be very quick (faster than in the case of technical innovation).


229

2.2 Own innovation Alfranca et al. [58] find that, in the international agri-food sector, ‘success breeds success’, i.e. companies that innovated in the past tend to be current innovators. The influence of past internal R&D on technological change tends to be almost permanent, in both the technical and design areas. However, previous research does not measure the real temporary impact of past innovation. Although past innovation can have almost permanent effects, such effects can become weak after a time. Measures of the actual temporary effect of innovation can provide information on the possible duration of R&D projects. The literature rarely provides empirical measures of possible lags between innovation and further innovation in F&B. Analysing US patents from 1790 to the present, Beggs [59] finds five-year lags in all industries although he admits that shorter lags may be expected within single industries. He also points to the possibility of more dynamic rhythms of patenting in more recent historical periods. Hence, we formulate the following hypothesis: Hypothesis 2: Own past innovation influences current patented innovation within the company Here we will assess the lags between innovation and further innovation within companies.

2.3 Technical and design innovation It is not clear whether technical and design innovations go hand-in-hand at the company level. In practice, new packaging design may be instrumental both when a new product is launched and when a brand needs revitalisation, i.e. for an ‘old’ product. The consumer and economic psychology literature has emphasised the importance of packaging design in attracting the attention of consumers and in helping them to categorise new products, i.e. to classify a novel item into an existing category of products on the basis of perceptual similarity [60,61]. Thus, this strand of theory suggests that new packaging is mostly used for new products or, in other words, that design and technical innovation are closely associated. Other authors have noticed the importance of synergies between design and technical innovation in food companies. Ward [62], who emphasises the joint importance of ‘new products’ and ‘images’, contends that attracting the most technically and possibly the most artistically competent employees is relevant in very large food firms. In his view, economies of large size enable such companies to respond to the high-income consumer by providing a stream of new products through the use of both science and communication. Van Trijp and Steenkamp [63] observe that the R&D and the marketing functions are linked in consumer-oriented new product design. Moreover, production of commercially successful items seems to require a broad multi-dimensional approach to design and innovation [64]. Connor [65] actually finds that packaging expenditure and product proliferation, defined as the production of multiple brands and flavours of a product, or as the production of slightly different new products, are associated in the US food industry (concentration and other variables checked). For Walsh [66], “design and technological change have something of a symbiotic relationship, each changing in nature over time but each connected to and interacting with the other”. However, she admits, “design overlaps only partially with innovation”.

230


A number of empirical studies point to the fact that design may not overlap with technical innovation. For instance, loss-making projects in British industries tend to be only styling-oriented, i.e. they introduce changes only in the image and packaging of products [64]. In a representative sample of British firms (food companies included), Bruce et al. [4] find that redesigning the packaging of existing products can be an important consideration among firms investing in design. In some industries, firms may use a strategy of ‘product churning’, consisting of the introduction every few months of new models involving design modification but very little technological innovation (even incremental innovation) [66]. An OECD report [44, p.172] suggests that one of the main axes of innovation in the US F&B industry is the modification of appearance of existing products. In fact, it is often argued that innovation in F&B firms is of such cosmetic sort. From this we formulate the following hypothesis: Hypothesis 3: Design and utility patents are associated It should be stressed that we are trying to test whether technological patterns in the international agri-food industry imply the positive association of product innovation and design innovation. For reasons explained below, only in this case are results clearly interpretable. A negative correlation would indicate that utility patents crowd out design patents. There is no easy economic intuition for this result because it could mean two different things: 1.

Product and design innovations are substitutes for one another.

2.

Process innovation, not necessarily associated with design innovation, plays a predominant role in the industry.

As noted below, our data do not allow us to distinguish product from process innovation. Even with these limitations in mind, it is worth testing the association of utility and design patents since the empirical evidence is quite mixed on this subject and, to our knowledge, no prior evidence exists for the F&B sector.

2.4 Empirical model We measure firm innovation by using patent data [67,53]. This method has some drawbacks because many successful inventions are never patented [68] and firms from different countries or industries show different propensities to patent [69]. Moreover, patent counts give no information on the technical importance or the market value of the inventions. However, some of the above objections lose their importance in homogeneous samples of firms, such as that in this study [41]. In addition, as Freeman [70, p.476] puts it, patent statistics provide a “unique long-term time series of inventive efforts on a worldwide basis”. Moreover, a number of empirical studies support the idea that patents reflect with some accuracy other manifestations of technological change, such as innovative activities and R&D expenditures at the firm level [71,72]. The variable used here is the number of patented innovations granted in the USA from 1977 to 1994 [73]. Our patent sample comprises 16,698 patents, and includes both utility patents and design patents. According to the US Patent and Trademark Office (USPTO) a design consists of “the visual ornamental characteristics embodied in, or applied to, an article of manufacture” [74]. Designs may relate to the shape of an article, to its surface, or to a combination of both. An ornamental design may be embodied in an


231

entire article or only in a portion of an article. A design patent protects “only the appearance of the article and not its structural or utilitarian features”. While a utility patent protects “the way an article is used and works”, a design patent protects the way it looks. As the USPTO web page explains, minimal differences between similar designs can render each patentable. The most important part of the application is, logically enough, a design or photograph of the article. For a design to be patentable it must be ‘original’. To determine the originality of the new design, the examiner at the USPTO, based on the identification of the article in which it is embodied, will develop “a complete field of search of the prior art”. ‘Prior art’ includes design patents for similar articles and published matters. Thus, even in the application phase, new designs ‘compete’ with other designs embodied in similar items. This consideration is relevant to our purpose since we will analyse competitive behaviour among FBMs in the same sector, which probably means competition of designs embodied in similar products. Firms were selected from AGRODATA [75,76,14]. Produced by the Institut Agronomique Méditérranéen de Montpellier (France), this database gathers information on the world’s 100 largest food multinationals since the 1970s [77,14]. Our sample includes more than 100 multinationals (actually 103) because of the entries and exits in the top group during the period 1977-94 [78]. The firms in our sample are active in a variety of industries, such as meat processing, confectionery, dairy products, canned specialties, spirits, etc. Whilst all are food or beverage processors, a number of them also have agribusinesses and other concerns. All these multinationals in our AGRODATA sample have patented at least one invention over the period. The database gives the UN-SIC (four-digit Standard Industrial Classification) classes in which firms operate, information we use to classify companies into three different types of business: agribusiness as well as basic food, highly processed food, and beverages. The list of F&B firms included in our sample is displayed in the Appendix. Unfortunately, short of detailed scrutiny of each patent specification, which, for the nearly 16,700 patents covered here, is beyond our means, it is not easily possible to distinguish process from product patents by using the US classification system [79,80]. The patents classified are all patents registered for the companies in our sample, and their affiliates, over the period specified. The patents in our sample consider a variety of technological fields such as food proper, biotechnology, tobacco and so on [80]. Innovative activities related to non-core businesses are also included. The structure of technological fields used for analysis is drawn from the categorisation into about 400 patenting fields defined by the USPTO. These have to be aggregated for practical use. The aggregation procedure utilised is one that is found to be robust for the particular industry at hand; so in this case we deploy one that is more fine-grained in the food area (broadly speaking) than in many other fields [81]. Science and Technology Policy Research (SPRU) at the University of Sussex (UK) collected the patent data. Foreign patenting in one particular country is often used in international analyses of innovation [82,83]. Patenting in the USA probably reflects accurately the world’s stock of technology, as shown by the results of Soete [83, p.110]. The characteristics of the sample are displayed in Table 1 and variables are described in Table 2. The distribution of total utility patents per firm has a mean of 8.68, a median of two patents, and a high standard deviation of 22.51. The distribution of total design patents per firm has a much smaller mean of 1.99, a median of one patent, and a standard deviation of 3.12 (these are the anti-logs of the figures in Table 1). The Jarque-Bera

232


normal statistic indicates that both utility patents (0.917) and design patents (0.083) follow a lognormal distribution. Table 1

Descriptive statistics for utility patents, design patents, internal* and external** patents and global sales, 1977-1994

LOG(P) LOG(PD) LOG(IPU-2) LOG(EPU-2) LOG(EPD) LOG(IPD) LOG(GS(-1)) Mean 1.006 0.323 5.750 6.321 4.696 4.341 10.415 Median 0.693 0.000 6.066 6.116 4.804 4.564 10.466 Maximum 5.136 3.497 6.706 7.462 5.778 5.303 13.135 Minimum 0.000 0.000 3.912 4.060 4.060 2.944 5.330 Std. Dev. 1.253 0.691 0.772 0.584 0.455 0.641 0.895 Skewness 0.133 0.037 -0.814 0.117 0.308 -0.433 0.085 Kurtosis 1.927 2.675 2.663 2.990 1.841 1.870 4.069 Jarque-Bera 0.917 0.083 189.935 3.761 118.160 139.203 80.456 Notes:

Description of the variables in Table 2 * Patents produced within the same sector of the firm

** Patents produced by companies operating in other agri-food sectors Source: SPRU and AGRODATA Table 2

Definitions of variables

Variable P PD

Definition/source Utility patents granted at the US Patent Office. Source: SPRU Design patents granted at the US Patent Office. Source: SPRU

IPU-2

Index of the inducement potential for utility patents in the same sector, with two lags (‘internal’ utility patents). The aggregation to calculate the inducement effect of patents across companies applies the methodology employed by Khanna et al. [12] for aggregating R&D expenditures across US states. Source: SPRU Index of the inducement potential for design patents in the same sector (‘internal’ design patents). Methodology as above. Source: SPRU Index of the inducement potential for utility patents from other sectors, with two lags (‘external’ utility patents). Methodology as above. Source: SPRU Index of the inducement potential of design patents from other sectors (‘external’ design patents). Methodology as above. Source: SPRU Global sales. Source: AGRODATA, in 1990 PPP prices. Source: OECD, Statistical Compendium. National Accounts, various issues. Fixed effect constant, for each of the firms in the model (a list of companies can be found in the Appendix)

IPD EPU-2 EPD GS D(l)

Before continuing with the econometric analysis, we test for differences in the innovative pattern of firms as measured by technological fields. Table 3 shows the distribution of the average number of patents by firm, classified by the sector in which the company markets most of its sales and the technological field of the patent. Patents produced by FBMs are related to the production of: food and drinks; inputs and equipment used by the F&B industry (columns from Machinery to Drugs in the Table); and non-related fields (‘Other’).

Competitive behaviour, design and technical innovation Table 3

233

Patents by firm (mean), classified by sector and technological field (1969-94)

Sector

F&B

Machinery

Agriculture

Bioengineering

Instruments

Chemicals Drugs

Other (1)

Agribusinesses and basic food

54.20

7.73

3.37

7.20

4.67

22.33

38.0

Processed food Beverages

3.60

(85.46) (12.37)

(5.74)

(23.29)

(8.64)

(36.15)

(5.15)

(127.70)

106.29

4.71

71.18

20.04

112.50

33.29

87.82

(58.39) (51.81)

(74.66)

(14.43)

(47.38)

(353.14)

(127.71)

(135.00)

50.63

0.91

3.60

4.81

15.27

0.91

23.91

(2.39)

(4.20)

(4.69)

(15.04)

(2.49)

(26.28)

31.32 26.27

(54.71) (58.02)

Notes: (1) Includes patents in the electronics, textiles and other non food-related technological fields (2) Figures in brackets are standard deviations

In what follows, we test whether the technological patterns of companies are similar across sectors within the agri-food international industry. Using cluster analysis (k-means of cases), we detect groupings of companies on the bases of technological similarities of such FBMs, i.e. their patenting by technological field. We use the average number of patents by firm over 1969-94 to calculate the groupings and perform these statistical tests with a sample of 54 companies. Disaggregated patent data by technological field were not available for all the 103 companies analysed in this study. Then, in order to investigate whether specific patterns of patenting are associated with FBMs in specific sectors, we cross tabulate the data on cluster membership which indicate different technological patterns with a categorical variable denoting the sector in which the company is most active. Clustering yielded a five-cluster solution (Table 4) [84]. The bulk of the companies (51) are included in cluster 1 and cluster 2. Three very large conglomerates with a large production of food patents but also of chemical, drug and ‘other’ (non-food or food-related) patents are included in clusters 3, 4 and 5, respectively. The cross-tabulation of these data with the sector variable does not allow the rejection of the null hypothesis of independence between both variables (χ2 = 2.224, p = 0.919; Fisher = 4.102, p = 1.000) [85]. We conclude that cluster membership is not associated with the sector to which the company belongs. Table 4

Cluster final centres

Technological field Food Bioengineering Machinery Agriculture Instruments Chemicals Drugs Other N Note:

1 140.33 14.50 62.83 7.25 18.25 48.08 7.83 136.75 12

2 17.36 1.49 5.33 1.90 3.79 5.77 0.85 11.00 39

Clusters 3 409.00 35.00 153.00 9.00 237.00 1574.00 658.00 442.00 1

4 1164.00 30.00 115.00 22.00 46.00 182.00 20.00 301.00 1

Clusters 3, 4 and 5 contain, respectively, Procter and Gamble, Philip Morris and Unilever

5 412.00 52.00 52.00 5.00 34.00 1095.00 191.00 479.00 1

234


Given that, across sectors, the companies in our sample seem to display a relatively homogeneous technological base, we now undertake the econometric analysis of the data. The econometric model of patenting activity incorporates variables representing the effect of design and utility patents granted to the firm in the past, utility and design patents in other global companies, and total firm sales (as mentioned above, definitions are in Table 2). Patents is a main research policy tool for agrifood multinationals. Four variables denote, respectively, patents produced within the same sector as the company (‘internal’ design and utility patents) and patents produced by FBMs operating in other agri-food sectors (‘external’ design and utility patents). Global size relates primarily to firm incentives. The econometric specification of the utility patent production function is: ln(Plt1)=

(1)

103

∑ D(l ) + β l =1

21

ln( PDlt1 ) + β 31 ln( Plt1−1 )

+ β 41 ln( Plt1− 2 ) + β 51 ( IPU lt1− 2 ) + β 61 ln( EPU lt1− 2 ) + β 71An(GSAt1−1 ) + + β101[AnPDAt1 ] ∗ [AnPAt1−1 ] + µ At1 E µ At1 = 0, E µ A2t1 = σ A2t1 , E µ At1 = σ A2t1 , ∇A, p, t where µ A t is a random disturbance term representing the effects of omitted variables that are peculiar to both a company and a time period. It has a zero mean, constant variance over time, and non-zero contemporaneous correlation across companies. Regarding utility patent production, we expect a positive relationship between utility patents and design patents, i.e. β21 > 0. Lagged utility patents represent both a stock of past discoveries that may be useful in future discoveries but also provide an indicator of some of the innovation potential of earlier scientific discoveries [86, 87]. In this empirical model, we have considered only the lagged patents that are significant in the regression equation, at least at the 5% significance level. The aggregation of patents to calculate the inducement effect of patents across companies applies the methodology employed by Khanna et al. [12] for aggregating agricultural R&D expenditures across US states. Of course, other weighting schemes exist. In the model, we test whether patent production by FBMs in the same and in other sectors represents a positive or negative influence on patent production, and if innovative activities in other global firms are a positive or negative determinant of patent production at the company level. Khanna and colleagues calculate the effects of total public (voluntary and non-voluntary) agricultural research expenditure in the different US states, in each year of the sample (1951-1985). The authors calculate the difference between total public (voluntary and non-voluntary) agricultural research activity of region r during year t, and the quantity for public (voluntary and non-voluntary) agricultural research activity in state i of region r during year t. We have followed a similar methodology for the patents obtained by the agri-food multinationals in the sample. We considered potential inducements to innovate coming about in two different ways:


235

•

Internal inducements are from patents obtained by FBMs in the same sector (‘internal’ patents). For instance, agribusinesses and manufacturers of basic food will be stimulated to innovate by patents granted to other agribusinesses and basic food multinationals.

•

External inducements arise from patents obtained by FBMs operating in a different sector (‘external’ patents). For instance, patents granted to multinationals in processed food and beverages will influence agribusinesses and manufacturers of basic food.

We expect that the size of the external effects, measured by inducements between FBMs, have a linear effect on the elasticity of patent production. As mentioned above, we will differentiate between internal inducements, stemming from the same sector, and external inducements from a different agri-food sector. If inducements are positive, then the larger the stimulus, the bigger will be the patent production at the company level. The size of the multinational company is proxied by the volume of sales. Larger sales are expected to increase the number of patents produced by the multinational because the use of new technologies generally requires a minimum amount of resources to process new information. The potential size of the market for patenting decisions is proxied by the global volume of sales (GS). Each company’s global sales were converted to real 1990 purchasing power parity dollars. We expect patent production to be positively related to the size of the FBM and β71 to be positive. We expect utility patents and design patents to be positively related as well, so that β81 > 0 (Equation (1)). The company dummy variables (D(l) in Equation (1)) are firm-specific intercept terms or fixed effects, which accommodate cross-company differences and omitted variables. The econometric design patent equation is: A n ( PRRINV A t ) = 103

∑ D(l ) + β l =1

22

(2)

ln( Plt 2 ) + β 32 ln( PDlt 2 −1 ) + β 42 1n( PDlt 2 − 2 )

+ β 52 ln( IPDlt 2 ) + β 62 ln( EPDlt 2 ) + β 72 A n ( GS A t 2 −1) + + β 82 [ A n PD A t 2 −1 ] * [ A n P A t 2 ] + µ A 2 t

2 E µ A t 2 = 0 , E µ A t 2 = σ A2 t 2 , E µ A t 2 µ q t 2 = σ A2 t 2 , ∇ A , q , t

where µlt2 is assumed to be a normally, identically and independently distributed random variable representing the effects of omitted variables that are peculiar to both a company and a time period. Omitted variables could be, for instance, variables related to management and organisational efficiency. Regarding the hypotheses about the production of design patents in multinational F&B enterprises, we expect β22 > 0 (that is, a larger utility patenting activity increases design patents). As in Equation (1), lagged patents provide an indicator of some of the innovative potential of earlier scientific discoveries. Design patents are also determined by global sales for the same reasons as utility patents. We expect utility patents and design patents to be positively related also, so that β82 > 0 (Equation (2)). Equation (1) for each of the 103 companies is stacked as a regression model with coefficients on identical regressors being constrained to be the same across companies, except for the intercept, and fitted by the ordinary least squares estimation method with

236


cross-country heteroscedasticity [88, pp.614–633]. The estimated coefficients of the aggregate patent production equation and associated t-ratios are presented in Table 5. Table 5

Estimates of the utility patent equation for the world’s 103 largest FBMs, 1977-1994

Dependent variable log(p) log(pd) log(p(-1)) log(p(-2)) log(ipu(-2)) log(epu(-2)) log(gs(-1))

Reg.1 0.0849 (2.69) 0.223 (8.69) 0.162 (6.024) 0.159 (1.808) -0.117 (-1.0851) 0.0852 (2.722)

log(pd)*log(p(-1)) adj R2 DW Wald test (no inducement effects) Note:

0.864 2.01

Reg. 2 0.0742 (1.67) 0.222 (8.477) 0.162 (6.015) 0.158 (1.794) -0.117 (-1.0839) 0.0494 (1.517) 0.005503 (0.316) 0.864 2.01 3.274

t values in parentheses

Regarding utility patent production, the hypothesis that the utility patent production equation has no explanatory power (i.e. all coefficients except for company fixed effects are zero) is rejected at the 1% significance level. Turning to particular effects, the effect of a larger (lagged) utility patent production is to increase current utility patent production and the significance is weak. The direct effect of design patents is positive, although smaller than the impact from utility patents. No clear econometric evidence exists for the interaction term between utility and design patents in the utility patent production function (the interaction term coefficient is 0.005503 and the t-value is 0.316; see regression 2, Table 5). In regression 1 (Table 5), the elasticity of the internal inducement potential from utility patents at the sample mean is 0.908. Therefore, the effect of an increase of utility patents within sectors on aggregate patent production is positive. The external inducement potential elasticity from utility patents at the sample mean is -0.739. The empirical evidence suggests that intra-sector technology production puts pressure on companies to generate more utility patents. The impact of additional global sales on utility patent production is positive, and the impact elasticity at the sample mean is 0.886. With the coefficient being close to one and with high significance levels, this suggests a large response of patenting activity as the size of a company grows, holding the share of output constant. The estimates of the firm-specific fixed effects in the utility patent production equation range from -1.264 (t-value: -3.137) for Beatrice Co. Inc. (USA), to 1.888 (t-value: 4.0243) for Ito Ham Foods Inc. (Japan). Representative multinationals with the smallest fixed effects include S&W Berisford Ltd. (UK) (-1.257; t-value: -3.124) and


237

Sandoz A.G. (Switzerland) (-1.252; t-value: -3.114). By contrast, companies with the highest coefficients are Philip Morris Companies Inc. (USA) (1.146; t-value: 2.913) and Procter and Gamble Company (USA) (1.348; t-value: 3.434). When firm-specific effects are large, then factors not included in our model, such as the quality of management, the design of the organisation structure of the firm or the efficiency of bureaucratic decision processes, might have a substantial effect on innovation at the company level. Thus, our model reflects better the pattern of innovation in companies with small fixed effects. Those listed above include some of the world’s leading companies. The empirical results for the IPU and EPU variables are rather weak in the utility patent equation; hence a joint test of the null hypothesis of ‘no effect of inducements’ is performed [89]. The sample value of the Chi-square statistic for the Wald test [88, pp.150–156] in the utility patent equation is 3.274, which is smaller than the critical value at the 5% significance level (5.99). Furthermore, when this restriction is imposed on the design patent equation, the sample value of the Chi-square test is 74.172, which soundly rejects the hypothesis that IPD and EPD do not influence patent production at the 1% significance level. Hence, the variables do significantly affect design patent production for the agri-food multinationals and are important factors determining multinational FBMs’ patent production. Nevertheless, only internal inducements present a positive effect on utility patent production. Most coefficients in the fitted model for design patent production are different from zero at the 5% significance level, and the hypothesis that the design patent production has no explanatory power is rejected at the 1% significance level (Table 6). Regarding particular effects, design patents seem to be strongly determined by internal design inducements (IPD). The internal design inducement variable has a positive sign, and it is clearly significant at the 5% level. Estimates of the design patent equation for the world’s 103 largest FBMs, 1977-1994

Table 6

Dependent variable log(pd) log(p) log(pd(-1)) log(pd(-2)) log(ipd) log(epd) log(gs(-1))

Reg. 1 0.0436 (2.157) 0.255 (10.366) 0.0634 (2.527) 0.335 8.0459 -0.0472 (-1.1001) -0.0289 (-1.177)

log(pd(-1))*log(p) adj R2 DW Wald test (no inducement effects) Note:

t values in parentheses

0.692 2.023

Reg. 2 0.0344 (1.678) 0.190 (5.197) 0.0583 (2.319) 0.333 8.0238 -0.05003 (-1.167) -0.0271 (-1.102) 0.0339 (2.407) 0.693 2.0213 74.172

238


The sign of the coefficients for the design patents is positive and highly significant. Although the sign of the utility patents coefficient is also positive, significance is slightly larger than 10%. The highest positive effects on design patents are mainly accumulated in the first lagged periods. There is econometric evidence (at 5% significance level) for the positive effects of past patents on current innovation in the design field. There is no clear empirical evidence for the positive effects of global sales on design patents. A burst of patent innovation is followed by a follow-up patent in a relatively short term (one year), and then by a second round of patents two years after the original patent is granted. Further effects of the initial patent are much weaker both for utility and for design patents. The results also show that the positive impact of design patents is also operating through interaction effects with utility patents. These results reinforce the hypothesis that it has been generally easier for companies to muster agri-food research support for design research than for utility research (more closely related to production). Hence, if total (utility and design) aggregated patents increase with the internal inducements, we would expect the design patent share to rise. The effect of intra-company potential inducements of design patent information is the most important determinant of design patent production. The external elasticity for design patents is -0.727 at the sample value, which is a value fairly close to the external inducement elasticity on utility patents (Table 6, regression 2). Nevertheless, the significance of the EPD coefficient is weak. The amount of patents produced by other FBMs has a different effect on the elasticity of patent production at the company level depending on the sectoral inducement potential. Only patents stemming from the same sector have a positive effect at the company level. Patents stemming from FBMs in the same sector also appear related to increases in design patent production at the company level. This indicates that, ceteris paribus, increasing the volume of within-sector patents should intensify patent production in the international agri-food sector. The range of firm-specific intercept terms in the design patents equation goes from 1.184 (t-value: -4.903) for Ajinomoto Co. Inc. (Japan) to 0.566 (t-value: 2.203) for Coca Cola (USA). FBMs with the smallest fixed effects are Nissin Food Products Co. Ltd. (Japan) (-1.159; t-value: -4.979) and Snow Brand Milk Products Co. (Japan) (-1.582; t-value: -4.748). Representative companies with the highest fixed effects are Ito Ham Foods Inc. (Japan) (0.471; t-value: 1.879) and International Multifoods (USA) (0.307; t-value: 1.326). Other factors being equal, the differences in size of these fixed effects do imply small differences in patent production associated with those omitted variables that are specific to each of the firms (and hence could be different for each of the multinationals considered in this sample) and stay constant over the studied period. As in the case of utility patents, our model reflects better the pattern of design innovation in companies with small fixed effects.

3

Conclusions

In this paper we undertake the analysis of regularities in the pattern of generating innovation among F&B multinationals. Innovative routines in such companies probably include active monitoring of R&D results and new design in other global companies


239

pertaining to the same sector (agribusinesses and basic food, processed food, and beverages), reliance on past recent experience, and inter-divisional exchanges of ideas implying effective communication between functional areas in charge of technical and design innovation. Competition is an important factor of technological dynamism but innovation in large food and drink multinationals also depends on self-generated accumulative innovation. In general, the current level of production of patented inventions in FBMs seems closely associated with the combined effect of technological competition with other global companies in the same sector and to past research effort in the multinational itself. Empirical evidence suggests that lagged innovation is an essential determinant of future discoveries and, at the same time, that exhaustion of the innovative potential might be occurring faster than it is being restored. Such firms develop bundles of design and technical innovation, which are complementary. Our interest has been in the pattern of technological change in the international agri-food industry, not in specific firms. However, our results also show that persistent, specific factors (sustained good R&D management, for instance) can affect technological patterns in individual companies, even in very homogeneous groups of companies such as the one analysed here. Multinationals, which are major players in the production of food and drink technology, are responsive, with a short lag, to innovations produced by their potential competitors. However, they do not seem incited to innovate owing to innovation developed by FBMs in other agri-food sectors. Even so, part of the inducement effect of innovative efforts carried out within the sector could probably be attributable not to reactive competitive behaviour but to spillovers of knowledge. This question would require further investigation than we have attempted. Effects of competition among FBMs pertaining to the same sector can be seen at the company level not only in production of utility patents, i.e. patents protecting technical characteristics embodied in or applied to F&B production, but also in the production of design patents, i.e. patents protecting innovation in the appearance of packaging. To isolate for analysis the effect of competition we tested whether differences among FBMs could be attributable to the fact that the different sectors had a different technological base, as measured by patenting in different technological fields (food, chemistry, bioengineering, etc.). However, we found that the technological base is relatively similar across the three sectors of the international agri-food industry. We deduced, therefore, that differences in the production of patents among FBMs operating in different sectors are not likely to depend on different technological opportunities but on the dynamism induced by technological competition within sectors (and probably also spillovers). The intensity of competition within sectors is confirmed, in our view, by the fact that the production of new designs at the company level is also influenced by the amount of design innovations patented by global firms in the same sector (but not by new designs patented by global firms in other agri-food sectors). In general, the multinational agri-food sector shows a pattern of technological accumulation in which ‘success breeds success’. Past recent innovation strongly influences current innovation. Even small changes dealing with packaging of products show cumulative properties. Original inventions are further developed in two following phases. As in Beggs [59], the association of the first round with the original patent is closer. The second round displays a positive but lower association with the original patent than the first.

240


The magnitude of follow-ups is smaller in further rounds. A burst of patent innovation is followed by a follow-up patent in one year, and then by a second round of patents two years after the original patent is granted. The production of utility patents is closely and permanently associated with that of design patents over the period analysed in this paper. Empirical evidence indicates that both fields display great potential for synergies. Pointing to practices of close communication between functional areas within the firm, the interconnectedness of both types of innovation is probably a barrier to entry in this international industry. On the other hand, this result contradicts the popular perception that, in F&B, improvements are only cosmetic, and suggests instead persistent relationships between different functional areas of the company, i.e. production and marketing. The evolution of technical and design innovation in FBMs shows some similarities that were already mentioned. However, while size of the company affects positively technical innovation, it does not influence design innovation (at least among the very large companies analysed in this study). On the other hand, logically enough, the FBM finds it easier to respond quickly to new design patents granted to potential competitors by creating new designs; much faster than it reacts to technical innovation in competitors.

Acknowledgements The authors wish to thank two referees for helpful comments on an earlier draft. Oscar Alfranca wants to acknowledge funding from project Nº SGR2001-160, Direcció General de Recerca, Departament d'Universitats, Recerca i Societat de la Informació, Generalitat de Catalunya

References and Notes 1 2

3 4 5 6 7

Traill, B. (1989) ‘The European food system: results from the EC FAST programme’, Food Policy, May, pp.180–184. Pavitt, K. (1992) ‘Some foundations for a theory of the large innovating firm’, in G. Dosi, R. Giannetti and P.A. Toninelli (Eds) Techonology and Enterprise in a Historical Perspective, Clarendon Press, Oxford. Nelson, R.R. and Winter, S. (1982) An Evolutionary Theory of Economic Change, Harvard University Press, Cambridge MA. Bruce, M., Potter, S. and Roy, R. (1995) ‘The risks and rewards of design investment’, Journal of Marketing Management, Vol. 11, pp.403–417. Kohls, R.L. and Uhl, J.N. (1998), Marketing of Agricultural Products, Prentice Hall, New Jersey, p.80. von Alvensleben, R. (1997) ‘Consumer behaviour’, in D.I. Padberg, C. Ritson and L.M. Albisu (Eds) Agrofood Marketing, CIHEAM-Cab International, Oxford. Among 500 US firms belonging to ten high-tech sectors, Traynor and Traynor [8] find that top managers perceived packaging as a promotional method more important than advertising in the media. While their study does not include the F&B industry, packaging is probably still more relevant in this sector. For instance, Bruce et al. [4] find that most packaging projects in their representative sample of UK companies were food and drink products. New packaging may be especially useful for FBMs because good, novel design may provide these companies with an advantage over national firms, which often merely copy old foreign designs – especially in developing countries (See Garza [9]).

Competitive behaviour, design and technical innovation 8

9 10 11 12

13 14

15

16 17 18 19 20 21

22 23 24 25 26 27 28 29

30

241

K. Traynor and S. Traynor (1997) ‘The degree of innovativeness and marketing approaches used by high-technology firms’, International Journal of Technology Management, Vol. 14, Nos. 2/3/4, pp.238–248. Garza, R. (1994) ‘El diseño industrial en México y los desafíos de la competencia externa’, Comercio Exterior, November. Dierickx, I. and Cool, K. (1989) ‘Asset stock accumulation and sustainability of competitive advantage’, Management Science, Vol. 15, pp.1504–1511. Telser, L. (1961) ‘How much does it pay whom to advertise?’ American Economic Review, Papers and Proceedings, Vol. 51, pp.194–205. Khanna, J., Huffman, W.E. and Sandler, T. (1994) ‘Agricultural research expenditures in the United States: a public goods perspective’, Review of Economics and Statistics, Vol. 76, pp.267–277. According to [14], the sales of the world’s 100 largest F&B multinationals account for one third of the world’s production of processed foodstuffs. Rastoin, J-L., Ghersi, G., Pérez, R. and Tozanli, S. (1998) Structures, Performances et Stratégies des Groupes Agro-Alimentaires Multinationaux, AGRODATA, Montpellier, France. Patel, P. and Pavitt, K. (1991) ‘Large firms in the production of the world’s technology: an important case of ‘non-globalisation’’, Journal of International Business Studies, Vol. 22, pp.1–21. Alfranca, O., Rama, R. and von Tunzelmann, N. (2001) ‘Cumulative innovation in food and beverage multinationals’, Global Business & Economics Review, Anthology, pp.446–459. OECD (1979) Impact of Multinational Enterprises on National Scientific and Technical Capacities, OECD, Paris. Wilkinson, J. (1998) ‘The R&D priorities of leading food firms and long-term innovation in the agrofood system’, International Journal of Technology Management, Vol. 16, pp.711–720. Porter, M. (1990) The Competitive Advantage of Nations, Macmillan, London. Tirole, J. (1988) The Theory of Industrial Organisation, MIT Press, Cambridge MA. Reinganum, J.F. (1989) ‘The timing of innovation: research, development, and diffusion’, in R. Schmalensee and R. Willig (Eds.) Handbook of Industrial Organisation, Vol. 1, North Holland, Amsterdam, pp.849–908. Cohen, W. (1995) ‘Empirical studies of innovative activity’, in P. Stoneman (Ed.) Handbook of the Economics of Innovation and Technological Change, Blackwell, Oxford. Peretto, P. (1999) ‘Firm size, rivalry and the extent of the market in endogenous technological change’, European Economic Review, Vol. 43, pp.1747–1773. Verboven F. (1999) ‘Product line rivalry and market segmentation – with an application to automobile optional engine pricing’, Journal of Industrial Economics, Vol. 47, pp.399. Traill, B. (1997) ‘Globalisation in the food industries?’ European Review of Agricultural Economics, Vol. 24, pp.390–410. From 1967 to 1985, for instance, value-added in US food manufacturing grew almost 40%, roughly one and a half times the rate of all US manufacturing industries (see [27]). Capps, O., Fuller, S.W. and Nichols, J.P. (1988) ‘Assessing opportunities in food and fiber processing and distribution’, American Journal of Agricultural Economics, Vol. 70, No.2. Rama, R. (1992) Investing in Food, OECD Development Centre Studies, Paris. Tozanli, S. (1998) ‘Capital concentration among the food multinational enterprises and development of the world’s agro-food system’, International Journal of Technology Management, Vol. 16, pp.695–710. The simultaneous presence of the top firms in specific geographic markets also occurs in some large developing countries. Brazil, for instance, hosted almost half the FBMs in the world’s top group.

242 31 32 33

34 35 36

37

38

39 40 41

42 43 44 45 46

47

O. Alfranca, R. Rama and N. von Tunzelmann Sutton, J. (1991) Sunk Costs and Market Structure: Price, Competition, Advertisement and the Evolution of Concentration, MIT Press, Cambridge, MA. On the other hand, in specific markets FBMs could also face competition from large one-country companies. Cantwell, J. and Hodson, C. (1991) ‘Global R&D and UK competitiveness’, in M. Casson (Ed.) Global Research Strategy and International Competitiveness, Basil Blackwell, Oxford, pp.133–183. Patel, P. and Vega, M. (1999) ‘Patterns of internationalisation of corporate technology: location vs. home country advantages’, Research Policy, Vol. 28, pp.145–155. Rama, R. (1996) ‘Les multinationales et l’innovation: localisation des activités technologiques de l’agro-alimentaire’, Economie Rurale, Paris, No.231, January/February, pp.62–68. Mansfield, E. (1984) ‘R&D and innovation: some empirical findings’, in Z. Griliches (Ed.) R&D, Patents and Productivity, National Bureau of Economic Research, Chicago and London, pp.127–155. Gonard, T., Green, R.H., Malerbe, A. and Requillart, V. (1991) ‘Changement technique et estratégie des acteurs dans le secteur de la chimie du sucre’, INRA, Economie et Sociologie Rurales, Vol. 7, Special Issue on ‘Changement technique et restructuration de l´industrie agro-alimentarie en Europe’, pp.143–158. Levin [39] reports that, in contrast with other US firms, F&B companies do not find spillovers from other firms particularly effective mechanisms of learning. Feldman and Audretsch [40] nevertheless detect evidence of geographically bounded R&D spillovers in a sample of 21 food and food-related US industries. Using CIS (Community Innovation Survey) data, Christensen et al. [41] find that imitative innovation was the strategy most commonly followed by F&B companies from Germany, Italy, the Netherlands and Norway at the beginning of the 1990s. The level and specialisation of innovation in the home country can affect the industrial pattern of trade and international production [42] or the international performance [43] of FBMs in early stages of internationalisation. This suggests some influence from national spillovers. Levin, R.C. (1988) ‘Appropriability, R&D spending and technological performance’, American Economic Review, Papers and Proceedings, Vol. 78, p.426, Feldman, M.P. and Audretsch, D.B. (1996) Location, Location, Location: the Geography of Innovation and Knowledge Spillovers, Wissenschaftszentrum, Berlin. Christensen, J.L., Rama, R. and von Tunzelmann, N. (1996) Study on Innovation in the European Food Products and Beverages Industry, The European Commission, EIMS/SPRINT, Brussels. Cantwell, J. (1989) Technological Innovation and Multinational Corporations, Basil Blackwell, Oxford. Rama, R. (1999) ‘Innovation and profitability of global food firms: testing for differences in the influence of the home base’, Environment and Planning A, Vol. 31, pp.735–751. OECD (1988) Industrial Revival Through Technology, OECD, Paris. Hermann R. (1997) ‘The distribution of product innovations in the food industry: economic determinants and empirical tests for Germany’, Agribusiness, Vol. 13, pp.319–334. Another reason for following a leader could be the difficulty in following market indications themselves. According to a study based on 225 US food manufacturing firms, in practice, managers find it difficult to interpret consumer’s requirements quickly and well, given the continuous evolution of markets [47]. Thus, once a group of firms has successfully interpreted such requirements, it may be easier for followers to imitate the leaders’ strategy, which does not necessarily mean imitating the product, process or design itself. Starbird and Agrawal (1996) ‘Competitive food manufacturing: evidence from the 1994 competitive manufacturing survey’, Agribusiness: an International Journal, Vol. 12, No.6, pp.525–539.

Competitive behaviour, design and technical innovation 48 49

50 51

52 53 54 55

56 57 58 59 60 61

62 63

64 65 66 67 68 69

243

Wu, Q. and Bjornson, B. (1996) ‘Value of advertising by food manufacturers as investment in intangible capital’, Agribusiness, Vol. 12, pp.147–156. However, this is not always true in this sample. Some firms classified, for instance, in the processed food sector may have some minor businesses in the agribusinesses and basic food. Thus, FBMs classified in one agri-food sector could eventually compete with FBMs classified in another. Paldberg, D.I. and Westgren, R.E. (1979) ‘Product competition and consumer behaviour in the food industries’, American Journal of Agricultural Economics, Vol. 61, November. Galizzi, G. and Venturini, L. (1996) ‘Product innovation in the food industry: nature, characteristics and determinants’, in G. Galizzi and L. Venturini (Eds) Economics of Innovation: the Case of Food Industry, Physica-Verlag, Heidelberg. For instance, obtaining ‘nature-identical’ additives or keeping the organoleptic properties of ‘light’ products, once sugar or fat are removed, see [41]. Rama, R. (1996) ‘An empirical study on sources of innovation in the international food and beverage industry’, Agribusiness: an International Journal, Vol. 12, pp.123–134. However, as mentioned above, in a number of cases information is transmitted among the same world’s excellence centres where subsidiaries co-exist. Brown, M.G. and Lee, J-Y. (1999) ‘Health and nutrition advertising impacts on the demands of orange juice in fifty metropolitan regions’, Journal of Food Products Marketing, Vol. 5, pp.31–47. Sproles, G.B. (1981) ‘Analyzing fashion life cycles – principles and perspectives’, Journal of Marketing, Vol. 45, pp.116–124. Pesendorfer, W. (1995) ‘Design innovation and fashion cycles’, American Economic Review, Vol. 85, pp.771–792. Alfranca, O., Rama, R. and von Tunzelmann, N. (2002) ‘A patent analysis of global food and beverage firms: the persistence of innovation’, Agribusiness, Vol. 18, No. 3, pp 349–368. Beggs, J.J. (1984) ‘Long-run trends in patenting’, in Z. Griliches (Ed.) R&D, Patents, and Productivity, National Bureau of Economic Research, Chicago and London, pp.155–174. For a review, see Shoormans and Robben [61]. Shoormans, J.P.L. and Robben, H.S.J. (1997) ‘The effect of new package design on product attention, categorisation and evaluation’, Journal of Economic Psychology, Vol. 18, pp.271–287. Ward, R.W. (1997) ‘Advertising and promotions’, in D.I. Padberg, C. Ritson and L.M. Albisu (Eds.) Agrofood Marketing, CIHEAM-Cab International, Oxon, UK and NY. Van Trijp, J.C.M. and Steenkamp, J.E.B.M. (1998) ‘Consumer-oriented new product development: principles and practice’, in W.M.E. Jongen and M.I.G. Meulenberg (Eds) Innovation of Food Production Systems: Product Quality and Consumer Acceptance, Wageningen Pes, The Netherlands. Roy, R. and Riedel, J.C.K.H. (1996) ‘The role of design and innovation in product competition’, Report WP-18, The Open University, UK. Connor, J.M. (1981) ‘Food product proliferation: a market structure analysis’, American Journal of Agricultural Economics, November. Walsh, V. (1996) ‘Design, innovation and the boundaries of the firms’, Research Policy, Vol. 25, pp.509–529. In this article we focus on innovations produced by F&B companies. This industry also uses innovations produced by manufacturers in other sectors (see [53]). Rosenberg, N. (1982) Inside the Black Box: Technology and Economics, Cambridge University Press, Cambridge. Archibugi, D. and Pianta, M. (1992) ‘Specialisation and size of technological activities in industrial countries: the analysis of patent data’, Research Policy, Vol. 21, pp.79–93.

244 70 71 72

73

74 75 76 77

78 79 80 81 82

83

84

85

O. Alfranca, R. Rama and N. von Tunzelmann Freeman, C. (1994) ‘The economics of technical change’, Cambridge Journal of Economics, Vol. 18, pp.463–514. Acs, Z.J. and Audretsch, D.B. (1989) ‘Patents as a measure of innovative activity’, WZB, Berlin, pp.1–13. Bound, J., Cummins, C., Griliches, Z., Hall, B.H. and Jaffe, A. (1984) ‘Who does R&D and who patents?’, in Z. Griliches (Ed.) R&D, Patents, and Productivity, NBER, University of Chicago Press, pp.21–54. The data are taken from the numbers of patents granted at the US Patent and Trademark Office (USPTO). The data from 1975 onwards (only) are nowadays available online from USPTO (http://www.uspto.gov). However, working the data from online sources or CD-ROM into usable results still involves intensive research efforts. Basically the USPTO assignees are given according to the name of the organisation to which they are directly affiliated, rather than the name of the corporation. A large patenting firm such as Unilever or Philip Morris may have hundreds of these patenting subunits in addition to the core corporation, and the task of consolidating them into corporate totals is a major one. USPTO (No date). Available from: www.uspto.gov/web/office (for other conceptions of design, see [64,66]). Padilla, M., Laval, G.G., Allaya, M-C. and Allaya, M. (1983) Les Cent Premiers Groupes Agro-Industriels Mondiaux, Montpellier, France. IAMM (1990) Les 100 Premiers Groupes Agro-Alimentaires Mondiaux, Vol. 1, Montpellier France. Its sources are Moody’s Industrial Manual, the Fortune Directory of the 500 largest US and the 500 largest non-US corporations, the ‘Dossier 5.000’ of the largest European companies published by Le Nouvel Economiste, Dun & Bradstreet, and the annual reports of the enterprises, among others. To be included in the database, the firms must meet several criteria [14]: their annual agrifood sales must be at least US$1 billion their sales of processed food and beverages must be more than 50% of their total sales they must have at least one foreign affiliate. By the mid-1990s, 151 firms met these criteria. The 100 largest, according to their sales value, were included in AGRODATA. ‘Entry’ here means entry into the top group, i.e. the world’s 100 largest F&B multinationals. Thus, the new entrant may have already existed. Of the firms in our sample, 55% were already in the top group in 1981. By the end of the 1980s almost all were in the top group. ‘New’ entrants were mostly Continental European and Japanese firms. Thus, the firms in our sample were not continuously in the top group from 1977 to 1994. However, our database includes information for all firms over this period since the companies existed before joining the top group. There are two main reasons for this. The first is that the US classification mixes product and process patents at the three-digit level, as the titles of the classes indeed indicate (for an example, see class 426 [80]). The second is the inherent technical difficulty of deciding whether a particular patent refers to a product or a process innovation, e.g. for many F&B patents in the area of ingredients or chemicals – within one and the same company it may well happen that a product innovation is developed at one site to be used as a process innovation on another site (and so on). ‘Food’ patents cover the three-digit classes of the USPTO as follows: 426 (‘Food or edible material: processes, compositions and products’), 127 (‘Sugar, starch and carbohydrates’) and 99 (‘Food and beverages: apparatus’). Tobacco patents are from class 131. A full concordance with the 400-odd USPTO classification is too long to publish here but is available from Prof. von Tunzelmann on request. Other (dis)aggregations can readily be tried out, although we strongly believe that they will make little difference to our present results.

Competitive behaviour, design and technical innovation 86

245

Fagerberg, J. (1987) ‘A technology gap approach to why growth rates differ’, Research Policy, Vol. 16, pp.87–99. 87 Soete, L. (1987) ‘The impact of technological innovation on international trade patterns: the evidence reconsidered’, Research Policy, Vol. 16, pp.101–130. 88 In the first four attempts we found one cluster that grouped almost all the companies of the sample and two, three or four clusters, respectively, containing only one firm. 89 Owing to the problem of thin cells we also performed a Monte Carlo test in which we found similar results.

246


Appendix: Firms included in the sample Company

Country

Industry

Global sales, 1994*

AJINOMOTO CO. INC

Japan

2

69383

ALLIED LYONS

UK

3

76978

AMERICAN BRANDS. INC

US

2

93917

ANHEUSER BUSCH CO. INC

US

3

120540

ARCHER DANIELS MIDLAND COMPANY

US

2

113740

ARLA

Sweden

2

78653

ASSOCIATED BRITISH FOODS PLC

UK

2

68065

B.P. NUTRITION LTD.

UK

1

78653

BARILLA SPA

Italy

2

20416

BARLOW RAND LTD.

South Africa

2

78653

BASS PLC

UK

1

59751

BEATRICE CO. INC

US

2

73077

BESNIER S.A.

France

2

43200

BOOKER PLC

UK

1

57318

BORDEN INC

US

2

56260

BSN GROUPE

France

2

138276

BUNGE & BORN CO

Argentina

1

78653

C.P.C INTERNATIONAL

US

1

9844

CADBURY SCHWEPPES PLC

UK

2

62062

CAMPBELL SOUP CO

US

2

66900

CANADA PACKERS INC

Canada

1

23250

CARGILL INC

US

1

47135

CARLSBERG A/S

Denmark

3

19764

CASTLE & COOKE INC

US

2

38420

CIE FINANCIÈRE SUCRES ET DENRÉES

France

1

78653

COBERCO

Holland

2

20748

COCA COLA COMPANY

US

3

139570

CONAGRA INC

US

1

235120

DALGETY PLC

UK

2

74325

DEAN FOODS CO

US

2

85170

ELDERS IXL LTD.

Australia

1

106427

EZAKI CUCO CO. LTD.

Japan

2

28628

FERRERO SPA.

Italy

2

22369

GENERAL MILLS INC.

US

1

78653

GEO HORMEL & CO.

US

1

30650

GEORGE WESTON LTD.

Canada

2

94914


247

Appendix: Firms included in the sample (continued) Company

Country

Industry

Global sales, 1994*

GOODMAN FIELDER WATTIE

Australia

2

26005

GRAND METROPOLITAN PLC

UK

3

106582

GRUPO FERRUZZI

Italy

1

78653

GUINNESS PLC

UK

3

53284

GUYOMARC’H S.A.

France

1

9205

H.J. HEINZ COMPNAY

US

2

70470

HANSON PLC

UK

2

105975

HEINEKEN N.V.

Holland

3

48244

HERSHEY FOODS CORP.

US

2

36060

HILLSDOWN HOLDINGS PLC

UK

1

65634

HOUSE FOOD INDUSTRIAL CO LTD

Japan

2

78653

IMASCO LTD

Canada

2

43747

INTERNATIONAL MULTIFOODS

US

2

22950

ITO HAM FOODS INC.

Japan

1

46475

JACOBS SUCHARD S.A.

Switzerland

2

35128

JOHN LABATT

Canada

3

36960

KELLOGG CO.

US

1

65620

KIKKOMAN CORP

Japan

2

91164

KONINKLIJKE WESSANEN N.V

Holland

2

29607

KYOKUYO CO LTD

Japan

1

78653

LAND O’LAKES INC

US

2

28590

LVMH MOET HENNESSY/LOUIS VUITTON

France

3

50340

MARS INC

US

2

78654

MC CORMICK & CO. LTD.

US

2

9090

MD FOODS AMBA

Denmark

2

19491

MEIJI SEIKA KAISHA

Japan

2

35251

MELKUNIE HOLLAND

Holland

2

78653

MOLSON COMPANIES LTD

Canada

3

14922

MORINAGA MILK INDUSTRY

Japan

2

40550

NESTLE

Switzerland

2

421015

NICHIREI CORP.

Japan

2

57550

NICHIRO GYOGYO KAISHA

Japan

1

24161

NIPPON MEAT PACKERS INC

Japan

1

77722

NIPPON SUISAN KAISHA LTD

Japan

1

48353

NISSHIN FLOUR MILLING CO. LTD.

Japan

1

35510

NISSIN FOOD PRODUCTS CO. LTD

Japan

2

27307

248


Appendix: Firms included in the sample (continued) Company

Country

Industry

Global sales, 1994*

PEPSICO INC

US

3

284720

PERNOD RICARD

France

3

28497

PHILIP MORRIS COMPANIES INC

US

2

537760

PILLSBURY CO.

US

2

57040

PROCTER AND GAMBLE COMPANY

US

2

302960

PROVENDOR GROUP

Sweden

2

78653

QP CORPORATION

Japan

2

29714

QUAKER OATS COMPANY

US

1

59550

RALSTON PURINA CO

US

2

77050

RANKS HOVIS MC DOUGALL PLC

UK

1

48675

RJR NABISCO INC

US

2

153660

S&W BERISFORD LTD

UK

2

768866

SANDOZ A.G.

Switzerland

2

117438

SAPPORO BREWERIES LTD

Japan

3

65664

SARA LEE CORPORATION

US

2

155360

SCOTTISH & NEWCASTLE BREWERIES PLC.

UK

3

21915

SEAGRAM CO. LTD

Canada

3

55630

SNOW BRAND MILK PRODUCTS CO.

Japan

2

119308

SOURCE-PERRIER

France

3

17542

SUNTORY LTD.

Japan

3

72515

TATE & LYLE PLC

UK

1

64159

TOYO SUISAN KAISHA LTD

Japan

2

25085

UNIGATE PLC

UK

2

29109

UNILEVER

Holland

2

462504

UNION INTERNATIONAL PLC

UK

1

19167

UNION LAITIÈRE NORMANDE

France

2

15799

UNITED BISCUITS

UK

2

52822

UNITED BRANDS CO.

US

1

39620

WHITBREAD & CO. PLC

UK

2

38316

WHITMAN (I.C. INDUSTRY)

US

2

39466

YAMAZAKI BAKING CO.

Japan

2

61648

Notes:

*Million 1990 PPP $ Country: Home-country of the company

Industry codes:

1: agribusiness and basic food 2: highly processed food 3: beverages

Source: AGRODATA

Competitive behaviour, design and technical innovation in ... - CiteSeerX

Competitive behaviour, design and technical innovation in ... - CiteSeerX

Suggest Documents

Competitive Behaviour and Business Innovation in the Forest Industry ...

Business Model Innovation and Competitive Imitation - CiteSeerX

Recent progress in Competitive Intelligence, Competitive Technical

Competitive Design Competitive Design

Innovation and Competitive Power - ScienceDirect.com

lexical behaviour in academic and technical corpora - CiteSeerX

innovation behaviour of spanish fashion manufacturing ... - CiteSeerX

Human information behaviour and design, development ... - CiteSeerX

innovation capability and competitive advantage: a case ... - CiteSeerX

Beyond competitive intelligence â innovation and competitive strategy

balancing antipredator behaviour and competitive ... - Chittka Lab

Combining Laboratory Innovation and a Design ... - CiteSeerX

Temperature modulates competitive behaviour: why

Combining Laboratory Innovation and a Design ... - CiteSeerX

Technical Innovation Concepts in Slovenian

Innovation and learning for sustainable competitive advantage ...

Competitive European regions through research and innovation

10 innovation strategies and competitive advantages

Corporate Innovation and Competitive Environment - Springer Link

Competitive strategies of knowledge and innovation ... - Revistas

Ownership Structure, Innovation Process and Competitive Performance

Corporate Innovation and Competitive Environment | SpringerLink

Market Orientation, Innovation and Competitive ... - United Nations ...

Competitive European regions through research and innovation

Competitive behaviour, design and technical innovation in ... - CiteSeerX